CENTRAL BANK AND REAL ESTATE / HOUSING MARKET IN TANZANIA
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CENTRAL BANK AND REAL ESTATE / HOUSING MARKET IN
TANZANIA
CENTRAL BANK AND REAL ESTATE / HOUSING MARKET IN
TANZANIA
CASE AT BANK OF TANZANIA [BoT] – HEAD OFFICE, DAR-ES-SALAAM
By
Herbert Maximillian Lyimo
Dissertation Submitted in Partial/Fulfillment of the Requirements for Award of the
Degree of Master of Business Administration in Corporate Management (MBA
CM) of Mzumbe University
2014
i
CERTIFICATION
We, the undersigned, certify that we have read and hereby recommend for acceptance by
the Mzumbe University, the research report titled “Central Bank and Real Estate
Market in Tanzania” in partial/fulfillment of the requirements for award of the degree
of Masters of Business Administration of Mzumbe University.
_______________
Major Supervisor
______________
Internal Examiner
Accepted for the Board of………………….…
____________________________________________________________
DEAN/DIRECTOR, FACULTY/DIRECTORATE/SCHOOL/BOARD
ii
DECLARATION
AND
COPYRIGHT
I, Herbert Maximillian Lyimo, declare that this proposal is my own original work and
that it has not been presented and will not be presented to any other university for a
similar or any other degree award.
Signature ____________________
Date ______________________
© 2014
This dissertation is a copyright material protected under the Berne Convention, the
Copyright Act 1999 and other international and national enactments, in that behalf, on
intellectual property. It may not be reproduced by any means in full or in parts, except
for short extracts in fair dealings, for research or private study, critical scholarly review
or discourse with an acknowledgement, without the written permission of Mzumbe
University, on behalf of the author.
iii
ACKNOWLEDGEMENT
I am grateful to my Lord and Saviour Jesus Christ for the honour of accomplishment of
this study marking the second degree of Business Administration in Corporate
Management, after the first degree of Business Administration which I earned in 2010.
God had much to do in accomplishment of my education than all my strengths put
together. I thank my mother for her support in my study and education; both morally and
financially. I acknowledge the support of friends specifically, Zola H. Komba and
Godfrey Malauri in walking me throughout my study and encouraging me.
I would love to acknowledge the contribution of my supervisor Godbertha Kinyondo
(PhD) for her guidance throughout this work; she is the best I‘ve ever known, so thank
you ‗madam‘. She is an inspiration to me in the economic field and I promised her to
keep up the spirit in my advanced future studies.
My research would not have been accomplished without key figures personnel in Bank
of Tanzania; Mr. Makene, Ms. Prisca, Mr. Milulu, Mr. Misangu and John Mello to
mention the few. It was not easy to penetrate my way into a highly structured and
sensitive organization like Bank of Tanzania, but these few individuals blessed my way
wherever I needed support and guidance.
I would love to appreciate the prayers and spiritual support from my church, Upper
Room Ministry (URM) Tanzania, in nurturing my soul to withheld turbulence in this
study. Specifically I extend my gratitude to Pastor Freddy Okolle and Pastor Casmir
Mabina for their endless encouragement.
It is also kind to appreciate the contribution my office played whenever I needed time-
off to accomplish this study. I appreciate the management of National Health Insurance
Fund (NHIF) in playing a role of making my dream come true.
iv
DEDICATION
I dedicate this work to my loving father, who is now resting in peace, Herbert
Maximillian (Sr) Lyimo. He was and will always be my inspiration to my work and
education. He would be happy to know how far I have reached in contributing this study
to my government.
v
ABBREVIATIONS AND ACRONYMS
BOT - Bank of Tanzania
BRICS - Brazil Russia India China South-Africa
CBD - Central Business District
CRB - Contractors Registration Board
CRDB Bank - Cooperative Rural Development Bank
DSE - Dar-es-salaam Stock Exchange
EU - European Union
EWURA - Energy and Water Utilities Regulatory Authority
GDP - Gross Domestic Product
HPI - House Price Indices
IIF - Institute of International Finance
IPD - Investment Property Databank
KDA - Kigamboni Development Agency
KIA - Kilimanjaro International Airport
NBC Bank - National Bank of Commerce
NHC - National Housing Corporation
NSSF - National Social Security Fund
PPF - Pension Parastatal Fund
SAPOA - South African Property Owners Association
TANESCO - Tanzania Electric Supply Company
TBA - Tanzania Building Agency
TCB - Tanzania Coffee Board
TCF - Trillion Cubic Feet
THB - Tanzania Housing Bank
TMFL - Tanzania Mortgage Finance Limited Company
TZS - Tanzania Shillings
UNESCO - United Nations Educational, Scientific and Cultural Organization
USD - United State Dollar
vi
ABSTRACT
This study evaluates how the Central Bank of Tanzania influences the real
estate/housing market through its policies. The research design employed was case
study. The source of data collection was at Bank of Tanzania (BoT) Head Office, Dar es
salaam. The study used non-probability sampling – ‗judgemental/purposive‘ sampling.
The primary data was gathered through interviews and questionnaires; whereas the
secondary data was gathered from organization brochures, website and empirical/textual
literature. The data collection started on 1st April 2014 and ended in 30
th April 2014.
Only ten (10) out of the intended fifteen (15) respondents could be reached. The data
was categorized and coded to be fed into SPSS (version 16.0) for analysis and
manipulation. The data analysis techniques included frequency analysis, factor analysis,
cross tabulation analysis, correlation analysis and cronbach‘s alpha analysis.
The researcher found that when there is low interest rate, the prices of commodities,
housing and rents also tend to rise up. It was also found that Central Bank exerts certain
penalties to institutions which don‘t adhere to regulations thereby controlling indirectly
housing costs. There is a general appreciation that Bank of Tanzania should be
controlling total volume of credit in the economy and thus principally be controlling real
estate prices and housing rents. It has been rather tricky in analysing the supervisory
discretion in targeting the activities of individual institutions since there are measures of
prudence to be considered; thereby an average consensus. However, there was a widely
accepted fact that Bank of Tanzania doesn‘t control capital flow with prudent purposes.
Thereby existences of weak supervision discretion in combination of slack prudence in
capital flow if not carefully reviewed may sets ground for bubble inflation.
Based on such findings, there is enrichment of monetary policy examination in East
Africa states that have similar economic infrastructures. The most agreed way of asset
bubble prevention is for the government to bail out the businesses; but what is more
important is for the serious and strict policies to take root in guiding businesses and
social lives of citizens.
vii
TABLE OF CONTENTS
CERTIFICATION ............................................................................................................ i
DECLARATION AND COPYRIGHT ......................................................................... ii
Acknowledgement .......................................................................................................... iii
Dedication ........................................................................................................................ iv
ABBREVIATIONS AND ACRONYMS ........................................................................ v
ABSTRACT ..................................................................................................................... vi
TABLE OF CONTENTS .............................................................................................. vii
TABLE OF LIST .......................................................................................................... xii
LIST OF FIGURES ...................................................................................................... xiv
CHAPTER ONE .............................................................................................................. 1
INSIGHT INTO TANZANIA MONETARY POLICY AND ITS LINKAGE TO
REAL ESTATE/HOUSING MARKET ......................................................................... 1 1.1 Background History of the Problem................................................................ 1 1.2 Statement of a Problem ................................................................................... 2 1.3 Objective of the Study ..................................................................................... 3 1.3.1 General Objectives .......................................................................................... 3 1.3.2 Specific Objectives .......................................................................................... 3 1.4 Research Question(s)....................................................................................... 3 1.5 Significance of the Study ................................................................................ 4 1.6 Rationale for Study.......................................................................................... 4 1.7 Scope of the Study........................................................................................... 5 1.8 Limitations of the study................................................................................... 5 1.9 Dissemination of Research Report .................................................................. 5
CHAPTER TWO ............................................................................................................. 6 LITERATURE REVIEW ................................................................................................ 6
2.1 Textual literature and Theoretical Framework ................................................ 6
2.1.1 Definition of Asset Bubble .............................................................................. 6
2.1.2 Current Economic Outlook of Tanzania ......................................................... 6
2.1.3 Inefficacy of Monetary Policies ...................................................................... 7
2.1.4 Household Debt and Monetary Policy ............................................................ 8
2.2 Empirical Literature and Conceptual Framework ......................................... 12
2.2.1 A Central Bank .............................................................................................. 16
2.2.2 Bank Regulation ............................................................................................ 18
2.2.3 Monetary Policy ............................................................................................ 19
2.2.4 Fiscal Policy .................................................................................................. 22
2.2.5 Economic Bubbles......................................................................................... 24
2.2.5.1.2 Housing debt Measures ................................................................................. 28
2.2.5.2 Indicators of bubble (evidence) in Tanzania ................................................. 32
viii
2.2.5.2.1Tanzania Inflation Rate .................................................................................. 35 2.2.5.2.2 Tanzania Shilling........................................................................................... 36
2.2.5.2.3 Tanzania GDP Annual Growth Rate ............................................................. 37
2.2.5.2.4 Tanzania Interest Rate ................................................................................... 37
2.2.5.3 Basic Coverage of a Bubble .......................................................................... 40
2.2.5.3.1 Stock Market Bubble ..................................................................................... 40
2.2.5.3.2 Real Estate Bubble ........................................................................................ 40
2.2.6 Construction Industry and Real Estate in Africa and Tanzania .................... 40
2.2.7 Relationship between monetary policy, economic bubble and real
Estate/Housing Market .................................................................................. 48
2.2.8 Monetary and Fiscal Policies of Tanzania in Assessment of Housing
Market/Real Estate ........................................................................................ 53
2.2.9 Extent of Monetary Policy in Precipitating Asset Bubble in Real
Estate/Housing Prices and what can Tanzania learn. .................................... 56
2.2.10 Economic Bubble Prevention ........................................................................ 61
2.3 Knowledge Gap ............................................................................................. 65
2.4 Conceptual Framework ................................................................................. 66
2.5 Hypotheses .................................................................................................... 67
CHAPTER THREE ....................................................................................................... 68
STATISTICS, COMPUTATION AND DESIGN OF A RESEARCH PROBLEM 69 3.1 Introduction: Research Methodology ............................................................ 69
3.2 Conceptual Definition ................................................................................... 69
3.2.1 Asset Bubble ................................................................................................. 69
3.2.2 Austrian Economic(s):................................................................................... 69
3.2.3 Bail (bail out): ............................................................................................... 69
3.2.4 Bond (Government Bond) ............................................................................. 70
3.2.5 Boom (Economic): ........................................................................................ 70
3.2.6 Borrowing...................................................................................................... 70
3.2.7 Budget ........................................................................................................... 70
3.2.8 Construction Industry .................................................................................... 70
3.2.9 Contractors .................................................................................................... 70
3.2.10 Credit Market ................................................................................................ 71
3.2.11 Crush (bubble, Economy) ............................................................................. 71
3.2.12 Currency Board ............................................................................................. 71
3.2.13 Debt ............................................................................................................... 71
3.2.14 Deregulation ................................................................................................. 71
3.2.15 Dollarization .................................................................................................. 71
3.2.16 Economic Bubble .......................................................................................... 71
3.2.17 Economic Crisis ............................................................................................ 72
3.2.18 Expenditure ................................................................................................... 72
3.2.19 Financial Crisis .............................................................................................. 72
3.2.20 Financial Institution(s) .................................................................................. 72
3.2.21 Financial Market .......................................................................................... 72
ix
3.2.22 Financial Year ............................................................................................... 72 3.2.23 Fiscal Policy .................................................................................................. 73
3.2.24 Government ................................................................................................... 73
3.2.25 Greater Fool (Theory) ................................................................................... 73
3.2.26 Heterodox Economic(s)................................................................................. 73
3.2.27 Housing Bubble ............................................................................................. 73
3.2.28 Housing Market ............................................................................................. 73
3.2.30 Inflation ......................................................................................................... 74
3.2.31 Infrastructure ................................................................................................. 74
3.2.32 Intrinsic Value (Finance) ............................................................................... 74
3.2.33 Investment (finance) ...................................................................................... 74
3.2.34 Jackson Hole Consensus ............................................................................... 75
3.2.35 Keynesian Economic(s)................................................................................. 75
3.2.36 Lending.......................................................................................................... 75
3.2.37 Liquidity Trap ............................................................................................... 75
3.2.38 Liquidity ........................................................................................................ 76
3.2.39 Macroeconomic ............................................................................................. 76
3.2.40 Macroprudential Regulation .......................................................................... 76
3.2.41 Mainstream economic(s) .............................................................................. 76
3.2.42 Monetary Policy ............................................................................................ 76
3.2.43 Mortgage Market ........................................................................................... 76
3.2.44 Mortgage (loan) ............................................................................................. 77
3.2.45 Open market operations (OMO) ................................................................... 77
3.2.46 Peak (Business, Economic) ........................................................................... 77
3.2.47 Pricking (punching) the bubble ..................................................................... 77
3.2.48 Purchase ........................................................................................................ 77
3.2.49 Real estate ..................................................................................................... 78
3.2.50 Recession (business, economic) .................................................................... 78
3.2.51 Rent .............................................................................................................. 78
3.2.52 Repo Market .................................................................................................. 78
3.2.53 Security (Banking, Economics)..................................................................... 78
3.2.54 Sell ................................................................................................................. 79
3.2.55 Speculation ................................................................................................... 79
3.2.56 Spending ........................................................................................................ 79
3.2.57 Stock Market Margin .................................................................................... 79
3.2.59 Taxation ......................................................................................................... 80
3.2.60 Taylor Rule .................................................................................................... 80
3.2.61 Time Varying Bank Capital Ratio ................................................................. 80
3.2.62 Too Big to Fail (Theory) ............................................................................... 81
3.3 Research Procedure ....................................................................................... 81
3.3.1 Research Design ............................................................................................ 81
3.3.2 Research Strategy .......................................................................................... 82
3.3.3 Area of the Research ..................................................................................... 83
3.3.4 Location of case study - Bank of Tanzania ................................................... 83
x
3.3.5 Unit of study .................................................................................................. 85
3.3.6 Types of Study .............................................................................................. 85
3.3.7 Types of Data ................................................................................................ 86
3.3.8 Unit of Analysis ............................................................................................ 86
3.3.9 Study Population ........................................................................................... 86
3.3.10 Sampling methods ......................................................................................... 87
3.3.10.2 Sample Frame/Size ........................................................................................ 88
3.3.10.3 Sample Size Determination ........................................................................... 89
3.3.11 Methods of Data Collection .......................................................................... 89
3.3.12 Tools of Data Collection ............................................................................... 90
3.3.13 Data Organization ......................................................................................... 90
3.3.13.1 Response Rate ............................................................................................... 90
3.3.13.2 Data organization .......................................................................................... 90
3.3.13.2 Data editing ................................................................................................... 90
3.3.13.3 Data processing and analysis........................................................................ 91
3.3.13.4 Data presentation ........................................................................................... 91
3.3.14 Variables and their measurements................................................................. 91
3.3.15 Reliability and validity issues ....................................................................... 92
3.3.16 Ethical Issues ................................................................................................. 93
CHAPTER FOUR .......................................................................................................... 93
PRESENTATION OF FINDINGS ............................................................................... 94
4.1 Introduction ................................................................................................... 94
4.2 Sample Characteristics ................................................................................. 94
4.3 Respondents .................................................................................................. 94
4.2.1 Age ................................................................................................................ 95
4.2.2 Gender ........................................................................................................... 95
4.2.3 Level of Education ........................................................................................ 96
4.2.4 Use of agents when buying and renting a house ........................................... 96
4.4 Frequency Analysis: Association of Monetary Regime and House/Real
Estate Inflating Prices.................................................................................... 98
4.5 Cross Tabulation: Association of Monetary Regime and House/Real Estate
Inflating Prices ............................................................................................ 103
4.6 Correlation Analysis – Bivariate Analysis; Measuring The Variables
[Independent And Dependent] .................................................................... 106
4.7 Cronbach‘s Alpha Analysis - Testing Consistency/Validity of Data .......... 108
4.8 Analyzing The Hypothesis of The Study .................................................... 108
4.8.1 When BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices. ................................................................ 109
4.8.2 The low interest rate charged to commercial banks and other depository
institutions on loans they receive from BoT encourage high money supply
resulting into inflationary tendencies giving negative effect in housing
market prices. .............................................................................................. 110
xi
4.8.3 Due to high cut throat competition in the banking and financial sector in
general, persuading a certain regulation without rigid laws and punishment
has proven ineffective in Tanzania. ............................................................. 110
4.8.4 It is logical when total volume of credit is controlled in the economy by the
Central Bank of Tanzania. ........................................................................... 111
4.8.5 BoT control capital flow with prudential purposes ..................................... 111
4.8.6 The Central Bank and where possible government should intervene
aggressively to the institution(s) which possess a threat in a forerunner in
accumulating and inflating real estate/house prices. ................................... 112
CHAPTER FIVE .......................................................................................................... 113
DISCUSSION OF THE FINDING ............................................................................. 113
5.0 Introduction ................................................................................................. 113
5.1 Discussion of General Findings and Data Analysis .................................... 114
5.2 Discussion of Specific Objectives ............................................................... 117
5.2.1 Traditional monetary policy tools effectiveness in addressing economic
bubble .......................................................................................................... 117
5.2.2 Supervisory discretion in targeting the activities of individual institutions ...... 119
5.2.3 Credit market controls evaluation ............................................................... 120
5.2.4 Establishment of a time varying bank capital ratio ..................................... 121
CHAPTER SIX ............................................................................................................ 123
CONCLUSION, IMPLICATIONS, LIMITATIONS, RECOMMENDATIONS
AND FUTURE RESEARCH ................................................................................ 123
6.0 Introduction ................................................................................................. 123
6.1 Conclusion ................................................................................................... 123
6.2 Implications of the Study ............................................................................ 123
6.3 Limitations of the Study .............................................................................. 124
6.4 Recommendations ....................................................................................... 124
6.5 Future Research Suggestion ........................................................................ 126
REFERENCE ............................................................................................................... 127
APPENDICES .............................................................................................................. 138
Appendix One: Questionnaire .................................................................................... 138
Appendix Two: Macroprudential regulation .............................................................. 151
Appendix 3: Budget for the Research ..................................................................... 153
Appendix 5: Concept Note ..................................................................................... 155
xii
TABLE OF LIST
Pages
2.2.5.1 Housing Market Indicators ..................................................................... 26
2.2.5.1.1 Housing Affordability Measures ............................................................ 27
2.2.5.1.3 Housing Ownership and Rent Measures ................................................ 29
2.2.5.1.4 Housing Price Indices ........................................................................... 32
3.3.10.1 Sampling technique ................................................................................ 87
Table 3.1: Distribution of Respondents ................................................................... 88
Table 4.1: Respondents Characteristics [Office Department/Unit]......................... 94
Table 4.2: Age of Respondents ............................................................................... 95
Table 4.3: Gender of respondents............................................................................ 95
Table 4.5: Use of agents When Buying and Renting A House ............................... 96
Table 4.6 Correlation matrix vs correlation of Monetary regime and House/Real
Estate inflating prices ............................................................................. 97
Table 4.7: Understanding regards to monetary policy of Tanzania conducts and
satisfied over the implementation of its objectives ................................ 98
Table 4.8: BoT is autonomous and independent from the government interventions
................................................................................................................ 99
Table 4.9: BoT should follow the lead of financial markets ................................... 99
Table 4.10 : It is logical for BoT to adopt gradualism attitude (steady and regular
techniques) in the housing market asset bubble circumstance at a
moment ................................................................................................. 100
Table 4.11: There is a tremendous pressure of rising rents in Dar es salaam (and
other regions) ....................................................................................... 101
Table 4.12: People have a hyper attitude to buy lands in Tanzania even though not
necessarily developing them ................................................................ 101
Table 4.13: Investors are overly optimistic in investing in real estate market now in
Dar es salaam and elsewhere................................................................ 102
xiii
Table 4.14 : Improvement of mortgage law in Tanzania is presently (and will in the
future) accelerate real estate industry and housing constructions ........ 102
Table 4.15: DSE stock brokers negatively drives up prices of major construction
industry particularly cement ................................................................. 103
Table 4.16: Crosstab*Count; Pressure of rising rents against monetary policy and
implementation of monetary objectives ............................................... 104
Table 4.17: Measuring the Dependent and Independent Variables......................... 106
Table 4.18 : Cranbach‘s alpha Analysis of the study variables – Reliability statistics
.............................................................................................................. 108
xiv
LIST OF FIGURES
Pages
Figure 2.1: Expansion vs Contraction Monetary Policy ............................................... 14
Figure 2.2: Bank of Tanzania view............................................................................... 17
Figure 2.3: Robert Shiller's plot of U.S. home prices, population, Building Costs, And
Bond Yields, from Irrational Exuberance ................................................ 28
Figure 2.4 : Inflation-adjusted Home Prices in Japan (1980–2005) ............................ 29
Figure 2.5 : The Case–Shiller index (national, quarterly) 1987–2008 ......................... 32
Figure 2.6 : Tanzania inflation Rate............................................................................. 35
Figure 2.7 : Tanzania Shilling ...................................................................................... 36
Figure 2.9: Tanzania Interest Rate .............................................................................. 38
Figure 2.10 : Conceptual Framework ............................................................................ 66
Figure 3.1: Research Process ...................................................................................... 83
Figure 3.2: Overview map of Dar es salaam ............................................................... 84
Figure 3.3 : Detail map of Dar es salaam City Centre (locating BoT) ........................ 85
Figure 4.1: Bar graph; Pressure of rising rents against monetary policy and
implementation of monetary objectives ................................................. 105
1
CHAPTER ONE
INSIGHT INTO TANZANIA MONETARY POLICY AND ITS LINKAGE TO
REAL ESTATE/HOUSING MARKET
1.1 Background History of the Problem
Monetary policy that increases the supply of money (expansionary policy) leads to
reduction in interest rates, stimulate the consumption and investment in the economy.
Increased consumption and investment mean higher aggregate demand as well as
increased personal income and employment. This all translates into ability to rent,
purchase and sell houses/apartment. Tanzania is in the heights of high inflation, meaning
there is plenty of money in circulation which clearly explains the use of Bank of
Tanzania (BOT) contractionary policy at a moment. Inflation is not always a bad thing
especially if it is on a short-run; it may suggest there is injection of some money
‗quantities‘ in the economy due to supposedly discovery of new sources of raw
materials, energy and minerals. This is what has undoubtedly taken place in Tanzania
giving citizens and private sector‘s power to drive real estate/housing market to high
new unimaginable levels. In financial year 2010/11, government allocated 13 per cent of
expenditure budget into infrastructure. Construction industry by 2009 accounted to 7.9
per cent of GDP, growing at a rate of 7.5 per cent and by 2010 it employed about 9 per
cent of Tanzania workforce (UNESCO, August 2010). There were 2,621 projects worth
nearly TZS 2.4 Trillion during 2009. Contractors Registration Board (CRB) of Tanzania
in 2009 registered 930 applicants compared to 656, 662 and 608 in 2008, 2007 and 2006
respectively. Some 33 of the newly registered contractors were foreigners, leading to a
total of 236 foreign contractors in the country which was 4.1 per cent of the total
contractors in the Contractors Registration Board (CRB) register compared to 3.6 per
cent in 2009, UNESCO report added. No hesitation that Tanzania is booming; the fiscal
policy is relaxed which encouraged spending and monetary policy though is tightened, is
not ‗tightened‘ enough and the central message of this research is that there is excessive
availability of credit in the economy.
2
According to National Housing Corporation (NHC), Tanzania runs a housing deficit
estimated at 3 million units valued at $180 billion by the end of 2007, while the current
annual demand for houses in urban areas is 200,000 units estimated to cost $12 billion.
1.2 Statement of a Problem
Though Tanzania housing/real estate market seems young, there are ongoing
developments which will soon in near future put the country at the edge. Tanzania
government has committed itself in Kigamboni City Project with expected cash injection
of about Tzs 11.6 trillion upon completion in 2012 (The East African, 12th
July 2012).
Monetary policy set up coincides with the rate of housing development, that is a relaxed
policy with evidence of 8.2 per cent of inflation (Bank of Tanzania, June 2012). In other
words, for the pace of construction to be encouraged, money supply needs to be
encouraged (in constricting supply of money, by raising interest rates or raising bank
rates is to discourage such developments). This is in alignment of a global annual value
of construction industry at about USD 1.5 trillion (Nguguna, H.B, 2008). Thereby rent
and housing market is expanding in Tanzania; with a current deficit of estimated 3
million units valued at USD 180 billion by the end of 2007, while current annual
demand of houses in urban areas is 200,000 units estimated to cost USD 12 billion
(Business Times, 2013).
Tanzania is therefore booming with housing industry, but there might be signs of unclear
regulation which could threaten the very economy; such as lack of real estate/housing
regulatory authority and the unclear policy set up of monetary policy. The future of the
economy is shrouded with doubts of how devastating might the housing prices and rents
rises to uncontrollable levels.
3
1.3 Objective of the Study
1.3.1 General Objectives
Evaluating how the Central Bank of Tanzania influences the real estate/housing market
through its policies.
1.3.2 Specific Objectives
(i.) To analyse if traditional monetary policy tools can effectively address
housing/real estate market. They include; bank rate, reserve requirements and
discount rate as well as moral suasion.
(ii.) To find out if supervisory discretion could be used to target the activities of
individual institutions that are systematically important firm so as to achieve a
level of controlling prices of housing market.
(iii.) To evaluate if employment of ‗credit market controls‘ aimed at specific market
such as mortgage market and commercial real estate can result into established
and stable housing market prices.
(iv.) To assess if establishing a time varying bank capital ratio-one in which the
capital ratio requirement varies over business cycle can address housing bubble
phenomenon.
1.4 Research Question(s)
How should the Central Bank of Tanzania influence the real estate/housing market
through its policies?
(i.) How can traditional monetary policy tools be effectively administered to address
housing market prices issue?
(ii.) Is supervisory discretion beneficial if it is targeted towards the activities of
individual institutions that are systematically important so as to achieve a level of
controlling prices of housing market?
4
(iii.) Does the employment of ‗credit market controls‘ at specific market such as
mortgage market and commercial real estate market result into established and
stable housing market prices?
(iv.) Can establishing a time varying bank capital ratio-one in which the capital ratio
requirement varies over business cycle address housing asset bubble
phenomenon?
1.5 Significance of the Study
By understanding the link between Central Bank and real estate/housing market,
pertinent measures can be taken to protect the policy set up in this fragile sector which is
given considerable amount of attention at a moment.
In addition, the following are important to this study:
(i.) Findings will bring new insights on how to effectively design the monetary
policies.
(ii.) Findings will add new information to the economic and business field as far as
Tanzania is concerned.
(iii.) The study aims at contributing in a small way towards a deeper understanding of
economic bubbles in the developing countries context.
(iv.) The beneficiaries of this information may include policy makers, ministries,
economists and academicians.
1.6 Rationale for Study
The economy at present times is unstable with inflation prices almost in every
commodity and other sectors. Construction industry being prime to Tanzanians, and thus
by understanding the right policy injection, we can save an important sector‘s
unnecessary rising of prices. Addressing of this current phenomenon will be a turning
point for the nation and most companies‘ achievements.
5
1.7 Scope of the Study
Evaluating how the Central Bank of Tanzania influences the real estate/housing market
through its policies.
1.8 Limitations of the study
The researcher encountered scarcity of literature contents relating to Tanzania and even
relating to East Africa. This study being an ongoing debate among world greatest
scholars, the researcher had to study and update himself with literatures in every
successive period of the research.
1.9 Dissemination of Research Report
This report will be distributed to the learning institutions, Bank of Tanzania, World
Bank and International Monetary Fund, government ministries, libraries and online
contents sites.
6
CHAPTER TWO
LITERATURE REVIEW
2.1 Textual literature and Theoretical Framework
2.1.1 Definition of Asset Bubble
This is an economic development in which the price of class of physical or financial
assets rises to a level that appears to be unsustainable and well above the asset‘s value as
determined by economic fundamentals (Lahart. J, 2008)
2.1.2 Current Economic Outlook of Tanzania
Giugale and Canuto (2010) noted that the global financial crises changed the way we
think about the global economic order leading to doubting the principles and practices
that were once accepted. For the developing world, that conceptual uncertainty is
particularly uncomfortable, and we have witnessed the various policies in Tanzania
bringing confusion and debates. Some people may relate the economic bubble in
Tanzania from the explicit cost side, on the basis of unaffordability of instrument like
treasuries, bonds and share of Tanzania financial market. This is not always the case, as
it could be a purely purchasing power issue with nothing to do with price increase or
inflation. The current times where the bubble is growing (has not burst yet) it is prudent
for the Central Bank of Tanzania to avoid any rush decisions. This is because as the
bubble build-up it takes years until a visual pattern is noticed, making it hard to identify
and predict the magnitude of the bubble. For such observance a precise monetary policy
can hardly be adopted in this period of uncertainty. Furthermore, there is no need to
directly target the bubble; as an asset bubble steadily increases so do the wealth build up,
that stimulates consumption. The more increase of asset bubble like for the case of real
estate/housing market should surely result in a dangerous limit of inflation, thus the
Central Bank of Tanzania should act to curb it. In other words we can agree that bank
rate cannot always be adjusted to housing market/real estate sector (until a certain right
time). It should be highly concerned that in this regard of inactiveness of monetary
7
policy the bubble keeps on inflating and ultimately burst. This burst leads to a decline of
a real economy which now forces the Central Bank to quickly reduce the bank rate to
offset the negative impacts of the bubble burst.
African Economic Outlook (2014) observed that inflation in Tanzania has declined to
single digits and gross domestic product (GDP) growth projected at about 7% in the
medium term where among the main drivers of growth being construction and such
growth is significantly being boosted by natural gas discoveries. But we ought to be
careful that it is not a mere rise or drop of inflation but at what rate and how much
supply of money is there in the economy; this is a gist of a story.
2.1.3 Inefficacy of Monetary Policies
During the 2008 Global Financial and Economic crisis there was shortage of money in
most Western economies thus no enough money to be lent to the businesses. According
to Ngowi (2013) one of the causes of the 2008‘s Economic Crisis is the situation where
banks and other financial institutions extended and made credit accessible and available
even to people and institutions who could not honour the loan covenant – that is
repaying the monies plus accrued interest when maturity was due. This occurred due to
inadequate supervision of banks and financial institutions by monetary authorities by
way of Central Banks in general and the Fed in the US in particular. Remember when
the recent crisis took place the most hit sectors were real estate and stock exchange, and
then ripple effects were felt in other sectors. It is unquestionably the affected people in
the West were concentrated into the housing market (so did the effect), this is another
way of saying most money borrowed from financial institutions large chunk of it was in
mortgage spending loans.
Supervision of banks and monetary matters in a country is the responsibility of central
bank, and for our case is Bank of Tanzania. In United States, regulation of financial
sector was left minimal - left too independent in a hope that the free forces of market
8
would sort out the demand and supply; but in the end it was a shameful devastation. In
2009 the government of Tanzania injected TZS 1.7 Trillion as a rescue package against
the global financial crisis; was this package sustainable and was it efficiently utilized? If
not, then it is another unhealthy ‗quantities‘ of money injected to weaken the TZS
strength (that is inflation).
Global economic crisis brought about careless policies of Federal Reserve in United
States led into the jobs loss, decline of GDP, increase in poverty levels, protest and civil
unrest, collapse of governments, and billions of business losses globally. Perhaps if we
can re-visit how the crisis crippled Tanzanian economy we might be careful to design
our local monetary policies and maybe shelter our little economy. Tanzania experienced
approximate downturn of economic growth from nearly 7 per cent in 2009 to 4.5 per
cent in 2010 (Ngowi, 2013). In 2008, proceeds from cotton dropped by 54.4 per cent,
losing TZS 40 billion due to export failure; by 2008 exports were expected to drop to 44
per cent. Arabica coffee price dropped to 34 per cent and Robusta coffee dropped to 30
per cent by December 2008, leading to an average decline of coffee export by 32 per
cent. Nile perch (fish) normally exported to European Union (EU), accounting to 80 per
cent of export dropped to average of between 50 to 60 per cent (normally Nile perch
brings over USD 200 million revenue). Now as it can be seen, the economic meltdown
due to ineffective monetary policy is not an easy forgiving circumstance as it tears apart
people‘s lives. This can happen to our economy too.
2.1.4 Household Debt and Monetary Policy
In the five years to 2003, US household debt rose by 52 per cent and the ratio to income
reached a record132 per cent. In the UK debt jumped 63 per cent over the same period,
while in Australia it rose even faster, by a whopping 90 per cent (Calverley, 2004). In
relation to household incomes, debts soared to over 150 per cent in both countries. By
way of contrast, Japan and Germany, where house prices are weak saw much smaller
increases in debt and their ratios to incomes have remained stable. Part of the rise in debt
9
was attributed to a greater proportion of the population owning their own homes; and
part is due to individuals taking out mortgages on investment properties. However, the
bulk of the increase in debt can only be explained in relation to higher home prices. New
buyers and people trading up are forced to take on large mortgages to be able to afford
today’s high prices. Meanwhile, many others are taking advantage of higher prices to
increase their existing mortgages, either to pay down debt or to finance major
purchases. In a rising market it is quiet rational for individuals to increase their
borrowing to finance buying a larger house for themselves or an investment property.
It should be noted that the amount of lending in the economy is determined by financial
institutions, based on their assessment of the risk and profitability of the lending
opportunities open to them. Overall lending is not controlled by the government; once it
was, and in some countries in the developing world it still is (Calverley, 2004). In
advanced economies the banking system can lend as much as it wants to, subject only to
having sufficient capital from shareholders and meeting the capital and regulatory
requirements of the authorities. But some people argue that the system encourages too
much lending; in principle if banks are to make profits and avoid bankruptcy they have a
strong incentive not to over lend. Still if banks relax their risk criteria even a little,
lending will increase. Suppose that banks raise the proportion of their mortgage book
provided at a risky 100 per cent loan-to-value ratio from 1 per cent to 2 per cent. If the
risk of loss on such loans is seen as 5 per cent (relatively high for mortgages), this may
still be an acceptable risk/reward for the bank and be prudent enough for the regulators.
But it is extra fuel for the market, allowing some people to buy who otherwise might not
have been able to afford to do so.
Banks also make mistakes; during a bubble the management can be caught up in the
general euphoria. There is a danger as the bank management take more risks than would
be ideal for their shareholders; earning high salaries and large bonuses. This keep on
crippling the free market system, but perhaps it is because the management and
10
shareholders know that there is a potential guarantor for the system, namely the
government.
At present banks regard consumer lending in general and mortgage lending in particular
as one of the most profitable areas of business. Lower interest rates have made it
possible for people to fund larger loans. But when mortgages are agreed based on the
appraised value of a house, while the value of housing is pushed higher by the easy
availability of mortgages, there is a serious risk that house prices can reach extreme
levels. If house prices should fall significantly, people who buy near the peak with high
loan-to-value ratios will face significant losses. High debt burdens can then exacerbate
the impact of falling house prices on the economy as a whole. It is at this period you
witness debt deflation, where people are forced to sell their homes to pay off debts,
leading to further falls in house prices.
In Tanzania, we have seen discovery of new oil fields, new minerals and influx of
foreign capital which obviously motivates the growth of construction industry. Indeed
housing and real estate is an engine of growth from low income citizen to a large
company. Thus it brings us to a very important area of observing interaction of housing
with the economy. Rising house prices and growing borrowing has supported low
savings rate and high consumer spending growth. We can clearly attribute the high
spending goes into the real estate/housing sectors. If we want to prevent a bigger asset
bubble in housing market in Tanzania it is wise to try to reverse the high spending habit
into housing (or at least control it). But it is not so simple to design this move and avoid
strong economic repercussions; that is increasing the saving rate imply reducing the
consumer spending and thus economy would grow much more slowly. It is thus
important if a government could increase spending so as to expand growth; but time and
time again the Tanzanian budget is ever in deficit (like the rest of developing nations). In
these turbulent global crises even the industrial nations are in steep deficit. The new
resources discovered in Tanzania cannot fast track high economic paces in a short-run,
11
much of the benefits will be realized in a long-run; this is due to Return on Invested
Capital – too much capital invested which takes many years to be recovered. The most
crucial sector to save the economy will always be export sector. This will also be saviour
area even in times of bubble burst in Tanzania; but it will all depend how prepared we
would be by then (or rather now).
Tanzania can learn much over application of monetary policy towards housing market
from the experiences of Britain as well. During 2001-2003, with the world economy
weak and the pound strong, hurting exports and depressing Britain‘s manufacturing
sector, the overall economy grew slower than its trend rate (around 2.5 per cent) and
inflation was below target (Calverley, 2004). As a result, interest rates were cut from 6
per cent to 3.5 per cent, well below ‗neutral‘ levels. But with unemployment stable and
consumers less pessimistic than manufacturers, house prices boomed.
The housing bubble threatens a weak economy in future if house prices fall abruptly,
which could pull inflation below the Bank of England‘s 2 per cent target. But trying to
prick the bubble to avoid this risk might simply precipitate the crisis later. In 2003-4,
with the economy strengthening, rates began to move up, but this was no more than the
conventional monetary policy response, aimed at returning interest rates gradually
towards the neutral level, believed to be around 5 per cent in the UK. The main reason
for gradualism is that the Bank of England wanted growth to exceed trend for a while, to
help push inflation back up to 2 per cent target. But, perhaps inevitably, house prices and
debt responded to this very gradual approach by accelerating in the first half of 2004. A
good lesson we can get during bubble inflation is that monetary policy cannot only alone
solve much to keep the economy afloat (but one of the means to try approach the crisis).
US household debt payments as a per cent of income reached their highest level in 2000
at over 13 per cent. But despite the fall in interest rates, the ratio has remained about the
same level since then, due to increased borrowing. In contrast, during the early 1990s in
the last recession, the ratio came down sharply, with lower interest rates and slower
12
borrowing. From the low point of 1 per cent in 2003 the Federal Funds moved back to
neutral levels and then rose higher (for Fed to slow the economy at some stage). Bond
yield was above 2002-3 levels of around 4 per cent, increasing mortgage rates on new
loans.
2.2 Empirical Literature and Conceptual Framework
The economic effects from the recent global financial crisis has undoubtedly triggered a
renewal discussion about the impact of bubbles and the role of public policy in
addressing them (Evanoff, D., Kaufman, D. and Malliaris, A.G1. It is enough to say that
the financial crisis can be looked into; (a) Conceptual issues concerning the existence of
asset price bubbles; (b) The consequences of bursting such bubbles; (c) Monetary policy
‗management‘ of bubbles and (d) The role of macro prudential regulation in addressing
bubbles.
Conceptual issues concerning the existence of asset price bubbles: A bubble is
generally said to exist if an asset price exceeds its price as determined by
―fundamentals‖ – i.e., the present value of its discounted expected future cash flows – by
a significant amount and this premium persists for some time. If the price of an asset
exceeds its fundamentals only by a very small amount, the differential may only
represent noise instead of bubble. If the deviation from fundamentals lasts for only a
very short trading interval, this may represent temporary mispricing. A bubble forms
because the purchase of an asset is made not necessarily based on the rate of return on
the investment, but in anticipation that the asset can be sold to a ―greater fool‖ at an ever
higher price. A price increase for an asset leads to investor enthusiasm, which further
causes increased demand and additional price increases, and so on. The high demand is
supported by the public‘s memory of high past returns or by optimism that this new asset
will generate high future earnings. This positive trend of increase in prices will finally
1 Evanoff, D.,Kaufman,G.,Mallians A.G. Asset Price Bubbles: Lessons from recent financial crisis.
Retrieved 11th
February 2014 from the World Wide Web: http://www.worldfinancialreview.com/?p=2200
13
change pace and sceptics will rise and turn-around the direction; now a bubble burst out
of this confusion due to sudden drop in price. The significant price decline reflect the
bursting of bubbles in stock markets and real estate markets since the macro economy
analysis on these sectors shows equity and homeownership account for most of
household wealth.
Asset Price Bubbles and Monetary Policy: Any Central Bank such (as Tanzania) has a
mandate to promote price stability and maximum sustainable employment, as well as
maintain financial stability. In United States, Federal Reserve Chairman Greenspan,
tried to formulate the monetary policy in a risk management framework. This framework
assessed the various sources of risks and uncertainty facing the economy, quantified the
risks, and calculated an expected cost associated with the risk. Now, whenever no
significant financial risks or bubble risks existed, the Fed would review inflation,
economic growth, and employment conditions and implement monetary policy by
adjusting the Fed funds rate along the lines of Taylor rule. At one point it was generally
concluded that during bubble‘s expansion stage, the Fed should not increase the Fed
fund rates to deflate the asset bubble. However, if the bubble burst, the Fed should act
immediately and reduce the Fed funds rate to reduce the adverse economic impact of the
bursting. This asymmetric approach to asset bubble became known as the ‘Jackson Hole
Consensus’.
14
Figure 2.1: Expansion vs Contraction Monetary Policy
Monetary policy division
Source: Researcher
Macroprudential Regulation: This relate to a specific policy tool that can be more
accurately directed at the bubble related sector (housing market) as well as bringing
price stability. Adjustment (changes) in bank rate is a blunt policy tool affecting the
market as a whole instead of specific sectors. In addressing asset bubbles, the goal is
typically to target a price build-up in a particular sector – housing market in such as our
concern. Financial regulation can broadly be separated into ‘microprudential’
regulation, which considers the condition of individual financial institutions, and
‘macroprudential’ regulation, which focuses across financial institutions and markets,
and on the efficient functioning of the financial system as a whole. Until recently,
regulatory and supervisory policies operated on the presumption that the financial
system as a whole could be made safe by ensuring that individual financial institutions
were made safe. This ignored market interconnections and externalities, whereby the
actions of one financial institution can lead to a spill-over effects that adversely affect
other financial institutions, general market conditions, and ultimately the economy as a
whole. Instead it may be necessary to use both microprudential and macroprudential
policies to manage financial system risks and achieve financial stability.General
15
monetary policy tools are used to influence the overall macroeconomic situation without
concern about the particular sector of the economy to be affected; such as bank rate,
reserve requirements and discount rate, and the use of moral suasion. Specific tools may
be a bit trickier however there are suggestions. These are; credit market control,
changes in stock market margin requirements, a time varying bank capital ratio,
monitoring of a credit to GDP ratio and supervisory discretion against activities of
important firms in the economy. Soft Central Bank policy may be the precursor of major
asset price exaggerations down the road Hofrichter (2014). Hofrichter says, according to
Charles Kindleberger, an economic historian from his seminal book, ―Maniacs, Panics,
and Crashes‖; asset bubbles usually do not come as single events, but rather as multiple
asset bubbles or as a series of bubbles in quick succession. Emerging markets, as far as
they have linked their currencies to hard currencies, are importing easy monetary policy
from the West. This also applies to developing countries like Tanzania. In a case of a
financial market deregulation2as it may seem practical tools can largely contribute to a
strong private sector credit growth and so precipitate the bubble.
It is undeniable truth that every citizen in the world if it were possible would love to own
a house someday, and this has proven true from the angle of Western nations judging
from the recent real estate bubble which devastated millions of household owners and
citizens. A house is a basic security and most potential part of any moral human.
Americans' love of their homes is widely known and acknowledged (Time, 2005)
however, many believe that enthusiasm for home ownership is currently high even by
American standards, calling the real estate market "frothy" (Greenspan, A. 2005). Only
if the ‗world‘ citizens knew that it has been observed historically; equity price busts
occur on average every 13 years, lasts for 2.5 years, and result in about 4 per cent loss in
GDP then we‘ll be keen on our drive in this sector. Housing price busts are less frequent,
2financial market deregulation include among others the liberalization of the credit market, introduction of
new financial instruments (such as wealth management products) as well as the opening up of the capital
account, which facilitate the capital inflows.
16
but last nearly twice as long and lead to output losses that are twice as large (IMF World
Economic Outlook, 2003). It has been noticed that whenever the Tanzania Electricity
Supply Company (TANESCO) rises the cost of their utility, owners of houses also finds
a way (or call it excuse) to raise the cost/price of their houses. TANESCO raises their
prices because of their struggle with debt and systemlosses. As at January 2014, Energy
and Water Utilities Regulatory Authority (EWURA) announced new power tariffs,
which are 40 per cent increase.3In this circle cyclical price war we can notice how the
monetary and fiscal policy affects the Tanzanians. We can refer to a letter of intent to
IMF in June 2013, when the state said it ‗would limit subsidies to TANESCO to 105
million USD (this is about TZS 200 billion) in the 2013/14 financial year against the
company‘s projected financial needs of 352 million USD (over TZS 560 billion).4It is
this that has pushed TANESCO to raise tariff, but we also see the hand of government
interplay in all this to influence the power costs. According to World Bank estimates,
TANESCO‘s arrears have jumped from 270 million USD as at the end of 2012 to about
500 million USD, with the figure said to be growing at 30 million USD monthly. It is
clearly, monetary policy is crawling beneath and influencing the value and figures
indirectly and we breathe the effects directly.
2.2.1 A Central Bank
A Central Bank, reserve bank or monetary authority is an institution that manages a
state‘s currency, money supply and interest rates. This is an organ which supervises
commercial banking system of their respective countries. Central Bank of Tanzania is a
typical example of one described here. The primary function of Bank of Tanzania (BoT)
3 Ihucha, A (1
st February 2014). Consumers to dig deeper into their pockets as TANESCO raises tariffs.
The East African. Retrieved 5th
March 2014 from World Wide Web:
http://www.theeastafrican.co.ke/business/Costly-power-as-Tanesco-raises-tariffs-/-/2560/2169138/-
/wdb61kz/-/index.html
4 Daily News (5
th July 2013). Power consumers to pay more as TANESCO seeks tariff hike. Daily News
retrieved 5th
March 2014 from World Wide Web: http://dailynews.co.tz/index.php/biz/19480-power-
consumers-to-pay-more-as-tanesco-seeks-tariff-hike?device=desktop
17
is to manage the national‘s money supply through ‗monetary policy‘. Bank of Tanzania
is responsible to monitor commercial banks do not run out of money, restrict discipline
in business conduct and act as lender of last resort.
Tanzania Central Bank and others worldwide possess the following functions;
(i.) Implementing monetary policies
(ii.) Determining interest rates
(iii.) Controlling the nation‘s entire money supply
(iv.) The government‘s banker and the bankers‘ bank (lender of last resort)
(v.) Managing the country‘s foreign exchange and gold reserves and the
government‘s stock register
(vi.) Regulating and supervising the banking industry
(vii.) Setting the official interest rate – used to manage both inflation and the country‘s
exchange rate – and ensuring that this rate take effect via a variety of policy
mechanisms
Figure 2.2: Bank of Tanzania view
Overview of Bank of Tanzania Twin Towers, Conference Centre and Parking Arcade
Source: Bank of Tanzania Org, ‗Overview of BOT‘ (2014)
18
2.2.2 Bank Regulation
Bank regulations are a form of government regulation which subject banks to certain
requirements, restrictions and guidelines. This regulatory structure creates transparency
between banking institutions and the individuals and corporations with whom they
conduct business, among other things. Given the interconnectedness of the banking
industry and the reliance that the national (and global) economy hold on banks, it is
important for regulatory agencies to maintain control over the standardized practices of
these institutions. Supporters of such regulation often hinge their arguments on the "too
big to fail" notion. This holds that many financial institutions (particularly investment
banks with a commercial arm) hold too much control over the economy to fail without
enormous consequences. This is the premise for government bailouts, in which
government financial assistance is provided to banks or other financial institutions that
appear to be on the brink of collapse. The belief is that without this aid, the crippled
banks would not only become bankrupt, but would create rippling effects throughout the
economy leading to systemic failure. General principles of bank regulation throughout
the world include; Minimum requirements, Supervisory review and Market discipline.
The recent asset bubble in housing market in the western nations is a result of market
irregularity and poor regulations of Central Banks, typically at a core of disaster –
United States of America [Federal Reserve]
Among the reasons for maintaining close regulation of banking institutions is the
concern over the global repercussions that could result from a bank's failure; the idea
that these bulge bracket banks are "too big to fail". The objective of Bank of Tanzania is
to avoid situations in which the government must decide whether to support a struggling
bank or to let it fail (this has been faced by Federal Reserve in United States in the
recent economic crisis, but luckily not in Tanzania). The issue, as many argue, is that
providing aid to crippled banks creates a situation of moral hazard. The general
premise is that while the government may have prevented a financial catastrophe for the
time being, they have reinforced confidence for high risk taking and provided an
19
invisible safety net. This can lead to a vicious cycle, wherein banks take risks, fail,
receive a bailout and then continue to take risks once again. Most economics have
further debated importance of bailout as ‗perhaps‘ it is interfering with principles of free
economy and thus seems with government money to these private firms comes strings
which gives a view of government in control of the economy. In fact the recent asset
bubble and global recession has led to economists to question over the efficiency of
‗capitalist market economy‘, is free-economy insufficient? As much as democracy is
now questioned in various governments and so is the whole trunk of capitalist economy
being doubted now when the government inject money to its agencies and private firms.
2.2.3 Monetary Policy
Is the process by which the monetary authority of a country controls the supply of
money, often targeting a rate of interest for the purpose of promoting economic growth
and stability (Elsevier, 2010). The official goals usually include relatively stable prices
and low unemployment. Monetary policy is referred to as either being expansionary or
contractionary, where an expansionary policy increases the total supply of money in the
economy more rapidly than usual, and contractionary policy expands the money supply
more slowly than usual or even shrinks it. Expansionary policy is traditionally used to
try to combat unemployment in a recession by lowering interest rates in the hope that
easy credit will entice businesses into expanding. This too often leads to bubble build up
as there is too much money in the economy that citizens (as Tanzanians) tempts to rise
prices to curb the endless lust and desire to grab everyshilling in the economy.For some
reasons, in most developing nations, Tanzania included there is relaxed monetary
policies (expansionary) during major political presidential campaigns and elections. This
awkward decision reinforced by politicians to Central Banks, in a brief time money
circulation brings happy faces and confidence to the government from its citizen (which
is a primary objective). The dark-side of this choice to the entire nation is that,it raises
the inflation levels, introducing a grim future of clean-up ofthe self-imposed economic
mess which deteriorate national development.Contractionary policy is intended to slow
20
inflation in order to avoid the resulting distortions and deterioration of asset values.
Contractionary monetary policy is also without neither weaknesses nor pinch no matter
how convincing it looks in solving inflationary tendencies.Bank of Tanzania (BoT) has
in the past constricted the money supply so as to control the supply of currency. This has
never gone smooth and enthusiastically accepted as it touches potential businesses and
slows economic growth as in the incidence of 2011.5Economy by itself is self-regulated,
prices being regulated by the demand and supply forces, though it is inevitable for
government not to interfere once in a while. Monetary policy actions prompt rise or fall
of prices, with that, gives the birth of the bubble. Speculation of bubble is a mere sight
of rising of the prices of assets from their intrinsic stage (value). It should be noted that,
speculation powerfully touches the high capital sectors – housing and stocks mostly. In
Tanzania, housing industry and stocks are not strongly reflected in bubble as compared
to the western nations, however all developing nations feels (or rather, have felt) is the
economic pressure (burst of bubbles) - as waves travels from industrial to developing
nations. In other words, we can use a term ‘ripple effects’. Tanzania economy is
surrounded by much tale-tale indicators to show not only economic bubbles are in
speculations, but indeed bubbles are inflating, and there is unforeseen danger if they are
not controlled.
Developing countries may have problems establishing an effective operating monetary
policy. The primary difficulty is that few developing countries have deep markets in
government debt. The matter is further complicated by the difficulties in forecasting
money demand and fiscal pressure to levy the inflation tax by expanding the monetary
base rapidly. In general, the central banks in many developing countries have poor
records in managing monetary policy. This is often because the monetary authorities are
5 Business Times. Tanzania: tighter monetary policy could slow down economic growth (23
rd December
2011). Retrieved 15th
February 2014 from World Wide Web:
http://www.businesstimes.co.tz/index.php?option=com_content&view=article&id=1614:-tanzania-tighter-
monetary-policy-could-slow-down-economic-growth&catid=1:latest-news&Itemid=57
21
not independent of government interference. Thereby, good monetary policy takes a
backseat to the political desires of the government or is used to pursue other non-
monetary goals. For this and other reasons, developing countries that want to establish
credible monetary policy may institute a currency board or adopt dollarization. Such
forms of monetary institutions thus essentially tie the hands of the government from
interference and, it is hoped, that such policies will import the monetary policy of the
anchor nation.
Monetary policy uses three main tactical approaches to maintain monetary stability:
The first tactic manages the money supply; involves buying government bonds
(expanding the money supply) or selling them (contracting the money supply). In the
Central Bank of Tanzania, these are known as open market operations, because the
central bank buys and sells government bonds in public markets. Most of the
government bonds bought and sold through open market operations are short-term
government bonds bought and sold from BoT member banks (like CRDB and NBC
Banks) and from large financial institutions. When the Central Bank disburses or
collects payment for these bonds, it alters the amount of money in the economy while
simultaneously affecting the price (and thereby the yield) of short-term government
bonds. The change in the amount of money in the economy in turn affects interbank
interest rates(Abel and Bernanke, 2005). The second tactic manages money demand;
demand for money, like demand for most things, is sensitive to price. For money, the
price is the interest rates charged to borrowers. Setting banking-system lending or
interest rates (such as overnight bank lending rate or discount rate) in order to manage
money demand is a major tool used by a Central Banks. Ordinarily, a Central Bank
conducts monetary policy by raising or lowering its interest rate target for the interbank
interest rate. If the nominal interest rate is at or very near zero, the central bank cannot
lower it further (this circumstance is known as a liquidity trap).
22
The third tactic involves managing risk within the banking system. Banking systems use
fractional reserve banking to encourage the use of money for investment and expanding
economic activity. Banks must keep banking reserves on hand to handle actual cash
needs, but they can lend an amount equal to several times their actual reserves. The
money lent out by banks increases the money supply, and too much money (whether lent
or printed) will lead to inflation. Central Banks manage systemic risks by maintaining a
balance between expansionary economic activity through bank lending and control of
inflation through reserve requirements.
Conclusively, we can say monetary policy is the process by which the monetary
authority of a country controls the supply of money, often targeting a rate of interest for
the purpose of promoting economic growth and stability.6This is opposed to fiscal
policy which is the use of government revenue collection (taxation) and expenditure
(spending) to influence the economy.7Monetary policy can be either expansionary or
contractionary; the former increasing money supply in the economy, especially during
the recession by lowering the interest rates, thus expanding business and investments in
hope to increase employments; whereas the later reduces the money supply in the
economy attempting to combat inflation so as to control rise in prices of the
commodities and assets.
2.2.4 Fiscal Policy
Is the use of government revenue collection (taxation) and expenditure (spending) to
influence the economy (O' Sullivan and Sheffrin, 2003). The two main instruments of
fiscal policy are changes in the level and composition of taxation and government
spending in various sectors. These changes can affect the macroeconomic variables in
an economy such as: aggregate demand and the level of economic activity; the
6 "Monetary and Exchange Rate Policies". Handbook of Development Economics, Elsevier. 2010.
7O' Sullivan, Arthur; Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River,
New Jersey 07458: Pearson Prentice Hall. pp. 387.
23
distribution of income; the pattern of resource allocation within the government sector
and relative to theprivate sector.
Types of Fiscal Policies include;
(i) Neutral fiscal policy: usually undertaken when an economy is in equilibrium.
Government spending is fully funded by tax revenueand overall the budget
outcome has a neutral effect on the level of economic activity.
(ii) Expansionary fiscal policy: involves government spending exceeding tax
revenue, and is usually undertaken during recessions.
(iii) Contractionary fiscal policy:this occurs when the government spending is lower
than tax revenue, and is usually undertaken to pay down government debt.
Governments spend money on a wide variety of things, thus the expenditure can be
funded in various forms like:
(i) Taxation
(ii) Seignior-age - the benefit from printing money
(iii) Borrowing money from the population or from abroad
(iv) Consumption of fiscal reserves and
(v) Sale of fixed assets (e.g., land)
Governments use fiscal policy to influence the level of aggregate demand in the
economy, in an effort to achieve economic objectives of price stability, full employment,
and economic growth. Keynesian economics suggests that increasing government
spending and decreasing tax rates are the best ways to stimulate aggregate demand, and
decreasing spending & increasing taxes after the economic boom begins. Keynesians
argue this method be used in times of recession or low economic activity as an essential
tool for building the framework for strong economic growth and working towards full
employment. In theory, the resulting deficits would be paid for by an expanded economy
during the boom that would follow. Governments can use a budget surplus to do two
24
things: to slow the pace of strong economic growth and to stabilize prices when inflation
is too high. Keynesian theory posits that removing spending from the economy will
reduce levels of aggregate demand and contract the economy, thus stabilizing prices. But
economists still debate the effectiveness of fiscal stimulus. The argument mostly centres
on crowding out: whether government borrowing leads to higher interest rates that may
offset the stimulative impact of spending. When the government runs a budget deficit,
funds will need to come from public borrowing (the issue of government bonds),
overseas borrowing, or monetizing the debt. When governments fund a deficit with the
issuing of government bonds, interest rates can increase across the market, because
government borrowing creates higher demand for credit in the financial markets. This
causes a lower aggregate demand for goods and services, contrary to the objective of a
fiscal stimulus. Neoclassical economists generally emphasize crowding out while
Keynesians argue that fiscal policy can still be effective especially in a liquidity trap
where, they argue, crowding out is minimal.
2.2.5 Economic Bubbles
An economic bubble (speculative bubble) is trade in high volumes at prices that are
considerably at variance with intrinsic values.8By intrinsic value, it means the value of
a security which is inherent to or contained in the security itself (it is also frequently
called fundamental value). It is ordinarily calculated by summing the future income
generated by the asset, and discounting it to the present value. The cause of bubbles
remains a challenge up to date, and while this is so for many years, it has become even
difficult to follow the changes of prices from their fundamental value of a particular item
/ product. Economists commonly observe bubble from a drop in prices – this is bubble
burst or crash – as a crisis of collapse of Wall Street in USA in recent years (2007 -
2010). Normally this takes a wave effect especially if it originate from a strong dominant
economy, as when the Wall Street stock exchange collapsed in 2008; the whole world
8 Lahart, J. (2008). "Bernanke's Bubble Laboratory, Princeton Protégés of Fed Chief Study the Economics
of Manias". The Wall Street Journal: p. A1.
25
felt the economic pain. Some scholars argues that bubble bursts gradually, with the most
exposed assets getting hurt first and then everyone else feels it, like the oil prices
scenario recently. Development of bubble involves various stages. There are certain
occurrences in the economy which take place such as war, new technology and new
production styles that may initiate a new cycle of productivity; leading into a boom, a
boom which is usually fuelled by financial institutions. More money is poured in the
economy (in that particular lucrative industry), new firms enter the industry and more
banks supports that initiatives, and hence everyone harvests profits and expands.
Meanwhile, prices get pushed up because there is more demand, and suppliers enjoy the
benefits of money gains. Consumers are reluctant of the rise in prices too. Speculation
start mounting while people are more optimistic in investments. Rumours start to fly in
the air over the rising trend in prices but no one listens to serious economists and
institutions pointing out the disease. Everyone wants quick money, and the market
becomes so saturated. Actually, the interesting part of any economic bubble including
housing market is that nobody listens to warnings because all are drunk from the
alcohol of money – greed and money never sleep.Suddenly in the midst of saturation and
information awareness to all in the economy, the market starts to slow and investments
lower. Now the government becomes cautious, the banking sector observes keenly the
low returns and prepares drastic measures. There is no particular reason as what could
trigger this phenomenon of low investment and drop in price– another mystery of
economic bubble!Truly, anything could come into a picture perhaps; war, or rumours of
war, high oil prices or change in government leadership! Up to this stage bankruptcy
may be witnessed now and there is mounting uncertainty, and the scope of business
confidence collapse. Consumer shows now the signs of hoarding. From this junction, we
say the bubble has burst. This is a short description of the bubble generation (inflation of
bubble) and burst. Depression is indeed the burst of the bubble.
26
2.2.5.1 Housing Market Indicators
A real estate bubble or property bubble (or housing bubble for residential markets) is a
type of economic bubble that occurs periodically in local or global real estate markets. It
can be identified through rapid increases in valuations of real property such as housing
until they reach unsustainable levels and then decline. The questions of whether real
estate bubbles can be identified and prevented and whether they have broader
macroeconomic significance are answered differently by schools of economic thought.
The financial crisis of 2007–2012 was related to the bursting of real estate bubbles
around the world, which had begun during the 2000s.9It is still argumentative how to
identify an asset bubble, but the scenery changes during a peak and a crush gives us a
window to observe the development of any particular sector of economy to attempt to
learn one or two about a bubble. Within mainstream economics, it can be posed that real
estate bubbles cannot be identified as they occur and cannot or should not be prevented,
with government and central bank policy rather cleaning up after the bubble bursts.
In attempting to identify bubbles before they burst, economists have developed a number
of financial ratios and economic indicators that can be used to evaluate whether homes
in a given area are fairly valued. By comparing current levels to previous levels that
have proven unsustainable in the past (i.e. led to or at least accompanied crashes), one
can make an educated guess as to whether a given real estate market is experiencing a
bubble. Indicators describe two interwoven aspects of housing bubble: a valuation
component and a debt (or leverage) component. The valuation component measures how
expensive houses are relative to what most people can afford. The debt component
measures how indebted households become in buying them, for home or profit (and also
how much exposure the banks accumulate by lending for them).
9Klein, Ezra (28
th May 2009). Bill Clinton and the Housing Bubble. Washington Post. Retrieved15th
February 2014 from World Wide Web: http://voices.washingtonpost.com/ezra-
klein/2009/05/bill_clinton_and_the_housing_b.html
27
2.2.5.1.1 Housing Affordability Measures
The price to income ratio is the basic affordability measure for housing in a given area.
It is generally the ratio of median house prices to median familial disposable incomes,
expressed as a percentage or as years of income. This ratio, applied to individuals, is a
basic component of mortgage lending decisions. According to a back-of-the-envelope
calculation by Goldman Sachs, a comparison of median home prices to median
household income suggests that U.S. housing in 2005 is overvalued by 10%. According
to Goldman's figures, a one-percentage-point rise in mortgage rates would reduce the
fair value of home prices by 8%. The deposit to income ratio is the minimum required
down payment for a typical mortgage, expressed in months or years of income. It is
especially important for first-time buyers without existing home equity; if the down
payment becomes too high then those buyers may find themselves ‗priced out‘ of the
market. The usefulness of this ratio in identifying a bubble is debatable; while down-
payments normally increase with house valuations, bank lending becomes increasingly
lax during a bubble and mortgages are offered to borrowers who would not normally
qualify for them.
The Affordability Index measures the ratio of the actual monthly cost of the mortgage to
take-home income. The Median Multiple measures the ratio of the median house price to
the median annual household income.
28
Figure 2.3: Robert Shiller's plot of U.S. home prices, population, Building Costs,
And Bond Yields, from Irrational Exuberance
Robert Shiller's plot of U.S. home prices, population, building costs, and bond yields, from Irrational
Exuberance, 2d ed. Shiller shows that inflation adjusted U.S. home prices increased 0.4% per year from
1890–2004, and 0.7% per year from 1940–2004, whereas U.S. census data from 1940–2004 shows that the
self-assessed value increased 2% per year.
Source: Wikipedia.org - Real Estate Bubble, ‗Robert Shiller‘s plot of US Home Prices‘ (June2013)
2.2.5.1.2 Housing debt Measures
The housing debt to income ratio or debt-service ratio is the ratio of mortgage payments
to disposable income. When the ratio gets too high, households become increasingly
dependent on rising property values to service their debt. A variant of this indicator
measures total home ownership costs, including mortgage payments, utilities and
property taxes, as a percentage of a typical household's monthly pre-tax income. The
housing debt to equity ratio (not to be confused with the corporate debt to equity ratio),
also called loan to value, is the ratio of the mortgage debt to the value of the underlying
29
property; it measures financial leverage. This ratio increases when the homeowner takes
a second mortgage or home equity loan using the accumulated equity as collateral. A
ratio greater higher than 1 implies that owner's equity is negative.
Figure 2.4 : Inflation-adjusted Home Prices in Japan (1980–2005)
Inflation-adjusted home prices in Japan (1980–2005) compared to home price appreciation in the United
States, Britain, and Australia (1995–2005).
Source: Wikipedia.org (Real Estate Bubble) – Economist Magazine (June 2005), ‗House Prices in
Industrialised Nations‘ (June2013).
2.2.5.1.3 Housing Ownership and Rent Measures
The ownership ratio is the proportion of households who own their homes as opposed to
renting. It tends to rise steadily with incomes. Also, governments often enact measures
such as tax cuts or subsidized financing to encourage and facilitate home ownership.
30
Bubbles can be determined when an increase in housing prices is higher than the rise in
rents. Rent over the past 30-years has risen steadily about 3-percent a year whereas
between 1997 and 2002 housing prices rose 6-percent a year. Between 2011 and the
third-quarter of 2013 housing prices rose 5.83-percent and rent increased 2-percent.10
In
the coming discussions we shall get precise statistics over the rising trends of housing
rents and prices in Tanzanian market
If a rise in ownership is not supported by a rise in incomes, it can mean either that,
buyers are taking advantage of low interest rates (which must eventually rise again as
the economy heats up) or that home loans are awarded more liberally, to borrowers
with poor credit. Therefore a high ownership ratio combined with an increased rate of
subprime lending may signal higher debt levels associated with bubbles. The price-to-
earnings ratio or P/E ratio is the common metric used to assess the relative valuation of
equities. To compute the P/E ratio for the case of a rented house, divide the price of the
house by its potential earnings or net income, which is the market annual rent of the
house minus expenses, which include maintenance and property taxes.
The house price-to-earnings ratio provides a direct comparison with P/E ratios utilised to
analyse other uses of the money tied up in a home. Compare this ratio to the simpler but
less accurate price-rent ratio below.
The price-rent ratio is the average cost of ownership divided by the received rent income
(if buying to let) or the estimated rent (if buying to reside):
10
Wallison, P. J (2014). The Bubble is Back, New York. The New York Times, p. A15. Retrieved 15th
February 2014 from World Wide Web: http://www.nytimes.com/2014/01/06/opinion/the-bubble-is-
back.html?ref=opinion
31
The latter is often measured using the "owner's equivalent rent" numbers (which is
published by the Bureau of Labour Statistics or statistical institution of a particular
country). It can be viewed as the real estate equivalent of stocks' price-earnings ratio; in
other terms it measures how much the buyer is paying for each dollar of received rent
income (or dollar saved from rent spending). Rents, just like corporate and personal
incomes, are generally tied very closely to supply and demand fundamentals; one rarely
sees an unsustainable "rent bubble" (or "income bubble" for that matter). Therefore a
rapid increase of home prices combined with a flat renting market can signal the onset of
a bubble.
The gross rental yield, a measure used in the United Kingdom, is the total yearly gross
rent divided by the house price and expressed as a percentage:
This is the reciprocal of the house price-rent ratio. The net rental yield deducts the
landlord's expenses (and sometimes estimated rental voids) from the gross rent before
doing the above calculation; this is the reciprocal of the house P/E ratio.
Because rents are received throughout the year rather than at its end11, both the gross and
net rental yields calculated by the above are somewhat less than the true rental yields
obtained when taking into account the monthly nature of rental payments. The
occupancy rate (opposite: vacancy rate) is the amount of occupied housing units divided
by the total amount of units in a given region [in commercial real estate, it is usually
expressed in terms of area (i.e. in square metres, acres, et cetera) for different grades of
buildings]. A low occupancy rate means that the market is in a state of oversupply
11 In Tanzania, rents are normally paid yearly, and hardly semi-annually in domestic rented homes. In
commercial real estates apartment and office space monthly rental arrangements can be made. There is no
law protecting the landlord/ lessee to pay/receive monthly rent giving some landlords power to abuse their
occupants.
32
brought about by speculative construction and purchase. In this context, supply-and-
demand numbers can be misleading: sales demand exceeds supply, but rent demand does
not.
2.2.5.1.4 Housing Price Indices
Measures of house price are also used in identifying housing bubbles; these are known
as house price indices (HPIs). A noted series of HPIs for the United States are the Case–
Shiller indices, devised by American economists Karl Case, Robert J. Shiller, and Allan
Weiss. As measured by the Case–Shiller index, the US experienced a housing bubble
peaking in the second quarter of 2006 (2006 Q2).
Figure 2.5 : The Case–Shiller index (national, quarterly) 1987–2008
The Case–Shiller index (national, quarterly) 1987–2008, showing a housing bubble peaking in 2006.
Source: Wikipedia.org (Real Estate Bubble) – Economist Magazine (June 2005), ‗House Prices in
Industrialised Nations‘ (June2013)
2.2.5.2 Indicators of bubble (evidence) in Tanzania
This section discuss economic indicators of the bubbles in the Tanzania economy; this is
not exhausted indicators, but enough to bring awareness of the subject under discussion
33
and anyone‘s judgement.These indicators don’t give specific housing asset indicators, as
Tanzania economy in a context of real estate is very young to segregate and separate
each of their variable contents - as in examining ‗real estate‘ in a separate variable
dimensions. A researcher uses these general indicators in a greater faith that they reflect
behaviour of housing bubble since housing market responds parallel to these indicators
dynamics. We can start observing natural resources discovery in Tanzania that is/will
propel a wheel of rise in prices of commodities as the welfare of the society improves
and money gains value pushing prices up. These include natural gas reserves estimated
at 43 Trillion Cubic feet (TCF) being valued around $430 billion (Think Africa Press,
May 2013). East Africa‘s coastal waters are thought to hold up to 441 trillion cubic feet
of natural gas (U.S. Geological Survey). Oil discovery in Lake Nyasa as witnessed
bringing hot debate over lake ownership between Tanzania and Malawi is yet another
resource on a way. The Indian Ocean shores have the potential for oil and gas, which has
also awaken the debate of ownership between Zanzibar and mainland Tanzania, bringing
the relics of long grievances - ―union terms and conditions between the colonial
neighbouring nations‖. All these are signs that the bubble‘s future development paces
are ‗guaranteed‘ and at a fastest rate; in fact it is building before our very economic
sphere.
The construction sector in Tanzania (as far as growth is concerned) it is primarily driven
from the roadwork, housing and mining industries. Sectors of works infrastructure,
transport and communication; their growths are also reflected from the expansion of
construction industry in Tanzania. According to ―Tanzania Construction Sector Report‖
by EP Media, the growth rate of the sector increased to 11.9% in 2005/06 from 10.8% in
2004/05 and the contribution of construction activity to the overall GDP rose to 5.7% in
2005/06 compared to a contribution of 5.4% in 2004/05. In 2005/06, the total
government expenditure for construction affairs and services was TZS 53,425 million
compared to the expenditures in 2004/05 which were estimated to be TZS 58,693
million and the expenditures in 2003/04 which were estimated to be TZS 29,740 million.
34
Looking also at the figures in cement consumption in Tanzania; in 2006, the cement
production rose by more than 9% in just the first quarter, whereby in 2005 the total
combined output of the three major cement companies (TWIGA cement, Tanga Cement
Company [SIMBA] and Mbeya Cement Company) reached 1.6 million tonnes.12
―Things have actually improved a lot [and] today we have over 4,470 contractors
registered in Tanzania, both local and foreign‖ says, Mr. B. C. Muhegi, Registrar of the
Tanzania Contractors Registration Board.13Perhaps a glimpse of near future where
Tanzania is heading in housing market and real estate development, or rather where we
have recently began is by appreciating the government bold move in the setting and
developing a New Kigamboni City. The government has set up an agency called
Kigamboni Development Agency (KDA) which manages the Kigamboni City Project in
three phases; 2012-2022, 2022-2027 and 2027-2032. The project is expected to cost
about TZS 11.6 trillion upon completion in year 2032. In 2012, the government of
Tanzania had already set aside (as being spent by this moment) TZS 60 billion on setting
up KDA; for conducting property assessment, social services, resettling residents and
measuring and drawing maps for the proposed town. ―The amount is about 59 per cent
(meaning, the TZS 60 billion set for the first phase to KDA) of a ministry‘s proposed
TZS 101.731 billion budget for the 2012/2013 financial year. Recurrent expenditure will
take up TZS 30.731 billion while TZS 71 billion will go to development projects.‖, the
minister for Lands, Housing and Human Settlements Development, Prof Anna Tibaijuka
said.14This alone has excited construction companies, retailers of building materials and
real estate developers; and so further push up the costs/prices internally (locally) in
irrespective the external (international) market forces already into play.
12Tanzania Construction Sector Report (2013). EP Media. Retrieved on 27th November 2013 from World
Wide Web: http://www.tanzaniainvest.com/construction/reports/58-tanzania-construction-sector-report
13 Ibid, [Tanzania Construction Sector Report
14 Kimboy, F. (12, July 2012). Tanzania sets aside Sh60bn for new Kigamboni city project. Retrieved 6
th
March 2014 from World Wide Web: http://www.theeastafrican.co.ke/news/Tanzania-sets-aside-Sh60bn-
for-new-Kigamboni-city-project/-/2558/1452098/-/kf9o97/-/index.html
35
From above, we can visit some specific housing bubble indicators in Tanzania, which
are:
2.2.5.2.1Tanzania Inflation Rate
The inflation rate in Tanzania was recorded at 12.10 per cent in November of 2012.
Inflation Rate in Tanzania is reported by the National Bureau of Statistics (NBS).
Historically, from 1999 until 2012, Tanzania Inflation Rate averaged 7.7 Per cent
reaching an all-time high of 19.8 per cent in December of 2011 and a record low of 3.4
per cent in February of 2003. In Tanzania, the inflation rate measures a broad rise or fall
in prices that consumers pay for a standard basket of goods.
Figure 2.6 : Tanzania inflation Rate
Source: Trading Economic.com, ‗Tanzania Economic Indicators‘ (2012)
Data above shows an annual change in the consumer price index (CPI). CPI measures
changes in the price level of consumer goods and services purchased by households. It is
calculated by taking price changes for each item in the predetermined basket of goods
36
and services and averaging them. Here, the weight is on energy, food, and housing,
clothing transport, medical care and household equipment.
2.2.5.2.2 Tanzania Shilling
The USDTZS spot exchange rate depreciated 18.0000 or 1.12 per cent during the last 30
days. Historically, from 2003 until 2012, the USDTZS averaged 1294.7700 reaching an
all-time high of 1797.4000 in October of 2011 and a record low of 1014.3000 in
December of 2004. The USDTZS spot exchange rate specifies how much one currency,
the USD, is currently worth in terms of the other, the TZS. While the USDTZS spot
exchange rate is quoted and exchanged in the same day, the USDTZS forward rate is
quoted today but for delivery and payment on a specific future date. Below a chart with
historical data for USDTZS - Tanzania Shilling Exchange rate as 21st December 2012.
Figure 2.7 : Tanzania Shilling
Source: Trading Economic.com, ‗Tanzania Economic Indicators‘ (2012)
37
2.2.5.2.3 Tanzania GDP Annual Growth Rate
Growth Domestic Product (GDP) in Tanzania expanded 6.90 per cent in the second
quarter of 2012 over the same quarter of the previous year. Nation bureau of statistic
reports from 2002 until 2012, Tanzania GDP annual growth rate averaged 7.0.
Figure 2.8 Tanzania GDP annual growth rate
Source: Trading Economic.com, ‗Tanzania Economic Indicators‘ (2012)
2.2.5.2.4 Tanzania Interest Rate
The benchmark interest rate in Tanzania was last recorded at 12 per cent. Interest Rate in
Tanzania is reported by the Bank of Tanzania. Historically, from 2002 until 2012,
Tanzania Interest Rate averaged 12.7 Per cent reaching an all-time high of 21.4 per cent
in October of 2007 and a record low of 3.7 Per cent in December of 2009. In Tanzania,
interest rates decisions are taken by the Bank of Tanzania. The Bank of Tanzania official
interest rate is the bank rate.
Interest rate shown below here on a figure refers to the central bank benchmark interest
rate. It is usual the overnight rate which the central bank makes loans to the commercial
banks under their jurisdiction.
38
Figure 2.9: Tanzania Interest Rate
Source: Trading Economic.com, ‗Tanzania Economic Indicators‘ (2012)
These indicators clearly testify to the improvements/changes observed in Tanzania real
estate/housing market such as office development, retail, industrial and residential
spaces. On the outside, it is admittedly that Tanzania real estate sector is not as highly
developed as the construction sector (in general totality of a sector), but there are proofs
that the developments within the construction sector have benefited the real estate sector.
Not ignoring increases in population growth and recent discovery of resources has
created not only a demand for real estate expansion but also we see inevitability of
investment in this sector. This is seen especially in regions of Dar-es-salaam, Mwanza
and Arusha – precisely in areas of largely office space and followed by residential.
According to ―Tanzania Real Estate Sector Report‖ by EP Media, in October of 2006,
NHC owned 10,790 residential units and 5,231 commercial units; in 2006 the total value
of these units was estimated to be TZS 172,678,098. Of these units, 60% were located
in the capital city of Dar es Salaam, which is in line with the increasing demand for
housing in the urban areas within Tanzania, and were valued at TZS
168,552,369,379.38. Interesting information is that Tanzania Building Agency (TBA)
39
reported that are not currently able to meet the needs of its large customer base (high
demand of residential space) due to low capital. ―Up to now, the agency is capable of
building only about 250 houses every year…but our customers are about 350,000 in
total. As you can see, the gap is very big." said, Architect Makumba T. Kimweri, Chief
Executive of the Tanzania Building Agency.15
The International Real Estate firm, Knight Frank LLP estimates that in Dar-es-salaam –
crucial/principal locations: the current rent prices for retail space are approximately
US$12 per square meter per month with a yield of 13.5%; the rent prices for industrial
space are approximately US$5 per square meter per month with a yield of 15% and for
residential space in Dar es Salaam are around US$4,000 per month with a yield of 12%.
Arusha has shown a noteworthy inflow of cash into the local economy primarily
attributed to the presence of International Criminal Tribunal for Rwanda (ICTR) which
estimated to bring about US$ 60 million between 2002 and 2004. This has benefited real
estate and construction sectors, hence witnessing a number of houses, shopping centres,
and hotels mushrooming in Arusha; as well as even Kilimanjaro International Airport
(KIA) development/improvements.16There are an estimated 14 million people who
spends approximately 40 per cent of their income for rent housing mostly single rooms
in urban areas in the country (The Guardian on Sunday, IPP Media, 2013), particularly
in Dar-es-salaam. There are tremendous efforts by government, private firms and
individuals in seeking a way out of the housing problem. Ironically in a way we are
solving our housing needs either for residential or commercial we are also creating an
economic disease – inflation of housing market prices, leading to housing market crush.
This research aims to find the optimum path to keep development and the asset bubble in
check.
15 Tanzania Real Estate Sector Report (2013). EP Media. Retrieved 27th November 2013 from World
Wide Web: http://www.tanzaniainvest.com/construction/reports/57-tanzania-real-estate-sector-report
16Ibid, [Tanzania Real Estate Sector Report
40
2.2.5.3 Basic Coverage of a Bubble
2.2.5.3.1 Stock Market Bubble
This refers to the rise in the share price of stocks in a particular industry. Bubble
happens when the speculators in a particular industry realises the lucrative nature of a
particular firm attracting more and more investors, thus attracting rise of share prices. As
more stocks are bought, investors keep anticipating more rise in prices until the actual
value of stocks becomes too much over valued creating inconsistency between price of a
share and actual value of stocks. Now the investors‘ finds share too expensive, no one
wants to buy and burst happens, and thus businesses closes.
2.2.5.3.2 Real Estate Bubble
Prices of housing rise rapidly, and investors and interested household families buys more
and more and enrol in mortgages, and thus at some point with rising prices the bubble
would burst and housing prices would come crushing down. The real estate boom
becomes greatly affected, and debt causes firms to close and individuals become
trapped. Those in mortgages are trapped further and become indebted more.
2.2.6 Construction Industry and Real Estate in Africa and Tanzania
Despite its recognized economic and social importance, housing finance often remains
underdeveloped in emerging economies. The importance of developing robust systems
of housing finance is paramount as emerging economy governments struggle to cope
with population growth, rapid urbanization, and rising expectations from a growing
middle class (Lea, Chiqoier and Hassler, 2004).
Investors Provident reported thatthe real estate market in Africa is growing due to
various investment projections ahead and especially the discovery of natural reserves.
South Africa, Nigeria, Kenya, Egypt property is one of the most interesting investments
41
available today.17Demand for high quality residential and commercial property continues
to grow across Africa on the back of the continent‘s sustained strong economic growth
and rising wealth. Africa is in the midst of a period of dynamic economic expansion,
having averaged GDP growth of more than 5% per annum over the last decade and this
is leading to a dynamic real estate market. According to Knight Frank‘s newly released
Africa Report 2013 this strong growth is expected to continue and is creating wealthier
populations, particularly in the largest and most rapidly growing urban centers.It says
that Africa‘s mega cities such as Lagos, Nairobi, Accra, Lusaka and Dar es Salaam are
increasingly becoming the drivers of its economic growth and, as a result, are attracting
growing interest from occupiers, developers and investors.‘Africa’s impressive economic
progress is generating a growing need for the construction of good quality property in
major cities across the continent. The rising wealth of Africa’s middle class is leading to
demand for increasingly sophisticated retail formats and better quality residential
property,’ said Matthew Colbourne, associate in commercial research at Knight
Frank.‘Meanwhile, as overseas companies seek to expand into Africa’s growing
markets, and as African based companies grow themselves, there is a need for
investment in the construction of high quality office buildings, which are currently in
short supply in many African cities,’ he added.
Oil companies and the banking sector are established sources of demand for office space
in Africa, but African economies are diversifying and non-traditional sectors are
emerging. The growth of mobile technology in Africa has been a particularly prominent
phenomenon over the last decade. We have seen how communication companies in
Tanzania have created direct and indirect labour and expanded their offices throughout
the regions. Africa‘s technology boom is generating new sources of office market
17
Investors Provident. Africa Property Market. Retrieved 14th
February 2014 from World Wide Web:
http://www.investorsprovident.com/africa/
42
demand and the continent is now home to a number of growing technology clusters,
such as Silicon Savannah in Nairobi and Silicon Lagoon in Lagos.
Property Wire (2008) reported that, a major developer was looking to Africa as the next
emerging market which is fresh and full of opportunity. Kensington Real Estate, a
Dubai-based developer, says it is targeting the continent for future projects. The
company planned major projects worth $5bn by 2011 across different locations
including Qatar, Morocco, Australia and India, said company director Ashish
Thakkar.18
It has completed two residential and commercial projects in Africa with a
third project underway. It announced big fourth project in Africa, according to Thakkar.
Its investments in Africa would‘ve toped $272m by the end of 2008.
According to Dar Property (2012),Tanzania‘s housing market has every indicator that
needs immediate review before the country‘s economy is ruined19
. The never ending
rising trend in the land and housing sectors are not going to reach stratosphere before
they crumbles. Most built houses and land are increasingly becoming untouchable for
the poor majority as their talks are in US Dollars and exceedingly expensive. Housing as
it seems to be basic factor worldwide, in Tanzania it is so, but more to that is a great
pride and hallowed asset. Many decent houses in the city charges from $1500 to $16,000
per month, far more expensive than Florida‘s exclusive West Palm Beach and other
wealthiest American and Canadian suburbs. One undeniable fact is that, Tanzania‘s
housing market is very young and disorganized and thus vulnerable to withstand serious
economic and political shock.This tendency of artificially pricing of houses has
somehow blended into the real economy, producingunusual ‗soup‘ of economic life
18
Property Wire, (2008). Opportunity coming out of Africa, developer predicts. Retrieved 14th February 2014 from
World Wide Web: http://www.propertywire.com/news/africa/opportunity-africa-200808021411.html
19
Mashaka,J.(2012). Tanzania's artificial housing market, how long it hold? Dar Property Co. Retrieved 14th February
2014 from World Wide Web: http://www.darproperty.co.tz/article/readArticle/4
43
cycle which is hardly unpredictable and we can be sure when it crumble will take the
entire economy to dust, bringing the importance of all stakeholders to take this research
seriously.The housing market is ignoring the obvious economic factors that dictate
housing prices; income distribution, market demand and competition, economic
conditions, and government of the day’s actions and policies. Housing brokers (Dalalis)
are also a big influence in the negatively rising of prices. They have no training or
knowledge on how housing market forces interplay can be justified in alignment to their
prices. They are perfect silent bubble blowers who inflate the real-estate/housing bubble
right at us.
It is claimed that only 3 per cent of the population in Sub-Saharan Africa currently have
income levels adequate to qualify for mortgages, which often come with interest rates as
high as 15%but this pace will soon change with high expectation in Tanzania economic
improvement. Thus putting us in radar of high construction activities, which means high
trading prices at certain point. The Government of Tanzania is pursuing a policy of
tackling the housing shortfall by working in partnership with the private sector and
through the National Housing Corporation to stimulate the supply of housing and access
to finance for borrowers. Business Times (2012) reported the debt market in Tanzania
keeps growing, as more financial institutions joins the mortgage lending pack that aims
at raising the profile of house ownership in the country. A debt market is a forum for
trading debt securities; involving corporate bonds, government bonds, municipal bonds,
negotiable certificates of deposit, and various other money market instruments.
A growing debt market would help the development of a longer-term yield curve.
Creating such investment pools of mortgage lending facilities is good news – especially
when the financial markets are reeling from the persisting global credit crunch. This is
beneficial to Tanzanians who have had to work on rigged finance spending plans to raise
additional money with which to live their collective dream of being the proud owners of
their own homes. Over three years, home ownership demand in the local market has
44
been underserved. This is despite the fact that there is a huge deficit of between two-
and-three million housing units in the market – with the shortfall increasing each year
[reported in 2012].20Mortgage lending facilities in Tanzania were severed in the 1980s
after the Tanzania Housing Bank (THB) went under due to a burden of non-performing
debts!
Business Times (2013) informed over the state of construction industry in Tanzania that,
there are observed construction of multi storey buildings mushrooming in big towns and
cities like Dar es salaam, Mbeya, Arusha, Mwanza, Moshi, Iringa, Dodoma, and Tanga.
The Guardian on Sunday (2013) reported that, living and doing business in Dar es
Salaam, is challenging due to high rents for both human shelter and business. A random
survey conducted in elite suburbs, among both middle and low-income earners, Dar es
Salaam is more expensive than Nairobi and Johannesburg. This is due to shortage of
housing which currently stands at a mere three million units. According to National
Housing Corporation(NHC), Tanzania runs a housing deficit estimated at 3 million units
valued at $180 billion by the end of 2007, while the current annual demand for houses in
urban areas is 200,000 units estimated to cost $12 billion. The deficit it was expected to
grow by 15 percent by the end of 2012 due to high migration of people from rural to
urban areas.21
But perhaps the most striking fact is that only one percent ($50million) of
the total loans issued by the banks in Tanzania is set aside for financing homes, putting
many future home owners at the crossroads. For instance, monthly rates for a two-
bedroom fully furnished apartment located at elite suburbs like Masaki, Mikocheni and
Oyster Bay range between $2000 and $4000, while the same cost an average of $2500 in
20
Mnubi, L.(2012). Tanzania: as the debt market keeps growing. Business Times. Retrieved 14th February 2014 from
World Wide Web: http://www.businesstimes.co.tz/index.php?option=com_content&view=article&id=1978:tanzania-
as-the-debt-market-keeps-growing&catid=1:latest-news&Itemid=57
21
Onyango, E.(2013). Dar`s rent nightmare. IPP Media (The Guardian on Sunday). Retrieved 15th
February 2014 from World Wide Web: http://www.ippmedia.com/frontend/?l=51859
45
Nairobi. In Kampala the same cost an average of $2200 while in Kigali it costs an
average of $1800. For a family house with three bedrooms located in Dar‘s posh
suburbs, it costs between $3000 and $4000, payable in one year period or six months to
those tenants who are lucky. The same would cost an average of $2700 per month in
Nairobi, and in Kampala an average of $2500, according to data gathered by the
Guardian on Sunday
In terms of office and commercial space, though, there has been a mushrooming of
skyscrapers in Dar es Salaam, Mwanza and Arusha, but the rent charged by landlords
has grown by 25 per cent during the past three years. According to reports by The South
African Property Owners Association (SAPOA) and Investment Property Databank
(IPD) released in 2012 the prime office properties in Johannesburg locations including
Illovo, Melrose/Waverley, Rosebank and Sandton and environs cost an average of $28
per square metres. Due to the increased scarcity of the office spaces however, some
residential flats in prime areas of Dar es Salaam have been converted to commercial
properties This is happening because offices are scarce in the city‘s central business
district (CBD) in downtown Dar es Salaam, this is an aspect which has forced many
people to look for offices in the city‘s outskirts.
It has been noticed whenever the Tanzania Electricity Supply Company (TANESCO)
rises the cost of their utility, owners of houses also finds anexcuse to raise the cost of
their houses. If one investigates backwards as to why TANESCO raises their prices
you‘ll be shocked to learn because this power producer company struggles with
mountain of debt and system losses. As at January 2014, Energy and Water Utilities
Regulatory Authority (EWURA) announced new power tariffs, which are 40 per cent
increase. This not only touches the real-estate and housing sector, but entire construction
industry. In fact, economists say price hikes of key commodities particularly foodstuffs
such as rice, flour, sugar and milk will fuel inflation, currently at around 5.6 per
46
cent.22
Under the new tariffs, domestic consumers are paying TZS 100 or USD0.065 per
unit, up from TZS 60 or USD 0.039. Large domestic consumers and small business
operators are paying TZS 306 or USD 0.199 per unit up from TZS 221 or USD 0.144
(The East African Times, 1st February 2014). We should expect this 40% increase in
price to be pushed tofinal consumers from businesses (real estate are not exception in the
trend as it seems). In a big way to see how the monetary and fiscal policy affects the
Tanzanians we can refer to a letter of intent to IMF in June 2013, when the state said it
‗would limit subsidies to TANESCO to 105 million USD (this is about TZS 200 billion)
in the 2013/14 financial year against the company‘s projected financial needs of 352
million USD (over TZS 560 billion).23
It is this that has pushed TANESCO to rise tariff,
but we also see the hand of a government interplay in all this to influence the power
costs. According to World Bank estimates, TANESCO‘s arrears have jumped from 270
million USD as at the end of 2012 to about 500 million USD, with the figure said to be
growing at 30 million USD monthly.
It is clearly, monetary policy is crawling beneath and influencing the value and figures
indirectly and we breathe the effects directly.It has been learned that a house is hired at
between TZS 300,000 and TZS500,000 per month for middle class people and a single
room is hired at between TZS 30,000 and TZS 80,000 in various parts of the city
suburbs which shelter the low-income earners or over 60 percent of Dar‘s population.
Interests rates, which is the cost of borrowing, stand between $17 and 20 percent
depending on whether the borrower borrowed in US dollars or local currency. As a
result, currently the mortgage sector‘s contribution to Tanzania‘s Gross Domestic
22 Ihucha, A (1
st February 2014). Consumers to dig deeper into their pockets as TANESCO raises tariffs.
The East African. Retrieved 5th
March 2014 from World Wide Web:
http://www.theeastafrican.co.ke/business/Costly-power-as-Tanesco-raises-tariffs-/-/2560/2169138/-
/wdb61kz/-/index.html
23 Daily News (5
th July 2013). Power consumers to pay more as TANESCO seeks tariff hike. Daily News
retrieved 5th
March 2014 from World Wide Web: http://dailynews.co.tz/index.php/biz/19480-power-
consumers-to-pay-more-as-tanesco-seeks-tariff-hike?device=desktop
47
Product is below 1 percent, while Kenya it contributes about 7 per cent. In South Africa
the mortgage contribute about 25 per cent of the GDP, while in the United States it
equates 75 per cent and in Europe its contribution stands at 25 percent. High interests
rates makes borrowing a threat, moreover the conditions are also very high to an extent
majority cannot afford. This makes housing in Tanzania a Pandora kind-of thing to
solve.
According to Tanzania Chamber of Minerals and Energy (2014), Tanzania is the 4th
largest gold producer in Africa after South Africa, Ghana and Mali. Gold production
currently stands at roughly 40 tonnes a year, copper at 2980 tonnes, silver at 10 tonnes
and diamond at 112670 carats. In total the mining sector contributes 2.8% to GDP each
year but this could rise considerably in future years, with Business Monitor International
(BMI) forecasting average annual growth in the sector of 7.7% between 2011 and 2015.
BMI also predict a doubling in value of the sector between 2010 and 2015, from
US$0.64bn to US$1.28bn.24 It is for this reason, construction sector is believed to
expand in Africa, Tanzania among them to give way to accommodate investors, workers
and increase national wealth to afford expanding the housing projects.Business Times
(08 October 2010), reported, developers of commercial and residential housing schemes
in the world of real estate in Tanzania are expected to spend more on some building
materials, following an imminent rise in retail prices. Because most of construction
materials were expected to increase by almost five per cent, it has forced consumers to
dig deeper in their pockets to finance ongoing and proposed construction works. The
state of the construction industry will affect most common measures of the national
24 Tanzania Chamber of Minerals and Energy (2014). State of Mining Sector in Tanzania. Retrieved 15
th
February 2014 from World Wide Web: http://www.tcme.or.tz/mining-in-tanzania/industry-overview/
48
economy like the Gross Domestic Product (GDP), capital and other decisions that the
government makes and even the social health of the country.25
2.2.7 Relationship between monetary policy, economic bubble and real
Estate/Housing Market
The recent asset bubble crisis started in 2007 was a biggest bubble in history.26Real
estate bubbles are invariably followed by severe price decreases that result in many
owners holding mortgages that exceed the value of their homes. As of the end of 2010,
11.1 million residential properties, or 23.1% of all U.S. homes, were in negative equity
at Dec. 31, 2010.27This circumstance has made banks become less willing to hold large
amounts of property backed debt.A real estate bubble or property bubble (or housing
bubble for residential markets) is a type of economic bubble that occurs periodically in
local or global real estate markets. It can be identified through rapid increases in
valuations of real property such as housing until they reach unsustainable levels and then
decline. The questions of whether real estate bubbles can be identified and prevented
and whether they have broader macroeconomic significance are answered differently by
schools of economic thought.
The financial crisis of 2007–2012 was related to the bursting of real estate bubbles
around the world, which had begun during the 2000s. Bubbles in housing markets are
more critical than stock market bubbles. Historically, equity price busts occur on
average every 13 years, lasts for 2.5 years, and result in about 4 percent loss in GDP.
25
Mrindoko, S. (2013). Tanzania: High Prices On Materials Cripple Construction Sector (7th
February
2012). All Africa. Retrieved 15th
February 2014 from World Wide Web:
http://allafrica.com/stories/201202070768.html
26
The Economist (16th
June 2005). The Global Housing Boom. Retrieved 15th
February 2014 from World
Wide Web: http://www.economist.com/opinion/displaystory.cfm?story_id=4079027
27
Philyaw, Jason. Underwater mortgages back above 11 million in 4Q. CoreLogic.
49
Housing price busts are less frequent, but last nearly twice as long and lead to output
losses that are twice as large (IMF World Economic Outlook, 2003). As of 2007, real
estate bubbles had existed in the recent past or were widely believed to still exist in
many parts of the world,28especially in Australia, Austria, the United States, Malta,
Argentina,29Brazil, Britain, Italy, Denmark, Iceland, Israel, Canada, New Zealand,
Ireland, Spain, France, Luxembourg, Poland,30Greece, Bulgaria, Croatia,31Norway,
Singapore, Hong Kong, Ukraine and China.32
The Institute of International Finance (IIF) in Washington estimates private net capital
flows to emerging economies in 2010 at US$ 908 billion, 50 per cent higher than in
2009. And it anticipates a further rise in private capital movements to emerging
economies to US$ 960 billion in 2011 and US$ 1,009 billion in 2012.33 At local levels,
developing nations due to the low capital base of indigenous private investors to venture
real estate developments they make effort to use national resources to develop housing
28
Putland, Gavin R. (June 1, 2009). From the subprime to the terrigenous: Recession begins at home.
Land Values Research Group. Retrieved 21st February 2014 from World Wide
Web:http://lvrg.org.au/blog/2009/06/from-subprime-to-terrigenous-recession.html
29
Global Property Guide. The good times are here again (28th
February 2008). Retrieved 21st February
2014 from World Wide Web: http://www.globalpropertyguide.com/Latin-America/Argentina/Price-
History
30
Global Property Guide. The end of Poland‘s house price boom (25th
August 2008). Retrieved 21st
February 2014 from World Wide Web: http://www.globalpropertyguide.com/Europe/Poland/Price-History
31
Global Property Guide. Real estate prices in Adriatic Coast up, Zagreb down (19th
August 2008).
Retrieved 21st February 2014 from World Wide Web:
http://www.globalpropertyguide.com/Europe/Croatia/Price-History
32
Global Property Guide. Looming housing slump in China (1st September 2008). Retrieved 21
st February
2014 from World Wide Web: http://www.globalpropertyguide.com/Asia/China/Price-History
33
Volz, U. (2011). Capital flows to emerging economies: prelude to the next crisis? German Development
Institute / Deutsches Institut für Entwicklungspolitik (DIE) (The current column of 2 May 2011)
50
for its citizens. Tanzania government for instance has committed itself in Kigamboni
City Project in three phases; 2012-2022, 2022-2027 and 2027-2032. The project is
expected to cost about TZS 11.6 trillion upon completion in year 2032 (The East
African, 12th
July 2012). In 2012, the government of Tanzania had already set aside TZS
60 billion on its first phase; for conducting property assessment, social services,
resettling residents and measuring and drawing maps for the proposed Kigamboni town.
The amount was about 59 per cent of a ministry for Lands, Housing and Human
Settlements Development proposed TZS 101.731 billion budget for the 2012/2013
financial year.
While most industrialised countries continue to struggle with the aftermath of the global
financial crisis, the economies of many developing and emerging countries are again
experiencing strong growth. The International Monetary Fund (IMF) estimated that the
industrialised countries would grow by 2.4 per cent in 2011 and by 2.6 per cent in 2012;
whereas developing and emerging countries would grow by 6.5 per cent in both years. It
was even anticipated that the Asian developing and emerging countries would grow by
over 8 per cent in 2011 and 2012. These significantly improved growth prospects are
attracting investors, as are the strong fundamental data on most emerging economies,
positive interest rate differentials and expected revaluations of their currencies.
Expansive monetary policies pursued by most industrialised countries have resulted to
high global liquidity, which flowed not only to the international oil, raw materials and
food markets but also to the emerging and developing economies in search of returns
part of it being the real estate/housing investments. In such trends we also witness in
Tanzania pool funds such as NSSF financing the construction of the Kigamboni bridge
Project which links to a New Kigamboni City.NHC ambitious project by Tanzania
government, a township project (New Kigamboni City) a 60 acres to be established on
the intersection of major highway on the outskirt of Dar-es-salaam. This project will re-
define the housing market and real estate in Tanzania and shall change the Tanzania
scenery forever. Keep in mind also the consumers of foodstuffs are affected by monetary
51
strings interplay. This present an interesting observation for this research too and to
prove basis of its arguments. It is also made possible to observe the monetary tools in
relation to housing market since this project consumes a significant cake of national
resources making it visible in radar of economic variables.
Financial flows to emerging economies are dominated by portfolio investments in bond
markets, which have historically been particularly volatile. In contrast, direct
investments, which tend to be long-term in nature and to which the greatest development
effects are generally ascribed, are again on the decline. A problem foreseen fromthis
period of capital injection is that international capital flows may help bubbles to form. In
many emerging economies credit allocation fuelled by low real interest rates has already
led to a boom in capital markets and the real estate sector. Further external capital flows
may encourage the tendency for bubbles to form. The recent experience of such crisis-
hit countries as the US, Ireland and Spain, whose investment booms not so long ago
were similarly fuelled by external investments, should cause concern to a country like
Tanzania new capital flows.
Housing finance markets have been changing dramatically in both emerging and
developed economies (Chiquier and Lea, 2009).On the one hand, housing finance
markets are expanding and represent a powerful engine for economic growth in many
emerging economies. However, the unfolding sub-prime mortgage crisis highlights the
risks and potential turbulence that this sector can introduce into the financial system
when expanding without proper infrastructure and regulation. As housing finance keeps
growing in emerging economies to match a rising demand for housing, new risk
management approaches, business models, funding tools, and policy instruments are
advised to be on a rise too. Yet many questions remain about the right balance between
innovation and regulation, the extent of risks to the financial system, the appropriate role
of the state to promote affordable housing, and the effects of the sub-prime crisis. The
52
question is, how far can Tanzania policy makers go to take seriously the global
challenges facts, covert and accustom them to the local solutions?
Exploring the bubble emergence and monetary policies interplay, we can reach to an
understanding that governments need to have a methodology in tackling the speculative
tendencies in stock exchange, specific policy tools and improved if not institutionalize
mortgage plans. For the African governments like Tanzania, it goes further into taking
an advice to leave their Central Banks autonomous. Tanzania has not felt the real burst
of the bubble, the inflation is still mounting. If for the concern of a local bubble, the
burst will be probably felt in Dar es Salaam, a central business hub. In tune with that, we
should expect the rest of the country might calmly respond later; but in exceptional to
the growing regions – Mwanza, Arusha, Mbeya, Shinyanga and Iringa which may
respond parallel to timing as in Dar-es-salaam due to their interweave of various
business sectors. Discovery of the oil and gas in Mtwara and Lake Nyasa, have led to
development of local boom – as investors flood in for housing and exploration of
resources. Construction industry is booming in such regions, lands and housing prices
are ever increasing. Arusha has experienced a rise of land prices, and Dar es salaam is
expanding with land (housing) growing exponentially, as lately the residents build
houses to as far as Bunju, Mbweni and Bagamoyo. In Dar-es-salaam; Oysterbay, an
approximately 2400 sq. meter land is valued as much as TZS 1.6 billion shillings; in
Morocco (Kinondoni), a 650 sq. meter land = TZS 300-350 million shillings; Mbweni, a
600 sq. meter land = TZS 35 – 40 million shillings; and their values keeps on
increasing34
. Expansionary policies as introduced by the Central Bank of Tanzania in
good faith they are to foster promotion of trade and employment, however such policy in
our particular economy cannot ignore injecting inflation thus fuelling up the bubble. On
the other hand to prickle the bubble is not a good idea as there could be attempt to
abruptly restrain inflation but end up devastating the general economic atmosphere thus
34Unpublished Source.Data according to a researcher various and random inquiries to different sources
(formal and informal); 27th
November 2013)
53
distorting the investment confidence at present. Care should be taken thereof by
understanding that economic bubble are part of the ongoing economic activity, only
monetary instruments are to be balanced in controlling this phenomenon.
2.2.8 Monetary and Fiscal Policies of Tanzania in Assessment of Housing
Market/Real Estate
Most monetary policies in the world, Tanzania is not the exception, their models are
built into considering perfect financial markets. These policy models tend to ignore debt
catastrophe associated with real estate crashes, and thus keep on creating further rounds
of economic distortions in the particular economy. Globally, the annual value of the
construction industry is USD 1.5 Trillion, consisting about 8 per cent of the GDP and
about 60% of fixed capital formation, representing about 7 per cent of total employment
(Nguguna, H.B, 2008). In Tanzania, since 2003 the budgetary allocation for construction
sector has shown to be increasing. In 2011, Sub-Saharan Africa still had a strong
economic performance notwithstanding adverse supply shocks from drought, especially
in Eastern and Western Africa (Bank of Tanzania, June 2012). Global inflation was
generally high in 2011, driven mainly by rising commodity prices. In advance
economies, average inflation was 2.7 per cent compared to 1.5 per cent in the preceding
year, while in emerging and developing countries inflation was 7.1 per cent compared
with 6.1 per cent. Sub Saharan Africa stood at 8.2 per cent compared 7.4 per cent. In
Tanzania mainland, fiscal operations during July 2011 to April 2012 exhibited strong
revenue performance, surpassing recurrent expenditure by about11per cent (Bank of
Tanzania, June 2012). In 2011/12 monetary policy continued to focus maintaining
appropriate level of liquidity in support of the macroeconomic objectives of the
government. BOT aimed at achieving;
(i) Expansion of average reserve money to an annual rate of 19.0%
(ii) Annual growth of extended broad money supply (M3) not exceeding 19.0%
(iii) Annual growth of private sector credit of at least 20.8%
54
(iv) Accumulation of gross official reserves adequate to cover at least 4.5% months
of projected import of goods and services.
Economic growth in Tanzania remained strong in the first three quarters of 2012,
growing at 6.8 per cent compared with 6.3 per cent recorded in the corresponding period
of 2011 (Bank of Tanzania, February 2013). In year 2012, economic growth was strong
at 6.9 per cent compared to projected growth of 6.8 per cent and 6.4 per cent recorded in
2011. Now if you take such figures and link with the housing deficit in Tanzania, which
is about 3 million, units (growing at a rate of 200,000 units per annum) it is simple to
understand demand for housing has a certain tie to a monetary policy. Simply you can
start by asking if the monetary policy is relaxed and the fiscal policy is expanded
wouldn‘t it encourage the building and construction activities? If the inflation is high,
that is money circulation is high wouldn‘t people have money to undertake construction
activities (in a short-run)? The traditional view sees expansionary monetary policy as
raising asset prices as part of the transmission mechanism of monetary policy. It works
through the adjustment of the commodity‘s portfolio as agents substitute from cash to
government securities to corporate securities; to equities; to real estate; old masters and
commodities – eventually leading to overall inflation (Bardo and Lane, 2012). Urban
population of Tanzania has grown from 14.8 per cent in 1980 to 37.5 per cent in 2002
and it is expected to reach 46.8 per cent by 2015. By 2010, housing deficit in urban areas
was estimated at 1,100,000 units as against the annual supply of 15,000 units (UNESCO,
August 2010).
Annual growth of average reserve money in BOT was 11.2 per cent in April 2012,
against the target of 19.0 per cent for the year ending June 2012, while extended broad
money (M3) grew by 13.6 per cent compared with the target of 19.0 per cent.
Meanwhile private sector grew by 24.0 per cent exceeding the target of 20.8 per cent
with the most of credit held in personal activities, trade, manufacturing, agriculture, and
transport and communication activities. In 2012/13, the fiscal policy thrust was directed
55
towards implementing five year development plan, which aims at sustaining strong
growth and reduction of income poverty. Real GDP was projected to grow by 6.8 in
2012, supported by improvement in power supply, prospects of increase in foreign direct
investments and infrastructure developments. Inflation was expected to slow down to
single digit level, supported by prudent fiscal policy. In monetary policy of 2012/13,
BOT aimed to still maintain liquidity level in the economy. Among its objectives were;
(i) Obtaining annual growth of average reserve money not exceeding 16.0 per cent
(ii) Annual growth of extended broad money (M3) of 18.0 per cent
(iii) Annual growth of private sector credit of 20.0 per cent
(iv) Accumulation of gross official reserves adequate to cover at least 4.5 months of
projected imports of goods and services.
According to BOT report of Monetary Policy Statement, mid-year review –
February2013, it stated that it is pursuing a tight monetary policy, and this will be
sustained in 2013/14. However, with inflationary tendencies in the economy and smooth
booming of the housing/real estate, shouldn‘t we worry perhaps the monetary policy is
not tight enough? According to Kilindo, A.A.L et al, majority policy makers in Tanzania
(90 per cent) shows that are aware of the way monetary policy is conducted, 60 per cent
do express dissatisfaction with the conduct of monetary policy pointing out conflicting
objectives, crowding out of the private sector, and the lack of transparency.Changes in
governmental fiscal policy affect aggregate demand (GNP) both directly and indirectly
through a series of complex multiplier and feedback mechanisms. Changes in GNP may,
in turn, affect disposable personal income, income distribution, employment, and price
levels. Housing market is sensitive to these economic parameters. Fiscal policy
instruments available are revenue policies and expenditure policies. Therefore in the
case of an increase (decrease) in tax rates lead to decrease (increase) in GNP; which
have consequence in housing market behaviours (Naylor, T.H). For instance in the case
of revenue policies which determine: personal income, tax rates, corporate profit tax
rates, indirect business (excise) tax rates, and contribution to social insurance (Social
56
Security and Medicare); if government lowers these tax related areas housing market
will boom since people will have much income for development.
Policies whichtend to increase the supply of money available in the economy will lead to
reductions in interest rates. Lower interest rates stimulate consumption and investment.
Increased consumption and investment mean higher aggregate demand as well as
increased personal income and employment. In housing sense of market, lower interest
rates imply lower credit costs; and in theory, lower credit costs should stimulate the
demand for housing (Naylor, T.H). We have all learned the monetary policy available to
most Central Banks include; Open market purchase and sale of government securities;
changes in reserve requirements of member banks and changes in the interest rate
charged to member banks by a Central Bank
2.2.9 Extent of Monetary Policy in Precipitating Asset Bubble in Real
Estate/Housing Prices and what can Tanzania learn.
Confidence in combining inflation-targeting-cum-flexible-exchange-rate regimes with
isolated microprudential regulation as a means to guarantee both macroeconomic and
financial stability has been shattered by the scale and synchronization of asset price
booms and busts that preceded the current global financial crisis (Canuto and Cavari,
2013). Within mainstream economics, economic bubbles, and in particular real estate
bubbles, are not considered major concerns. Within some schools of heterodox
economics, by contrast, real estate bubbles are considered of critical importance and a
fundamental cause of financial crises and ensuing economic crises.
The pre-dominating economic perspective is that economic bubbles result in a temporary
boost in wealth and a redistribution of wealth. When prices increase, there is a positive
wealth effect (property owners feel richer and spend more), and when they decline, there
is a negative wealth effect (property owners feel poorer and spend less). These effects
can be smoothed by counter-cyclical monetary and fiscal policies. The ultimate effect on
57
owners who bought before the bubble formed and did not sell is zero. Those who bought
when low and sold high profited, whereas those who bought high and sold low (after the
bubble has burst) or held until the price fell lost money. In some schools of heterodox
economics, notably Austrian economics and Post-Keynesian economics, real estate
bubbles are seen as an example of credit bubbles because property owners generally use
borrowed money to purchase property, in the form of mortgages. These are then argued
to cause financial and hence economic crises. This is first argued empirically –
numerous real estate bubbles have been followed by economic slumps, and it is argued
that there is a cause-effect relationship between these. The Post-Keynesian theory of
debt deflation takes a demand-side view, arguing that property owners not only feel
richer but borrow to (i) consume against the increased value of their property – by taking
out a home equity line of credit, for instance; or (ii) speculate by buying property with
borrowed money in the expectation that it will rise in value. When the bubble bursts, the
value of the property decreases but not the level of debt. The burden of repaying or
defaulting on the loan depresses aggregate demand, it is argued, and constitutes the
proximate cause of the subsequent economic slump. Now, as Tanzania has opened the
doors of house mortgages, each should learn on such investment behaviours.
According to Landsman (2006), regulators need to consider how to let bank managers
reveal private information in their fair value estimates while minimising strategic
manipulation of model inputs to manage income and regulatory capital. Secondly,
regulators need to consider how best to minimise measurement error in fair values to
maximise their usefulness to investors and creditors when making investment decisions,
and to ensure bank managers have incentives to select investments that maximise
economic efficiency of the banking system. Third, cross-country institutional differences
are likely to play an important role in determining the effectiveness of using mark-to-
market accounting for financial reporting and bank regulation.The housing bust has led
58
to a persistent shortfall in aggregate demand, through a variety of channels.35The
problems in housing have affected the transmission of monetary policy.
A notable policy challenge is that the reduction in household and business demand has
pushed some nations (especially the industrialized) to the zero lower bound on the bank
rate. A range of monetary policy rules suggest that the target nominal funds rate should
have been substantially negative in recent years.36
Another challenge is that the monetary
transmission mechanism is partially clogged. Credit market frictions make refinancing
and other housing activity less responsive to changes in interest rates. Fortunately, the
monetary transmission mechanism doesn‘t work solely through its effects on housing or
even through balance sheets and collateral constraints more generally. Monetary policy
also affects the economy through wealth effects, household intertemporal substitution,
the user cost of capital generally, and exchange rates, among other mechanisms.37
In October 2011, the Central Bank of Tanzania raised the statutory minimum reserves
for commercial banks from 20 to 30 per cent. This is in an effort to mop up excess
liquidity (that is reducing money ‗quantity‘ in the economy). It also lowered the foreign
exchange net open position limit for banks from 20 to 10 per cent to curb speculative
trading. ―With inflation spiking higher, we believe that the Bank of Tanzania will begin
to tighten monetary policy over the coming months with particular focus on controlling
money supply via the repo market and open market operations,‖ says the BMI
report.38
―Because these are financed to a large extent by foreign money (in the form of
35
Williams, J.C. (2012). The Federal Reserve and the Economic Recovery. Presentation to the Bishop
Ranch Forum, San Ramon, CA, (8th
February 2012)
36
Rudebusch, G. (2009). The Fed‘s Monetary Policy Response to the Current Crisis. FRBSF Economic
Letter 2009-17 (22nd
May 2009)
37 Reifschneider, D., Robert T., Williams, J.C. (1999). Aggregate Disturbances, Monetary Policy, and the
Macroeconomy: The FRB/US perspective. Federal Reserve Bulletin (January 1999), pp. 1–19 38
Business Times. Tanzania: tighter monetary policy could slow down economic growth (23rd
December
2011). Retrieved 15th
February 2014 from World Wide Web:
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grants and loans), there is always the danger that a souring of relations with donor/lender
partners could impact upon Tanzania‘s balance of payments and fiscal positions — with
negative implications for macroeconomic stability,‖ the report concludes.
Regulatory instruments have long been understood to have a powerful effect on
investment, and part of the motivation for introducing higher-powered regulatory
regimes and contracts was to reduce incentives for inefficiency and over-investment
(gold plating) inherent in cost-plus regulatory schemes. In practice, the mix of incentives
and the institutional framework that make up a higher-powered regulatory regime can
also lead to unintended distortions on investment behaviour; such as for our case – real
estate/housing.Two good factors which are conducive to strong private sector credit
growth which ultimately lead to precipitate the bubble according to Hofrichter (2014)
are ‘linking a currency to hard currencies’, which leads to easy importing easy
monetary policy from the West; and ‘financial market deregulation’ - includes amongst
others, the liberalization of the credit market, the introduction of new financial
instruments as well as the opening up of the capital account, which facilitate the capital
inflows.
Micro, small and medium manufacturing enterprises gives a good picture in Tanzania, as
the growth of cluster-based, micro and small furniture-manufacturing firms such as
those located in the Keko, Buguruni-Malapa and Mbezi beach kwa Komba in Dar es
salaam have exposed the seriousness of the competition in furniture, with the
challenging prices but yet again competing with established firms. The rise in prices and
the consumer broad choices implies the expansion of this area.Tanzania seems to have
had informal construction sector and poor organization in the construction industry in
the past until recently we witness good improved laws to guide the local constructors.
http://www.businesstimes.co.tz/index.php?option=com_content&view=article&id=1614:-tanzania-tighter-
monetary-policy-could-slow-down-economic-growth&catid=1:latest-news&Itemid=57
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Yet the formal organization of this area has also witness the rise of the prices of
construction materials, and the prices have been shooting up since then, coupled with the
complication of recession and global oil prices.
Pool funds from NSSF and PPF and the rest of financial institutions are used to fund
major housing constructions.National Housing Corporation (NHC) is also implementing
its long reserved strategic plans, the speculation is building so strongly, that we observe
office space already full booked even before the end of construction; the apartments also
are fully booked before the final construction phase! Have you noticed how most
commercial building which are half completed and barely furnished in the construction
phases being already booked with clients signs? Indicators are ever becoming widely
convincing that now in Tanzania, especially with the under-review ‗land act‘ law(s)
plans with a court to arbitrate disputes would improve land administration and relations.
Undoubtedly this factor too it will speed up construction/housing sector too.
Sustainable Industrial Development Policy of Tanzania is focusing to take the nation by
2025 into a semi-industrialized so as this area may account for over 40% of the GDP.
This in mind there has been mushrooming of industrial activities, so we witness now
even the agricultural sector benefiting. Commodity prices are shooting up to raise every
possible ‗tip‘ of profit to be gained whether by the domestic market or foreign market.
The guardian news (December 2012) reported that coffee prices rose as reported by
Tanzania Coffee Board (TCB); benchmark grade AA sold at $ 147.00 - $ 170.20 per
bag. Grade A fetched $ 147.00 - $151.20. The cost of consumable are yet high than
historical prices (as at December 2012); averages prices milk (regular), 1 litre is
Tzs.1700.40; Loaf white bread (500g) – Tzs.1509.98; Rice (1kg) - Tzs. 2250; Eggs (12)
- Tzs. 3168; Oranges (1kg) - Tzs.2772; Tomato (1kg) - Tzs.6000; Water (1.5 litre bottle)
- Tzs.1500; Transportation: one way ticket (local transport) – Tzs.475.20; Gasoline (1
litre) – Tzs.2074.50; Taxi start (Normal tariff) - Tzs.3960. There are every signs the
inflation is persistent now, we cannot avoid it, and inside it the bubble is growing.
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2.2.10 Economic Bubble Prevention
The most agreed way of prevention of the bubble effect is for the government to bail the
businesses; in particular the central bank is to bail financial institutions. But again, by
‗bail-out‘ it means the bubble has already burst, so we are offering a medicine to a
patient and not a vaccine. It is widely debatable on how the asset bubble can be
prevented other than speculate as it is inflating.International lender of last resort is
another best way to rely to bail out the economy; as we have witnessed the Greece
economy in Europe being supported by European Union. International Monetary Fund
(IMF) and World Bank can act, and have acted in the past to support various economies.
In the 1990s, the United States performed the role of lender of last resort.
A good question is to ask ourselves what shall we do to prevent Tanzania from the asset
bubble hazardous effects in case we ‗reach‘ there? There are simple quick hints to
consider according to Financial Plan (2014);
(i) Buy a house that you can afford with a traditional mortgage where you make
principal and interest payments at a fixed interest rate.
(ii) Follow the rule of thumb that you should limit your housing costs (including
property taxes, principal and interest, and homeowners' insurance) to between
25% and 32% of your family's gross income.
(iii) Don't assume that your house will continue to appreciate at the fast pace that it
may have in recent years.
(iv) Don't buy a house whose price is artificially inflated just because you're afraid
you'll miss out on the opportunity to buy before prices go up yet again.
(v) Don't buy a house you can't really afford just because you think it's a good
investment. The more real estate prices rise, the less likely they'll continue to do
so. Eventually the bubble will burst, and you don't want to be caught in "bubble
trouble."
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(vi) Don't indulge in cash-back refinancing and use the equity in your home to buy
cars or boats, take vacations, or pay off debt (unless you're committed to
avoiding the spending habits that got you into debt in the first place). It could
come back to bite you if real estate values decline.
(vii) Don't purchase real estate with an interest-only loan if you can't afford the
property otherwise. These loans usually have adjustable interest rates, which
could make your payments unaffordable. Once the interest-only period ends and
you must start paying principal as well as interest, you may not be able to make
the payments and could be forced to sell the property at a loss.
(viii) Choose a modest home in a good neighbourhood rather than buying a home
larger or fancier than you need or a bigger home in a less desirable
neighbourhood.
(ix) Avoid buying a house in an area that has appreciated well above the average rate
of appreciation in that area over the past few years.
(x) The bottom line: don't panic about a potential real estate bubble, but exercise
caution and good financial judgment when buying real estate, choosing your
mortgage type, and taking equity out of your home.
An average Tanzanian citizen should stop buying lands recklessly in anticipation of the
value to rise (since this is a pre-requisite of land bubble inflation). We should also stop
worrying missing opportunities associated with land appreciated value. You could be the
land ‗greater fool‘ to ever push that price/cost to another ‗greater-fool‘ to buy that land;
and thus get stuck to a deteriorated high purchased value of asset in the midst of land
bubble burst. This is in line one should avoid buying lands which seems expensive than
ordinary; and thereby also avoid taking loans to buy such lands – could end with
unmanageable debt. The Tanzanian government should control land valuations and
pricing through their authorities like municipals. At the moment local governments are
selling great chunks of lands; what is the valuation and pricing criteria being used? The
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answer can help to decide if the government is up to task to tackle real estate bubble in
Tanzania.
Tanzania has had a glance from a distance from the monetary policy strategies employed
by the US Federal reserve – ‗The Jackson Hole Consensus‘, which favoured an
asymmetric approach responding to asset price bubbles. This tactic is nowbeing
challenged by the global financial crisis;the Tanzania‘s economists should take caution
on more serious approaches. This brings to mind that more strategies need to be
developed especially with the presence of concurrent bubbles in the housing and the
stock market. Macropudential regulation can be helpful if the policy makers in Tanzania
can design the framework in the context of our economy, instead of administering a
general pain-killer like interest rates regulations.
There is still much to learn over the full characteristics of asset bubbles, for example
why do they form, why do they burst and who benefits from sharp price increases? All
we have is a bunch of collected conflicting theories, not a bad start but need to work
hard! It is well understood that Tanzania has linked its currency (TZS) to hard currency
like USD which undoubtedly lead us to experience the effects of ‗Wall-Streets‘ and
recent ‗Oil Shocks‘ among others. Tanzania scholars should now question is there a way
out of this or we are stuck forever? Financial market deregulation’ - includes amongst
others, the liberalization of the credit market, the introduction of new financial
instruments as well as the opening up of the capital account, which facilitate the capital
inflows is another area that Central Bank of Tanzania should investigate and highly
regulate if we are to combat the asset bubble of housing market.
While some asset prices may look high in the developed world, broadly speaking we
cannot always characterize them as bubbles: valuations may not be stretched enough and
private sector leverage at times shows signs of decline, not rise. In the emerging world,
notably in Asia, the rise in credit is a cause of concern, but again, with very few
exceptions (notably real estate in Hong Kong), we find prices for liquid assets still to be
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in line with fundamentals. Nevertheless, given the ongoing monetary policy support, we
have to continue to watch out for potential bubbles – globally. If the politicians in
Tanzania can discipline themselves not to meddle the monetary policies and regulations
with politics we have hope to stand on a winning side, when the asset bubble are nearing
their burst. It is thus not a matter of debate that Central Bank of Tanzania is to be
autonomous in all the way of its functioning – it should be indeed independent.
There should be strict emphasize towards ethical attitude of Dar-es-salaam Stock
Exchange Market (DSE) conducts to discourage the unnecessary price speculation of
shares – from stock broker. A very important element of price inflation is the local land
brokers ‗dalali‘ whose operations seems to be unlimited and unmonitored by the
government‘s ‗eye‘. ‗Dalalis‘ at local level have contributed in price hike in Dar-es-
salaam housing market, especially in ‗rents‘; thus government need to see this through.
Land and Housing Authorities should explain to the public steps they have taken, or
plans they have in place to contain or control this vital sector from institutions, firms or
individuals. Housing brokers (Dalalis) have no training or knowledge on how housing
markets are to be integrated to a local economy to justify their prices. Dalalis are
beautiful unrecognized agents at the blowing part of a bubble who slowly inflates it.
Yet even with literature knowledge of bubble remedy the strangest partis inability to
eliminate it, as one can argue if it is created then can be destroyed. We call this punching
of a bubble. Normally, by pricking (punching) of the bubble means aggressively
responding to the inflating tendency of a bubble. Central Bank may raise up the bank
rates at a very high level, which in-turn the commercial banks shifts that burden to the
consumers who will hardly manage to conduct business (less lending). The exceedingly
high interests means then tougher loan and interests rates to debtors (borrowers). Since
this is normally a time accompanied by inflation and not necessarily a favourable
employment landscape citizens may be hurt more by this move of stinging a bubble. It is
right to say in a moderate inflation (rising of prices) businesses may be in good hands
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and in a short-term livelihood of citizens are better-off. In a long-run it is where
devastation happens, particular in asset bubble like real-estate; why? Because nobody
knows in this transitionary period of rise of prices how long prices should be left rising,
and this is what in the end we are shocked nobody can buy or rent a particular house
and cripple the market system!
2.3 Knowledge Gap
A bubble dominance is in stock market and real estate, as far as global economic
diagnose is concerned. In the large industrial economies stock markets and real estate
have a strong economic string, and thus with the onset on wall street market collapse in
2007/2008 these two giant sectors suffered most in US and in the rest of major
economies. Developing nations like Tanzania cannot completely ignore the major
effects; the waves were felt and dragged most of the dependent economies to shock
especially after lacking market for the export of raw agricultural produce. Tanzania
depends for as much as 80% income contribution from export of its raw materials, hence
this is enough to give insight how the nation was affected. In a developing nation it is
still primitive to analyse bubble in the context of stock and real estate in the same boat
with the major industrial economies; but we can analyse through commodities prices and
other economic variables which attach to these sectors. But why being naïve to venture
the real estate/housing sector in a country like Tanzania and investigate the signs, and go
further to look the entire construction industry? We hear so much from the industrial
nations about financial stress in association with bubbles and depression because stock
market and real estate/housing is enormously advanced in such economies. This explains
why they were hit hard; wouldn‘t it be so even statistics, first hand news and even
‗gossip‘ would start there? Researcher believes even in Tanzania, no matter how small
real estate/housing sector is, bubble at local level are precipitating.
We can assume even if the bubble burst (of Tanzania origin) may not lead to a
connected global economy crush like for the case of United States in 2007/2008. But,
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understanding ‗it‘ would lead to a better economy design in Tanzania and the rest of
developing nations. Since most of developing nations economies are similarly tied
together, with more or less same fiscal and monetary instruments styles/designs, this
study can be used to help neighbouring nations too. Tanzania, like rest of developing
nations‘ bubbles are not clearly explained by international scholars; thus researcher aims
to draw that line and be the fore-runner in explaining the bubble phenomenon, accounts
for the rise and provide remedies in Tanzanian context.
2.4 Conceptual Framework
Figure 2.10 : Conceptual Framework
Source: Researcher 2014
Any framework expresses the system direction or rather the illustrative way a researcher
is looking at a way of going throughout his research work. This model clearly stipulates
CONCEPTUAL FRAMEWORK
Independent Variable
Dependent Variable
[A] General Monetary Policy Tools (i) Bank rate changes (ii) Reserve requirements
Old-age monetary policies (iii) Discount
rate (iv) Moral suasion
[B] Specific tools (Macroprudential regulation) (i) Credit market controls (ii) Changes in stock market margin requirements (iii) A time varying bank capital ratio
Recommended new
Indirect agents (iv) Maintaining of a credit to -
GDP ratio monetary policies
of asset bubble (v) Supervisory
discretion Real Estate/
Economic Bubble Housing Market
Price (Real Estate Asset Bubble) [C] Financial Market
Deregulation (i) Liberalization of credit market (ii) Introduction of new financial instrument
New open market policies (iii) Opening of capital
account (iv) Policies of land and housing authorities
[D] Other miscellaneous (i) Tie local currency to hard currency (ii) Non-autonomous of Central Bank of Tanzania
Self imposed conditions (iii) Artificial pricing tendency of
local market Direct agents (iv) Dalali (house-brokers) pricey
behaviours of asset bubble
INPUT
PROCESS
OUTPUT
CENTRAL BANK AND REAL ESTATE MARKET IN TANZANIA
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three zones of a framework; the input (policy tools); the process (area being acted upon
by the injected decisions of policies = real estate/housing market); and the output - the
product of interaction between the policies and the asset in the market (economic
bubble). A good research indisputably shows the variables involved and their resultant
effects upon each other. Independent variable is the ‗monetary policy‘ and a
dependent variable is a ‗real estate‘. Not all agents which influence a bubble inflation
are monetary origin like the part C – ‗financial market deregulation‘ and part D – ‗other
miscellaneous‘. If the tools and policies are positively or rather correctly ‗introduced‘ in
the economy stream we can expect good fruits such as: stable prices of premise and
house rents costs, stable prices of construction materials, affordable houses purchase and
reliable mortgage plans.
If such policies and tools are negatively injected into the stream of economy (or if
something else is manipulated negatively other than monetary policy) we expect the
negative turn of events such as: high rent costs, high construction material costs,
unaffordable prices of houses and unreliable mortgage loans to the population.
Tanzania is not yet clearly if it is in an era of administering macro/microprudential
regulation in a positive way to tackle economy issues. Policy makers should consider
this advice among tools for solution. The local economy is again tied to industrial
nations economy hence we are swinged in a wind of global monetary policies even by
locally administering corrective measures. This research will look into measures to make
Tanzania‘s economy independent and yet adaptable to international shares of policies
set-up and constant shocks.
2.5 Hypotheses
The research hypothesis was constructed out of ‗null-hypothesis‘ since the null-
hypothesis relates to the statement being tested, whereas the ‗alternative hypothesis‘
relates to the statement to be accepted if / when the null is rejected [as normal research
standard practice].
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Hypothesis;
Ho = When BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices
Ho = The low interest rate charged to commercial banks and other depository institutions
on loans they receive from BoT encourage high money supply resulting into inflationary
tendencies giving negative effect in housing market prices
Ho = Due to high cut throat competition in the banking and financial sector in general,
persuading a certain regulation without rigid laws and penalty has proven ineffective in
Tanzania.
Ho = It is logical when total volume of credit is controlled in the economy by the Central
Bank of Tanzania
Ho = BoT control capital flow with prudential purposes.
Ho = The Central Bank and where possible government should intervene aggressively to
the institution(s) which possess a threat as a forerunner in accumulating and inflating
real estate/house prices.
CHAPTER THREE
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STATISTICS, COMPUTATION AND DESIGN OF A RESEARCH PROBLEM
3.1 Introduction: Research Methodology
This chapter mainly explains the methodological choices, and steps followed by the
researcher in collection of data and the ultimate testing of the hypothesis as expressed
earlier. Research methodology refers to a systematic, theoretical analysis of the methods
applied to a field of study; typically, it encompasses concepts such as paradigm,
theoretical model, phases and quantitative or qualitative techniques.
3.2 Conceptual Definition
3.2.1 Asset Bubble
An economic development in which the price of a class of physical or financial assets
(such as houses or securities) rises to a level that appears to be unsustainable and well
above the assets' value as determined by economic fundamentals.
3.2.2 Austrian Economic(s):
Is a school of economic thought which bases its analysis on the purposeful actions of
individuals. It originated in late-19th and early-20th century Vienna with the work of
Carl Menger, Eugen von Böhm-Bawerk, Friedrich von Wieser, and others.
3.2.3 Bail (bail out):
A bailout is a colloquial term for giving a loan to a company or country which faces
serious financial difficulty or bankruptcy. It is a provision of financial help
or liquidity to a corporation that otherwise would be on the brink of failure
or bankruptcy. A bailout might be performed for the benefit of the
one providing the monetary aid (someone who bails out a struggling company in order
to gain control of that company), or simply for the benefit of the company and anyone
who consumes the goods or services offered by that company.
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3.2.4 Bond (Government Bond)
In finance, a bond is an instrument of indebtedness of the bond issuer to the holders. It is
a debt security, under which the issuer owes the holders a debt and, depending on the
terms of the bond, is obliged to pay them interest (the coupon) and/or to repay the
principal at a later date, termed the maturity date.A government bond is a bond issued by
a national government, generally with a promise to pay periodic interest payments and to
repay the face value on the maturity date. Government bonds are usually denominated in
the country's own currency. Bonds issued by national governments in foreign currencies
are normally referred to as "sovereign bonds"
3.2.5 Boom (Economic):
An economic boom is a period characterised by an increase in output and rapid
economic growth. In the boom-bust cycle, the boom is the period accompanied by an
increase in the sales of a commodity or product and a resultant rise in the economy
3.2.6 Borrowing
Is receiving something in exchange for an obligation to return it or give something else
of usually greater value at a particular time in future.
3.2.7 Budget
An estimate of income and expenditure for a set period of time.
3.2.8 Construction Industry
Sector of national economy engaged in preparation of land and construction, alteration,
and repair of buildings, structures, and other real estate property.
3.2.9 Contractors
As used in this research refers to one responsible for the day-to-day oversight of a
construction site, management of vendors and trades, and communication of information
to involved parties throughout the course of a building project
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3.2.10 Credit Market
A marketplace for the exchange of debt securities and short-term commercial paper.
Companies and the government are able to raise funds by allowing investors to purchase
these debt securities.
3.2.11 Crush (bubble, Economy)
A period where the bubble burst and economy is shattered at its knees.
3.2.12 Currency Board
A monetary authority which is required to maintain a fixed exchange rate with a foreign
currency. This policy objective requires the conventional objectives of a central bank to
be subordinated to the exchange rate target.
3.2.13 Debt
A debt is an obligation owed by one party (debtor) to a second party, the creditor.
3.2.14 Deregulation
Is the act or process of removing or reducing state regulations.
3.2.15 Dollarization
Is the adoption of a foreign country‘s currency as a legal tender for monetary
transactions.
3.2.16 Economic Bubble
Is a trade in high volumes at prices that are considerably at variance with intrinsic
values.
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3.2.17 Economic Crisis
Negative GDP growth lasting two or more quarters which brings recession, and when it
is prolonged brings depression; and while a long period of slow growth lead to economic
stagnation. This is normally caused by the financial crisis (see the meaning below)
3.2.18 Expenditure
The act of spending funds; disbursement, consumption. It is amount of money spent on
something.
3.2.19 Financial Crisis
A situation in which the value of financial institutions or assets drops rapidly. It is
usually associated with a panic or a run on the banks, in which investors sell off assets or
withdraw money from savings accounts with the expectation that the value of those
assets will drop if they remain at a financial institution.
3.2.20 Financial Institution(s)
An establishment that focuses on dealing with financial transactions, such as
investments, loans and deposits.
3.2.21 Financial Market
Is a market in which people and entities can trade financial securities, commodities, and
other fungible items of value at low transaction cost and at prices that reflect supply and
demand. Securities include stocks and bonds, and commodities include precious metals
or agricultural goods.
3.2.22 Financial Year
It is also known as fiscal year or budget year. Is a period used for calculating
annual/yearly financial statements in businesses and other organizations. In Tanzania
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fiscal year is 1st July, where accounting and taxation reports are presented to the
parliament.
3.2.23 Fiscal Policy
Is the use of government revenue collection (taxation) and expenditure (spending) to
influence the economy.
3.2.24 Government
A system by which a state or community is governed.
3.2.25 Greater Fool (Theory)
The greater theory states that the price of an object is determined not by its intrinsic
value, but rather by the often irrational beliefs and expectations of market participant.
Therefore, a price is justified by a rational buyer under the belief that another party is
willing to pay an even higher price. It is why it is stated, one expects an asset can be
resold to a ‗greater fool‘ later on.
3.2.26 Heterodox Economic(s)
Refers to methodologies or schools of economic thought that are considered outside of
‗mainstream economics‘, often represented by expositors as contrasting with or going
beyond neoclassical economics.
3.2.27 Housing Bubble
refers to ever rising prices of real estates/houses which reach the point no one can afford
to buy such asset then the economy shatters into pieces.
3.2.28 Housing Market
Is the four interrelated submarkets; (i) newly constructed single – family houses not yet
sold or occupied, (ii) new rental units, (iii) previously occupied units being offered for
resale, and (iv) previously occupied units offered for rent (Maisel, 1963).
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3.2.29 Income
Is the consumption and savings opportunity gained by an entity within a specified
timeframe, which is generally expressed in monetary terms. For household and
individuals, income is the sum of all the wages, salaries, profits, interests payments,
rents and other forms of earnings received in a given period of time.
3.2.30 Inflation
A sustained increase in the general price level of goods and services in an economy over
a period of time. As the general price level rises, each unit of currency buys fewer goods
and services; reducing the purchasing power per unit of money – a loss of real value in
the medium of exchange and unit of account within the economy.
3.2.31 Infrastructure
A basic physical and organizational structure needed for the operation of a society or
enterprise or reproductive system or the services and facilities necessary for an economy
to function. Thereby it is a set of interconnected structural elements that provide
framework supporting an entire structure of development.
3.2.32 Intrinsic Value (Finance)
Also known as fundamental value. It refers to the value of a company, stock, currency or
product determined through fundamental analysis without reference to its market value.
It is ordinarily calculated by summing the discounted future income generated by the
asset to obtain the present value.
3.2.33 Investment (finance)
An asset or item that is purchased with the hope that it will generate income or
appreciate in the future. Economically, an investment is the purchase of goods that are
not consumed today but are used in the future to create wealth.
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3.2.34 Jackson Hole Consensus
An annual symposium (conference) sponsored by the Federal Reserve Bank of Kansas
City since 1978, and held in Jackson Hole, Wyoming, since 1981. The symposium
focuses on an important economic issue that faces U.S. and world economies.
Participants include prominent central bankers and finance ministers, as well as
academic luminaries and leading financial market players from around the world. The
Symposium proceedings are closely followed by market participants, as unexpected
remarks emanating from the heavyweights at the Symposium have the potential to affect
global stock and currency markets.
(Investopedia [2014]. Jackson Hole Economic Symposium. Retrieved 9th April 2014
from World Wide Web: http://www.investopedia.com/terms/j/jackson-hole-
symposium.asp)
3.2.35 Keynesian Economic(s)
Is the view that in the short run, especially during recessions, economic output is
strongly influenced by aggregate demand (total spending in the economy).
3.2.36 Lending
To give or allow the use of temporarily on the condition that the same or its equivalent
will be returned.
3.2.37 Liquidity Trap
Is a situation described in Keynesian economics in which injections of cash into the
private banking system by a central bank fail to lower interest rates and hence make
monetary policy ineffective. It is caused when people hoard cash because they expect an
adverse event such as deflation, insufficient aggregate demand, or war. Common
characteristics of a liquidity trap are interest rates that are close to zero and fluctuations
in the money supply that fail to translate into fluctuations in price levels.
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3.2.38 Liquidity
The degree to which an asset or security can be bought or sold in the market without
affecting the asset‘s price.
3.2.39 Macroeconomic
The field of economics that studies the behaviour of the aggregate economy.
3.2.40 Macroprudential Regulation
Characterizes the approach to financial regulation aimed to mitigate the risk of the
financial system as a whole (or systematic risk).
3.2.41 Mainstream economic(s)
Refer to widely accepted economics as taught across prominent universities and in
contrast to heterodox economics.
3.2.42 Monetary Policy
Is the process by which the monetary authority of a country controls the supply of
money, often targeting the rate of interest for the purpose of promoting the economic
growth and stability.
3.2.43 Mortgage Market
A market for loans to people and organizations buying property. A market for mortgages
that have been bought by financial institutions and are then traded as assets-backed
securities.
Two markets exist.
Primary mortgage market – where borrowers and mortgage originators come together to
negotiate terms and effectuate mortgage transactions. Mortgage brokers, mortgage
bankers, credit unions and banks are all part of the primary mortgage market.
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Secondary mortgage market – where mortgage loans and servicing rights are bought and
sold between mortgage originators, mortgage aggregators (securitizers) and investors. It
is extremely large and liquid.
3.2.44 Mortgage (loan)
Is a loan secured by real property through the use of mortgage note which evidences the
existence of the loan and the encumbrance (burden) of that realty through the granting of
a mortgage which secures the loan.
3.2.45 Open market operations (OMO)
The buying and selling of government securities in the open market in order to expand
or contract the amount of money in the banking system. Purchases inject money into the
banking system and stimulate growth; selling removes money in the circulation and
contracts the economy.
3.2.46 Peak (Business, Economic)
High point of prosperity of the business cycle of some particular phase of economic
activity.
3.2.47 Pricking (punching) the bubble
It is an attempt to stop the inflation of an asset bubble through harsh/abrupt policies
management like raising interest rates. It is often feared by doing so you can cause
economic collapse or push the bubble cycle in the future economic period. Economists
tend to agree to let the bubble develop to its peak and burst, meanwhile applying steady
monetary policies.
3.2.48 Purchase
Refers to an individual or business or organization attempt to acquire goods and services
to accomplish a personal or enterprise goal.
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3.2.49 Real estate
is a property consisting of land and the buildings on it, along with its natural resources
such as crops, minerals, or water, immovable property on this nature; an interest vested
in this; (also) an item of real property; (more generally) buildings or housing in general;
as well as the profession of buying, selling, or renting land, buildings or housing (Oxford
English Dictionary online, 2014)
3.2.50 Recession (business, economic)
A general slowdown in economic activity, where there is a widespread drop in spending
usually triggered by financial crisis, external trade shock, adverse supply shock or the
bursting of an economic bubble.
3.2.51 Rent
Compensation paid by a tenant (or lessee) to the property owner (or lessor) for use or
occupancy of a property.
3.2.52 Repo Market
Repo is an acronym for ‗repurchase agreement‘. It is a short-term borrowing for dealers
in government securities. The dealer sells the government securities to investors, usually
on an overnight basis, and buys them back the following day.
Repo market is therefore where dealers sell the government securities to investors on an
overnight basis and buys them back the following day.
3.2.53 Security (Banking, Economics)
A financial instrument that represents: an ownership position in a publicly – traded
corporation (stock), a creditor relationship with governmental body or a corporation
(bond), or rights to ownership as represented by an option. A security is a fungible,
negotiable financial instrument that represents some type of financial value. The
company or entity that issues the security is known as issuer.
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In another perspective, when one goes to a financial institution to get a loan you are
asked to provide security. In this sense then, security stands to mean leveraging your
personal assets so as to get access to a loan (secure a loan) or line of credit at a lower
interest rate.
3.2.54 Sell
An act of exchanging (something) for money; to make something available to be bought.
3.2.55 Speculation
Is the practice of engaging in risky financial transactions in an attempt to profit from
short or medium term fluctuations in the market value of a tradable good such as a
financial instrument. Thereby one ignores normal patience to wait to profit from the
underlying financial attributes embodied in the instrument such as capital gains, interest
or dividends.
3.2.56 Spending
In a government sense it is a state consumption and investment but exclude transfer
payments made the state. It is a government acquisition of goods and services for current
use to directly satisfy individual or collective needs of the members of the community;
as well as intending to create future benefits.
3.2.57 Stock Market Margin
Borrowed money that is used to purchase securities.
The amount of equity contributed by a customer as a percentage of the current market
value of the securities held in a margin account.
3.2.58 Supervisory Discretion
Financial supervisors‘ main task is to monitor the behaviour and actions of the
institutions under their area of responsibility. They check compliance with the regulatory
framework, and when necessary impose sanctions and enforce them. It is all in an effort
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to protect the depositors of these institutions and of other institutions, as well as the
taxpayers‘ money by avoiding or limiting systematic/contagion risks. Unfortunately, if
the regulatory framework is weak, interference of politicians or influencing people is left
unchecked or corruption gets on the way of the process, it disrupts the whole meaning of
supervision. Some have led to question ‗discretion‘ isn‘t enough but rather there should
be strict rules bounded in the process. For by mere discretion we imply one acts on
scenario judgement in monitoring financial institutions which can easily be swept by
poor choice of line of thoughts; which has proven to be a major factor during the 2007/8
global financial crush – real estate/housing crisis and stock.
3.2.59 Taxation
Refers to the act of a taxing authority actually levying tax.
The purpose of taxation is to finance government expenditure.
By definition, ‗tax‘ is a fee charged (levied) by a government on a product, income, or
activity.
3.2.60 Taylor Rule
Is a monetary policy rule that stipulates how much the central bank should change the
nominal interest rate in response to changes in inflation, output, or other economic
conditions. The rule stipulates that for each one – per cent increase in inflation, the
central bank should raise the nominal interest rate by more than one percentage point.
3.2.61 Time Varying Bank Capital Ratio
Also known as ‗time varying reserve requirement‘. It is a means to control capital flows
with prudential purposes, especially for emerging economies.
Reserve requirement or cash reserve ratio sets the minimum fraction of customer
deposits and notes that each commercial bank must hold as reserves (rather than lend
out). These required reserves are normally in the form of cash stored physically in a
bank vault (vault cash) or deposits made with a central bank. In monetary policy,
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required reserve ratio is used to influence the country‘s borrowing and interest rates by
changing the amount of funds available for banks to make loans with. When the reserve
requirement is adjusted periodically and varied over time for certain goals such as
inflation combating, it is called ‗time carrying bank capital ratio‘. In macroprudential
applications time varying bank capital ratio is normally advised.
3.2.62 Too Big to Fail (Theory)
This theory asserts that certain financial institutions are so large and so interconnected
that their failure would be disastrous to the economy, and they therefore must be
supported by the government when they face difficulty. This is to say such institutions
should become recipients of beneficial financial and economic policies from
governments or central banks. Opponents of this theory argues that there is a moral
hazard implications as the institutions who benefits from these protective policies will
seek to profit from them, deliberately taking positions that are high-risk high return, as
they are able to leverage these risks based on the policy preference they receive.
3.2.63 Valuation(s)
In finance, it means determination of the economic value of an asset or liability.
In real estate appraisal (property valuation), is the appraisal [assessment] of land or
buildings.
3.3 Research Procedure
3.3.1 Research Design
This is a plan of action through which a researcher organizes his/her work from data
collection, data organization to data analysis in a manner that aims to combine relevance
to the purpose with economy in procedure, Kothari (1997). This research is carefully
planned from careful investigation of all variables and relationships, asking the key
expert of the study field by the researcher then compare such information with existing
literatures. This truly ensures there won‘t be biased information to misrepresent the
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findings. The research design employed was case study. Krishnaswami (1998), defines a
case study as an in depth comprehensive study of a person, a social group, an episode, a
process, a situation, a programme, or a community. The researcher employed a case
study because it is flexible with respect to data collection. Case study helps to build up a
picture from a relatively small sample of how the population functions. The case study
design was adopted because it focuses on the particular cases and helps to make some
generalization/conclusions. This is to say that the conclusions drawn from the study at
Bank of Tanzania was used in making inferences to other studies in other Central Banks
across East Africa and other developing nations. The commercial banks and other
financial institutions will have much to learn and apply from the research findings.
Using this method, the researcher gathered comprehensive information from various
sources, including participant observation, interviews and questionnaires.
3.3.2 Research Strategy
In order to follow through the objectives of this research study, single case strategy was
applied to fit them. According to Yin (1994), case study benefits from prior development
of theoretical preposition that used to guide data collection and analysis. This fact
rationalizes the suitability of single case study in a study like this.
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Figure 3.1: Research Process
Literature review
Research problem
Research objective
s
Research question
s
Conceptual framework
Hypothesis and Unit of
study
Problem area
Research design
Data collection
Data analysis
Reliability and validity
Policy implementation
Policy recommendation
Areas for further study
The extent of Tanzania monetary
policy in precipitating asset bubble in real estate/housing
market
Source: Researcher 2014
3.3.3 Area of the Research
The area of research which is the source of datawas Bank of Tanzania (BoT), situated at
Dar-es-salaam around Mirambo Street.
3.3.4 Location of case study - Bank of Tanzania
Bank of Tanzania is in Tanzania, at East Africa. Its headquarters are situated at Dar-es-
salaam city centre, where this research was carried out. BoT postal address is;
Bank of Tanzania
P.O. Box 2939
Dar-es-salaam
Tanzania.
Its street address is;
2 Mirambo Street
11884 Dar es salaam
Tanzania
The Bank buildings are about three minutes‘ walk from the ‗Askari Monument‘ and the
‗Movenpick Hotel‘ respectively
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Figure 3.2: Overview map of Dar es salaam
Source: Bank of Tanzania (2014). About the Bank – Bank of Tanzania Location. Retrieved on 15th
April
2014 from World Wide Web: http://www.bot-tz.org/AboutBOT/BOTLocation.asp
85
Figure 3.3 : Detail map of Dar es salaam City Centre (locating BoT)
Source: Bank of Tanzania (2014). About the Bank – Bank of Tanzania Location. Retrieved on 15th
April
2014 from World Wide Web: http://www.bot-tz.org/AboutBOT/BOTLocation.asp
3.3.5 Unit of study
Bank of Tanzania (BOT)
3.3.6 Types of Study
There are two types of study approaches, quantitative and qualitative research.
Quantitative research is based on the measurement of quantity or amount. It is applicable
to phenomena that can be expressed in terms of quantity.Qualitative research, on the
other hand, is concerned with qualitative phenomenon, i.e. phenomena relating to or
involving quality or kind.
86
This research is highly quantitative than qualitative based on measurement of variables
of highly econometric applications. It should be noted that there is neither purely
quantitative nor qualitative standalone research studies (it is a matter of degree).
3.3.7 Types of Data
Types of data in research are usually primary and secondary data. The primary data are
those which are collected afresh and for the first time, and thus happen to be original in
character. The secondary data, on the other hand, are those which have already been
collected by someone else and which have already been passed through the statistical
process. Primary data in this research was gathered through interviews and
questionnaire. Secondary data was gathered from organization brochures, website,
journals, textual and empirical literature and otherfactual documents.
3.3.8 Unit of Analysis
Units of analysis are factor influencing asset - housing bubble inflation, which includes;
(i) Effectively administer bank rate tool.
(ii) Assessing addressing of reserve requirements and discount rate tool.
(iii) Investigating feedback of moral suasion tool.
(iv) Evaluate credit market controls in the market.
(v) Consideration of changes in stock market margin requirement in DSE
(vi) Assessing establishment of time varying bank capital ratio
(vii) Monitoring of a credit-to-GDP ratio
(viii) Necessity of supervision discretion to individual institutions.
3.3.9 Study Population
From a statistical point of view, the term ‘population’ refers to the total of items about
which information is desired. The attributes that are the object of study are referred to as
characteristics and the units possessing them are called as elementary units. The
aggregate of such units is generally described as population. Thus, all units in any field
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of inquiry constitute universe and all elementary units (on the basis of one characteristic
or more) constitute population. The population or universe can be finite or infinite. The
population is said to be finite if it consists of a fixed number of elements so that it is
possible to enumerate it in its totality. An infinite population is that population in which
it is theoretically impossible to observe all the elements. Thus, in an infinite population
the number of items is infinite i.e., we cannot have any idea about the total number of
items.
The study population of this research wasfinite, which is by understanding that BOT
(Dar-es-salaam, Head Office) has fixed number of employees.
3.3.10 Sampling methods
3.3.10.1 Sampling technique
There are two techniques of sampling, the sample may be probability sampling or it may
be non-probability sampling.
Probability sampling is based on the concept of random selection, giving each element
in the population an equal chance of getting into the sample; and all choices are
independent of one another. Types of probability sampling include simple random,
systematic, stratified, probability proportional to size and cluster/multistage sampling.
Non-probability sampling is that sampling procedure which does not afford any basis for
estimating the probability, that each item in the population has a chance of being
included in the sample. In this type of sampling, items for the sample are selected
deliberately by the researcher; his choice concerning the items remains supreme. This is
suitable for in-depth study research in a particular investigation limited by number of
respondents. Types of non-probability sample include; convenience,
haphazard/accidental, snowball, judgmental/purposive, deviant, case study and ad-hoc
quotas.
This study have used non-probability sampling - ‘judgmental/purposive’ sampling,
where a sample was chosen on who are appropriate for the study (focusing on the
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expertise of selected individuals). In a purposive sampling, a researcher deliberately
selected a particular unit of universe for constructing a sample that represents the
universe. In this way a specific individuals (respondents) in BoT were selected to offer
information to the findings.
3.3.10.2 Sample Frame/Size
This refers to the number of items to be selected from the universe to constitute a
sample. The size of sample should neither be excessively large, nor too small. It should
be optimum. An optimum sample is one which fulfils the requirements of efficiency,
representativeness, reliability and flexibility. While deciding the size of sample,
researcher must determine the desired precision as also an acceptable confidence level
for the estimate. The size of population variance needs to be considered as in case of
larger variance usually a bigger sample is needed. The size of population must be kept in
view for this also limits the sample size. The parameters of interest in a research study
must be kept in view, while deciding the size of the sample.
Due to adoption of the purposive sampling (non-probability sampling), the researcher
found it sufficient to have a size of fifteen (15) who will be drawn from BoT areas like;
(i.) project management unit
(ii.) monetary and financial affairs department
(iii.) bank supervision unit
(iv.) domestic market
Table 3.1: Distribution of Respondents
S/N Types of respondent Number of respondent
1 Project Management unit 5
2 Monetary and Financial affairs unit 3
3 Bank supervision unit 4
4 Domestic market unit 3
Total 15
Source: Researcher 2014
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At the end of the administration of data tools, the researcher collected only ten (10)
respondents out of fifteen (15), this being 66 per cent of the filled questionnaire to which
were used in the analysis of this study.
3.3.10.3 Sample Size Determination
According to Kothari (1990) one can say that the sample must be of an optimum size
i.e., it should neither be excessively large nor too small. Technically, the sample size
should be large enough to give a confidence interval of desired width and as such the
size of the sample must be chosen by some logical process before sample is taken from
the universe.
There are two alternative approaches for determining the size of the sample.
The first approach is ―to specify the precision of estimation desired and then to
determine the sample size necessary to insure it‖ and the second approach ―uses
Bayesian statistics to weigh the cost of additional information against the expected value
of the additional information. ―The first approach is capable of giving a mathematical
solution, and as such is a frequently used technique of determining ‗n‘. The limitation of
this technique is that it does not analyse the cost of gathering information as compared
with the expected value of information. The second approach is theoretically optimal,
but it is seldom used because of the difficulty involved in measuring the value of
information. This research adopted the first approach.
3.3.11 Methods of Data Collection
Methods of data collection were Questionnaire and Interview. For interview to be
efficient it was emphasized on basis of one to one discussion. For the questionnaire to be
reliable it was designed as a structured one. These methods made a basis for a primary
data usage. With the advancement of online communication, even research has
experienced a boost of tools such as online survey tools. A link for online survey (with
90
questionnaire) was designed and sent to the respondents. The link address for survey
is:http://kwiksurveys.com/s.asp?sid=ckzgy4dbgnt0nnh327177.
3.3.12 Tools of Data Collection
Tools of data collection were Questionnaire template and Interview schedule.
3.3.13 Data Organization
3.3.13.1 Response Rate
The data collection started on 1st April 2014 and ended in 30th April 2014. The task was
not easy as the researcher had to struggle through conflicting schedules of the
respondents who were mostly on work travels or assignments outside Dar es salaam and
Tanzania. Only ten (10) out of the intended fifteen (15) respondents could be reached
throughout this whole research period.
3.3.13.2 Data organization
Data organization is the orderliness in research data, therefore putting the data into some
systematic form such as identifying and correcting errors in the data, coding and
recording data in appropriate form. Data collection was under strict precision sent to the
respondents through a web-link which allows one user (respondent) per single browser;
either internet browser on a mobile phone or personal computer (PC). The link had
‗cookies‘ which restrict only one respondent per questionnaire; thereby removing the
possibility of repetition among respondents. The data was categorized and coded to be
fed into SPSS for analysis and manipulation.
3.3.13.2Data editing
The data of the study was edited through two procedures; field editing and office editing.
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3.3.13.3 Data processing and analysis
The data was processed and analysed by using quantitative software. SPSS was used for
the descriptive statistics analysis, univariate analysis and multivariate analysis.
The data was compiled by data editing, data coding and data tabulation..
Respondents characteristics were examined by frequency analysis (section 4.2); which
was helpful in evaluating the number of times an event occurred in a study. Factor
analysis was used for data reduction and summarization and found its application in
‗Association of monetary regime and house/real estate inflating prices (section4.3).
Cross tabulation analysis has been used to summarize categorical data – as in section 4.5
‗Association of monetary regime and house/real estate inflating prices. Correlation
analysis has been employed in measuring the strength of the relationship between two
variables as in section 4.6 ‗Measuring of independent and dependent variables‘ of the
study. Cronbach‘s alpha analysis was used in measuring the reliability of the sample
(study). This is a method of testing internal consistency; thereby testing validity of data
as it was applied in section 4.7.
3.3.13.4 Data presentation
The data was presented by using a combination of statistical and graphical techniques
like graphs, tables and pictures.
3.3.14 Variables and their measurements
The research variables which are expressed in this research were;
(i.) Monetary policy – Independent Variable
(ii.) Real estate/Housing market prices – Dependent Variable
This research is bivariate.
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3.3.15 Reliability and validity issues
Reliability is the degree to which an assessment tool produces stable and consistent
results. There are several types of reliability such as; test-retest, parallel forms, inter-
rater and internal consistency validity.
Validity refers to how well a test measures what it is purported to measure. There are
several types of validity such as; face, construct, criterion-related, formative and
sampling validity.
Inter-rater reliability is a measure of reliability used to assess the degree to which
different judges or raters agree in their assessment decisions. It is a useful reliability tool
since human observations does not necessarily interpret answers the same way; raters
may disagree as to how well certain responses or material demonstrate knowledge of the
construct (hypothesis/concept/idea) or skill being assessed.
The assessment of monetary policy of Tanzania in relation to asset bubble varies from
individual to individual, as much as it is a global debatable matter ever since 2007/8
Financial market crush. Thus the inter-rater reliability makes it a convenient measure
for this research work. It is a necessary tool as there will be different stakeholders who
will be evaluating the degree to which the hypothesis meet some standards – which are
obvious relatively subjective.
Sampling Validity (Content Validity) ensures that the measure covers the broad range
of areas within the concept under study. Not everything can be covered, so items need to
be sampled from all of the domains.
The design of the sample to assess monetary policy in relation to asset bubble it is wise
not only to end in housing/real estate but to include the entire construction industry.
Confirmatory factor analysis was carried out to investigate the convergent and
discriminant validity of the constructs proposed. The factor analysis has helped to define
93
the underlying pattern of factor as related to the data collected from the field. In the
study, reliability and internal consistency was measured by cronbach‘s Alpha. This is a
method of testing internal consistency; thereby testing validity of data (see section 4.7).
3.3.16 Ethical Issues
Research is guided by ethical codes and the respondents have to be protected from
confidentiality. Furthermore, the permission has to be given to conduct data collection.
The letter from Mzumbe University was given to the researcher to get access for data at
the Bank of Tanzania. The researcher also took personal effort to prepare a ―Request
letter to conduct research at BoT addressing the Governor; this letter indicated the aim
of the research, significance, research plan and method, how the data will be collected
and what to expect, research strategy, research process, unit of analysis and sample
frame. The letter of researcher was attached with Mzumbe University approval letter,
Concept Note, Questionnaire and Researcher‘s Curriculum Vitae.
CHAPTER FOUR
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PRESENTATION OF FINDINGS
4.1 Introduction
In this chapter the researcher presents his findings as reflected from the purpose and
objective of the study.
4.2 Sample Characteristics
The researcher adopted a purposive sampling, aiming to interview experts of monetary
and fiscal policies. The study has ten (10) respondents against the earlier expected of
fifteen (15) responses. Due to inconveniences beyond the researcher these five experts
could not be reached.
4.3 Respondents
The targeted respondents were individuals who were in capacity of making informed
decisions as to the regard of monetary policy and housing bubble burst. The researcher
examined the age, gender, level of education and use of agents when buying and renting
a house.
Table 4.1: Respondents Characteristics [Office Department/Unit]
Category Frequency Percent
Project Management unit 2 20.0
Monetary and Financial affairs 2 20.0
Bank supervision unit 3 30.0
Domestic market unit 3 30.0
Total 10 100.0
Source: Study findings 2014
It was found that 20 per cent of respondents came from project management unit, 20 per
cent from Monetary and Fiscal affairs unit, 30 per cent from Bank supervision unit and
30 percent from Domestic market unit.
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4.3.1 Age
The study found out that the organization has high mid-age personnel of between 31-
40years who highly contributed to the responses, making up 70 percent of the sample.
Table 4.2: Age of Respondents
Category Frequency Percent
21- 30 years 1 10.0
31- 40 years 7 70.0
41 - 50 years 2 20.0
Total 10 100.0
Source: Study findings 2014
It was also observed that 21-30 years of old represented 1 per cent of the sample while 2
per cent of the sample represented 41-50 years. The organization encourages youths who
are versatile for work and development to work for them.
4.3.2 Gender
The study noted that men were highly reached to respond to the study questionnaire,
comprising of 80 per cent of the sample. This is probably due to the dispersion of
employees to various travel work.
Table 4.3: Gender of respondents
Category Frequency Percent
Male 8 80.0
96
Female 2 20.0
Total 10 100.0
Source: Study findings 2014
Women represented 20 percent of the sample.
4.3.3 Level of Education
It was observed that Bank of Tanzania (BoT) has a high skilled labour with high
education; that Master‘s holders were 90 percent of the sample and PhD holders
represented 10 per cent of the sample.
Table 4.4 Level of Education
Category Frequency Percent
Master's degree 9 90.0
PhD 1 10.0
Total 10 100.0
Source: Study findings 2014
BoT emphasizes high level of education personnel.
4.3.4 Use of agents when buying and renting a house
Majority of the respondents representing 60 per cent of the sample agreed over the use
of agents when it comes to a need of house purchase or renting.
Table 4.5: Use of agents When Buying and Renting A House
Category Frequency Percent
Yes 6 60.0
No 4 40.0
Total 10 100.0
Source: Study findings 2014
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The rest of 40 per cent agreed not over the idea.
Most uses local agents ‗dalali‘; since they are cheap, though are a contributing factor to
bubble inflation.
3 Factor Analysis: Association of Monetary Regime and House/Real Estate
Inflating Prices
Factor analysis was conducted for data reduction and summarization. Factor analysis is
an interdependence technique in that an entire set of interdependent relationships is
examined without making the distinction between the dependent and independent
variables.
Table 4.6 Correlation matrix vs correlation of Monetary regime and
House/Real Estate inflating prices
Correlation Matrix
Knowledge over
the operation of
money supply
and interest rate
BoT is autonomous and
independent from the
government
interventions
People have a hyper
attitude to buy lands
in Tanzania even
though not
necessarily
developing them
Improvement of mortgage
law in Tanzania is presently
(and will in the future)
accelerate real estate
industry and housing
constructions
There is a basis
for a current
estimation of
real estate
prices value
DSE stock brokers
negatively drives
up prices of major
construction
industry
particularly cement
Correlation
Knowledge over the
operation of money supply
and interest rate
1 0.337 0.045 0.709 -0.247 0.38
BoT is autonomous and
independent from the
government interventions
0.337 1 -0.435 0.306 -0.031 -0.04
People have a hyper attitude
to buy lands in Tanzania
even though not necessarily
developing them
0.045 -0.435 1 -0.098 -0.022 0.398
Improvement of mortgage
law in Tanzania is presently
(and will in the future)
accelerate real estate
industry and housing
constructions
0.709 0.306 -0.098 1 -0.606 0.176
There is a basis for a current
estimation of real estate
prices value
-0.247 -0.031 -0.022 -0.606 1 0.291
DSE stock brokers negatively
drives up prices of major
construction industry
particularly cement
0.38 -0.04 0.398 0.176 0.291 1
Sig. (1-tailed)
Knowledge over the
operation of money supply
and interest rate
0.171 0.45 0.011 0.246 0.14
BoT is autonomous and
independent from the
government interventions
0.171 0.105 0.195 0.466 0.456
People have a hyper attitude
to buy lands in Tanzania
even though not necessarily
developing them
0.45 0.105 0.394 0.476 0.127
Improvement of mortgage
law in Tanzania is presently
(and will in the future)
accelerate real estate
industry and housing
constructions
0.011 0.195 0.394 0.032 0.313
There is a basis for a current
estimation of real estate
prices value
0.246 0.466 0.476 0.032 0.208
DSE stock brokers negatively
drives up prices of major
construction industry
particularly cement
0.14 0.456 0.127 0.313 0.208
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Source: Study findings 2014
The correlation above with interval or ratio – scaled data (variables) of ranges from -
1.00 or 1.00 indicates a strong relationship among the variables (perfect and strong
correlation among each other). The values close to 0.0 indicate a weak correlation.
Thereby it was found that there is a good relationship between improvement of mortgage
law in Tanzania and knowledge of operation of money supply and interest rate (0.709).
There is a moderate relationship between hyper attitude of people to buy lands and the
knowledge over money supply and interest rate (0.45). There is also a moderate
relationship between autonomous nature of BoT and a basis for a current estimation of
real estate price value (0.466) and DSE driving up of prices of construction materials
(0.456). These positive values indicated a direct relationship among variables.
There is weaker association between hyper attitudes of people in buying lands and
improvement of mortgage law in Tanzania (-0.098) and basis of estimation of real estate
prices (-0.022). There was also found a good relationship between improvement of
mortgage law and a basis for a current estimation of real estate price value (-0.606).
4.4 Frequency Analysis: Association of Monetary Regime and House/Real
Estate Inflating Prices
In statistics, the frequency (or absolute frequency) of an event ‗i‘ is the number ‗ni‘ of
times the event occurred in an a study
Table 4.7: Understanding regards to monetary policy of Tanzania conducts and
satisfied over the implementation of its objectives
Rating Frequency Percent
strongly agree 3 30.0
Agree 5 50.0
slightly agree 1 10.0
neither agree nor disagree 1 10.0
Total 10 100.0
99
Source: Study findings 2014
It was found that 30 per cent of the respondents only strongly agreed over satisfaction
and implementation of monetary policy. Majority simply agreed who represented 50 per
cent of the respondents. The rest slightly agreed and neither agreed nor disagreed who
both represented a portion of 10 per cent.
Table 4.8: BoT is autonomous and independent from the government
interventions
Rating Frequency Percent
strongly agree 1 10.0
Agree 3 30.0
slightly agree 4 40.0
slightly disagree 2 20.0
Total 10 100.0
Source: Study findings 2014
Only 10 per cent strongly agreed that the Central Bank is autonomous from government
intervention.30 per cent agreed over moderate intervention, whereas majority seems to
see only slightly intervention (40 per cent). Respondents who slightly disagreed were 20
per cent.
Table 4.9: BoT should follow the lead of financial markets
Rating Frequency Percent
strongly agree 3 30.0
Agree 6 60.0
slightly agree 1 10.0
Total 10 100.0
Source: Study findings 2014
100
Majority agreed that BoT should follow the lead of financial markets, comprising of 60
per cent of respondents. Only 30 per cent strongly agreed and 10 per cent slightly
agreed.
With the world interacting with each other‘s national policies to harmonize economic
policies in regional blocks, Tanzania monetary policies should seek similar paths with its
neighbouring and global economies monetary set up.
Table 4.10 : It is logical for BoT to adopt gradualism attitude (steady and regular
techniques) in the housing market asset bubble circumstance at a moment
Rating Frequency Percent
strongly agree 2 20.0
Agree 6 60.0
neither agree nor disagree 2 20.0
Total 10 100.0
Source: Study findings 2014
60 per cent agreed over the steady and regular technique of monetary policy adoption by
the Central Bank. 20 per cent strongly agreed and the other 20 per cent neither agreed
nor disagreed. This adoption of steady techniques is one Tanzania has been using in
recent years as it avoids disturbing bubble phenomenon least it could quickly inflate and
burst unpreparedness.
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Table 4.11: There is a tremendous pressure of rising rents in Dar es salaam (and
other regions)
Rating Frequency Percent
strongly agree 6 60.0
Agree 3 30.0
slightly agree 1 10.0
Total 10 100.0
Source: Study Findings 2014
Indeed majority strongly agreed that there is a pressure of rising rents in Dar es salaam
and other commercial hub towns and cities, comprising of 60 per cent of the
respondents. 30 per cent simply agreed and the rest of 10 per cent slightly agreed.
For example, monthly rent rate for a 2 bedroom fully furnished apartment located at elite
suburbs like Masaki, Mikocheni and Oysterbay ranges between USD 2000 and USD
4000 (The Guardian,2013). In Sinza, rent goes as much as TZS 400,000 from TZS
300,000 and in Mwenge as much as TZS 350,000 from TZS 200,000 in these recent
years.
Table 4.12: People have a hyper attitude to buy lands in Tanzania even though
not necessarily developing them
Rating Frequency Percent
strongly agree 6 60.0
Agree 4 40.0
Total 10 100.0
Source: Study findings 2014
102
Majority strongly agreed over the phenomenon of hyper attitude of citizens in buying
lands (even real estates/houses) though not necessarily developing them; these were 60
per cent of the respondents. 40 per cent simply agreed over the matter.
Table 4.13: Investors are overly optimistic in investing in real estate market now
in Dar es salaam and elsewhere
Rating Frequency Percent
strongly agree 4 40.0
Agree 5 50.0
neither agree nor disagree 1 10.0
Total 10 100.0
Source: Study findings 2014
There was observed stark minor difference between those who strongly agreed and those
who agreed by variation of 10 percent as seen from the table above. Strongly agreed
were 40 per cent, where those who agreed were 50 per cent. Moreover, those who
neither agreed nor disagreed were 10 per cent.
Table 4.14 : Improvement of mortgage law in Tanzania is presently (and will in
the future) accelerate real estate industry and housing constructions
Rating Frequency Percent
strongly agree 2 20.0
Agree 6 60.0
slightly agree 1 10.0
neither agree nor disagree 1 10.0
Total 10 100.0
Source: Study findings 2014
103
It was observed only 20 per cent were optimistic over the introduction of mortgage law
and improvements of current legislations related to it (strongly agreed). 60 per cent
agreed over the matter and whereby the rest who slightly agreed and neither agreed nor
disagreed were both 10 per cent.
Table 4.15: DSE stock brokers negatively drives up prices of major construction
industry particularly cement
Rating Frequency Percent
Agree 1 10.0
slightly agree 5 50.0
neither agree nor disagree 3 30.0
Disagree 1 10.0
Total 10 100.0
Source: Study findings 2014
Only 10 per cent agreed that stock market brokers do drive prices up of major
construction companies. 50 per cent slightly agreed, 30 per cent neither agree nor
disagree and 10 per cent disagreed.
4.5 Cross Tabulation: Association of Monetary Regime and House/Real Estate
Inflating Prices
Cross tabulation is a statistical process that summarizes categorical data to create
contingency table. It provides a basic picture of the interrelation between two variables,
assisting in finding interactions between them.
104
Table 4.16: Crosstab*Count; Pressure of rising rents against monetary policy
and implementation of monetary objectives
Count
Understanding regards to monetary policy of Tanzania conducts and satisfied
over the implementation of its objectives
strongly agree agree slightly agree
neither agree
nor disagree
There is a
tremendous
pressure of
rising rents in
Dar es salaam
(and other
regions)
strong
ly
agree
2 3 0 1
Agree 0 2 1 0
slightl
y
agree
1 0 0 0
Total 3 5 1 1
Source: Study findings 2014
105
Figure 4.1: Bar graph; Pressure of rising rents against monetary policy and
implementation of monetary objectives
Source: Study findings 2014
It was observed that, a strongly agreed interrelation as to regards to monetary policy
satisfaction and tremendous pressure of rising rents in Dar es salaam by a count of 2
respondents. Another interrelationship is found between monetary policy satisfaction
‗agreed‘ against rising pressure of rent ‗strongly agreed‘ by a count of 3. However rising
pressure ‗agreed‘ against monetary policy implementation was observed by a count of 2.
106
4.6 Correlation Analysis – Bivariate Analysis; Measuring The Variables [Independent And Dependent]
Table 4.17: Measuring the Dependent and Independent Variables
Correlations
Control Variables Government and
BoT should
intervene
aggressively to
institutions which
accumulates and
inflate real
estate/house
prices
BoT control capital
flow with prudential
purposes
It is logical
when total
volume of credit
is controlled in
the economy by
the Central Bank
of Tanzania
Persuading certain
regulations without rigid
laws and punishment has
proven ineffective in
Tanzania
Low interest rates is charged
to commercial banks thereby
pushing high housing prices
and related costs
When BoT lower the interest rate
there is unhealthy inflation in
Tanzania encouraging high
housing prices
Prices are
temporarily
high in real
estate and
housing market
of Tanzania &
Investors are
overly
optimistic in
investing in
real estate
market now in
Dar es salaam
and elsewhere
Government and
BoT should
intervene
aggressively to
institutions which
accumulates and
inflate real
estate/house prices
Correlation 1.000 -.275 .304 .546 .165 .027
Significanc
e (1-tailed) . .255 .232 .081 .348 .475
df
0 6 6 6 6 6
BoT control capital
flow with
prudential
purposes
Correlation -.275 1.000 .254 .310 .489 .268
Significanc
e (1-tailed) .255 . .272 .227 .110 .261
Df 6 0 6 6 6 6
It is logical when
total volume of
credit is controlled
in the economy by
the Central Bank
of Tanzania
Correlation .304 .254 1.000 .167 .716 .833
Significanc
e (1-tailed) .232 .272 . .346 .023 .005
Df
6 6 0 6 6 6
Persuading certain Correlation .546 .310 .167 1.000 .644 -.301
107
regulations without
rigid laws and
punishment has
proven ineffective
in Tanzania
Significanc
e (1-tailed) .081 .227 .346 . .042 .235
Df
6 6 6 0 6 6
Low interest rates
is charged to
commercial banks
thereby pushing
high housing prices
and related costs
Correlation .165 .489 .716 .644 1.000 .344
Significanc
e (1-tailed) .348 .110 .023 .042 . .202
Df
6 6 6 6 0 6
When BoT lower
the interest rate
there is unhealthy
inflation in
Tanzania
encouraging high
housing prices
Correlation .027 .268 .833 -.301 .344 1.000
Significanc
e (1-tailed) .475 .261 .005 .235 .202 .
Df
6 6 6 6 6 0
Source: Study findings 2014
In measuring the strength of the relationship (correlation) between two variables; we consider interval or ratio-scaled data (variables). It ranges from -1.00 to 1.00. Values of -
1.00 or 1.00 indicate perfect and strong correlation. Values close to 0.00 indicate weak correlation. Negative values indicate inverse relationship and positive values indicate a
direct relationship.
From the results above we therefore find the following relationships positive values of direct relationship and convincing correlations;
(i.) Persuading a regulation without rigid laws and punishment has proven ineffective in Tanzania ‗against‘ government and BoT should intervene aggressively to institutions
which accumulate and inflate real estate/house prices has 0.546.
(ii.) Low interest rates is charged to commercial banks thereby pushing high housing prices and related costs ‗against‘ it is logical when total volume of credit is controlled in
the economy by the Central Bank of Tanzania is 0.716.
(iii.) When BoT lower the interest rate there is unhealthy inflation in Tanzania encouraging high housing prices ‗against‘ it is logical when total volume of credit is controlled
in the economy by the Central Bank of Tanzania is 0.833.
(iv.) Low interest rates is charged to commercial banks thereby pushing high housing prices and related costs ‗against‘ persuading certain regulations without rigid laws and
punishment has proven ineffective in Tanzania is 0.644.
108
4.7 Cronbach’s Alpha Analysis - Testing Consistency/Validity of Data
Cronbach‘s α (alpha) is a coefficient on internal consistency, used for estimating the
reliability of a psychometric test for a sample it examines (Cronbach, 1951).
―Coefficient alpha and the internal structure of tests‖. Psychometrika 16(3):297-334].
Theoretical values of alpha varies from 0 to 1; highest values being more desirable. Less
than 0.5 is unacceptable value, between 0.6 and 0.7 is acceptable value, whereas more
than 0.9 is the excellent value(high-stakes testing)
Table 4.18 : Cranbach’s alpha Analysis of the study variables – Reliability
statistics
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.670 .660 6
Source: Study findings 2014
From the computation of the alpha of the study, it was obtained to be 0.670 being the
acceptable value for use in an instrument. Cronbach‘s alpha will generally increase as
the conditions among test items increase, and thus we call it ‗internal consistency‘
estimate of reliability scores.
4.8 Analyzing The Hypothesis of The Study
In this section the researcher presents the empirical testing of the hypotheses. The main
objective of this study was to evaluate the extent of the monetary policy of Tanzania in
advancing asset-bubble in real estate/housing market prices; this was expressed well in
chapter one (1) alongside its specific objectives. In chapter five (5) the researcher
presents various analytical data tools addressing the questions related to the respondents;
the monetary policy of Tanzania in relation to the asset-bubble in real estate/house
109
market. In this section we shall verify what the researcher has collected and analysed in
the perspective of approving or disapproving the hypothesis brought forward.
The research hypothesis was constructed out of ‗null-hypothesis‘ - Ho [relating to the
statement being tested]. In case the null hypothesis is rejected, researcher accepts
‗alternative-hypothesis – H1
The hypotheses being tested are;
4.8.1 When BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices.
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of this hypothesis was at 0.833 when it was
analysed against total volume of credit controlled by the Central Bank. This is true as the
body mandated to control the volume of credit can subject the very same economy into
the verge of inflation by lowering interest rates thus encourage commercial banks to
borrow more and thus individuals possessing too much money raises the value of houses
by compensating the incremental loss of money value and as well as to take advantage
of the too much credit possession in the circulation.
Thereby the researcher accepted this hypothesis [accepted Ho] since the scale offered is
convincingly good and enough to show interrelationship between low interest rate and
inflationary tendencies rising the houses costs.
110
4.8.2 The low interest rate charged to commercial banks and other depository
institutions on loans they receive from BoT encourage high money supply resulting
into inflationary tendencies giving negative effect in housing market prices.
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of this hypothesis was at 0.716 against total
volume of credit controlled in the economy by the Central Bank of Tanzania. As there is
a prevalence of low interest rate charged to commercial banks, there is encouragement
of borrowing and lending to and from the public respectively. This leads to drop in value
of the currency and in return rises the prices of commodities, as well as housing/real
estate value as businesses, land owners, estate owners and even landlords will attempt
not to reduce costs but rather increase the prices to make up for the loss resulted from
inflation.
In the light of such findings, the researcher accept this hypothesis [accepted Ho] since
the interrelationship between low interest rate and inflationary tendencies rising the
houses costs is moderately observed.
4.8.3 Due to high cut throat competition in the banking and financial sector in
general, persuading a certain regulation without rigid laws and punishment has
proven ineffective in Tanzania.
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of this hypothesis was at 0.546 against
government and BoT intervening aggressively to those institutions which accumulates
and inflate real estate/house prices.
The researcher has accepted this hypothesis [accepted Ho]
111
4.8.4 It is logical when total volume of credit is controlled in the economy by the
Central Bank of Tanzania.
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of this hypothesis was at 0.716 against low
interest rates charged to commercial banks thereby pushing high housing prices and
related costs. Moreover this variable was at a scale of 0.833 against when BoT lower the
interest rate there is unhealthy inflation in Tanzania encouraging high housing prices.
The general conclusion of interrelation of this variable is that, the higher the volume of
credit there is in the economy‘s circulation, the lower it is the interest rate set up which
has a resulting effect of inflation generation.
In the light of such evidence, the researcher has accepted this hypothesis [accepted Ho]
4.8.5 BoT control capital flow with prudential purposes
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of the hypothesis was observed in the following
manner;
(i.) against government and BoT should intervene aggressively to institutions which
accumulates and inflate real estate/house price -0.275
(ii.) against total volume of credit being controlled in the economy by the Central
Bank of Tanzania 0.254
(iii.) against persuading certain regulations without rigid laws and punishment has
proven ineffective in Tanzania 0.310
(iv.) against low interest rates is charged to commercial banks thereby pushing high
housing prices and related costs 0.489
(v.) against when BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices 0.268
112
The interval or ratio-scaled data (variables) do not range closely to -1 or +1 and neither
are they exactly -1 or +1; thus being too close to 0.00 indicates a weak correlation. In
additional, negative values indicates inverse relationship among variables being tested.
In the light of such findings, the researcher rejects null hypothesis[Ho], and accepts
alternative hypothesis [H1]. Thus it is now stated that, ―BoT does not control capital
flow with prudential purposes‖ – H1
4.8.6 The Central Bank and where possible government should intervene
aggressively to the institution(s) which possess a threat in a forerunner in
accumulating and inflating real estate/house prices.
In section 4.6, at a Correlation Analysis – Bivariate Analysis of the independent and
dependent variables; ratio-scaled data of this hypothesis was at 0.546 against persuading
regulations without rigid laws and punishment has proven ineffective in Tanzania.
Thereby it is seen a strong interrelationship when BoT needs to tackle the monetary
policy against ineffective firms that rigid policies and where possible aggressively
imposing order and penalty to protect the final consumer of credit and prevents
deterioration of currency.
The researcher has accepted this hypothesis [accepted Ho].
113
CHAPTER FIVE
DISCUSSION OF THE FINDING
5.0 Introduction
In this chapter, the researcher discusses the fulfilment. of the objectives to the
implementation of this study; as it was pointed out in chapter two (2). The main
objective of this research study was to evaluate the extent of the monetary policy of
Tanzania in advancing asset-bubble in real estate/housing market prices. Therefore in
this chapter we shall discuss the research findings detailed in chapter four (4) against our
theoretical framework developed in the first three chapters alongside the textual
literatures which the researcher saw fit to incorporate in his study.
The conceptual framework design has considered the old-age traditional monetary
policy tools which the current new age economists of latest 2007 have now seen to be
ineffective in solving the Financial Crisis as it was observed in a case of 2007/2008
Global Financial order crisis. The framework has also included current suggested tools
which are largely used in advanced economies. It was also necessary to incorporate
financial market deregulations as part of independent variable; and local variables such
as ‗dalali‘ [house brokers] and finally tying the local currency to hard currency. This has
helped to generate rich data with familiarity of that local economy of Tanzania.
According to National Housing Corporation (NHC), Tanzania runs a housing deficit
estimated at 3 million units valued at $180 billion by the end of 2007, while the current
annual demand for houses in urban areas is 200,000 units estimated to cost $12 billion.
The deficit it was expected to grow by 15 percent by the end of 2012 due to high
migration of people from rural to urban areas. The results presented in this discussion
are a bridge between housing deficit in Tanzania and reasonable pace that we should
expect to attain such houses in need; but in consideration of monetary policy in harmony
with a pre-existing economy.
114
5.1 Discussion of General Findings and Data Analysis
The targeted respondents were individuals who were in capacity to make informed
decisions as to regard to monetary policy and housing bubble burst. It was found that 20
per cent of respondents came from Project Management unit, 20 per cent - Monetary and
Fiscal affairs unit, 30 per cent - Bank Supervision unit and 30 per cent came from
Domestic Market unit. The organization has mid-age personnel of between 31-40 years
who highly contributed to the responses, making up 70 per cent of the sample. 21-30
years of old represented 1 per cent of the sample while 2 per cent of the sample
represented 41-50 years of age. Men were highly reached to respond to the study
questionnaire, comprising of 80 per cent where as women represented 20 per cent of the
respondents. Bank of Tanzania has a high skilled labor; whereas Master‘s holders were
90 per cent of the respondents and 10 per cent represented PhD holders.
Majority of the respondents representing 60 per cent of the sample agreed over the use
of agents when it comes to a need of house purchase or renting. However 40 per cent did
not agree to the idea. The study found a good relationship between improvement of
mortgage law in Tanzania and knowledge of operation of money supply and interest rate
with a ration-scale value of 0.709 under correlation matrix versus correlation of
monetary regime and house/real estate inflating prices. A mortgage market is a market
for loans to people and organizations buying property. A market for mortgages that have
been bought by financial institutions and are then traded as assets-backed securities.Two
types of markets exists. Primary mortgage market – where borrowers and mortgage
originators come together to negotiate terms and effectuate mortgage transactions.
Mortgage brokers, mortgage bankers, credit unions and banks are all part of the primary
mortgage market. The second type is secondary mortgage market – where mortgage
loans and servicing rights are bought and sold between mortgage originators, mortgage
aggregators (securitizers) and investors. It is extremely large and liquid.
115
The study found a moderate interrelationship between hyper attitude of people to buy
lands and the knowledge over the money supply and interest rate at a scale of 0.45. This
result is very alarming, as it imply citizens and policy makers are not aware of the
bubble build up in their midst. If Asian economies have some similarities with the
developing countries like Tanzania, shouldn‘t we have much to worry if not to be
prepared with asset bubble inflation? The current times where the bubble is growing
(though has not burst yet) it is prudent for the Central Bank of Tanzania to avoid any
rush decisions even if it notices signals now that we have submerged in the water. This
is because as the bubble build-up it takes years until a visual pattern is noticed, making it
hard to identify and predict the magnitude of the bubble; being also among the reasons
even policy makers seems not frightened by this economic ‗beast‘. For such observance
a precise monetary policy can hardly be adopted in this period of uncertainty giving a
reflection of steady policies or adjusted policies to suit the economies being set-up time
and time again. There is also a moderate relationship between autonomous nature of
BoT and a basis for a current estimation of real estate price value at a scale of 0.466 and
DSE driving up of prices of construction materials (0.456). The study found a weaker
association between hyper attitudes of people in buying lands and improvement of
mortgage law in Tanzania at a scale of -0.098 and a basis of estimation of real estate
prices (-0.022). It was found a good interrelationship between improvement of mortgage
law and a basis for a current estimation of real estate price value at a scale of -0.606.
These results were analyzed under factor analysis; association of monetary regime and
house/real estate inflating prices (section 4.3).
The study learned that 30 per cent of the respondents only ‗strongly agreed‘ over the
satisfaction and implementation of monetary policy of Tanzania and its implementation.
Majority simply ‗agreed‘ representing 50 per cent of the respondents. The rest, ‗slightly
agreed‘ and ‗neither agreed nor disagreed‘ who both represented a portion of 10 per
cent. Only 10 per cent ‗strongly agreed‘ that the Central Bank of Tanzania is
autonomous from government interventions. 30 per cent ‗agreed‘ over moderate
116
intervention, whereas majority seems to see only ‗slightly‘ intervention, representing 40
per cent of the respondents. If the politicians in Tanzania can discipline themselves not
to meddle the monetary policies and regulations with politics we have hope to stand on a
winning side, when the asset bubble are nearing their burst. It is thus not a matter of
debate that Central Bank of Tanzania is to be autonomous in all the way of its
functioning – it should be indeed independent. Majority ‗agreed‘ that BoT should follow
the lead of financial markets, comprising of 60 per cent of respondents. Only 30 per cent
‗strongly agreed‘ and 10 per cent ‗slightly agreed‘. 60 per cent agreed over the steady
and regular technique of monetary policy (gradualism attitude policy) adoption by the
Central Bank. 20 per cent ‗strongly agreed‘ and the other 20 per cent ‗neither agreed nor
disagreed‘. Majority ‗strongly agreed‘ that there is pressure of rising rents in Dar es
salaam and other commercial hub towns and cities, comprising of 60 per cent of the
respondents. 30 per cents simply ‗agreed‘ and the rest of 10 per cent ‗slightly agreed‘.
Majority ‗strongly agreed‘ over the phenomenon of hyper attitude of citizens in buying
lands and houses though not necessarily developing them, comprising of 60 per cent of
the respondents. 40 per cent simply ‗agreed‘ over the matter.
It was also observed a stark minor difference between those who ‗strongly agreed‘ and
those who ‗agreed‘ by variation of 10 per cent; by 40 percent and 50 per cent
respectively; over the introduction of mortgage law. Those who neither agreed nor
disagreed were 10 per cent. It was found that 20 per cent were optimistic over the
introduction of mortgage law and improvement of current legislation relate to it (those
who ‗strongly agreed‘). 60 percent ‗agreed‘ over it and the rest who ‗slightly agreed‘ and
‗neither agreed nor disagreed‘, both represented a 10 per cent. It was observed that 10
per cent ‗agreed‘ that stock market brokers do drive prices up of major construction
companies. 50 per cent ‗slightly agreed‘, 30 per cent ‗neither agreed nor disagreed‘ and
10 per cent ‗disagreed‘.
117
The study found there is a ‗strongly agreed‘ interrelation as to regard monetary policy
satisfaction and tremendous pressure of rising rents in Dar es salaam by a count of 2
respondents. There is also found interrelationship between monetary policy satisfaction
‗agreed‘ against rising pressure of rent ‗strongly agreed‘ by a count of 3. Bubbles can be
determined when an increase in housing prices is higher than the rise in rents. Rent over
the past 30-years has risen steadily about 3-percent a year whereas between 1997 and
2002 housing prices rose 6-percent a year (in United States). Between 2011 and the
third-quarter of 2013 housing prices rose 5.83-percent and rent increased 2-percent
(Wallison, P. J, 2014). In additional, rising pressure ‗agreed‘ against monetary policy
implementation was observed by a count of 2. This analysis was under cross tabulation;
association of monetary policy regime and house/real estate inflating prices (section 4.5)
5.2 Discussion of Specific Objectives
5.2.1 Traditional monetary policy tools effectiveness in addressing economic
bubble
In section 4.3 - Factor analysis of association of monetary regime and house/real estate
inflating prices, the correlation matrix versus correlation of monetary regime and
house/real estate prices gave convincing results (ratio-scaled data of variables) against
bank rate. There was a good relationship between improvement of mortgage law in
Tanzania and knowledge of operation of money supply and interest rate (0.709). There
was a moderate relationship between hyper attitude of people to buy lands and the
knowledge over money supply and interest rate (0.45).
In section 4.6 – Correlation analysis of Bivariate analysis (measuring of variables;
independent and dependent) we observe a good relationship between a bank rate; low
interest rate is charged to commercial banks thereby pushing high housing prices and
related costs ‗against‘ it is logical when total volume of credit is controlled in the
economy by the Central Bank of Tanzania – with a scale of 0.716. It should be noted
that bank rate cannot always be adjusted to housing market/real estate sector (until a
118
certain right time). Thereby in a period of inactiveness of monetary policy the bubble
keeps on inflating and ultimately burst. This burst leads to a decline of a real economy
which now forces the Central Bank to quickly reduce the bank rate to offset the negative
impacts of the bubble burst. We also see when BoT lower the interest rate there is
unhealthy inflation in Tanzania encouraging high housing prices ‗against‘ it is logical
when total volume of credit is controlled in the economy by the Central Bank of
Tanzania with a scale of 0.833. Finally we observe low interest rates charged to
commercial banks thereby pushing high housing prices and related costs ‗against‘
persuading certain regulations without rigid laws and punishment has proven ineffective
in Tanzania with a scale of 0.644.
Interest rate was constructed in the hypothesis of the study [when BoT lower the interest
rate there is unhealthy inflation in Tanzania encouraging high housing prices]. In the
light of its positive interrelation as was seen under analysis, the hypothesis was accept
[null hypothesis accepted] – as it was seen in section 4.8.2 [analysis of hypothesis of the
study]. Historically, from 2002 until 2012, Tanzania Interest Rate averaged 12.7 Per cent
reaching an all-time high of 21.4 per cent in October of 2007 and a record low of 3.7 Per
cent in December of 2009. In Tanzania, interest rates decisions are taken by the Bank of
Tanzania. The Bank of Tanzania official interest rate is the bank rate.
In section 4.6 – Correlation analysis of Bivariate analysis (measuring of variables;
independent and dependent) we observe an interrelationship between persuading
regulations without rigid laws and punishment has proven ineffective in Tanzania
‗against‘ government and BoT should intervene aggressively to institutions which
accumulates and inflate real estate/house prices with a scale of 0.546.
This moral suasion tool was constructed in the hypothesis of the study [due to high cut
throat competition in the banking and financial sector in general, persuading a certain
regulation without rigid laws and punishment has proven ineffective in Tanzania]. In
119
view of its analysis, the null hypothesis was accepted – as it was seen in section 4.8.3
[analysis of hypothesis of the study]
5.2.2 Supervisory discretion in targeting the activities of individual institutions
In section 4.6 – Correlation analysis of Bivariate analysis (measuring of variables;
independent and dependent) we observe an interrelationship between persuading
regulations without rigid laws and punishment has proven ineffective in Tanzania
‗against‘ government and BoT should intervene aggressively to institutions which
accumulates and inflate real estate/house prices with a scale of 0.546. Financial
supervisors‘ main task is to monitor the behavior and actions of the institutions under
their area of responsibility. They check compliance with the regulatory framework, and
when necessary impose sanctions and enforce them. It is all in an effort to protect the
depositors of these institutions and of other institutions, as well as the taxpayers‘ money
by avoiding or limiting systematic/contagion risks. Unfortunately, if the regulatory
framework is weak, interference of politicians or influencing people is left unchecked or
corruption gets on the way of the process, it disrupts the whole meaning of supervision.
Some have led to question ‗discretion‘ isn‘t enough but rather there should be strict rules
bounded in the process. For by mere discretion we imply one acts on scenario judgement
in monitoring financial institutions which can easily be swept by poor choice of line of
thoughts; which has proven to be a major factor during the 2007/8 global financial crush
Supervisory discretion was constructed in the hypothesis of the study [the central bank
and where possible government should intervene aggressively to the institutions which
possess a threat in a forerunner in accumulating and inflating real estate/house prices.
The null hypothesis was accepted – as it was seen in section 4.8.6 [analysis of
hypothesis of the study]. Supervision of banks and monetary matters in a country is the
responsibility of central bank, and for our case is Bank of Tanzania. In United States,
regulation of financial sector was left minimal - left too independent in a hope that the
free forces of market would sort out the demand and supply; but in the end we all saw
the results in 2007/8 Financial Crises. It is good to argue is the Tanzania financial
120
market left too much relaxed? In 2009 the government of Tanzania injected TZS 1.7
Trillion as a rescue package against the global financial crisis; was this package
sustainable and was it efficiently utilized? If not, then it is another unhealthy ‗quantities‘
of money injected to weaken the TZS strength (that is inflation).
5.2.3 Credit market controls evaluation
In section 4.6 – Correlation analysis of Bivariate analysis (measuring of variables;
independent and dependent) we observe relationship between low interest rates is
charged to commercial banks thereby pushing high housing prices and related costs
‗against‘ it is logical when total volume of credit is controlled in the economy by the
Central Bank of Tanzania with a scale of 0.716. We need to be careful over the trend of
rising prices in that, while some asset prices may look high in Tanzania, we cannot
always characterize them as bubbles: valuations may not be stretched enough and
private sector leverage at times shows signs of decline, not rise. In the emerging world,
notably in Asia, the rise in credit is a cause of concern, but again, with very few
exceptions (notably real estate in Hong Kong), we find prices for liquid assets still to be
in line with fundamentals. Nevertheless, given the ongoing monetary policy support,
Tanzania policymakers have to continue to watch out for potential bubbles – globally
and learn how to infuse the knowledge locally. Again, we observe the relationship
between when BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices ‗against‘ it is logical when total volume of credit is
controlled in the economy by the Central Bank of Tanzania with a scale of 0.833.
This credit market control, was used in the hypothesis [it is logical when total volume of
credit is controlled in the economy by the Central Bank of Tanzania]. The null
hypothesis was accepted in the view of analysis – as it was seen in section 4.8.4
[analysis of hypothesis of the study]. In October 2011, the Central Bank of Tanzania
raised the statutory minimum reserves for commercial banks from 20 to 30 per cent.
This was in an effort to mop up excess liquidity (that is reducing money ‗quantity‘ in the
121
economy). It also lowered the foreign exchange net open position limit for banks from
20 to 10 per cent to curb speculative trading.
A credit market is a marketplace for the exchange of debt securities and short-term
commercial paper. Companies and the government are able to raise funds by allowing
investors to purchase these debt securities.
5.2.4 Establishment of a time varying bank capital ratio
In section 4.6 – Correlation analysis of Bivariate analysis (measuring of variables;
independent and dependent) we noted that as to the regards of BoT controlling capital
flow with prudential purposes, the interval or ratio-scaled data (variables) do not range
closely to -1 or +1 and neither are they exactly -1 or +1; in other words they are too
close to 0.00 which indicates a weak correlation among variables. Negative values
moreover indicate inverse relationship among variables being tested. Thus it was
observed this variable against government and BoT should intervene aggressively to
institutions which accumulate and inflate real estate/house prices giving a scale of -
0.275. The variable (BoT control capital flow with prudential purposes) against total
volume of credit being controlled in the economy by the Central Bank of Tanzania
giving a scale of 0.254. Again, the variable under analysis relationship against
persuading certain regulations without rigid laws and punishment has proven ineffective
in Tanzania giving a scale of 0.310. The variable under analysis gave a scale of 0.489
against low interest rates is charged to commercial banks thereby pushing high housing
prices and related costs. Lastly the relationship between BoT control capital flow with
prudential purposes against when BoT lower the interest rate there is unhealthy inflation
in Tanzania encouraging high housing prices gave a scale of 0.268.
This establishment of a time varying bank capital ratio was used in constructing the
hypothesis [BoT control capital flow with prudential purposes]. In the view of the
122
findings and analysis, the null hypothesis was rejected, and alternative hypothesis was
accepted - as it was seen in section 4.8.5 [analysis of hypothesis of the study].
Time varying bank capital ratio also known as ‗time varying reserve requirement‘ is a
means to control capital flows with prudential purposes.Reserve requirement or cash
reserve ratio sets the minimum fraction of customer deposits and notes that each
commercial bank must hold as reserves (rather than lend out). These required reserves
are normally in the form of cash stored physically in a bank vault (vault cash) or
deposits made with a central bank. In monetary policy, required reserve ratio is used to
influence the country‘s borrowing and interest rates by changing the amount of funds
available for banks to make loans with. When the reserve requirement is adjusted
periodically and varied over time for certain goals such as inflation combating, it is
called ‗time carrying bank capital ratio‘. In macroprudential applications time varying
bank capital ratio is normally advised.
123
CHAPTER SIX
CONCLUSION, IMPLICATIONS, LIMITATIONS, RECOMMENDATIONS
AND FUTURE RESEARCH
6.0 Introduction
This chapter presents a synopsis of this study briefing the theoretical, conceptual and
practical issues as related to the Central Bank and real estate market in Tanzania.
Housing asset bubble in the concept of developing economy like Tanzania is a young
concept, and more to it the housing market muscle of this nation is still yet tender.
6.1 Conclusion
Based on the study findings, researcher concludes that the examination of the contextual
and empirical literature have provided a forecasted future for the monetary policy set up
warnings and corrective areas to the Central Bank of Tanzania. The study finding results
have enriched a new field of monetary policy examination in Africa, and particularly
East African states which have similar economic infrastructures. This study has offered a
light for the policy makers, particularly these challenging times in Tanzania under
constitutional review.
6.2 Implications of the Study
This study has drawn theoretical and policy implications; first from the literature review
and second from the findings themselves. Due to the threat of a weaker monetary policy
may pose to any economy; any weaknesses may be catastrophic like the case of a New
York Wall street saga in 2007. Tanzania has to be keen thereof. Theoretical implications
simply are emphasizing on distribution, sharing and teaching of these findings in
institutions and publication. Policy implications are the diffusion of the study findings
and incorporation of the sense made in the research to the management of financial
institutions, policy makers and issues as reviewed and worked-out by the government.
124
6.3 Limitations of the Study
Due to the nature of the subject in place, not anyone could respond to the study queries.
This is a study which calls for economic experts, particularly in the field of monetary
policy and domestic market. For such phenomenon it was imperative the respondents to
come from the uniquely sample size from Bank of Tanzania, a precise organization to
furnish the research with answers it deserve. This sample had to be small, as experts are
limited in the field and in the organization. Thereby, this led to a use of purposive
sampling which calls for a very limited number of respondents; experts who are obvious
few in Tanzania. There is therefore a risk of biasness in the study; however researcher
took high caution in this. To strengthen the study, a high caution was even designed in
generalization of the results of this study.
There was no challenge in funding of this research in the course of data collection;
however there was a lot of stumbling block as to regard the meeting the experts who are
ever in a run due to either office assignment or office trip. There was a use of online
survey questionnaire to overcome this barrier of meeting up; and at times even this
method proved failure unlike its anticipation.
6.4 Recommendations
The most agreed way of prevention of the bubble effect is for the government to bail the
businesses; but there is a risk of creating unethical practices where businesses may be
sucking government and squeeze every tiny reserve and funds for their own agendas. It
is therefore important for the government like Tanzania to establish serious and strict
policies and regulations to guide business practices.
To an individual;
(i.) One should strictly buy a house with which he/she can afford with traditional
mortgage where you make principal and interest payments at a fixed rate.
125
(ii.) There is a tendency for people to buy lands and expect to sell at higher prices in
the future; this in essence inflates the asset bubble. It is dangerous, though
control can be hard; people need to be aware.
(iii.) Consumers should be keen in buying lands, houses or even renting the artificially
prices of such assets; as doing so is submerging oneself in the economic bubble
disease.
(iv.) A wise consumer (buyer) avoids buying land/house/renting in an area that has
appreciated well above the average rate of appreciation in that area over the past
few years.
(v.) To the government of Tanzania;
(vi.) There should be a control of land evaluations and pricing through the relevant
authorities; perhaps at a moment what is the criteria of valuation and pricing of
lands being used?
(vii.) There is a necessity for establishment of authority in Tanzania to deal with real
estate and housing rents regulations; as at a moment there is none hence
unregulated.
(viii.) ‗Dalalis‘ [local land/house agents] need to be taken seriously as their presence
under unregulated terms frustrates the basic accepted prices of lands/houses/rents
and thus pushes high their values at absurd levels.
(ix.) To the policy makers and local economists;
(x.) They should take cautions over serious monetary policy strategies, as ―The
Jackson Hole Consensus‖ which favored an asymmetric approach responding to
asset bubbles is being challenged at a moment.
(xi.) Macroprudential regulations can be helpful if the policy makers in Tanzania can
design the framework in the context of local economy; instead of administering a
general pain-killer like interest rates regulations.
126
6.5 Future Research Suggestion
There is still much to learn over the full characteristics of asset bubbles, for example
why do they form, why do they burst and who benefits from sharp price increases?
Future researches should take off from here and use the findings found in this research to
enrich themselves from the broader uncertainties of this bubble phenomenon. A good
question to a future researcher is to ask, ―Is Tanzania stuck on a trend of rising prices of
real estate and housing? Or, perhaps the monetary policy can still be well adjusted to
neutralize price hike?
127
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138
APPENDICES
Appendix One: Questionnaire
Questionnaire No. ________
The Extent of Monetary Policy of Tanzania in Precipitating Asset-Bubble in Real Estate/Housing
Market Prices
CASE OF BANK OF TANZANIA [BoT] – HEAD OFFICE, DAR-ES-SALAAM
The data provided in this questionnaire is confidential and will be used for scientific purpose only by the
researcher.
Start Date: ____________________
End Date: _____________________
139
Researcher’s name: Herbert M. Lyimo, Mobile no: 0713480934, E-mail: [email protected]
The series of numbers (with sub-series) you will see in this questionnaire, ranging from 100 to 300 are the
input ID numbers ‗code‘ for the SPSS software and MS Excel which would later be used to manipulate
and calculate various parameters of the responses below.
PART A: General background information (100)
These questions are for statistical purposes used only to interpret your responses on other questions and
for the researcher to draw association. Please put tick [√ ] in the box of the best alternative(s)
(101) What is your gender?
Male
Female
(103) What is your marital status
Si gle
Married
Other (Specify)__________
(102) Whi h f the follow n ateg ries c n
st descr es yo r age?
Below 20years
21-30 years
31-40 years
41-50years
Above 50 years
140
(104) Which alternative is your highest
educational level?
Primary school
Secondary/High school
Certificate/Diploma
Bachelor degree/Advanced Diploma
Master‘s degree
Other level (specify)
________________
(105) What is the name of your office and your job
title?
___________________________________
(106) How long have you been working in your
organization?
Less than 6 months
6 months – 1 year
1-2 years
2-3 years
3-4 years
Above 4 years
141
(107) Which categories can best describe
your financial ability to rent a house?
15,000Tshs/month
20,000-50,000Tshs/month
70,000-200,000Tshs/month
Above 250,000Tshs/month
(108) Do you use agents when buying,
selling or renting a house (home)
Yes
No
If Yes, which among the
al ernative(s) bel w? Please put tick
( ) to the box
Real estate agents
‗Dalalis‘ – house roker
Published so rces
(advertisements)
(109) Do you own a house?
Yes
No
If Yes, which categories can best describe
approximate value of the house that you own?
Below TZS 25 million
TZS 35 – 50 million
TZS 60 - 95 million
TZS 100 – 300 million
142
PART B: How you understand monetary policy of Tanzania.
Your knowledge over real estate and housing market.
How you can associate monetary regime and house/real estate inflating prices – real
estate/housing asset bubble (200)
These questions measures you economic knowledge in developing and emerging economies.
Please indicate your level of agreement with each of the following statements. For each
statement below please circle the number that best describe your view
Code
No.
Construct and its
measurement
items
Strongly
Agree
Agree
Slightly
Agree
Neither
agree
nor
disagree
Slig
htly
Dis
agr
Disagr
ee
Stro
ngly
Disa
gree
Above TZS 400 million
(110) Which categories can best describe your current
ability to rent an apartment?
800,000Tshs/month
900,000-2,000,000Tshs/month
3,000,000-5,000,000Tshs/month
Above 6,000,000Tshs/month
143
ee
(200) Monetary Policy
(201) I am aware of the
policy and tools
Bank of Tanzania
uses to control
money supply and
interest rate
1 2 3 4 5 6 7
(202) I am
knowledgeable
over the operation
of money supply
and interest rate
1 2 3 4 5 6 7
(203) I know about the
monetary and
fiscal policies and
tools of Tanzania
1 2 3 4 5 6 7
(204) I do understand
how monetary
policy of Tanzania
is conducted and I
am satisfied over
the implementation
of its objectives
1 2 3 4 5 6 7
(210) Central Bank of
Tanzania
(211) I perceive BoT is
transparent
1 2 3 4 5 6 7
(212) I recognize BoT is 1 2 3 4 5 6 7
144
autonomous and
independent from
the government
interventions
(213) BoT should follow
the lead of
financial markets
1 2 3 4 5 6 7
(214) It is logical for
BoT to adopt
gradualism attitude
(steady and regular
techniques) in the
housing market
asset bubble
circumstance at a
moment
1 2 3 4 5 6 7
(220) Real
estate/housing
market
(221) I feel the
tremendous
pressure of rising
rents in Dar-es-
salaam (and other
regions)
1 2 3 4 5 6 7
(222) People have a
hyper attitude to
buy lands in
Tanzania even
though not
1 2 3 4 5 6 7
145
necessarily
developing it
(223) Investors are
overly optimistic
in investing in real
estate market now
in Dar es salaam
and elsewhere
1 2 3 4 5 6 7
(224) Improvement of
mortgage law in
Tanzania is
presently (and will
in the future)
accelerate real
estate industry and
housing
constructions
1 2 3 4 5 6 7
(230) Real
estate/housing
market bubble
(231) Prices are
temporarily high in
real estate/house
market
1 2 3 4 5 6 7
(232) I know there is a
basis for a current
estimation of real
estate/housing
prices value
1 2 3 4 5 6 7
(233) I closely associate 1 2 3 4 5 6 7
146
the high money
supply with
current interest
rates keeps
pushing up the
housing market
prices
(234) Prices are
permanently high
in real
estate/housing
market in Tanzania
1 2 3 4 5 6 7
(235) In Dar-es-salaam
Stock Exchange
(DSE) market
stock brokers
speculation
negatively affect
construction
industry by driving
stock of major
companies of the
economy, cement
companies and
associated sectors
1 2 3 4 5 6 7
PART C: The extent of monetary policy of Tanzania in precipitating asset bubble in real
estate/housing market (300)
147
These are units of analysis as described in chapter three. They are also research questions
described in chapter one of the research paper. The ‘Ho’ as seen in the series of questions
are the hypotheses selected to be tested as explained in chapter two.The ‘n/q’ are the
supplementary questions, which are not included in objectives/variables/research questions.
Please indicate your level of agreement with each of the following statements. For each
statement below please circle the number that best describe your view
Code
No.
Construct and its
measurement items
Strongly
Agree
Agree
Slightly
Agree
Neither
agree nor
disagree
Slight
ly
Disag
ree
Disagre
e
Stron
gly
Disag
ree
(300) Effectively
administering bank
rate tool
(301) Bank of Tanzania
(BoT) is positively
utilizing this tool
1 2 3 4 5 6 7
(302)
[Ho]
When BoT lower the
interest rate there is
unhealthy inflation in
Tanzania
encouraging high
housing prices
1 2 3 4 5 6 7
(303) The economy of
Tanzania is
dominated with high
money supply
leading to increasing
economic activities
1 2 3 4 5 6 7
(304) There is a high real
estate/house prices
1 2 3 4 5 6 7
148
because of set-up of
bank rate tool; which
encourage high
lending by the banks,
high debts and high
spending in
economic activities
like construction.
(310) Assessing addressing of reserve requirements and
discount rate tool
(311) The amount of funds that commercial banks hold in
reserve against specified liabilities is low at Bot,
explaining the high inflation in the Tanzania economy.
1 2 3 4 5 6 7
(312)
[Ho]
The low interest rate charged to commercial banks and
other depository institutions on loans they receive from
BoT encourage high money supply resulting into
inflationary tendencies giving negative effect in
housing market prices.
1 2 3 4 5 6 7
(313) The need to solve the liquidity problem (lack of
money to businesses) gives birth to unnecessary excess
liquidity in Tanzania economy.
1 2 3 4 5 6 7
(314) Commercial banks in Tanzania get cheap loans from
BoT
1 2 3 4 5 6 7
(320) Investigating feedback on moral suasion tool
(321) The banks and other financial institutions comply over the
proclaimed BoT agendas by moral appeal.
1 2 3 4 5 6 7
(322) There is probably a legal coercion by the government and
BoT against financial institutions over cooperation in certain
1 2 3 4 5 6 7
149
areas.
(323)
[Ho]
Due to high cut throat competition in the banking and
financial sector in general, persuading a certain regulation
without rigid laws and punishment has proven ineffective in
Tanzania.
1 2 3 4 5 6 7
(324) BoT and government if can openly discuss with the market
over its ranges of appropriate values for its currency may
positively impact the trading of the currency.
(325) The publication of BoT over the information regarding
monetary and fiscal policy, tools and objectives with their
implementations in the easily understood language to the
population can flourish citizens‘ behavior over monetary
policy reaction.
1 2 3 4 5 6 7
(330) Evaluate credit market controls in the market
(331)
[Ho]
It is logical when total volume of credit is controlled in the
economy by the Central Bank of Tanzania
1 2 3 4 5 6 7
(332) It is necessary that BoT should intervene in regard to the
purpose for which the credit is used in the economy; starting
with commercial banks.
1 2 3 4 5 6 7
(333) You should be involved when BoT formulates a specific
policy, such as to expand or contract the money supply in the
economy
1 2 3 4 5 6 7
(340)
[n/q]
Consideration of changes in stock market margin
requirement in DSE market
(341) If there is tax amnesty for the companies listed in Dar-es-
salaam stock exchange (DSE), this can greatly contribute to
expansion of stock market in Tanzania
1 2 3 4 5 6 7
(342)
[Ho]
In case housing market bubble burst in Tanzania, DSE
market will contract, people will receive margin calls; they
1 2 3 4 5 6 7
150
will have to deliver more money to their brokers or their
shares would be sold. In consequent stock market will be
affected leading to even its crush.
(350) Assessing establishment of time varying bank capital ratio
(351)
[Ho]
BoT control capital flow with prudential
purposes.
1 2 3 4 5 6 7
(360)
[n/q]
Monitoring of credit-to-GDP ratio
(361 The difference between the credit-to-GDP ratio and its
long-term trend is widening in Tanzania. This is an early
indicator for banking crises.
1 2 3 4 5 6 7
(370) Necessity of supervision discretion to individual
institutions
(371) Financial institution need to continue to express
confidence to its depositors; reducing unnecessary losses
and systematic risks which can partly be achieved by BoT
supervision.
1 2 3 4 5 6 7
(372)
[Ho]
The Central Bank and where possible government should
intervene aggressively to the institution(s) which possess a
threat in a forerunner in accumulating and inflating real
estate/house prices.
1 2 3 4 5 6 7
(373) By entertaining so called ‗discretion‘ in supervisory of
financial and related sectors touching the real
estate/housing market in Tanzania we are also embracing
corruption. Hiding potential details from the public has a
strong correlation in collusion of personal interest.
1 2 3 4 5 6 7
151
NB:
This questionnaire is also available online for online survey. The link address is:
http://kwiksurveys.com/s.asp?sid=ckzgy4dbgnt0nnh327177. This link can be visited by
anyone either from a mobile device or a personal computer and respond to
questionnaire; available from 21st March to 21 September 2014 (6 months).
Appendix Two: Macroprudential regulation
In the financial crisis of 2007/8, policy makers started a debate that has changed the way
monetary policy is being viewed now. The term macroprudential regulation
characterizes the approach to financial regulation aimed to alleviate the risk of the
financial system as a whole (or "systemic risk").
Objectives and justification of macroprudential regulation
The main goal of macroprudential regulation is to reduce the risk and the
macroeconomic costs of financial instability. It is recognized as a necessary ingredient to
fill the gap between macroeconomic policy and the traditional microprudential
regulation of financial institutions.39
The macro and microprudential perspectives: understanding the difference
The macro- and microprudential perspectives differ in terms of their objectives and
understanding on the nature of risk. Traditional microprudential regulation seeks to
enhance the safety and soundness of individual financial institutions, as opposed to the
macroprudential view which focuses on welfare of the financial system as a whole.
Further, risk is taken as exogenous under the microprudential perspective, in the sense of
assuming that any potential shock triggering a financial crisis has its origin beyond the
39 Bank of England (2009). The role of macroprudential policy. Bank of England Discussion Paper,
November
152
behavior of the financial system. The macroprudential approach, on the other hand,
recognizes that risk factors may configure endogenously, i.e. as a systemic phenomenon.
In line with this reasoning, macroprudential policy addresses the interconnectedness of
individual financial institutions and markets, as well as their common exposure to
economic risk factors. It also focuses on the procyclical behavior of the financial system
in the effort to foster its stability.
Macroprudential vs Microprudential
Differences between macro- and microprudential approaches (Source: C. Borio, 2003)
153
Appendix 3: Budget for the Research
Costs to be incurred are as follows:
Budget for Research
S/N
Particular
Quantity
Amount (in TZS) 1 Equipme
nt (a)
Laptop
1 1,000,000 (b
) Camera(sill picture)
1 600,000
2 Material (a
) Stationery
500,000 (b
) Secretarial services
200,000
3 Transport allowance
1,000,000
4 Meals and Accommodation (a
) Meals
500,000 (b
) Accommodation
1,000,000
5 Communication (a
) Airtime
500,000 (b
) Postage (mail)
100,000 C
) Courier
100,000 (d
) Internet
200,000
TOTAL
5,700,000
Central Bank and Real Estate Market in Tanzania
154
Appendix f3: Time schedule of Research
Duration and the timeline for major activities
Time Period: 8 Months and 17 days.
155
Appendix 5: Concept Note
“The Extent of Monetary Policy of Tanzania in precipitating asset bubble in real
estate/housing market prices”
Case Study: Bank of Tanzania (BOT)
By Herbert Maximillian Lyimo
Year: 2012-2014
Master’s of Business Administration (MBA) – Corporate Management (CM)
1. Research Title: ―The Extent of Monetary Policy of Tanzania in precipitating asset
bubble in real estate/housing market prices‖
2. Thematic Area: Monetary Policy and Economic Bubble [Managerial
Economics]
3. Research Problem
(a) What a researcher/investigator want to find out?
The 2008 Global Financial and Economic crisis started in September 2008 in United
States of America, where there was shortage of money in the country‘s economy leading
to inefficient service by the commercial banks towards the citizens. There was no
enough money to be lent to the businesses and thus commerce started to shrink. The real
estates companies in Tanzania are engaged in massive projects of building commercial
and home residential apartments. The normal citizens are also in much hyper than ever
in everyday ticking hours to either buy new plots someplace, somewhere, and friends
excite one another every now and then over housing ownership. The landlords are not
too far from the truth, they raise rents everyday giving headaches to occupants. We all
know, as long as one has spent several years in Tanzania, especially in Dar-es-salaam,
156
Mwanza and Arusha how recent years housing construction at family and commercial
levels have risen! This is not bad sign in an economic eye-ball, it is very supportive, but
the million dollar question is that, is this maniac and overexcitement a progressive trend
to Tanzanians or perhaps somewhere monetary policy in Tanzania is too lax? If so what
does it mean or at least what does the future suggest? Should we assume there is
unhealthy inflation in the midst of Tanzanian economy that is why we have excess
money to flow in this hyper fashion of buying lands or building house? What if we are
getting false alarm in this sudden race of aggressively purchase plots and house and rent
homes?
(b) What will be known after doing this research?
The global financial crises changed the way we think about the global economic order
leading to doubting the principles and practices that were once accepted. For the
developing world, that conceptual uncertainty is particularly uncomfortable, and we
have witnessed the various policies in Tanzania bringing confusion and debate. The
current times where the bubble is growing (has not burst yet) it is prudent for the Central
Bank of Tanzania to avoid any rush decisions. This is because as the bubble build-up it
takes years until a visual pattern is noticed, making it hard to identify and predict the
magnitude of the bubble. Supervision of banks and monetary matters in a country is the
responsibility of central bank, and for our case is Bank of Tanzania. In United States,
regulation of financial sector was left minimal - left too independent in a hope that the
free forces of market would sort out the demand and supply; but in the end we all saw
the results – Global financial collapse of 2007/8.
The growth rate of the sector increased to 11.9% in 2005/06 from 10.8% in 2004/05 and
the contribution of construction activity to the overall GDP rose to 5.7% in 2005/06
compared to a contribution of 5.4% in 2004/05. In 2005/06, the total government
expenditure for construction affairs and services was TZS 53,425 million compared to
the expenditures in 2004/05 which were estimated to be TZS 58,693 million and the
157
expenditures in 2003/04 which were estimated to be TZS 29,740 million. Looking also
at the figures in cement consumption in Tanzania; in 2006, the cement production rose
by more than 9% in just the first quarter, whereby in 2005 the total combined output of
the three major cement companies (TWIGA cement, Tanga Cement Company [SIMBA]
and Mbeya Cement Company) reached 1.6 million tonnes. Perhaps a glimpse of near
future where Tanzania is heading in housing market and real estate development, or
rather where we have recently began is by appreciating the government bold move in the
setting and developing a New Kigamboni City. The government has set up an agency
called Kigamboni Development Agency (KDA) which manages the Kigamboni City
Project in three phases; 2012-2022, 2022-2027 and 2027-2032. The project is expected
to cost about TZS 11.6 trillion upon completion in year 2032. Most built houses and land
are increasingly becoming untouchable for the poor majority as their talks are in US
Dollars and exceedingly expensive. Housing as it seems to be basic factor worldwide, in
Tanzania it is so, but more to that is a great pride and hallowed asset. Many decent
houses in the city charges from $1500 to $16,000 per month, far more expensive than
some of advanced economies known cities.
(c) What is the research question?
What is the extent of the monetary policy of Tanzania precipitating asset-bubble in real-
estate/housing market prices?
4. Background
Monetary policy that increases the supply of money (expansionary policy) leads to
reduction in interest rates, stimulate the consumption and investment in the economy.
Increased consumption and investment mean higher aggregate demand as well as
increased personal income and employment. This all translates into ability to rent,
purchase and sell houses/apartment. Tanzania is in the heights of high inflation, meaning
there is plenty of money in circulation which clearly explains the use of BOT
contractionary policy at a moment. Inflation is not always a bad thing especially if it is
158
on a short-run; it may suggest there is injection of some money ‗quantities‘ in the
economy due to supposedly discovery of new sources of raw materials, energy and
minerals. This is what has undoubtedly taken place in Tanzania giving citizens and
private sector‘s power to drive real estate/housing market to high new unimaginable
levels. In financial year 2010/11, government allocated 13 per cent of expenditure
budget to infrastructure. Construction industry by 2009 accounted to 7.9 per cent of
GDP, growing at a rate of 7.5 per cent and by 2010 it employed about 9 per cent of
Tanzania workforce (UNESCO, August 2010). There were 2,621 projects worth nearly
TZS 2.4 Trillion during 2009. Contractors Registration Board (CRB) of Tanzania in
2009 registered 930 applicants compared to 656, 662 and 608 in 2008, 2007 and 2006
respectively. Some 33 of the newly registered contractors were foreign leading to a total
of 236 foreign contractors in the country which was 4.1 per cent of the total contractors
in the CRB register compared to 3.6 per cent in 2009. According to National Housing
Corporation (NHC), Tanzania runs a housing deficit estimated at 3 million units valued
at $180 billion by the end of 2007, while the current annual demand for houses in urban
areas is 200,000 units estimated to cost $12 billion. This statistical figure can help a
reader to understand that we shouldn‘t expect a threatening burst of a bubble like the one
in United States or Europe. But just because the housing market in Tanzania is small and
immature we cannot be naïve to ignore the subject matter in our thoughts and minds.
5. Objectives and Hypothesis
Objective
Evaluating the extent of the monetary policy of Tanzania in advancing asset-bubble in
real-estate/housing market prices.
Hypothesis
Ho = When BoT lower the interest rate there is unhealthy inflation in Tanzania
encouraging high housing prices
159
Ho = The low interest rate charged to commercial banks and other depository institutions
on loans they receive from BoT encourage high money supply resulting into inflationary
tendencies giving negative effect in housing market prices
Ho = Due to high cut throat competition in the banking and financial sector in general,
persuading a certain regulation without rigid laws and punishment has proven ineffective
in Tanzania.
Ho = It is logical when total volume of credit is controlled in the economy by the Central
Bank of Tanzania
Ho = BoT control capital flow with prudential purposes.
Ho = The Central Bank and where possible government should intervene aggressively to
the institution(s) which possess a threat in a forerunner in accumulating and inflating
real estate/house prices.
6. Methodology
This research is highly quantitative than qualitative based on measurement of variables
of highly econometric applications. Primary data in this research will be gathered
through interviews and questionnaire. Secondary data will be gathered from organization
brochures, website, journals, textual and empirical literature and other factual
documents. The research design to be employed will be a case study. The source of data
will be from Bank of Tanzania (BOT), situated at Dar-es-salaam - Tanzania. However,
other sources may come handy to supplement the data if the researcher shall see it fit.
These areas may include Tanzania Ministry of Finance and Economic Affairs, Dar-es-
salaam Stock Exchange (DSE) and National Housing Corporation (NHC) both situated
in Dar-es-salaam. There other group of data pertinent to the study if the researcher may
deem fit include; Imalaseko Supermarket, Knight Frank and Tanzania Ministry of Lands
160
and Human Settlements Development. Interesting sector that can enrich this research is
the banking industry which may be approach also to supplement information.
Methods of data collection will be Questionnaire and Interview. These methods makes
basis for a primary data usage Social media will also be involved for engaging important
discussions and collection of data. There will be a link posted to social sites and
distributed to emails for online. The link address for survey is:
http://kwiksurveys.com/s.asp?sid=ckzgy4dbgnt0nnh327177. This link can be visited by
anyone either from a mobile device or a personal computer and respond to
questionnaire; available from 21st March to 21 September 2014 (6 months). The study
population of this research is finite, which is by understanding that BOT (Dar-es-salaam,
Head Office) has fixed number of employees. Sample size for the research is fifteen
(15). This research will use non-probability sampling - ‗judgmental/purposive‘
sampling, where a sample will be chosen on who are appropriate for the study (focusing
on the expertise of selected individuals). Data of this proposal will be edited data
through two procedures; field editing and office editing. The data will be compiled by
data editing, data coding and data tabulation. Data analysis will be conducted by the use
of Statistical Package for the Social Scientists (SPSS) which will provide descriptive
statistical data. MS Excel will too be incorporated to obtain a summary of regression and
the linear regression model.
Unit of analysis
Units of analysis are factor influencing asset - housing bubble inflation, which include;
(i.) Effectively administer bank rate tool.
(ii.) Assessing addressing of reserve requirements and discount rate tool
(iii.) Investigating feedback of moral suasion tool.
(iv.) d. Evaluate credit market controls in the market.
(v.) Consideration of changes in stock market margin requirement in DSE
(vi.) Assessing establishment of time varying bank capital ratio
(vii.) Monitoring of a credit-to-GDP ratio
161
(viii.) Necessity of supervision discretion to individual institutions.
Expected outputs and outcomes of research proposal
This proposal shall be acknowledged and recognized by the government of republic of
Tanzania and interested stakeholders. It is the researcher‘s upper most expectation that
the various stakeholders like the Tanzania Ministry of Finance, Bank of Tanzania
(BOT), Ministry of Lands and Human Settlements Development and Dar-es-Salaam
Stock Exchange (DSE) will apply the knowledge gathered later (in the report) for the
country‘s benefits. This research is based on a notion that upon understanding the strong
link between real estate/housing market asset bubbles at a moment and the loopholes of
monetary policy, measures can be taken to correct the effects which are still building up
that may cripple the economy of Tanzania.
Research Timeframe
Duration and the timeline for major activities
Time Period: 8 Months and 17 days.
162
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