The determinants of terrace housing rates in malaysia

THE DETERMINANTS

OF TERRACE

HOUSING RATES IN

MALAYSIA1st Presenter: ASMA LIYANA JA’AFAR

2014838744

2nd Presenter: SYAHIRAH AMIRA MD. DIN

2014223624

3rd Presenter: AMIRUL NIZAM MOKHTAR

2014604954

OUTLINES 1.0

INTRODUCTION

Problem Statements

RQ & RO

Significance of Study

Limitation of Study

Scopes of Study

Definition of Terms

LITERATURE

METHODOLOGY

DISCUSSION

INTRODUCTION

Average housing prices in Malaysia increases up to 20% per

year after year 2007 (Tze San Ong,2013).

Terrace housing industry is very salient beneficial to Malaysia

especially in the process of becoming a developed country

(Jarad, 2010).

Government identifies that terrace housing is a basic need for

every citizen.

Housing scheme (PR1MA).

Malaysia’s Property Market

Slowing

Global Property Guide. (2014, June 15). Malaysia's PropertyMarket Slowing. Retrieved from Global Property Guide:http://www.globalpropertyguide.com/Asia/malaysia/Price-History

Malaysia’s nationwide houseprices rose to RM276,668

Nominal (red line): Excludesmacroeconomic factors

Real (blue line): Includesmacroeconomic factors

PROBLEM STATEMENTS

Rapid economic development has resulted in an increasing

demand in Malaysia.

The price of house increasing dramatically, which has affected

the decision making for house buyers.

This is a worrying trend for lenders and brings out a big issue. (Tze

San Ong, 2013)

Been a major problem for Malaysian middle-class incomers.

Average monthly household income increase to RM5,900 from

RM5,000 in 2012. (Malay Mail Online, 2014)

Median household income for 2014 is RM4,258 compared to

2012, RM3,626. (Malay Mail Online, 2014)

Affordability of Middle-Income

Earner & Average House Prices

Dr W. N. Azriyati, A. P. (2009). Affordability Compared to Mean Housing Price For Current Middle Income Home Owners. A Study on Affordable Housing Within The Middle Income Households in The Major Cities and Towns in Malaysia, 15.

Aidila, C. (2011, May 12). Rising House Prices Create Homeless Generation. Retrieved from Malaysia Kini: www.malaysiakini.com/news/163963

RESEARCH QUESTIONS &

RESEARCH OBJECTIVES

RESEARCH QUESTIONS

• Does terrace housing rates in

Malaysia increase when Foreign

Direct Investment (FDI) increases?

• Does increase in inflation rate

influenced the increased of

terrace housing rates in

Malaysia?

• When population growth rates

increase, does terrace housing

rate in Malaysia increases?

RESEARCH OBJECTIVES

• To identify the relationship

between Foreign Direct

Investment (FDI) with terrace

housing rates in Malaysia.

• To examine the relationship

between inflation rate with

terrace housing rates in Malaysia.

• To study the relationship between

population growth rates with

terrace housing rates in Malaysia.

SIGNIFICANCE OF STUDY

Researchers & Academicians

Government policy

Banking sector

LIMITATION OF STUDY

Availability of data

Data is available but the components are

comprehensive. Some data collected were not properly

in quarterly basis.

SCOPE OF STUDY

Identify the determinants of housing rates in Malaysia

using four theories.

Selected macroeconomic variables.

Secondary data (BNM, MIDA, DOSM & World Bank).

Quarterly basis (30 data).

Period Q3 2006 – Q4 2013.

DEFINITION OF TERMS

• Labour in various specialty in construction, material costs, and investment which can influence the property rates.

Foreign Direct Investment (FDI)

• Immediate increase in price of such “store of value” real assets that directly influence the housing rate.

Inflation rate

• Indicates that the demand for the housing is high when the population is increases.

Population growth rate

OUTLINES 2.0

INTRODUCTION

LITERATURE

Literature Review

Underpinning Theories

Research Framework

Hypothesis Statement

METHODOLOGY

DISCUSSION

LITERATURE

REVIEW

FOREIGN DIRECT INVESTMENT

(FDI) When the developer runs FDI, it will affect the cost incurred to be

increased and this will lead to upturn of property price which will

be a major problem to the purchaser (MacDonald, 2010).

Another studies conducted by David (2010) found something

more which stated that when the developer used foreign

investment on workers at low-cost property building, it is not really

appropriate as trade barriers for investment exist as uncertainty.

These correlation drawback between FDI and workers which

increase the housing price is called the shadow house price.

Wang (2013), in the other hand found the extra finding of the

impact of FDI on house price was greater than that of house price

on FDI.

INFLATION RATE An increase in the expected rate of inflation causes an immediate

increased in the relative price of such "store of value" real assets

(Felstein, 1983). So, when cost of building increase, of course the

developer will tend to charge higher price for their terrace housing

property to the purchaser. The research done by Piazzesi and

Schneider (2009) made an extension from the previous study which

commended that higher the expected inflation tends to lead to an

increase in the price-dividend ration on houses. Another finding

from McBride (2013) supported this variable which indicated that

when inflation is high, the cost of buying a home increases as

lenders raise interest rates to curb inflation. As the dollar loses some

of its purchasing power with a rise in inflation, any savings have to

put aside for a down payment loses value as well.

POPULATION GROWTH RATE

According to Ley (2010) and Ong (2013), agreed that housing prices are

related to the population. A study done stated that an increase in the

population in Malaysia increases the housing demand and therefore

increases the housing price. If there is a greater demand than a supply for

housing, it will affect the housing price too. When there are fewer houses in

the market, people are willing to spend more money to buy a house. This will

cause the housing price to increase. Another study conducted by The

finding by Swann (2013) go beyond the previous research by indicated that

the overall direction of population growth and housing increase is however

jointly upward, and population remains a major determinant of housing

requirement. This is strengthen by Pettinger (2014), emphasized that if supply

of housing fails to meet the growth in the number of households, it will

increase the cost of living, house prices and the cost of renting. This shortfall

is causing an increase in long-term house prices, reducing affordability.

UNDERPINNING THEORIES Demand and Supply Theory (Marshall, 1890)

This theory is used to determine the price of market product or services .

Quantity demanded is the amount of the good that buyers are willing to

purchase and quantity supply is the amount that sellers are willing to sell in

the market.

Maslow Hierarchy of Needs (Maslow, 1943)

This theory represented the human’s physiological needs as the base of

a triangle to show that meeting these needs are the most important in our

lives; shelter or house is one of the requirements for addressing the

physiological needs.

Quantity Theory of Money (Fisher, 1867)

The quantity theory of money states that there is a direct relationship

between the quantity of money in an economy and the level of prices of

goods and services sold.

FDI Macro-Micro Level Theory (Hymer, 1976)

The macro-level FDI theories give the macroeconomic factors that

determine the FDI and micro-level theories discuss the motivation of FDI

associated with the firm level.

RESEARCH FRAMEWORK

Foreign Direct Investment

(FDI)

Inflation Rate

Population Growth Rate

Terrace Housing

Rate

INDEPENDENT VARIABLES DEPENDENT VARIABLE

HYPOTHESIS STATEMENTS

Foreign Direct Investment (FDI)

H1: If FDI is high, then the terrace housing rates in Malaysia will

increase.

Inflation rate

H1: If inflation rate is high, then the terrace housing rates in

Malaysia will increase.

Population growth rate

H1: If population growth rate is high, then the terrace housing

rates in Malaysia will increase.

OUTLINES 3.0 INTRODUCTION

LITERATURE

METHODOLOGY

Research design

Data collection method

Regression Flows

Unit Root Test

Normality Test

Auto-Correlation Test

Multicollinearity Test

Correlation Test

Multiple Regression – Findings

DISCUSSION

RESEARCH DESIGN

Purpose of study – Causal study/Hypothesis testing

Type of investigation - Correlation

Study setting – Non-contrived

Time horizon - Longitudinal

Unit of analysis - Macro economy

DATA COLLECTION METHOD

Secondary data

Retrieved from Bank Negara Malaysia,

Department of Statistics Malaysia, MIDA & World

Bank

Using 30 data start from Quarter 3, 2006 until

Quarter 4, 2013

Journals retrieved from Emerald, UiTM Ez Access

and Google Scholar

Regression Flows

Secondary Data Collected

Unit Root Test

Multiple Regression

Analysis• F-test

• R-squared

• Significant Level

Correlation Test

Multicollinearity Test

Normality Test

Auto-Correlation TestControlling

Variables

Unit Root Test

A condition with a constant mean, constant variance,

and constant auto-covariances for each given lag.

Variables5% Significant at

Level (intercept)

5% Significant at

1st Difference

(intercept)

Housing Price

Indicator (Y)0.7609 0.0000

Foreign Direct

Investment (X1)0.3212 0.0003

Inflation Rate

(X2)0.4133 0.0128

Population

Growth Rate

(X3)

0.3731 0.0001

The data has no unit root

Normality Test Determine whether error term is normally distributed

The error term is normally distributed > 5%

Auto-Correlation Test To investigate whether there is a serial independence

for the error term

Breusch-Godfrey Serial Correlation LM Test:

F-statistic 3.986378 Prob. F(2,23) 0.0326

Obs*R-

squared7.464945

Prob. Chi-

Square(2)0.0239

Error term is serially independent > 5%

Multicollinearity Test

Whether independent variables are highly correlated

with each other or not

Independent VariablesCentered Variation

Inflation Factor

Foreign Direct Investment

(X1)1.224135

Inflation Rate (X2) 1.233808

Population Growth Rate

(X3)1.051758

There is no multicollinearity problem < 10 value

Correlation Test

If there exists any linear relationship or correlation of

the dependent variable with any of the independent

variable

There is a correlation < 5%

P-Value of T- Statistic

Foreign

Direct

Investment

(X1)

Inflation

Rate (X2)

Population

Growth

Rate (X3)

Housing

Price

Indicator

(Y)

0.420155 0.020211 0.733684

Multiple Regression - FindingsVariable Coefficient Std. Error t-Statistic Prob.

C 31.39395 4.859412 6.460443 0.0000

Foreign Direct

Investment0.839862 0.285685 2.939816 0.0070

Inflation Rate -0.186718 0.316382 -0.590168 0.5604

Population Growth

Rate-15.95356 2.784843 -5.728710 0.0000

R-squared 0.661821

Prob. F-statistic 0.000004

Most Significant : Population Growth Rate

Independent Variables

Hypothesis FindingsRelationship with

DV

Foreign Direct Investment

If FDI is high, then the terracehousing rates in Malaysia willincrease

Significant at 5%

Confidencelevel

Directly Proportional

Inflation Rate

If inflation rate is high, thenthe terrace housing rates inMalaysia will increase

Not Significant at 5%

Confidencelevel

-

Population Growth Rate

If population growth rate ishigh, then the terracehousing rates in Malaysia willincrease

Significant at 5%

Confidencelevel

Inversely Related

OUTLINES 4.0

INTRODUCTION

LITERATURE

METHODOLOGY

DISCUSSION

DISCUSSION

For future research undertakings, we recommend that the

researcher:

To use panel data, varies in term of geographical area (etc

urban/rural).

To use data period on yearly basis (widen the spurious

regression).

Using currency value instead of rate of percentage for

dependent variable.