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1 DEPARTMENT OF AGRICULTURAL ECONOMICS, UNIVERSITY OF AGRICULTURAL SCIENCES, GKVK, BANGALORE - 560065 Seminar Report On Curse of Natural Resources SUBMITTED TO: DR. G. S. MAHADEVAIAH, SHRI HONNAIAH, SEMINAR TEACHERS SUBMITTED BY: GOURAV KUMAR VANI PALB2103 Sr. M. SC. (AGRI.)
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DEPARTMENT OF AGRICULTURAL ECONOMICS,

UNIVERSITY OF AGRICULTURAL SCIENCES,

GKVK, BANGALORE - 560065

Seminar Report

On

Curse of Natural Resources

SUBMITTED TO:

DR. G. S. MAHADEVAIAH,

SHRI HONNAIAH,

SEMINAR TEACHERS

SUBMITTED BY:

GOURAV KUMAR VANI

PALB2103

Sr. M. SC. (AGRI.)

DEPT. OF AGRICULTURAL ECONOMICS

UAS, GKVK, BENGALURU – 560065

DATE: 01-03-2014 SEMINAR NO. -2

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CONTENT

SL. No. PARTICULARS PAGE NO. 1 INTRODUCTION 3-42 CURSE OF NATURAL RESOURCES 43 DUTCH DISEASE 84 CASE STUDY 8-135 SYMPTOMS/ CONSEQUENCES OF

RESOURCE CURSE12-20

6 CRITICISM AGAINST THE RESOURCE CURSE

20-21

7 HOW TO AVOID RESOURCE CURSE 218. REFERENCES 229. APPENDIX 22

Content of Figures and Tables

SL. No. PARTICULARS PAGE NO.

1 Figure No. 1 52 Figure No. 2 63 Figure No. 3 74 Table No. 1 95 Table No. 2 116 Table No. 3 127 Table No. 4 138 Table No. 5 169 Table No. 6 179 Table No. 7 1810 Table No. 8 20

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“Ten Years from now, twenty years from now, you will see: oil bring us ruin….. Oil is devil’s excrement”.

- Venezuelan Politician Juan Pablo Perez Alfonzo’s view on oil discovered in his country during early 1970’s, He was one of the founding member of OPEC and minister of minerals and Hydrocarbons in second democratic government of Venezuela.

1. INTRODUCTION

One of the surprising features of economic life is that resource poor economies often vastly outperform resource rich economies in economic growth. Here resources mean Agriculture, Minerals, Forest and Fuels. History speaks to us for many such examples. Some of the examples cited in research papers are

• In 17th century, resource-poor Netherland eclipsed Spain, despite the overflow of gold and silver from the Spanish colonies to the New World.

• In the 19th and 20th centuries, resource-poor countries such as Switzerland and Japan surged ahead of resource-abundant economies of Russia.

• In post 2nd world war scenario, star performers had been resource-poor Newly Industrializing Economies of East Asia-Korea, Taiwan, Hong Kong and Singapore while many resource-rich economies such as the oil-rich countries of Mexico, Nigeria and Venezuela , had gone bankrupt.

From Figure No. 1, it can be observed that those countries where mining as percentage of GDP exceeded 25percent had weak manufacturing base with some exceptions like Venezuela and Brunei Darussalam. This list includes most of the underdeveloped countries. On the other hand, there are countries where mining as value added to GDP is very low but (less than 25 percent) but has very strong manufacturing base. This list includes all the top ten economies, other developed and developing economies including Indonesia.

From Figure No. 2, it is evident that in the economies where agriculture exceed 25 percent of GDP in economy, manufacturing has remained weak i.e. share of manufacturing sector in economy is less than or equal to 10 percent of GDP.

From Figure No. 3, it can be concluded that those economies where there is abundance of natural resources (contribution of agriculture and mining to GDP is high) in such economies manufacturing base remains weak. List of such countries includes Nigeria, Angola, Saudi Arabia, Cong Democratic Republic, Azerbaijan, Trinidad & Tobago, UAE, Kenya, Venezuela, Brunei Darussalam, Mauritania and Bhutan. It also looks surprising that these economies end up with lower GDP than those countries with poor intensity of natural resources. For example Saudi Arabia, UAE, Venezuela, Nigeria, Angola, Kenya and Congo DR are ranked 20, 28, 33, 39, 60, 88 and 115th in the world economy according to the size of

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their GDP as against resource poor Japan and Germany which are ranked 3rd and 4th largest economy in the world. India here is a mixed example having high proportion of natural resource dependence (> 25 percent) but still has better proportion of manufacturing sector in economy as compared to developed economies.

This conclusion leads us to a puzzle that though natural resources increase wealth and purchasing power over imports, so that resource abundance might be expected to raise an economy’s investment and growth rates as well. But reality manifests a much different scenario which is called Curse of Natural Resources or Resource Curse.

2. CURSE OF NATURAL RESOURCES

Definition: According to Wikipedia “Paradox that countries and regions with an abundance of natural resources, specifically point-source non renewable resources like minerals and fuels, tend to have less economic growth and worse development outcomes than countries with fewer natural resources”.

First described by Richard M. Auty in 1990 in his book “Resource Based Industrialization: sowing the oil in Eight Developing countries”. He coined this term in 1993. This term is alternatively called as “Paradox of Plenty”. First observation of Resource Curse was made in 1960’s when Dutch Disease was observed in Netherland.

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Source: Author

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Source: Author

Countries with high proportion of agriculture in economy with very low manufacturing base.

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Source: Author

Countries with high natural resource intentsity

Countries with less natural resource intensity

Extreme case

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3. DUTCH DISEASE

“THE ECONOMIST” magazine coined this term in 1977. Massive Natural gas field was discovered in Groningen, Netherland in 1959. The country wanted to profit from this gas by exporting it. With the Govt. focus primarily on development of new gas field all the problem started to increase. Too much concentration on new gas field and neglect of manufacturing sector led to slowing down of manufacturing growth.

Natural Gas export started to increase but with trade surplus created by increased export, Dutch Currency started to appreciatei against the foreign currencies leading to loss in export competitiveness. Compared to manufacturing sector, Natural Gas exploration, development and extraction employ less no. of labourers. Therefore slowdown in growth rate of manufacturing sector led to unemployment on mass scale. Slowdown of manufacturing also led to Deindustrialization. This deindustrialization was supported by increase in wages due to high wages paid by natural gas sector and high inflation resulting from increased government spending due to high tax receipts from oil and gas firms. This made high wages unaffordable to manufacturers in the short run.

This led to influx of foreign goods dumped in Netherland and at a very cheap rate by foreign companies. With the growing natural gas market and the shrinking export economy, the Netherland began to experience a recession. This situation of economy is called Dutch Disease and was witnessed in multiple countries around the world including Britain, Norway, Australia, Mexico and parts of USA.

4. CASE STUDY

“Natural Resource Abundance and Economic Growth” is a study was done by Jeffrey D. Sachs and Andrew M. Warner while working for Centre for International Development & Harvard Institute for International Development. This study is an updated and Extended Version of National Bureau of Economic Research Working Paper No. 5398 (1995b). Sachs and Warner argues that growth or decline in growth rate of real GDP is affected through factors such as

1. Initial GDP of economy ,

2. Share of primary product exports ,

3. Openness of Economy to the world ,

4. Investment to GDP ratio ,

5. Global Commodity Prices ,

6. Adherence to rules and regulations by citizens of country .

7. Quality of Governance .

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Sachs and Warner took data on 87 countries for a period 1970-90. They followed the model of Barrow (1991) with less no. of regressor than in original model.

GEA7089=A0 + A1 *SXP+ A2 *SOPEN+ A3 *INV7089+ A4 *RL+ A5 * LGDP70 + A6 * DTT7089+ e

GEA7089: Growth in GDP per unit of economically active population (1970 -90).

SXP: Share of primary product exports in GDP of 1970.

SOPEN: Dummy for openness of economy during 1970-1990.

INV7089: Investment to GDP ratio averaged over period 1970-89.

RL: Rule of Law is an index reflecting the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes. Rule of law is scored from 0 (low) to 6 (high).

LGDP70: Natural log of real GDP divided economically active population.

DTT7089: Average annual growth of the ratio of export to import prices between 1971 and 1990.

These regressors excluding SXP are meant to control for their effect or satisfy ceterus paribus condition.

Table No. 1: Results of Stepwise Regression

Variables 1.1 1.2 1.3 1.4 1.5 LGDPEA70 -0.11 -0.96*** -1.34*** -1.76*** -1.79***

SXP -9.43*** -6.96*** -7.29*** -10.57*** -10.26*** SOPEN - 3.06*** 2.42*** 1.33** 1.34*** INV7089 - - 1.25*** 1.02*** 0.81.

RL - - - 0.36*** 0.40*** DTT7090 - - - - 0.09_

Adjusted R2 0.20 0.55 0.67 0.72 0.73 Sample size 87 87 87 71 71 Standard Error 1.62 1.22 1.04 0.93 0.92

Significance codes: 0 ‘***’ ,0.001 ‘**’ ,0.01 ‘*’ ,0.05 ‘.’ ,0.1 ‘_ ’ ,1 Since data is run on normalized/standardized variables hence we do not get intercept in this case.

Mean of SXP variable is 0.16 and standard deviation of 0.16. Regression 1.1 implies that a unit standard deviation increase in the share of primary exports in 1970 would be associated with a reduction in annual growth of 1.51% points (-1.51=-9.43*0.16).

It is possible that this negative association between natural resource intensity and growth is spurious, reflecting an association between resource wealth and something else that affects growth.

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Some common arguments are that

1. resource-rich countries are more likely to adopt import-substitution, state-led development strategies,

2. are less likely to accumulate capital at home because they can live off natural resource rents ,

3. are more prone to rent-seeking and to develop large inefficient bureaucracies, or

4. are less likely to develop market supporting legal institutions.

5. In addition, a long standing view in the development literature is that countries that specialization in natural resource exports are more likely to suffer from unpredictable and disruptive shocks in global commodity prices.

But Sachs and Warner had overcome these arguments by including

• SOPEN dummy variable for first arguments.

• INV7089 variable for second argument.

• RL variable takes care of third and fourth argument.

• DTT7090 variable for fifth argument.

Hence it can be argued that adverse effect was due to resource abundance and not due to other prevailing factors.

Since from the above regression equation it is not proved that high intensity of natural resources leads to bad governance and poor quality of institutions. Therefore to test this hypothesis Sachs and Warner had run the regression as provided in Table No. 2. From the results of regression it is evident that government repudiation of contracts, risk of expropriation, corruption, rule of law and Bureaucratic quality are negatively related to the intensity of primary exports. All the coefficients are significant at 5 percent level of significance.

Table No. 2: Association between Quality of Institutions and Natural Resource Intensity

Variables Government Repudiation of Contracts

Risk of Expropriation

Corruption Rule of Law

Bureaucratic Quality

Log of Real GDP 1980

0.49(2.35)

0.44(1.66)

1.35(8.49)

1.31(7.80)

1.35(8.58)

SXP -3.90(-3.41)

-4.60(-3.17)

-3.29(-3.17)

-5.47(-5.00)

-5.86(-5.70)

Adjusted R2 0.16 0.12 0.48 0.49 0.55 sample size 65 65 85 85 85 Standard Error 1.40 1.78 1.40 1.47 1.38

Figures in parentheses are t statistics.

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Robert Barro’s research paper titled “Economic Growth in a cross section of countries” was published in Quarterly Journal of Economics in 1991. This paper highlighted the variables influencing growth rate of income across countries. Sachs and Warner replicated the work of Barro by re-estimating the same model with latest data at that time (1970-89) compared to 1960-1990 sample data.

Sachs and Warner used the following variables for re-estimating the Barro’s model.

• GEA7089: Average Annual Growth in real GDP per economically active population of duration 1970-90.

• SXP: Share of exports of primary products in GNP in 1970.

• DTT7090: Average annual growth in the log of the external terms of trade (1970-90).

• SOPEN: fractions of years’ during1970-90 in which economy was open.

• SEC70: Secondary school enrollment rate.

• PRI70: primary school enrolment rate.

• GVXDXE: ratio of real government consumption spending (excluding on military and education).

• REVCOUP: average no. of revolutions and coups over the period 1970-1985.

• ASSASSP: average no. of assassinations per million persons over the period 1970-1985.

• PPI70DEV: It measures the deviation of the (log) price level of investment goods from the cross country mean in 1970.

• INV7090: mean ratio of real domestic investment (public plus private) to real GDP over the period 1970-1990.

In Table No. 3, first regression reports replication of regression 24 in Barro (1991). The replication is close but not exact, due to different sample (1970-89 rather than 1960-89). In second column, three additional regressors are added. From Table No. 3, it can be observed that SXP and SOPEN remain significant when included in Barro (1991) specification. The estimated coefficient on SXP is -9.17 and on SOPEN is 1.96. With the exception of initial income and the average investment income ratio, a no. of the variables in the original specification no longer appears significant, although the sign in the original study are preserved. But from the regression it is confirmed that intensity of natural resource export has negative effect on growth of gross domestic product per unit of economically active population.

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Table No. 3: Estimation of Barrow’s Model with Variables from Sachs and Warner’s paper

Independent Variables GEA7089 GEA7089

SXP - -9.17S

SOPEN - 1.96S

DTT7090 - 0.10NS

LGDPEA70 -1.31S -1.92S

SEC70 3.51NS 2.89NS

PRI70 -0.38NS 0.20NS

GVXDXE -4.67NS -4.24NS

REVCOUP -0.04NS -1.04NS

ASSASSP -1.62NS 0.89NS

PPI70DEV -0.41NS 0.03NS

INV7089 0.17S 0.09S

Adjusted R2 0.34 0.71Sample Size 70 69Standard Error 1.57 1.04

S: Significant at 5% level of significance and NS: Not significant

Sachs and Warner (2001) opined that there exists disparity among the countries which are developed and resource cursed countries. Hence to prove exactly the resource curse of these countries we need to prove that even after controlling for the effect of these differences resource curse exist. These critical differences are

1. Access to sea (whether country is land locked or has sea access).

2. Most of the resource rich countries are having high proportion of area under tropical region i.e. more coverage of forest. This leads to more obstacles for setting up of manufacturing industry and also for agriculture.

3. High proportion of forest is also positively associated with Falciparam malaria and greater chance of other diseases compared to temperate countries of Europe.

4. A country having greater distance to the port will obviously have to incur more expense on transporting its goods to the port which will reduce its competitiveness in international market. There can be a case even after having access to sea through when country has very much width.

This also leads to lower incentive to invest in the manufacturing in these countries by foreign firm. Even if manufacturing is for domestic purpose, high cost of imported critical input will obviate a greater incentive to import in short run than to manufacture that good domestically.

Variables selected here are…

• LGDP70 :log of GDP per capita in 1970

• GDP70*SOPEN :Interaction term

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• SOPEN : share of years open

• SXP : Natural Resource Abundance

• % of land within 100 Km coast

• DPORT: distance (km) to closest major port

• TROPICS:% of land in geographical tropics

• FMALARIA 66:Falciparam Malaria index, 1966

Table No. 4: Growth regressions with the natural resource variable and the geography and climate variables

Variables 1 2 3 4 5 LGDPPP70 -0.31NS -0.20NS -0.37NS -0.69S -0.86S

GDP70*SOPEN -1.52S -1.68S -1.82S -1.13S -1.11S

SOPEN 16.21S 17.63S 18.77S 12.75S 12.45S

SXP -0.05S -0.05S -0.04S -0.04S -0.03S

% land within 100 Km coast

0.63NS - - - 0.60

DPORT - 0.00NS - - 0.00NS

TROPICS - - -0.87NS - -0.64NS

FMALARIA 66 - - - -1.41S -1.22S

Intercept 3.40NS 2.79NS 4.52NS 7.17S 8.48S

Observations 97 97 97 94 93 R2 0.57 0.57 0.58 0.58 0.59

S: Significant at 5% level of significance and NS: Not significant Here dependent variable is Growth per-capita 1970-1989

From Table No. 4, it can be observed that even after accounting for geographical variables and related variables, the proof for curse of natural resource is not eliminated. Still we get negative association between primary export intensity and growth of gross domestic product per unit of economically active population.

5. SYMPTOMS OR CONSEQUENCES OF RESOURCE CURSE

• Natural resource abundance leads to greater corruption and inefficient bureaucracies. Bhattacharyya and Hodler (2009) found that natural resource rents lead to corruption, but only in absence of high quality democratic institutions.

• High rents distract governments from investing in the ability to produce growth supporting public goods, such as infrastructure or legal codes.

• Natural resource production generates high economic rents. Government of resource rich countries tend to become dependent on rents received from natural resources.

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• Economies rich in natural resources adopt import substitution policies and protect domestic industries from foreign competition leading to underdeveloped manufacturing base. This also leads to high inflation in economy.

• Compared to mining sector, manufacturing sector requires more skilled worker. So when the mining sector boom increases the wages for beyond marginal value product of worker. This is crowding out of human capital from manufacturing sector.

• This leads to two problems….

1. Increased wages without productivity increase leads to inflation.

2. Youngsters get attracted to the mining sector at early stage of their education. This leads next generations to be low skilled, low incentive to invest in education and less skilled teachers in the next generation.

• Due to boom in the natural resource sector people feel sufficiency and hence necessary environment for innovations is not provided by these cursed economies leading to suppression of innovations.

• Innovations also get suppressed because of low quality of education.

o Innovations also get suppressed because of high cost of performing research in these countries and new innovations can be sourced easily from advanced foreign economies.

• Government that controlled natural resource rents tended to waste the rents through profligate or inappropriate consumption. For example Saddam Hussein spent money on luxuries for his personal desire and for his family.

Saddam Hussein’s Palace

Too much optimistic government about resource prices acted in hurry to announce and implement large public investments in projects that were hugely inefficient when the

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government’s optimism turns out to be wrong. As a result these economies end up with more inappropriate capital on their hands than other economies.

• Arezki and Bruckner (2010 a) find that commodity price booms lead to increased government spending, external debt and default risk in autocracies and but do not have those effect in democracies. It is also a fact that, of the 20 major oil exporting countries in 2000, only Mexico and Venezuela are democracies and both have experienced prolonged period of authoritarian rule. Thus we can establish the fact that results of Arezki an Bruckner are true for oil dependent countries leading to resource curse.

• Fight for resources also lead to civil war in country which deteriorates nation’s peace status. Let’s take example of Congo. Congo’s second II war began in 1998 just one year after its first war was over. In this war rebel groups attacked the government to gain control of Congo's natural resources. Today these armed rebels are in control of Eastern Congo’s mineral wealth, trading routes and other strategic areas. UN has put sanction on all countries/ companies in the world from importing minerals from these armed groups because wealth generated from these minerals sold by rebels is used for financing arms and armed groups.

.

• Table No. 5 gives the recent civil wars in oil and mineral dependent states.

M23 rebel fighters walk as they withdraw near the town of Sake, some 42 km (26 miles) west of Goma

With marbled walkways, raised escalators and gold-plated walls, this proposed new metro station on Riyadh, Saudi Arabia.

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Table No. 5: Recent Civil Wars in Oil and Mineral Dependent States

Country Duration Algeria 1991-2002Angola 1975-2002Chad 1975-1982Colombia 1984-presentCongo Rep. 1997-1999Indonesia (Aceh) 1986-2004Iraq 1974-1975, 1985-1992,2003Liberia 1989-1995Nigeria 1967-1970, 1980-1984Papua New Guinea 1988-2003Sierra Leone 1991-2002Sudan 1983-presentYemen 1986-1987, 1990-1994

Source: Terry Karl (2009)

• Resources hinder the democracy. Resources break the link between taxation and state building. Spending on patronage weakens pressure for representation and accountability. Usually resource rich countries have autocratic regime and to maintain that autocratic rule, autocrats spend only on those who groups who favour them and spend a negligible amount on those who doesn’t.

• Usually Government of resource rich states get majority of their revenue from taxing the resource sector. Often it happens that government doesn’t tax its citizen. It is obvious that those who pay tax demand the basic necessities from the government like health care, infrastructure etc. But when they don’t pay taxes to the government they cannot put pressure their government. This also weakens the democracy in these countries.

• Most of the time, extraction of minerals and oil is done by foreign firms because domestic firms are not capable enough, usually in countries like Nigeria, Congo, due to lacking technological knowledge. When these firms pay the governments royalties and taxes, the data on how much is paid by the foreign firms to the government is not published. This leads to distrust among public regarding the finances of the government and result of these public resentment is Publish What You Pay Campaign. So this campaign asks the companies to publish the data on how they have paid the government of their respective nations.

To provide support in favour of symptoms expressed above some statistics need to be provided. In this regard, it is imperative to select good examples of resource rich, resource poor and mixed type to understand symptoms in the light of data on various socio economic indicators. Table No. 6 shows us the list of selected resource poor and resource rich countries in the world and their respective natural resources. Here Japan, India and Australia are selected as examples for resource poor, mixed type and resource rich (but with exceptional socio-economic indicators) country. Congo DR, Nigeria, Angola and Botswana are examples of resource rich countries.

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Table No. 6: List of Selected Resource Rich and Poor Countries and Their Natural Resources

Country Natural Resource Angola Diamond, Petroleum, Uranium, Gold, Bauxite, Iron ore, Phosphates, Feldspar. Congo (DR) Gold, tungsten, tantalum, tin. Nigeria Petroleum, Coal, Natural Gas, Iron Ore, Tin, Lead, Zinc, Limestone, Arable Land.

Botswana Diamonds, Copper, Nickel, Salt, Soda Ash, Potash, Coal, Iron Ore, Silver India Coal (Fourth-largest Reserves In The World), Iron Ore, Manganese, Mica,

Bauxite, Rare Earth Elements, Titanium Ore, Chromites, Natural Gas, Diamonds, Petroleum, Limestone, Arable Land

Australia Bauxite, Coal, Iron Ore, Copper, Tin, Gold, Silver, Uranium, Nickel, Tungsten, Rare Earth Elements, Mineral Sands, Lead, Zinc, Diamonds, Natural Gas, Petroleum. Note: Australia is the world's largest net exporter of coal accounting for 29% of global coal exports

Japan Negligible Mineral Resources, Fish Note: with virtually no energy natural resources, Japan is the world's largest importer of coal and liquefied natural gas, as well as the second largest importer of oil

Source: https://www.cia.gov/library/publications/the-world-factbook/Table No. 7 shows the performance of selected countries, named in table no. 6, on different socio-economic indicator. These socio-economic indicators includes Human Development Index, Per capita Income status, Compound Annual Growth Rate (CAGR) of GDP per capita for a period of 1985 to 2010, Resource Rent as percentage of GDP, Peace Status, Global Governance Index, Unemployment rate, Corruption Index , Poverty rate at less than $2 per day global poverty line and Adjusted Net savings. From table no. 6, it can be observed that resource rich countries have poor performance on Human Development Index (HDI) while resource poor Japan fares far better on HDI. Though Australia which is also a resource rich country but did better on HDI. India being an example of mixed type is not better in performance on HDI.

For per capita income, World Bank Criteria is adopted here to give status to various economies. This criterion says those countries which have per capita income status expressed in US dollar ranging from $1,035 or less, $1,036 to $4,085, $4,086 to $12,615 and $12,616 or more shall be classified as low income, lower middle income, upper middle income and high income economies respectively. According to these criteria resource poor economies of Japan is high income economy while resource rich economies of Congo, Nigeria, Angola and Botswana have low, lower middle, upper middle and upper middle income status with exception being Australia having status of high per capita income. India though example of mixed type falls under lower middle income group along with Nigeria.

Compound Annual Growth rate for per capita income was calculated by the author himself using the data obtained from World Bank Development Indicator. Method used for calculating the CAGR is discrete method. Formula is provided in the appendix to this report ii. With regard to CAGR, Congo DR had negative growth rate while Angola, Nigeria and Botswana had positive growth rate while India, Australia and Japan had also positive growth

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rate. Japan and Australia had lower growth rates compared to Botswana, Nigeria and Angola because Japan and Australia reached the peak of their demographic development.

Table No. 7: Comparison of Selected Resource Rich and Poor Countries across World on Different Socio-Economic Indicator

Country Congo(DR) Nigeria Angola Botswana India Australia Japan

HDI rank (2013)# 186 153 148 119 136 2 10 Per capita income status @

L LM UM UM LM H H

CAGR of GDP per capita (1985-2010) ~

-3.13 1.61 2.38 3.98 4.46 1.81 1.51

Resource Rent as% of GDP(rank)@

 35.2(19)

35.8(18)

46.67(7)

4.7 (100)

7.4 (66)

10.7 (58)

0.0

Peace status VL  L M H L VH VH Rank in World Governance index 2009^

176 163 166 80 163 10 20

Unemployment rate (%) *

53 23.9 26 17.8 8.5 5.20 4.40

Corruption ranking^^ 22 29 23 146 77 167 158

Poverty (<$2 a day,2010)@

95.2  84.5  70.2 49.4 68.7 0.00 0.00

Inflation rate(CPI, 2000-11) @

47.9 12.2 33.2 8.8 6.4 2.0 -0.2

Adjusted Net Savings@

-8.63 -58.58 -23.2 10.1 22.5 6.8 10.1

Global Innovation Index rank 2013**

- 120 135 91 66 19 22

UM: Upper middle, UP: Upper, LM: Lower middle, VL: Very Low, L: Low, M: Medium, H: High, VH: Very High, CAGR: Compound Annual Growth Rate.

Source:*https://www.cia.gov/library/publications/the-world-factbook/, @http://wdi.worldbank.org/table, ~Author# hdr.undp.org/en/statistics/hdi, ! Global Peace Index, ^http://www.world.governance.org, ^^ www.transparency.org › ... › Corruption Perceptions Index › CPI 2013, **http://www.globalinnovationindex.org/content.aspx?page=GII-Home

Indicator of Peace status is provided by Global Peace Index prepared by Institute for Economics and Peace. Continuous maintenance of Peace is considered to be the boon for development of Industries and society. This fact was evident in post second world war in Europe where unprecedented level of peace led to not just rebuilding of war ravaged economies but also high levels of growth. This factor is missing from resource rich economies of Congo DR, Nigeria and Angola. Botswana because of good quality of governance and institutions managed to escape the conflict. India though a mixed type had low peace status, not because of resource per se but due to political and social reasons. Japan and Australia had very high level of peace.

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It is a fact proven worldwide that good peace status is largely due to good governance. Indictor of governance is prepared by Forum for New Governance and is named as World Governance index. In 2009, Congo DR, Nigeria and Angola had 176th, 163rd and 166th rank in index respectively while India shared the rank with Nigeria, i.e. 163rd rank. Australia and Japan had 10th and 20th rank respectively. This ranks in the World Governance Index matches very much with the peace status of the respective countries.

Unemployment rate measured as proportion of labour force without jobs. Unemployment rate was quite high in the countries which are resource rich compared to resource poor with exception of Australia. Unemployment rate in the resource rich countries is so high in usual years that it is more than the unemployment rate of USA during great depression of 1929. The main reason for such high rate of unemployment is their underdeveloped manufacturing sector.

In case of Corruption, measured by Corruption perception index prepared by Transparency International, resource rich countries are in the top of the list with exception of Botswana and Australia. Resource poor Japan had very low ranking in corruption while India being a mixed type had more corruption than resource rich Botswana.

For measuring poverty, World Bank data on Poverty rate at poverty line of $2 per day per person is used. On poverty issues, resource rich countries have very high rate of poverty ranging from 95 percent in Congo DR to 70 percent in Angola and 49 percent in Botswana. India being a mixed type has more poverty than Botswana. This high rate of poverty in resource rich country is indicator of ill distribution of income in the society. Japan and Australia have no person earning less than two dollar per day per person.

To measure price rise in the economies, most of the countries adopted consumer price index. From the data obtained from World Bank, it is evident that resource rich countries had very high rate of inflation, Congo DR had 47 percent inflation rate which means that prices will double after every 14 month. This leads to high poverty which is discussed in above paragraph. Although Botswana and India had moderate level of inflation while Australia has very low level of inflation rate and Japan had experienced price decline.

Adjusted net saving, (also known as genuine saving), is a sustainability indicator building on the concepts of green national accounts. Adjusted net savings measure the true rate of savings in an economy after taking into account investments in human capital, depletion of natural resources and damage caused by pollution. For resource rich economies adjusted net savings are negative except Botswana, which implies low levels of sustainability. For India, Australia and Japan it is positive indicating good levels of sustainability.

To measure innovativeness of a country Global Innovation Index is prepared by Cornell University, INSEAD, and the World Intellectual Property Organization (WIPO, an agency of the United Nations, UN).For year 2013, resource rich economies were at the bottom of the index. Nigeria and Angola received ranking of 120 and 135 out of 142 countries. Index was not prepared for Congo DR. India and Botswana received 66th and 91st rank while Japan and Australia received 22nd and 19th rank respectively. The lower rank received by resource rich

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countries is an indication of huge impediments to research and developments in these countries.

In conclusion to this statistics provided in Table No. 6 and inferred later on, it can be concluded that resource curse is a complex problem leading to and supported by poverty, inflation, low level of education, bad governance, unemployment, corruption, violence, rent seeking, suppression of innovations and harm to environment leading to lower growth rates of per capita income.

Among all the resource rich countries Botswana managed to escape from the curse by having good governance. Botswana is known to retain more diamonds then it exports. It has better status on many indicators than India. India on other hand seems to be falling under resource trap. Recent scams of Bellary mine, Coal gate scam, and 2G scam were some of the noticeable examples in India.

6. CRITICISM AGAINST THE RESOURCE CURSE

1. High wages are not necessarily unproductive because they are kept high to attract labourers to risky jobs like mining and exploration.

2. Much of the variation in resource curse is accounted by quality of institutions, which was weak at the time resources were discovered in these countries. Hence peace and socio-economic conditions remained poor.

3. Most of the countries in the list of resource curse were colonized. This also impaired their ability to prosper by eliminating institutions originally present in those countries.

Table No. 8: List of Selected Resource Rich Countries and Their Respective Foreign Rulers

Country Foreign Ruler(s) Nigeria British (1861-1960) Angola Portuguese ( 1480s -1975) Congo (DR) Belgium ( 1908-1960) Sudan British ( 1898-1956) Kenya Portuguese ( 16th century till 1920)

British ( 1920-1963) Ghana Portuguese (15th century)

British (1874-1957) Syria French ( 1918 – 1946) Libya Italy ( 1911-1951) Iran Russia and Britain economically controlled in

19th century. Iraq None

Source: Encyclopædia Britannica 2013 Ready Reference CD

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4. Previous research works on Curse of Natural Resource took into account data for 30 to 40 years i.e. short run. In long run all the resource cursed economies start performing well as is the case of Angola which is now recovering from the resource curse.

5. Appreciation of currency in FOREX market, as depicted in Dutch Disease can also be due to excessive or large amount of foreign fund flowing into country, may be in the form of foreign investment or foreign aid. Hence Dutch Disease can’t always be attributed to resource led appreciation.

But this criticism is not correct, because though these foreign funds can lead to appreciation but also shift focus away from (non-booming) tradable to non tradable. Again in this case, the real appreciation takes the form of a nominal appreciation if the exchange rate is flexible and inflation if the exchange rate is fixed.

7. How to manage curse of Natural resource? Following points were suggested by Jeffrey Frankel19 of Harvard Kennedy School, Harvard University, USA.

1. Include in contracts with foreign purchasers clauses for automatic adjustment of the price if world market conditions change.

2. Hedge export proceeds in commodity futures markets.

3. Denominate debt in terms of commodity prices.

4. Allow some nominal currency appreciation in response to an increase in world prices of the commodity, but also add to foreign exchange reserves, especially at the early stages of the boom when it may prove to be transitory.

5. If the monetary regime is to be Inflation Targeting, consider using as the target, in place of the standard CPI, a price measure that puts greater weight on the export commodity, such as an index of export prices or producer prices.

6. Emulate Chile: to avoid excessive spending in boom times, allow deviations from a target surplus only in response to output gaps and long-lasting commodity price increases, as judged by independent panels of experts rather than politicians.

7. Commodity Funds should be transparently and professionally run, with rules to govern the payout rate and with insulation of the managers from political pressure in their pursuit of the financial wellbeing of the country.

8. When spending oil wealth, consider lump-sum distribution on an equal per capita basis.

9. An external agent, for example a financial institution that houses the Commodity Fund, could be mandated to provide transparency and to freeze accounts in the event of a coup.

Needless to say, policies and institutions have to be tailored to local circumstances, country by country. But with good intentions and innovative thinking, there is no reason why resource-rich countries need fall prey to the curse.

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8. REFERENCES

1. Encyclopædia Britannica 2013 Ready Reference CD

2. KARL, T. (2009, October 1). overcoming the resource curse. (W. I. environment, Producer, & Stanford Univesity) Retrieved february 13, 2014, from Youtube: https://www.youtube.com/watch?v=ORkgMaHkv6U

3. SACHS J.D. and WARNER A.M., Nov. 1997,Natural Resource Abudance and Economic Growth, Cengtre for International Development and Harward Institutue for International Development, Harward University.

4. SACHS J.D. and WARNER A.M.,2001, The Curse of Natural Resources. European Economic Review , 45:827-838.

Web Sites

5. http://www.raisehopeforcongo.org/content /initiatives/conflict-minerals 6. http://www.un.org/sc/committees/1533/ 7. http://en.wikipedia.org/wiki/Second_Congo_War 8. http://www.globalresearch.ca/congos-m23-conflict-rebellion-or-resource-war/

53191789. http://www.dailymail.co.uk/news/article-2327383/Riyadh-metro-station-

Luxurious- rail-hub-King-Saudi-Arabia-ordered-built-just-years.html10. http://content.time.com/time/photogallery/0,29307,1973064_2089044,00.html 11. http://content.time.com/time/photogallery/0,29307,1973064_2089038,00.html 12. http://www.InflationData.com 13. http://en.wikipedia.org/wiki/Resource_curse 14. http://www.world.governance.org 15. http://money.cnn.com/magazines/fortune/fortune_archive/2003/02/03/336434/ 16. http://wdi.worldbank.org/table 17. http://www.globalinnovationindex.org/content.aspx?page=GII-Home 18. hdr.undp.org/en/statistics/hdi19. http://www.hks.harvard.edu/m-rcbg/heep/papers/FrankelHEEPDP21.pdf20. www.transparency.org › ... › Corruption Perceptions Index › CPI 2013

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iAppendix For this to happen, country should follow flexible exchange rate, and here appreciation will be of nominal one.

ii Formula to calculate CAGR is CAGR= ([V n

V 0 ]1/n

−1)∗100

Where Vn: Value in nth year, V0: Value in initial year, n: no. of years from initial to final value.