curse of natural resources: theory and evidences
TRANSCRIPT
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Curse of Natural Resources: Theory and Evidences
1st Credit Seminar Gourav Kumar Vani
Roll No. 10678
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Natural Resources
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What are natural resources ?• materials or substances occurring in nature which can be exploited for economic gain1.
• Gift of the nature
• Freely occurs in environment
• Without actions of humankind
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Source: 1. https://en.oxforddictionaries.com/definition/natural_resources
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Natural Resources and Economic Growth
• Natural resources as such can be exported in raw form to earn foreign currency for imports.
• Natural resources are inputs to industrialization because
• metal production requires ore and coal,
• fertilizer production requires natural gas,
• Paper and pulp industry requires softwood lumber,
• agro-industries requires raw agricultural produce, etc.
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Source: Sachs and Warner (1999)
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Natural Resources and Economic Growth
• Natural resources helps to increase employment and growth of economy.
• But the limit to forward and backward linkages through resource-intensive production comes
from
• small size of domestic market (due to small population) and
• Economy being close to foreign trade
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Source: Sachs and Warner (1999)
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Natural Resources and Economic Growth
• Resource-rich U.S.A., Britain and Germany fuelled their rapid economic growth using vast
domestic reserves of natural resources.
• Resource-poor Japan and South Korea casted their economic growth by importing natural
resources from other countries.
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Source: Sachs and Warner (1999)
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Natural Resources and Economic Growth
• Resource abundance is not sin qua non as long as resources can be imported at economically cheaper rate.
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Puzzle: If natural resources abundance is no longer required to advance economically then how can such abundance create hurdles for economic expansion.
Source: Sachs and Warner (1999)
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Natural Resources Abundance and Economic Growth
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Source: Calculations by presenter using data from World Bank database. 1. at constant 2010 US $, * For 1970-2015, # Excluding crop component
Groups Per capita Natural Capital #
at 2005 US $Growth rate (%) of GDP per capita1 1968-
2015
High income 11,956 2.65
Upper middle income 10,938 4.36
Lower middle income 2,359 4.52
Low income 1,286 3.20
Europe & Central Asia 13,185 2.10*
Latin America & Caribbean 8,039 1.57
Middle East & North Africa 7,918 1.79
Sub-Saharan Africa 2,620 0.72
East Asia & Pacific 1,962 3.22
South Asia 1,349 3.17
World 5,052 1.57
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Resource Curse • 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”.
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Source:* http://en.wikipedia.org/wiki/Resource_curse
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Literature on Resource Curse
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Source: I Kolstad A. Wiig, Energy Policy 37 (2009) 5317-5325
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Staple Thesis • Staple is an important traditional commodity.
• Important points related to Staples are
• Production of commodity requires substantial natural resources
• Little or no processing before sale/export
• Harold Innis and W. A. Mackintosh proposed this thesis.
• Development of Canada took place around the search, production and export of staples.
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Staple Thesis • Fur, timber, cod and wheat were staples for Canada.
• Later on ores, metals and petroleum joined the list of new staples.
• For long time, these were untapped resources.
• The hinterlands were the locations for search and production of these staples.
• It was pattern of settlement that created hinterland and heartland in Canada.
• For trade and export hinterlands were dependent on heartlands.
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Staple Thesis • This cemented a link between hinterlands and heartland.
• Export of Staples remained the main source of growth for Canadian economy through forward
and backward linkages.
• Choy and Sugimoto reported Rubber, Tin and petroleum as three staples for British ruled
Singapore from 1900-1939.
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Dutch Disease and Resource Curse • Coined by “The Economist” magazine, 1977.
• Massive Natural gas field in Groningen, Netherland in 1959.
• The country wanted to profit from this gas by exporting it.
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Discovery of Natural Resources
Govt. focus shifts to resource sector
High Domestic & Foreign investment in resource sector
High tax receipts from Resource sector
High inflation rate
Low manufacturing growth
Increased Govt. expenditure
High growth of resource sector led by export of resources
High wages attract labour from manufacturing sector
Appreciation of Domestic currency
Loss in export competitiveness of non-resource sector
Import of Foreign goods Deindustrialisation
Capital intensive resource sector creates unemployment
Recession
Source: Prepared by Presenter
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Other consequences of resource abundance• Compared to mining sector, manufacturing sector requires more
skilled worker. So when the mining sector boom increase the wages for beyond marginal value product of worker. • 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.
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Case study
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Natural Resource Abundance and Economic Growth
By Jeffrey D. Sachs and Andrew M. Warner
Centre for International Development & Harvard Institute for International Development
Working Paper No. 5398 (Updated) (1997 November)
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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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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.
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 regressor excluding SXP is meant to control for their effect or satisfy ceterus paribus
condition.
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Results of Stepwise Regression
Variables 1 2 3 4 5LGDPEA70LGDPEA70 -0.11 -0.96*** -1.34*** -1.76*** -1.79***
SXPSXP -9.43*** -6.96*** -7.29*** -10.57*** -10.26***
SOPENSOPEN - 3.06*** 2.42*** 1.33** 1.34***
INV7089INV7089 - - 1.25*** 1.02*** 0.81.
RLRL - - - 0.36*** 0.40***DTT7090 - - - - 0.09_
Adjusted R2 0.20 0.55 0.67 0.72 0.73Sample size 87 87 87 71 71
Standard Error 1.62 1.22 1.04 0.93 0.92
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Since data is run on normalized/standardized variables hence we do not get intercept in this case.
Significance codes: 0 ‘***’ ,0.001 ‘**’ ,0.01 ‘*’ ,0.05 ‘.’ ,0.1 ‘_ ’ ,1
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Interpretation• Mean for 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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• Sachs and Warner 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.
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• These critical differences are 1.Access to sea (% of land within 100 Km coast)2.high proportion of area under tropical region
(TROPICS:% of land in geographical tropics)3.Falciparum malaria positively associated with forest
cover (FMALARIA 66:Falciparam Malaria index, 1966)4.greater distance to the port (DPORT: distance (km) to
closest major port)5.high cost of imported critical input
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Growth regressions with the natural resource variable and the geography
and climate variables
Variables 1 2 3 4 5LGDPPP70 -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
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Here dependent variable is Growth per-capita 1970-1989
S: Significant at 5% level of significance and NS: Not significant Division of Agricultural Economics, IARI, New Delhi-110012
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Association between natural resource abundance & other explanatory
variables• NS7089: National saving as a percent of GDP.• LINV7089: natural log of the ratio of real gross domestic investment
(public + private) to real GDP averaged over the period 1970-89. • DTYR7090: Change in the total years of education in the population
above age 15 from 1970-90.• LPIP70: the log of the ratio of the investment deflator to the GDP
deflator in 1970
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Association between natural resource abundance and other explanatory variables
Variables NS7090 LINV7089 DTYR7090 SOPEN LPIP70LGDPEA70LGDPEA70 6.38*** - 0.05 - -0.16*
SXPSXP 0.19 0.40 -0.95 -1.89. 0.08
SXP^2SXP^2 - - - 3.24* -
SOPENSOPEN - 0.14 - - -0.40*
RLRL - 0.06. - - -
LPIP70LPIP70 - -0.82*** - - -
LANDLAND - - - -0.09** -
Adjusted R2 0.36 0.67 -0.1 0.21 0.31Sample size 104 80 90 104 102
Standard Error 7.64 0.31 0.89 0.40 0.43
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Since data is run on normalized/standardized variables hence we do not get intercept in this case.
Significance codes: 0 ‘***’ ,0.001 ‘**’ ,0.01 ‘*’ ,0.05 ‘.’ ,0.1 ‘_ ’ ,1
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Other consequences of resource abundanceEconomies 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.
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Source: Prepared by presenter using data from World Bank database.
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Institutions and Resource Curse • Dutch Disease explanation resource curse relies purely on economic
incentives and aspects.• However, it can not explain all the differences in growth rates of
different countries with nearly equal amount of resource abundance. • Role of institutions has been cited as reasons for difference in
economic outcomes.
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Centralized PE Model
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Inefficient public sector
Economy with resource abundance
Incumbent Politician
Extraction of resources in current period
Allocation of Resource Rents
Faces election in next period
Value of being in power ≈ Resource Rents enjoyed
Lower extraction
Higher extraction
High probability of being re-elected
Low probability of being re-elected Consume
himself/herself
Distribute it as Patronage
Socially inefficient extraction
Permanent Resource Price
Boom
Increases the value of being in the power
Socially efficient
extraction path
Source: Prepared by presenter based on model of Robinson et. al. (2006)
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Decentralized PE Model
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Decentralized PE Model• It is being assumed that resources interacts with quality of
institutions.• Thus resource abundance turns blessing only when quality of
institutions is good. • Resource booms may tempts politicians to dismantle the state
institutions to extract resource rents for their own private use. • According to Ross (2001), Timber booms have led political insiders to
dissolve state forestry management in many countries, in particular in South-East Asia.
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Source: Mehlum et. al. (2006)
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Decentralized PE Model
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Source: Prepared by presenter based on model of Mehlum et. al. (2006)
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Decentralized PE Model• Comparison of four hypothetical countries
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Institutions Resource Poor
Resource Rich
Grabber Friendly
InstitutionsA B
Producer Friendly
Institutions A* B*
Source: Prepared by presenter based on model of Mehlum et. al. (2006)
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Source: Calculations by presenter using data from World Bank database.* As percentage of GDP 1992
Empirical Association between Resource Rents and Rule of Law Index
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Case study
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Institutions and the Resource CurseBy Halvor Mehlum, Karl Moene, Ragnar Torvik
The Economic Journal Volume 116, Issue 508
January 2006
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Dependent Variable: average growth rate of real GDP per capita between 1965 and 1990Variables 1 2 3 4 5 6
Initial Income level -1.33 -1.88* -1.33* -1.34* -1.36* -1.45*
Openness 1.87 1.34* 1.60* 1.59* 1.63* 1.56*
Resource abundance - -10.92* -16.35* -13.70* 14.78* -16.25*
Mineral abundance -17.71* - - - - -
Institutional Quality -0.20 1.83 -0.90 -1.15 -1.18 -0.78
Investment 0.15* 0.11* 0.15* 0.15* 0.15* 0.14*
Interaction term 29.43 11.01 18.31* 15.86* 16.84* 19.01*
Secondary - - -0.60 - - -0.57
Ethnic fract. - - - -0.88 - -0.77
Language Fract. - - - - -0.36 -0.11*
Africa excluded No Yes No No No No
Observations 87 59 76 86 84 74
Adjusted R2 0.63 0.79 0.70 0.71 0.70 0.70
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Results of Stepwise Regression
* Indicates significance at 5 percent level of significance
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Empirical Evidence on Resource Curse and Institutions
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Empirical Evidence on Resource Curse on India
Growth rate of real net state domestic product at factor cost (NSDPFC) per
capita (2000-01 to 2010-11) is considered as a function of
1.Initial NSDPFC per capita (NSDPPCNSDPPC)
2.Primary sector contribution to NSDPFC 2000-01 (PrimaryPrimary)
3.Coastal line length (km) (CLCL)
4.SC/ST population as percentage of total state population 2000-01 (SCSTSCST)
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Empirical Evidence on Resource Curse on India
5. Urban population as percentage of total state population 2000-01 (URB)(URB)
6. Area under forest as percentage of total state geographical area 1999
(AUF)(AUF)
7. Literacy rate 2000-01 (LR)(LR)
8. Infant Mortality rate 2000-01 (IMR)(IMR)
9. Workforce population as percentage of total state population 2000-01
(WF)(WF)
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Empirical Evidence on Resource Curse on India
Data Sources•RBI Handbook of Statistics on Indian Economy 2008 and 2012•Census 2001 and 2011•www.data.gov.in•State of Forest Report 2001•Answer to starred question no. 498 from Lok Sabha Record 30th April 2013.
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Correlation matrix of variables involved
GR Primary LR AUF IMR SCST WF NSDPPW CL URB
GR 1.00Primary -0.14 1.00LR 0.04 -0.71 1.00AUF 0.05 0.21 0.13 1.00IMR 0.11 0.52 -0.73 -0.40 1.00SCST 0.02 0.24 -0.13 0.65 -0.07 1.00WF 0.28 0.05 0.07 0.37 0.04 0.47 1.00NSDPPW -0.08 -0.80 0.67 -0.23 -0.55 -0.34 -0.17 1.00CL 0.20 -0.07 0.23 0.10 -0.12 -0.33 0.05 0.08 1.00URB -0.06 -0.86 0.59 -0.27 -0.45 -0.23 -0.18 0.85 0.07 1.00
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Result of Stepwise Regression Explanatory Variables Model 1 Model 2 Model 3 Model 4 Model 5
Constant 7.165*** 10.605 14.488*** 12.488*** 12.541***
Primary −0.038
−0.241** −0.196** −0.233** −0.235***
AUF 0.012
IMR - 0.041 - - -
SCST - 0.003 - - -
WF - 0.079 - - -
NSDPPC - −1.882X 10-5 - - -
CL - 0.001 - - -
URB - −0.076 −0.095** - -
LR - −0.017 - - -
PC1 - - - −1.268** −1.278**
PC2 - - - 0.062 -
PC3 - - - −0.993** −0.996**
F statistic 1.038 2.326** 2.549* 3.485* 4.440**01/05/23 Division of Agricultural Economics, IARI, New Delhi-110012 44Source: Estimated by presenter, Significance code: * 10%, ** 5%, *** 1% and below
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How to avoid resource curse??• Diversification of economy • Improving quality of institutions • Measures to reduce volatility of commodity prices
1. Marketing boards2. Taxation of commodity production3. Producer subsidies 4. Other government stockpiles
01/05/23 Division of Agricultural Economics, IARI, New Delhi-110012 45
Source: Frankel, A Jeffrey (March, 2010)
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How to avoid resource curse??5. Price control for consumers6. OPEC and other international cartels
• Devices to share risks1. Price setting in contract with foreign companies 2. Hedging commodity futures market 3. Denomination of debt in terms of commodity prices
• Monetary Policies 1. Fixed vs. Floating exchange regimes
01/05/23 Division of Agricultural Economics, IARI, New Delhi-110012 46
Source: Frankel, A Jeffrey (March, 2010)
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How to avoid resource curse??2. Alternate nominal anchors (like Inflation targeting)
• Institutions to make savings pro-cyclical 1. Rules for the budget deficit (Ex. Chile) 2. Commodity Funds or Sovereign Wealth Funds 3. Foreign Exchange Reserves 4. Reducing Net Private Capital Inflows during booms5. Lump sum distribution
• Efforts to impose external checks (Publish What You Pay Campaign)
01/05/23 Division of Agricultural Economics, IARI, New Delhi-110012 47
Source: Frankel, A Jeffrey (March, 2010)
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Thank You Very Much for Your Patience and Kind Attention
Questions if any???
01/05/23 Division of Agricultural Economics, IARI, New Delhi-110012 48