DEVELOPMENT ECONOMICS

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DEVELOPMENT ECONOMICS

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DEVELOPMENT ECONOMICS

Sponsored by a Grant TÁMOP-4.1.2-08/2/A/KMR-2009-0041 Course Material Developed by Department of Economics,

Faculty of Social Sciences, Eötvös Loránd University Budapest (ELTE) Department of Economics, Eötvös Loránd University Budapest

Institute of Economics, Hungarian Academy of Sciences Balassi Kiadó, Budapest

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DEVELOPMENT ECONOMICS

Author: Katalin Szilágyi

Supervised by Katalin Szilágyi January 2011

ELTE Faculty of Social Sciences, Department of Economics

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DEVELOPMENT ECONOMICS

Week 7

Resource curse

Katalin Szilágyi

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Natural resources

• Conventional wisdom: More wealth is good

• More consumption, more leisure

• Resource curse / paradox of plenty:

wealth can be dangerous

• Discovery of natural resources often goes together with: lower growth,

“bad” sectoral structure, rent-seeking, bad institutions, less human capital

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Outline

1. Concept, stylized facts

• Case studies

2. Estimating average effects

• Cross-country regressions 3. Accounting for cross-country

heterogenity

• Conditional effects

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1.Concept and stylized facts

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Resource curse

• Discovery of new natural resources can be harmful for development.

• Phenomenon: resource curse / paradox of plenty

• Stylized facts: countries rich in natural resources

• Lower growth

• Worse institutional quality

• More conflict

• Examples: Angola, Nigeria, Sudan, Venezuela, Sierra Leone, Congo, Columbia, Bolivia

• Counter-examples:

• Botswana, Norway (Chile, Indonesia, Thailand)

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Resources and growth

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Resources and growth

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Nigeria

Nigéria (1970)

• GDP per cap (PPP):

$1113

• Poverty rate: 36%

• Number of poor: 19m

• Top 2% have same bottom

income as: 17%

• Oil revenues since

<$2bn

1965 (1995 prices)

• Source: IMF WP/03/139

Nigéria (2000)

• GDP per cap: $1084

• Poverty Rate: 70%

• Number of poor: 90m

• Top 2% have same bottom income as: 55%

• Oil revenues since $350bn 1965 (1995 prices)

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Explanations

• Dutch disease: resources → real

appreciation → loss of competitiveness

→ ”bad” sectoral structure

• Rent-seeking: resources → rent- seeking→ bad institutions

• Human capital: resources → false

sense of security → lack of investment

→ lower (human) capital stock later

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Dutch disease

• Dutch disease: resources → real appreciation

→ loss of competitiveness → ”bad” sectoral structure (lower share of manufacturing)

• Structural transformation (tradable → nontradable)

• Transitory frictions vs. long-term structural problem

• Long-term effect if manufacturing is

”special” (industrial linkages,

complementarities, growth externalities)

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Structural transformation

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Dutch disease

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Dutch disease: examples

• Spain in the 16th century

• Gold rush in Australia

• Norway and Holland in the 1970s

• Russia (Azerbaijan) in the 1990s (2000s)

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Holland

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Columbia

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Columbia

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Rent-seeking

• Effect of more resources:

• Corruption (moral hazard): more wealth

• Sorting: job of politicians become more attractive

• Consequences: more rent-seeking, worse institutions

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Equilibrium

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Effect of a new discovery

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Human capital

• Discovery of new resources → false sense of security → less incentive to invest in (human) capital

• Implicit assumption: less human capital is needed in the (primary) resource-

sector

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Natural resources and education

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Natural resources and human capital

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2.Cross-country regressions

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Growth effects

• Sachs–Warner (1995, 2001): The curse of natural resources, NBER WP 5398

• Cross-country growth regressions (Barro, MRW) augmented with natural resources (NR)

• NR: natural resources/GDP (primary sectors/GDP, natural resources export / total export etc.)

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Interpretation

• Robust empirical finding

• Multiple measures, multiple specifications

• No structural relation

• Indirect effects: mostly through a decrease in openness

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Indirect effects

• Gylfason (2000): Natural Resources,

Education, and Economic Development CEPR DP 2594

• Cross-country regressions:

• Direct effect: resources → growth

• Indirect effect: resources → human capital, human capital → growth

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Direct and indirect effects

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3.Cross-country heterogenity

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Heterogenity

• Good and bad examples:

• Norway, Botswana, Chile, Malaysia

• Sudan, Nigeria, Azerbajidan, Bolivia

• Differential effect of natural resources reflects deeper causes

• Differences in institutions is the key

• Proper question: blessing or curse given institutional quality?

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Different types of capital

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Countries with presidential regime

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Countries with parliamentary regime

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Role of institutions

• Mehlum–Moene–Torvik (2006):

Institutions and the resource curse EJ, 2006/1

• Institutions are a prerequisite

• Cross-country regressions (SW), but:

augmented with institutional quality (IQ)

• IQ: average of Political Risk Services measures

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Results

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Estimated partial effect

• Estimated partial effect of reasources:

• Interpretation:

• Threshold

• Can be blessing or curse

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Political effects within a country

• Brollo–Nannicini–Perotti–Tabellini (2010): The Political Resource Curse, CEPR Discussion Paper 7672

• Municipalities in Brazil (with and without oil):

the effects of new discoveries?

• Corruption

• Average human capital of political candidates decreases

• Chances of incumbents being re-elected go up