## NATURAL RESOURCES AND INSTITUTIONS IN TRANSITION ECONOMIES

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**Canonical URL:** [NATURAL RESOURCES AND INSTITUTIONS IN TRANSITION ECONOMIES](https://www.imf.org/-/media/files/news/seminars/1b_discussant_gombojav.pdf)

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### Aims and main hypothesis
- The paper examines the relationship between natural resource abundance and institutions in transition countries (including Mongolia) between 2000 and 2012.
- Core hypothesis (drawing on Mehlum and others, 2006): natural resource abundance hinders economic growth in countries with bad institutions but raises income in countries with good institutions. Resource-rich countries can be either growth losers or growth winners depending on institutional quality.

### Model of natural resources and institutions: Grabbing versus Production
- Total entrepreneurs: N = ng + np, where np are producers and ng are grabbers.
- Grabbers target rents from natural resources R and use all their capacity to appropriate rents; success of grabbing depends on institutional quality parameter λ.
- λ measures the resource rents accruing to each producer relative to each grabber:
  - When λ = -2.5, the system is completely grabber friendly; grabbers extract the entire rent, each obtaining R/ng.
  - When λ = 2.5, institutions are producer friendly and there are no gains from specialization in grabbing; both grabbers and producers obtain R/N.
- Comparative dynamics:
  - With grabber-friendly institutions (low λ) a country converges to a lower-income steady state (point b’).
  - With producer-friendly institutions (high λ) a country converges to a higher-income steady state (point b”).
  - More producer-friendly institutions can eliminate the resource curse for resource-rich country B relative to resource-poor country A (Mehlum and others, 2006).

### Sample and data definitions
- Geographic sample: transition economies in Central and Eastern Europe and Baltics (CEB), the Commonwealth of Independent States (CIS), and selected Asian countries (China, Mongolia, Vietnam). The sample used in main analysis consists of 27 countries, limited by data availability.
- Time period: 2000 to 2012.
- Dependent variable: GDP growth – average growth rate of real GDP per capita between 2000 and 2012.
- Explanatory variables:
  - initial income – log of GDP per capita, PPP (constant 2005 international $) in 2000 (RGDPpc00),
  - openness – average trade (% of GDP) over the same period,
  - resource abundance – the share of average natural resource exports in GDP in the same period,
  - investments – log of the average ratio of gross capital formation over GDP,
  - population growth – average population growth over the same period,
  - export growth – average annual growth of exports in the same period,
  - institutional quality (IQ) – unweighted average of six World Bank indexes (voice and accountability; political stability and absence of violence/terrorism; government effectiveness; regulatory quality; rule of law; control of corruption), index ranges from -2.5 to 2.5 (2.5 = maximum producer-friendly; -2.5 = maximum grabber-friendly).
- Interaction term included to capture model prediction that the effect of resource abundance on growth depends on institutional quality.

### Key empirical specifications
- Main cross-section regression form:
  G_i = α + β1 I_i + β2 N_i + β3 Inv_i + β4 P_i + β5 X_i + β6 Op_i + β7 IQ_i + β8 (N_i × IQ_i) + ε_i
  where:
  - i is country index,
  - G is per capita real GDP growth,
  - I is initial income (per capita real GDP in 2000),
  - N is natural resource abundance,
  - Inv is investment rate,
  - X is export growth,
  - P is population growth,
  - Op is openness,
  - IQ is institutional quality (World Bank indicators).

### Empirical analysis results (selected coefficient estimates and model fit)
- Sample size: 27 observations (main regressions).
- Selected regression results (columns correspond to alternative specifications; t-values in parentheses; *, ** indicate statistical significance at 5%, 10% levels as reported):
  - Initial income level:
    - (1) -0.86* (-2.54)
    - (2) -1.15* (-3.30)
    - (3) -0.91* (-2.81)
    - (4) -0.76* (-2.40)
    - (5) -1.55 (-2.68)
  - Natural resource abundance:
    - (1) 0.11* (5.42)
    - (2) 0.11* (5.14)
    - (3) 0.11* (5.63)
    - (4) 0.23* (3.30)
    - (5) 0.11* (3.87)
  - Openness:
    - (1) -0.02* (-2.59)
    - (2) -0.02* (-2.60)
    - (3) -0.01* (-1.92)
    - (4) -0.03* (-2.27)
  - Population growth:
    - (1) -1.35* (-3.45)
    - (2) -1.49* (-3.57)
    - (3) -1.36* (-3.65)
    - (4) -1.51* (-4.14)
  - Investments:
    - (1) 6.40* (4.70)
    - (2) 5.86* (4.03)
    - (3) 6.28* (4.83)
    - (4) 6.83* (5.36)
  - Export growth:
    - (1) 0.18** (1.75)
    - (2) 0.16** (1.79)
    - (3) 0.16** (1.91)
  - Rule of law (where included): 1.22** (1.59)
  - Interaction term (Natural resource abundance × Institutional quality):
    - Specification reporting negative interaction: -0.06** (-1.76) with a p–value reported elsewhere as 0.09.
  - Model fit:
    - Observations = 27; Adjusted R2 = 0.75, 0.78, 0.78, 0.80 across specifications (columns (1)–(4)); one specification reports Adjusted R2 = 0.52.
    - Summary multiple correlation: Multiple correlation coefficient: 0.92; Adjusted R2: 0.83; Observations: 20 (for an alternative specification reported).
- Interpretation of key coefficients from main regressions:
  - Natural resource abundance coefficient is positive and statistically significant in multiple specifications (e.g., 0.11* with t-values 5.42, 5.14, 5.63; 0.23* with t-value 3.30).
  - Interaction term between resource abundance and institutional quality is negative (e.g., -0.06** (-1.76)), consistent with the model prediction that resource abundance is harmful to growth when institutions are grabber friendly.
  - Initial income negative coefficients indicate conditional convergence among transition economies.
  - Investment and export growth positively associated with growth; population growth negatively associated with growth.
  - The seven variables (natural resource abundance, export growth, investment, initial income, openness, population growth, interaction term) collectively explain more than 80 percent of variation in growth rates among transition countries in some specifications.

### Alternative regression results and Tobias Kronenberg comparison
- Tobias Kronenberg (MERIT) regression results (alternative specification reported):
  - Dependent variable: AvGroRGDPpC
  - Coefficients (with standard errors, t-statistics, p-values provided in one table):
    - intercept: -5.15 (4.03) -1.28 0.21
    - ShaPrimEx: -12.03 (1.55) -7.74 8.42E-07
    - Log(RGDPpC89): 1.60 (1.08) 1.47 0.16
    - Interaction: 0.375 (0.113) 3.60 0.002
  - Kronenberg regression summary:
    - Table shows a model with three explanatory variables explaining more than 80 percent of variation in growth rates of transition economies during the 1990s.
    - ShaPrimEx coefficient is negative and highly significant (extremely low p-value).
    - Interaction term is highly significant (supports notion that export growth has a positive but asymmetric effect on growth).
- Comparative coefficients (Kronenberg versus current paper, selected):
  - Kronenberg (alternative): Natural resource abundance (ShaPrimEx) = -12.04* (-7.75) in one column of a comparison table.
  - Current paper Regression 4 (alternative column): Natural resource abundance = 0.23* (3.30).
  - Interaction term in Kronenberg specification: 0.38* (3.64); in current paper interaction reported as -0.06** (-1.76).

### Graphical and country-level observations (Mongolia focus)
- Mongolia:
  - Economic growth trend plotted for 2000–2012; regression line reported: y = 0.5562x + 2.7898, R² = 0.1755.
  - From 2009 exponential growth increased due to a large-scale mega copper-gold mining project (Ouy).
  - Government effectiveness indicator (World Governance Indicators) shows values in the slide: -0.70, -0.53, -0.35, -0.18, 0.00 with note “The effectiveness of the government has decreased.”
  - Corruption control plotted: regression line y = -0.0438x + 87.429, R² = 0.5097; note: “The corruption control has been on steady decline, except for the latest effort that has been taken.”
  - Voice and accountability plotted with values ranging up to 0.40 and noted decline as corruption increased.
- Comparative figures:
  - Scatter regressions reported separately for:
    - (a) All transition countries: y = 0.003x^2 - 0.0167x + 4.4882, R² = 0.3985; Mongolia point reported as 6.0668 (presumably GDP growth).
    - (b) Countries with good institutions: y = 0.0028x^2 + 0.134x + 2.911, R² = 0.2964.
    - (c) Countries with bad institutions: y = 0.0053x^2 - 0.1466x + 5.9064, R² = 0.4289.
  - Figures illustrate that an indication of a resource curse appears primarily for countries with bad institutions (grabber friendly), while countries with good institutions show resource-related growth benefits.

### Interpretation and policy-relevant findings
- Empirical findings consistent with theoretical model:
  - Resource abundance can be growth-enhancing in transition economies overall (positive coefficient on resource abundance in main regressions).
  - The negative interaction between resource abundance and institutional quality suggests resources harm growth when institutions are grabber friendly (interaction term -0.06**, p–value 0.09 reported for interaction effect).
- Other robust determinants of growth in the sample:
  - Investment and export growth are positively associated with GDP growth.
  - Initial income negatively associated with subsequent growth (conditional convergence).
  - Population growth and openness show negative associations in several specifications.
- Magnitude of explanatory power:
  - Selected specifications report Adjusted R2 values up to 0.80 and a reported multiple correlation coefficient of 0.92 (Adjusted R2: 0.83 in one summary), indicating a high share of cross-country growth variation explained by the chosen variables in certain models.
- Temporal contrast with earlier literature:
  - The paper notes that prior studies covering earlier periods (e.g., Kronenberg 2004 using 1989–1999 data) found resource curse effects; using data for 2000–2012 the relationship is positive in aggregate, indicating temporal variation in the resource-growth relationship.

### Conclusion
- Cross–section empirical analysis of 27 transition economies between 2000 and 2012 indicates that transition economies benefited from natural resource exports in the sample and period studied.
- While earlier studies reported a negative relationship between natural resources and growth in transition countries, the current analysis finds a positive relationship overall, with the caveat that resource abundance can be detrimental to growth in countries with grabber-friendly institutions.
- The contrast between findings across different years and samples suggests that the relationship between natural resources and growth can vary over time and depends critically on institutional quality and complementary growth factors (investment, export growth, population dynamics).

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_Source: https://www.imf.org/-/media/files/news/seminars/1b_discussant_gombojav.pdf_