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Commodity price shocks, growth and structural transformation in low-income countries

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  • McGregor, Thomas

Abstract

This paper uses a panel-VAR approach to estimate both the dynamic and structural macroeconomic response of resource-rich, low-income countries to global commodity price shocks. I use a block recursive ordering, as well as a simple Choleski decomposition, to identify structural commodity price shocks for a set of developing countries. The block recursive identification strategy assumes only that global macroeconomic conditions do not respond to individual low-income country conditions contemporaneously. The results suggest that a one standard deviation increase in commodity prices raises per capita income in developing countries by 0.26% and government spending and investment by 4.4% and 12.4%. The effects are larger for less developed countries, economies with fixed exchange rate regimes and those that are more depended on commodity exports. Commodity price shocks also result in significant transformation of these economies, with the share of value-added in manufacturing contracting by 0.17–0.22 percentage points. Whilst these effects may appear small, they represent the effect of exogenous commodity price shocks that are not due to changes in aggregate demand or global financial conditions. This suggests that commodity price movements alone may be less important in explaining the volatility of low-income country growth than other explanations. Taken together, these results present a more nuanced picture of the ‘resource curse’ in poor countries. Whilst per capital income levels are positively affected by resource booms, the potential for de-industrialisation does exist. The channel through which this link operates appears to be the real exchange rate, with resource booms leading to appreciation pressures. To illustrate the relevance of these results, I investigate the impact of the recent oil price collapse on the Nigerian economy.

Suggested Citation

  • McGregor, Thomas, 2017. "Commodity price shocks, growth and structural transformation in low-income countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 285-303.
  • Handle: RePEc:eee:quaeco:v:65:y:2017:i:c:p:285-303
    DOI: 10.1016/j.qref.2017.01.006
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    Cited by:

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    3. Thomas McGregor, 2017. "Pricing sovereign debt in resource rich economies," OxCarre Working Papers 194, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    4. Gnangnon, Sèna Kimm, 2022. "Internet, Participation in International Trade, and Tax Revenue Instability," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 37(2), pages 267-315.
    5. Kacou, Kacou Yves Thierry & Kassouri, Yacouba & Evrard, Talnan Hongwopena & Altuntaş, Mehmet, 2022. "Trade openness, export structure, and labor productivity in developing countries: Evidence from panel VAR approach," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 194-205.
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    7. Diego A. Agudelo & Ignacio Arango, 2017. "How does information disclosure affect liquidity? Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16944, Universidad EAFIT.
    8. Helder Ferreira de Mendonça & Iven Silva Valpassos, 2022. "Combination of economic policies: how the perfect storm wrecked the Brazilian economic growth," Empirical Economics, Springer, vol. 63(3), pages 1135-1157, September.
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    More about this item

    Keywords

    Dutch disease; Natural resources; Structural transformation; Panel-VAR;
    All these keywords.

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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