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Application Of A Dynamic Panel Data Estimator To Cross-Country Coffee Demand: A Tale Of Two Eras

Author

Listed:
  • Michael S. Webb

    (School of Economics and Finance, Victoria University of Wellington)

  • Viv B Hall

    () (School of Economics and Finance, Victoria University of Wellington)

Abstract

We estimate price and income elasticities of demand for green coffee beans in panels of up to 40 countries, both during and after the operation of export quotas under International Coffee Agreements. The dynamic panel estimator proposed in Han and Phillips (2007) is used because it is a consistent estimator, for any length of panel, regardless of the presence of unit roots. Dynamic panel data models, of any type, do not seem to have been previously applied to coffee demand. We find evidence of a concave relationship between income and coffee consumption for countries which are members of the International Coffee Organization, but no evidence of such a relationship for other countries. A further conclusion is that measures which increase the price of coffee beans can be expected to have little effect on coffee sales.

Suggested Citation

  • Michael S. Webb & Viv B Hall, 2009. "Application Of A Dynamic Panel Data Estimator To Cross-Country Coffee Demand: A Tale Of Two Eras," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 34(1), pages 1-17, June.
  • Handle: RePEc:jed:journl:v:34:y:2009:i:1:p:1-17
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    References listed on IDEAS

    as
    1. Mehta, A. & Chavas, Jean-Paul, 2008. "Responding to the Coffee Crisis: What We Can Learn from Price Dynamics," Working Papers 201444, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    2. Herrmann, Roland, 1986. "Free riders and the redistributive effects of international commodity agreements: The Case of Coffeee," Journal of Policy Modeling, Elsevier, vol. 8(4), pages 597-621.
    3. Mehta, Aashish & Chavas, Jean-Paul, 2008. "Responding to the coffee crisis: What can we learn from price dynamics?," Journal of Development Economics, Elsevier, vol. 85(1-2), pages 282-311, February.
    4. Olekalns, Nilss & Bardsley, Peter, 1996. "Rational Addiction to Caffeine: An Analysis of Coffee Consumption," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 1100-1104, October.
    5. Lord, M J, 1991. "Price Formation in Commodity Markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 239-254, July-Sept.
    6. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    7. Durevall, Dick, 2005. "Demand for Coffee: The Role of Prices, Preferences and Market Power," Working Papers in Economics 162, University of Gothenburg, Department of Economics.
    8. Feuerstein, Switgard, 2002. "Do coffee roasters benefit from high prices of green coffee?," International Journal of Industrial Organization, Elsevier, vol. 20(1), pages 89-118, January.
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    More about this item

    Keywords

    Coffee Demand; Dynamic Panel Data; International Coffee Organization;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F53 - International Economics - - International Relations, National Security, and International Political Economy - - - International Agreements and Observance; International Organizations
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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