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Sample Selection in Appalachian Research

Author

Listed:
  • Stratford Douglas

    (Department of Economics, West Virginia University)

  • Annie Walker

    (Department of Economics, West Virginia University)

Abstract

The Appalachian Regional Commission’s definition of the Appalachian region is the one used most often by scholars, politicians, and the popular press. The uncritical use of this definition of Appalachia raises issues of both selection bias and excess heterogeneity in regression analysis of Appalachian income and growth. The ARC was created as part of President Johnson’s war on poverty, and the geographical extent of its purview has been driven by politics and by the geography of poverty, neither of which is exogenous. It is well known that endogenous choice of a sample creates bias and inconsistency in estimation of regression coefficients. To identify the counties that belong to the Appalachian region exogenously we use an algorithm based on three criteria: topography, contiguity, and prevalence of slavery in the 1860 census. We apply our sample to growth regressions using data from 1970 to 2008, addressing the question of the existence of a resource curse from coal extraction.

Suggested Citation

  • Stratford Douglas & Annie Walker, 2012. "Sample Selection in Appalachian Research," Working Papers 12-01, Department of Economics, West Virginia University.
  • Handle: RePEc:wvu:wpaper:12-01
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    File URL: http://be.wvu.edu/phd_economics/pdf/12-01.pdf
    File Function: First Version, August 31, 2012
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    References listed on IDEAS

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    1. Jeffrey D. Sachs & Andrew M. Warner, 1995. "Natural Resource Abundance and Economic Growth," NBER Working Papers 5398, National Bureau of Economic Research, Inc.
    2. Frederick van der Ploeg, 2011. "Natural Resources: Curse or Blessing?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 366-420, June.
    3. B. James Deaton & Ekaterina Niman, 2012. "An empirical examination of the relationship between mining employment and poverty in the Appalachian region," Applied Economics, Taylor & Francis Journals, vol. 44(3), pages 303-312, January.
    4. Mark D. Partridge & Michael R. Betz & Linda Lobao, 2013. "Natural Resource Curse and Poverty in Appalachian America," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 449-456.
    5. Guy Michaels, 2011. "The Long Term Consequences of Resource‐Based Specialisation," Economic Journal, Royal Economic Society, vol. 121(551), pages 31-57, March.
    6. James, Alex & Aadland, David, 2011. "The curse of natural resources: An empirical investigation of U.S. counties," Resource and Energy Economics, Elsevier, vol. 33(2), pages 440-453, May.
    7. Matthew J. Higgins & Daniel Levy & Andrew T. Young, 2006. "Growth and Convergence across the United States: Evidence from County-Level Data," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 671-681, November.
    8. Edward B. Barbier, 2005. "Natural Resource-Based Economic Development in History," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 6(3), pages 103-152, July.
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    11. Sachs, Jeffrey D & Warner, Andrew M, 1997. "Sources of Slow Growth in African Economies," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 6(3), pages 335-376, October.
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    Cited by:

    1. Betz, Michael R. & Partridge, Mark D. & Farren, Michael & Lobao, Linda, 2015. "Coal mining, economic development, and the natural resources curse," Energy Economics, Elsevier, vol. 50(C), pages 105-116.
    2. Munasib, Abdul & Rickman, Dan S., 2015. "Regional economic impacts of the shale gas and tight oil boom: A synthetic control analysis," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 1-17.

    More about this item

    Keywords

    Sample Selection; Regions; Resource Curse;

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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