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Shadow wages, allocative inefficiency, and labor supply in smallholder agriculture

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  • Christopher B. Barrett
  • Shane M. Sherlund
  • Akinwumi A. Adesina

Abstract

This article introduces a method for estimating structural labor supply models in the presence of unobservable wages and deviations of households' marginal revenue product of self‐employed labor from their shadow wage. This method is therefore robust to a wide range of assumptions about labor allocation decisions in the presence of uncertainty, market frictions, locational preferences, etc. We illustrate the method using data from rice producers in Côte d'Ivoire. These data, like previous studies, reveal significant systematic differences between shadow wages and the marginal revenue product of family farm labor. We demonstrate how one can exploit systematic deviations, in the present case related to household characteristics such as the land/labor endowment ratio, to control for both unobservable wages and prospective allocative inefficiency in labor allocation in structural household labor supply estimation.

Suggested Citation

  • Christopher B. Barrett & Shane M. Sherlund & Akinwumi A. Adesina, 2008. "Shadow wages, allocative inefficiency, and labor supply in smallholder agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 21-34, January.
    • Handle: RePEc:bla:agecon:v:38:y:2008:i:1:p:21-34
    DOI: 10.1111/j.1574-0862.2007.00278.x
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    References listed on IDEAS

    as
    1. Emmanuel Skoufias, 1994. "Using Shadow Wages to Estimate Labor Supply of Agricultural Households," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(2), pages 215-227.
    2. Barrett, Christopher B., 1996. "On price risk and the inverse farm size-productivity relationship," Journal of Development Economics, Elsevier, vol. 51(2), pages 193-215, December.
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    9. Sherlund, Shane M. & Barrett, Christopher B. & Adesina, Akinwumi A., 2002. "Smallholder technical efficiency controlling for environmental production conditions," Journal of Development Economics, Elsevier, vol. 69(1), pages 85-101, October.
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