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Modeling Conditional Yield Densities

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  • Alan P. Ker
  • Keith Coble

Abstract

Given the increasing interest in agricultural risk, many have sought improved methods to characterize conditional crop-yield densities. While most have postulated the Beta as a flexible alternative to the Normal, others have chosen nonparametric methods. Unfortunately, yield data tends not to be sufficiently abundant to invalidate many reasonable parametric models. This is problematic because conclusions from economic analyses, which require estimated conditional yield densities, tend not to be invariant to the modeling assumption. We propose a semiparametric estimator that, because of its theoretical properties and our simulation results, enables one to empirically proceed with a higher degree of confidence. Copyright 2003, Oxford University Press.

Suggested Citation

  • Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
    • Handle: RePEc:oup:ajagec:v:85:y:2003:i:2:p:291-304
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    File URL: http://hdl.handle.net/10.1111/1467-8276.00120
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