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A Note on Cost Functions and the Regression Fallacy

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  • Martin, William J.

Abstract

Random variation in output may lead to serious bias in cost function estimates. Despite the availability of simple, consistent instrumental variable estimators to deal with this problem, most empirical studies appear to have ignored this errors-in-variables problem, or dealt with it in an ad hoc manner. In this note, an instrumental variable approach is suggested, and applied to the estimation of cost-output relationships for a sample of irrigated citrus farms. Ordinary least squares was found to result in a statistically significant bias. Although this bias did not alter the economic interpretation of the results for the sample used, the bias is likely to be more serious for samples with greater chance variation in output. Thus, it is argued that all cost function studies should explicitly deal with this problem.

Suggested Citation

  • Martin, William J., 1983. "A Note on Cost Functions and the Regression Fallacy," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 51(03), pages 1-7, December.
    • Handle: RePEc:ags:remaae:12514
    DOI: 10.22004/ag.econ.12514
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    Cited by:

    1. Kawasaki, Kentaro, 2010. "The costs and benefits of land fragmentation of rice farms in Japan," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 1-18.
    2. Kawasaki, Kentaro, 2011. "The Impact of Land Fragmentation on Rice Production Cost and Input Use," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 13, pages 1-14.

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    Keywords

    Demand and Price Analysis;

    Statistics

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