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Estimating Monotone Concave Stochastic Production Frontiers

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  • Mike G. Tsionas

Abstract

Recent research shows that the search for Bayesian estimation of concave production functions is a fruitful area of investigation. In this article, we use a flexible cost function that satisfies globally the monotonicity and curvature properties to estimate features of the production function. Specification of a globally monotone concave production function is a difficult task which is avoided here by using the first-order conditions for cost minimization from a globally monotone concave cost function. The problem of unavailable factor prices is bypassed by assuming structure for relative prices in the first-order conditions. The new technique is shown to perform well in a Monte Carlo experiment as well as in an empirical application to rice farming in India.

Suggested Citation

  • Mike G. Tsionas, 2022. "Estimating Monotone Concave Stochastic Production Frontiers," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1403-1414, June.
    • Handle: RePEc:taf:jnlbes:v:40:y:2022:i:3:p:1403-1414
    DOI: 10.1080/07350015.2021.1931240
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