Estimating the Technology Coefficients in Linear Programming Models

Bruce L. Dixon and Robert H. Hornbaker

No 270519, 1989 Annual Meeting, July 30-August 2, Baton Rouge, Louisiana from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)

Abstract: Linear constraints for mathematical programming models are . demonstrated to be random coefficient regression (RCR) models when estimating constraint coefficients from samples. Monte·carlo experiments show an RCR estimator preferable to least squares although least squares is also acceptable. Dependence between output levels and technical coefficients can lead to biased estimates.

Keywords: Agricultural and Food Policy; Research and Development/Tech Change/Emerging Technologies (search for similar items in EconPapers)
Pages: 15
Date: 1989-07-30
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea89:270519

DOI: 10.22004/ag.econ.270519

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