Testing for Optimization Behavior in Production when Data is with Measurement Errors: A Bayesian Approach

Mike Tsionas and Valentin Zelenyuk

No WP012022, CEPA Working Papers Series from University of Queensland, School of Economics

Abstract: The purpose of this paper is to develop formal tests for cost / profitt rationalization of observed data sets under measurement errors in both prices and quantities. The new techniques are based on new statistical formulations for inequalities that describe cost and pro t rationalizability, developed in a Bayesian framework. The new likelihood-based methods of inference are introduced and then illustrated using a data set of large U.S. banks. We also develop various robustness checks, including a normal and lognormal speci cation of the data generating process, as well as a multivariate mixture-of-normal-distributions.

Keywords: Cost Minimization; Profit Maximization; Likelihood-based methods; Markov Chain Monte Carlo; Banking. (search for similar items in EconPapers)
Date: 2022-01
New Economics Papers: this item is included in nep-ecm, nep-eff and nep-his
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Persistent link: https://EconPapers.repec.org/RePEc:qld:uqcepa:173

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