Generating Random Optimising Choices

Jan Heufer

Computational Economics, 2014, vol. 44, issue 3, 295-305

Abstract: We provide an efficient way to generate random choices which are consistent with utility maximisation. They are drawn from an approximate uniform distribution on the admissible region on each budget based on a Markovian Monte Carlo algorithm due to Smith (Oper Res 32(6):1296–1308, 1984 ). This can be used to extend Bronars’ (Econometrica 55(3):693–698, 1987 ) method by approximating the power of tests for conditions for which utility maximisation is necessary but not sufficient (e.g., homotheticity, separability, etc.). The approach can also be applied to production analysis. Copyright Springer Science+Business Media New York 2014

Keywords: Monte Carlo methods; Non-parametric tests; Optimisation; Revealed preference (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10614-013-9393-8

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