Testing for optimality in job search models
Koop, G.M. and Poirier, D. (2002) Testing for optimality in job search models. Econometrics Journal, 4 (2). pp. 257-272. ISSN 1368-4221 (http://dx.doi.org/10.1111/1368-423X.00066)
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Models of search in labor markets are potentially of great use for policy analysis since their parameters are structural. However, a common feature of these models is that an assumption of optimal behavior on the part of agents is necessary to achieve identification. From a classical econometric perspective, this means the assumption of optimality is untestable and, if optimality is not imposed, it is impossible to learn about the unidentified parameters. This paper argues that Bayesian methods can overcome both of these problems. In particular, we discuss testing optimality in stationary job search models with reservation wages. Learning about economically meaningful quantities such as the discount rate and risk aversion, not identified by the data alone, is considered.
ORCID iDs
Koop, G.M.
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Item type: Article ID code: 6944 Dates: DateEventJune 2002PublishedKeywords: bayesian, reservation wage, SIR, posterior simulation, statistics, employment, econometrics, Probabilities. Mathematical statistics, Economic Theory, Economics and Econometrics Subjects: Science > Mathematics > Probabilities. Mathematical statistics
Social Sciences > Economic TheoryDepartment: Strathclyde Business School > Economics Depositing user: Strathprints Administrator Date deposited: 03 Oct 2008 Last modified: 18 Jan 2023 08:31 URI: https://strathprints.strath.ac.uk/id/eprint/6944