Nonstationary Markov Modeling: An Application to Wage-Influenced Industrial Relocation

Christina M. L. Kelton
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Christina M. L. Kelton: Department of Economics, Wayne State University, Detroit, Michigan 48202 USA

International Regional Science Review, 1984, vol. 9, issue 1, 75-90

Abstract: A recently proposed technique for estimating nonstationary transition probabilities for a Markov process is developed for empirical implementation. Its use is then demonstrated by analyzing the process of industrial relocation for the U.S. apparel industries. Transition probabilities for twenty-one apparel industries and four time periods are estimated with aggregate frequency data and an embedded wage-adjustment model. The stationarity assumption of no wage-rate effect on the transition probabilities cannot be rejected.

Date: 1984
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Persistent link: https://EconPapers.repec.org/RePEc:sae:inrsre:v:9:y:1984:i:1:p:75-90

DOI: 10.1177/016001768400900104

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