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

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  • Christina M. L. Kelton

    (Department of Economics, Wayne State University, Detroit, Michigan 48202 USA)

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.

Suggested Citation

  • Christina M. L. Kelton, 1984. "Nonstationary Markov Modeling: An Application to Wage-Influenced Industrial Relocation," International Regional Science Review, , vol. 9(1), pages 75-90, September.
    • Handle: RePEc:sae:inrsre:v:9:y:1984:i:1:p:75-90
    DOI: 10.1177/016001768400900104
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    References listed on IDEAS

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