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Changepoint Analysis of Binary and Ordinal Probit Models: An Application to Bank Rate Policy Under the Interwar Gold Standard

Published online by Cambridge University Press:  04 January 2017

Jong Hee Park
Jong Hee Park*
Affiliation:
Department of Political Science, The University of Chicago, 5828 S. University Ave., Chicago, IL 60637 e-mail: jhp@uchicago.edu
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Abstract

In this paper, I introduce changepoint models for binary and ordered time series data based on Chib's hidden Markov model. The extension of the changepoint model to a binary probit model is straightforward in a Bayesian setting. However, detecting parameter breaks from ordered regression models is difficult because ordered time series data often have clustering along the break points. To address this issue, I propose an estimation method that uses the linear regression likelihood function for the sampling of hidden states of the ordinal probit changepoint model. The marginal likelihood method is used to detect the number of hidden regimes. I evaluate the performance of the introduced methods using simulated data and apply the ordinal probit changepoint model to the study of Eichengreen, Watson, and Grossman on violations of the “rules of the game” of the gold standard by the Bank of England during the interwar period.

Type
Regular Articles
Information
Political Analysis , Volume 19 , Issue 2 , Spring 2011 , pp. 188 - 204
Copyright
Copyright © The Author 2011. Published by Oxford University Press on behalf of the Society for Political Methodology 

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