Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-05T15:22:19.522Z Has data issue: false hasContentIssue false
  • English
  • Français

A Bayesian Change Point Model for Historical Time Series Analysis

Published online by Cambridge University Press:  04 January 2017

Bruce Western  and
Meredith Kleykamp
Bruce Western
Affiliation:
Department of Sociology, Princeton University, Princeton, NJ 08544. e-mail: western@opr.princeton.edu
Meredith Kleykamp
Affiliation:
Department of Sociology, Princeton University, Princeton, NJ 08544. e-mail: western@opr.princeton.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Political relationships often vary over time, but standard models ignore temporal variation in regression relationships. We describe a Bayesian model that treats the change point in a time series as a parameter to be estimated. In this model, inference for the regression coefficients reflects prior uncertainty about the location of the change point. Inferences about regression coefficients, unconditional on the change-point location, can be obtained by simulation methods. The model is illustrated in an analysis of real wage growth in 18 OECD countries from 1965–1992.

Type
Research Article
Information
Political Analysis , Volume 12 , Issue 4: Special Issue on Bayesian Methods , Autumn 2004 , pp. 354 - 374
Copyright
Copyright © Society for Political Methodology 2004 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bai, Jushan, and Perron, Pierre. 1998. “Estimating and Testing Linear Models with Multiple Structural Changes.” Econometrica 66: 47–78.Google Scholar
Bartels, Larry M. 1997. “Specification Uncertainty and Model Averaging.” American Journal of Political Science 41: 641–674.Google Scholar
Beck, Nathaniel. 1983. “Time-Varying Parameter Models.” American Journal of Political Science 27: 557–600.Google Scholar
Beck, Nathaniel, and Katz, Jonathan. 1995. “What to Do (and Not to Do) with Time-Series Cross-Section Data.” American Political Science Review 89: 634–647.Google Scholar
Box, George E.P., Jenkins, Gwilym M., and Reinsel, Gregory C. 1994. Time Series Analysis: Forecasting and Control, 3rd ed. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Brown, R. L., Durbin, J., and Evans, J. M. 1975. “Techniques for Testing the Constancy of Regression Relationships over Time” [with discussion]. Journal of the Royal Statistical Society, Series B 37: 149–192.Google Scholar
Büthe, Tim. 2002. “Taking Temporality Seriously: Modeling History and the Use of Narrative as Evidence.” American Political Science Review 96: 481–494.CrossRefGoogle Scholar
Carlin, Bradley P., and Louis, Thomas A. 2000. Bayes and Empirical Bayes Methods for Data Analysis. New York: Chapman and Hall.Google Scholar
Chin, Choy J.H., and Broemeling, L. D. 1980. “Some Bayesian Inferences for a Changing Linear Model.” Technometrics 22: 71–78.Google Scholar
Freedman, David A. 1983. “A Note on Screening Regression Equations.” American Statistician 37: 152–155.Google Scholar
Hamilton, James D. 1989. “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica 57: 357–384.CrossRefGoogle Scholar
Hamilton, James D. 1994. Time Series Analysis. Princeton, NJ: Princeton University Press.Google Scholar
Hansen, Bruce E. 2000. “Testing for Structural Change in Conditional Models.” Journal of Econometrics 97: 93–115.Google Scholar
Harvey, Andrew C. 1989. Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge, UK: Cambridge University Press.Google Scholar
Hsiao, Cheng. 1986. Analysis of Panel Data. Cambridge, UK: Cambridge University Press.Google Scholar
Isaac, Larry, and Griffin, Larry J. 1989. “Ahistoricism in Time-Series Analyses of Historical Process: Critique, Redirection, and Illustrations from U.S. Labor History.” American Sociological Review 54: 873–890.Google Scholar
Jackman, Simon. 2000. “Estimation and Inference via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo.” American Journal of Political Science 44: 375–404.Google Scholar
Kenworthy, Lane. 2002. “Corporatism and Unemployment in the 1980s and 1990s.” American Sociological Review 67: 367–388.Google Scholar
Kim, Chang-Jin, and Nelson, Charles R. 1999. State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Application. Cambridge, MA: MIT Press.Google Scholar
Lieberman, Robert C. 2002. “Ideas, Institutions, and Political Order: Explaining Political Change.” American Political Science Review 96: 697–712.Google Scholar
Long, J. Scott, and Ervin, Laurie H. 2000. “Using Heteroscedasticity Consistent Standard Errors in the Linear Regression Model.” American Statistician 54: 217–224.Google Scholar
Mitchell, Sara McLaughlin, Gates, Scott, and Hegre, Havard. 1999. “Evolution in Democracy-War Dynamics.” Journal of Conflict Resolution 43: 771–792.Google Scholar
Richards, Mark J., and Kritzer, Herbert M. 2002. “Jurisprudential Regimes in Supreme Court Decision Making.” American Political Science Review 96: 305–320.Google Scholar
Schickler, Eric, and Green, Donald P. 1997. “The Stability of Party Identification in Western Democracies: Results from Eight Panel Surveys.” Comparative Political Studies 30: 450–483.CrossRefGoogle Scholar
Thelen, Kathleen, and Steinmo, Sven. 1992. “Historical Institutionalism in Comparative Politics.” In Structuring Politics: Historical Institutionalism in Comparative Perspective, eds. Steinmo, Sven, Thelen, Kathleen, and Longstreth, Frank. New York: Cambridge University Press, pp. 1–32.Google Scholar
Western, Bruce. 1996. “Vague Theory and Model Uncertainty in Macrosociology.” Sociological Methodology 26: 165–192.CrossRefGoogle Scholar
Western, Bruce, and Healy, Kieran. 1999. “Explaining the OECD Wage Slowdown Recession or Labour Decline?” European Sociological Review 15: 233–249.Google Scholar
Supplementary material: File

Western and Kleykamp supplementary material

Supplementary Material

Download Western and Kleykamp supplementary material(File)
File 57.3 KB