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How Smart Is my Dummy? Time Series Tests for the Influence of Politics

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  • Caporale, Tony
  • Grier, Kevin

Abstract

Of necessity, many tests for political influence on policies or outcomes involve the use of dummy variables. However, it is often the case that the hypothesis against which the political dummies are tested is the null hypothesis that the intercept is otherwise constant throughout the sample. This simple null can cause inference problems if there are (nonpolitical) intercept shifts in the data and the political dummies are correlated with these unmodeled shifts. Here we present a method for more rigorously testing the significance of political dummy variables in single equation models estimated with time series data. Our method is based on recent work on detecting multiple regime shifts by Bai and Perron. The article illustrates the potential problem caused by an overly simple null hypothesis, exposits the Bai and Perron model, gives a proposed methodology for testing the significance of political dummy variables, and illustrates the method with two examples. Before the curse of statistics fell upon mankind we lived a happy, innocent life —Hilaire Belloc, On Statistics

Suggested Citation

  • Caporale, Tony & Grier, Kevin, 2005. "How Smart Is my Dummy? Time Series Tests for the Influence of Politics," Political Analysis, Cambridge University Press, vol. 13(1), pages 77-94, January.
    • Handle: RePEc:cup:polals:v:13:y:2005:i:01:p:77-94_00
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    Citations

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    Cited by:

    1. Tony Caporale & Marc Poitras, 2014. "Voter turnout in US presidential elections: does Carville’s law explain the time series?," Applied Economics, Taylor & Francis Journals, vol. 46(29), pages 3630-3638, October.
    2. Kevin Grier & Haichun Ye, 2009. "Twin Sons Of Different Mothers: The Long And The Short Of The Twin Deficits Debate," Economic Inquiry, Western Economic Association International, vol. 47(4), pages 625-638, October.
    3. Fang‐Shuo Chang & Shiu‐Sheng Chen & Po‐Yuan Wang, 2020. "Politics and the UK's monetary policy," Scottish Journal of Political Economy, Scottish Economic Society, vol. 67(5), pages 486-522, November.
    4. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    5. Shiu-Sheng Chen & Chun-Chieh Wang, 2014. "Do Politics Cause Regime Shifts In Monetary Policy?," Contemporary Economic Policy, Western Economic Association International, vol. 32(2), pages 492-502, April.
    6. Mishra, Ankita & Moosa, Imad A. & Tawadros, George B. & Mishra, Vinod, 2023. "The effect of political and bureaucratic regime changes on Australia's real interest rate," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 124-136.
    7. Zeravan Abdulmuhsen Asaad & Amjad Saber Al-Delawi & Omed Rafiq Fatah & Awaz Mohamed Saleem, 2023. "Oil Exports, Political Issues, and Stock Market Nexus," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 362-373, January.
    8. Paul D. Mueller, 2016. "Public and Private Institutions in the Federal Reserve," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 31(Fall 2016), pages 49-68.
    9. Alan Marco & Shawn Miller, & Ted Sichelman, 2015. "Do Economic Downturns Dampen Patent Litigation?," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 12(3), pages 481-536, September.
    10. Edward Feser, 2013. "Isserman’s Impact," International Regional Science Review, , vol. 36(1), pages 44-68, January.

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