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Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects

Published online by Cambridge University Press:  04 January 2017

Thomas Plümper and
Vera E. Troeger
Thomas Plümper
Affiliation:
Department of Government, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom, and Max-Planck-Institute of Economics, Kahlaische Strasse 10, 07745 Jena, Germany. e-mail: tpluem@essex.ac.uk (corresponding author)
Vera E. Troeger
Affiliation:
Department of Government, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom, and Max-Planck-Institute of Economics, Kahlaische Strasse 10, 07745 Jena, Germany. e-mail: vtroe@essex.ac.uk
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Abstract

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This paper suggests a three-stage procedure for the estimation of time-invariant and rarely changing variables in panel data models with unit effects. The first stage of the proposed estimator runs a fixed-effects model to obtain the unit effects, the second stage breaks down the unit effects into a part explained by the time-invariant and/or rarely changing variables and an error term, and the third stage reestimates the first stage by pooled OLS (with or without autocorrelation correction and with or without panel-corrected SEs) including the time-invariant variables plus the error term of stage 2, which then accounts for the unexplained part of the unit effects. We use Monte Carlo simulations to compare the finite sample properties of our estimator to the finite sample properties of competing estimators. In doing so, we demonstrate that our proposed technique provides the most reliable estimates under a wide variety of specifications common to real world data.

Information

Type
Research Article
Information
Political Analysis , Volume 15 , Issue 2: Special Issue: Time-Series Cross-Sectional Analysis , Spring 2007, pp. 124 - 139
Copyright
Copyright © The Author 2007. Published by Oxford University Press on behalf of the Society for Political Methodology 

References

Acemoglu, Daron, Johnson, Simon, Robinson, James, and Thaicharoen, Yunyong. 2002. Institutional causes, macroeconomic symptoms: Volatility, crises and growth. NBER working paper 9124.Google Scholar
Amemiya, Takeshi, and MaCurdy, Thomas E. 1986. Instrumental-variable estimation of an error-components model. Econometrica 54: 869–81.CrossRefGoogle Scholar
Baltagi, Badi H. 2001. Econometric analysis of panel data. Chichester, UK: Wiley and Sons.Google Scholar
Baltagi, Badi H., Bresson, Georges, and Pirotte, Alain. 2003. Fixed effects, random effects or Hausman-Taylor? A pretest estimator. Economics Letters 79: 361–9.CrossRefGoogle Scholar
Baltagi, Badi H., and Khanti-Akom, Sophon. 1990. On efficient estimation with panel data: An empirical comparison of instrumental variable estimators. Journal of Applied Econometrics 5: 401–6.Google Scholar
Beck, Nathaniel. 2001. Time-series-cross-section data: What have we learned in the past few years? Annual Review of Political Science 4: 271–93.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: 634–47.Google Scholar
Beck, Nathaniel, and Katz, Jonathan. 2001. Throwing out the baby with the bath water: A comment on Green, Kim, and Yoon. International Organization 55: 487–95.Google Scholar
Breusch, Trevor S., Mizon, Grayham E., and Schmidt, Peter. 1989. Efficient estimation using panel data. Econometrica 57: 695–700.CrossRefGoogle Scholar
Cornwell, Christopher, and Rupert, Peter. 1988. Efficient estimation with panel data: An empirical comparison of instrumental variables estimators. Journal of Applied Econometrics 3: 149–55.Google Scholar
Egger, Peter, and Pfaffermayr, Michael. 2004. Distance, trade and FDI: A Hausman-Taylor SUR approach. Journal of Applied Econometrics 19: 227–46.CrossRefGoogle Scholar
Elbadawi, Ibrahim, and Sambanis, Nicholas. 2002. How much war will we see? Explaining the prevalence of civil war. Journal of Conflict Resolution 46: 307–34.Google Scholar
Green Donald, P., Kim, Soo Yeon, and Yoon, David H. 2001. Dirty pool. International Organization 55: 441–68.Google Scholar
Greenhalgh, C., Longland, M., and Bosworth, D. 2001. Technological activity and employment in a panel of UK firms. Scottish Journal of Political Economy 48: 260–82.Google Scholar
Hausman, Jerry A. 1978. Specification tests in econometrics. Econometrica 46: 1251–71.Google Scholar
Hausman, Jerry A., and Taylor, William E. 1981. Panel data and unobservable individual effects. Econometrica 49: 1377–98.Google Scholar
Hsiao, Cheng. 1987. Identification. In Econometrics, ed. Eatwell, J., Milgate, M., and Newman, P., 95–100. London: W.W. Norton.Google Scholar
Hsiao, Cheng. 2003. Analysis of panel data. Cambridge: Cambridge University Press.Google Scholar
Huber, Evelyne, and Stephens, John D. 2001. Development and crisis of the welfare state. Parties and policies in global markets. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
Iversen, Torben, and Cusack, Thomas. 2000. The causes of welfare state expansion. Deindustrialization of globalization. World Politics 52: 313–49.Google Scholar
King, Gary, Keohane, Robert O., and Verba, Sidney. 1994. Designing social inquiry: Scientific inference in qualitative research. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Knack, Stephen. 1993. The voter participation effects of selecting jurors from registration lists. Journal of Law and Economics 36: 99–114.Google Scholar
Oaxaca, Ronald L., and Geisler, Iris. 2003. Fixed effects models with time-invariant variables. A theoretical note. Economics Letters 80: 373–7.Google Scholar
Plumper, Thomas, Troeger, Vera E., and Manow, Philip. 2005. Panel data analysis in comparative politics. Linking method to theory. European Journal of Political Research 44: 327–54.CrossRefGoogle Scholar
Wilson, Sven E., and Butler, Daniel M. 2007. A lot more to do: The sensitivity of time-series cross-section analyses to simple alternative specifications. Political Analysis 10.1093/pan/mpl012.Google Scholar
Wooldridge, Jeffrey M. 2002. Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.Google Scholar
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