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Not so Harmless After All: The Fixed-Effects Model

  • Thomas Plümper (a1) and Vera E. Troeger (a2)

Abstract

The fixed-effects estimator is biased in the presence of dynamic misspecification and omitted within variation correlated with one of the regressors. We argue and demonstrate that fixed-effects estimates can amplify the bias from dynamic misspecification and that with omitted time-invariant variables and dynamic misspecifications, the fixed-effects estimator can be more biased than the ‘naïve’ OLS model. We also demonstrate that the Hausman test does not reliably identify the least biased estimator when time-invariant and time-varying omitted variables or dynamic misspecifications exist. Accordingly, empirical researchers are ill-advised to rely on the Hausman test for model selection or use the fixed-effects model as default unless they can convincingly justify the assumption of correctly specified dynamics. Our findings caution applied researchers to not overlook the potential drawbacks of relying on the fixed-effects estimator as a default. The results presented here also call upon methodologists to study the properties of estimators in the presence of multiple model misspecifications. Our results suggest that scholars ought to devote much more attention to modeling dynamics appropriately instead of relying on a default solution before they control for potentially omitted variables with constant effects using a fixed-effects specification.

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Authors’ note: We thank Jonathan Kropko and the participants of the workshop “Modeling Politics & Policy in Time and Space” organized by Guy Whitten and Scott Cook at Texas A&M for helpful comments and input.

The replication files for the MC analysis can be found on the PA dataverse: Troeger and Pluemper (2017), “Replication Data for: Not so Harmless After All: The Fixed-Effects Model”, doi:10.7910/DVN/RAUIHG, Harvard Dataverse.

Contributing Editor: Suzanna Linn

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Acemoglu, D., Johnson, S., James, A., Robinson, J. A., and Yared, P.. 2008. Income and democracy. American Economic Review 98(3):808842.
Achen, C. H.2000. Why lagged dependent variables can suppress the explanatory power of other independent variables. Presented at the Annual Meeting of the Political Methodology, Los Angeles.
Adolph, C., Butler, D. M., and Wilson, S. E.. 2005. Like shoes and shirt, one size does not fit all: Evidence on time series cross-section estimators and specifications from Monte Carlo experiments. unpubl. Manuscript, Harvard University.
Ahn, S. C., and Low, S.. 1996. A reformulation of the Hausman-test for regression models with pooled cross-section-time-series data. Journal of Econometrics 71:309319.
Ahn, S. C., Lee, Y. H., and Schmidt, P.. 2013. Panel data models with multiple time-varying individual effects. Journal of Econometrics 174:114.
Allan, J. P., and Scruggs, L.. 2004. Political partisanship and welfare state reform in advanced industrial societies. American Journal of Political Science 48(3):496512.
Angrist, J. D., and Pischke, J. S.. 2009. Mostly harmless econometrics. An empiricists’ companion . Princeton: Princeton University Press.
Antonakis, J., Bendahan, S., Jacquart, P., and Lalive, R.. 2010. On making causal claims: a review and recommendations. Leadership Quarterly 21:10861120.
Arellano, M. 1993. On the testing of correlated effects with panel data. Journal of Econometrics 59(1–2):8797.
Arellano, M., and Bond, S.. 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58:277297.
Baltagi, B. 2001. Econometric analysis of panel data . John Wiley & Sons.
Beck, N., and Katz, J. N.. 1995. What to do (and not to do) with time-series cross-section data. American Political Science Review 89(03):634647.
Beck, N., and Katz, J. N.. 2001. Throwing out the Baby with the Bath Water: A comment on Green, Kim, and Yoon. International Organization 55:487-+.
Becker, S. O., and Woessmann, L.. 2013. Not the opium of the people: Income and secularization in a panel of Prussian counties. American Economic Review 103(3):539544.
Bell, A., and Jones, K.. 2015. Explaining fixed effects: Random effects modeling of time-series cross-sectional and panel data. Political Science Research and Methods 3(01):133153.
Besley, T., and Reynal-Querol, M.. 2011. Do democracies select more educated leaders? American Political Science Review 105(3):552566.
Blundell, R., and Bond, S.. 1998. Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87(1):115143.
Bole, V., and Rebec, P.. 2013. Bootstrapping the Hausman test in panel data models. Communications in Statistics-Simulation and Computation 42(3):650670.
Box, G. E. P. 1976. Science and Statistics. Journal of the American Statistical Association 71:791799.
Clark, T. S., and Linzerx, D. A.. 2015. Should I use fixed or random effects? Political Science Research and Methods 3(02):399408.
DeBoef, S., and Keele, L. J.. 2008. Taking time seriously: Dynamic regression. American Journal of Political Science 52(1):184200.
Egorov, G., Guriev, S., and Sonin, K.. 2009. Why resource-poor dictators allow freer media: A theory and evidence from panel data. American Political Science Review 103(4):645668.
Franzese, R. J. Jr. 2003a. Multiple hands on the wheel: empirically modeling partial delegation and shared policy control in the open and institutionalized economy. Political Analysis 445474.
Franzese, R.J. 2003b. Quantitative empirical methods and the context-conditionality of classic and modern comparative politics. CP: Newsletter of the Comparative Politics Organized Section of the American Political Science Association 14(1):2024.
Franzese, R. J. Jr, and Hays, J. C.. 2007. Spatial econometric models of cross-sectional interdependence in political science panel and time-series-cross-section data. Political Analysis 140164.
Franzese, R., and Kam, C.. 2009. Modeling and interpreting interactive hypotheses in regression analysis . University of Michigan Press.
Frondel, M., and Vance, C.. 2010. Fixed, random, or something in between? A variant of Hausman’s specification test for panel data estimators. Economics Letters 107:327329.
Gamm, G., and Kousser, T.. 2010. Broad bills or particularistic policy? Historical patterns in American state legislatures. American Political Science Review 104(1):151170.
Gerber, A. S., Gimpel, J. G., Green, D. P., and Shaw, D. R.. 2011. How large and long-lasting are the persuasive effects of televised campaign ads? Results from a randomized field experiment. American Political Science Review 105(01):135150.
Getmansky, A., and Zeitzoff, T.. 2014. Terrorism and voting: The effect of rocket threat on voting in Israeli elections. American Political Science Review 108(3):588604.
Godfrey, L. G. 1998. Hausman tests for autocorrelation in the presence of lagged dependent variables Some further results. Journal of econometrics 82(2):197207.
Green, D. P., Kim, S. Y., and Yoon, D. H.. 2001. Dirty Pool. International Organization 55:441-+.
Guisinger, A., and Singer, D. A.. 2010. Exchange Rate proclamations and inflation-fighting credibility. International Organization 64(2):313337.
Haber, S., and Menaldo, V.. 2011. Do natural resources fuel authoritarianism? A reappraisal of the resource curse. American Political Science Review 105(01):126.
Hahn, J., and Kuersteiner, G.. 2011. Bias reduction for dynamic nonlinear panel models with fixed effects. Econometric Theory 27:11521191.
Harris, M. N., Kostenko, W., Matyas, L., and Timol, I.. 2009. The robustness of estimators for dynamic panel data models to misspecification. Singapore Economic Review 54:399426.
Hausman, J. A. 1978. Specification tests in econometrics. Econometrica 46(6):12511271.
Hedrick, P. W. 2005. A standardized genetic differentiation measure. Evolution 59:16331638.
Hendry, D. F. 1995. Dynamic econometrics . Oxford: Oxford University Press.
Hoechle, D. 2007. Robust standard errors for panel regressions with cross-sectional dependence. Stata Journal 7(3):281.
Hsiao, C. 2014. Analysis of panel data . Cambridge: Cambridge University Press.
Huber, J. D., and Stevens, E.. 2012. Democracy and the left: Social policy and inequality in Latin America. Journal of Social Policy 42(3):660661.
Humphreys, M., and Weinstein, J. M.. 2006. Handling and manhandling civilians in civil war. American Political Science Review 100(3):429.
Kayser, M. A., and Satyanath, S.. 2014. Fairytale Growth. Unp. Manuscript, Hertie School of Governance, Berlin.
Kayser, M. A. 2009. Partisan waves: International business cycles and electoral choice. American Journal of Political Science 53(4):950970.
Keele, L. J., and Kelly, N. J.. 2006. Dynamic models for dynamic theories: The ins and outs of LDVs. Political Analysis 14(2):186205.
Keele, L., Linn, S., and Webb, C. M.. 2016. Treating time with all due seriousness. Political Analysis 24(1):3141.
Kiviet, J. F. 1995. On bias, inconsistency, and efficiency of various estimators in dynamic panel data models. Journal of Econometrics 68(1):5378.
Kogan, V., Lavertu, S., and Peskowitz, Z.. 2016. Performance federalism and local democracy: Theory and evidence from school tax referenda. American Journal of Political Science 60(2):418435.
Lancester, T. 2000. The Incidental Parameter Problem since 1948. Journal of Econometrics 95:391413.
Lebo, M. J., McGlynn, A. J., and Koger, G.. 2007. Strategic party government: Party influence in congress, 1789–2000. American Journal of Political Science 51(3):464481.
Lee, Y. 2012. Bias in dynamic panel models under time series misspecification. Journal of Econometrics 169:5460.
Lipsmeyer, C. S., and Zhu, L.. 2011. Immigration, globalization, and unemployment benefits in developed EU states. American Journal of Political Science 55(3):647664.
Lupu, N., and Pontusson, J.. 2011. The structure of inequality and the politics of redistribution. American Political Science Review 105(02):316336.
Menaldo, V. 2012. The middle east and north Africa’s resilient monarchs. The Journal of Politics 74(3):707722.
Morgan, S. L., and Winship, C.. 2007. Counterfactuals and causal inference. Methods and principles for social research . Cambridge: Cambridge University Press.
Mukherjee, B., Smith, D. L., and Li, Q.. 2009. Labor (im) mobility and the politics of trade protection in majoritarian democracies. Journal of Politics 71(1):291308.
Neumayer, E., and Plümper, T.. 2017. Robustness tests for quantitative research . Cambridge University Press.
Neumayer, E., and Plümper, T.. 2016. W. Political Science Research and Methods 4(1):175193.
Neyman, J., and Scott, E.. 1948. Consistent estimates based on partially consistent observations. Econometrica 16:132.
Nickell, S. 1981. Biases in dynamic models with fixed effects. Econometrica 49:14171426.
North, D. C. 1990. Institutions, institutional change, and economic performance . Cambridge: Cambridge University Press.
Park, J. H. 2012. A unified method for dynamic and cross-sectional heterogeneity: Introducing hidden markov panel models. American Political Science Review 56:10401054.
Pickup, M.2017. A general-to-specific approach to dynamic panel models with a very small $T$ . Presented to the 2017 Meeting of the Midwest Political Science Association, Chicago Illinois.
Plümper, T., Troeger, V. E., and Manow, P.. 2005. Panel data analysis in comparative politics: Linking method to theory. European Journal of Political Research 44(2):327354.
Plümper, T., and Troeger, V. E.. 2007. Efficient estimation of time-invariant and rarely changing variables in finite sample panel analyses with unit fixed effects. Political Analysis 15(2):124139.
Plümper, T., and Troeger, V. E.. 2011. Fixed-effects vector decomposition: properties, reliability, and instruments. Political Analysis 19(2):147164.
Ross, M. L. 2008. Oil, Islam, and women. American Political Science Review 102(1):107123.
Soroka, S. N., Stecula, D. A., and Wlezien, C.. 2015. It’s (change in) the (future) economy, stupid: economic indicators, the media, and public opinion. American Journal of Political Science 59(2):457474.
Treisman, D. 2015. Income, democracy, and leader turnover. American Journal of Political Science 59(4):927942.
Troeger, Vera, and Pluemper, Thomas. 2017. Replication Data for: Not so Harmless After All: The Fixed-Effects Model. doi:10.7910/DVN/RAUIHG, Harvard Dataverse.
Wegener, A. 1912. Die Entstehung der Kontinente. Geologische Rundschau 3:276292.
Wilson, S. E., and Butler, D. M.. 2007. A lot more to do: The sensitivity of time-series cross-section analyses to simple alternative specifications. Political Analysis 15(2):101123.
Wooldridge, J. M. 2002. Econometric analysis of cross section and panel data . Cambridge, MA: MIT Press.
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