Fixed Effects Regression and Effect Heterogeneity

An Illustration Using a Causal Inference Perspective


Fixed effects regressions are commonly used by social scientists to identify causality. However, several criticisms against the fixed effects estimator emerged in recent years. In addition to confounding factors that are associated with time variant covariates, fixed effects can lead to an improper aggregation of heterogeneous effects. In the present chapter, we discuss the problem that pertains to the fixed effect estimator and show techniques that do not suffer from this source of bias. We also illustrate the problem with empirical analysis of Chilean students for the period time from 2007 to 2013. On the basis of the theoretical framework developed in the chapter and empirical findings, we suggest some implications for research in social sciences.


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© Springer Fachmedien Wiesbaden GmbH 2018

Authors and Affiliations

  1. 1.SantiagoChile

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