Abstract

The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects. This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias, and we illustrate our arguments and our method using National Longitudinal Survey of Youth 1979 (NLSY79) data. data.

Highlights

  • The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists

  • We develop this argument initially using the potential outcomes approach to explain what we mean by selection on baseline differences and by heterogeneous causal effects

  • Selection, bias will vary over values of the propensity score

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Summary

Potential Outcome Causal Models

Gatekeepers for a particular program (college admissions officers, for example) will select participants on the grounds that they are the ones who will benefit most; in other cases people choose the treatment they think will be most beneficial for them These considerations point to heterogeneity of causal effects according to the likelihood of receiving (through being allocated to, or choosing) treatment, and recently Brand and Xie (2010), Xie, Brand, and Jann (2012), and Brand and Davis (2011) have analyzed heterogeneity in treatment effects across the values of the estimated propensity score. Investigating heterogeneity according to propensity score values means examining how average treatment effects differ according the estimated probability of receiving treatment

Classical Selection Bias
We can write
Classical Selection Bias and Heterogeneous Causal Effects
Common Support and Partial Observability
The General Case
Robustness Tests
Data and Variables
Analysis and Robustness of Negative Selection
Conclusion
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