On the Sensitivity of Return to Schooling Estimates to Estimation Methods, Model Specification, and Influential Outliers If Identification Is Weak

David Jaeger and Juliane Parys ()
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Juliane Parys: McKinsey&Co

No 3961, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We provide a comparison of return to schooling estimates based on an influential study by Angrist and Krueger (1991) using two stage least squares (TSLS), limited information maximum likelihood (LIML), jackknife (JIVE), and split sample instrumental variables (SSIV) estimation. We find that the estimated return to education is quite sensitive to the age controls used in the models as well as the estimation method used. In particular, we provide evidence that JIVE coefficients' standard errors are inflated by a group of extreme years of education observations, for which identification is especially weak. We propose to use Cook's Distance in order to identify influential outliers having substantial influence on first-stage JIVE coefficients and fitted values.

Keywords: Cook's Distance; heteroskedasticity; outliers; return to education; specification; weak instruments (search for similar items in EconPapers)
JEL-codes: C13 C31 J31 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2009-01
New Economics Papers: this item is included in nep-ecm, nep-edu and nep-lab
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