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Nonlinear Correlated Random Effects Models with Endogeneity and Unbalanced Panels

Michael Bates (), Leslie Papke () and Jeffrey Wooldridge ()
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Michael Bates: Department of Economics, University of California Riverside
Leslie Papke: Michigan State University
Jeffrey Wooldridge: Michigan State University

No 202305, Working Papers from University of California at Riverside, Department of Economics

Abstract: We present simple procedures for estimating nonlinear panel data models in the presence of unobserved heterogeneity and possible endogeneity with respect to time-varying unobservables. We combine a correlated random effects approach with a control function approach while accounting for missing time periods for some units. We examine the performance of the approach in comparisons with standard estimators using Monte Carlo simulation. We apply the methods to estimate the effects of school spending on student pass rates on a standardized math exam. We find that a 10 percent increase in spending leads to an approximately two percentage point increase in math pass rates.

Keywords: Control function; instrumental variables; education finance (search for similar items in EconPapers)
JEL-codes: C33 C36 I22 I26 (search for similar items in EconPapers)
Pages: 36 Pages
Date: 2022-09, Revised 2023-08
New Economics Papers: this item is included in nep-dcm
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Downloads: (external link) First version, 2022 (application/pdf) Revised version, 2023 (application/pdf)

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