Nonlinear Correlated Random Effects Models with Endogeneity and Unbalanced Panels

Michael Bates, Jeffrey Wooldridge () and Lelsie Papke ()

No 202214, 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 unobervables. 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 estimating 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.

Pages: 31 Pages
Date: 2022-09
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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https://economics.ucr.edu/repec/ucr/wpaper/202214.pdf First version, 2022 (application/pdf)

Related works:
Journal Article: Non linear correlated random effects models with endogeneity and unbalanced panels (2024)
Working Paper: Nonlinear Correlated Random Effects Models with Endogeneity and Unbalanced Panels (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:ucr:wpaper:202214

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