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Spatial differencing for sample selection models with ‘site-specific’ unobserved local effects

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  • Alexander Klein
  • Guy Tchuente

Abstract

SummaryThis paper proposes an estimator which combines spatial differencing with a two-step sample selection estimator. We derive identification, estimation, and inference results from ‘site-specific’ unobserved effects. These effects operate at a spatial scale that cannot be captured by administrative borders. Therefore, we use spatial differencing. We show that under justifiable assumptions, the estimator is consistent and asymptotically normal. A Monte Carlo experiment illustrates the small sample properties of our estimator. We apply our procedure to the estimation of a female wage offer equation in the United States and the results show the relevance of spatial differencing to account for ‘site-specific’ unobserved effects.

Suggested Citation

  • Alexander Klein & Guy Tchuente, 2024. "Spatial differencing for sample selection models with ‘site-specific’ unobserved local effects," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages 235-257.
  • Handle: RePEc:oup:emjrnl:v:27:y:2024:i:2:p:235-257.
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    1. Sandra E. Black, 1999. "Do Better Schools Matter? Parental Valuation of Elementary Education," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 577-599.
    2. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    3. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Wild Bootstrap and Asymptotic Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 505-519, March.
    4. Hannah Druckenmiller & Solomon Hsiang, 2018. "Accounting for Unobservable Heterogeneity in Cross Section Using Spatial First Differences," NBER Working Papers 25177, National Bureau of Economic Research, Inc.
    5. Lee, Myoung-jae, 2001. "First-difference estimator for panel censored-selection models," Economics Letters, Elsevier, vol. 70(1), pages 43-49, January.
    6. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    7. Djogbenou, Antoine A. & MacKinnon, James G. & Nielsen, Morten Ørregaard, 2019. "Asymptotic theory and wild bootstrap inference with clustered errors," Journal of Econometrics, Elsevier, vol. 212(2), pages 393-412.
    8. Gilles Duranton & Laurent Gobillon & Henry G. Overman, 2011. "Assessing the Effects of Local Taxation using Microgeographic Data," Economic Journal, Royal Economic Society, vol. 121(555), pages 1017-1046, September.
    9. Emily Oster, 2019. "Unobservable Selection and Coefficient Stability: Theory and Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 187-204, April.
    10. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    11. Ekaterini Kyriazidou, 1997. "Estimation of a Panel Data Sample Selection Model," Econometrica, Econometric Society, vol. 65(6), pages 1335-1364, November.
    12. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    13. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    14. Whitney K. Newey, 2009. "Two-step series estimation of sample selection models," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 217-229, January.
    15. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
    16. Thomas J. Holmes, 1998. "The Effect of State Policies on the Location of Manufacturing: Evidence from State Borders," Journal of Political Economy, University of Chicago Press, vol. 106(4), pages 667-705, August.
    17. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 33-58.
    18. Gibbons, Steve & Machin, Stephen, 2003. "Valuing English primary schools," Journal of Urban Economics, Elsevier, vol. 53(2), pages 197-219, March.
    19. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    20. Stéphane Bonhomme, 2012. "Functional Differencing," Econometrica, Econometric Society, vol. 80(4), pages 1337-1385, July.
    21. Gary Chamberlain, 2010. "Binary Response Models for Panel Data: Identification and Information," Econometrica, Econometric Society, vol. 78(1), pages 159-168, January.
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