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Weak Instrumental Variables Models for Longitudinal Data

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  • Zongwu Cai
  • Ying Fang
  • Henong Li

Abstract

This article considers the estimation and testing of a within-group two-stage least squares (TSLS) estimator for instruments with varying degrees of weakness in a longitudinal (panel) data model. We show that adding the repeated cross-sectional information into a regression model can improve the estimation in weak instruments. Moreover, the consistency and limiting distribution of the TSLS estimator are established when both N and T tend to infinity. Some asymptotically pivotal tests are extended to a longitudinal data model and their asymptotic properties are examined. A Monte Carlo experiment is conducted to evaluate the finite sample performance of the proposed estimators.

Suggested Citation

  • Zongwu Cai & Ying Fang & Henong Li, 2012. "Weak Instrumental Variables Models for Longitudinal Data," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 361-389.
  • Handle: RePEc:taf:emetrv:v:31:y:2012:i:4:p:361-389
    DOI: 10.1080/07474938.2011.607356
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    2. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2023. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," Econometrica, Econometric Society, vol. 91(1), pages 107-146, January.
    3. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2021. "Heterogeneous Choice Sets and Preferences," Econometrica, Econometric Society, vol. 89(5), pages 2015-2048, September.
    4. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.

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