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Weak Instrumental Variables Models for Longitudinal Data

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  • Zongwu Cai
  • Ying Fang
  • Henong Li

Abstract

In this paper, we study a weak instrumental variables model for longitudinal data. A two stage least-squares estimator (the instrumental variables estimator) is presented. We show that the asymp-totic property for the proposed estimator is different from that for cross-sectional data. Also, similar to Hahn and Kuersteiner (2002), we extend a local-to-zero assumption as in Staiger and Stock (1997) on the coefficients of the instruments in the first stage equation to a more general setting by allowing for different degrees of weakness. Moreover, the consistency and limiting distribution of the proposed estimators are established and the explicit expressions for the asymptotic bias are given. Further, we show that the discontinuity phenomenon observed in Hahn and Kuersteiner (2002) still exists for the longitudinal data case. Finally, we examine the finite sample properties of the proposed estimator by Monte Carlo simulations.

Suggested Citation

  • Zongwu Cai & Ying Fang & Henong Li, 2013. "Weak Instrumental Variables Models for Longitudinal Data," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:002001
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    2. 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.
    3. Badi H. Baltagi & Chihwa Kao & Long Liu, 2012. "On the Estimation and Testing of Fixed Effects Panel Data Models with Weak Instruments," Advances in Econometrics, in: 30th Anniversary Edition, pages 199-235, Emerald Group Publishing Limited.
    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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