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2SLS and IV Estimation of Dynamic Panel Models with Heterogeneous Trend

Cao, Shiyun ; Zhang, Yonghui ; Zhou, Qiankun

Oxford bulletin of economics and statistics, 2021-12, Vol.83 (6), p.1408-1431 [Periódico revisado por pares]

Oxford: Blackwell Publishing Ltd

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  • Título:
    2SLS and IV Estimation of Dynamic Panel Models with Heterogeneous Trend
  • Autor: Cao, Shiyun ; Zhang, Yonghui ; Zhou, Qiankun
  • Assuntos: Bias ; Panel data ; Weighting
  • É parte de: Oxford bulletin of economics and statistics, 2021-12, Vol.83 (6), p.1408-1431
  • Notas: We thank the editor and two anonymous referees for helpful comments. Cao acknowledges the financial support from the National Natural Science Foundation of China (Project No. 11861014). Zhang gratefully acknowledges the financial support from the National Natural Science Foundation of China (No. 71973141 and No. 71873033). All errors are the authors’ sole responsibilities.
  • Descrição: In this paper, we consider two‐stage least squares (2SLS) and simple instrumental variable (IV) type estimation of dynamic panel data models with both individual‐specific effects and heterogeneous time trend when both N and T tend to infinity. We consider the forward orthogonal deviations (FOD) proposed by (Hayakawa, et al. Econometric Reviews, 2019. Vol. 38, pp. 1055–1088) and the double first difference (2FD) to remove both the individual‐specific effects and heterogeneous trend. As the main theoretical contribution, we establish the asymptotic properties of the 2SLS estimation of the lag coefficient and find that the 2SLS estimation using FOD and optimal 2SLS estimation using 2FD are asymptotically biased of order TN, while the 2SLS based on 2FD using non‐optimal weighting matrix is asymptotically biased of order T3N. We also establish the asymptotic unbiasedness of the simple IV estimation using first differenced lagged dependent variable as instrument, and establish the invalidity of using level lagged dependent variable as instrument for the simple IV estimation. Monte Carlo simulations confirm our findings in this paper.
  • Editor: Oxford: Blackwell Publishing Ltd
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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