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Panel threshold spatial Durbin models with individual fixed effects

Author

Listed:
  • Wei, Lili
  • Zhang, Chunli
  • Su, Jen-Je
  • Yang, Lixiong

Abstract

This paper introduces a new panel threshold spatial Durbin (PTSD) model. A within-group spatial two-stage least squares estimator and a threshold test of the PTSD model are suggested. Simulation results show that the proposed estimator and test work well in finite samples

Suggested Citation

  • Wei, Lili & Zhang, Chunli & Su, Jen-Je & Yang, Lixiong, 2021. "Panel threshold spatial Durbin models with individual fixed effects," Economics Letters, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:ecolet:v:201:y:2021:i:c:s0165176521000550
    DOI: 10.1016/j.econlet.2021.109778
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    References listed on IDEAS

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    1. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    3. Deng, Ying, 2018. "Estimation for the spatial autoregressive threshold model," Economics Letters, Elsevier, vol. 171(C), pages 172-175.
    4. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    5. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    6. Bruce E. Hansen, 2017. "Regression Kink With an Unknown Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 228-240, April.
    7. Zhu, Yanli & Han, Xiaoyi & Chen, Ying, 2020. "Bayesian estimation and model selection of threshold spatial Durbin model," Economics Letters, Elsevier, vol. 188(C).
    8. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
    9. Guo, Juncong & Qu, Xi, 2020. "Fixed effects spatial panel data models with time-varying spatial dependence," Economics Letters, Elsevier, vol. 196(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Spatial Durbin model; Threshold model; Spatial two-stage least squares; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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