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Spatial dynamic panel data models with interactive fixed effects

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  • Shi, Wei
  • Lee, Lung-fei

Abstract

This paper studies the estimation of a dynamic spatial panel data model with interactive individual and time effects with large n and T. The model has a rich spatial structure including contemporaneous spatial interaction and spatial heterogeneity. Dynamic features include individual time lag and spatial diffusion. The interactive effects capture heterogeneous impacts of time effects on cross sectional units. The interactive effects are treated as parameters, so as to allow correlations between the interactive effects and the regressors. We consider a quasi-maximum likelihood estimation and show estimator consistency and characterize its asymptotic distribution. The Monte Carlo experiment shows that the estimator performs well and the proposed bias correction is effective. We illustrate the empirical relevance of the model by applying it to examine the effects of house price dynamics on reverse mortgage origination rates in the US.

Suggested Citation

  • Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
  • Handle: RePEc:eee:econom:v:197:y:2017:i:2:p:323-347
    DOI: 10.1016/j.jeconom.2016.12.001
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    References listed on IDEAS

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    1. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    2. Hyungsik Roger Moon & Martin Weidner, 2015. "Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects," Econometrica, Econometric Society, vol. 83(4), pages 1543-1579, July.
    3. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    4. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
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    10. Lung‐fei Lee & Jihai Yu, 2016. "Identification of Spatial Durbin Panel Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 133-162, January.
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    Cited by:

    1. repec:eee:eejocm:v:28:y:2018:i:c:p:108-123 is not listed on IDEAS
    2. repec:eee:regeco:v:72:y:2018:i:c:p:6-34 is not listed on IDEAS
    3. repec:spr:empeco:v:55:y:2018:i:1:d:10.1007_s00181-017-1415-2 is not listed on IDEAS
    4. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2019. "Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure," SERIES 03-2019, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Jun 2019.
    5. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    6. Yang, Cynthia Fan, 2017. "Common Factors and Spatial Dependence: An Application to US House Prices," MPRA Paper 89032, University Library of Munich, Germany, revised 20 Aug 2018.

    More about this item

    Keywords

    Spatial panel; Dynamics; Multiplicative individual and time effects;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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