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Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients

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  • Dou, Baojun
  • Parrella, Maria Lucia
  • Yao, Qiwei

Abstract

We consider a class of spatio-temporal models which extend popular econometric spatial autoregressive panel data models by allowing the scalar coefficients for each location (or panel) different from each other. To overcome the innate endogeneity, we propose a generalized Yule–Walker estimation method which applies the least squares estimation to a Yule–Walker equation. The asymptotic theory is developed under the setting that both the sample size and the number of locations (or panels) tend to infinity under a general setting for stationary and α-mixing processes, which includes spatial autoregressive panel data models driven by i.i.d. innovations as special cases. The proposed methods are illustrated using both simulated and real data.

Suggested Citation

  • Dou, Baojun & Parrella, Maria Lucia & Yao, Qiwei, 2016. "Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients," Journal of Econometrics, Elsevier, vol. 194(2), pages 369-382.
  • Handle: RePEc:eee:econom:v:194:y:2016:i:2:p:369-382
    DOI: 10.1016/j.jeconom.2016.05.014
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    References listed on IDEAS

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    1. 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.
    2. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2012. "Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration," Journal of Econometrics, Elsevier, vol. 167(1), pages 16-37.
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    1. repec:eee:econom:v:208:y:2019:i:1:p:211-230 is not listed on IDEAS

    More about this item

    Keywords

    α-mixing; Dynamic panels; High dimensionality; Least squares estimation; Spatial autoregression; Stationarity;

    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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