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QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices

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  • Qu, Xi
  • Lee, Lung-fei
  • Yu, Jihai

Abstract

In spatial panel data models, when a spatial weights matrix is constructed from economic or social distance, spatial weights could be endogenous and also time varying. This paper presents model specification and proposes QMLE estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices. Asymptotic properties of the proposed QMLE are rigorously established. We extend the notion of spatial near-epoch dependence to allow time dependence. By using spatial-time LLN for near-epoch dependence process and CLT for martingale difference sequence, we establish the consistency and asymptotic normality of QMLE. Monte Carlo experiments show that the proposed estimators have satisfactory finite sample performance.

Suggested Citation

  • Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
  • Handle: RePEc:eee:econom:v:197:y:2017:i:2:p:173-201
    DOI: 10.1016/j.jeconom.2016.11.004
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    1. Baltagi, Badi H & Levin, Dan, 1986. "Estimating Dynamic Demand for Cigarettes Using Panel Data: The Effects of Bootlegging, Taxation and Advertising Reconsidered," The Review of Economics and Statistics, MIT Press, vol. 68(1), pages 148-155, February.
    2. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2013. "A Generalized Spatial Panel Data Model with Random Effects," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 650-685, August.
    3. Brueckner, Jan K. & Saavedra, Luz A., 2001. "Do Local Governments Engage in Strategic Property-Tax Competition?," National Tax Journal, National Tax Association;National Tax Journal, vol. 54(2), pages 203-230, June.
    4. 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.
    5. 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.
    6. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    7. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    8. Yu, Jihai & Lee, Lung-fei, 2010. "Estimation Of Unit Root Spatial Dynamic Panel Data Models," Econometric Theory, Cambridge University Press, vol. 26(05), pages 1332-1362, October.
    9. Kelejian, Harry H. & Piras, Gianfranco, 2014. "Estimation of spatial models with endogenous weighting matrices, and an application to a demand model for cigarettes," Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 140-149.
    10. Zhenlin Yang & Jihai Yu & Shew Fan Liu, 2015. "Bias correction for fixed effects spatial panel data models," Working Papers 04-2015, Singapore Management University, School of Economics.
    11. Bernard Fingleton, 2008. "A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 27-44.
    12. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    13. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(2), pages 167-196.
    14. Qu, Xi & Lee, Lung-fei, 2015. "Estimating a spatial autoregressive model with an endogenous spatial weight matrix," Journal of Econometrics, Elsevier, vol. 184(2), pages 209-232.
    15. Baltagi, Badi H. & Levin, Dan, 1992. "Cigarette taxation: Raising revenues and reducing consumption," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 321-335, December.
    16. Brueckner, Jan K., 1998. "Testing for Strategic Interaction Among Local Governments: The Case of Growth Controls," Journal of Urban Economics, Elsevier, vol. 44(3), pages 438-467, November.
    17. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    18. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    19. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    20. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    21. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    22. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
    23. Rincke, Johannes, 2010. "A commuting-based refinement of the contiguity matrix for spatial models, and an application to local police expenditures," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 324-330, September.
    24. Korniotis, George M., 2010. "Estimating Panel Models With Internal and External Habit Formation," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 145-158.
    25. Jenish, Nazgul & Prucha, Ingmar R., 2012. "On spatial processes and asymptotic inference under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 170(1), pages 178-190.
    26. Baicker, Katherine, 2005. "The spillover effects of state spending," Journal of Public Economics, Elsevier, vol. 89(2-3), pages 529-544, February.
    27. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
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    Citations

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    as


    Cited by:

    1. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada
      [Fundamentals of Applied Spatial Econometrics]
      ," MPRA Paper 80871, University Library of Munich, Germany.
    2. repec:eee:regeco:v:69:y:2018:i:c:p:130-142 is not listed on IDEAS
    3. repec:bpj:jecome:v:8:y:2019:i:1:p:33:n:7 is not listed on IDEAS
    4. repec:eee:ecolet:v:162:y:2018:i:c:p:62-68 is not listed on IDEAS
    5. Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Networks in risk spillovers: a multivariate GARCH perspective," Working Papers 2016:03, Department of Economics, University of Venice "Ca' Foscari".

    More about this item

    Keywords

    Spatial autoregression; Dynamic panels; Fixed effects; Endogenous spatial weights matrix; QMLE;

    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
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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