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The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar

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  • J. Paul Elhorst

    (University of Groningen)

Abstract

The dynamic general nesting spatial econometric model for spatial panels with common factors is the most advanced model currently available. It accounts for local spatial dependence by means of an endogenous spatial lag, exogenous spatial lags, and a spatial lag in the error term. It accounts for dynamic effects by means of the dependent variable lagged in time, and the dependent variable lagged in both space and time. Finally, it accounts for global cross-sectional dependence by means of cross-sectional averages or principal components with heterogeneous coefficients, which generalizes the traditional controls for time-invariant and spatial-invariant variables by unit-specific and time-specific effects. This paper provides an overview of the main arguments in favor of each of these model components, as well as some potential pitfalls.

Suggested Citation

  • J. Paul Elhorst, 2022. "The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 249-267, December.
    • Handle: RePEc:spr:jahrfr:v:42:y:2022:i:3:d:10.1007_s10037-021-00163-w
    DOI: 10.1007/s10037-021-00163-w
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    as
    1. Parent, Olivier & LeSage, James P., 2010. "A spatial dynamic panel model with random effects applied to commuting times," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 633-645, June.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    3. Besley, Timothy & Case, Anne, 1995. "Incumbent Behavior: Vote-Seeking, Tax-Setting, and Yardstick Competition," American Economic Review, American Economic Association, vol. 85(1), pages 25-45, March.
    4. Stephen Gibbons & Henry G. Overman, 2012. "Mostly Pointless Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 172-191, May.
    5. M Ensar Yesilyurt & J Paul Elhorst, 2017. "Impacts of neighboring countries on military expenditures," Journal of Peace Research, Peace Research Institute Oslo, vol. 54(6), pages 777-790, November.
    6. J. Paul Elhorst & Marco Gross & Eugen Tereanu, 2021. "Cross‐Sectional Dependence And Spillovers In Space And Time: Where Spatial Econometrics And Global Var Models Meet," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 192-226, February.
    7. Bruce A. Blonigen & Ronald B. Davies & Glen R. Waddell & Helen T. Naughton, 2019. "FDI in Space: Spatial Autoregressive Relationships in Foreign Direct Investment," World Scientific Book Chapters, in: Foreign Direct Investment, chapter 2, pages 55-88, World Scientific Publishing Co. Pte. Ltd..
    8. 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.
    9. Kristian Behrens & Cem Ertur & Wilfried Koch, 2012. "‘Dual’ Gravity: Using Spatial Econometrics To Control For Multilateral Resistance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 773-794, August.
    10. Donald J. Lacombe & James P. LeSage, 2015. "Using Bayesian posterior model probabilities to identify omitted variables in spatial regression models," Papers in Regional Science, Wiley Blackwell, vol. 94(2), pages 365-383, June.
    11. Nicolas DEBARSY (CERPE De Namur) & Cem ERTUR & James P. LeSAGE, 2010. "Interpreting Dynamic Space-Time Panel Data Models," LEO Working Papers / DR LEO 800, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    12. Pim Heijnen & J. Paul Elhorst, 2018. "The Diffusion of Local Differentiated Waste Disposal Taxes in the Netherlands," De Economist, Springer, vol. 166(2), pages 239-258, June.
    13. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    14. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    15. Wildasin, David E., 1988. "Nash equilibria in models of fiscal competition," Journal of Public Economics, Elsevier, vol. 35(2), pages 229-240, March.
    16. Diego Firmino Costa da Silva & J. Paul Elhorst & Raul da Mota Silveira Neto, 2017. "Urban and rural population growth in a spatial panel of municipalities," Regional Studies, Taylor & Francis Journals, vol. 51(6), pages 894-908, June.
    17. Cem Ertur & Wilfried Koch, 2007. "Growth, technological interdependence and spatial externalities: theory and evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1033-1062.
    18. Giuseppe Arbia & Anil K. Bera & Osman Doğan & Süleyman Taşpınar, 2020. "Testing Impact Measures in Spatial Autoregressive Models," International Regional Science Review, , vol. 43(1-2), pages 40-75, January.
    19. Bao, Yong & Ullah, Aman, 2007. "Finite sample properties of maximum likelihood estimator in spatial models," Journal of Econometrics, Elsevier, vol. 137(2), pages 396-413, April.
    20. Maarten A. Allers & J. Paul Elhorst, 2011. "A Simultaneous Equations Model Of Fiscal Policy Interactions," Journal of Regional Science, Wiley Blackwell, vol. 51(2), pages 271-291, May.
    21. H. Hanson, Gordon, 2005. "Market potential, increasing returns and geographic concentration," Journal of International Economics, Elsevier, vol. 67(1), pages 1-24, September.
    22. Ciccarelli, Carlo & Elhorst, J.Paul, 2018. "A dynamic spatial econometric diffusion model with common factors: The rise and spread of cigarette consumption in Italy," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 131-142.
    23. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    24. Kelley Pace, R. & LeSage, James P., 2008. "A spatial Hausman test," Economics Letters, Elsevier, vol. 101(3), pages 282-284, December.
    25. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    26. Morgan Kelly, 2019. "The Standard Errors of Persistence," Working Papers 201913, School of Economics, University College Dublin.
    27. Michael Beenstock & Daniel Felsenstein, 2019. "The Econometric Analysis of Non-Stationary Spatial Panel Data," Advances in Spatial Science, Springer, number 978-3-030-03614-0, Fall.
    28. James P. Lesage, 1997. "Bayesian Estimation of Spatial Autoregressive Models," International Regional Science Review, , vol. 20(1-2), pages 113-129, April.
    29. Achim Ahrens & Arnab Bhattacharjee, 2015. "Two-Step Lasso Estimation of the Spatial Weights Matrix," Econometrics, MDPI, vol. 3(1), pages 1-28, March.
    30. LeSage, James P. & Vance, Colin & Chih, Yao-Yu, 2017. "A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel duopoly pricing," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 46-55.
    31. 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.
    32. J. Paul Elhorst, 2003. "The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 709-748, December.
    33. Alessandra Fogli & Laura Veldkamp, 2011. "Nature or Nurture? Learning and the Geography of Female Labor Force Participation," Econometrica, Econometric Society, vol. 79(4), pages 1103-1138, July.
    34. Giuseppe Arbia & Bernard Fingleton, 2008. "New spatial econometric techniques and applications in regional science," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 311-317, August.
    35. Joris Pinkse & Margaret E. Slade & Craig Brett, 2002. "Spatial Price Competition: A Semiparametric Approach," Econometrica, Econometric Society, vol. 70(3), pages 1111-1153, May.
    36. Keller, Wolfgang & Shiue, Carol H., 2007. "The origin of spatial interaction," Journal of Econometrics, Elsevier, vol. 140(1), pages 304-332, September.
    37. Solmaria Halleck Vega & J. Paul Elhorst, 2017. "Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 138-160, July.
    38. Xu, Xingbai & Lee, Lung-fei, 2019. "Theoretical foundations for spatial econometric research," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 2-12.
    39. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    40. Maria Kyriacou & Peter C. B. Phillips & Francesca Rossi, 2017. "Indirect inference in spatial autoregression," Econometrics Journal, Royal Economic Society, vol. 20(2), pages 168-189, June.
    41. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    42. Kelly, Morgan, 2019. "The Standard Errors of Persistence," CEPR Discussion Papers 13783, C.E.P.R. Discussion Papers.
    43. Glaeser, Edward L., 2008. "Cities, Agglomeration, and Spatial Equilibrium," OUP Catalogue, Oxford University Press, number 9780199290444.
    44. 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.
    45. Daniel P. McMillen, 2012. "Perspectives On Spatial Econometrics: Linear Smoothing With Structured Models," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 192-209, May.
    46. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    47. Maria Kyriacou & Peter C. B. Phillips & Francesca Rossi, 2017. "Indirect inference in spatial autoregression," Econometrics Journal, Royal Economic Society, vol. 20(2), pages 168-189, June.
    48. 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.
    49. 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.
    50. Frank Brechling, 1967. "Trends And Cycles In British Regional Unemployment," Oxford Economic Papers, Oxford University Press, vol. 19(1), pages 1-21.
    51. Mark D. Partridge & Marlon Boarnet & Steven Brakman & Gianmarco Ottaviano, 2012. "Introduction: Whither Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 167-171, May.
    52. A. P. Thirlwall, 1966. "Regional Unemployment As A Cyclical Phenomenon1," Scottish Journal of Political Economy, Scottish Economic Society, vol. 13(2), pages 205-219, June.
    53. Jan K. Brueckner, 2003. "Strategic Interaction Among Governments: An Overview of Empirical Studies," International Regional Science Review, , vol. 26(2), pages 175-188, April.
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    2. Rolf Bergs & Rüdiger Budde, 2022. "The potential of small-scale spatial data in regional science," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(2), pages 97-110, August.

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    More about this item

    Keywords

    Spatial panels; Dynamic effects; Spatial spillovers; Common factors; Estimation;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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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