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Spatial Panel Data Models

In: Spatial Econometrics


  • J. Paul Elhorst

    (University of Groningen)


This chapter provides a survey of the specification and estimation of spatial panel data models. Five panel data models commonly used in applied research are considered: the fixed effects model, the random effects model, the fixed coefficients model, the random coefficients model, and the multilevel model. Today a (spatial) econometric researcher has the choice of many models. First, he should ask himself whether or not, and, if so, which type of spatial interaction effects should be accounted for. Second, he should ask himself whether or not spatial-specific and/or time-specific effects should be accounted for and, if so, whether they should be treated as fixed or as random effects. A selection framework is demonstrated to determine which of the first two types of spatial panel data models considered in this chapter best describes the data. The well-known Baltagi and Li (2004) panel dataset, explaining cigarette demand for 46 US states over the period 1963 to 1992, is used to illustrate this framework in an empirical setting.

Suggested Citation

  • J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
  • Handle: RePEc:spr:sbrchp:978-3-642-40340-8_3
    DOI: 10.1007/978-3-642-40340-8_3

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    Cited by:

    1. Skevas, Ioannis & Skevas, Theodoros, 2021. "A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1131-1142.
    2. Matthew J. Higgins & Donald J. Lacombe & Briana S. Stenard & Andrew T. Young, 2021. "Evaluating the effects of Small Business Administration lending on growth," Small Business Economics, Springer, vol. 57(1), pages 23-45, June.
    3. Rao, Purnima & Goyal, Nisha & Kumar, Satish & Hassan, M. Kabir & Shahimi, Shahida, 2021. "Vulnerability of financial markets in India: The contagious effect of COVID-19," Research in International Business and Finance, Elsevier, vol. 58(C).
    4. Demidova, O. & Timofeeva, E., 2021. "Spatial aspects of wage curve estimation in Russia," Journal of the New Economic Association, New Economic Association, vol. 51(3), pages 69-101.
    5. Cristiana Fiorelli & Alfredo Cartone & Matteo Foglia, 2021. "Shadow rates and spillovers across the Eurozone: a spatial dynamic panel model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 223-245, February.
    6. Ferry Syarifuddin, 2020. "The Dynamics Of Foreign Portfolio Investment And Exchange Rate: An Interconnection Approach In Asean," Working Papers WP/08/2020, Bank Indonesia.
    7. Cheng, Muxi & McCarl, Bruce A. & Fei, Chengcheng, 2021. "Climate Change Effects on the U.S. Hog production," 2021 Annual Meeting, August 1-3, Austin, Texas 313966, Agricultural and Applied Economics Association.


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