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Group Interaction in Research and the Use of General Nesting Spatial Models

In: Spatial Econometrics: Qualitative and Limited Dependent Variables

Author

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  • Peter Burridge
  • J. Paul Elhorst
  • Katarina Zigova

Abstract

This paper tests the feasibility and empirical implications of a spatial econometric model with a full set of interaction effects and weight matrix defined as an equally weighted group interaction matrix applied to research productivity of individuals. We also elaborate two extensions of this model, namely with group fixed effects and with heteroskedasticity. In our setting, the model with a full set of interaction effects is overparameterised: only the SDM and SDEM specifications produce acceptable results. They imply comparable spillover effects, but by applying a Bayesian approach taken from LeSage (2014), we are able to show that the SDEM specification is more appropriate and thus that colleague interaction effects work through observed and unobserved exogenous characteristics common to researchers within a group.

Suggested Citation

  • Peter Burridge & J. Paul Elhorst & Katarina Zigova, 2016. "Group Interaction in Research and the Use of General Nesting Spatial Models," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 223-258, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320160000037016
    DOI: 10.1108/S0731-905320160000037016
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    Cited by:

    1. Yuan, Hang & Guan, Zhihua & Jiang, Changmin & Yang, Hangjun, 2023. "Peer effect in the construction of China’s high-speed rail stations: Empirical evidence from spatial econometric analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    2. Mounir Amdaoud & Nadine Levratto, 2024. "Sectoral Diversity and Local Employment Growth in France [Diversité sectorielle et croissance de l’emploi local en France]," Post-Print hal-05185983, HAL.
    3. Zhongbo Jing & J. Paul Elhorst & Jan P. A. M. Jacobs & Jakob Haan, 2018. "The propagation of financial turbulence: interdependence, spillovers, and direct and indirect effects," Empirical Economics, Springer, vol. 55(1), pages 169-192, August.
    4. Katarina Zigova, 2017. "Specifying Social Weight Matrices of Researcher Networks: The Case of Academic Economists," Working Paper Series of the Department of Economics, University of Konstanz 2017-10, Department of Economics, University of Konstanz.
    5. Thanasis Ziogas & Dimitris Ballas & Sierdjan Koster & Arjen Edzes, 2020. "How happy are my neighbours? Modelling spatial spillover effects of well-being," Papers 2007.11580, arXiv.org.
    6. Elhorst, J. Paul & Madre, Jean-Loup & Pirotte, Alain, 2020. "Car traffic, habit persistence, cross-sectional dependence, and spatial heterogeneity: New insights using French departmental data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 614-632.
    7. Wang, Jian & Wu, Qun & Yan, Siqi & Guo, Guancheng & Peng, Shangui, 2020. "China’s local governments breaking the land use planning quota: A strategic interaction perspective," Land Use Policy, Elsevier, vol. 92(C).
    8. Fernando A. López & Pedro J. Martínez-Ortiz & Juan-Gabriel Cegarra-Navarro, 2017. "Spatial spillovers in public expenditure on a municipal level in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 39-65, January.
    9. Jonathan Norris, 2017. "Family and Peer Social Identity Effects on Schooling Attitudes and Performance," UNCG Economics Working Papers 17-1, University of North Carolina at Greensboro, Department of Economics.
    10. Ferry Syarifuddin, 2020. "The Dynamics Of Foreign Portfolio Investment And Exchange Rate: An Interconnection Approach In Asean," Working Papers WP/08/2020, Bank Indonesia.
    11. Osman Doğan & Süleyman Taṣpınar & Anil K. Bera, 2018. "Simple tests for social interaction models with network structures," Spatial Economic Analysis, Taylor & Francis Journals, vol. 13(2), pages 212-246, April.

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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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