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Interpreting heterogeneous coefficient spatial autoregressive panel models

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  • LeSage, James P.
  • Chih, Yao-Yu

Abstract

We consider interpretation of estimates from the heterogeneous coefficient spatial autoregressive panel model of Aquaro et al. (2015) and derive partial derivatives (marginal effects) for this model, an issue not discussed in Aquaro et al. (2015). We show how these differ from a conventional spatial autoregressive panel model.

Suggested Citation

  • LeSage, James P. & Chih, Yao-Yu, 2016. "Interpreting heterogeneous coefficient spatial autoregressive panel models," Economics Letters, Elsevier, vol. 142(C), pages 1-5.
    • Handle: RePEc:eee:ecolet:v:142:y:2016:i:c:p:1-5
    DOI: 10.1016/j.econlet.2016.02.033
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    References listed on IDEAS

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    1. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2015. "Quasi Maximum Likelihood Estimation of Spatial Models with Heterogeneous Coefficients," Working Papers 749, Queen Mary University of London, School of Economics and Finance.
    2. Giuseppe Arbia & Badi H. Baltagi (ed.), 2009. "Spatial Econometrics," Studies in Empirical Economics, Springer, number 978-3-7908-2070-6, March.
    3. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
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    Cited by:

    1. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2016. "Estimating individual effects and their spatial spillovers in linear panel data models: Public capital spillovers after all?," Working Papers 2072/321479, Universitat Rovira i Virgili, Department of Economics.
    2. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2021. "Estimation and inference for spatial models with heterogeneous coefficients: An application to US house prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 18-44, January.
    3. Ge, S., 2020. "Text-Based Linkages and Local Risk Spillovers in the Equity Market," Cambridge Working Papers in Economics 20115, Faculty of Economics, University of Cambridge.
    4. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    5. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    6. Corinne Autant-Bernard & James P. LeSage, 2019. "A heterogeneous coefficient approach to the knowledge production function," Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(2), pages 196-218, April.
    7. Michael Alexeev & Yao-Yu Chih, 2017. "Oil Price Shocks and Economic Growth in the Us," CAEPR Working Papers 2017-011, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    8. 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.
    9. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    10. Thibault Laurent & Christine Thomas-Agnan & Anne Ruiz-Gazen, 2023. "Covariates impacts in spatial autoregressive models for compositional data," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-23, December.
    11. Isabel Proença & Ludgero Glórias, 2021. "Revisiting the Spatial Autoregressive Exponential Model for Counts and Other Nonnegative Variables, with Application to the Knowledge Production Function," Sustainability, MDPI, vol. 13(5), pages 1-22, March.
    12. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    13. LeSage, James P. & Chih, Yao-Yu, 2018. "A Bayesian spatial panel model with heterogeneous coefficients," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 58-73.
    14. Elhorst, J. Paul & Emili, Silvia, 2022. "A spatial econometric multivariate model of Okun's law," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    15. Edoardo Otranto & Massimo Mucciardi, 2019. "Clustering space-time series: FSTAR as a flexible STAR approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 175-199, March.
    16. Yuxue Sheng & James Paul LeSage, 2021. "Interpreting spatial regression models with multiplicative interaction explanatory variables," Journal of Geographical Systems, Springer, vol. 23(3), pages 333-360, July.
    17. Debarsy, Nicolas & Yang, Zhenlin, 2018. "Editorial for the special issue entitled: New advances in spatial econometrics: Interactions matter," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 1-5.
    18. Miranda, Karen & Martínez Ibáñez, Oscar & Manjón Antolín, Miguel C., 2018. "A correlated random effects spatial Durbin model," Working Papers 2072/313840, Universitat Rovira i Virgili, Department of Economics.
    19. 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.
    20. Yao‐Yu Chih & Ruby P. Kishan & Andrew Ojede, 2022. "Be good to thy neighbours: A spatial analysis of foreign direct investment and economic growth in sub‐Saharan Africa," The World Economy, Wiley Blackwell, vol. 45(3), pages 657-701, March.
    21. Zeno Adams & Kristian Blickle, 2018. "Immigration And The Displacement of Incumbent Households," Working Papers on Finance 1809, University of St. Gallen, School of Finance.
    22. Cornwall, Gary J. & Parent, Olivier, 2017. "Embracing heterogeneity: the spatial autoregressive mixture model," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 148-161.
    23. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.
    24. E. Otranto & M. Mucciardi, 2017. "Clustering Space-Time Series: A Flexible STAR Approach," Working Paper CRENoS 201707, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    25. Adolfo Maza & Paula Gutiérrez‐Portilla & José Villaverde, 2020. "On the drivers of UK direct investment in the Spanish regions: A spatial Durbin approach," Growth and Change, Wiley Blackwell, vol. 51(2), pages 646-675, June.

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    More about this item

    Keywords

    Static space–time panel data models; Marginal effects estimates; Spatial dependence;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe

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