IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v17y2015i4p297-310.html
   My bibliography  Save this article

Software for Bayesian cross section and panel spatial model comparison

Author

Listed:
  • James LeSage

Abstract

A wide variety of spatial regression specifications that include alternative types of spatial dependence (e.g., lagged values of the dependent variable, spatial lags of explanatory variables, dependence in the model disturbances) have been the focus of a literature on statistical tests for distinguishing between alternative specifications. LeSage (Spat Stat 9:122–145, 2014 ) argues that a Bayesian approach to model comparison for cross-sectional and static panel models considerably simplifies the task of selecting an appropriate model. MATLAB software functions for carrying out Bayesian cross-sectional and static spatial panel model comparisons described in LeSage ( 2014 ) are described here along with a number of illustrative applications. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • James LeSage, 2015. "Software for Bayesian cross section and panel spatial model comparison," Journal of Geographical Systems, Springer, vol. 17(4), pages 297-310, October.
    • Handle: RePEc:kap:jgeosy:v:17:y:2015:i:4:p:297-310
    DOI: 10.1007/s10109-015-0217-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10109-015-0217-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10109-015-0217-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Han, Xiaoyi & Lee, Lung-fei, 2013. "Bayesian estimation and model selection for spatial Durbin error model with finite distributed lags," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 816-837.
    2. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
    3. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, March.
    4. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    5. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    6. J Mur, 1999. "Testing for Spatial Autocorrelation: Moving Average versus Autoregressive Processes," Environment and Planning A, , vol. 31(8), pages 1371-1382, August.
    7. Giuseppe Arbia & Badi H. Baltagi (ed.), 2009. "Spatial Econometrics," Studies in Empirical Economics, Springer, number 978-3-7908-2070-6, December.
    8. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    9. Manfred M. Fischer & Peter Nijkamp (ed.), 2014. "Handbook of Regional Science," Springer Books, Springer, edition 127, number 978-3-642-23430-9, March.
    10. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Craig Wesley Carpenter & Scott Loveridge, 2019. "A spatial model of growth relationships and Latino-owned business," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 63(3), pages 541-557, December.
    2. Raffaella Santolini, 2020. "Spatial effects on local government efficiency," Papers in Regional Science, Wiley Blackwell, vol. 99(1), pages 183-200, February.
    3. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    4. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    5. Jae Hong Kim & Kevin Kane & Young-An Kim & John R. Hipp, 2024. "Business Churning and Neighborhood Instability: Is There a Link?," International Regional Science Review, , vol. 47(1), pages 45-66, January.
    6. Laura Frassine & Nicola Pontarollo & Carolina Serpieri, 2024. "Strengths and weaknesses of EU regional reactivity to shocks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(4), pages 1593-1624, December.
    7. Elias Giannakis & Theofanis P. Mamuneas, 2022. "Labour productivity and regional labour markets resilience in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 691-712, June.
    8. Xiaojing Li & Jing Chen, 2023. "Global or Local Spatial Spillovers? Industrial Diversity and Economic Resilience in the Middle Reaches of the Yangtze River Urban Agglomeration, China," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    9. 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.
    10. Giulio Cainelli & Roberto Ganau & Marco Modica, 2019. "Does related variety affect regional resilience? New evidence from Italy," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 657-680, June.
    11. Zizi Goschin & Mihai Antonia & Horia Tigau, 2021. "Entrepreneurship Recovery in Romania after the Great Recession. A Dynamic Spatial Panel Approach," Sustainability, MDPI, vol. 13(19), pages 1-12, September.
    12. Andrés Vallone & Coro Chasco & Beatriz Sánchez, 2020. "Strategies to access web-enabled urban spatial data for socioeconomic research using R functions," Journal of Geographical Systems, Springer, vol. 22(2), pages 217-239, April.
    13. Jin Guo & Yingzhi Xu & Zhengning Pu, 2016. "Urbanization and Its Effects on Industrial Pollutant Emissions: An Empirical Study of a Chinese Case with the Spatial Panel Model," Sustainability, MDPI, vol. 8(8), pages 1-15, August.
    14. Elías Melchor-Ferrer, 2020. "Determinants of labour productivity growth in Spanish and Portuguese regions: a spatial shift-share approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(1), pages 45-65, August.
    15. , Aisdl, 2021. "Factors Determining the Development of Minimum Comparable Areas and Spatial Interaction," OSF Preprints 9e7xz, Center for Open Science.
    16. Marcos Álvarez‐Díaz & Béatrice D’Hombres & Lewis Dijkstra & Claudia Ghisetti & Nicola Pontarollo, 2021. "Unveiling the local determinants of population growth in the European Union," Growth and Change, Wiley Blackwell, vol. 52(1), pages 150-166, March.
    17. Sijin Chen, & Ning Li,, 2024. "From carbon-intensive to mineral resources: Barriers and motivators for embracing natural resource in the transition process," Resources Policy, Elsevier, vol. 91(C).
    18. Shishir Shakya & Alicia Plemmons & Juan Tomas Sayago-Gomez, 2022. "Spatial spillovers and the productivity-compensation gap in the United States," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 669-689, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James P. LESAGE, 2014. "Software For Bayesian Spatial Model Comparison," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 40, pages 11-24.
    2. Philipp Piribauer & Jesús Crespo Cuaresma, 2016. "Bayesian Variable Selection in Spatial Autoregressive Models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(4), pages 457-479, October.
    3. Fischer, Manfred M. & Piribauer, Philipp, 2013. "Model uncertainty in matrix exponential spatial growth regression models," Department of Economics Working Paper Series 158, WU Vienna University of Economics and Business.
    4. Taşpınar, Süleyman & Doğan, Osman & Bera, Anil K., 2017. "GMM gradient tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 65-88.
    5. Andrew Ojede & Bebonchu Atems & Steven Yamarik, 2018. "The Direct and Indirect (Spillover) Effects of Productive Government Spending on State Economic Growth," Growth and Change, Wiley Blackwell, vol. 49(1), pages 122-141, March.
    6. Manfred M. Fischer & James P. LeSage, 2015. "A Bayesian space-time approach to identifying and interpreting regional convergence clubs in Europe," Papers in Regional Science, Wiley Blackwell, vol. 94(4), pages 677-702, November.
    7. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    8. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    9. Ji Uk Kim, 2020. "Technology diffusion, absorptive capacity, and income convergence for Asian developing countries: a dynamic spatial panel approach," Empirical Economics, Springer, vol. 59(2), pages 569-598, August.
    10. Chagas, André L.S. & Azzoni, Carlos R. & Almeida, Alexandre N., 2016. "A spatial difference-in-differences analysis of the impact of sugarcane production on respiratory diseases," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 24-36.
    11. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    12. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    13. Deeken, Tim, 2015. "Schumpeterian growth with technological interdependence: An application to US states," Working Paper Series in Economics 75, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    14. Rey, Sergio, 2015. "Bells in Space: The Spatial Dynamics of US Interpersonal and Interregional Income Inequality," MPRA Paper 69482, University Library of Munich, Germany.
    15. Atems, Bebonchu, 2013. "The spatial dynamics of growth and inequality: Evidence using U.S. county-level data," Economics Letters, Elsevier, vol. 118(1), pages 19-22.
    16. Geerte Cotteleer & Tracy Stobbe & G. Cornelis van Kooten, 2011. "Bayesian Model Averaging In The Context Of Spatial Hedonic Pricing: An Application To Farmland Values," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 540-557, August.
    17. Manfred M. Fischer & Nico Pintar & Benedikt Sargant, 2016. "Austrian Outbound Foreign Direct Investment in Europe:A spatial econometric study," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 10(1), pages 1-22, JUNE.
    18. Samantha Leorato & Maura Mezzetti, 2015. "Spatial Panel Data Model with error dependence: a Bayesian Separable Covariance Approach," CEIS Research Paper 338, Tor Vergata University, CEIS, revised 09 Apr 2015.
    19. Sergio J. Rey, 2018. "Bells in Space," International Regional Science Review, , vol. 41(2), pages 152-182, March.
    20. Giulio Cainelli & Roberto Ganau & Marco Modica, 2019. "Does related variety affect regional resilience? New evidence from Italy," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 657-680, June.

    More about this item

    Keywords

    Static space–time panel data models; Bayes factors ; Local versus global spatial spillovers; C11; C23; O47; O52;
    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:jgeosy:v:17:y:2015:i:4:p:297-310. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.