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Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms

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  • L W Hepple

    (Department of Geography, University of Bristol, Bristol BS8 1SS)

Abstract

Bayesian theory has been seen as having considerable potential and attractiveness for model estimation and analysis in spatial and network econometrics. However, analytical and computational problems have also been seen as a great barrier. In this paper the analytical simplifications available are developed and the algorithms required are examined. The author argues that, for a broad class of models in spatial econometrics, Bayesian analysis is quite practicable and can be implemented without great cost. The spatial specifications are mapped into the various forms of Bayesian computation available and detailed examples are provided. Recent developments on the frontier of Bayesian computation have potential to expand further the practical applicability of the Bayesian approach to spatial econometrics.

Suggested Citation

  • L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms," Environment and Planning A, , vol. 27(4), pages 615-644, April.
    • Handle: RePEc:sae:envira:v:27:y:1995:i:4:p:615-644
    DOI: 10.1068/a270615
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    References listed on IDEAS

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    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Chib, B. & Osiewalski, J. & Steel, M., 1990. "Regression Models Under Competing Covariance Matrices: A Baysian Perspective," Papers 9063, Tilburg - Center for Economic Research.
    3. Osiewalski, Jacek, 1991. "A note on Bayesian inference in a regression model with elliptical errors," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 183-193.
    4. Park M. Reilly, 1976. "The Numerical Computation of Posterior Distributions in Bayesian Statistical Inference," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(3), pages 201-209, November.
    5. Bolduc, Denis & Dagenais, Marcel G. & Gaudry, Marc J. I., 1989. "Spatially autocorrelated errors in origin-destination models: A new specification applied to aggregate mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 23(5), pages 361-372, October.
    6. Naylor, J. C. & Smith, A. F. M., 1988. "Econometric illustrations of novel numerical integration strategies for Bayesian inference," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 103-125.
    7. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
    8. Osiewalski, Jacek & Steel, Mark F. J., 1992. "A Bayesian note on competing correlation structures in the dynamic linear regression model," Economics Letters, Elsevier, vol. 40(4), pages 383-388, December.
    9. Chib, Siddhartha, 1993. "Bayes regression with autoregressive errors : A Gibbs sampling approach," Journal of Econometrics, Elsevier, vol. 58(3), pages 275-294, August.
    10. A S Brandsma & R H Ketellapper, 1979. "A Biparametric Approach to Spatial Autocorrelation," Environment and Planning A, , vol. 11(1), pages 51-58, January.
    11. Zellner, Arnold & Moulton, Brent R., 1985. "Bayesian regression diagnostics with applications to international consumption and income data," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 187-211.
    12. Bolduc, Denis & Laferriere, Richard & Santarossa, Gino, 1992. "Spatial autoregressive error components in travel flow models," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 371-385, September.
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    Cited by:

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    3. LeSage, James P. & Chih, Yao-Yu & Vance, Colin, 2019. "Markov Chain Monte Carlo estimation of spatial dynamic panel models for large samples," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 107-125.
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    5. Manfred M. Fischer & James P. LeSage, 2020. "Network dependence in multi-indexed data on international trade flows," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-26, December.
    6. Doğan, Osman, 2023. "Modified harmonic mean method for spatial autoregressive models," Economics Letters, Elsevier, vol. 223(C).
    7. Dargel, Lukas, 2021. "Revisiting Estimation Methods for Spatial Econometric Interaction Models," TSE Working Papers 21-1192, Toulouse School of Economics (TSE).
    8. Elhorst, J. Paul & Lacombe, Donald J. & Piras, Gianfranco, 2012. "On model specification and parameter space definitions in higher order spatial econometric models," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 211-220.
    9. Lukas Dargel, 2021. "Revisiting estimation methods for spatial econometric interaction models," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-41, December.
    10. Doğan, Osman & Taşpınar, Süleyman, 2014. "Spatial autoregressive models with unknown heteroskedasticity: A comparison of Bayesian and robust GMM approach," Regional Science and Urban Economics, Elsevier, vol. 45(C), pages 1-21.
    11. López-Hernández, Fernando A., 2013. "Second-order polynomial spatial error model. Global and local spatial dependence in unemployment in Andalusia," Economic Modelling, Elsevier, vol. 33(C), pages 270-279.
    12. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    13. M Tiefelsdorf & D A Griffith & B Boots, 1999. "A Variance-Stabilizing Coding Scheme for Spatial Link Matrices," Environment and Planning A, , vol. 31(1), pages 165-180, January.
    14. Han, Xiaoyi & Lee, Lung-fei, 2013. "Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 250-271.
    15. 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.
    16. Osman Doğan, 2015. "Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with a Moving Average Disturbance Term," Econometrics, MDPI, vol. 3(1), pages 1-27, February.
    17. Virgilio Gómez-Rubio & Roger S. Bivand & Håvard Rue, 2021. "Estimating Spatial Econometrics Models with Integrated Nested Laplace Approximation," Mathematics, MDPI, vol. 9(17), pages 1-23, August.
    18. Manfred M. Fischer & Daniel A. Griffith, 2008. "Modeling Spatial Autocorrelation In Spatial Interaction Data: An Application To Patent Citation Data In The European Union," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 969-989, December.

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