References

[Ans96]

L Anselin. The \Moran\ scatterplot as an \ESDA\ tool to assess local instability in spatial association. In M Fischer, H J Scholten, and D Unwin, editors, Spatial \Analytical\ \Perspectives\ on \GIS\. Taylor and Francis, 1996.

[Ans88]

Luc Anselin. Spatial Econometrics: Methods and Models. Volume 4. Springer Netherlands, 1988. ISBN 978-90-481-8311-1. URL: http://www.amazon.com/Spatial-Econometrics-Methods-Operational-Regional/dp/9024737354, arXiv:1011.1669v3, doi:10.1007/978-94-015-7799-1.

[ABFY96]

Luc Anselin, Anil Bera, Raymond J G M Florax, and M Yoon. Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26:77–104, 1996. doi:10.1016/0166-0462(95)02111-6.

[ALGJ08]

Luc Anselin, Julie Le Gallo, and Hubert Jayet. Spatial panel econometrics. In László Mátyás and Patrick Sevestre, editors, The Econometrics of Panel Data, pages 625–660. Springer, 2008. doi:10.1007/978-3-540-75892-1_19.

[ABDouganTacspinar20]

Giuseppe Arbia, Anil K. Bera, Osman Doğan, and Süleyman Taş pınar. Testing Impact Measures in Spatial Autoregressive Models. International Regional Science Review, 43(1-2):40–75, January 2020. URL: https://doi.org/10.1177/0160017619826264 (visited on 2023-11-18), doi:10.1177/0160017619826264.

[BKP99]

Ronald Paul Barry and R. Kelley Pace. Monte Carlo estimates of the log determinant of large sparse matrices. Linear Algebra and its Applications, 289(1):41–54, 1999. URL: https://www.sciencedirect.com/science/article/pii/S002437959710009X (visited on 2026-04-20), doi:10.1016/S0024-3795(97)10009-X.

[BDTL19]

Anil K. Bera, Osman Doğan, Süleyman Taşpınar, and Yufan Leiluo. Robust LM tests for spatial dynamic panel data models. Regional Science and Urban Economics, 76:47–66, 2019. URL: https://www.sciencedirect.com/science/article/pii/S0166046217303940 (visited on 2026-04-25), doi:10.1016/j.regsciurbeco.2018.08.001.

[BY93]

Anil K. Bera and Mann J. Yoon. Specification testing with locally misspecified alternatives. Econometric Theory, 9(4):649–658, 1993. doi:10.1017/S0266466600008111.

[DEL12]

Nicolas Debarsy, Cem Ertur, and James P. LeSage. Interpreting dynamic space–time panel data models. Statistical Methodology, 9(1–2):158–171, 2012. URL: https://linkinghub.elsevier.com/retrieve/pii/S1572312711000165 (visited on 2023-10-25), doi:10.1016/j.stamet.2011.02.002.

[DTB21]

Osman Doğan, Süleyman Taşpınar, and Anil K. Bera. A Bayesian robust chi-squared test for testing simple hypotheses. Journal of Econometrics, 222(2):933–958, 2021. URL: https://www.sciencedirect.com/science/article/pii/S0304407620303018 (visited on 2026-04-21), doi:10.1016/j.jeconom.2020.07.046.

[Elh14a]

J. Paul Elhorst. Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. SpringerBriefs in Regional Science. Springer Berlin Heidelberg, 2014. ISBN 978-3-642-40339-2 978-3-642-40340-8. URL: https://link.springer.com/10.1007/978-3-642-40340-8 (visited on 2023-04-30), doi:10.1007/978-3-642-40340-8.

[Elh14b]

J. Paul Elhorst. Spatial Panel Models. In Handbook of Regional Science, pages 1637–1652. Springer Berlin Heidelberg, 2014. URL: http://link.springer.com/10.1007/978-3-642-23430-9_86, doi:10.1007/978-3-642-23430-9_86.

[ETTM24]

J. Paul Elhorst, Ioannis Tziolas, Chen Tan, and Petros Milionis. The distance decay effect and spatial reach of spillovers. Journal of Geographical Systems, 26:381–407, 2024. URL: https://doi.org/10.1007/s10109-024-00440-5, doi:10.1007/s10109-024-00440-5.

[GCS+14]

Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. Bayesian Data Analysis. Chapman and Hall/CRC, Boca Raton, FL, 3rd edition, 2014. ISBN 978-1-4398-4095-5.

[GSW20]

Quentin F. Gronau, Henrik Singmann, and Eric-Jan Wagenmakers. Bridgesampling: an r package for estimating normalizing constants. Journal of Statistical Software, 92(10):1–29, 2020. doi:10.18637/jss.v092.i10.

[KR95]

Robert E. Kass and Adrian E. Raftery. Bayes factors. Journal of the American Statistical Association, 90(430):773–795, 1995. doi:10.1080/01621459.1995.10476572.

[KB24]

Malabika Koley and Anil K. Bera. To use, or not to use the spatial Durbin model? – that is the question. Spatial Economic Analysis, 19(1):30–56, 2024. URL: https://doi.org/10.1080/17421772.2023.2256810 (visited on 2025-05-21), doi:10.1080/17421772.2023.2256810.

[LP09]

J LeSage and R K Pace. Introduction to Spatial Econometrics. CRC Press, 2009.

[LeS14]

James P. LeSage. Spatial econometric panel data model specification: A Bayesian approach. Spatial Statistics, 9:122–145, 2014. URL: https://linkinghub.elsevier.com/retrieve/pii/S2211675314000128 (visited on 2023-07-25), doi:10.1016/j.spasta.2014.02.002.

[LF10]

James P. LeSage and Manfred M. Fischer. Spatial Econometric Methods for Modeling Origin-Destination Flows. In Manfred M. Fischer and Arthur Getis, editors, Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, pages 409–433. Springer, Berlin, Heidelberg, 2010. URL: https://doi.org/10.1007/978-3-642-03647-7_20 (visited on 2025-07-21), doi:10.1007/978-3-642-03647-7_20.

[LP08]

James P. LeSage and R Kelley Pace. Spatial Econometric Modeling Of Origin-Destination Flows. Journal of Regional Science, 48(5):941–967, 2008. doi:10.1111/j.1467-9787.2008.00573.x.

[LP14]

James P. LeSage and R. Kelley Pace. Interpreting Spatial Econometric Models. In Handbook of Regional Science, pages 1535–1552. Springer Berlin Heidelberg, 2014. URL: http://link.springer.com/10.1007/978-3-642-23430-9_91, doi:10.1007/978-3-642-23430-9_91.

[MBSL19]

Dominique Makowski, Mattan S. Ben-Shachar, and Daniel Lüdecke. Bayestestr: describing effects and their uncertainty, existence and significance within the Bayesian framework. Journal of Open Source Software, 4(40):1541, 2019. doi:10.21105/joss.01541.

[MW96]

Xiao-Li Meng and Wing Hung Wong. Simulating Ratios of Normalizing Constants Via a Simple Identity: A Theoretical Exploration. Statistica Sinica, 6(4):831–860, 1996. URL: https://www.jstor.org/stable/24306045 (visited on 2026-04-25), arXiv:24306045.

[MV25]

Giacomo Micaletto and Aki Vehtari. Monte carlo standard errors for bridge sampling marginal likelihood estimation. arXiv preprint, 2025. arXiv:2508.14487.

[MV26]

Giorgio Micaletto and Aki Vehtari. Bridge Sampling Diagnostics. February 2026. URL: http://arxiv.org/abs/2508.14487 (visited on 2026-04-25), arXiv:2508.14487, doi:10.48550/arXiv.2508.14487.

[PL04]

R. Kelley Pace and James P. LeSage. Chebyshev approximation of log-determinants of spatial weight matrices. Computational Statistics & Data Analysis, 45(2):179–196, 2004. URL: https://www.sciencedirect.com/science/article/pii/S0167947302003213 (visited on 2026-04-20), doi:10.1016/S0167-9473(02)00321-3.

[PL16]

R. Kelley Pace and James P. LeSage. Fast Simulated Maximum Likelihood Estimation of the Spatial Probit Model Capable of Handling Large Samples. In Advances in Econometrics, volume 37, pages 3–34. 2016. URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-905320160000037008/full/html, doi:10.1108/S0731-905320160000037008.

[SL04]

Tony E. Smith and James P. LeSage. A Bayesian Probit Model with Spatial Dependencies. In Advances in Econometrics, volume 18, pages 127–160. 2004. URL: https://www.emerald.com/insight/content/doi/10.1016/S0731-9053(04)18004-3/full/html, doi:10.1016/S0731-9053(04)18004-3.

[Wag07]

Eric-Jan Wagenmakers. A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14(5):779–804, 2007. doi:10.3758/BF03194105.

[WAArribasBel18]

Levi John Wolf, Luc Anselin, and Daniel Arribas-Bel. Stochastic Efficiency of Bayesian Markov Chain Monte Carlo in Spatial Econometric Models: An Empirical Comparison of Exact Sampling Methods. Geographical Analysis, 50(1):97–119, 2018. URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12135 (visited on 2026-04-20), doi:10.1111/gean.12135.

[Yan10]

Zhenlin Yang. A robust LM test for spatial error components. Regional Science and Urban Economics, 40(5):299–310, 2010. URL: https://linkinghub.elsevier.com/retrieve/pii/S0166046209000908 (visited on 2026-04-25), doi:10.1016/j.regsciurbeco.2009.10.001.

[ThomasAgnanL14]

Christine Thomas-Agnan and James P. LeSage. Spatial Econometric OD-Flow Models. In Manfred M. Fischer and Peter Nijkamp, editors, Handbook of Regional Science, pages 1653–1673. Springer Berlin Heidelberg, Berlin, Heidelberg, 2014. URL: http://link.springer.com/10.1007/978-3-642-23430-9, doi:10.1007/978-3-642-23430-9_87.