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A Bayesian Markov-switching SAR model for time-varying cross-price spillovers

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  • Christian Glocker
  • Matteo Iacopini
  • Tam'as Krisztin
  • Philipp Piribauer

Abstract

The spatial autoregressive (SAR) model is extended by introducing a Markov switching dynamics for the weight matrix and spatial autoregressive parameter. The framework enables the identification of regime-specific connectivity patterns and strengths and the study of the spatiotemporal propagation of shocks in a system with a time-varying spatial multiplier matrix. The proposed model is applied to disaggregated CPI data from 15 EU countries to examine cross-price dependencies. The analysis identifies distinct connectivity structures and spatial weights across the states, which capture shifts in consumer behaviour, with marked cross-country differences in the spillover from one price category to another.

Suggested Citation

  • Christian Glocker & Matteo Iacopini & Tam'as Krisztin & Philipp Piribauer, 2023. "A Bayesian Markov-switching SAR model for time-varying cross-price spillovers," Papers 2310.19557, arXiv.org.
    • Handle: RePEc:arx:papers:2310.19557
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    References listed on IDEAS

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    1. Tamás Krisztin & Philipp Piribauer, 2023. "A Bayesian approach for the estimation of weight matrices in spatial autoregressive models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(1), pages 44-63, January.
    2. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    3. Debarsy, Nicolas & Dossougoin, Cyrille & Ertur, Cem & Gnabo, Jean-Yves, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 21-45.
    4. Yuriy Gorodnichenko & Viacheslav Sheremirov & Oleksandr Talavera, 2018. "Price Setting in Online Markets: Does IT Click?," Journal of the European Economic Association, European Economic Association, vol. 16(6), pages 1764-1811.
    5. Qu, Xi & Lee, Lung-fei & Yang, Chao, 2021. "Estimation of a SAR model with endogenous spatial weights constructed by bilateral variables," Journal of Econometrics, Elsevier, vol. 221(1), pages 180-197.
    6. Regmi, Anita & Seale, James L., Jr., 2010. "Cross-Price Elasticities of Demand Across 114 Countries," Technical Bulletins 59870, United States Department of Agriculture, Economic Research Service.
    7. 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.
    8. Zhang, Xinyu & Yu, Jihai, 2018. "Spatial weights matrix selection and model averaging for spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 203(1), pages 1-18.
    9. Yuriy Gorodnichenko & Oleksandr Talavera, 2017. "Price Setting in Online Markets: Basic Facts, International Comparisons, and Cross-Border Integration," American Economic Review, American Economic Association, vol. 107(1), pages 249-282, January.
    10. Carrière-Swallow, Yan & Deb, Pragyan & Furceri, Davide & Jiménez, Daniel & Ostry, Jonathan D., 2023. "Shipping costs and inflation," Journal of International Money and Finance, Elsevier, vol. 130(C).
    11. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    12. Clifford Lam & Pedro C.L. Souza, 2020. "Estimation and Selection of Spatial Weight Matrix in a Spatial Lag Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 693-710, July.
    13. Regmi, Anita & Seale, James L., Jr., 2010. "Cross-Price Elasticities of Demand Across 114 Countries," Technical Bulletins 59870, United States Department of Agriculture, Economic Research Service.
    14. Piribauer, Philipp & Glocker, Christian & Krisztin, Tamás, 2023. "Beyond distance: The spatial relationships of European regional economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    15. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    16. Nicolas Debarsy & James P. LeSage, 2022. "Bayesian Model Averaging for Spatial Autoregressive Models Based on Convex Combinations of Different Types of Connectivity Matrices," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 547-558, April.
    17. Harald Badinger & Peter Egger, 2010. "Horizontal vs. Vertical Interdependence in Multinational Activity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(6), pages 744-768, December.
    18. 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.
    19. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    20. Anna Gloria Billé & Marco Rogna, 2022. "The effect of weather conditions on fertilizer applications: A spatial dynamic panel data analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 3-36, January.
    21. Süleyman Taşpınar & Osman DoĞan & Jiyoung Chae & Anil K. Bera, 2021. "Bayesian Inference in Spatial Stochastic Volatility Models: An Application to House Price Returns in Chicago," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1243-1272, October.
    22. Treb Allen & Costas Arkolakis, 2023. "Economic Activity across Space: A Supply and Demand Approach," Journal of Economic Perspectives, American Economic Association, vol. 37(2), pages 3-28, Spring.
    23. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    24. Florian Huber & Manfred M. Fischer, 2018. "A Markov Switching Factor‐Augmented VAR Model for Analyzing US Business Cycles and Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 575-604, June.
    25. Bernard Fingleton, 2014. "Forecasting with dynamic spatial panel data: practical implementation methods," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 194-207.
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