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Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement

In: Dynamic Factor Models

Author

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  • Laura E. Jackson
  • M. Ayhan Kose
  • Christopher Otrok
  • Michael T. Owyang

Abstract

We compare methods to measure comovement in business cycle data using multi-level dynamic factor models. To do so, we employ a Monte Carlo procedure to evaluate model performance for different specifications of factor models across three different estimation procedures. We consider three general factor model specifications used in applied work. The first is a single-factor model, the second a two-level factor model, and the third a three-level factor model. Our estimation procedures are the Bayesian approach ofOtrok and Whiteman (1998), the Bayesian state-space approach ofKim and Nelson (1998)and a frequentist principal components approach. The latter serves as a benchmark to measure any potential gains from the more computationally intensive Bayesian procedures. We then apply the three methods to a novel new dataset on house prices in advanced and emerging markets fromCesa-Bianchi, Cespedes, and Rebucci (2015)and interpret the empirical results in light of the Monte Carlo results.

Suggested Citation

  • Laura E. Jackson & M. Ayhan Kose & Christopher Otrok & Michael T. Owyang, 2016. "Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 361-400, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320150000035009
    DOI: 10.1108/S0731-905320150000035009
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    Cited by:

    1. Jackson, Laura E. & Owyang, Michael T. & Zubairy, Sarah, 2018. "Debt and stabilization policy: Evidence from a Euro Area FAVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 67-91.
    2. Shiyi Wang, 2019. "Capital Flow Volatility: The Effects of Financial Development and Global Financial Conditions," 2019 Papers pwa945, Job Market Papers.
    3. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    4. Raphael A. Auer & Andrei A. Levchenko & Philip Sauré, 2019. "International Inflation Spillovers through Input Linkages," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 507-521, July.
    5. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
    6. Krzysztof Beck & Karen Jackson, 2024. "International trade fluctuations: Global versus regional factors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(1), pages 331-358, February.
    7. Beck, Krzysztof, 2021. "Why business cycles diverge? Structural evidence from the European Union," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    8. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    9. Guisinger, Amy Y. & Owyang, Michael T. & Soques, Daniel, 2024. "Industrial Connectedness and Business Cycle Comovements," Econometrics and Statistics, Elsevier, vol. 29(C), pages 132-149.
    10. Petre Caraiani & Adrian Cantemir Călin, 2020. "Housing markets, monetary policy, and the international co‐movement of housing bubbles," Review of International Economics, Wiley Blackwell, vol. 28(2), pages 365-375, May.
    11. Arango-Castillo, Lenin & Orraca, María José & Molina, G. Stefano, 2023. "The global component of headline and core inflation in emerging market economies and its ability to improve forecasting performance," Economic Modelling, Elsevier, vol. 120(C).
    12. Xufeng Jiang & Zelu Jia & Lefei Li & Tianhong Zhao, 2022. "Understanding Housing Prices Using Geographic Big Data: A Case Study in Shenzhen," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    13. Zahid,Hamza, 2023. "Global Footprints of U.S. Energy Innovations: Energy Efficiency and the Shale Revolution," Policy Research Working Paper Series 10402, The World Bank.
    14. Beetsma, Roel & Cimadomo, Jacopo & van Spronsen, Josha, 2024. "One scheme fits all: A central fiscal capacity for the EMU targeting eurozone, national and regional shocks," European Economic Review, Elsevier, vol. 165(C).
    15. Krzysztof Beck & Piotr Stanek, 2019. "Globalization or Regionalization of Stock Markets? the Case of Central and Eastern European Countries," Eastern European Economics, Taylor & Francis Journals, vol. 57(4), pages 317-330, July.
    16. Klarl, Torben, 2018. "Housing is local: Applying a dynamic unobserved factor model for the Dutch housing market," Economics Letters, Elsevier, vol. 170(C), pages 79-84.
    17. Saban Nazlioglu & Sinem Pinar Gurel & Sevcan Gunes & Tugba Akin & Cagin Karul & Muhsin Kar, 2025. "Inflation co-movement: new insights from quantile factor model," Empirical Economics, Springer, vol. 69(1), pages 431-464, July.
    18. Harrison, James M., 2023. "Exploring 200 years of U.S. commodity market integration: A structural time series model approach," Explorations in Economic History, Elsevier, vol. 88(C).
    19. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    20. Shambaugh, Jay C. & Zhou, Hang, 2024. "Interest rates across the world: Global, regional, and idiosyncratic factors," Journal of Banking & Finance, Elsevier, vol. 163(C).
    21. Mirco Balatti & M. Ayhan Kose & Kate McKinnon & Edoardo Palombo & Naotaka Sugawara & Guillermo Verduzco-Bustos & Dana Vorisek, 2025. "From Tailwinds to Headwinds: Emerging and Developing Economies in the Twenty-First Century," CAMA Working Papers 2025-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    22. Caraiani, Petre & Călin, Adrian Cantemir, 2024. "The comovement of bubbles’ responses to monetary policy shocks," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    23. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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