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Business, Housing, and Credit Cycles – The Case of Hungary

Author

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  • Eyno Rots

    (Magyar Nemzeti Bank)

Abstract

This paper studies the characteristics of financial cycles in Hungary. It applies existing methodology from the literature to Hungarian data to estimate a multivariate structural time-series model. The model allows for a joint examination of the behaviour of the Hungarian financial sector and the overall economy, and estimates their cyclical positions. According to the results of the estimation, the financial sector in Hungary seems to experience volatile cycles, which last more than 15 years on average. Moreover, the cyclical position of output seems to show strong comovement with the long financial-sector cycles. Although the data series available for Hungary are relatively short, the results of the estimation are quite credible, since they conform to the existing international evidence and seem robust to even stricter data limitations.

Suggested Citation

  • Eyno Rots, 2018. "Business, Housing, and Credit Cycles – The Case of Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 17(4), pages 5-22.
  • Handle: RePEc:mnb:finrev:v:17:y:2018:i:4:p:5-22
    as

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    References listed on IDEAS

    as
    1. Tamás Berki & Tibor Szendrei, 2017. "The cyclical position of housing prices – a VECM approach for Hungary," MNB Occasional Papers 2017/126, Magyar Nemzeti Bank (Central Bank of Hungary).
    2. Galati, Gabriele & Hindrayanto, Irma & Koopman, Siem Jan & Vlekke, Marente, 2016. "Measuring financial cycles in a model-based analysis: Empirical evidence for the United States and the euro area," Economics Letters, Elsevier, vol. 145(C), pages 83-87.
    3. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    4. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
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    6. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Preface," MPRA Paper 17451, University Library of Munich, Germany.
    7. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
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    9. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Chapter 1," MPRA Paper 17452, University Library of Munich, Germany.
    10. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring financial cycles with a model-based filter: Empirical evidence for the United States and the euro area," DNB Working Papers 495, Netherlands Central Bank, Research Department.
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    12. Levente Kocsis & Miklos Sallay, 2018. "Credit-to-GDP gap calculation using multivariate HP filter," MNB Occasional Papers 2018/136, Magyar Nemzeti Bank (Central Bank of Hungary).
    13. Rünstler, Gerhard & Balfoussia, Hiona & Burlon, Lorenzo & Buss, Ginters & Comunale, Mariarosaria & De Backer, Bruno & Dewachter, Hans & Guarda, Paolo & Haavio, Markus & Hindrayanto, Irma & Iskrev, Nik, 2018. "Real and financial cycles in EU countries - Stylised facts and modelling implications," Occasional Paper Series 205, European Central Bank.
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    Cited by:

    1. Paolo Guarda & Alban Moura, 2019. "Measuring real and financial cycles in Luxembourg: An unobserved components approach," BCL working papers 126, Central Bank of Luxembourg.

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    More about this item

    Keywords

    time-series models; financial cycles; real business cycles; house prices; MLE;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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