IDEAS home Printed from https://ideas.repec.org/p/mnb/wpaper/2017-7.html
   My bibliography  Save this paper

The EAGLE model for Hungary - a global perspective

Author

Listed:
  • László Békési

    (Magyar Nemzeti Bank (Central Bank of Hungary))

  • Lorant Kaszab

    (Magyar Nemzeti Bank (Central Bank of Hungary))

  • Szabolcs Szentmihályi

    (Magyar Nemzeti Bank (Central Bank of Hungary))

Abstract

In this paper we adopt the Hungarian version of the EAGLE (Euro Area GLobal Economy) model. The version of the EAGLE model used in this paper allows for the high import content of export a typical feature of small open economies such as Hungary. We study the effects of four globally important shocks on Hungary: i) a slowdown of the Chinese economy, ii) more restrictive US monetary policy, iii) a reduction in oil prices, and iv) more protectionist US trade policy. We found these policies to have non-negligible indirect e/ects (beyond the relatively small direct ones) on Hungary mostly due to the workings of the shock to the eurozone which is our main trade partner.

Suggested Citation

  • László Békési & Lorant Kaszab & Szabolcs Szentmihályi, 2017. "The EAGLE model for Hungary - a global perspective," MNB Working Papers 2017/7, Magyar Nemzeti Bank (Central Bank of Hungary).
    • Handle: RePEc:mnb:wpaper:2017/7
    as

    Download full text from publisher

    File URL: http://www.mnb.hu/letoltes/mnb-wp-2017-7-final.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Forecasting with factor-augmented error correction models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 589-612.
    2. Ricardo J. Caballero & Arvind Krishnamurthy, 2008. "Collective Risk Management in a Flight to Quality Episode," Journal of Finance, American Finance Association, vol. 63(5), pages 2195-2230, October.
    3. Sims, Christopher A., 1988. "Bayesian skepticism on unit root econometrics," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 463-474.
    4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    5. Grzegorz Hałaj & Christoffer Kok, 2013. "Assessing interbank contagion using simulated networks," Computational Management Science, Springer, vol. 10(2), pages 157-186, June.
    6. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
    7. Geweke, John & Koop, Gary & van Dijk, Herman (ed.), 2011. "The Oxford Handbook of Bayesian Econometrics," OUP Catalogue, Oxford University Press, number 9780199559084.
    8. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    9. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    10. Mr. Fabian Valencia & Mr. Luc Laeven, 2008. "Systemic Banking Crises: A New Database," IMF Working Papers 2008/224, International Monetary Fund.
    11. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    12. Gary Gorton, 2009. "Information, Liquidity, and the (Ongoing) Panic of 2007," American Economic Review, American Economic Association, vol. 99(2), pages 567-572, May.
    13. Illing, Mark & Liu, Ying, 2006. "Measuring financial stress in a developed country: An application to Canada," Journal of Financial Stability, Elsevier, vol. 2(3), pages 243-265, October.
    14. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    15. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    16. Judit Páles & Lóránt Varga, 2008. "Trends in the liquidity of Hungarian financial markets – What does the MNB’s new liquidity index show?," MNB Bulletin (discontinued), Magyar Nemzeti Bank (Central Bank of Hungary), vol. 3(1), pages 44-51, April.
    17. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    18. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    19. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    20. Otrok, Christopher & Whiteman, Charles H, 1998. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 997-1014, November.
    21. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    22. Mr. Amadou N Sy & Mr. Jorge A Chan-Lau, 2006. "Distance-to-Default in Banking: A Bridge Too Far?," IMF Working Papers 2006/215, International Monetary Fund.
    23. Jin-Chuan Duan & Tao Wang, 2012. "Measuring Distance-to-Default for Financial and Non-Financial Firms," World Scientific Book Chapters, in: Risk Management Institute, Singapore (ed.), Global Credit Review, chapter 6, pages 95-108, World Scientific Publishing Co. Pte. Ltd..
    24. Jan Hatzius & Peter Hooper & Frederic S. Mishkin & Kermit L. Schoenholtz & Mark W. Watson, 2010. "Financial Conditions Indexes: A Fresh Look after the Financial Crisis," NBER Working Papers 16150, National Bureau of Economic Research, Inc.
    25. Jin-Chuan Duan & Tao Wang, 2012. "Measuring Distance-to-Default for Financial and Non-Financial Firms," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 95-108.
    26. Freixas, Xavier & Laeven, Luc & Peydró, José-Luis, 2015. "Systemic Risk, Crises, and Macroprudential Regulation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262028697, December.
    27. Gabor Fukker, 2017. "Harmonic distances and systemic stability in heterogeneous interbank networks," MNB Working Papers 2017/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    28. Eickmeier, Sandra, 2005. "Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model," Discussion Paper Series 1: Economic Studies 2005,02, Deutsche Bundesbank.
    29. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5.
    30. Hooper, Peter & Kohlhagen, Steven W., 1978. "The effect of exchange rate uncertainty on the prices and volume of international trade," Journal of International Economics, Elsevier, vol. 8(4), pages 483-511, November.
    31. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    32. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    33. Cevik, Emrah Ismail & Dibooglu, Sel & Kutan, Ali M., 2013. "Measuring financial stress in transition economies," Journal of Financial Stability, Elsevier, vol. 9(4), pages 597-611.
    34. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    35. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    36. Uhlig, Harald, 1994. "What Macroeconomists Should Know about Unit Roots: A Bayesian Perspective," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 645-671, August.
    37. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tibor Szendrei & Katalin Varga, 2020. "FISS - A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.
    2. Tibor Szendrei & Katalin Varga, 2020. "FISS - A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.
    3. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    4. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    5. repec:hum:wpaper:sfb649dp2014-004 is not listed on IDEAS
    6. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    7. Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    8. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    9. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    10. Stelios D. Bekiros & Alessia Paccagnini, 2016. "Policy‐Oriented Macroeconomic Forecasting with Hybrid DGSE and Time‐Varying Parameter VAR Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 613-632, November.
    11. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    12. Pirschel, Inske & Wolters, Maik, 2014. "Forecasting German key macroeconomic variables using large dataset methods," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100587, Verein für Socialpolitik / German Economic Association.
    13. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    14. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    15. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
    16. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
    17. Tomasz Wozniak, 2016. "Rare Events and Risk Perception: Evidence from Fukushima Accident," Department of Economics - Working Papers Series 2021, The University of Melbourne.
    18. repec:hum:wpaper:sfb649dp2013-011 is not listed on IDEAS
    19. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    20. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    21. И Управления Мир Экономики, 2017. "Байесовский подход к анализу влияния монетарной политики на макроэкономические показатели России. Bayesian approach to the analysis of monetary policy impact on Russian macroeconomics indicators," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(4), pages 53-70.
    22. Geiger, Martin & Gründler, Daniel & Scharler, Johann, 2023. "Monetary policy shocks and consumer expectations in the euro area," Journal of International Economics, Elsevier, vol. 140(C).

    More about this item

    Keywords

    Multi-country DSGE; price and wage rigidity; EAGLE model; trade matrix; import content of export; local currency pricing; monetary policy shock; consumption preference shock; markup-shock.;
    All these keywords.

    JEL classification:

    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • F11 - International Economics - - Trade - - - Neoclassical Models of Trade
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mnb:wpaper:2017/7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lorant Kaszab (email available below). General contact details of provider: https://edirc.repec.org/data/mnbgvhu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.