IDEAS home Printed from https://ideas.repec.org/a/ksa/szemle/1296.html
   My bibliography  Save this article

A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel
[The sectoral effects of monetary policy in Hungary: a structural factor]

Author

Listed:
  • Pellényi, Gábor

Abstract

A monetáris politika magyar gazdaságra gyakorolt hatásait vizsgáló strukturális, dinamikus faktormodell számos makrogazdasági és ágazati idősor együttes tanulmányozását teszi lehetővé, így az eddigi idősoros elemzéseknél gazdagabb képet nyújt a monetáris transzmisszióról. A modell kvalitatív következtetései általában összhangban állnak a korábbi, VAR modelleken alapuló elemzésekkel, ám erősebbnek tűnnek a monetáris politika munkapiacra, illetve lakossági fogyasztásra gyakorolt hatásai. Az általunk vizsgált modell szerint a makrogazdasági folyamatokat 2000 óta elsősorban a kereslet ingadozásai határozták meg. A monetáris politika hosszabb távon szisztematikusan reagál a gazdaságot ért sokkokra, a meglepetésszerű monetáris politikai lépések szerepe mérsékelt.

Suggested Citation

  • Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
  • Handle: RePEc:ksa:szemle:1296
    as

    Download full text from publisher

    File URL: http://www.kszemle.hu/tartalom/letoltes.php?id=1296
    Download Restriction: Registration and subscription. 3-month embargo period to non-subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Marek Jarocinski, 2010. "Responses to monetary policy shocks in the east and the west of Europe: a comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 833-868.
    3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    4. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    5. Vonnák Balázs, 2010. "Risk Premium Shocks, Monetary Policy and Exchange Rate Pass-Through in the Czech Republic, Hungary and Poland," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 28(61), pages 306-351, August.
    6. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    7. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    8. Neumeyer, Pablo A. & Perri, Fabrizio, 2005. "Business cycles in emerging economies: the role of interest rates," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 345-380, March.
    9. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2011. "Non‐Fundamentalness in Structural Econometric Models: A Review," International Statistical Review, International Statistical Institute, vol. 79(1), pages 16-47, April.
    10. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
    11. Gábor Pellényi, 2012. "The Sectoral Effects of Monetary Policy in Hungary: A Structural Factor Analysis," MNB Working Papers 2012/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    12. Ms. Adina Popescu & Ms. Alina Carare, 2011. "Monetary Policy and Risk-Premium Shocks in Hungary: Results from a Large Bayesian VAR," IMF Working Papers 2011/259, International Monetary Fund.
    13. 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.
    14. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    15. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
    16. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2009. "Opening The Black Box: Structural Factor Models With Large Cross Sections," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1319-1347, October.
    17. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
    18. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1113-1141, December.
    19. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    20. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    21. G. Peersman & R. Straub, 2006. "Putting the New Keynesian Model to a Test," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/375, Ghent University, Faculty of Economics and Business Administration.
    22. Forni, Mario & Gambetti, Luca, 2010. "The dynamic effects of monetary policy: A structural factor model approach," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
    23. Konstantins Benkovskis & Andrejs Bessonovs & Martin Feldkircher & Julia Wörz, 2011. "The Transmission of Euro Area Monetary Shocks to the Czech Republic, Poland and Hungary: Evidence from a FAVAR Model," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-36.
    24. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    25. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    26. Ágnes Horváth & Zoltán M. Jakab & Gábor P. Kiss & Balázs Párkányi, 2006. "Myths and Maths: Macroeconomic Effects of Fiscal Adjustments in Hungary," MNB Occasional Papers 2006/52, Magyar Nemzeti Bank (Central Bank of Hungary).
    27. Amengual, Dante & Watson, Mark W., 2007. "Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 91-96, January.
    28. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
    29. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
    30. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
    31. Zoltán Reppa, 2009. "A joint macroeconomic-yield curve model for Hungary," MNB Working Papers 2009/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    32. Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
    33. Zoltán M. Jakab & Éva Kaponya, 2010. "A Structural Vector Autoregressive (SVAR) model for the Hungarian labour market," MNB Working Papers 2010/11, Magyar Nemzeti Bank (Central Bank of Hungary).
    34. Mark Gertler & Kenneth Rogoff (ed.), 2005. "NBER Macroeconomics Annual 2004," MIT Press Books, The MIT Press, edition 1, volume 1, number 026257229x, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Szabolcs Szikszai & Tamás Badics & Csilla Raffai & Zsolt Stenger & András Tóthmihály, 2013. "Studies in Financial Systems No 8 Hungary," FESSUD studies fstudy08, Financialisation, Economy, Society & Sustainable Development (FESSUD) Project.
    2. Katalin Szilágyi & Dániel Baksa & Jaromir Benes & Ágnes Horváth & Csaba Köber & Gábor D. Soós, 2013. "The Hungarian Monetary Policy Model," MNB Working Papers 2013/1, Magyar Nemzeti Bank (Central Bank of Hungary).

    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. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    2. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    3. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    4. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    5. Gábor Pellényi, 2012. "The Sectoral Effects of Monetary Policy in Hungary: A Structural Factor Analysis," MNB Working Papers 2012/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    6. Jin, Xisong & Nadal De Simone, Francisco, 2020. "Monetary policy and systemic risk-taking in the Euro area investment fund industry: A structural factor-augmented vector autoregression analysis," Journal of Financial Stability, Elsevier, vol. 49(C).
    7. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    8. Forni, Mario & Gambetti, Luca, 2010. "The dynamic effects of monetary policy: A structural factor model approach," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
    9. Kabundi, Alain & De Simone, Francisco Nadal, 2022. "Euro area banking and monetary policy shocks in the QE era," Journal of Financial Stability, Elsevier, vol. 63(C).
    10. Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
    11. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    12. Forni, Mario & Cavicchioli, Maddalena & Lippi, Marco & Zaffaroni, Paolo, 2016. "Eigenvalue Ratio Estimators for the Number of Common Factors," CEPR Discussion Papers 11440, C.E.P.R. Discussion Papers.
    13. Mario Forni & Luca Gambetti, 2010. "Fiscal Foresight and the Effects of Government Spending," UFAE and IAE Working Papers 851.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    14. Jörg Breitung & In Choi, 2013. "Factor models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 11, pages 249-265, Edward Elgar Publishing.
      • In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
    15. 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.
    16. Mario Forni & Luca Gambetti, 2010. "Macroeconomic Shocks and the Business Cycle: Evidence from a Structural Factor Model," Center for Economic Research (RECent) 040, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    17. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    18. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    19. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," Working Papers ECARES ECARES 2011-019, ULB -- Universite Libre de Bruxelles.
    20. Luca Gambetti, 2010. "Fiscal Policy, Foresight and the Trade Balance in the U.S," UFAE and IAE Working Papers 852.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    More about this item

    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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    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:ksa:szemle:1296. 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: Odon Sok (email available below). General contact details of provider: http://www.kszemle.hu .

    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.