IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20100040.html
   My bibliography  Save this paper

Is Economic Recovery a Myth? Robust Estimation of Impulse Responses

Author

Listed:
  • Coen N. Teulings

    (CPB, The Hague, and University of Amsterdam)

  • Nick Zubanov

    (CPB, The Hague)

Abstract

See the publication in the 'Journal of Applied Econometrics' (2014). We estimate the impulse response function (IRF) of GDP toa banking crisis, applying an extension of the local projectionsmethod developed in Jorda (2005). This method is shown to bemore robust to misspecification than calculating IRFs analytically. However, it suffers from a hitherto unnoticed systematicbias which increases with the forecast horizon. We propose asimple correction to this bias, which our Monte Carlo simulations show works well. Applying our corrected local projectionsestimator to a panel of 99 countries observed between 1974-2001,we find that an average banking crisis yields a long-term GDP lossof around 10 percent with little sign of recovery within 10 years.GDP losses to banking crises are even more severe in Africancountries. Like the original Jorda's (2005) method, our extensionof it is quite widely applicable.

Suggested Citation

  • Coen N. Teulings & Nick Zubanov, 2010. "Is Economic Recovery a Myth? Robust Estimation of Impulse Responses," Tinbergen Institute Discussion Papers 10-040/3, Tinbergen Institute, revised 07 Jul 2011.
  • Handle: RePEc:tin:wpaper:20100040
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/10040.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    2. Valerie Cerra & Sweta Chaman Saxena, 2008. "Growth Dynamics: The Myth of Economic Recovery," American Economic Review, American Economic Association, vol. 98(1), pages 439-457, March.
    3. Soskice, David, 1990. "Wage Determination: The Changing Role of Institutions in Advanced Industrialized Countries," Oxford Review of Economic Policy, Oxford University Press, vol. 6(4), pages 36-61, Winter.
    4. John Y. Campbell & N. Gregory Mankiw, 1987. "Are Output Fluctuations Transitory?," The Quarterly Journal of Economics, Oxford University Press, vol. 102(4), pages 857-880.
    5. Layard, Richard & Nickell, Stephen & Jackman, Richard, 2005. "Unemployment: Macroeconomic Performance and the Labour Market," OUP Catalogue, Oxford University Press, number 9780199279173.
    6. Jennifer Hunt, 1994. "Firing Costs, Employment Fluctuations and Average Employment: An Examination of Germany," NBER Working Papers 4825, National Bureau of Economic Research, Inc.
    7. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    8. Katharine G. Abraham & Susan N. Houseman, 1994. "Does Employment Protection Inhibit Labor Market Flexibility? Lessons from Germany, France, and Belgium," NBER Chapters, in: Social Protection versus Economic Flexibility: Is There a Trade-Off?, pages 59-94, National Bureau of Economic Research, Inc.
    9. Katharine G. Abraham & Susan Houseman, 1995. "Earnings Inequality in Germany," NBER Chapters, in: Differences and Changes in Wage Structures, pages 371-404, National Bureau of Economic Research, Inc.
    10. Stewart, Mark B, 1990. "Union Wage Differentials, Product Market Influences and the Division of Rents," Economic Journal, Royal Economic Society, vol. 100(403), pages 1122-1137, December.
    11. Samuel Bentolila & Giuseppe Bertola, 1990. "Firing Costs and Labour Demand: How Bad is Eurosclerosis?," Review of Economic Studies, Oxford University Press, vol. 57(3), pages 381-402.
    12. Eric A. Hanushek & Dongwook Kim, 1995. "Schooling, Labor Force Quality, and Economic Growth," NBER Working Papers 5399, National Bureau of Economic Research, Inc.
    13. Jon Faust & Jonathan H. Wright, 2011. "Efficient Prediction of Excess Returns," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 647-659, May.
    14. Hashimoto, Masanori, 1981. "Firm-Specific Human Capital as a Shared Investment," American Economic Review, American Economic Association, vol. 71(3), pages 475-482, June.
    15. Hart, Oliver, 1995. "Firms, Contracts, and Financial Structure," OUP Catalogue, Oxford University Press, number 9780198288817.
    16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    17. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    18. Cai, Xiaoming & Den Haan, Wouter, 2009. "Predicting recoveries and the importance of using enough information," CEPR Discussion Papers 7508, C.E.P.R. Discussion Papers.
    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. Machiel van Dijk & Machiel Mulder, 2005. "Regulation of telecommunication and deployment of broadband," CPB Memorandum 131.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    2. Coen N. Teulings & Nikolay Zubanov, 2014. "Is Economic Recovery A Myth? Robust Estimation Of Impulse Responses," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 497-514, April.
    3. Afonso, António & Jalles, João Tovar, 2019. "The Fiscal consequences of deflation: Evidence from the Golden Age of Globalization," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 129-147.
    4. Sanz, Carlos & Gonzalo Muñoz, Jesus & Alloza, Mario, 2019. "Dynamic Effects of Persistent Shocks," UC3M Working papers. Economics 29187, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2011. "When credit bites back: leverage, business cycles, and crises," Working Paper Series 2011-27, Federal Reserve Bank of San Francisco.
    6. repec:eee:labchp:v:3:y:1999:i:pc:p:2985-3028 is not listed on IDEAS
    7. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    8. Murtin, Fabrice & de Serres, Alain & Hijzen, Alexander, 2014. "Unemployment and the coverage extension of collective wage agreements," European Economic Review, Elsevier, vol. 71(C), pages 52-66.
    9. Furceri, Davide & Zdzienicka, Aleksandra, 2012. "How costly are debt crises?," Journal of International Money and Finance, Elsevier, vol. 31(4), pages 726-742.
    10. Davide Furceri & Aleksandra Zdzienicka, 2012. "The Consequences of Banking Crises for Public Debt," International Finance, Wiley Blackwell, vol. 15(3), pages 289-307, December.
    11. Ruta Aidis & Kate Bishop & Sjef Ederveen & Jan Fidrmuc & Jana P. Fidrmuc & Janos Köllö & Tomasz Mickiewicz & Almos Telegdy & Laura Thissen, 2004. "Wage and Employment Decisions of Enterprises in Downsized Industries," WIFO Studies, WIFO, number 25287, December.
    12. Mickiewicz, Tomasz & Gerry, Christopher J. & Bishop, Kate, 2005. "Privatisation, corporate control and employment growth: Evidence from a panel of large Polish firms, 1996-2002," Economic Systems, Elsevier, vol. 29(1), pages 98-119, March.
    13. Tomasz Marek Mickiewicz & Christopher Gerry & Kate Bishop, 2004. "Inherited labour hoarding, insiders and employment growth. Panel data results: Poland, 1996-2002," UCL SSEES Economics and Business working paper series 37, UCL School of Slavonic and East European Studies (SSEES).
    14. Furceri, Davide & Zdzienicka, Aleksandra, 2012. "Banking Crises and Short and Medium Term Output Losses in Emerging and Developing Countries: The Role of Structural and Policy Variables," World Development, Elsevier, vol. 40(12), pages 2369-2378.
    15. Steve Nickell & Jan van Ours, 2000. "The Netherlands and the United Kingdom: a European unemployment miracle?," Economic Policy, CEPR;CES;MSH, vol. 15(30), pages 136-180.
    16. J. Rodrigo Fuentes & Verónica Mies, 2007. "Changes in Monetary Policy Conduct and Their Effects on Banking Spreads," Working Papers Central Bank of Chile 428, Central Bank of Chile.
    17. Lapatinas, Athanasios, 2009. "Labour adjustment costs: Estimation of a dynamic discrete choice model using panel data for Greek manufacturing firms," Labour Economics, Elsevier, vol. 16(5), pages 521-533, October.
    18. Bentolila Samuel & Saint-Paul Gilles, 2003. "Explaining Movements in the Labor Share," The B.E. Journal of Macroeconomics, De Gruyter, vol. 3(1), pages 1-33, October.
    19. Caballero, Ricardo J. & Cowan, Kevin N. & Engel, Eduardo M.R.A. & Micco, Alejandro, 2013. "Effective labor regulation and microeconomic flexibility," Journal of Development Economics, Elsevier, vol. 101(C), pages 92-104.
    20. Addison, John T. & Teixeira, Paulino, 2001. "Employment Adjustment in Portugal: Evidence from Aggregate and Firm Data," IZA Discussion Papers 391, Institute of Labor Economics (IZA).
    21. Ant�nio Afonso & Jalles, 2016. "Markups' cyclical behaviour: the role of demand and supply shocks," Applied Economics Letters, Taylor & Francis Journals, vol. 23(1), pages 1-5, January.

    More about this item

    Keywords

    banking crisis; impulse response; panel data;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:tin:wpaper:20100040. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    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: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.