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Is Economic Recovery A Myth? Robust Estimation Of Impulse Responses

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  • Coen N. Teulings
  • Nikolay Zubanov

Abstract

SUMMARY We estimate the impulse response function (IRF) of GDP to a banking crisis using an extension of the local projections method. We demonstrate that, though robust to misspecifications of the data‐generating process, this method suffers from a hitherto unnoticed bias which increases with the forecast horizon. We propose a correction to this bias and show through simulations that it works well. Applying our corrected local projections estimator to the data from a panel of 99 countries observed between 1974 and 2001, we find that an average banking crisis yields a GDP loss of just under 10% in 10 years, with little sign of recovery. Like the original local projections method, our extension of it is widely applicable. Copyright © 2013 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:japmet:v:29:y:2014:i:3:p:497-514
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Yanping Chong & Òscar Jordà & Alan M. Taylor, 2012. "The Harrod–Balassa–Samuelson Hypothesis: Real Exchange Rates And Their Long‐Run Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 609-634, May.
    6. 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.
    7. 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.
    8. Jon Faust & Jonathan H. Wright, 2008. "Efficient Prediction of Excess Returns," NBER Working Papers 14169, National Bureau of Economic Research, Inc.
    9. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    10. 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.
    11. 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.
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    JEL classification:

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

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