Hostname: page-component-84b7d79bbc-4hvwz Total loading time: 0 Render date: 2024-07-29T09:54:05.118Z Has data issue: false hasContentIssue false
  • English
  • Français

Recovery from economic disasters

Published online by Cambridge University Press:  07 September 2023

Bruno Ćorić  and
Blanka Škrabić Perić
Bruno Ćorić*
Affiliation:
Faculty of Economics Business and Tourism, University of Split, Split, Croatia CERGE-EI Foundation, Newark, NJ, USA
Blanka Škrabić Perić
Affiliation:
Faculty of Economics Business and Tourism, University of Split, Split, Croatia
*
Corresponding author: Bruno Ćorić; Email: bcoric@efst.hr
Get access Rights & Permissions [Opens in a new window]

Abstract

This study uses two large datasets to explore the output dynamics following economic disasters, one including 180 economic disasters across 38 countries over the last two centuries and the other including 204 disasters in 182 countries since World War II. Our results suggest that extreme economic crises are associated with huge and remarkably persistent loss. On average, output loss surges to above 26% in the first few years after the outbreak of a disaster and remains above 20% for as long as 20 years. It is only after more than 50 years that the loss is fully recovered.

Keywords

Economic disastereconomic recoveryoutput loss
Type
Articles
Information
Macroeconomic Dynamics , First View , pp. 1 - 26
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aslanidis, N. and Fountas, S.. (2014) Is real GDP stationary? Evidence from a panel unit root test with cross-sectional dependence and historical data. Empirical Economics 46(1), 101–108.CrossRefGoogle Scholar
Barro, R. (2006) Rare disasters and asset markets in the twentieth century. The Quarterly Journal of Economics 121(3), 823–866.CrossRefGoogle Scholar
Barro, R. (2009) Rare disasters, asset prices, and welfare costs. American Economic Review 99(1), 243–264.CrossRefGoogle Scholar
Barro, R. and Liao, G.. (2020). Rare Disaster Probability and Options-Pricing. Finance and Economics Discussion Series 2019-073, Board of Governors of the Federal Reserve System, Washington CrossRefGoogle Scholar
Barro, R. and Ursúa, J.. (2008) Macroeconomic crises since 1870. Brookings Papers on Economic Activity 1, 255–335.CrossRefGoogle Scholar
Barro, R. and Ursúa, J.. (2010) Barro-Ursua Macroeconomic Data.Google Scholar
Barro, R. and Ursúa, J. (2012) Rare macroeconomic disasters. Annual Review of Economics 4(1), 83–109.CrossRefGoogle Scholar
Baum, C. and Lewbel, A.. (2019) Advice on using heteroscedasticity based identification. Stata Journal 19(4), 757–767.CrossRefGoogle Scholar
Bazzi, S. and Clemens, M.. (2013) Blunt instruments: Avoiding common pitfalls in identifying the causes of economic growth. American Economic Journal: Macroeconomics 5(2), 152–186.Google Scholar
Blundell, R. and Bond, S.. (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87(1), 115–143.CrossRefGoogle Scholar
Carrion-i-Silvestre, J., Kim, D. and Perron, P.. (2009) GLS-based unit root tests with multiple structural breaks both under the null and the alternative hypotheses. Econometric Theory 25(6), 1754–1792.CrossRefGoogle Scholar
Cerra, V., Fatás, A. and Sweta C. Saxena, S. C.. (2023) Hysteresis and business cycles. Journal of Economic Literature 61(1), 181–225.CrossRefGoogle Scholar
Cerra, V. and Saxena, S. C.. (2008) Growth dynamics: The Myth of economic recovery. American Economic Review 98(1), 439–457.CrossRefGoogle Scholar
Ćorić, B. (2021) Economic disasters: A new data set. Finance Research Letters 39, 101612.CrossRefGoogle Scholar
Cushman, D. (2016) A unit root in postwar U.S. Real GDP still cannot be rejected, and yes, it matters. Econ Journal Watch 13, 5–46.Google Scholar
da, R., Bruno, T. and Solomou, S.. (2015) The effects of systemic banking crises in the inter-war period. Journal of International Money and Finance 54, 35–49.Google Scholar
Darné, O. (2009) The uncertain unit root in real GNP: A re-examination. Journal of Macroeconomics, Advances in Historical Macroeconomics 31(1), 153–166.Google Scholar
Diebold, F. X. and Senhadji, A. S.. (1996) The uncertain unit root in real GNP: Comment. The American Economic Review 86, 1291–1298.Google Scholar
Farhi, E. and Gabaix, X.. (2016) Rare disasters and exchange rates. The Quarterly Journal of Economics 131(1), 1–52.CrossRefGoogle Scholar
Furceri, D. and Muorougane, A.. (2012) The effect of financial crises on potential output: New empirical evidence from OECD countries. Journal of Macroeconomics 34(3), 822–832.CrossRefGoogle Scholar
Furceri, D. and Zdzienicka, A.. (2012) Banking crises and short and medium term output losses in emerging and developing countries: The role of structural and policy variables. World Development 40(12), 2369–2378.CrossRefGoogle Scholar
Gabaix, X. (2012) Variable rare disasters: An exactly solved framework for ten puzzles in macro-finance. The Quarterly Journal of Economics 127(2), 645–700.CrossRefGoogle Scholar
Galvao, A. (2009) Unit root quantile autoregression testing using covariates. Journal of Econometrics 152(2), 165–178.CrossRefGoogle Scholar
Gorodnichenko, Y. and Auerbach, A. J.. (2013) Fiscal multipliers in recession and expansion. In: Gorodnichenko, Y. and Auerbach, A. J.. (eds.), Fiscal Policy after the Financial Crisis, pp. 63–98. Chichago: The University of Chicago Press.Google Scholar
Gourio, F. (2008) Disasters and recoveries. The American Economic Review 98(2), 68–73.CrossRefGoogle Scholar
Gourio, F. (2012) Disaster risk and business cycles. American Economic Review 102(6), 2734–2766.CrossRefGoogle Scholar
Gourio, F. (2013) Credit risk and disaster risk. American Economic Journal: Macroeconomics 5(3), 1–34.Google Scholar
Hamilton, J. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57(2), 357–384.CrossRefGoogle Scholar
Hosseinkouchack, M. and Wolters, M. H.. (2013) Do large recessions reduce output permanently? Economics Letters 121(3), 516–519.CrossRefGoogle Scholar
Isoré, M. and Szczerbowicz, U.. (2017) Disaster risk and preference shifts in a New Keynesian model. Journal of Economic Dynamics and Controls 79, 97–125.CrossRefGoogle Scholar
Jordà, Ò. (2005) Estimation and inference of impulse responses by local projections. American Economic Review 95(1), 161–182.CrossRefGoogle Scholar
Jordà, Ò., Singh, S. R. and Taylor, A. M.. (2022) Longer-run economic consequences of pandemics. The Review of Economics and Statistics 104(1), 166–175.CrossRefGoogle Scholar
Koenker, R. and Xiao, Z.. (2004) Unit root quantile autoregression inference. Journal of the American Statistical Association 99(467), 775–787.CrossRefGoogle Scholar
Lewbel, A. (2012) Using heteroscedasticity to identify and estimate mismeasured and endogenous regressor models. Journal of Business & Economic Statistics 30(1), 67–80.CrossRefGoogle Scholar
Maddison, A. (2010). Historical Statistics of the World Economy: 1-2008 AD.Google Scholar
Murray, C. and Nelson, C. R.. (2000) The uncertain trend in U.S GDP. Journal of Monetary Economics 46(1), 79–95.CrossRefGoogle Scholar
Nakamura, E., Steinsson, J., Barro, R. and Ursúa, J.. (2013) Crises and recoveries in an empirical model of consumption disasters. American Economic Journal: Macroeconomics 5(3), 35–74.Google Scholar
Nelson, C. R. and Plosser, C. R.. (1982) Trends and random walks in macroeconmic time series: Some evidence and implications. Journal of Monetary Economics 10(2), 139–162.CrossRefGoogle Scholar
Ng, S. and Perron, P.. (2001) Lag length selection and the construction of unit root tests with good size and power. Econometrica 69(6), 1519–1554.CrossRefGoogle Scholar
Nickell, S. (1981) Biases in dynamic models with fixed effects. Econometrica 49(6), 1417–1426.CrossRefGoogle Scholar
Rebelo, S., Wang, N. and Yang, J.. (2022) Rare disasters, financial development, and sovereign debt. The Journal of Finance 77(5), 2719–2764.CrossRefGoogle Scholar
Reinhart, C. and Rogoff, K.. (2011) From financial crash to debt crisis. American Economic Review 101(5), 1676–1706.CrossRefGoogle Scholar
Romer, C. D. and Romer, D. H.. (2017) New evidence on the aftermath of financial crises in advanced countries. American Economic Review 107(10), 3072–3118.CrossRefGoogle Scholar
Roodman, D. (2009a) How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal 9(1), 86–136.CrossRefGoogle Scholar
Roodman, D. (2009b) A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics 71(1), 135–158.CrossRefGoogle Scholar
Rudebusch, G. (1993) The uncertain unit root in real GNP. American Economic Review 83, 264–272.Google Scholar
Sarkees, R. M. and Wayman, F. W.. (2010) Resort to War: 1816 - 2007. Washington: CQ Press.CrossRefGoogle Scholar
Seo, S. B. and Wachter, J. A.. (2018) Option prices in a model with stochastic disaster risk. Management Science 65(8), 3449–3469.CrossRefGoogle Scholar
Shelley, G. L. and Wallace, F. H.. (2011) Further evidence regarding nonlinear trend reversion of real GDP and the CPI. Economics Letters 112(1), 56–59.CrossRefGoogle Scholar
Teulings, C. N. and Zubanov, N.. (2014) Is economic recovery a Myth? Robust estimation of impulse responses. Journal of Applied Econometrics 29(3), 497–514.CrossRefGoogle Scholar
Tola, A. and Waelti, S.. (2018) Financial crises, output losses, and the role of structural reforms. Economic Inquiry 56(2), 761–798.CrossRefGoogle Scholar
Tsai, J. and Wachter, J. A.. (2015) Disaster risk and its implications for asset pricing. Annual Review of Financial Economics 7(1), 219–252.CrossRefGoogle Scholar
Wachter, A. J. (2013) Can time-varying risk of rare disasters explain aggregate stock market volatility? The Journal of Finance 68(3), 987–1035.CrossRefGoogle Scholar
Yellen, J. (2016). Macroeconomic Research After the Crisis. A speech at The Elusive ‘Great’ Recovery: Causes and Implications for Future Business Cycle Dynamics, 60th annual economic conference sponsored, Speech 915 (Board of Governors of the Federal Reserve System).Google Scholar