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A NOTE ON MEASURING US TIME SERIES VOLATILITY DURING THE GREAT MODERATION

Published online by Cambridge University Press:  26 June 2019

Isaiah Hull
Isaiah Hull*
Affiliation:
Research Division, Sveriges Riksbank
*
Address correspondence to: Isaiah Hull, Research Division, Sveriges Riksbank, SE-103 37, Stockholm, Sweden. e-mail: [email protected]. Phone: +46 076 589 0661. Fax: +46 80 821 0531.
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Abstract

We identify volatility breaks in all testable series in the FRED database over the 1957–2013 period. This yields 17,681 breaks, which we categorize using text analysis. We show that 70.5% of series categories experienced a decline in volatility over the 1985–1999 period, suggesting that the Great Moderation was far broader in scope than the literature has documented. We also show that this decline reversed in 2000, leading to a sharp increase in volatility for most time series categories; however, this did not fully materialize in GDP volatility until the Great Recession. Finally, we identify labor markets, demographics, finance, and government debt as potential drivers of low-frequency shifts in volatility over the 1957–2013 period.

Keywords

Great ModerationMacroeconomicsBusiness CyclesVolatility
Type
Notes
Information
Macroeconomic Dynamics , Volume 25 , Issue 4 , June 2021 , pp. 1126 - 1143
Copyright
© Cambridge University Press 2019

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Footnotes

I would like to thank Gaetano Antinolfi, Martin D. Evans, Edward Kung, Andres Liberman, Jesper Lindé, Alexander Ludwig, George Skiadopoulos, Hiroatsu Tanaka, Robert Vigfusson, and Xin Zhang, as well as participants at the GSMG, CEF, and SNDE for their comments and suggestions. The views expressed in this paper are solely the responsibility of the author and should not be interpreted as reflecting the views of the Executive Board of Sveriges Riksbank.

References

REFERENCES

Acemoglu, D., Carvalho, V., Ozdaglar, A. and Tahbaz-Salehi, A. (2012) The network origins of aggregate fluctuations. Econometrica 80(5), 1977–2016.Google Scholar
Ahmed, S., Levin, A. and Wilson, B. (2004) Recent U.S. macroeconomic stability: Good policies, good practices, or good luck? The Review of Economics and Statistics 86(3), 824–832.CrossRefGoogle Scholar
Bai, J. and Perron, P. (2003) Computation and analysis of multiple structural breaks. Journal of Applied Econometrics 18(1), 1–22.CrossRefGoogle Scholar
Bils, M. and Kahn, J. (2000) What inventory behavior tells us about business cycles. American Economic Review 90(3), 458–481.CrossRefGoogle Scholar
Blanchard, O. and Simon, J. (2001) The long and large decline in U.S. output volatility. Brookings Papers on Economic Activity 32(1), 135–164.CrossRefGoogle Scholar
Boivin, J. and Giannoni, M. (2006) Has monetary policy become more effective? The Review of Economics and Statistics 88(3), 445–462.CrossRefGoogle Scholar
Burren, D. and Neusser, K. (2013) The role of sectoral shifts in the decline of real GDP Volatility. Macroeconomic Dynamics 17(3), 477–500.CrossRefGoogle Scholar
Carvalho, V. and Gabaix, X. (2013) The great diversification and its undoing. American Economic Review 103(5), 1697–1727.CrossRefGoogle Scholar
Clarida, R., Gali, J. and Gertler, M. (2000) Monetary policy rules and macroeconomic stability: Evidence and some theory. The Quarterly Journal of Economics 115(1), 147–180.CrossRefGoogle Scholar
Clark, T. (2009) Is the great moderation over? An empirical analysis. Federal Reserve Bank of Kansas City, Economic Review 4, 5–42.Google Scholar
Coibion, O. and Gorodnichenko, Y. (2011) Monetary policy, trend inflation, and the great moderation: An alternative interpretation. American Economic Review 101(1), 341–370.CrossRefGoogle Scholar
Davidian, M. and Carroll, R. (1987) Variance function estimation. Journal of the American Statistical Association 400(82), 1079–1091.CrossRefGoogle Scholar
Davis, S. and Kahn, J. (2008) Interpreting the great moderation: Changes in the volatility of economic activity at the macro and micro levels. Journal of Economic Perspectives 22(4), 155–180.CrossRefGoogle Scholar
Everaert, G. and Vierke, H. (2016) Demographics and business cycle volatility: A spurious relationship? Journal of Applied Econometrics 31, 1467–1477.CrossRefGoogle Scholar
Gabaix, X. (2011) The granular origins of aggregate fluctuations. Econometrica 79(3), 733–772.Google Scholar
Grydaki, M. and Bezemer, D. (2013) The role of credit in the great moderation: A multivariate GARCH approach. Journal of Banking and Finance, 37, 4615–4626.CrossRefGoogle Scholar
Heer, B., Rohrbacher, S. and Scharrer, C. (2017) Aging, the great moderation, and business-cycle volatility in a life-cycle model. Macroeconomic Dynamics 21(2), 362–383.CrossRefGoogle Scholar
Herrera, A.M. and Pesavento, E. (2009) Oil price shocks, systematic monetary policy, and the “Great Moderation.” Macroeconomic Dynamics 13(1), 107–137.CrossRefGoogle Scholar
Hornik, K., Kleiber, C., Krämer, W. and Zeileis, A. (2003) Testing and dating of structural changes in practice. Computational Statistics & Data Analysis 44(1-2), 109–123.Google Scholar
Jaimovich, N. and Siu, H. (2009) The young, the old, and the restless: Demo- graphics and business cycle volatility. American Economic Review 99(3), 804–829.CrossRefGoogle Scholar
Kahn, J. (2008) Durable goods inventories and the great moderation. Federal Reserve Bank of New York Staff Report No. 325.CrossRefGoogle Scholar
Kim, C. and Nelson, C. (1999) Has The U.S. economy become more stable? A bayesian approach based on a Markov-Switching model of the business cycle. The Review of Economics and Statistics 81(4), 608–616.CrossRefGoogle Scholar
Lubik, T. and Schorfheide, F. (2004) Testing for indeterminacy: An application to U.S. monetary policy. American Economic Review 94(1), 190–217.CrossRefGoogle Scholar
Lugaeur, S. (2012a) Demographic change and the great moderation in an overlapping generations model with matching frictions. Macroeconomic Dynamics, 16(5), 706–731.CrossRefGoogle Scholar
Lugaeur, S. (2012b) Estimating the effect of the age distribution on cyclical output volatility across the United States. Review of Economics and Statistics 94(4), 896–902.CrossRefGoogle Scholar
Lugaeur, S. and Redmond, M. (2012) The age distribution and business cycle volatility: International evidence. Economics Letters 117(3), 694–696.CrossRefGoogle Scholar
McConnell, M. and Perez-Quiros, G. (2000) Output fluctuations in the United States: What has changed since the early 1980s. The American Economic Review 90(5), 1464–1476.CrossRefGoogle Scholar
Maccini, L.J. and Pagan, A. (2013) Inventories, fluctuations, and goods sector cycles. Macroeconomic Dynamics 17(1), 89–122.CrossRefGoogle Scholar
Primiceri, G. E. (2006) Why inflation rose and fell: Policy-Makers beliefs and U.S. postwar stabilization policy. The Quarterly Journal of Economics 121(3), 867–901.CrossRefGoogle Scholar
Sarte, P., Schwartzman, F. and Lubik, T. (2015) What inventory behavior tells us about how business cycles have changed. Journal of Monetary Economics 76, 264–283.CrossRefGoogle Scholar
Sensier, M. and van Dijk, D. (2004) Testing for volatility changes in U.S. macroeconomic time series. The Review of Economics and Statistics 86(3), 833–839.CrossRefGoogle Scholar
Sims, C. and Zha, T. (2006) Were there regime switches in U.S. monetary policy. American Economic Review 96(1), 54–81.CrossRefGoogle Scholar
Stock, J. and Watson, M. (2012) Disentangling the Channels of the 2007–2009 Recession, NBER Working Papers: No. 18094.Google Scholar
Stock, J. H. and Watson, M. W. (2002) Has the business cycle changed and why? NBER Macroeconomics Annual 17, 160–230.CrossRefGoogle Scholar