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Aggregate skewness and the business cycle

Author

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  • Martin Iseringhausen

    (ESM)

  • Ivan Petrella

    (University of Warwick, CEPR)

  • Konstantinos Theodoridis

    (ESM)

Abstract

We develop a data-rich measure of expected macroeconomic skewness in the US economy. Expected macroeconomic skewness is strongly procyclical, mainly reflects the cyclicality in the skewness of real variables, is highly correlated with the cross-sectional skewness of firm-level employment growth and is distinct from financial market skewness. Revisions in expected skewness deliver dynamics that are nearly indistinguishable from those produced by the main business cycle shock of Angeletos et al. (2020). This result is robust to controlling for macroeconomic volatility and uncertainty, and alternative macroeconomic shocks. Our findings highlight the importance of higher-order dynamics for business cycle theories.

Suggested Citation

  • Martin Iseringhausen & Ivan Petrella & Konstantinos Theodoridis, 2022. "Aggregate skewness and the business cycle," Working Papers 53, European Stability Mechanism.
    • Handle: RePEc:stm:wpaper:53
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    1. Segal, Gill & Shaliastovich, Ivan & Yaron, Amir, 2015. "Good and bad uncertainty: Macroeconomic and financial market implications," Journal of Financial Economics, Elsevier, vol. 117(2), pages 369-397.
    2. Fève, Patrick & Sanchez, Pablo Garcia & Moura, Alban & Pierrard, Olivier, 2021. "Costly default and skewed business cycles," European Economic Review, Elsevier, vol. 132(C).
    3. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-236, April.
    4. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    5. George‐Marios Angeletos & Fabrice Collard & Harris Dellas, 2018. "Quantifying Confidence," Econometrica, Econometric Society, vol. 86(5), pages 1689-1726, September.
    6. Forni, Mario & Gambetti, Luca & Sala, Luca, 2021. "Downside and Upside Uncertainty Shocks," CEPR Discussion Papers 15881, C.E.P.R. Discussion Papers.
    7. Henrik Jensen & Ivan Petrella & Søren Hove Ravn & Emiliano Santoro, 2020. "Leverage and Deepening Business-Cycle Skewness," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 245-281, January.
    8. Michael W. McCracken & Serena Ng, 2021. "FRED-QD: A Quarterly Database for Macroeconomic Research," Review, Federal Reserve Bank of St. Louis, vol. 103(1), pages 1-44, January.
    9. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    10. Nicholas Bloom & Fatih Guvenen & Sergio Salgado, 2016. "Skewed Business Cycles," 2016 Meeting Papers 1621, Society for Economic Dynamics.
    11. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    12. Riccardo Colacito & Eric Ghysels & Jinghan Meng & Wasin Siwasarit, 2016. "Skewness in Expected Macro Fundamentals and the Predictability of Equity Returns: Evidence and Theory," Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2069-2109.
    13. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
    14. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    15. George-Marios Angeletos & Fabrice Collard & Harris Dellas, 2020. "Business-Cycle Anatomy," American Economic Review, American Economic Association, vol. 110(10), pages 3030-3070, October.
    16. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2013. "Pricing the term structure with linear regressions," Journal of Financial Economics, Elsevier, vol. 110(1), pages 110-138.
    17. James Morley & Jeremy Piger, 2012. "The Asymmetric Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 208-221, February.
    18. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    19. Marek Jarociński & Peter Karadi, 2020. "Deconstructing Monetary Policy Surprises—The Role of Information Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(2), pages 1-43, April.
    20. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    21. Mumtaz, Haroon & Theodoridis, Konstantinos, 2020. "Dynamic effects of monetary policy shocks on macroeconomic volatility," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 262-282.
    22. 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.
    23. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    24. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    25. Gorodnichenko, Yuriy & Ng, Serena, 2017. "Level and volatility factors in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 91(C), pages 52-68.
    26. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    27. Jesús Fernández‐Villaverde & Oren Levintal, 2018. "Solution methods for models with rare disasters," Quantitative Economics, Econometric Society, vol. 9(2), pages 903-944, July.
    28. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    29. Stefano Giglio & Matteo Maggiori & Johannes Stroebel & Stephen Utkus, 2021. "The joint dynamics of investor beliefs and trading during the COVID-19 crash," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(4), pages 2010316118-, January.
    30. Veldkamp, Laura L., 2005. "Slow boom, sudden crash," Journal of Economic Theory, Elsevier, vol. 124(2), pages 230-257, October.
    31. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    32. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    33. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2020. "Disasters Everywhere: The Costs of Business Cycles Reconsidered," Staff Reports 925, Federal Reserve Bank of New York.
    34. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    35. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    36. Xavier Gabaix, 2008. "Variable Rare Disasters: A Tractable Theory of Ten Puzzles in Macro-finance," American Economic Review, American Economic Association, vol. 98(2), pages 64-67, May.
    37. Nicolas Petrosky-Nadeau & Lu Zhang & Lars-Alexander Kuehn, 2018. "Endogenous Disasters," American Economic Review, American Economic Association, vol. 108(8), pages 2212-2245, August.
    38. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    39. Del Negro, Marco & Hasegawa, Raiden B. & Schorfheide, Frank, 2016. "Dynamic prediction pools: An investigation of financial frictions and forecasting performance," Journal of Econometrics, Elsevier, vol. 192(2), pages 391-405.
    40. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    41. Christopher Busch & David Domeij & Fatih Guvenen & Rocio Madera, 2018. "Asymmetric Business-Cycle Risk and Social Insurance," NBER Working Papers 24569, National Bureau of Economic Research, Inc.
    42. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    43. Robert J. Barro, 2009. "Rare Disasters, Asset Prices, and Welfare Costs," American Economic Review, American Economic Association, vol. 99(1), pages 243-264, March.
    44. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
    45. Veldkamp, Laura & Orlik, Anna, 2014. "Understanding Uncertainty Shocks and the Role of Black Swans," CEPR Discussion Papers 10147, C.E.P.R. Discussion Papers.
    46. Guillermo Ordoñez, 2013. "The Asymmetric Effects of Financial Frictions," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 844-895.
    47. Fève, Patrick & Sanchez, Pablo Garcia & Moura, Alban & Pierrard, Olivier, 2021. "Costly default and skewed business cycles," European Economic Review, Elsevier, vol. 132(C).
    48. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2021. "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 369-410, October.
    49. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    50. Geert Bekaert & Eric Engstrom, 2017. "Asset Return Dynamics under Habits and Bad Environment-Good Environment Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 713-760.
    51. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    52. Robert J. Barro & Jose F. Ursua, 2008. "Macroeconomic Crises since 1870," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 39(1 (Spring), pages 255-350.
    53. Haroon Mumtaz & Francesco Zanetti, 2012. "Neutral Technology Shocks And The Dynamics Of Labor Input: Results From An Agnostic Identification," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(1), pages 235-254, February.
    54. Valerie A. Ramey & Sarah Zubairy, 2018. "Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 850-901.
    55. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
    56. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    57. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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    1. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).

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    More about this item

    Keywords

    Business cycles; downside risk; skewness;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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