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Asymmetric Phase Shifts in the U.S. Industrial Production Cycles

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Abstract

We identify the cyclical turning points of 74 U.S. manufacturing industries and uncover new empirical regularities: (i) Cyclical phase shifts are highly concentrated around the aggregate turning points; (ii) In contrast to the conventional notion of a sudden stop and slow recovery, troughs are much more concentrated than peaks; (iii) Occurrences of phase shifts across industries support the spillovers through input-output linkages; (iv) The common macroeconomic shocks, such as exogenous changes in the federal funds rate, government spending, and oil prices, are significant drivers of industrial phase shifts; (v) Both monetary and fiscal policy shocks are more effective in recessions.

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  • Yongsung Chang & Sunoong Hwang, 2011. "Asymmetric Phase Shifts in the U.S. Industrial Production Cycles," RCER Working Papers 564, University of Rochester - Center for Economic Research (RCER).
    • Handle: RePEc:roc:rocher:564
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    Cited by:

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    2. Sumru Altug & Fabio Canova, 2014. "Do Institutions and Culture Matter for Business Cycles?," Open Economies Review, Springer, vol. 25(1), pages 93-122, February.
    3. Steven Cassou & Jesús Vázquez, 2014. "Employment comovements at the sectoral level over the business cycle," Empirical Economics, Springer, vol. 46(4), pages 1301-1323, June.
    4. Hyun, Junghwan, 2018. "The dynamics of credit reallocation: South Korea's post-crisis experience," Japan and the World Economy, Elsevier, vol. 48(C), pages 57-70.
    5. Ritabrata Bose & Ashima Goyal, 2020. "Disaggregated Indian industrial cycles: A Spectral analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-033, Indira Gandhi Institute of Development Research, Mumbai, India.
    6. Palenzuela, Diego Rodriguez & Saiz, Lorena & Stoevsky, Grigor & Tóth, Máté & Warmedinger, Thomas & Grigoraș, Veaceslav, 2024. "The euro area business cycle and its drivers," Occasional Paper Series 354, European Central Bank.
    7. Donayre Luiggi & Eo Yunjong & Morley James, 2018. "Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-11, February.
    8. Guisinger, Amy Y. & Owyang, Michael T. & Soques, Daniel, 2024. "Industrial Connectedness and Business Cycle Comovements," Econometrics and Statistics, Elsevier, vol. 29(C), pages 132-149.
    9. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.

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    More about this item

    Keywords

    Business cycles; Comovement; Turning points; Asymmetries;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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