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Measuring international business cycles by saving for a rainy day

Author

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  • Mario J. Crucini
  • Mototsugu Shintani

Abstract

Macroeconomics inevitably begins with a trend-cycle decomposition of a nation's output. We propose a decomposition in which consumption is the trend component and savings is the cycle component. Using data from the G-7 plus Australia, we show that this decomposition identifies international business cycles that are: (i) more volatile, (ii) of longer mean duration and (iii) less correlated across countries than the cycle component from the Hodrick-Prescott filter. We argue that this difference stems from the fact that our method imposes a basic theoretical restriction arising from the permanent income hypothesis similar to the restriction used in Cochrane's ( ) decomposition.

Suggested Citation

  • Mario J. Crucini & Mototsugu Shintani, 2015. "Measuring international business cycles by saving for a rainy day," Canadian Journal of Economics, Canadian Economics Association, vol. 48(4), pages 1266-1290, November.
    • Handle: RePEc:cje:issued:v:48:y:2015:i:4:p:1266-1290
    DOI: 10.1111/caje.12146
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    Cited by:

    1. Kan Chen & Mario Crucini, 2016. "Trends & Cycles in Small Open Economies:Making the Case for a General Equilibrium Approach," Working Papers 16/12, BBVA Bank, Economic Research Department.
    2. David Amdur & Eylem Ersal Kiziler, 2014. "Trend shocks and the countercyclical U.S. current account," Canadian Journal of Economics, Canadian Economics Association, vol. 47(2), pages 494-516, May.
    3. Martínez-García Enrique, 2018. "Modeling time-variation over the business cycle (1960–2017): an international perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    4. Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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