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On the role of domestic and international financial cyclical factors in driving economic growth

Author

Listed:
  • M. Billio
  • M. Donadelli
  • G. Livieri
  • A. Paradiso

Abstract

We investigate the effects of (domestic and international) financial cyclical factors on the US business cycle over the period 1890–2013 using an augmented stochastic version of the neoclassical growth model. In our setting, financial factors enter as determinants of the total factor productivity cyclical pattern. By means of static and dynamic estimations we find that (i) the inclusion of financial cyclical factors improves the model’s performance; (ii) the sensitivity of economic growth to financial factors is time-varying; (iii) domestic financial factors have a key role in explaining short-run output fluctuations only in the first half of the 20th century; (iv) US business cycle fluctuations have been mainly driven by global financial factors (i.e., financial integration) over the last three decades.JEL CODES: O40, E32, C32

Suggested Citation

  • M. Billio & M. Donadelli & G. Livieri & A. Paradiso, 2020. "On the role of domestic and international financial cyclical factors in driving economic growth," Applied Economics, Taylor & Francis Journals, vol. 52(11), pages 1272-1297, March.
    • Handle: RePEc:taf:applec:v:52:y:2020:i:11:p:1272-1297
    DOI: 10.1080/00036846.2019.1659934
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    Cited by:

    1. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).

    More about this item

    JEL classification:

    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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