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Is Industrial Production Still the Dominant Factor for the US Economy?

Author

Listed:
  • Elena Andreou

    (University of Cyprus - Department of Economics)

  • Patrick Gagliardini

    (University of Lugano and Swiss Finance Institute; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute)

  • Eric Ghysels

    (University of North Carolina Kenan-Flagler Business School; University of North Carolina (UNC) at Chapel Hill - Department of Economics)

  • Mirco Rubin

    (Università della Svizzera Italiana and Swiss Finance Institute)

Abstract

We propose a new class of approximate factor models which enable us to study the full spectrum of quarterly IP sector data combined with annual non-IP sectors of the economy. We derive the large sample properties of the estimators for the new class of factor models involving mixed frequency data. Despite the growth of service sectors, we find that a single common factor explaining 90% of the variability in IP output growth index also explains 60% of total GDP output growth fluctuations. A single low frequency factor unrelated to manufacturing explains 14% of GDP growth. The picture with a structural factor model featuring technological innovations is quite different. IP sectors technology shocks do not play a dominant role.

Suggested Citation

  • Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2016. "Is Industrial Production Still the Dominant Factor for the US Economy?," Swiss Finance Institute Research Paper Series 16-11, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1611
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    Cited by:

    1. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
    2. Constantino Hevia & Ivan Petrella & Martin Sola, 2022. "Bond Risk Premia, Priced Regime Shifts, and Macroeconomic Fundamentals," Working Papers 200, Red Nacional de Investigadores en Economía (RedNIE).
    3. Markus Pelger & Ruoxuan Xiong, 2022. "State-Varying Factor Models of Large Dimensions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1315-1333, June.
    4. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.

    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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