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

Author

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  • Andreou, Elena
  • Gagliardini, Patrick
  • Ghysels, Eric
  • Rubin, Mirco

Abstract

We propose a new class of large approximate factor models which enable us to study the full spectrum of quarterly Industrial Production (IP) sector data combined with annual non-IP sectors of the economy. We derive the large sample properties of the estimators and test statistics for the new class of unobservable factor models involving mixed frequency data and common as well as frequency-specific factors. 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. Last but not least, our identification and inference methodology rely on novel results on group factor models that are of general interest beyond the mixed frequency framework and the application of the paper.

Suggested Citation

  • Andreou, Elena & Gagliardini, Patrick & Ghysels, Eric & Rubin, Mirco, 2017. "Is Industrial Production Still the Dominant Factor for the US Economy?," CEPR Discussion Papers 12219, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:12219
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    References listed on IDEAS

    as
    1. Thomas Piketty & Emmanuel Saez & Gabriel Zucman, 2016. "Distributional National Accounts: Methods and Estimates for the United States," NBER Working Papers 22945, National Bureau of Economic Research, Inc.
    2. Bertrand Garbinti & Jonathan Goupille-Lebret & Thomas Piketty, 2017. "Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France (1800-2014)," Working Papers 201605, World Inequality Lab.
    3. Wojciech Kopczuk, 2014. "What Do We Know About Evolution of Top Wealth Shares in the United States?," NBER Working Papers 20734, National Bureau of Economic Research, Inc.
    4. Rochelle L. Antoniewicz, 1996. "A comparison of the household sector from the Flow of Funds Accounts and the Survey of Consumer Finances," Finance and Economics Discussion Series 96-26, Board of Governors of the Federal Reserve System (U.S.).
    5. Kaymak, Barış & Poschke, Markus, 2016. "The evolution of wealth inequality over half a century: The role of taxes, transfers and technology," Journal of Monetary Economics, Elsevier, vol. 77(C), pages 1-25.
    6. Wojciech Kopczuk, 2015. "What Do We Know about the Evolution of Top Wealth Shares in the United States?," Journal of Economic Perspectives, American Economic Association, vol. 29(1), pages 47-66, Winter.
    7. Wojciech Kopczuk & Emmanuel Saez & Jae Song, 2010. "Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937," The Quarterly Journal of Economics, Oxford University Press, vol. 125(1), pages 91-128.
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    More about this item

    Keywords

    GDP growth; Group Factor models; MIDAS;

    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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