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Dimensions of macroeconomic uncertainty: A common factor analysis

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  • Steffen Henzel
  • Malte Rengel

Abstract

In the current literature uncertainty about the future course of the economy is identified as a possible driver of business cycle fluctuations. In fact, uncertainty surrounds the movements of all economic variables which gives rise to a monitoring problem. We identify the different dimensions of uncertainty in the macroeconomy. To this end, we construct a large dataset covering all forms of economic uncertainty and unravel the fundamental factors that account for the common dynamics therein. These common factors are interpreted as macroeconomic uncertainty. Our results show that the first factor captures business cycle uncertainty while the second factor is identified as oil and commodity price uncertainty. Finally, we demonstrate that a distinction between both types of macroeconomic uncertainty is essential since they have rather different implications for economic activity.

Suggested Citation

  • Steffen Henzel & Malte Rengel, 2013. "Dimensions of macroeconomic uncertainty: A common factor analysis," ifo Working Paper Series 167, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_167
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    Cited by:

    1. Klaus Wohlrabe & Teresa Buchen, 2014. "Assessing the Macroeconomic Forecasting Performance of Boosting: Evidence for the United States, the Euro Area and Germany," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 231-242, July.
    2. Francesco Trebbi & Eric Weese, 2015. "Insurgency and Small Wars: Estimation of Unobserved Coalition Structures," NBER Working Papers 21202, National Bureau of Economic Research, Inc.
    3. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy: Evidence from an Uncertainty Composite Indicator," Working Papers 2017-25, CEPII research center.
    4. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, Reading University.
    5. repec:gam:jecnmx:v:6:y:2018:i:2:p:23-:d:143630 is not listed on IDEAS
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
    7. Gloria Gonzalez-Rivera & Esther Ruiz & Javier Vicente, 2018. "Growth in Stress," Working Papers 201805, University of California at Riverside, Department of Economics.
    8. repec:kob:wpaper:1628 is not listed on IDEAS
    9. Vicente Maldonado, Javier de & Ruiz Ortega, Esther & González-Rivera, Gloria, 2018. "Growth in Stress," DES - Working Papers. Statistics and Econometrics. WS 26623, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Berg, Tim Oliver, 2016. "Business Uncertainty and the Effectiveness of Fiscal Policy in Germany," MPRA Paper 69162, University Library of Munich, Germany.
    11. repec:taf:jnlbes:v:35:y:2017:i:3:p:420-433 is not listed on IDEAS
    12. Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018. "Forecasting Inflation Uncertainty in the G7 Countries," Econometrics, MDPI, Open Access Journal, vol. 6(2), pages 1-25, April.
    13. Michael P. Clements, 2017. "Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 420-433, July.
    14. Dimitrios Bakas & Athanasios Triantafyllou, 2017. "The Impact of Uncertainty Shocks on the Volatility of Commodity Prices," Working Paper series 17-31, Rimini Centre for Economic Analysis.

    More about this item

    Keywords

    Macroeconomic uncertainty; factor model; factor-augmented VAR; aggregate fluctuation.;

    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
    • 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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