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Analyzing business cycle asymmetries in a multi-level factor model

Author

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  • Breitung, Jörg
  • Eickmeier, Sandra

Abstract

We study the business cycle in the US over 1959–2011 using a large-dimensional multi-level factor model. We find notable asymmetries over the business cycle, but the bulk of common dynamics is stable over time. The comovement among variables is larger in recessions compared to expansions. The recession factor is highly correlated with monetary and financial variables, whereas expansion and symmetric factors are mainly related to real activity variables.

Suggested Citation

  • Breitung, Jörg & Eickmeier, Sandra, 2015. "Analyzing business cycle asymmetries in a multi-level factor model," Economics Letters, Elsevier, vol. 127(C), pages 31-34.
  • Handle: RePEc:eee:ecolet:v:127:y:2015:i:c:p:31-34
    DOI: 10.1016/j.econlet.2014.12.001
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    References listed on IDEAS

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    2. Caporin, Massimiliano & Pelizzon, Loriana & Plazzi, Alberto, 2020. "Does monetary policy impact international market co-movements?," SAFE Working Paper Series 276, Leibniz Institute for Financial Research SAFE.
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    4. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    5. Mohammadi, H. & Abolhasani, L. & Shahnoushi, N. & Shabanian, F., 2018. "The effects of business cycle indicators on stock market indices of food industry in Iran," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277425, International Association of Agricultural Economists.
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    7. Carlomagno Real, Guillermo & Espasa, Antoni, 2017. "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS 25392, Universidad Carlos III de Madrid. Departamento de Estadística.

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    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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