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Measuring Real-Financial Connectedness in the U.S. Economy

Author

Listed:
  • Erhan Uluceviz

    () (Gebze Technical University)

  • Kamil Yilmaz

    () (Koç University)

Abstract

We analyze connectedness between the real and financial sectors of the U.S. economy. Using the weekly ADS index of the Philadelphia FED (the widely used business conditions indicator) to represent the real side, we find that during times of financial distress and/or business cycle turning points the direction of connectedness runs from the real sector to financial markets. The ADS index is derived from a model containing a measure of term structure along with real variables, therefore, it might not be the best representative of the real activity to be used in the connectedness analysis. As an alternative, we derive a real activity index (RAI) from a dynamic factor model of the real sector variables only. The behavior of RAI over time is quite similar to that of the ADS index. When we include RAI to represent the real side of the economy in the connectedness analysis, the direction of net connectedness reverses: financial markets generate positive net connectedness to the real side of the economy.

Suggested Citation

  • Erhan Uluceviz & Kamil Yilmaz, 2018. "Measuring Real-Financial Connectedness in the U.S. Economy," Koç University-TUSIAD Economic Research Forum Working Papers 1812, Koc University-TUSIAD Economic Research Forum.
    • Handle: RePEc:koc:wpaper:1812
    as

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    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1812.pdf
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Francis X. Diebold & Kamil Yilmaz, 2013. "Measuring the Dynamics of Global Business Cycle Connectedness," PIER Working Paper Archive 13-070, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    3. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.
    4. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    5. Alessandro Barattieri & Maya Eden & Dalibor Stevanovic, 2013. "The Connection between Wall Street and Main Street: Measurement and Implications for Monetary Policy," Cahiers de recherche 1331, CIRPEE.
    6. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    7. Anand, Kartik & Gai, Prasanna & Kapadia, Sujit & Brennan, Simon & Willison, Matthew, 2013. "A network model of financial system resilience," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 219-235.
    8. Zhigu He & Arvind Krishnamurthy, 2012. "A Model of Capital and Crises," Review of Economic Studies, Oxford University Press, vol. 79(2), pages 735-777.
    9. Markose, Sheri & Giansante, Simone & Shaghaghi, Ali Rais, 2012. "‘Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic risk," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 627-646.
    10. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
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    More about this item

    Keywords

    Macro-financial linkages; Connectedness; ADS index; Dynamic factor model; Volatility; Vector autoregression; Variance decomposition.;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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