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Credit Indicators as Predictors of Economic Activity: A Real‐Time VAR Analysis

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  • N. KUNDAN KISHOR
  • EVAN F. KOENIG

Abstract

Using readily available indicators of the profitability, price, and availability of credit—the term spread, junk‐bond spread, and banks’ “willingness to lend” as reported by the Federal Reserve—we show that it is possible to significantly improve on the real‐time output and employment predictions of forecasting professionals at the medium‐run horizons that are most relevant to policymakers and private decision makers. Key to this improvement is a flexible state–space model of data revisions. The willingness‐to‐lend variable is the best real‐time predictor of GDP growth. For forecasting job growth, all three credit indicators prove helpful.

Suggested Citation

  • N. Kundan Kishor & Evan F. Koenig, 2014. "Credit Indicators as Predictors of Economic Activity: A Real‐Time VAR Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(2-3), pages 545-564, March.
    • Handle: RePEc:wly:jmoncb:v:46:y:2014:i:2-3:p:545-564
    DOI: 10.1111/jmcb.12116
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    References listed on IDEAS

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    Cited by:

    1. Alan Armen & Evan F. Koenig, 2015. "Assessing monetary accommodation: a simple empirical model of monetary policy and its implications for unemployment and inflation," Staff Papers, Federal Reserve Bank of Dallas, issue Dec.
    2. Seitz, Franz & Baumann, Ursel & Albuquerque, Bruno, 2015. "The information content of money and credit for US activity," Working Paper Series 1803, European Central Bank.
    3. Kishor, N. Kundan, 2023. "Forecasting House Prices: The Role of Fundamentals, Credit Conditions, and Supply Indicators," MPRA Paper 116819, University Library of Munich, Germany.
    4. João Pedro Pereira & António Rua, 2018. "Asset Pricing with a Bank Risk Factor," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 993-1032, August.
    5. Michelle L. Barnes & Giovanni P. Olivei, 2017. "Consumer Attitudes and Their Forecasting Power for Consumer Spending," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 1031-1058, August.
    6. Kurowski, Łukasz & Rogowicz, Karol, 2018. "Are business and credit cycles synchronised internally or externally?," Economic Modelling, Elsevier, vol. 74(C), pages 124-141.
    7. N. Kundan Kishor & Evan F. Koenig, 2016. "The roles of inflation expectations, core inflation, and slack in real-time inflation forecasting," Working Papers 1613, Federal Reserve Bank of Dallas.
    8. repec:ecb:ecbwps:20141803 is not listed on IDEAS
    9. Narayan Kundan Kishor, 2021. "Forecasting real‐time economic activity using house prices and credit conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 213-227, March.
    10. Albuquerque, Bruno & Baumann, Ursel & Seitz, Franz, 2016. "What does money and credit tell us about real activity in the United States?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 328-347.

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