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The Role of Credit in Predicting US Recessions

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  • Harri Ponka

Abstract

We study the role of credit in forecasting US recession periods with probit models. We employ both classical recession predictors and common factors based on a large panel of financial and macroeconomic variables as control variables. Our findings suggest that a number of credit variables are useful predictors of US recessions over and above the control variables both in and out of sample. Especially the excess bond premium, capturing the cyclical changes in the relationship between default risk and credit spreads, is found to be a powerful predictor. Overall, models that combine credit variables, common factors, and classic recession predictors, are found to have the best forecasting performance.
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  • Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.
    • Handle: RePEc:wly:jforec:v:36:y:2017:i:5:p:469-482
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    Cited by:

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    3. Claudio Borio & Mathias Drehmann & Dora Xia, 2018. "The financial cycle and recession risk," BIS Quarterly Review, Bank for International Settlements, December.
    4. Ihejirika, Peters. O, 2020. "Does the Credit-to-GDP Gap Predict Financial Crisis in Nigeria?," International Journal of Social and Administrative Sciences, Asian Economic and Social Society, vol. 5(2), pages 109-126, June.
    5. Marius M. Mihai, 2020. "Do credit booms predict US recessions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 887-910, September.
    6. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    7. Hwang, Youngjin, 2019. "Forecasting recessions with time-varying models," Journal of Macroeconomics, Elsevier, vol. 62(C).
    8. Morana, Claudio, 2024. "A new macro-financial condition index for the euro area," Econometrics and Statistics, Elsevier, vol. 29(C), pages 64-87.
    9. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    10. Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
    11. Borio, Claudio & Drehmann, Mathias & Xia, Fan Dora, 2020. "Forecasting recessions: the importance of the financial cycle," Journal of Macroeconomics, Elsevier, vol. 66(C).
    12. Claudio Borio & Mathias Drehmann & Dora Xia Author-X-Name_First: Dora, 2019. "Predicting recessions: financial cycle versus term spread," BIS Working Papers 818, Bank for International Settlements.
    13. Guender, Alfred V, 2018. "Credit prices vs. credit quantities as predictors of economic activity in Europe: Which tell a better story?," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 380-399.
    14. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
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    17. Anastasios Evgenidis & Anastasios G. Malliaris, 2022. "Monetary policy, financial shocks and economic activity," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 429-456, August.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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