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Forecasting U.S. Recessions Using Over 150 Years of Data: Stock-Market Moments versus Oil-Market Moments

Author

Listed:
  • Elie Bouri

    (Adnan Kassar School of Business, Lebanese American University, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany.)

  • Onur Polat

    (Department of Public Finance, Bilecik Seyh Edebali University, Bilecik, Turkiye)

Abstract

Using monthly data from 1871 to 2024 and logistic models with shrinkage estimators, we compare the contribution of stock and oil-market moments (returns, volatility, skewness, and kurtosis) to the accuracy of out-of-sample forecasts of U.S. recessions at various forecast horizons, while controling for various standard macroeconomic predictors and the total connectedness indexes of the moments. Adding stock-market moments to the potential predictors improves significantly the accuracy of out-of-sample forecasts at the long forecast horizon, whereas oil-market moments and connectedness indexes do not contribute much. The lagged recession dummy, the term spread, and stock returns are found to be the top predictors of recessions.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Christian Pierdzioch & Onur Polat, 2024. "Forecasting U.S. Recessions Using Over 150 Years of Data: Stock-Market Moments versus Oil-Market Moments," Working Papers 202435, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202435
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    References listed on IDEAS

    as
    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. Balcilar, Mehmet & Gupta, Rangan & Wohar, Mark E., 2017. "Common cycles and common trends in the stock and oil markets: Evidence from more than 150years of data," Energy Economics, Elsevier, vol. 61(C), pages 72-86.
    3. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    4. Francis X. 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.
    5. Pablo Burriel & Iván Kataryniuk & Carlos Moreno Pérez & Francesca Viani, 2024. "A New Supply Bottlenecks Index Based on Newspaper Data," International Journal of Central Banking, International Journal of Central Banking, vol. 20(2), pages 17-67, April.
    6. Darwin Choi & Zhenyu Gao & Wenxi Jiang, 2020. "Attention to Global Warming," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1112-1145.
    7. Lutz Kilian & Robert J. Vigfusson, 2017. "The Role of Oil Price Shocks in Causing U.S. Recessions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1747-1776, December.
    8. Huang, Yu-Fan & Startz, Richard, 2020. "Improved recession dating using stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 507-514.
    9. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    10. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    11. 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.
    12. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2021. "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 369-410, October.
    13. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    14. Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
    15. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    16. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2017. "Do leading indicators forecast U.S. recessions? A nonlinear re†evaluation using historical data," International Finance, Wiley Blackwell, vol. 20(3), pages 289-316, December.
    17. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).
    18. Bouri, Elie & Lei, Xiaojie & Jalkh, Naji & Xu, Yahua & Zhang, Hongwei, 2021. "Spillovers in higher moments and jumps across US stock and strategic commodity markets," Resources Policy, Elsevier, vol. 72(C).
    19. Kurov, Alexander & Olson, Eric & Zaynutdinova, Gulnara R., 2022. "When does the fed care about stock prices?," Journal of Banking & Finance, Elsevier, vol. 142(C).
    20. Gupta, Rangan & Pierdzioch, Christian & Salisu, Afees A., 2022. "Oil-price uncertainty and the U.K. unemployment rate: A forecasting experiment with random forests using 150 years of data," Resources Policy, Elsevier, vol. 77(C).
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    More about this item

    Keywords

    Recessions; Stock-market and oil-market moments; Forecasting; Shrinkage estimators; AUC statistics;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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