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Forecasting the Probability of Recessions in South Africa: The Role of Decomposed Term-Spread and Economic Policy Uncertainty

Author

Listed:
  • Goodness C. Aye

    (Department of Economics, University of Pretoria, South Africa)

  • Christina Christou

    (School of Economics and Management, Open University of Cyprus, Cyprus)

  • Luis A. Gil-Alana

    (Universidad de Navarra, Faculty of Economics and Business Administration, Spain)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, South Africa)

Abstract

This paper extends the vast literature forecasting the probability of recession by including the different components of the term spread, namely the expectation and the term premium components obtained from a fractional integration approach. We also augment these with the economic policy uncertainty index. We use 10 specifications of the probit prediction model and quarterly data from South Africa covering the period 1990:1 to 2012:1 for analyses. Our out-of-sample results show that the model that incorporates the expectation component of the yield spread in addition to economic policy uncertainty provides the best forecast of recession in South Africa. All three recession periods in our sample were accurately dictated by the prediction models and the best forecast occurred at the four quarters ahead horizon. These results were also robust to the full sample prediction

Suggested Citation

  • Goodness C. Aye & Christina Christou & Luis A. Gil-Alana & Rangan Gupta, 2016. "Forecasting the Probability of Recessions in South Africa: The Role of Decomposed Term-Spread and Economic Policy Uncertainty," Working Papers 201680, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201680
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    1. Fabio Moneta, 2005. "Does the Yield Spread Predict Recessions in the Euro Area?," International Finance, Wiley Blackwell, vol. 8(2), pages 263-301, August.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    4. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
    5. Pauwels, Laurent & Vasnev, Andrey, 2014. "Forecast combination for U.S. recessions with real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 138-148.
    6. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
    7. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Keith Kuester & Juan Rubio-Ramírez, 2015. "Fiscal Volatility Shocks and Economic Activity," American Economic Review, American Economic Association, vol. 105(11), pages 3352-3384, November.
    8. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    9. Dionisios Chionis & Periklis Gogas & Ioannis Pragidis, 2010. "Predicting European Union Recessions in the Euro Era: The Yield Curve as a Forecasting Tool of Economic Activity," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 16(1), pages 1-10, February.
    10. Melvin Muzi Khomo & Meshach Jesse Aziakpono, 2007. "Forecasting Recession In South Africa: A Comparison Of The Yield Curve And Other Economic Indicators," South African Journal of Economics, Economic Society of South Africa, vol. 75(2), pages 194-212, June.
    11. Born, Benjamin & Pfeifer, Johannes, 2014. "Policy risk and the business cycle," Journal of Monetary Economics, Elsevier, vol. 68(C), pages 68-85.
    12. Reuben A. Kessel, 1965. "The Cyclical Behavior of the Term Structure of Interest Rates," NBER Books, National Bureau of Economic Research, Inc, number kess65-1.
    13. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    14. Ann M. Dombrosky & Joseph G. Haubrich, 1996. "Predicting real growth using the yield curve," Economic Review, Federal Reserve Bank of Cleveland, issue Q I, pages 26-35.
    15. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    16. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    17. Steven J. Davis, 2016. "An Index of Global Economic Policy Uncertainty," NBER Working Papers 22740, National Bureau of Economic Research, Inc.
    18. repec:kap:iaecre:v:16:y:2010:i:1:p:1-10 is not listed on IDEAS
    19. Ferdi Botha & Gavin Keeton, 2014. "A Note on the (Continued) Ability of the Yield Curve to Forecast Economic Downturns in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 468-473, September.
    20. Gil-Alana, Luis A. & Moreno, Antonio, 2012. "Uncovering the US term premium: An alternative route," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1181-1193.
    21. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    22. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.
    23. Jonathan Brogaard & Andrew Detzel, 2015. "The Asset-Pricing Implications of Government Economic Policy Uncertainty," Management Science, INFORMS, vol. 61(1), pages 3-18, January.
    24. Oral Erdogan & Paul Bennett & Cenktan Ozyildirim, 2015. "Recession Prediction Using Yield Curve and Stock Market Liquidity Deviation Measures," Review of Finance, European Finance Association, vol. 19(1), pages 407-422.
    25. Arturo Estrella & Frederic S. Mishkin, 1996. "The yield curve as a predictor of U.S. recessions," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 2(Jun).
    26. Henri Nyberg, 2010. "Dynamic probit models and financial variables in recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 215-230.
    27. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2020. "The Effectiveness Of Monetary Policy In South Africa Under Inflation Targeting: Evidence from a Time-Varying Factor-Augmented Vector Autoregressive Model," Journal of Developing Areas, Tennessee State University, College of Business, vol. 54(4), pages 55-73, October-D.
    28. Nyberg, Henri, 2014. "A Bivariate Autoregressive Probit Model: Business Cycle Linkages And Transmission Of Recession Probabilities," Macroeconomic Dynamics, Cambridge University Press, vol. 18(4), pages 838-862, June.
    29. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    30. Karnizova, Lilia & Li, Jiaxiong (Chris), 2014. "Economic policy uncertainty, financial markets and probability of US recessions," Economics Letters, Elsevier, vol. 125(2), pages 261-265.
    31. Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2020. "Forecasting output growth using a DSGE-based decomposition of the South African yield curve," Empirical Economics, Springer, vol. 58(1), pages 351-378, January.
    32. Ratcliff, Ryan, 2013. "The “probability of recession”: Evaluating probabilistic and non-probabilistic forecasts from probit models of U.S. recessions," Economics Letters, Elsevier, vol. 121(2), pages 311-315.
    33. Chatterjee, Ujjal K., 2016. "Do stock market trading activities forecast recessions?," Economic Modelling, Elsevier, vol. 59(C), pages 370-386.
    34. Mathias Moersch & Armin Pohl, 2011. "Predicting recessions with the term spread - recent evidence from seven countries," Applied Economics Letters, Taylor & Francis Journals, vol. 18(13), pages 1285-1288.
    35. Masashi Hasegawa & Yuichi Fukuta, 2011. "An empirical analysis of information in the yield spread on future recessions in Japan," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1865-1881.
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    Cited by:

    1. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
    2. João Frois Caldeira & Rangan Gupta & Muhammad Tahir Suleman & Hudson S. Torrent, 2021. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4312-4329, December.
    3. Johannes W. Fedderke, 2020. "Is the Phillips curve framework still useful for understanding inflation dynamics in South Africa," Working Papers 10142, South African Reserve Bank.
    4. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    5. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    6. Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
    7. 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).
    8. Yizheng Fu & Zhifang Su & Aihua Lin, 2024. "Functional Cointegration Test for Expectation Hypothesis of the Term Structure of Interest Rates in China," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 799-820, December.

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    More about this item

    Keywords

    Expected term spread; term premium; economic policy uncertainty; recession; out-of-sample forecast; Probit model;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory

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