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Forecasting Output Growth using a DSGE-Based Decomposition of the South African Yield Curve

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Hylton Hollander

    (African Institute of Financial Markets & Risk Management, Faculty of Commerce, University of Cape Town, South Africa)

  • Rudi Steinbach

    (Economic Research and Statistics Department, South African Reserve Bank)

Abstract

Evidence in favor of the ability of the term spread to forecast economic growth of the South African economy is non-existent. Presuming that this could be due to the term spread aggregating, and hence loosing out on important, information contained in the expected spread and the term premium, we: (i) Develop an estimable Small Open Economy New Keynesian Dynamic Stochastic General Equilibrium (SOENKDSGE) model of the in ation targeting South African economy; (ii) Use the SOENKDSGE model, estimated using Bayesian methods, to decompose the term spread into an expected spread and the term premium over the quarterly period of 2000:01-2014:04, and; (iii) Use a linear predictive regression framework to analyze the out-of-sample forecasting ability of the aggregate term spread, as well as the expected spread and term premium. Our forecasting results fail to detect forecasting gains from the aggregate term spread and also the term premium, but the expected spread is found to contain important information in forecasting the output growth over short- to medium-run horizons, over the out-of-sample period of 2004:01-2014:04. In other words, we confirm our presumption, and in the process highlight the importance of the forward looking component of the term spread, i.e., the expected spread, in forecasting output growth of South Africa.

Suggested Citation

  • Rangan Gupta & Hylton Hollander & Rudi Steinbach, 2015. "Forecasting Output Growth using a DSGE-Based Decomposition of the South African Yield Curve," Working Papers 201567, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201567
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    Cited by:

    1. 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.
    2. Goodness C. Aye & Christina Christou & Luis A. Gil‐Alana & Rangan Gupta, 2019. "Forecasting the Probability of Recessions in South Africa: the Role of Decomposed Term Spread and Economic Policy Uncertainty," Journal of International Development, John Wiley & Sons, Ltd., vol. 31(1), pages 101-116, January.
    3. Ronald Ravinesh Kumar & Peter Josef Stauvermann & Hang Thi Thu Vu, 2021. "The Relationship between Yield Curve and Economic Activity: An Analysis of G7 Countries," JRFM, MDPI, vol. 14(2), pages 1-23, February.

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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