IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/200621.html
   My bibliography  Save this paper

A Small-Scale DSGE Model for Forecasting the South African Economy

Author

Listed:
  • Guangling (Dave) Liu

    (Department of Economics, University of Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

Abstract

This paper uses a version of Hansen’s (1985) Dynamic Stochastic General Equilibrium (DSGE) model to forecast the South African economy. The calibrated model, based on annual data over the period of 1970-2000, is used to generate one- to eight-quarters-ahead out-of-sample forecast errors for the period of 2001:1 to 2005:4. The forecast errors are then compared with the unrestricted versions of the Classical and Bayesian VARs. A Bayesian VAR with relatively loose priors outperforms both the classical VAR and the DSGE model.

Suggested Citation

  • Guangling (Dave) Liu & Rangan Gupta, 2006. "A Small-Scale DSGE Model for Forecasting the South African Economy," Working Papers 200621, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:200621
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ben Smit & Le Roux Burrows, 2002. "Estimating potential output and output gaps for the South African economy," Working Papers 05/2002, Stellenbosch University, Department of Economics.
    2. Christian Zimmermann, 2001. "Forecasting with Real Business Cycle Models," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 36(1), pages 189-203, January.
    3. Uhlig, H.F.H.V.S., 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper 1995-97, Tilburg University, Center for Economic Research.
    4. Frank Smets & Raf Wouters, 2004. "Forecasting with a Bayesian DSGE Model: An Application to the Euro Area," Journal of Common Market Studies, Wiley Blackwell, vol. 42(4), pages 841-867, November.
    5. Uhlig, H.F.H.V.S., 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Other publications TiSEM cc1b2469-9d2f-445a-a2b3-1, Tilburg University, School of Economics and Management.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zimmermann, Tobias, 2007. "Reale Konjunkturzyklen, Effizienzlöhne und die Rolle von Ölpreisschocks: Eine theoretische und empirische Analyse für Deutschland," RWI Schriften, RWI - Leibniz-Institut für Wirtschaftsforschung, volume 81, number 81.
    2. Gonzalo Fernández-de-Córdoba & José Torres, 2011. "Forecasting the Spanish economy with an augmented VAR–DSGE model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(3), pages 379-399, September.
    3. Zhicheng Zhou & Prapatchon Jariyapan, 2013. "The impact of macroeconomic policies to real estate market in People's Republic of China," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 2(3), pages 75-92, September.
    4. Luca Brugnolini & Luisa Corrado, 2018. "Fiscal Compact and Debt Consolidation Dynamics," CEIS Research Paper 436, Tor Vergata University, CEIS, revised 06 Nov 2018.
    5. Jean-Paul L'Huillier & Sanjay R. Singh & Donghoon Yoo, 2021. "Incorporating Diagnostic Expectations into the New Keynesian Framework," Working Papers 339, University of California, Davis, Department of Economics.
    6. Scheffel, Eric, 2008. "A Credit-Banking Explanation of the Equity Premium, Term Premium, and Risk-Free Rate Puzzles," Cardiff Economics Working Papers E2008/30, Cardiff University, Cardiff Business School, Economics Section.
    7. Guerrieri, Luca & Iacoviello, Matteo, 2015. "OccBin: A toolkit for solving dynamic models with occasionally binding constraints easily," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 22-38.
    8. Chung-Fu Lai, 2016. "The Effects of Anti-Dumping Duties in a Fixed Exchange Rate Regime," Applied Economics and Finance, Redfame publishing, vol. 3(3), pages 25-36, August.
    9. Jaromír Hurník & Ondøej Kameník & Jan Vlèek, 2008. "The History of Inflation Targeting in the Czech Republic Through the Lens of a Dynamic General Equilibrium Model," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(09-10), pages 454-469, December.
    10. Wieland, Volker & Cwik, Tobias & Müller, Gernot J. & Schmidt, Sebastian & Wolters, Maik, 2012. "A new comparative approach to macroeconomic modeling and policy analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 523-541.
    11. Fabrice Collard & David de la Croix, 2000. "Gift Exchange and the Business Cycle: The Fair Wage Strikes Back," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(1), pages 166-193, January.
    12. Guanghua Wan & Chen Wang & Hua Yin & Yan Zhang, 2018. "From Equality of Deprivation to Disparity of Prosperity: The Poverty–Growth–Inequality Triangle in Post†reform China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 26(2), pages 50-67, March.
    13. Jim Malley & Anton Muscatelli & Ulrich Woitek, 1999. "Real Business Cycles or Sticky Prices? The Impact of Technology Shocks on US Manufacturing," Working Papers 1999_15, Business School - Economics, University of Glasgow.
    14. Jana Hromcová, 2007. "On Income Velocity of Money, Precautionary Money Demand and Growth," Journal of Economics, Springer, vol. 90(2), pages 143-166, March.
    15. Psaradakis, Zacharias & Vávra, Marián, 2014. "On testing for nonlinearity in multivariate time series," Economics Letters, Elsevier, vol. 125(1), pages 1-4.
    16. Stefan RIED, 2010. "New Keynesian Open Economy Models versus the Six Major Puzzles in International Macroeconomics," EcoMod2004 330600119, EcoMod.
    17. Uhlig, H.F.H.V.S. & Xu, Y., 1996. "Effort and the Cycle : Cyclical Implications of Efficiency Wages," Other publications TiSEM dc793f82-7aaa-4ad9-8af4-2, Tilburg University, School of Economics and Management.
    18. Hsu, Alex & Palomino, Francisco, 2015. "A simple nonnegative process for equilibrium models," Economics Letters, Elsevier, vol. 132(C), pages 39-44.
    19. Charles Olivier Mao Takongmo, 2021. "DSGE models, detrending, and the method of moments," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 67-99, January.
    20. Eijffinger, Sylvester C. W. & Grajales-Olarte, Anderson & Uras, Burak R., 2020. "Heterogeneity In Wage Setting Behavior In A New-Keynesian Model," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1512-1546, September.

    More about this item

    Keywords

    DSGE Model; VAR and BVAR Model; Forecast Accuracy; DSGE Forecasts; VAR Forecasts; BVAR Forecasts;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • 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
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:200621. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.