IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/200618.html
   My bibliography  Save this paper

Forecasting the South African Economy with VARs and VECMs

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria)

Abstract

The paper develops a Bayesian Vector Error Correction Model (BVECM) of the South African economy for the period of 1970:1-2000:4 and forecasts GDP, consumption, investment, short-term and long term interest rates, and the CPI. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out-of-sample-forecast accuracy resulting from the BVECM is compared with those generated from the Classical variant of the VAR and VECM and the Bayesian VAR. The BVECM is found to produce the most accurate out of sample forecasts. It also correctly predicts the direction of change in the chosen macroeconomic indicators.

Suggested Citation

  • Rangan Gupta, 2006. "Forecasting the South African Economy with VARs and VECMs," Working Papers 200618, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:200618
    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. Marwan Chacra & Maral Kichian, 2004. "A Forecasting Model for Inventory Investments in Canada," Staff Working Papers 04-39, Bank of Canada.
    2. Pami Dua & Anirvan Banerji & Stephen M. Miller, 2006. "Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 415-437.
    3. Hossain Amirizadeh & Richard M. Todd, 1984. "More growth ahead for Ninth District states," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    4. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    5. William C. Gruben & William T. Long, 1988. "The New Mexico economy: outlook for 1989," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Nov, pages 21-36.
    6. David A. Dickey & Dennis W. Jansen & Daniel L. Thornton, 1994. "A Primer on Cointegration with an Application to Money and Income," Palgrave Macmillan Books, in: B. Bhaskara Rao (ed.), Cointegration, chapter 2, pages 9-45, Palgrave Macmillan.
    7. William C. Gruben & William T. Long, 1988. "Forecasting the Texas economy: applications and evaluation of a systematic multivariate time series model," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Jan, pages 11-28.
    8. James J. Balazsy & James G. Hoehn, 1985. "The Ohio economy: a time series analysis," Economic Review, Federal Reserve Bank of Cleveland, issue Q III, pages 25-36.
    9. H. Smith & J.n. Blignaut & J.h. Van Heerden, 2006. "An Analysis Of Inventory Investment In South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 74(1), pages 6-19, March.
    10. William C. Gruben & Donald W. Hayes, 1991. "Forecasting the Louisiana economy," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Mar, pages 1-16.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 763-782, June.
    2. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    3. Eric Schaling & Guangling Dave Liu & Rangan Gupta, 2007. "Forecasting the South African Economy: A DSGE-VAR Approach," Working Papers 051, Economic Research Southern Africa.
    4. Guangling 'Dave' Liu & Rangan Gupta & Eric Schaling, 2009. "A New-Keynesian DSGE model for forecasting the South African economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 387-404.
    5. repec:ipg:wpaper:2014-471 is not listed on IDEAS
    6. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods Of Forecasting House Prices In Six Metropolitan Areas Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 298-313, June.
    7. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    8. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working papers 2009-13, University of Connecticut, Department of Economics.
    9. Rangan Gupta & Stephen Miller, 2012. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 339-361, April.
    10. Annari De Waal & Rene頖an Eyden & Rangan Gupta, 2015. "Do we need a global VAR model to forecast inflation and output in South Africa?," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2649-2670, May.
    11. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00511979, HAL.
    12. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, March.
    13. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.
    14. Patrick T. Kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2016. "Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2412-2427, June.
    15. Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, vol. 28(3), pages 891-899, May.
    16. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    17. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," PSE-Ecole d'économie de Paris (Postprint) halshs-00511979, HAL.
    18. Rangan Gupta & Alain Kabundi, 2010. "Forecasting macroeconomic variables in a small open economy: a comparison between small- and large-scale models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 168-185.
    19. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00505165, HAL.

    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. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, March.
    2. Rangan Gupta & Moses M. Sichei, 2006. "A Bvar Model For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 74(3), pages 391-409, September.
    3. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    4. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2013. "Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes," Empirical Economics, Springer, vol. 44(2), pages 387-417, April.
    5. repec:emu:wpaper:dp15-01.pdf is not listed on IDEAS
    6. Levent, Korap, 2007. "Modeling purchasing power parity using co-integration: evidence from Turkey," MPRA Paper 19584, University Library of Munich, Germany.
    7. Levent KORAP, 2008. "Exchange Rate Determination Of Tl/Us$:A Co-Integration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 7(1), pages 24-50, May.
    8. Ali Darrat & Fatima Al-Shamsi, 2005. "On the path of integration in the Gulf region," Applied Economics, Taylor & Francis Journals, vol. 37(9), pages 1055-1062.
    9. Shu‐Hen Chiang, 2012. "The Source of Metropolitan Growth: The Role of Commuting," Growth and Change, Wiley Blackwell, vol. 43(1), pages 143-166, March.
    10. Darrat, Ali F. & Al-Sowaidi, Saif S., 2009. "Financial progress and the stability of long-run money demand: Implications for the conduct of monetary policy in emerging economies," Review of Financial Economics, Elsevier, vol. 18(3), pages 124-131, August.
    11. Korap, Levent, 2011. "A closer look at the money multipliers for the Turkish economy: Is there a stable relationship?," MPRA Paper 40778, University Library of Munich, Germany.
    12. Varshavsky, Alexander, 2009. "Questionable Innovations in Data Processing with Incomplete Information about the Analyzed System in Absence of Applications Limitations," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 16(4), pages 116-133.
    13. Rangan Gupta & Stephen Miller, 2012. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 339-361, April.
    14. Levent, Korap, 2007. "Testing causal relationships between energy consumption, real income and prices: evidence from Turkey," MPRA Paper 21834, University Library of Munich, Germany.
    15. Rangan Gupta, 2007. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH GIBBS SAMPLED BVECMs," South African Journal of Economics, Economic Society of South Africa, vol. 75(4), pages 631-643, December.
    16. BOONE, Christophe & BROUWER, Aleid & JACOBS, Jan & VAN WITTELOOSTUIJN, Arjen, 2009. "Religious pluralism and organizational diversity: An empirical test for the city of Zwolle, the Netherlands, 1851-1914," ACED Working Papers 2009002, University of Antwerp, Faculty of Business and Economics.
    17. Zou, Gaolu & Chau, K.W., 2006. "Short- and long-run effects between oil consumption and economic growth in China," Energy Policy, Elsevier, vol. 34(18), pages 3644-3655, December.
    18. David Gray, 2004. "Persistent Regional Unemployment Differentials Revisited," Regional Studies, Taylor & Francis Journals, vol. 38(2), pages 167-176.
    19. Tronzano, Marco, 2018. "Does the Expectations Hypothesis of the Term Structure Hold in Korea after the Asian Financial Crisis? Some Empirical Evidence (1999-2017)," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 191-226.
    20. Ali F. Darrat & Saif S. Al‐Sowaidi, 2009. "Financial progress and the stability of long‐run money demand: Implications for the conduct of monetary policy in emerging economies," Review of Financial Economics, John Wiley & Sons, vol. 18(3), pages 124-131, August.
    21. Mohammad Afzal & Ijaz Hussain, 2010. "Export-Led Growth Hypothesis: Evidence from Pakistan," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 130-147, January.

    More about this item

    Keywords

    VECM and BVECM; VAR and BVAR Model; Forecast Accuracy; BVECM;
    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
    • 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:200618. 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.