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Estimating potential output and output gaps for the South African economy


  • Ben Smit

    () (Department of Economics and Bureau of Economic Research, Stellenbosch University)

  • Le Roux Burrows

    () (Department of Economics, Stellenbosch University)


An economy's level of potential output plays a central (and critical) role in the formulation of monetary policy focused on maintaining low and stable inflation. Assuming that potential output is determined mainly by the quantity and quality of its productive factors and the level of technology, it follows that potential output is related to the capacity of the economy to supply goods and services. Thus the growth rate of potential output is the rate of growth that the economy can sustain for long periods of time. If the economy grows at a different rate from the potential output, then inflation will tend to adjust in response to demand pressures. In modern macroeconomic theory, one of the key sources of inflationary pressure is the difference between aggregate demand and potential output which can be quantified as the percentage difference between actual output and potential output (or the output gap). If the output gap is positive inflation tends to rise and vice versa if the gap is negative. The problem, however, is that potential output cannot be directly observed. A variety of techniques are currently used in other countries to estimate potential output, including the use of the Hodrick-Prescott filter. In this paper the various available techniques will be surveyed and applied to South African data in order to generate an economy-wide measure of potential output and the output gap.

Suggested Citation

  • 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.
  • Handle: RePEc:sza:wpaper:wpapers5

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    References listed on IDEAS

    1. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    2. Evans, George & Reichlin, Lucrezia, 1994. "Information, forecasts, and measurement of the business cycle," Journal of Monetary Economics, Elsevier, vol. 33(2), pages 233-254, April.
    3. P Clark & D Laxton, 1997. "Phillips Curves," CEP Discussion Papers dp0344, Centre for Economic Performance, LSE.
    4. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    5. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    6. Guay, A & St-Amant, P, 1996. "Do Mechanical Filters Provide a Good Approximation of Business Cycles?," Working Papers-Department of Finance Canada 1996-2, Department of Finance Canada.
    7. Cote, D. & Hostland, D., 1996. "An Econometric Examination of the Trend Unemployment Rate in Canada," Staff Working Papers 96-7, Bank of Canada.
    8. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    9. Paul Conway & Ben Hunt, 1997. "Estimating potential output: a semi-structural approach," Reserve Bank of New Zealand Discussion Paper Series G97/9, Reserve Bank of New Zealand.
    10. Alain DeSerres, & Alain Guay & Pierre St-Amant, "undated". "Estimating and Projecting Potential Output Using Structural VAR Methodology: The Case of the Mexican Economy," Staff Working Papers 95-2, Bank of Canada.
    11. Chantal Dupasquier & Alain Guay & Pierre St-Amant, 1997. "A Comparison of Alternative Methodologies for Estimating Potential Output and the Output Gap," Staff Working Papers 97-5, Bank of Canada.
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    Cited by:

    1. Stan du Plessis & Ben Smit & Federico Sturzenegger, 2007. "Identifying aggregate supply and demand shocks in South Africa," Working Papers 11/2007, Stellenbosch University, Department of Economics.
    2. Stan du Plessis & Ben Smit & Federico Sturzenegger, 2008. "Identifying Aggregate Supply and Demand Shocks in South Africa †," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 17(5), pages 765-793, November.
    3. Rulof P. Burger & Francis J. Teal, 2014. "The effect of schooling on worker productivity: Evidence from a South African industry panel," Working Papers 04/2014, Stellenbosch University, Department of Economics.
    4. Johannes Hermanus Kemp, 2015. "Measuring Potential Output for the South African Economy: Embedding Information About the Financial Cycle," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 549-568, December.
    5. Guangling (dave Liu & Rangan Gupta, 2007. "A Small-Scale Dsge Model For Forecasting The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 75(2), pages 179-193, June.
    6. Marina Marinkov & Jean-pierre Geldenhuys, 2007. "Cyclical Unemployment And Cyclical Output: An Estimation Of Okun'S Coefficient For South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 75(3), pages 373-390, September.
    7. repec:bla:sajeco:v:85:y:2017:i:2:p:161-177 is not listed on IDEAS

    More about this item


    Potential output; inflation; output gaps; South Africa;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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


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