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Nowcasting Real GDP growth in South Africa

Author

Listed:
  • Alain Kabundi
  • Elmarie Nel
  • Franz Ruch

Abstract

This paper uses nowcasting to forecast real GDP growth in South Africa from 2010Q1 to 2014Q3 in real time. Such an approach exploits the flow of high-frequency information underlying the state of the economy. It overcomes one of the major challenges faced by forecasters, policymakers, and economic agents - having a clear view of the state of the economy in real time. This is often not the case as many economic variables are only available at low frequency and with considerable lags, making it difficult to have information on the state of the economy even after the end of the quarter. The pseudo out-of-sample forecasts show that the nowcasting models performance is comparable to those of professional forecasters even though the latter enhance their forecasting accuracy with judgement. The nowcast model also outperforms all other benchmark models by a significant margin.

Suggested Citation

  • Alain Kabundi & Elmarie Nel & Franz Ruch, 2016. "Nowcasting Real GDP growth in South Africa," Working Papers 7068, South African Reserve Bank.
  • Handle: RePEc:rbz:wpaper:7068
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    Cited by:

    1. Wolszczak-Derlacz Joanna, 2014. "The Impact Of Domestic And Foreign Competition On Sectoral Growth: A Cross-Country Analysis," Bulletin of Economic Research, Wiley Blackwell, vol. 66(S1), pages 110-131, December.
    2. Sara Amoroso & Peter M. Kort & Bertrand Melenberg & Joseph Plasmans & Mark Vancauteren, 2010. "Firm Level Productivity under Imperfect Competition in Output and Labor Markets," CESifo Working Paper Series 3082, CESifo.
    3. Saten Kumar & Gail Pacheco & Stephanié Rossouw, 2010. "How to Increase the Growth Rate in South Africa?," EERI Research Paper Series EERI_RP_2010_31, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    5. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    6. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    7. Evžen Kočenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
    8. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    9. Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
    10. Delfin Go & Marna Kearney & Vijdan Korman & Sherman Robinson & Karen Thierfelder, 2010. "Wage Subsidy and Labour Market Flexibility in South Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 46(9), pages 1481-1502.
    11. Byron Botha & Geordie Reid & Tim Olds & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African GDP using a suite of statistical models," Working Papers 11001, South African Reserve Bank.
    12. Alain Kabundi & Asithandile Mbelu, 2021. "Estimating a time-varying financial conditions index for South Africa," Empirical Economics, Springer, vol. 60(4), pages 1817-1844, April.
    13. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.
    14. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
    15. Ashwin Madhou & Tayushma Sewak & Imad Moosa & Vikash Ramiah, 2017. "GDP nowcasting: application and constraints in a small open developing economy," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3880-3890, August.
    16. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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