Skip to main content
SpringerLink
Log in

Business Confidence and the Business Cycle in South Africa

  • Chapter
  • First Online:
Business Cycles and Structural Change in South Africa

Abstract

Business confidence indicators are widely used leading indicators of economic activity. A large international literature has also investigated the potential role of low confidence in shaping economic outcomes. It is therefore important to measure business confidence as accurately as possible. The authors use the microdata from the BER’s business tendency surveys to create new composite indicators of business confidence for South Africa. The indicators are refined by incorporating more survey information and applying a consistent weighting procedure. The authors demonstrate a significant positive relationship between confidence and real economic activity, the consistent timing of this relationship, and that it remains significant after taking other variables into account. The confidence indicators therefore contain useful information about current and future economic developments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    For this reason, the BER includes only main building contractors, and not sub-contractors. It also excludes the other services sectors, until more information on their cyclical behaviour becomes available.

  2. 2.

    The microdata for architects, quantity surveyors, and civil engineers are only available from 2001Q1.

  3. 3.

    It excludes financial, telecommunication, postal, government, and other cultural services. Its coverage is therefore narrower than the quarterly GDP numbers for the services sector.

  4. 4.

    The ‘other services’ survey results are preliminary and have been provided to the authors to complete their research. According to the BER, of the various ‘other services’ subsectors, so far the cycle of only land freight transport services appears to co-move with the other typical cyclical sectors at the peaks.

  5. 5.

    The trade and ‘other services’ indicators are slightly over-weighted, in the sense that the survey coverage is narrower than the quarterly GDP numbers for these sectors.

  6. 6.

    The new confidence indicators differ from the BER BCIs in a number of ways. First, the new confidence indicators are composite indicators that combine the responses to five types of variables. Second, the new indicators include all of the construction subsectors and the survey of ‘other services’. Third, the new indicators use weights that are equivalent to an explicit two-step weighting procedure, whereby weighted means are calculated for each subsector separately, and then aggregated with the subsector weightings. Fourth, the new indicators use simple linear firm weights, as opposed to exponential firm weights, based on the size categories. Fifth, the new indicators weigh all of the sectors in the same way. Sixth, the new sectoral series are aggregated with weights based on GDP value added shares to create the overall confidence indicators.

  7. 7.

    The corresponding reference series for the BER’s surveys are manufacturing production, buildings completed, and sales volumes. This differs from the GDP value added series, which exclude intermediate demand.

  8. 8.

    The SARB’s monthly business cycle dates were converted to their corresponding quarters, to agree with the BER’s survey frequency. This involves an inevitable loss of detail and some potential inaccuracies. For example, if the SARB dates a turning point in April (Q2), while the confidence indicator indicates a turning point in the first quarter, it appears as if the BER data leads the cyclical indicator by one quarter, whereas the actual lead would only be 1 month.

References

  • Acemoglu, D., & Scott, A. (1994). Consumer confidence and rational expectations: Are agents’ beliefs consistent with the theory? The Economic Journal, 104, 1–19.

    Article  Google Scholar 

  • Akerlof, G., & Shiller, R. J. (2015). Animal spirits: How human psychology drives the economy, and why it matters for global capitalism. Princeton: Princeton University Press.

    Google Scholar 

  • Bachmann, R., Elstner, S., & Sims, E. R. (2013). Uncertainty and economic activity: Evidence from business survey data. American Economic Journal: Macroeconomics, 5(2), 217–249.

    Google Scholar 

  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593–1636. https://doi.org/10.1093/qje/qjw024.Advance

    Article  Google Scholar 

  • Barsky, R. B., & Sims, E. R. (2012). Information, animal spirits, and the meaning of innovations in consumer confidence. American Economic Review, 102(4), 1343–1377. https://doi.org/10.1257/aer.102.4.1343

    Article  Google Scholar 

  • Beaudry, P., & Portier, F. (2004). An exploration into Pigou’s theory of cycles. Journal of Monetary Economics, 51(6), 1183–1216. https://doi.org/10.1016/j.jmoneco.2003.10.003

    Article  Google Scholar 

  • Bosch, A. (2015, March 24). Composite Business Cycle Indicators for South Africa. South African Reserve Bank.

    Google Scholar 

  • Boshoff, W. H. & Du Plessis, S. A. (2020). Chapter 2: What do we know about the South African Business Cycle. In W. H. Boshoff (Ed.), Business Cycles and Structural Change in South Africa. Switzerland: Springer.

    Chapter  Google Scholar 

  • Bry, G., & Boschan, C. (1971). Cyclical analysis of economic time series: selected procedures and computer programs. NBER Technical Working Paper, No. 20.

    Google Scholar 

  • Carroll, C. D., Fuhrer, J. C., & Wilcox, D. W. (1994). Does consumer sentiment forecast household spending? If so, why? American Economic Review, 84(5), 1397–1408.

    Google Scholar 

  • Cochrane, J. H. (1994). Shocks. In Carnegie-Rochester Conference Series on Public Policy, December 1994 (Vol. 41, pp. 295–364).

    Google Scholar 

  • Driver, C., & Urga, G. (2004) Transforming qualitative survey data: Performance comparisons for the UK. Oxford Bulletin of Economics and Statistics, 66(1), 71–89. https://doi.org/10.1111/j.1440-1754.2007.01273.x

    Article  Google Scholar 

  • European Central Bank. (2013, January). Confidence indicators and economic developments. ECB Monthly Bulletin, 45–58.

    Google Scholar 

  • European Commission. (2006). European Economies: The Joint Harmonised EU Programme of Business and Consumer Surveys. Directorate-General for Economic; Financial Affairs (Special Report No. 5).

    Google Scholar 

  • Fuhrer, J. C. (1988). On the information content of consumer survey expectations. The Review of Economics and Statistics, 70, 140–144.

    Article  Google Scholar 

  • Gayer, C., Girardi, A., & Reuter, A. (2014, December). The Role of Survey Data in Nowcasting Euro Area GDP Growth. European Commission Economic Papers, 538. https://doi.org/10.2765/71951

  • Gehlbach, H., & Barge, S. (2012). Anchoring and adjusting in questionnaire responses. Basic and Applied Social Psychology, 34(5), 417–433. https://doi.org/10.1080/01973533.2012.711691

    Article  Google Scholar 

  • Giannone, D., Reichlin, L., & Small, D. (2008). Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, 55, 665–676. https://doi.org/10.1016/j.jmoneco.2008.05.010

    Article  Google Scholar 

  • Girardi, A., & Reuter, A. (2017). New uncertainty measures for the euro area using survey data. Oxford Economic Papers, 69(1), 278–300. https://doi.org/10.1093/oep/gpw058

    Article  Google Scholar 

  • Harding, D., & Pagan, A. (2002). Dissecting the cycle: A methodological investigation. Journal of Monetary Economics, 49(2), 365–381. https://doi.org/10.1016/S0304-3932(01)00108-8

    Article  Google Scholar 

  • Harding, D., & Pagan, A. (2006). Synchronization of cycles. Journal of Econometrics, 132, 59–79. https://doi.org/10.1016/j.jeconom.2005.01.023

    Article  Google Scholar 

  • International Monetary Fund. (2017, July 23). World Economic Outlook Update. IMF Publications.

    Google Scholar 

  • Kabundi, A. (2004). Estimation of Economic Growth in France Using Business Survey Data. IMF Working Paper, WP/04/69.

    Google Scholar 

  • Kabundi, A., Nel, E., & Ruch, F. (2016). Nowcasting Real GDP Growth in South Africa. ERSA Working Paper, 581.

    Google Scholar 

  • Kershoff, G. (2000, December). Measuring Business and Consumer Confidence in South Africa. Bureau for Economic Research.

    Google Scholar 

  • Kershoff, G. (2002). An analysis of the BER’s trade and building survey panels. Journal for Studies in Economics and Econometrics, 26(1), 1–17.

    Google Scholar 

  • Kershoff, G. (2015). South Africa: The BER’s Business Tendency Surveys. Bureau for Economic Research (pp. 1–19).

    Google Scholar 

  • Keynes, J. M. (1936). General theory of employment, interest and money. London: Macmillan. https://doi.org/10.2307/2143949

    Google Scholar 

  • Kilic, E., & Cankaya, S. (2016). Consumer confidence and economic activity: A factor augmented VAR approach. Applied Economics, 48(32), 3062–3080. https://doi.org/10.1080/00036846.2015.1133902

    Article  Google Scholar 

  • Laubscher, P. (2014). A New Recession-Dating Algorithm for South Africa. Stellenbosch Economic Working Papers, 06/14.

    Google Scholar 

  • Leduc, S., & Liu, Z. (2016). Uncertainty shocks are aggregate demand shocks. Journal of Monetary Economics, 82, 20–35. https://doi.org/10.1016/j.jmoneco.2016.07.002

    Article  Google Scholar 

  • Leduc, S., & Sill, K. (2013). Expectations and economic fluctuations: An analysis using survey data. Review of Economics and Statistics, 95, 1352–1367.

    Article  Google Scholar 

  • Ludvigson, S. C. (2004). Consumer confidence and consumer spending. Journal of Economic Perspectives, 18(2), 29–50

    Article  Google Scholar 

  • Matheson, T. D. (2010). An analysis of the informational content of New Zealand data releases: The importance of business opinion surveys. Economic Modelling, 27(1), 304–314. https://doi.org/10.1016/j.econmod.2009.09.010

    Article  Google Scholar 

  • Mendicino, C., & Punzi, M. T. (2013, Winter). Confidence and economic activity: The case of Portugal. Banco de Portugal, 39–49

    Google Scholar 

  • Nardo, M. (2003). The quantification of qualitative survey data: A critical assessment. Journal of Economic Surveys, 17(5), 645–668.

    Article  Google Scholar 

  • Organisation for Economic Co-operation and Development. (2003). In E. Giovannini & E. Burgeat (Eds.), Business tendency surveys: A handbook. Paris, France: OECD Publications.

    Google Scholar 

  • Parigi, G., & Golinelli, R. (2004). Consumer sentiment and economic activity. Journal of Business Cycle Measurement and Analysis, 2004(2), 147–170. https://doi.org/10.1787/jbcma-v2004-art10-en

    Article  Google Scholar 

  • Pellissier, M. (2002). Business confidence and the South African business cycle. Journal for Studies in Economics and Econometrics, 26(2), 51–67.

    Google Scholar 

  • Pellissier, M., & Smit, E. vd M. (1994) Constructing sectoral leading indicators using data reduction techniques. In Business cycle surveys: Forecasting issues and methodological aspects (pp. 271–290). Aldershot: Avebury.

    Google Scholar 

  • Redl, C. (2015). Macroeconomic Uncertainty in South Africa. ERSA Working Paper, 509.

    Google Scholar 

  • SACCI. (2011). Updated and Revised SACCI Business Confidence Index. South African Chamber of Commerce and Industry.

    Google Scholar 

  • Santero, T., & Westerlund, N. (1996). Confidence Indicators and Their Relationship to Changes in Economic Activity. OECD Economics Department Working Papers, 170. https://doi.org/10.1787/537052766455

  • Smit, E. vd M. (1983). ’n Ekonomiese bestedingsmodel vir die Suid-Afrikaanse ekonomie gebaseer op kwalitatiewe data-insette. Journal for Studies in Economics and Econometrics, 15, 5–36.

    Google Scholar 

  • Smit, E. vd M. (1984) A systematic comparison of expenditure models of the South African economy excluding and including opinion survey variables. CIRET Studies, 34, 219–234.

    Google Scholar 

  • Taylor, K., & McNabb, R. (2007). Business cycles and the role of confidence: Evidence for Europe. Oxford Bulletin of Economics and Statistics, 69(2), 185–208. https://doi.org/10.1111/j.1468-0084.2007.00472.x

    Article  Google Scholar 

  • Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

    Article  Google Scholar 

  • United Nations. (2015). Handbook on economic tendency surveys. New York: United Nations Publications.

    Google Scholar 

  • Van Aarle, B., & Kappler, M. (2012). Economic sentiment shocks and fluctuations in economic activity in the Euro Area and the USA. Intereconomics, 47(1), 44–51. https://doi.org/10.1007/s10272-012-0405-z

    Article  Google Scholar 

  • Venter, J. C. (2005, September) Reference turning points in the South African business cycle: Recent developments. SARB Quarterly Bulletin, 61–70.

    Google Scholar 

  • Venter, J. C. (2020). Chapter 9: Assessing the 2013 and 2017 business cycle turning points signalled by the SARB’s composite leading business cycle indicator. In W. H. Boshoff (Ed.), Business Cycles and Structural Change in South Africa. Switzerland: Springer.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, Stellenbosch University, Stellenbosch, South Africa

    L. H. Binge

Authors
  1. L. H. Binge
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Economics, Stellenbosch University, Stellenbosch, South Africa

    Willem H. Boshoff

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Binge, L.H. (2020). Business Confidence and the Business Cycle in South Africa. In: Boshoff, W. (eds) Business Cycles and Structural Change in South Africa. Advances in African Economic, Social and Political Development. Springer, Cham. https://doi.org/10.1007/978-3-030-35754-2_8

Download citation

Publish with us

Policies and ethics

Search

Navigation