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2020 | OriginalPaper | Chapter

What Do We Know About the South African Business Cycle?

Authors : W. H. Boshoff, S. A. du Plessis

Published in: Business Cycles and Structural Change in South Africa

Publisher: Springer International Publishing

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Abstract

A significant amount of macroeconomic research on the South African business cycle has appeared since the late 1990s, mostly with the turning point cycles identified by the South African Reserve Bank (SARB) as an empirical starting point. Following the established nomenclature of the international literature—we summarize key trends and conclusions in this literature along three lines: firstly, studies aimed at identifying and describing key properties of South African business cycles, secondly, studies concerning the forecasting of South African cycles and, thirdly, studies on the relationship between stabilization policy and the South African cycle. This thematic summary pays special attention to cyclical developments after the financial crisis and identifies key gaps in the state of knowledge.

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previous chapter Introduction

next chapter The South African Economy in the Twentieth Century

See Achuthan and Banerji (2004) for a nontechnical history of cyclical measurement.

A third, though rarely used, class of methods assume sinusoidal periodicity.

The upper end of the frequency range (8 years) is somewhat lower than the 10 to 12 years range identified earlier by Mitchell (1927).

Refer to Boshoff and Fourie (2020) in this volume, which revisits data and business cycle turning points in South Africa for the entire twentieth century.

Harding and Pagan revitalised the literature on nonparametric business cycle identification in the early 2000s with a set of publications—see the debate between Harding and Pagan (2003a, b) and Hamilton (2003).

Note that this involves subtracting a deterministic (linear) time trend (Du Plessis 2006). Harding and Pagan (2001) suggest that this form of detrending is most appropriate, as it does not result in a significant loss of information about the turning points.

Statistically, the first principal component carries most information, that is, it captures the largest portion of variance in the data.

The converse has not been attempted in the South African literature, where turning points are identified for every individual series and then aggregated to a common set of turning points (Harding and Pagan (2006) suggests such a clustering approach).

This cycle concept underlying this debate is a classical cycle version of the so-called “technical” recession, according to which a recession is identified if output contracts for two consecutive quarters. This clearly differs from the longer time horizon of the BB algorithm. It is therefore clear that the South African public still very much holds a classical cycle view.

The degree of synchronisation between two series relates to the probability that the two economic series are in the same business cycle phase. The sample equivalent of this probability is the concordance index. It is calculated as the proportion of the sample period during which the two series share the same business cycle phase (Harding and Pagan 2006).

Refer to Venter (2018) for a comprehensive historical overview of the development of composite indicators in South Africa.

See a subsequent chapter in this volume, by Binge (2019), on the predictive content of confidence, which is related to economic uncertainty.

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Title: What Do We Know About the South African Business Cycle?
Authors: W. H. Boshoff
S. A. du Plessis
Publisher: Springer International Publishing
Book: Business Cycles and Structural Change in South Africa
Print ISBN: 978-3-030-35753-5

Electronic ISBN: 978-3-030-35754-2

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-35754-2_2