South African Business Cycle Research Articles

Business Cycles and Growth of South African Steel Manufacturing Industry

The paper studies the relationship between the South African business cycle and the performance of the steel industry. The analysis was conducted by first providing a brief bibliometric review of the definitions used for business cycles in literature. From this initial analysis, emerging themes were used to define the narrative literature review on the relationship between business cycles, economic growth, and supply-demand of the steel industry. Findings from the review, indicate a binary relationship between economic growth and steel industry output. It is recommended that future studies be done on quantitative analysis of the binary and ternary relationships between economic growth and other primary manufacturing industries in South Africa.

Fiscal Cyclicality in South African Public Expenditures: Do Asymmetries Explain the Inconsistencies?

The most recent sub-prime crisis, the Euro-debt crisis and the global recessionary period have resurrected a debate on the nature of fiscal cyclicality in the South African economy. Previous literature on the South African economy has been inconclusive and we attribute this inconclusiveness to possible asymmetries existing in the fiscal cyclicities. Our study questions whether the cyclicality of public policy has evolved asymmetrically and holds differently over the recessionary and expansionary phases of the South African business cycle for a quarterly period of 2001:01 – 2018:04. To ensure that the business cycle is inherent to our estimation process we rely on the nonlinear autoregressive distributive lag (N-ARDL) model as empirical framework. For comparative purposes, we firstly examined fiscal cyclicality in fiscal expenditures by estimating the conventional ARDL using H-P filter to extract cyclical terms. Our preliminary results point to fiscal procyclicity in fiscal expenditures over the short-run but not over the long-run. However, in proceeding to our main empirical N-ARDL estimates, we observe nonlinear behaviour in the cyclicality of fiscal expenditures in which fiscal authorities behave procyclical in the upswing of the business cycle whilst behaving countercyclical during economic downswings. These findings are robust to alternative specifications, inclusion of control variables and estimations across different subsamples corresponding the pre- and post- 2007 financial crisis. Our findings have two important policy implications. Firstly, our findings reveal fiscal authorities have been implementing wrong policies during the upswing of the business cycle whilst implementing correct fiscal policies during the downswing. Secondly, our findings implore fiscal authorities to incorporate asymmetric fiscal cyclicality within the design of optimal fiscal policy rules in order to avoid making policy decisions based on inaccurate diagnosis of fiscal behaviour.

Suicide and the South African Business Cycle

Using monthly data for January 2006 - December 2015, this study explores the relationship between suicide and the South African business cycle. Contrary to most previous research, the findings reveal that suicide is pro-cyclical.

Obtaining Clear and Timely Business Cycle Turning Point Signals With a Composite Leading Business Cycle Indicator

The upward phase of the South African business cycle that followed the global financial crisis gradually lost momentum from 2012 onwards, resulting in a peak in the business cycle being reached in November 2013. The subsequent downward phase has so far lasted for 48 months, up to November 2017. The gradual loss of momentum in domestic output growth was not widely recognised by many economists, judging by consensus forecasts of annual GDP growth. However, the South African Reserve Bank (SARB) composite leading business cycle indicator reached a peak in February 2011 before trending gradually lower, suggesting a continued deterioration in output growth. The leading indicator reached a trough in April 2016, suggesting an imminent end to the downward phase of the business cycle, in line with consensus forecasts. However, output growth slowed further with the economy experiencing a technical recession. This paper employs the indicator approach to business cycle analysis in order to establish whether the current downward phase in the South African business cycle could reasonably have been predicted, and also whether the recent strong increase in the composite leading business cycle indicator provided a clear signal that the current downward phase might have ended. The results show that closer analysis of the leading indicator and its subcomponents would have revealed that a broad slowdown in the South African economy was underway since 2012. Also, the recent upward trend in the leading indicator did initially signal the end of the current downward phase in the business cycle in an unambiguous manner. However, the anticipated business cycle recovery appears to have been postponed by idiosyncratic exogenous factors.

The Impact of Oil Price on South African GDP Growth: A Bayesian Markov Switching‐VAR Analysis

AbstractOne characteristic of many macroeconomic and financial time series is their asymmetric behaviour during different phases of a business cycle. Oil price shocks have been amongst those economic variables that have been identified in theoretical and empirical literature to predict phases of business cycles. However, the role of oil price shocks to determine business cycle fluctuations has received less attention in emerging and developing economies. The aim of this study is to investigate the role of oil price shocks in predicting phases of the South African business cycle associated with higher and lower growth regimes. By adopting a regime dependent analysis, we investigate the impact of oil price shocks under two phases of the business cycle, namely high and low growth regimes. As a net importer of oil, South Africa is expected to be vulnerable to oil price shocks irrespective of the phase of the business cycle. Using a Bayesian Markov switching vector autoregressive (MS‐VAR) model and data for the period 1960Q2 to 2013Q3, we found the oil price to have predictive content for real output growth under the low growth regime. The results also show the low growth state to be shorter‐lived compared to the higher growth state.

Forecasting The South African Business Cycle Using Fourier Analysis

A Fourier transform analysis is proposed to determine the duration of the South African business cycle, measured using log changes in nominal gross domestic product (GDP). The most prominent cycle (two smaller, but significant, cycles are also present in the time series) is found to be 7.1 years, confirmed using Empirical Mode Decomposition. The three dominant cycles are used to estimate a 3.5 year forecast of log monthly nominal GDP and these forecasts compared to observed (historical) data. Promising forecast potential is found with this significantly-reduced number of cycle components than embedded in the original series. Fourier analysis is effective in estimating the length of the business cycle, as well as in determining the current position (phase) of the economy in the business cycle.

Identifying an index of financial conditions for South Africa

Purpose – The purpose of this study is to construct a financial conditions index (FCI) for the South African economy to enable the gauging of financial conditions and to better understand the macro-financial linkages in the country. The global financial crisis that began in 2007-2008 demonstrated how severe the impact of financial markets’ stress on real economic activity can be. In the wake of the financial crisis, policy-makers and decision-makers across the world identified the critical need for a better understanding of financial conditions, and more importantly, their impact on the real economy. Design/methodology/approach – The FCI is constructed using monthly data over the period 1966 to 2011, and is based on a set of 16 financial variables, which include variables that define the state of international financial markets, asset prices, interest rate spreads, stock market yields and volatility, bond market volatility and monetary aggregates. The authors explore different methodologies for constructing the FCI, including full sample and rolling-window principal components analysis. Furthermore, the authors investigate whether it is beneficial to purge the FCI of the real effects of inflation, economic growth and interest rates, and evaluate the performance of our constructed FCIs by comparing their ability to pick up turning points in the South African business cycle, and by running in-sample causality (forecast) tests. Findings – The authors find that the estimated FCIs are good predictors of economic activity; with the rolling-window FCI being the “best” performing index. Causality tests indicate that this FCI is a good in-sample predictor of industrial production growth and the Treasury Bill rate, but a weak predictor of inflation. Practical implications – The authors find that the resulting FCI can act as an “early warning system”. This, in turn, may serve to indicate that monetary policy should take broader financial conditions into account. Originality/value – This study offers three main contributions to the existing literature on financial conditions in South Africa: the authors construct an FCI over a sample period that is three decades longer than existing indices, the FCI of this paper comprises a wider coverage of financial variables than others and the authors make use of rolling-window estimation techniques that allow them to account for parameter instability and to capture the real-time constraints faced by a policymaker.

Dating the Business Cycle in South Africa by Using a Markov-Switching Model

This paper applies a Markov-switching dynamic regression model to the real quarterly GDP time series from 1981 to 2010 in order to detect turning points in the South African business cycle. The model comprises several explicative variables. These include short- and long- term interest rates, monetary aggregates as well as the difference between long- and short-term interest rates. For all these variables, the possibility of dynamic lags was also considered. A chronology for the South African classical and growth cycles, using a quarterly algorithm is established. Application of this non-parametric procedure yields six complete cycles over the period 1960-2011.

Rethinking ASGISA and the rand exchange rate

Abstract: The ASGISA policy document identifies the exchange rate as one of the factors constraining accelerated growth in South Africa. This note argues that currency developments do not translate into business cycle movements in the aggregate economy, and that a weaker exchange rate is less likely to boost either foreign investment or export performance in the face of regulatory uncertainty. The South African government has recently launched the Accelerated and Shared Growth Initiative (ASGISA) aimed at raising the long-term growth path of the economy. The plan identifies several so-called “binding constraints” that are considered to be inhibiting the economy from rising to more elevated levels of economic growth. One such “constraint”, according to the ASGISA policy document, is the “volatility and level of the currency” (Republic of South Africa, 2006). By including this issue, policymakers have signalled that fluctuations in the Rand are considered significant to broader economic fluctuations in South Africa. This research note questions such a conviction by offering evidence that currency fluctuations are not mirrored in the South African business cycle. Nonetheless, proponents may argue that a weaker Rand will stimulate particular sectors, mostly those that are export-oriented, while it will boost Foreign Direct Investment (FDI). However, this note argues further that a weaker Rand is less likely to generate sustainable improvement in either export-oriented industries or FDI in the absence of other reforms. The following sections consider these two issues in sequence.

The South African business cycle: what has changed?

This paper identifies the basic empirical characteristics and changes of the South African business cycle since 1960. As such, the paper examines changes in volatility as well as the co-movement between several national account variables and real GDP. To examine the co-movements the paper follows Kydland and Prescott, Gavin and Kydland as well as Bergman, Bordo and Jonung and uses correlation coefficients and Granger causality tests. Following Ramos, the paper extends the results of the Granger causality tests using variance decomposition analysis in the context of a VAR (vector auto regression) to establish the contribution that selected national account variables make to the h-period-ahead forecast error variance of themselves and the other variables included in the VARs. The paper indicates that since 1994 volatility in the South African economy decreased significantly, while durable consumption appears to lead the business cycle.

Monetary Policy And Long-Term Interest Rates In South Africa

This paper examines how short-term and long-term interest rates react to supply, demand and monetary policy shocks in South Africa. Use is made of the impulse response functions obtained from the structural vector autoregressive model with long-term restrictions. We find a positive correlation between the two interest rates after a monetary and demand shock and a negative correlation after a supply shock. The finding of this paper is that the operation of the monetary transmission mechanism should be effective in South Africa. Furthermore, this paper provides an approach to identify supply shocks in the South African business cycle.

THE ROLE OF THE EXCHANGE RATE IN A NEW KEYNESIAN DSGE MODEL FOR THE SOUTH AFRICAN ECONOMY

We build a small open economy New Keynesian dynamic stochastic general equilibrium model for South Africa similar to Steinbach et al. We abandon their assumption of complete risk sharing with the foreign economy, and introduce country risk shocks to allow deviations from uncovered interest rate parity. These changes allow us to include the exchange rate as an observable variable in the estimation of the model. Using forecast error variance decompositions and historical decompositions, we show that country risk shocks have sizable effects on the South African business cycle. We also explore the optimal monetary policy implications of our model within the context of Taylor rules.

Identifying Aggregate Supply and Demand Shocks in South Africa

This paper uses a structural VAR methodology to identify aggregate demand and supply shocks to real output for the South African economy. Demand shocks, in turn, are separated into fiscal and monetary shocks. The model is estimated with quarterly data over two overlapping samples: 1960Q2--2006Q4 and 1983Q4--2006Q4. The identified (structural) shocks were used in a historical decomposition to split output into a measure of potential output (resulting from the evolution of supply shocks) and a measure of the business cycle (the gap between actual and potential output). This measure of potential output suggests a significant decline relative to trend in the years prior to the political transition of 1994 and a swift reversal thereafter. The paper presents evidence from three sources to support its identification of aggregate supply and demand shocks. These sources are the following: theory consistent impulse response functions; a close match between the implied measure of the business cycle and independent information about the South African business cycle and a demonstration of the close match between the identified series of aggregate supply shocks and important historical events in the decades prior to and following 1994 that have been identified by economic historians as important shocks to the South African economy. Copyright 2008 The author 2008. Published by Oxford University Press on behalf of the Centre for the Study of African Economies. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Co-movement between South Africa and the Southern African Development Community: An empirical analysis

This paper uses a novel dynamic factor model à la Forni et al. [Forni, M., Hallin, M., Lippi, M., Reichlin, L., 2003. The Generalized Factor Model: One-Sided Estimation and Forecasting. ECARES–ULB Working Paper. www.dynfactors.org] to investigate the nature and extent of co-movement of the South African business cycle with those of eleven of the Southern African Development Community (SADC) countries, covering the period 1980–2002. The results show strong and significant evidence of co-movement or synchronization of the South African business cycle with those of Swaziland, Botswana, Zimbabwe, the DRC, Lesotho and Angola. A moderate but still significant synchronization with Mozambique, Mauritius and Namibia is also evident, while no significant co-movement exists between the South African business cycle and those of Malawi and Zambia, respectively. In isolating the regional common component, the results show that such a component significantly explains growth in less than a third of SADC economies, implying that global and/or country specific common components still outweighs regional common components. The striking result is that South Africa, justified by its geographical location and increased participation in the global economy, cannot isolate itself from its SADC neighbours, and that regional policy coordination is of the utmost importance.

Modelling the Business Cycle in South Africa: A Non-Linear Approach

In this paper the South African business cycle is modeled, using a simple linear method and comparing it to non-linear methods. This is useful to address the debate between the Classical and Keynesian economists regarding their views on the business cycle. They believe in a stable economy with exogenous shocks and an unstable economy with an endogenous business cycle respectively. Linear models are usually associated with the Classical view and non-linear models with the Keynesian view.A detailed discussion on the non-linear model-building process, with particular emphasis on the family of STAR models is done. The South African GDP is used and AR, TAR, LSTAR and ESTAR models are fitted and compared.It finds that a parameterized nonlinear model (such as the family of STAR models) outperforms the simple regression model. This is due to asymmetric behaviour in the GDP data and the possibility of a threshold between a recession and an expansion.The results in this paper support the structural or institutional view of business cycles, which states that economic fluctuations are caused by various structural or institutional changes.

Reconsidering the business cycle and stabilisation policies in South Africa

This paper applies an alternative dating algorithm – suggested by Harding and Pagan (for example, [Harding, D., and Pagan, A., 2002a. A comparison of two business cycle dating methods. Journal of Economic Dynamics and Control 27, 1681–1690.]) – to uncover the turning points of the South African business cycle. The characteristics of the resulting business cycle are analysed and compared with results obtained for the official cycle in recent papers on the South African business cycle [du Plessis, S.A., and Smit, B.W., 2003. Stabilisation policy. Stellenbosch, Paper presented at the eight annual conference for econometric modelling in Africa.; du Plessis, S.A. 2004. Stretching the South African business cycle. Economic Modelling 21 (1), 685–701.]. The alternative business cycle has plausible characteristics and provides supporting evidence for the thesis that monetary policy has been used more consistently to dampen the cycle of economic activity in South Africa since the early nineties.

Stretching the South African business cycle

This paper investigates duration dependence in the South African business cycle using non-parametric tests. The evidence falls into three parts. First, there is little evidence of duration dependence in periods of expansion. Secondly, there is some evidence of positive duration dependence in contractions for a pre-1972 sub-sample. Thirdly, there has been significant lengthening in the total cycle and of downturns since 1972, but no lengthening of expansions. It is consistent with these observations to argue that the stretching of the South African business cycle may be due to a loss of duration dependence in downturns since the early 1970s.

Stretching the South African business cycle

This paper investigates duration dependence in the South African business cycle using non-parametric tests. The evidence falls into three parts. First, there is little evidence of duration dependence in periods of expansion. Secondly, there is some evidence of positive duration dependence in contractions for a pre-1972 sub-sample. Thirdly, there has been significant lengthening in the total cycle and of downturns since 1972, but no lengthening of expansions. It is consistent with these observations to argue that the stretching of the South African business cycle may be due to a loss of duration dependence in downturns since the early 1970s.

A Markov switching regime model of the South African business cycle

Linear models are incapable of capturing business cycle asymmetries. This has recently spurred interest in non-linear models such as the Markov switching regime (MS) technique of modelling business cycles. The MS model can distinguish business cycle recession and expansion phases, and is sufficiently flexible to allow different relationships to apply over these phases. In this study, the South African business cycle is modelled using a MS model. This technique can be used to simultaneously estimate the data generating process of real GDP growth and classify each observation into one of two regimes (i.e. low-growth and high-growth regimes).

A Markov switching regime model of the South African business cycle

A Markov switching regime model of the South African business cycle