The Transmission of Monetary Policy in South Africa Before and After the Global Financial Crisis

Abstract

This paper examines whether the transmission mechanism of monetary policy in South Africa has changed after the global financial crisis (GFC). We use a Bayesian vector autoregressive (BVAR) model with Minnesota priors and 15 monthly variables, extending the system of Christiano, Eichenbaum, with Evans (1999). The benefit of the BVAR approach is that it can accommodate a large cross section of variables without running out of degrees of freedom. To identify the change in the transmission process, we divide the sample size into two subsamples, namely the pre‐GFC period (March 2001 to August 2008) and the post‐GFC period (September 2008 to February 2016). The results indicate that a change in the transmission of monetary policy occurred after the GFC. The magnitude of the effect of a monetary policy shock on output is considerably greater in the pre‐GFC period compared to the post‐GFC period. Moreover, the impact of a policy shock on inflation is not statistically significant in the post‐GFC period. The variance decomposition shows that the interest‐rate channel has possibly weakened in the post‐GFC period.

A deep learning approach to estimation of the Phillips curve in South Africa

“…On South Africa, interpret this finding to be a result of both an increase in the credibility of the SARB to maintain their inflation target and 'good luck' (p. 94). 1 In contrast to Kabundi and Rapapali (2019), their findings do not point to a decreased potency of monetary policy on inflation through the real economy following the global financial crisis. In short, rather than being 'dead', the Phillips curve more likely exhibits non-linear relationships over time and in response to permanent versus temporary shocks, which leads to a complex lead-lag relationship between inflation and real activity (Reinbold and Wen 2020).…”

Law of interest rate changes in financial markets based on the differential equation model of liquidity

“…Then the value at risk closely related to volatility should also have similar properties. For this reason, the author proposes a CAViaR model with autocorrelation characteristics based on the idea of quantile regression to directly measure the value at risk of financial markets [2]. However, the CAViaR model is mainly suitable for analysing the dynamic risk characteristics of a single sector.…”

Spillovers of the Conventional and Unconventional Monetary Policy from the US to South Africa

“…Other factors prevailing during this periods include high indebtedness of households, which led to impaired balance sheets following the financial crisis and therefore deleveraging. Another factor relates to the change in regulations, such as Basel II, Basel III, and the Affordability Assessment Regulations (AARs) of the National Credit Regulator (NCR) which could have had a negative impact on the supply of credit, as shown in Kabundi and Rapapali (2019). Whatever the reason (s), our results are consistent with the sluggish economic growth over the past decade in South Africa following the 2007-2008 global financial crisis, which has resulted in South Africa not being able to take advantage of low inflation nor the global economic recovery.…”