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The present study aims to examine the relationship between exchange rate undervaluation and economic growth in South Africa, focusing on the various transmission mechanisms through which this relationship occurs. Through the adoption of secondary quarterly data spanning the period 1980 to 2018 and a two-step Generalised Method of Moments approach. The study estimated a Behavioural Equilibrium Exchange Rate of South Africa and used it to construct a measure of Exchange rate undervaluation. Further, the study examined the effects of Exchange rate undervaluation on the tradable sector, the savings/capital accumulation sector, and the total factor productivity sector. The study found evidence of the tradable sector and total factor productivity (TFP) channels in South Africa. Therefore, we conclude that there exist valuable lessons to be learnt through the analysis of this relationship on a micro level compared to a macro level. Macro-level studies overlook the individual effects, hence why results have been inconclusive. This, therefore, means that South Africa has an incentive to keep the Rand at a competitive level since the industrial and agricultural sectors benefit from a competitive Exchange rate.

This study investigates the dynamic relationship between credit supply and demand shocks and household consumption in South Africa using a quantile autoregressive distributed lag (QARDL) model. Motivated by the increasing reliance of South African households on debt amid stagnant income growth, rising living costs, and persistent unemployment, the research aims to understand how credit market conditions influence consumption across different segments of the income distribution. Drawing on data spanning from 1970 to 2024, the study incorporates key macroeconomic variables including real GDP per capita, household income per capita, household debt as a percentage of GDP, the credit-to-GDP ratio, inflation, interest rates, and the unemployment rate. The QARDL framework allows for the estimation of both short-run and long-run relationships while accounting for heterogeneity across consumption quantiles. The results indicate that household consumption is more responsive to income shocks and credit availability in the lower and middle quantiles, suggesting heightened sensitivity among poorer households. Credit supply, proxied by the credit-to-GDP ratio, exhibits weak but positive short-run effects, while household debt consistently exerts a negative influence on consumption across all quantiles and time horizons, with stronger effects in lower quantiles. These findings highlight the consumption-depressing effects of excessive debt, especially for financially vulnerable households. Moreover, macroeconomic stability indicators such as inflation and interest rates are found to negatively affect consumption, particularly in lower quantiles, underscoring the uneven transmission of monetary policy. The empirical results support the hypothesis that household debt contributes to financial fragility and undermines consumption over time, while credit supply shocks play a more modest role. The study concludes that policies aimed at improving income stability, managing household debt levels, and enhancing financial inclusion—particularly for low-income groups—are essential for sustaining household consumption and promoting inclusive economic growth in South Africa.

Several official dating institutions viz: SARB, NBER, OECD, CEPR, and others, provide Business Cycle (BC) chronologies with lags ranging from three months to several years. This is problematic for the various oppressed as it poses limits to the usefulness of BC indicators in terms of forecasting and policy implementation at large. In this article, we propose the construction of composite indicators as accurate measures of business cycles in South Africa. We use this composite index to facilitate comparison of both a non-parametric Bry and Boschan dating algorithm and a parametric Markov Switching dating method, in terms of performance and accuracy of dating business cycle turning points in South Africa. Utilising data spanning the period 2000M1 – 2018M12, empirical evidence obtained is such that, composite indices are better than single indicators due to information rich. Further, while the parametric and non-parametric methods’ performances are matched in terms of the number of turning points identified, however, the non-parametric method is more accurate in identifying these turning points. Due to its accuracy the non-parametric method proved to be a promising method of dating business cycle turning points in South Africa and alleviate the problems which are currently facing the South African Reserve Bank, the private sector and the economy at large.

The article reports on the complementarity and substitutability of Macroprudential and Monetary policies in South Africa, based on the interactions of both Business and Financial cycles. To this end, a Dynamic Conditional Correlations and the Asymmetric Dynamic Conditional Correlations MGARCH models together with the Granger Causality model, the Artificial Neural Network VAR model, and the Structural VAR model, were adopted for the analyses of synchronization, causality, and the analysis of shocks to cycles, respectively. Empirical evidence obtained is such that, under conditions of financial and real economic stress in South Africa, there exists high synchronicity and bidirectional causality between CBCI and CFCI. Hence, Macroprudential and Monetary policies become complements, there exists interdependence between the two policies and actions of one policy contributes to the improvement of the other. However, under normal times there exist no synchronicity and a unidirectional causality relationship running from CBCI to CFCI, was observed. Under such conditions, Macroprudential and Monetary policies become substitutes, therefore, the two policies become independent of each other, hence, only one policy can achieve the desired outcome. Overall, a shock to one cycle is a major determinant of the fluctuations of the other cycle.

This paper examines the exchange rate pass-through (ERPT) and its impact on home inflation in Bangladesh, particularly in the post-pandemic era. Examining important economic factors including the nominal exchange rate (NER), money supply (M2), industrial production (IP), and global commodity index (GCI) using monthly data from January 2002 to August 2023 helps one to grasp their combined influence on consumer price inflation (CPI). By means of Johansen cointegration and Vector Error Correction Model (VECM) approaches, the study reveals important short-term and long-term dynamics. Contrary to patterns in many emerging nations, the results show that changes in exchange rates have apparently little impact on home prices. Rather, changes in the money supply and world commodities prices mostly influence inflation; the latter becomes a major factor. The study also exposes an unexpected positive link between industrial production and CPI, implying complexity in Bangladesh's production-driven economic structure. Moreover, this investigation underlines how complex monetary expansion, external commodities shocks, and devaluation of money interact to shape inflationary pressures. These results offer legislators important new perspectives and support strong monetary policies and focused involvement in world commodities markets to help to lower inflation. This study clarifies ERPT in developing countries and provides direction on inflation control techniques for Bangladesh.

There has been increasing studies that details the transmission channels through which financial development permeates to speed up growth to higher echelon. Studies have underpinned that financial development yield more growth when these channels are optimized. With studies on real sector performance sparse, this paper contributes to this discussion as it examined the effect of financial development in fostering industrial growth under the condition of high and low human capital endowment. This was investigated for a sample of five (5) West African Monetary Zone (WAMZ) countries from 1990 to 2022. The study developed a panel threshold regression (PTR) model where human capital functioned as threshold variable and data collected from the United Nations Conference on Trade and Development (UNCTAD), World Development Indicator (WDI) and International Monetary Fund (IMF) databases. The study finds a threshold effect of financial development on industrial sector growth. The PTR estimator shows financial development can produce more industrial growth if human capital exceeds a gross of 62.9493%. Additionally, other factors such as trade openness, natural resource rents and higher labour participation in economic activities support industrial sector growth. In the design of industrial growth enhancing policies, policy mandarins should implement measures that improve human capital and further develop the financial system by scaling up education expenditure to the UNESCO prescribed 26% of GDP, educating women, leveraging technology to improve human capital productivity and outcomes, reducing loan collateral requirements, strengthening legal frameworks, and boosting banking competition by allowing entrant of capitalized financial institutions and timely exist of insolvent ones.