Background: Globalisation has brought significant benefits to countries’ industrialisation, but its impact has not been uniform. Policymakers in developing countries have increasingly focused on sound institutions’ role in offsetting the potential negative effects of an integrated economic structure. However, evidence of the mediating role of institutional quality in South Africa’s unique economic globalisation and industrial development relationship has been limited. Objective: This study had the primary objective to assess the mediating role of institutional quality within the globalisation and industrialisation nexus in South Africa. Method: The analysis used a quantitative research approach through a time series analysis, based on secondary data from 1980 to 2021. The long-run relationships between the variables were assessed through novel cointegration tests, while three different cointegration regression estimation techniques were employed to estimate the elasticities. Moreover, Toda-Yamamoto causality tests were utilised to evaluate the causal linkages between the variables. Results: The findings suggest that South Africa’s unique integration path has benefited industrial output significantly since its move to a more liberal and democratic structure. However, the level of institutional quality has contributed to a diminishing effect in this regard. This emanates primarily from a misalignment between institutional frameworks and the demands of globalisation, including increased competition and regulatory challenges. Conclusion: Based on this, the study recommends that policymakers prioritise developing a comprehensive industrial policy to promote key strategic sectors, regional integration, and public–private partnerships. Moreover, they should improve the business environment and infrastructure by means of reducing the costs of doing business, enhance the rule of law, ensure a stable financial system to attract foreign investment and foster sound regional partnerships.

Following the 2007-2009 global financial crisis, the South African Reserve Bank (SARB) prioritised financial stability. This study assesses the impact of financial stability on South Africa's output and price stability, which is crucial for framing its monetary policy. Utilising a Structural Vector Autoregression (SVAR) approach, the influence of the Financial Conditions Index (FCI) on the Gross Domestic Product (GDP) and Consumer Price Index (CPI) between 1960Q1 and 2022Q4 was analysed. Results revealed a strong connection between these objectives. GDP drops after an FCI disturbance, whereas the CPI trends upwards when the SARB counters financial imbalances. This vital finding indicates a positive relation between enhanced financial conditions and output stabilisation but reveals a trade-off between price and financial stability. After a GDP shock, financial conditions improve, but they deteriorate following a CPI shock. If the SARB reacts by "mopping up" post-crisis, the policy rate typically drops, pointing to potential financial vulnerabilities. Both GDP and CPI react positively to FCI disturbances when SARB is passive. The evidence suggests that while financial stability bolsters output stability, it might endanger price stability. Thus, amongst other recommendations, South Africa's monetary policy authorities must lean against financial imbalances instead of mopping after a crisis

Traditional approaches to predicting business cycles are limited by their omission of financial variables, which, in turn, leads to failures to signal financial-sector crises and to misestimate the duration and intensity of economic events. This study addresses this challenge by constructing a real-financial activity gap for South Africa and utilising it to predict the occurrence of economic recoveries. The study examines the period from 1970Q1 to 2023Q4, using real GDP, domestic credit, house prices, and share prices. The dynamic factor model and the Hodrick–Prescott filter are employed to construct the real-financial activity gap. The recursive ADF unit root test is used to assess the presence, frequency, and duration of economic recoveries. To validate the results, a Markov switching dynamic regression model is applied. The results reveal that the new gap tends to produce economic recovery predictions that are less frequent but longer in duration. In contrast, predictions based on real GDP lead to more frequent but shorter recoveries. The new gap suggests that financial variables contribute to stabilising growth over extended periods, whereas real GDP reflects quicker but more volatile economic adjustments. The latest gap offers a more stable basis for forecasting recoveries, aiding policymakers in better anticipating and mitigating economic downturns. Accordingly, the output gap and the real-financial activity gap should be used as complements.