Research Articles (Economics)

Permanent URI for this collectionhttp://hdl.handle.net/2263/2391

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Macroeconomic determinants of SME growth in South Africa : evidence from ARDL analysis
Adesile, Olusegun (Adonis and Abbey Publishers, 2026-06)
Using quarterly data (2009Q2–2022Q2), this study investigates the macroeconomic determinants of SME growth in South Africa through ARDL bounds testing and Granger causality. Findings show a long-run negative relationship between SME growth, unemployment, and GDP growth, while inflation and exchange rate have a long-run positive effect on SME revenue growth. Short-run dynamics indicate that GDP growth and REER both have a strong positive impact on SME revenue growth, while other macroeconomic variables are insignificant in the short run. These results highlight the need for macroeconomic stability and long-term targeted funding for SMEs in order to promote inclusive growth and job creation. THEORETICAL CONTRIBUTION/ORIGINALITY : The theoretical contribution of this study is to integrate the resource-based view with the macro-financial framework to explain how external economic conditions affect the internal growth capacity of SMEs in South Africa. Unlike previous studies, which have focused mainly on firm-level or access-to-financing constraints, this study advances the theory that macroeconomic stability through GDP growth, low inflation, job dynamics, and exchange rate behaviour creates an environment in which SMEs can use internal resources efficiently. This study employs the ARDL model to capture short- and long-term interdependencies, offering the first empirical evidence on how national macroeconomic conditions drive firm-level competitiveness and inclusive growth in emerging economies across Africa.
Corporate earnings announcements and stock market bubbles
Bouri, Elie; Can, Ufuk; Cepni, Oguzhan; Gupta, Rangan (Elsevier, 2026-09)
We examine how corporate earnings announcement shocks influence US stock market bubbles using daily data from January 1990 to June 2025. After identifying positive and negative bubbles, we derive corporate earnings announcement shocks using a heteroskedastic vector autoregression model and estimate their dynamic effects on bubble indicators using local projections, with vector autoregression-based impulse responses reported as a robustness check. Positive earnings shocks boost positive bubbles, particularly at the medium to long-term, while reducing negative bubbles at the short-term. Therefore, favorable earnings news can fuel prolonged speculative episodes by increasing investor optimism, and lead to deep crashes but mild recoveries. HIGHLIGHTS • Link stock bubbles to corporate earnings announcements using local projections. • Apply vector autoregression-based impulse responses as a robustness check. • Positive earnings shocks boost positive bubbles, notably in the medium to long-term. • Positive earnings shocks reduce negative bubbles in the short-term.
The effects of xenophobia on migrants' small businesses in South Africa
Adesile, Olusegun; Chisadza, Carolyn (Sage, 2026)
This exploratory study investigates the experiences of migrant-owned small businesses in Sunnyside and Marabastad affected by xenophobic incidents. The research aims to understand the effects of xenophobic experiences on their business performance, social capital and perceptions regarding future operations in South Africa. Using responses from a sample of 91 migrant business owners, the findings reveal that they faced financial losses and operational disruptions. The migrants also noted limited support from local businesses, in contrast to an increase in solidarity within migrant communities. Most respondents expressed a preference for enhanced security and public awareness campaigns over financial assistance, suggesting a desire for social acceptance and an enabling business environment amid their vulnerability. The findings also underscore a disconnect between the needs of migrant business owners and state support, highlighting opportunities for targeted interventions to assist migrant-owned small businesses.
Spillover and predictability of volatility of 50 major cryptocurrencies : evidence from a LASSO-regularized quantile VAR
Bonaccolto, Giovanni; Karmakar, Sayar; Bouri, Elie; Gupta, Rangan (Elsevier, 2026-07)
Previous studies examine spillover effects across the volatility of several cryptocurrencies in the mean or across quantiles without addressing the issue of high dimensionality. Using a large dataset of 50 cryptocurrencies, we employ a LASSO-regularized Quantile VAR framework and show that spillover effects differ across low, medium, and high volatility regimes, especially when evaluated dynamically over time, with sharp increases around tail events such as the war in Ukraine. Importantly, we demonstrate that the LASSO-QVAR model delivers statistically significant forecasting improvements over its univariate counterpart, underscoring the role of interconnectedness in enhancing volatility prediction across cryptocurrencies. HIGHLIGHTS • Consider a large dataset of 50 cryptocurrencies. • Use LASSO-regularized Quantile VAR model to tackle the issue of high dimensionality. • Show that the dynamic spillovers differ across low, medium, and high volatility regimes. • They exhibit sharp increases around tail events such as the war in Ukraine. • LASSO-QVAR model delivers significant forecasting improvements.
Environmental and socioeconomic factors : weather and COVID-19 cases in Cape Town
Koch, Steven F.; Mashinda, Antoinette Mujinga; Wichmann, Janine (Routledge, 2026-05)
Cape Town, a microcosm of one of the most unequal societies in the world, remains both socially and spatially segregated. In this research, we address whether or not that separation is related to recorded COVID-19 cases in the city. We estimate both the temperature and relative humidity relationship to cases, via distributed-lag nonlinear model (DLNM) components, since the relationship between environmental factors and health can be delayed. The DLNM framework describes the additional time (lag) of the exposure-response association, capturing both the nonlinear exposure-response and the delays. We also expand the discussion to include lockdown measures, their association with infections and socio-economic status in Cape Town. We find that (i) relative humidity, more than temperature, is associated with changes in reported COVID-19 risk; (ii) at relatively high temperatures (21 °C), relative case risk is lower in the low socio-economic status areas; (iii) case risk is generally higher in the same areas.
ESG environmental performance and energy sources diversification : insights from quantile regressions
Catik, A. Nazif; Inglesi-Lotz, Roula; Kuziboev, Bekhzod; Kalandarov, Feruz; Makhmudov, Samariddin; Moise Minani, Leon (Taylor and Francis, 2026-06)
This study investigates the effects of energy source diversification on countries' ESG environmental performance scores. To this aim, we use panel data from 36 developed economies covering the period from 2000 to 2018. As a novelty, in contrast with the point estimators based on OLS, we employ the recently introduced robust estimators, i.e., Method of moments quantile regression (MMQR) and instrumental variable quantile regression (IVQREG), to account for the variation in the energy diversification and environmental performance relationship across the different levels of the ESG score. The empirical results from both robust estimators support the positive effects of energy diversification on ESG environmental performance across most quantiles. However, this relationship is less significant for countries with higher environmental scores. The positive effect of diversification is more pronounced in countries with lower environmental performance. As the country reaches higher environmental performance quantiles, the impact of diversification diminishes. The results show that economic growth increases environmental performance across all quantiles. The results also suggest that although government effectiveness is an essential prerequisite for achieving environmental objectives, globalization has a negative effect on environmental quality, especially in lower ESG-score countries, as it leads to higher energy consumption. Hence, policymakers should not rely on fossil fuels but rather focus on energy sources that emit zero or negligible carbon. The transition to renewable energy requires establishing economic expertise and stability to foster the breakthroughs needed.
Herding spillover effects in US REIT sectors
Babalos, Vassilios; Ngene, Geoffrey; Gupta, Rangan; Bouri, Elie (Emerald, 2026-04-29)
PURPOSE : This study examines the sector-level herding and herding spillover across 11 US-listed Real Estate Investment Trust (REIT) sectors. DESIGN/METHODOLOGY/APPROACH : We examine herding behaviour of REITs employing returns-based methods in the context of the standard linear model, along with extensions that capture any time-varying component of herding. FINDINGS : A standard linear model shows no herding behaviour for all sectors, except for the lodging and resorts sector; whereas, a more robust quantile regression reveals significant herding in all 11 sectors and for the overall market at the lower tails of the distribution of cross-sectional return dispersion. The time-varying parameter ordinary least squares approach demonstrates spasmodic switches between herding and anti-herding behaviours during the sample period across all sectors and the overall market. A spillover analysis highlights significant and original herding spillover effects across REIT sectors. PRACTICAL IMPLICATIONS : Our results could be useful for investment management purposes since herding can drive asset price volatility to a higher level and undermine the effects of portfolio diversification. Thus, investors should pay attention to sectors that are involved in significant herding spillovers for the sake of portfolio and risk management inferences in the US REIT sectors. Regulators should monitor the developments and deploy effective policies to mitigate the effects of herding since it is widely known that herding could ultimately pose a threat to market stability. ORIGINALITY/VALUE : This study contributes to the dynamic nature of behavioural biases of investors in US equity REITs and enhances our understanding of contagious effects of herding across sectors.
Unravelling financial fragility of global markets using machine learning
Plakandaras, Vasilios; Gupta, Rangan; Ji, Qiang (Wiley, 2026)
The study investigates systemic financial risk in global markets, attributing it to geopolitical instability, climate risks, and economic uncertainties. Utilising a state-of-the-art machine learning heterogeneous panel regression framework capable of capturing cross-sectional dependencies and nonlinear patterns, we examine financial stress across multiple economies, including China, the U.S., the U.K., and 10 EU nations. Through extensive out-of-sample rolling window analysis, we show that while geopolitical uncertainty enhances short-term predictions, long-term risk forecasting is better achieved using financial and economic data. The study underscores the limitations of conventional regression models in capturing financial risk dynamics and suggests that machine learning-based panel regressions provide a more nuanced and accurate forecasting tool. The findings bear significant policy implications, highlighting the necessity for regulatory bodies to reassess risk frameworks and the role of climate-related disclosures in financial markets.
The global financial cycle (GFC) and the risk premia of the U.S. Real Estate Investment Trusts (REITs) market
Salisu, Afees A.; Rufai, Aliyu Akorede (Routledge, 2026)
Recent global financial stress highlights the need to reassess the impact on major investment vehicles. This study examines whether US Real Estate Investment Trusts (REITs) serve as defensive investment vehicles during periods of global financial stress by analyzing the impact of the Global Financial Cycle (GFC) on REIT risk premia across sectors. Our findings highlight that most REIT sectors exhibit defensive characteristics against global financial risks. A few instances in which REITs deviate from their traditional pattern also suggest possible heterogeneity in their exposure to global financial conditions. While additional analysis indicates that gold, as expected, mirrors the REITs, the contrasting behavior of conventional risky assets relative to the REITs and gold provides strong validation of the study’s outcomes. Forecasting experiments conducted indicate improved forecast accuracy for REIT risk premia using our proposed predictive model. Our findings provide robust evidence that REITs serve as defensive investment vehicles during times of global financial stress across most sectors and play a mixed role in a few others, depending on sectoral exposure and global financial conditions, offering valuable insights for portfolio diversification and risk management aligned with GFCs.
The international spill-over effects of US political signal quality: a GVAR approach
Hammed, Yinka S.; Salisu, Afees A.; Akume, Michael (Routledge, 2026)
The quality of political signals, reflecting policy clarity and credibility, remains a distinct but underexplored dimension of uncertainty in international studies. We investigate the influence of the quality of political signals (Q-index) in the United States (US) on the equity markets of 32 advanced and emerging economies using the Global Vector Autoregressive (GVAR) model, which also accounts for the macroeconomic conditions of the shock-recipient markets. We show an immediate negative impact on equity markets, with a response of about 0.15% to a one-standard-deviation shock to the US Q-index. However, we find clear asymmetry after decomposing the index into high- and low-quality regimes: low-quality shocks on average raise foreign equity prices by up to 0.12% but act slowly, whereas high-quality shocks reduce equity prices by a comparable magnitude but transmit more quickly. Both effects operate through the exchange-rate channel. Additional evidence involving the Global Economic Policy Uncertainty (GEPU) index reveals a contrasting pattern: GEPU shocks affect real equity prices directly and instantaneously, without exchange-rate mediation, highlighting the distinct transmission channel through which political signal quality operates. Our findings suggest that monetary authorities in trade-linked economies should monitor US political communication quality as a leading indicator of exchange-rate and equity-market pressure.
The dynamic impact of the energy transition on food security in developing countries
Soh Wenda, Boris D.; Pondie, Thierry Messie; Ndiaye, Aissatou; Uckert, Gotz; Lohr, Katharina; Sieber, Stefan (Wiley, 2026)
In the context of persistent food insecurity and the global push for the transition toward clean energy in developing countries, understanding the association between clean energy access and food affordability is increasingly important to inform multisectoral policy interventions. Against this background, this study explores the dynamic impact of the transition to clean cooking energy on the cost and affordability of a healthy diet in developing countries. Using recent panel data and robust estimation techniques, including quantile regression, fixed effects models, and asymmetry tests, we find that access to clean cooking fuels can, in some contexts, exacerbate food costs. The results reveal a nonlinear relationship between access to clean cooking energy and the cost of healthy diets. Specifically, in countries with the lowest levels of food costs, access to clean cooking energy improves the affordability of healthy diets, whereas in countries where diet costs are already high, the transition to clean cooking energy tends to exacerbate the cost of healthy diets. These findings underscore the need for multisectoral policy interventions that jointly address clean energy access, nutrition, and social protection to address interconnected challenges such as climate change and food insecurity.
Energy poverty and climate shocks : are changing weather patterns leaving South Africa in the dark?
Kritzinger, WiZelle; Inglesi-Lotz, Roula (Wiley, 2026)
Energy and climate change are deeply interlinked, with the latter exerting significant influence on energy demand and supply. In regions such as South Africa, where socio-economic vulnerability is high, understanding how climate change affects energy poverty is essential to achieving the Sustainable Development Goals, particularly SDG 7 (affordable and clean energy) and SDG 13 (climate action). While the climate-energy nexus has received growing attention, limited empirical work has explored how climate change affects multiple dimensions of energy poverty in South Africa using long-run time series analysis. This study addresses this gap by investigating whether climate change exacerbates energy poverty, focusing on two dimensions: electricity access and a novel indicator, the electricity cost burden growth rate. The study uses annual average minimum, mean, and maximum temperatures, along with precipitation, as proxies for climate change. It applies the Autoregressive Distributed Lag (ARDL) approach to assess long-run relationships using data from 1996 to 2023, given its suitability for small samples and mixed integration orders. The findings indicate that a 1°C increase in the minimum, mean, and maximum temperatures is associated with long-run declines in electricity access of 2.86%, 2.50%, and 2.15%, respectively. Additionally, a 1 mm increase in annual precipitation in the current period is associated with a 0.083 unit decrease in the growth rate of the electricity cost burden in the short-run, ceteris paribus. The findings highlight the need for climate-informed energy policies that address both affordability and access, offering valuable insights for South Africa and other countries facing similar climate and energy challenges.
Effects of development finance on energy transitions and geen growth in Sub-Saharan Africa
Oteng, Clement; Gamette, Pius; Nunoo, Edward Kweku; Takyi, Frederick (Wiley, 2026)
While global agendas promote energy transition and green growth, Africa south of the Sahara (SSA) struggles with low energy access, highlighting a development paradox between climate goals and energy poverty. By aligning aid and development finance with SDGs 7 and 13, we analyze whether development finance is at a crossroads in supporting green growth and energy transition in SSA. The data covers 44 SSA countries from 2000 to 2023. We use Driscoll-Kraay standard errors and linear dynamic panel-data estimation by Arellano-Bover and Blundell-Bond as robustness checks. The study reveals that official development assistance (ODA) improves access to clean cooking fuels and technologies. ODA also promotes renewable energy transition and increases carbon intensity. IMF concessional loans enhance clean cooking and carbon efficiency, while Regional Development Banks (RDB) loans have weak and mixed effects. The study calls for concessional lending programs to more explicitly integrate green growth and energy access objectives into their macroeconomic frameworks.
Impact of food inflation on household welfare in Ethiopia
Wieser, Christina; Tesfaye, Wondimagegn; Yitbarek, Eleni (Elsevier, 2026-08)
The study examines the welfare effects of food inflation in Ethiopia using the last two waves of the Ethiopian Socioeconomic Panel Survey and a difference-in-difference framework. Household specific exposure to food infaltion is measured using Laspeyres price indices constrcted from obserevd consumption baskets. The results show that food inflation significantly reduces real household consumption, with the effects concentrated in urban areas. Households exposed to above-median food price inflation between 2019 and 2022 experienced substantial decline in real per adult-equivalent consumption, while the effects in rural areas were comparativley limited. The effects are also uneven across the welfare distribution. In urban areas, consumption losses are concentrated among households in the bottom 40 percent in urban areas, whereas higher-income households are largely insulated from rising food prices. Food inflation further increases the likelihood of experiencing both consumption poverty and multidimensional deprivation among vulnerable urban households. The findings suggest that recent food price increases have disproportionately affected poorer households highlighting the importance of reforming food policy to counterbalance the effect of food price shocks. HIGHLIGHTS • Exposure to above-average food inflation significantly lowers household welfare in Ethiopia. • Urban households are more vulnerable to food price shocks than rural households. • The largest welfare losses occur among the urban bottom 40 percent. • Food inflation raises the risk of overlapping poverty and deprivation. • Policies to mitigate food price shocks can protect vulnerable households.
Social capital and protests in the United States
Chisadza, Carolyn; Clance, Matthew W.; Gupta, Rangan (Nova Southeastern University, 2025-06)
In the last decade we have witnessed rising protests in the United States associated with issues that form part of society’s social fabric that can either facilitate or break down collective behaviour. Rising social inequalities can cause people to no longer share the same values and force individuals to work against each other. This breakdown in social capital can be a key driver for protests as the marginalised attempt to voice their grievances. Using social capital data from the Social Capital Project and protest data from the GDELT Project for U.S counties, we find that higher social capital is negatively associated with different types of protests, moreso demonstrations and violent protests. At a disaggregated level, we find that collective efficacy (i.e., level of social organisation) is a better predictor of protests in relation to other types of social capital. These results remain consistent when controlling for economic and social inequalities, such as income, unemployment, and race. The findings highlight the importance of social capital in the development process, particularly in mitigating the incentives to engage in violence.
Public transport, sexual harassment, and social norms : some evidence from South Africa
Chisadza, Carolyn; Clance, Matthew W.; Nicholls, Nicky; Zawaira, Tendai (Elsevier, 2026-10)
Research has highlighted various challenges facing public transport users, particularly women. We conduct a survey of 1000 male and female public transport users in South Africa to better understand the commuting experiences of these users, including vulnerability to sexual harassment and violence. We find that women are selective in their transport modes based on safety and accessibility in relation to men. We also observe that while women witness more incidents of sexual harassment, they are also less likely to report the incidents due to fear of victimisation and the belief that no change will come about. In addition, we note that both women and men overestimate other commuters’ tolerance for sexual harassment and unwanted sexual advances in the public transport setting. This finding could be leveraged in policies highlighting that most public transport users find such behaviours unacceptable. Existing research on the positive effects on behaviour of correcting erroneous normative beliefs suggests that communicating accurate norms might reduce engagement in behaviour (such as sexual harassment) that deviates from the accepted norms. HIGHLIGHTS • Women avoid trains/buses due to safety and accessibility concerns. • Men and women overestimate others’ tolerance of harassment on transport. • Women feel significantly less safe than men across all commute stages. • Erroneous social-norm beliefs shape behaviours linked to harassment. • Communicating accurate norms may reduce harassment on public transport.
Forecasting volatility of commodity, currency, and stock markets : evidence from Markov-switching multifractal models
Liu, Ruipeng; Segnon, Mawuli; Cepni, Oguzhan; Gupta, Rangan (Wiley, 2026)
This paper adopts a bivariate Markov-switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio managers, traders, and governments. Using daily data on stock indices and FX rates from developed and emerging countries and a range of commodities such crude oil, natural gas, aluminum, copper, gold, silver, platinum, wheat, corn, soybean, and soybean oil, we find evidence of (re)correlation between commodity, FX, and stock markets. The BMSM model is very competitive to the DCC-GARCH and the MSM models at short forecasting horizons (1 up to 10 days ahead) but outperforms them at long forecasting horizons (20 days ahead and beyond). Furthermore, we show that an investor with mean-variance preferences gains in most cases the highest utility benefits based on the BMSM model.
Do shortages forecast aggregate and sectoral U.S. stock market realized variance? Evidence from a century of data
Bonato, Matteo; Gupta, Rangan; Pierdzioch, Christian (Elsevier, 2026-04)
Recent global economic and political events have made clear that shortages are a key factor driving macroeconomic and financial market developments. Against this backdrop, we studied the forecasting value of shortages for monthly U.S. stock market realized variance (RV) at the aggregate and sectoral level using data spanning the period 19002024 and 19262023 (for most sectors), respectively. To this end, we considered linear and non-linear statistical learning estimators. When we used linear estimators (OLS and shrinkage estimators), we did not find evidence that aggregate and disaggregate shortage indexes have predictive value for subsequent market or sectoral RVs. In contrast, when we used random forests, a nonlinear nonparametric estimator, we detected that aggregate and disaggregate shortage indexes improve forecast accuracy of market and sectoral RVs after controlling for realized moments (realized leverage, realized skewness, realized kurtosis, realized tail risks). We then decomposed RV into a high, medium, and low frequency component and found that the shortages indexes are correlated mainly with the medium and low frequencies of RV. Finally, we found that the predictive value of shortages for RV was larger in the 1980s and 1990s than in later parts of our sample period. HIGHLIGHTS • Uses shortages to forecast aggregate and sectoral U.S. stock market realized variance. • Studies data spanning 19002024 and 19262023 (for most sectors). • Estimates random forests to recover forecasting value of shortages. • Controls for realized moments and other common predictors. • Predictive value of shortages has decreased in later parts of the sample period.
Return-volatility nexus in the digital asset class : a dynamic multilayer connectedness analysis
Bouri, Elie; Foglia, Matteo; Karmakar, Sayar; Gupta, Rangan (Wiley, 2026-04)
Based on the rationale that returns and volatility are interrelated, we apply a multilayer network framework involving the return layer and volatility layer of cryptocurrencies, NFTs, and DeFi assets over the period January 1, 2018–January 23, 2024. The results show significant connectedness in each of the return and volatility layers, with major cryptocurrencies such as Bitcoin and Ethereum playing a central role. Large spikes in the level of connectedness are noticed around COVID-19 pandemic and Russia–Ukraine conflict, and Bitcoin and Ethereum emerge as net transmitters of returns and volatility shocks, emphasizing their significant role around these crisis periods. Notably, a strong positive rank correlation exists between the return and volatility layers, highlighting the significant risk–return relationship in the digital asset class. The findings suggest that economic actors should not ignore the interconnectedness between the return and volatility layers in the system of cryptocurrencies, NFTs, and DeFi assets for the sake of a comprehensive analysis of information flow. Otherwise, a share of the information flow concerning the return–volatility nexus across these digital assets would be missed, possibly leading to inferences regarding asset pricing, portfolio allocation, and risk management.
Sustainability uncertainty and the stock market volatility in advanced and emerging markets : the role of the oil orientation of countries
Salisu, Afees A.; AbdulHakeem, AbdulHameed; Raddaoui, Mounira (Elsevier, 2026-06)
We provide new evidence on the relationship between sustainability uncertainty and stock market volatility, focusing on two channels of transmission: level of development and oil orientation. We categorize markets into advanced and emerging economies, and oil-producing and non-oil-producing countries. Our findings show that the relationship varies significantly. Oil-producing countries exhibit a notable sensitivity to sustainability-related uncertainty, particularly during heightened uncertainty, while emerging markets respond more to it, seeking higher expected returns. In contrast, developed markets show weaker or opposing reactions. We suggest that empirical research should consider countries' oil orientation and the level of development when analyzing climate-related shocks in financial markets. Our results highlight the need for distinct market classifications and underscore the importance of market development in shaping responses to sustainability uncertainty, advocating coordinated global efforts to reduce it.

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