Purpose This paper aims to explore the role of two transmission channels between “green” transition and (overall and core) inflation, the so-called “greenflation” in the USA. The first channel is related to the “green” macroeconomic characteristics, and the second channel is associated with the “green” banking/financial characteristics of the US economy. Design/methodology/approach The empirical analysis spans the period 1990–2023, while it uses two-stage least square regressions and causality tests. The analysis is conducted across the full sample and sub-periods to assess robustness and structural shifts. Findings The findings through regression estimates and causality tests, clearly document that both channels (fiscal spending on renewables and “green” credit) impact inflation, validating the effect of “green” transition on inflation, with the “green” credit channel having the strongest effect, followed by the mechanism of “green” fiscal spending. Originality/value To the best of the authors’ knowledge, this study is the first to determine the primary channels through which the “green” transition impacts inflation. It offers first-time evidence on the role of fiscal spending on “green” transition and “green” credit on inflation.
Purpose This study aims to investigate the impact of geopolitical risk on selected energy and precious metal commodities, namely WTI crude oil, Brent crude oil, natural gas, gold and silver. Design/methodology/approach The study uses a Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity Mixed Data Sampling (DCC GARCH MIDAS) model to examine the relationship between geopolitical tensions and commodity price volatility. This framework enables the integration of lower-frequency geopolitical risk measures with higher-frequency commodity price data, providing a nuanced view of their dynamic linkages. Findings The results confirm that energy commodities, particularly the two benchmark crude oils (WTI and Brent), are highly sensitive to geopolitical uncertainty. The strongest positive correlation between geopolitical risk and oil prices is observed during the Russia–Ukraine invasion. In contrast, gold and silver exhibit relatively low correlations with geopolitical risk and their price responses appear to be more event-specific. Originality/value This study contributes to the literature on geopolitical risk by jointly examining its effects on both energy commodities and precious metals. The findings show that gold’s hedging capacity is not consistently effective, as its role as a hedge appears to depend on the nature of the geopolitical event. Overall, the results provide useful insights for risk management in periods of heightened geopolitical uncertainty.
Purpose This study aims to explore the role of green finance in achieving a cleaner environment. More specifically, it examines the short- and long-run impacts of green finance on environmental degradation. Design/methodology/approach This study uses balanced panel data for a selected set of seven BRICS + nations, covering 2000–2023. It uses a panel Autoregressive Distributed Lag (ARDL) or a pooled mean group (PMG) model to assess the impact of green finance on ecological footprint (EFP). The panel ARDL model provides long- and short-run coefficients and an error-correction term, clearly showing the dynamics of the relationship between green finance and environmental sustainability. Findings The findings reveal that green finance significantly and negatively affects the EFP in the long run, but has no such impact in the short run. As green finance supports environmentally friendly investments in an economy, it can reduce harmful environmental emissions over time, but because these projects require longer gestation periods, the beneficial impact on the environment does not appear in the short run. Research limitations/implications Green finance plays a crucial role in the green transformation of the financial system by promoting environmentally friendly investments. Green finance instruments such as green bonds, sustainability-linked loans and carbon credit financing are valuable for financing environmentally friendly projects and reducing EFPs. Originality/value This study adds to existing literature on green finance by exploring its impact on EFP. Research on this field is relatively scarce in the existing literature for BRICS+.
Purpose This paper aims to examine whether the forces linking financial markets to real economic activity operate differently across business cycle phases, using quarterly US data from 1990 to 2024, spanning four recession episodes. Specifically, the author asks whether the mechanism that normally keeps equity markets anchored to corporate earnings and real output remains stable between expansions and recessions and what the accumulated output cost is when that mechanism breaks down. Design/methodology/approach The author first estimates a vector error correction model among real gross domestic product (GDP), the S&P 500 Total Return Index and Earnings Per Share, using cointegration tests to identify the long-run equilibrium structure and controlling for monetary policy, consumer confidence, market uncertainty and real GDP expectations. The author then extends this to a Bayesian Markov-Switching vector error correction model that holds the cointegrating vectors constant while allowing adjustment dynamics and shock covariance structures to vary across regimes, with regime identification anchored to NBER recession dates. Findings The author identifies two stable long-run equilibria anchored by earnings per share. This study finds that the stock market index self-corrects toward its earnings equilibrium in normal expansions, while in recessions, the adjustment coefficient linking the stock market index to earnings reverses sign, with the index moving further from earnings fundamentals; as the Granger causality tests detect predictive content from stock returns and earnings growth to GDP growth but not in the reverse direction, no offsetting predictive force is found within the estimated system. The accumulated output cost amounts to 1.78 percentage points of cumulative GDP growth deficit by quarter 20 following a recession onset. Originality/value The author provides direct evidence that the corrective mechanism linking the stock market index to its long-run earnings equilibrium is regime-dependent, reversing during recessions in a way that has not previously been documented within a regime-switching cointegration framework.
Purpose This study aims to detect speculative price bubbles in major cryptocurrencies and NFT indices and measure how sentiment from the cryptocurrency market, NFT market and broader equity market uncertainty transmits across these digital assets.Design/methodology/approach Using daily data from May 6, 2021, to March 1, 2024, this study examines the dynamic price changes in Bitcoin (BTC), Ethereum (ETH), the NFT Blue-Chip Index (BCI) and the NFT Potential Index (PNI). Bubble episodes are identified via the Backward Supremum Augmented Dickey-Fuller (BSADF) procedure. To model dynamic spillovers between returns and sentiment, a vector autoregression (VAR) is estimated incorporating equity-market volatility (VIX), the crypto Fear and Greed Index and NFT/market sentiment indicators.Findings Findings reveal various speculative bubble episodes in BTC, ETH and the NFT BCI, indicating recurrent boom-burst dynamics in core crypto and mature NFT segments. VAR estimates show significant sentiment and risk transmission across markets. BCI generates a significant positive spillover to BTC and ETH returns, suggesting that mature NFT activity can act like a multiplier on the normal boom-bust pattern of BTC/ETH by adding extra momentum into crypto returns. Market sentiment is significantly negatively associated with subsequent ETH returns, consistent with short-run corrections after optimism. Finally, VIX and NFT sentiment are significantly linked to NFT index movements, and the NFT Potential Index (PNI) is particularly sensitive to broader risk conditions and NFT-specific sentiment.Practical implications Findings provide useful information and strategy recommendations for investors, portfolio managers and financial regulators in digital assets. Investors should monitor NFT sentiment and market volatility as indicators of price dynamics in cryptocurrency markets.Originality/value Through an in-depth analysis of the relationship between the sentiment indicators of the stock market, the NFT market and the cryptocurrency market, this paper supports the transmission effect mechanism of market sentiment among different markets.
Purpose This study aims to examine how perceived control is associated with retail investor behavior in high-variance cryptocurrency markets. It develops a moderated-mediation framework in which overconfidence, operationalized as calibration error, transmits the effects of perceived control to trading frequency, portfolio concentration, risk-taking and net investment performance, while realized volatility conditions the strength of these relationships. Design/methodology/approach This study uses a theory-calibrated simulated panel of 1,000 heterogeneous investors. Standardized linear models, interaction terms and bootstrapped indirect-effect estimates are used to assess internally coherent, design-implied relationships under explicitly maintained assumptions. The analysis is intended as a transparent structural pattern check rather than as a causal estimate derived from observed brokerage or exchange data. Standardized coefficients are subsequently translated into practically interpretable indicators, including portfolio turnover, the Herfindahl–Hirschman index and drawdown exposure. Findings Within the simulated environment, higher perceived control is associated with more frequent trading, greater portfolio concentration, higher risk-taking and weaker net performance. Overconfidence partially mediates these relationships, reducing the magnitude of the direct coefficients once calibration error is introduced. Realized volatility strengthens both the direct associations between perceived control and investor behavior and the indirect pathways operating through overconfidence. The findings indicate that behavioral vulnerabilities linked to perceived control may become more consequential when market variance increases. Originality/value This study integrates perceived control, overconfidence and market volatility within a unified moderated-mediation framework and connects standardized behavioral relationships to platform-relevant risk metrics. It also derives design implications, including volatility-adaptive trading throttles, leverage gating, calibrate-before-trade prompts and cost-salience panels. By clearly separating simulation-based theoretical validation from empirical causal inference, this study provides a reproducible foundation and an external-validation roadmap using brokerage panels, exchange records and event-based quasi-experimental designs.
Purpose The purpose of this study is to examine the specific relationships across various forms of climate-related events and assorted segments of the energy market in diverse geographic regions in the US. Design/methodology/approach Numerous wavelet coherence analyses inspect the co-movements of 15 key energy economic indicators (average price, production, and consumption estimates of oil, gasoline, coal, electricity, natural gas, renewable energy, wood and biofuels) and diverse climate-related events (temperature-related, precipitation-related and wind-related incidents), in 12 US states (in the Gulf Coast, the West Coast, the East Coast, a Southern Plains state and a Pacific Islands state), and along 53 years, from 1970 until 2022. Findings This study’s tests have repeatedly uncovered periodic though robust co-movements of energy price, production and consumption indicators and extreme weather incidents that continued for a number of years at a time. Many of the co-movements detected are well synchronized, where in various instances, severe weather episodes led the progressive changes in energy indicators. Research limitations/implications Although robust association is established, no causality is declared. Practical implications Regulators, policymakers, investors, rating agencies and predominantly energy market participants can extract valuable insight from the empirical evidence found concerning different states, geographic areas and types of climate events. Originality/value This study examines the miscellaneous relationships through a granular approach by isolating particular regions and states in the US, different types of climate events and risks, and diverse forms of energy indicators. It contributes to stakeholders in this realm by identifying specific weather exposures and thus guide protective measures suitable for unique circumstances.
Purpose This paper aims to show that innovation does not exclude the possibility of risk minimisation. Design/methodology/approach The axiomatic model presented is a modification of a two-period financial economy with corporations in which real market activities are coordinated by the financial market and risk is seen through the prism of utility theory. Assuming that in an initial period, it is known what new commodities or what new assets will appear on the market in a second period and what their prices in every state will be, the complete financial market is considered. Findings It is shown that in the considered economy, under the assumption that every consumer is risk-averse as well as total endowments are not the sources of risk, there is a Pareto optimal allocation in which the plan of every consumer is risk-free. The proposed measure of risk is coherent, in some cases, with one of those used in practice. Originality/value The results provide new insights into the possibility of risk aggregation leading to its minimisation, on the basis of analysis of a newly specified two-period economy with a financial market of bonds and equity contracts.
Purpose This study aims to examine how informal institutions, particularly social trust, shape firms' corporate social engagements (CSE) across countries, and how this relationship is moderated by the strength of formal institutions.Design/methodology/approach The authors use OLS regressions with firm-, year- and industry-fixed effects as our baseline empirical specification. To address potential endogeneity concerns, they complement the baseline analysis with instrumental-variable (2SLS) estimations that exploit exogenous variation in social trust driven by historical and cultural factors that predate contemporary corporate behavior. The final sample comprises 21,563 firm-year observations across 20 countries. Firm-level financial and ESG data are obtained from the Refinitiv Eikon (formerly Thomson Reuters Eikon) database. Social trust is measured using panel data from the World Values Survey, which provides cross-country, time-series data on generalized trust across societies.Findings Higher levels of societal trust significantly reduce firms' participation in CSE activities. Moreover, the moderating analysis shows that trust and formal institutions interact to shape CSE, with trust exerting a stronger influence in institutional environments with more developed legal protections. These results highlight the dual roles of informal and formal institutions in corporate strategy, both as substitutes and complements. The findings imply that trust is particularly effective in substituting for weak or moderately developed institutions, but once institutional quality is very strong, trust's marginal role fades.Originality/value By focusing on social trust as a key determinant of CSE across countries, this study extends the literature on the institutional foundations of corporate behavior. To the best of the authors' knowledge, it is among the first to demonstrate that trust - an informal institution - can reduce the strategic necessity of CSE by reinforcing implicit contracting, thereby complementing or substituting formal governance mechanisms depending on institutional strength. Existing studies have mainly overlooked this view and have primarily focused on firm-specific drivers (e.g. governance, profitability, stakeholder pressure) and formal regulatory environments.
Purpose This study aims to investigate how market concentration and business-cycle conditions shape bank profitability across developing and emerging economies. Beyond their individual effects, it examines whether market concentration moderates profitability's procyclicality and whether this moderation varies by income group.Design/methodology/approach Using aggregate banking-sector data for 118 developing and emerging economies over 2000-2021, the authors estimate dynamic panel models with interaction terms between concentration and cyclical indicators. The authors use the generalized method of moments (GMM) to address endogeneity, unobserved heterogeneity and profit persistence. Robustness checks include alternative concentration measures (five-bank concentration ratio [CR5]) and business-cycle dummies.Findings Bank profitability is procyclical on average - rising during economic upturns. However, the concentration-cycle nexus is development-contingent: in high- and middle-income economies, greater concentration dampens procyclicality, consistent with the concentration-stability hypothesis; in low-income economies, higher concentration amplifies cyclicality, pointing to weaker institutional capacity and governance. These results remain stable across alternative specifications and proxies, including CR5 and business-cycle dummies.Originality/value The study provides large-scale cross-country evidence that the profitability effects of concentration depend on a country's level of development and financial structure. By combining a long panel with GMM estimation and explicit income-group heterogeneity, it clarifies when consolidation is stabilizing versus destabilizing. The findings offer actionable guidance for competition policy, prudential calibration and governance reforms aimed at strengthening financial resilience in diverse institutional settings.
Purpose This study aims to investigate whether family firms are more resilient than non-family firms and seeks to identify the main determinants of corporate resilience. Design/methodology/approach Using panel data analysis, this study examines a sample of listed firms in a small European country with a bank-based financial system over the period between 2010 and 2023. Findings The results show that family firms are more resilient than non-family firms, except for one resilience proxy, suggesting that managers contribute to the resilience of family firms, that the market recognizes the value in this kind of company, and that family firm shareholders have specific goals that go beyond profitability. The findings also indicate that liquidity, capital structure, revenue streams, board gender diversity, board size, CEO duality and firm size significantly influence the resilience of family businesses. Additionally, the results provide some support for the pecking order theory. Originality/value This study contributes to the literature on family business resilience by examining a relatively understudied context, Portugal, and by identifying firm-specific determinants of resilience. The findings offer relevant insights for both managers and researchers.
Purpose - This study aims to investigate tail-dependent risk spillovers between the Dow Jones Best-in-Class World Index (DJSI) and major asset classes - global equities (MSCI World Index), gold, Brent crude oil, bonds (S&P 500 Bond Index) and Bitcoin - and derive hedging and portfolio implications. Design/methodology/approach - Daily price data from April 30, 2015 to May 19, 2025 are analyzed using the quantile-on-quantile (QoQ) connectedness framework developed by Gabauer and Stenfors (2024), which captures directional spillovers across specific quantile pairs in non-normal, asymmetric return distributions. Findings - The DJSI shows stronger direct quantile connectedness than reverse quantile connectedness with all assets except Bitcoin. Connectedness is pronounced in lower and upper quantiles (except for equities, where it is consistently high across quantiles). The DJSI acts as a net shock transmitter in extreme quantiles, while oil, equities and gold transmit shocks in median quantiles. Economic, political and social events - such as oil price shocks, the US-China trade war, the COVID-19 pandemic, Russia's invasion of Ukraine, the Israel-Hamas conflict and Trump's tariff policies - have significantly influenced both direct and reverse connectedness among markets. The DJSI enhances pairwise and multiasset portfolio diversification, providing hedging against bonds, gold and Bitcoin. Research limitations/implications - Although the study spans a relatively long period that includes multiple crises, the specific time frame and selected events may not fully capture longer-term structural shifts or future unprecedented shocks. Results may be partially period-specific. Practical implications - Institutional investors seeking environmental, social and governance compliant diversification may benefit from overweighting sustainable assets, particularly in extreme risk scenarios, where these assets appear to amplify risk transmission during market turmoil yet also provide protection when traditional assets are under distress. This dual role reinforces their value in robust, resilience-oriented portfolio construction. Furthermore, policymakers and central banks should incorporate sustainability-linked assets into macroprudential surveillance frameworks, taking into account their spillover potential when designing crisis response measures. Originality/value - This study provides one of the first QoQ connectedness analyses integrating the DJSI with equities, commodities, bonds and cryptocurrencies, revealing tail risks, event-driven asymmetries and portfolio strategies overlooked in prior studies.
Purpose This study aims to examine how firms' pricing power, captured through markups, shapes their exposure to downside risk in the context of global value chain restructuring and heightened macroeconomic and geopolitical uncertainty.Design/methodology/approach This study uses a panel data set of firms from 31 countries over the period 2002-2022 and assess how markups interact with external shocks to influence downside risk. Sectoral heterogeneity and the moderating role of geopolitical risk (GPR) are explicitly analysed.Findings Results show that firms with higher markups experience significantly lower downside risk, indicating that pricing power acts as an internal risk-hedging mechanism. This buffering effect is weaker in the energy sector, reflecting structural rigidities unique to that industry. Moreover, the authors find that elevated GPR strengthens the protective role of markups, suggesting that geopolitical uncertainty enhances the strategic value of pricing power.Originality/value This study provides novel evidence on the risk-management role of markups, demonstrating their dual function as both a measure of competitive advantage and a financial resilience tool. By highlighting industry heterogeneity and the amplifying effect of geopolitical uncertainty, the study contributes new insights into how firms can adapt financial strategies to navigate increasingly volatile global environments.
PurposeThis study aims to examine whether sentiment polarity or public attention conveys informational value for Bitcoin return and volatility dynamics by separating human-generated signals from automation-driven amplification.Design/methodology/approachThe analysis uses more than sixteen million Bitcoin-related tweets, classifies accounts into human-like and automation-like groups and constructs separate sentiment and attention indices. These indicators enter a multi-stage empirical framework comprising return-prediction models, GARCH-X volatility estimation and VAR-based return-attention dynamics across volatility regimes.FindingsPolarity-based sentiment, hype, anxiety and divergence exhibit no predictive power for returns across all specifications. Public attention, however, significantly amplifies conditional variance and improves GARCH-X model performance while offering no directional content for returns. VAR and Granger causality show that attention reacts to price shocks rather than forecasting them. Automation-like accounts dominate the dataset and dilute polarity signals, whereas attention remains robust as a behavioural intensity measure.Originality/valueThe study demonstrates that attention, not textual polarity, drives short-horizon volatility in cryptocurrency markets and provides a refined empirical framework for modelling digitally mediated market behaviour.
PurposeTthe British National Balancing Point (NBP), Dutch Title Transfer Facility (TTF), Trading Hub Europe (THE) and Italian Punto di Scambio Virtuale (PSV) - under low- and high-volatility regimes. This study aims to uncover how shock transmission patterns shift across stress and stress-free periods.Design/methodology/approachThe empirical strategy is structured in three complementary stages. First, a Markov switching model is employed to estimate the likelihood of the system being in either a low-volatility or a high-volatility regime. Second, a time-varying parameter vector autoregressive (TVP-VAR) connectedness approach is applied to capture structural changes in the data while avoiding the information loss that can result from arbitrary subsample selection or rolling-window estimation. Finally, a quantile-VAR connectedness framework is implemented to measure nonlinear and asymmetric spillovers across different market conditions.FindingsFindings show that connectedness among European natural gas markets intensifies markedly in high-volatility regimes. In low-volatility periods, TTF acts as a net shock receiver, whereas NBP, THE and PSV serve as net transmitters. During high-volatility regimes, all markets except PSV shift to net receivers. Connectedness surges during major global events, underscoring the markets' vulnerability to systemic shocks. The quantile-connectedness results show particularly strong connectedness in bearish (lower-quantile) conditions. Before COVID-19, TTF and THE acted as net transmitters, while NBP and PSV served as net receivers regardless of market conditions. However, European natural gas markets' roles as shock transmitters or receivers were significantly influenced by the pandemic, Russia-Ukraine conflict and Israel-Palestine conflict.Practical implicationsUnderstanding how shock transmission varies across volatility regimes provides valuable insights for market participants. Market participants (including traders and portfolio managers) should recognize that interdependence among European gas hubs intensifies during turbulent periods, and that the directional magnitude of transmission of shocks among European hubs evolve over time. For investors, awareness of how shocks propagate across markets under different market conditions (bullish or bearish) can enhance hedging efficiency and portfolio diversification. For regulators, the results highlight the importance of closely monitoring the TTF hub, which plays a central role in shaping the dynamics and systemic risk of the European gas market.Originality/valueThis paper contributes to the literature by providing a novel examination of interconnectedness among major European natural gas markets across different volatility regimes. Unlike previous studies that assume constant relationships, this paper integrates a Markov switching framework with a TVP-VAR and a quantile-VAR connectedness approach to capture regime shifts, time variation and nonlinear spillovers simultaneously. By distinguishing between low- and high-volatility periods, the study reveals how shock transmission patterns change during stress and tranquil market conditions. The analysis also relies on the impact of major geopolitical and global events on the connectedness across European natural gas hubs.
PurposeThis paper examines the relationship between financial development, green energy security, and income inequality for emerging and developing economies.Design/methodology/approachThe authors use dynamic panel quantile regression with nonadditive fixed effects for a sample of 112 emerging and developing economies spanning from 2001 to 2021.FindingsThe findings demonstrate that financial development has a nonlinear relationship with income inequality. The interaction term between financial development and green energy security indicates that there is an inverted U-shaped relationship.Originality/valueLimited studies have investigated the combined impact of financial development and green energy security on inequality. The majority of previous research has focused on the relationship between financial development and inequality or the relationship between energy security and inequality. The combined impact of these two variables on income inequality has not been examined in previous studies.
Purpose This study aims to analyze the behavior of volatility connectedness among green exchange-traded funds (ETFs) and cryptocurrency markets. The study also examines the hedging effectiveness between green ETFs and cryptocurrencies. Design/methodology/approach This study uses a Time-Varying Parameter Vector Autoregression (TVP-VAR) model to highlight the salient facts of volatility connectedness between green ETFs and cryptocurrencies during the period 22 / 10 / 2021–05 / 01 / 2024. Findings The empirical findings reveal that cryptocurrencies (particularly, Bitcoin and Ethereum) consistently act as net transmitters of shocks, amplifying systemic risk during crisis periods. However, green ETFs primarily behave as net receivers, providing a conditional and modest hedging or safe-haven role. Portfolio-level analyses indicate that green ETFs (especially ICLN) help reduce overall portfolio risk within Minimum Variance Portfolios (MVP) under turbulent market conditions, enhancing risk-adjusted returns when included alongside cryptocurrencies. Conversely, cryptocurrencies contribute to substantial diversification benefits in terms of Minimum Correlation (MCP) and Minimum Connectedness Portfolios (MCoP) but exhibit higher volatility and tail-risk exposure. Dynamic Sharpe ratio analysis further demonstrates that no single allocation dominates across market regimes; instead, adaptive strategies – switching between MVP during calm periods and risk-parity portfolios (RPP) during crises – yield superior performance. These findings underscore the conditional stabilizing role of green ETFs and the dominant diversification and risk-transmission role of cryptocurrencies, highlighting important implications for portfolio management, sustainable investment and regulatory oversight in integrated digital and green finance markets. Practical implications The empirical findings offer insightful implications for policymakers, regulatory authorities and investors to promote sustainable and strategic allocation, as well as support and expand sustainable investment markets. Originality/value This study explores if and to what extent cryptocurrencies could be linked to green ETFs. It also examines the diversification and hedging features of green ETFs for portfolio including Bitcoin and Ethereum given the ongoing debate regarding the effective hedging instruments for cryptocurrency portfolios.
PurposeThis study aims to propose a new perspective on identifying herd behavior at the market-wide level by using panel data analysis on 56 countries around the globe.Design/methodology/approachTraditional herding detection models at the market-wide level are based on time series analysis of return variations and market returns to capture trading behavior within an individual country. The authors augment four widely used herding detection models, those are the models of Chang et al. (2000), Yao et al. (2014) and Bui et al. (2017), by using panel data analyses with fixed effects for the entire 56 countries.FindingsThe authors confirm the existence of herd behavior in all 56 countries and within 33 developing markets. Interestingly, anti-herd behavior is present among 23 developed markets. Herd behavior is more dominant during down and crisis periods, whereas anti-herd behavior disappears. Severe herd behavior is the most prominent during the crisis period. In addition, the results demonstrate economic significance. An increase of one standard deviation of the return squared (as a proxy for herding) decreases return dispersion by 0.0466, accounting for 6.8544% per annum relative to the cross-sectional absolute deviation. The economic significance is more amplified to 17.9172% per annum and 1,590.15% per annum over the negative market return and the financial turmoil periods, respectively. All of these support herd behavior in global equity markets.Practical implicationsInvestors and fund managers could design profitable investment strategies based on these premises. Policymakers and regulators could monitor investment performance and improve market efficiency.Originality/valueFirst, the authors propose a different approach to investigating herd behavior by using panel data on international equity markets rather than focusing on time series data from a single country, as prior research has done. This fills the gap left by prior mixed findings on the existence of herd behavior at the individual country level. Second, the authors compare the efficacy of the aforementioned four well-known herding detection models found in empirical research and find that each model possesses relatively similar power to detect herd behavior in international equity markets.
Purpose This study aims to examine the impact of the increasing adoption of a commercial approach on the financial performance and outreach of microfinance institutions (MFIs). Drawing on institutional theory, it investigates whether commercialisation enhances MFIs’ financial performance and outreach while also considering the risk of mission drift. Design/methodology/approach A two-step system generalised method of moments estimation is applied to a dataset of 2,102 MFIs across 114 countries over a 15-year period. The study evaluates both traditional financial performance measures, such as return on assets and operational self-sufficiency, and outreach indicators, including number of active borrowers, average loan size (ALS) and new measures, such as market share of borrowers (MSB) and market share by assets (MSBA). Robustness checks, including the Arellano–Bond and Hansen tests, confirm the validity of the instruments and the reliability of the results. Further, the authors conducted mean difference tests to confirm the results. Findings Results show that commercialisation has no significant effect on the financial performance of MFIs. However, commercialisation is positively associated with breadth of outreach, as reflected in an increased number of active borrowers and with the depth of outreach, as reflected in larger ALSs. The increase in ALS suggests a shift away from serving the poorest clients, indicating mission drift. Additional results reveal that overall, commercial MFIs are moving towards larger scale and profitability but with reduced focus on their traditional social mission. Originality/value This paper extends the debate on commercialisation and mission drift in microfinance by using a large cross-country data set and multiple outreach measures, going beyond previous region-specific studies. It challenges the effectiveness of new outreach indicators such as MSBA in dynamic panel models and highlights the trade-offs between social and financial goals. The findings provide valuable implications for policymakers and practitioners, suggesting the need for frameworks that encourage MFIs to balance legitimacy, scale and sustainability with their original poverty alleviation mission.
