This study analyses the determinants of micro and small enterprise survival in a high-poverty setting, drawing on a longitudinal cohort of 1,861 firms registered under REMYPE in Cajamarca province, Peru, where monetary poverty affects 44.5% of the population (2015–2024). Using Kaplan–Meier curves and Cox proportional hazards regression, we assess how firm size, geographic location, and economic sector shape closure risk over time. Firm size is the dominant determinant: microenterprises face a substantially higher closure risk than small enterprises, a gap that persists despite REMYPE benefits. Geographic location shows no significant effect, while the economic sector exerts a substantial influence, with essential services proving more resilient than discretionary ones. Closures cluster in the post-pandemic period rather than during the pandemic, consistent with a delayed crisis. The findings indicate that, under structural poverty, standard support mechanisms are insufficient and differentiated, size- and sector-sensitive policies are required.
This study combines institutional theory with the capability perspective to investigate how the institutional characteristics of export markets served by firms from a post-transition economy affect their export performance. We analyse a dataset of 500 exporting firms from Poland, a post-transition economy, by using regression analyses. This research aims to explore how the relative institutional maturity of a firm’s export markets affects performance, as well as to establish the moderating role of managerial capabilities and export intensity for this performance effect. Relative institutional maturity is negatively associated with export performance only for exporters characterised by both low managerial capabilities and low export intensity. For firms with greater export exposure, this negative effect disappears, suggesting that accumulated international involvement may partly offset the challenges of operating in more institutionally mature markets.
Foreign Direct Investment (FDI) has emerged as a pivotal force in the economic development trajectory of emerging economies, catalysing growth, technological transfer, and global integration. The World Investment Report of 2025 states that, as of 2024, 57.5% ($867.2 billion) of all global FDI inflows went to emerging economies, up from just 16.4% ($222.7 billion) in 2000. The existing literature on FDI determinants mostly uses the multiple regression approach. However, we employ a novel approach using Interpretive Structural Modelling (ISM) coupled with MICMAC analysis. This qualitative methodology provides a holistic understanding of the hierarchical relationships and interdependencies among FDI drivers. A key finding of this study is that the three most significant factors influencing FDI in emerging economies are political stability, corruption, and the state of infrastructure. These factors significantly impact all other drivers in the system. The drivers were categorised into clusters using MICMAC based on their dependence and driving power.
Recent literature reveals that economic complexity (EC) has important implications for shadow economy and has generated mixed empirical conclusions. This paper contributes to this debate by investigating the nonlinear and asymmetric effects of EC on shadow economy in 28 Africa countries between 1995 and 2020. Granger and Yoon’s (2002) approach is used to decompose the EC into positive and negative components, while the dynamic panel threshold regression, two-step system generalised method of moments, pooled mean group, augmented mean group, and common correlated mean group are employed as the estimation techniques. The results indicate that positive EC shocks reduce the size of the shadow economy, whereas negative shocks contribute to the growth of informality, thus suggesting the presence of asymmetry. The threshold of economic complexity was found to be 0.41.
This study examines short-term return forecasting for Bitcoin, Ethereum, and Litecoin over 2020-2024, comparing autoregressive benchmarks with Kitchen Sink and VARX-type models using point and density accuracy measures supported by Diebold-Mariano and Model Confidence Set inference. The results demonstrate that the AR(1) benchmark and parsimonious specifications incorporating cryptocurrency-specific variables consistently outperform the more elaborate linear frameworks considered, while the inclusion of macro-financial predictors offers limited benefits. Findings highlight the robustness of autoregressive dynamics for short-term cryptocurrency forecasting and underscore the importance of parsimony over model complexity. These results are consistent with a market environment characterised by high structural uncertainty, sentiment-driven trading and rapidly shifting regimes, in which additional macro-financial information contributes little to forecastability beyond short-run return momentum and crypto-specific volatility.
This study examines how aggregate market liquidity influences the cross-section of Indian equity mutual fund returns through two mechanisms: (1) funds' long-run exposure to liquidity risk, and (2) managers' time-varying liquidity timing. Using a comprehensive sample from 2007-2024, we estimate rolling liquidity betas, form portfolios sorted by liquidity exposure, and compute a high-minus-low liquidity--beta return spread. The liquidity premium is positive and economically meaningful in tranquil and recovery regimes, but weakens or vanishes during systemic stress, consistent with state-dependent liquidity pricing. Adding a traded equity-liquidity factor to standard benchmarks explains a meaningful portion of the spread, while an independently constructed timing factor captures an additional 55%-64%, highlighting the importance of conditional beta management. Timing effects are concentrated among high-liquidity-beta funds, smoothing returns in normal markets but offering limited protection in crises. Findings are robust to alternative benchmarks, flow-adjusted timing specifications, and post-COVID subperiod definitions.
This study compares the relationships between Bitcoin and Ethereum's energy consumption and price dynamics. Using daily frequency data, Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), ARDL cointegration tests, and Toda-Yamamoto causality analysis were applied to evaluate the effects of cryptocurrency markets on energy demand from both short-term and long-term perspectives. The results indicate that there is a long-term cointegration relationship between energy consumption and prices for Bitcoin, and also unidirectional causality from prices to energy consumption. In contrast, ARDL boundary test results for Ethereum revealed no long-term relationship, and causality analysis also failed to detect any directional causality between price and energy consumption. This indicates that with Ethereum's transition to a Proof-of-Stake mechanism, energy consumption has become independent of price movements. The findings reveal that the effects of crypto-currency markets on the energy economy vary according to technology-specific structural characteristics.
ESG has attracted widespread attention in China’s capital markets. This study investigates the impact of corporate executives’ political connections on firms’ ESG performance in China. Using panel data from A-share listed companies between 2009 and 2022, this study empirically tests whether politically connected executives influence ESG ratings. The results show a significant positive association between political connections and ESG scores. Mechanism analysis reveals that such connections improve ESG performance by enhancing media scrutiny, alleviating financing constraints, and increasing access to government subsidies. To address endogeneity concerns, we employ Two-Stage Least Squares (2SLS) regression, confirming the robustness of the findings. These results highlight the role of political capital in promoting sustainable corporate practices.
‘Productivism’ refers to an approach that prioritises the dissemination of productive economic opportunities throughout the entire economy and segments of the labour force. It differs from what has come to be called ‘neoliberalism’ by assigning governments and civil society significant roles in achieving this goal. Productivism puts less faith in markets and is suspicious of large corporations. It emphasises production and investment over finance and the revitalisation of local communities over globalisation. It also departs from the Keynesian welfare state by focusing less on redistribution, social transfers, and macroeconomic management, and more on creating economic opportunity by working on the supply side of the economy to create good, productive jobs for everyone. This article relates the contemporary labour market problems of advanced economies to the dualism literature in economic development, which focuses on the divergence between ‘modern’ and ‘traditional’ segments within poor economies. It then highlights the nature of the new challenges and why established models of economic growth and Keynesian social welfare need to be updated. It describes new modes of industrial policy required to deal with these challenges and questions whether our governments are up to it. It also discusses how the elements of this new strategy are drawing support from both sides of the political spectrum.
Increasing income inequality has raised concerns about social cohesion, yet the subjective dimension of inequality and its relationship to trust remain underexplored. This article examines links between attitudes toward income inequality and generalised and institutional trust in Poland, a post-socialist state characterised by strong anti-inequality sentiment and low trust. Using data from the 5th wave of the European Values Study (N = 1,352), we employ an economic stratification framework with five income classes, complemented by non-parametric tests and logistic regression. The results show that acceptance of inequality increases with income, with the sharpest contrasts between low- and high-income classes, while middle strata remain relatively homogeneous. Generalised trust rises with income, whereas institutional trust follows more complex, non-linear patterns. Crucially, the links between trust and inequality attitudes are class-specific: generalised trust in strangers legitimises inequality overall, while generalised trust in relatives has divergent effects across lower- and upper-middle-income groups.
This study investigates whether investor sentiment shapes dividend policy among publicly listed firms in Bangladesh by testing the hypothesis that firms alter their dividend smoothing practices in response to market optimism. We utilise a balanced panel of 116 firms from 2010 to 2021, applying robust panel regression techniques, including random effects, panel-corrected standard errors, and instrumental variable estimation to address model imperfections and potential endogeneity. Our findings show that, on average, firms increase dividends during periods of heightened investor optimism. However, this effect is moderated by prior dividend levels, indicating a tendency toward dividend smoothing. Firms appear to balance market sentiment with the need to maintain consistent payout signals. The findings contribute to the behavioural finance literature by highlighting sentiment as a key determinant of dividend behaviour within the Bangladesh context, where market volatility and retail participation are pronounced.
The main objective of the article is to identify and evaluate the key determinants of consumer recommendation intention with Buy Now, Pay Later (BNPL) services, operationalised through the intention to recommend such services to others. The study investigates the influence of five core constructs: perceived usefulness, perceived ease of use, perceived trust, and perceived risk. Data are collected from a quota sample of 350 users of deferred payment services, selected in accordance with the demographic profile of BNPL users. The study employs PLS-SEM. The results show that perceived usefulness and perceived trust in the BNPL provider significantly boost recommendation intention. Perceived risk negatively impacts recommendation intention, while perceived ease of use has only a marginal effect. These results contribute to the existing literature by elucidating the behavioural mechanisms underlying BNPL usage and provide actionable insights for financial service providers aiming to enhance consumer recommendation intention and retention.
The aim of this study is to investigate if the French R&D tax credit targeted at small and medium-sized enterprises (SMEs) has a positive impact on innovative activity. The French institutional setting provides a unique research setting as the R&D tax credit targeted at SMEs only applies to expenditures incurred during the development phase of R&D projects instead of all eligible R&D expenditures. In order to explore the effectiveness of the French R&D tax credit, a regression discontinuity design (RDD) is applied by comparing targeted SMEs with larger firms not subject to the tax credit over the period 2014-2018. In general, we find that the French R&D tax credit has a positive impact on innovative activity. Moreover, SMEs react more strongly to this incentive in their growth stage. The findings suggest, however, that this effectiveness in increasing SMEs’ innovation does not persist over time.
The aim of this paper is to examine the causality between pairs of measures that describe the intensity of algorithmic trading, market liquidity and volatility for selected blue-chip companies from the Warsaw Stock Exchange, which were permanently included in the WIG20 index from January 1, 2020, to August 31, 2023. In the study, both daily and high-frequency intraday data are used. The research is based on fundamental concepts of information theory, namely entropy and transfer entropy. Additionally, Rényi entropy is used to examine the causal relationships between extreme values of the variables. Our results, based on Shannon’s transfer entropy, suggest that algorithmic trading affects liquidity and volatility. The main finding is that if the frequency increases, the number of companies for which information transfer is significant also grows. However, this relationship is not observed for extreme values, for which Rényi entropy is applied.
This research aims to examine the effect of financial inclusion on economic growth in Vietnam. Using panel data from 63 provinces during 2014–2020, estimations are conducted for both the full sample and across two income groups. Financial inclusion is measured by indicators capturing geographical penetration and using products and services in commercial banks and insurance. The difference-GMM estimation results demonstrate that financial inclusion captured by higher commercial bank branches and using bank accounts, saving passbooks, and ATM cards present significant positive effects on economic growth in Vietnam. In contrast, participating life and non-life insurance shows a non-significant effect. For high-income provinces, participating in life and non-life insurance positively affects economic growth. In addition, the study indicates robust effects of commercial bank branch penetration and using ATM cards in enhancing economic growth in both low-income and high-income localities.
This study examines the Environmental, Social, and Governance (ESG) performance of S&P 500 companies using three clustering algorithms: K-Means, Gaussian Mixture Model, and Agglomerative Clustering. ESG scores from leading data providers are analysed to uncover sectoral patterns and performance trends. The findings indicate that technology and healthcare firms achieve the highest ESG scores, particularly in the governance and social dimensions, while the industrial and energy sectors face the greatest environmental challenges. Among the methods compared, K-Means demonstrates superior clustering performance by forming compact and well-separated ESG groups. These results offer a robust foundation for sector-specific ESG benchmarking, supporting investors and policymakers in identifying sustainability leaders, assessing risk, and targeting areas for improvement.
The ‘fair trade’ movement aims to promote equitable trade relations between developed and developing countries. By guaranteeing producers a fair price, it seeks to improve the livelihoods of farmers and workers in marginalised regions. This review critically explores Fairtrade certification’s impact on the economic, social and environmental sustainability of agri-food systems using PRISMA methodology and SWOT analysis. Key themes emerging from the reviewed papers include sustainable consumption, social equity and women empowerment, and governance in alternative food networks. Most sources focus on consumer behaviour and Fairtrade, concluding that consumer-driven strategies are crucial for systemic change and long-term success. Fairtrade still faces obstacles, including market competition with other certification schemes and the uneven distribution of benefits between producers and supply chain actors. The final retail price is significantly affected by the value added by retailers, contrary to the Fairtrade mission, which can undermine confidence in the system.
This article examines the relationship between employee voice and affective commitment in co-operative financial institutions. It focuses particularly on the moderating role that perceived employer orientation towards co-operative values and principles as well as job type (front-or back-office) has regarding the relationship between two types of voice (challenging and supportive) and affective commitment. The analysis was performed with a dataset of 217 employees from 8 UK building societies. The results indicate a clear positive relationship between supportive employee voice and affective commitment, while the effect of challenging voice is more complex. Moreover, both employee voice types correlate with higher affective commitment for employees who view their employer as little oriented towards co-operative values and principles, but not for those who rated their employer attached to these values. Finally, job type has little impact on the effects of employee voice, although a slightly more positive reaction from back-office staff is noticeable.
This study explores the relationship between CEO values and corporate performance across five standard dimensions of companies’ activity: liquidity, profitability, solvency, operating efficiency, and valuation. Utilising two complementary approaches—dictionary-based text mining and a ChatGPTbased approach to analyse over 4300 CEO interviews, we identified the CEO Schwartz value profiles and compared them with corporate outcomes. The findings indicate that that CEOs with a stronger emphasis on the Achievement value tend to be associated with higher corporate profitability. In turn, CEOs with a strong orientation toward Security are associated with higher corporate liquidity and long-term value creation. In addition, CEOs emphasising Self-direction or Stimulation are observed in firms with higher cash reserves and relatively lower operating efficiency. The results suggest that CEOs’ values may lead to different strategies and, as a consequence, differences in companies’ financial results. The findings contribute to a better understanding of the sources of these differences.
Using annual data from 49 publicly listed non-financial firms from January 2011 to December 2022, this study investigates how board gender diversity affects firm risk-taking behaviour in Pakistan. We use the exogenous shock introduced by the Securities and Exchange Commission of Pakistan (SECP) through the Companies Act in 2017, mandating the inclusion of at least one female director on corporate boards in Pakistan. To address endogeneity, we employ the Two-stage Least Squares (2SLS) and Two-stage Residual Inclusion (2SRI) estimations and validate the findings with the Difference-in-Differences (DiD) and Markov Switching (MS) models. The results indicate that greater female board representation correlates significantly with lower financial leverage and reduced earnings volatility. These results suggest that mandated gender diversity can shape strategic decisions that can help mitigate firm-level financial risk.
