Purpose This study aims to investigate the determinants of efficiency and profitability among fintech firms in China and India, with a particular focus on macro-level information and communication technology (ICT) development as a key factor. Design/methodology/approach The study sample includes fintech firms from China and India. We apply instrumental variable techniques and the Arellano–Bond model to panel data from each country and compare the results. Findings The findings show substantial disparities between China and India. In China, a robust digital infrastructure has consistently enhanced fintech profitability and efficiency by facilitating customer acquisition and operational optimization. In contrast, India's fintech sector has yet to fully capitalize on the country's ICT growth. Practical implications These findings highlight that investing in technology alone is insufficient – it must be complemented by broader ecosystem development. In China, efforts should focus on managing costs while deepening innovation. In India, critical actions include addressing regional digital divides, improving service reliability and advancing digital inclusion to unlock the full potential of ICT for fintech performance. In both countries, mobile payment systems should be reviewed to identify opportunities for reducing costs and creating value. Originality/value This paper advances the fintech literature by empirically examining the impact of macro-level ICT development on fintech firm performance in China and India, moving beyond previous research focused predominantly on the micro level. Moreover, the study investigates the underlying mechanisms driving these associations, including scalability, customer acquisition and operational optimization. Building on previous research, we employ both static and dynamic econometric models to ensure robustness and methodological rigor, effectively capturing both cross-sectional and time-dependent effects. Furthermore, by analyzing the COVID-19 period, the study offers insights into fintech resilience and adaptability to external shocks.

Purpose It develop a dynamic general equilibrium model, calculates fundamental house value as well as their deviations, analyzes their main factors and explores a closer housing policy in future. Design/methodology/approach Incorporating the stylized facts, this paper initially develops a dynamic general equilibrium model to determine house price. Findings (1) Per capita income, urban population, M2 growth rate and land finance dependence significantly and positively affect fundamental house values but minimum down payment ratio and deposit rates do not. (2) Extreme deviations stem from large swings in income, population, M2 growth, land finance, regulatory policies and housing price expectations, while down payment ratio (DPR), rational expectations and loan rates don't significantly affect deviations. (3) Excessive bubbles cluster in eastern and southern cities while severe slumps prevail in central-western and northern regions. Housing regulations have effectively curbed soaring prices but caused mild slumps. Housing policies may have partially strayed from their original goals. (4) Housing policy direction may be to align with the current stage of its development, closely monitor price trends and adjust key factors accordingly. Research limitations/implications Firstly, interpolation methods are used to improve a few data for several years or cities for short of official statistics. Secondly, the sample city size is only limited to 35 large- and medium-sized cities instead of 70-cities, 100-cities or all prefecture cities because of workload and statistical deficiencies. Thirdly, there are some literature discussing the intra-temporal non-separability between housing and non-durable consumption in fact (for example, Khorunzhina, 2021). However, the discussion is too complex to be completed in this article. Practical implications We provide with a theoretical evidence to explain why house price deviations are highly uneven across time and regions during the past 2 decades in China and explore the direction of their housing policies in future. Social implications This paper helps residents and businesses to evaluate house prices reasonably, avoiding their excessive optimism or pessimism about the housing market. Originality/value We develops a dynamic general equilibrium model with endogenized markets and six agents. Second, the stylized facts in China are introduced into the dynamic general equilibrium model (DGEM) to match house value in the real world, which consist of fueling house price, explosive currency and credit, local land leasing finance, rapid population urbanization, the housing purchase restrictions and the dominantly quantitative monetary policy. Third, we calculate the fundamental house values, the extreme deviations and their main factors. Then, we explore the direction of housing policy in the long run and in the short term.

Purpose This study aims to find if subjective financial knowledge (SFK), objective financial literacy (OFL) and financial behavior are associated with financial resilience, directly and indirectly through digital financial services (DFS) comfortability. Design/methodology/approach Using data from the European Union (n = 16,988), a logistic regression model is used for the analysis purpose. Furthermore, Model 4 in the PROCESS macro for SPSS is used to conduct mediation analysis. In addition, several sensitivity checks, sub-sample analyses and endogeneity checks were applied to see if the results remain robust. Findings The findings indicate that SFK, OFL and financial behavior are positively associated with financial resilience. Other results show that DFS comfortability plays a partial yet strong mediation role. These findings remain the same after applying several sensitivity and endogeneity checks. Practical implications Regulators should ensure that people have ease of access to DFS and there are no security concerns regarding using DFS. Furthermore, policymakers can design specific policies for financial institutions in paving the way to design relevant financial products for their clients, which will assist them in raising their financial resilience levels. Originality/value The results add value to the growing literature on financial literacy, financial technology (FinTech) and financial resilience. Furthermore, this study integrates the resource-based view and the dynamic capabilities view to demonstrate that individuals' internal resources and dynamic capabilities are important proficiencies to overcome future financial shocks.

Purpose To investigate how the facial trustworthiness of financial analysts affects their ability to privately gather information from corporate insiders. The channels are hypothesized to be managerial features, information environment and legal enforcement. Design/methodology/approach The study employs a quantitative research design using a comprehensive sample of Chinese financial analyst reports. Machine learning techniques for facial analysis are applied to assess the trustworthiness of analysts, and the relationship between facial trustworthiness and the informativeness of the analysts' reports is analyzed. Findings We first find that more trustful-looking analysts can produce more informative reports upon their visits to the corporate insiders. The effect of analysts’ facial trustworthiness is driven by the gender difference and the level of professional competency of the visited insiders. Moreover, when information disclosure of the reported firm is lower, the trust effects become more pronounced. Finally, the trust effect disappears after a legal action against an insider trading activity related to one of the analysts’ visits. Originality/value We find that more trustful-looking analysts can gain more material information during their visits to the firms, particularly when interacting with managers who have lower professional competency and a greater tendency to trust others. This trust-based informational advantage is also amplified in firms with poorer information environments. Furthermore, this trust effect disappears after a legal action against an insider trading activity related to one of the analyst visits. Our results are robust after controlling for analysts’ competency, facial attractiveness and industrial concentration.

Purpose As a critical pathway toward achieving agricultural modernization, high-quality agricultural development requires the efficient optimization of factor allocation. This study aims to examine green finance and assess its impact on high-quality agricultural development from the perspective of financial resource allocation. Design/methodology/approach A comprehensive evaluation index system for both green finance and high-quality agricultural development is constructed, employing the Epsilon-Based Measure and global Malmquist-Luenberger index in conjunction with the global entropy weight method for measurement. Furthermore, the system generalized method of moments (GMM) method is employed to empirically analyze the influence of green finance on high-quality agricultural development. Findings The conclusion that green finance can effectively drive high-quality agricultural development remains robust across multiple empirical tests. Environmental regulation plays a substantial positive role in promoting high-quality agricultural development; however, it also attenuates the positive impact of green finance on such progress. Social implications This paper recommends strengthening the green financial system, diversifying green financial services and fully leveraging the potential of green finance in advancing high-quality agricultural development. Originality/value This research integrates green finance and high-quality agricultural development into a unified analytical framework. It theoretically explicates multiple mechanisms through which green finance influences high-quality agricultural development and empirically tests these relationships using inter-provincial panel data and the system GMM. This approach broadens the analytical scope of research on the determinants of high-quality agricultural development.

Purpose The frequent emergence of zombie firms jeopardizes the development of the real economy, and bank credit misallocation is the key reason for this. In this regard, the paper examines whether Joint Credit Granting-a policy regulating bank credit practices-effectively mitigates corporate zombification. Design/methodology/approach This paper analyzes a dataset of Chinese listed firms from 2013 to 2022 and uses a difference-in-differences approach. The Joint Credit Granting is regarded as a quasi-natural experiment. Findings The implementation of Joint Credit Granting significantly inhibits corporate zombification. This effect is realized through two primary channels: enhancing corporate information transparency and internal governance efficiency, and correcting the misallocation of bank credit. Originality/value This paper offers novel insights into the efficacy of Joint Credit Granting and provides valuable perspectives on the governance of zombie firms. In addition, this paper enriches the economic effects research on bank information-sharing mechanisms.

Purpose This research explores the relationship between banks’ environmental, social, and governance (ESG) performance and lending practices throughout the world. Design/methodology/approach The authors employ a linear regression model with fixed effects and apply the Generalized Method of Moments (GMM), an instrumental variable approach, to address potential endogeneity in analyzing the impact of Environmental, Social, and Governance (ESG) factors on bank lending. The study utilizes data from 53 countries over the period 2002–2022, providing a broad international perspective on the relationship between ESG considerations and lending behavior. Findings The research discovered empirical evidence that banks’ ESG performance significantly influences their lending activities. Interestingly, this relationship is insignificant in developing nations. In addition, this paper examines the moderating influence of the Coronavirus pandemic on the association between ESG performance on bank lending. This paper finds evidence that banks’ increased ESG activities during the health crisis tend to improve their lending performance, especially in developed countries. Our findings indicate that societal trust, bank capital, bank size, and credit risk exposure serve as moderating factors in the relationship between ESG and loan growth. Practical implications Based on the study, this paper presents some implications for policymakers and stakeholders to address some of the pressing concerns. Originality/value This paper examines the role of the COVID-19 health crisis in the association between ESG activities and bank lending across countries.

Purpose The purpose of this study is to explore the impact of digital financial inclusion and its sub-dimensions on agricultural modernization, clarify the specific pathways through which digital financial inclusion empowers agricultural modernization and assess its effects on agricultural productivity and sustainable development. Additionally, the study aims to identify and analyze potential obstacles encountered in this process and propose corresponding solutions. Design/methodology/approach This study utilizes panel data from 31 provinces in China from 2011 to 2021 to calculate the agricultural modernization index using the entropy weight method. It empirically analyzes the role of digital financial inclusion in promoting agricultural modernization and delves into the mechanisms by which digital financial inclusion affects agricultural modernization. Findings The findings are as follows: (1) Digital financial inclusion and its sub-dimensions have a significant positive impact on agricultural modernization. (2) Regional heterogeneity exists in this impact, with the eastern region benefiting most prominently, followed by the central region. (3) Digital financial inclusion enhances agricultural modernization by alleviating information asymmetry, improving financial service accessibility, boosting agricultural productivity and optimizing resource allocation efficiency. Originality/value The contributions of this paper are as follows: (1) This study not only provides theoretical support for understanding the intrinsic mechanisms of digital financial inclusion but also offers practical guidance on how to effectively utilize digital financial tools to promote agricultural development. (2) By using China as a case study, this research offers a comprehensive understanding of how digital technologies are applied in agricultural modernization and their outcomes. It also offers specific strategic recommendations and implementation pathways for other countries and regions to develop digital financial inclusion.

Purpose This study aims to investigate the empirical relation between illiquidity and yield spread in China's corporate bond market. Design/methodology/approach We rely on panel regressions to identify the empirical relation between illiquidity and bond yield spread. Findings We find a significant liquidity discount instead of liquidity premium for corporate bonds traded in the exchange market in China prior to 2014. The discount becomes insignificant afterward and ultimately turns positive after 2018. By contrast, in the interbank market, the liquidity premium effect persists. We relate the liquidity discount in the exchange market to retail investors’ yield-chasing behavior. Originality/value This study is the first to document the significant liquidity discount in the exchange market for corporate bonds, in contrast to the liquidity premium in the interbank market. This study is also the first to link the liquidity discount to investors’ yield-chasing behavior.

Purpose Our study explores the association between data assetization and corporate credit financing from bank loans. By examining the hidden champion small- and medium-sized enterprises (SMEs) sample from China, we want to reveal whether firms with higher data assets improve their bank credit financing. Design/methodology/approach Our study uses the sample of China's hidden champion listed SMEs from 2011 to 2021 to examine the association between data assetization and corporate credit financing. We use the multiple regression analysis approach and the neural network model to construct accurate firm-level data assets. Findings Our study finds that firms with higher data assets improve their bank credit financing. This finding arises because data assetization helps reduce information asymmetry and obtain government subsidies. Moreover, we reveal that enterprises with more extended credit-term structures tend to prefer short-term financing as data assets increase. Regarding influencing factors, enterprises with higher risk-taking, lower industry positions and higher economic policy uncertainty will enhance the effect of data assetization on bank credit financing. Additionally, the data assetization also reduces the over-financialization among hidden champion SMEs. Originality/value Our study makes the following contributions. Firstly, we enrich the research on the data assets and economic outcomes. Secondly, we contribute to the literature on how corporate digital transformation shapes bank credit resource allocations (e.g. Liu and Wang, 2023; Zhou and Li, 2023). Finally, our study contributes to the literature on the hidden champions' financial features in emerging markets.