Credit Market Research Articles

Enhancing emission reductions in South African agriculture: The crucial role of carbon credits in incentivizing climate-smart farming practices

Agriculture faces environmental threats caused by climate change, exacerbated by greenhouse gas emissions (GHG). As a result, climate change is a pressing issue for agriculture, necessitating strategies like carbon credits to mitigate emissions and enhance productivity. Carbon credits are recognized as a prominent avenue for reducing emissions, as highlighted in the 2023 Climate Change Conference (COP28). However, research on carbon credit targeting non-CO2 emissions from agriculture is limited. Thus, this study employed stochastic frontier analysis (SFA) to examine panel data from 1991 to 2020, focusing on the effectiveness of climate-smart agriculture in reducing South African agricultural GHG emissions. The data included non-mechanical agricultural emissions sources, paying attention to emissions from crops and livestock. The findings supported the hypothesis, suggesting that increasing incentives, specifically carbon credits, can raise agricultural productivity while reducing emissions. The study also found that inefficiencies in agriculture significantly impact farm output and emissions. The results indicate that offering GHG carbon credits for agriculture promotes sustainable practices, as methane and nitrous oxide emissions are short-lived and can help reduce climate change impact through carbon sequestration. Prioritizing on-farm emissions, soil fertility improvement, reduced fertilizer use, and better livestock management can lead to positive change through climate-smart farming practices. Therefore, promoting customized GHG credits for agriculture mechanisms can lead to positive change through climate-smart farming practices. Thus, it is necessary to enhance mitigation strategies, policies, and farm practices. Finally, the study emphasizes the significance of evidence-based GHG credits for agriculture mechanisms policies and the need for future research into ways to persuade farmers to participate in the carbon credit market.

Climate risk and the systemic risk of banks: A global perspective

This paper explores the impact of climate risk on the systemic risk of banks around the world and examines its influence channels. Our findings indicate that a country’s exposure to climate risk can significantly increase the systemic risk level of its banks. Moreover, we find that the increased bank systemic risk due to higher climate risk is mostly driven by worsened credit quality rather than the depreciation of the bank’s investment portfolio. The adverse impact of climate risk is mitigated when banks have higher profitability or capital adequacy. Cross-sectionally, this effect is particularly significant for banks with extensive branch networks, high importance in the domestic credit market, a lack of dividend payments, and those classified as commercial banks. We also find that banks located in countries with higher loan interest rates, worse regulatory quality, and higher carbon emission intensity are more impacted by climate risk.

Financial literacy and borrower discouragement

This study provides first empirical evidence on the impact of entrepreneurs’ financial literacy on borrower discouragement. Using novel survey data on Italian micro-enterprises, we find that less financially knowledgeable entrepreneurs are more likely to be discouraged from applying for new financing, especially due to higher application costs. Our results are robust to several sensitivity checks, including accounting for potential endogeneity. Furthermore, we show that the observed self-rationing mechanism is rather inefficient, suggesting that financial literacy might play a key role in reducing credit market imperfections.

Bridging the credit gap: The influence of regional bank structure on the expansion of peer-to-peer lending

This paper investigates the extent to which the regional credit market structures, characterized by the presence and lending capacity of traditional banks, shape the growth of online lending marketplaces using peer-to-peer (P2P) lending data. Using an instrumental variables (IV) approach, our study suggests that areas underserved by traditional banks witness more significant growth in P2P lending. This impact is more pronounced in regions with a lower presence of small bank outreach. Furthermore, we find that an increase in P2P lending is associated with a reduced risk of borrower default. Our findings also show that the expansion of online lending marketplaces positively impacts borrowers’ financial well-being by improving their credit scores.

Financial statements not required

Using a dataset covering 3 million commercial borrower financial statements, we document a substantial, nearly monotonic decline in banks’ use of attested financial statements (AFS) in lending over the past two decades. Two market forces help explain this trend. First, technological advances provide lenders with access to a growing array of borrower information sources that can substitute for AFS. Second, banks are increasingly competing with nonbank lenders that rely less on AFS in screening and monitoring. Our results illustrate how technology adoption and changes in credit market structure can render AFS less efficient than alternative information sources for screening and monitoring.

Bank deregulation and corporate social responsibility

We show how external credit market development can affect corporate social responsibility. Using a sample of US public firms over the period 1991–2010, we find that bank deregulation negatively affects CSR performance. We argue that deregulation-induced banking competition enhances credit accessibility, thereby reducing firms’ incentives to pursue CSR as a means of securing stakeholder rewards. Empirical evidence shows that firms increase their use of debt financing in response to the intensified banking competition, and these firms experience a more pronounced decline in CSR performance. We alleviate the potential concern that the observed decline in CSR could be attributed to changes in bank monitoring following deregulation. Further analyses find that firms reduce CSR regardless of their material nature, suggesting that the primary driver of CSR could be the trade-off between costs and returns. Overall, our findings shed light on the strategic motives of CSR, which exhibits adaptability in response to business dynamism.

The crowding out effect of local government debt expansion: Insights from commercial credit financing

Understanding the impact of local government debt expansion on microeconomic entities is crucial in evaluating local government debt policies. This study explored the crowding-out effect of local government debt on firms' commercial credit financing. We found that local government debt plays a crucial role in enhancing corporate commercial credit financing by exacerbating the financing constraints faced by firms. Second, the impact of local government debt on commercial credit financing is more pronounced for firms with lower leverage and a more stable capital chain. Third, state-owned enterprises (SOEs) are more susceptible to the impact of local government debt on commercial credit financing compared to private enterprises. And the crowding-out effect of local government debt on firms' commercial credit financing is more pronounced in the regions where the credit market regulation is relatively weaker. Our findings provide valuable insights that can contribute to the reform of the local government debt management system.

Does Managerial Overconfidence Change with Market Conditions? Risk Management for Financial Institutions

Overconfidence (hubris or overestimation of one’s ability to perform) has been viewed in the finance literature as a character trait that is stable over time, e.g., assuming that if a manager is overconfident, he/she is overconfident all the time. In this paper, we aim to show that managerial overconfidence can be state-contingent, i.e., the level of managerial overconfidence could be influenced by an external economic shock such as the global financial crisis in 2008. A novelty of this paper is to provide evidence for and application of the concept of state-based managerial overconfidence, which is new in the finance literature. Two empirical studies were reported. In the first study (Study 1), we analyzed real market data by linear regression. We found that managerial overconfidence could vary according to changes in the state of the macroeconomy or tightening of corporate governance policies. In the second study (Study 2), we conducted a lab experiment simulating how external manipulations could alter participants’ confidence level. Both our empirical studies provide strong evidence of state-contingent overconfidence by Student’s t-test and contribute to the current finance literature, which assumes overconfidence as a personality trait. Our findings have important practical implications for the credit market. According to the state-contingent overconfidence hypothesis, creditors might reduce the loan amount or the loan duration (or other loan contract terms) too excessively by more than the efficient level during an economic downturn if the offsetting effect of state-contingent overconfidence is ignored.

Credit market conditions, expected return proxies, and bank stock returns

We evaluate the performance of expected return proxies during extreme credit market conditions and extreme phases of business cycles when realized returns on banks stocks are large in absolute value. We construct three sets of expected return proxies for individual bank stocks: (i) characteristic-based proxies; (ii) standard risk-factor-based proxies; and (iii) risk-factor-based proxies in which betas depend on firm characteristics. Based on the newly developed minimum error variance (MEV) criterion (Lee et al., 2020), the best performing expected return proxy is the risk-factor-based model that allows betas to vary with firm characteristics. We also examine whether these three expected return proxies can capture actual returns during either extreme credit market or extreme business-cycle conditions. We find that both risk-factor-based proxies explain returns better than characteristic-based proxies during these periods.

Your friends, your credit: Social capital measures derived from social media and the credit market

We document a robust correlation between the Bricker and Li (2017) social trust indicator and the Chetty et al. (2022a) economic connectedness measure. The two indicators predict upward income mobility independently to a comparable extent. The Bricker–Li indicator is defined as the average credit score of a community, and the Chetty et al. measures are based on Facebook befriending data. The consistency and complementarity between these two indicators underscore trust as a crucial ingredient of social capital.

Time-varying default risk of Chinese-listed companies: From empirical test to theoretical conjecture

Default risk is one of the major challenges faced by the financial industry. This paper aims to investigate the dynamic of enterprise debt default risk law after Initial Public Offerings (IPO). The paper also proposes a theoretical conjecture to explain the logic of the time-varying law. To achieve this objective, the paper used panel data of non-financial enterprises in Shanghai and Shenzhen A-share markets from 2002 to 2020. We found that the debt default risk and IPO have an inverted U-shape relationship, the inflection point is at 8 years of IPO. Moreover, adding control variables and changing measurement indicators did not change the time-varying law. The theoretical conjecture showed that the default risk is low at the initial stage of IPO. Furthermore, over-investment of managers triggers IPO exuberance, and with the recognition of the credit market, can lead to an increase in the debt level of the enterprises and default risk. However, with time, default risk will decrease as the business behavior is adjusted and impulsive investment is reduced. Therefore, the debt default risk of listed companies presents a significant and robust “inverted U” characteristic over time.

Retraction Note: Research on prediction of power market credit system based on linear model and improved BP neural network

Retraction Note: Research on prediction of power market credit system based on linear model and improved BP neural network

Inequality in high-cost borrowing and unemployment insurance generosity in US states during the COVID-19 pandemic.

US consumers may turn to the private market for credit when income and government benefits fall short. The most vulnerable consumers have access only to the highest-cost loans. Prior research on trade-offs of credit with government welfare support cannot distinguish between distinct forms of unsecured credit due to data limitations. Here we provide insight on credit-welfare state trade-offs vis-à-vis unemployment insurance generosity by leveraging a large sample of credit data that allow us to separate credit cards, personal loans and alternative financial services loans and to analyse heterogeneity in credit use by household income. We find that more generous state unemployment insurance benefits were associated with a lower probability of high-cost credit use during the first seven quarters of the coronavirus disease 2019 (COVID-19) pandemic. This inverse association was concentrated among consumers living in low-income households. Our results support theories that public benefits are inversely associated with the use of costly credit.

Move a Little Closer? Information Sharing and the Spatial Clustering of Bank Branches

Abstract We present a model of credit market competition to derive key hypotheses about how information sharing between banks influences the spatial clustering of their branches. We then test these hypotheses using data on 56,555 branches owned by 614 banks across 19 countries. We find that information sharing incentivizes banks to establish branches in localities that are new to them but that are already served by other banks. The resultant branch clustering is associated with reduced spatial credit rationing, as information sharing enables firms to access credit from more distant banks. These findings underscore how information sharing makes it more important for banks to move closer to each other rather than closer to their borrowers.

Innovation, Disruption and Consumer Harm in the Buy Now Pay Later Industry: An Empirical Study

‘Buy now pay later’ (‘BNPL’) has been described as ‘an Australian fintech growth story’, an innovative and disruptive financial product that has fundamentally changed the global market for consumer credit. Providers assert that BNPL promotes financial inclusion, allowing consumers to avoid the fees and interest associated with other, more expensive financial products. Yet critics maintain that BNPL is too readily accessible and that it can cause serious hardship, particularly for low income earners. This article is the first scholarly empirical study to focus on low income earners’ use of BNPL. It draws on a series of focus groups with consumer advocates and an online survey of consumers who have used BNPL, either alone or in conjunction with payday loans or pawn loans. Drawing on this data, the authors evaluate the Commonwealth Government’s current proposal to regulate BNPL more stringently, under the National Consumer Credit Protection Act 2009 (Cth).

Granular satellite data to assess the potential for nature based solutions at a national scale: a proof of concept with data from Rwanda and Lesotho

ABSTRACT Nature-based Solutions (NbS) form a substantial part of cost-efficient climate change mitigation options. However, public financial flows towards NbS have been limited. Among the factors impeding investments in NbS are challenges in reliable remote project identification and comparison. In this article, we demonstrate a technological solution to these challenges. Using cloud-based satellite data processing and the proliferation of open geospatial data, we developed a methodology to map NbS suitability based on a set of biophysical, pedological, hydrological and climatological criteria. To provide a proof of concept, we identify potential project areas for eight types of NbS in Rwanda and Lesotho. Building on these spatially-explicit NbS suitability data layers (accessible at https://williamouellette.users.earthengine.app/view/ncs-potential), we develop marginal abatement cost curves for projects in Rwanda and Lesotho. We thus provide a proof of concept for remote identification and project comparison. These technological developments can help investors, such as multilateral donors or governments, alleviate additionality concerns that are implied by local project selection. Key Policy Insights Investment in climate change mitigation through Nature-based Solutions (NbS) is limited, in spite of the large, cost-efficient potential for achieving national and global goals. Remote project identification and comparison can help alleviate some of the impediments to international investment in NbS. Such remote identification and comparison of NbS projects is now possible because of breakthroughs in cloud-based satellite data processing technologies and increased availability of geospatial data. We present a proof of concept, establishing marginal abatement cost curves for climate change mitigation through NbS in Rwanda and Lesotho. Coupled with the institutional improvements necessary to create a reliable intergovernmental carbon credit market, these technological developments have the potential to boost international investment in NbS.

Sustainability and the domestic credit market: worldwide evidence

This paper aims to uncover the cross-sectional relationship between country-level sustainability performance and the domestic lending activity of commercial banks. Considering a worldwide sample of countries, it uses publicly available sustainability scores from SolAlability Sustainable Intelligence, macroeconomic data, and banking sector data from the World Bank. The results show that the country’s sustainability performance is positively related to the amount of domestic credit granted by banks to the private sector and negatively related to the importance of nonperforming loans. Moreover, looking at the pillars that constitute the sustainability scores, this work finds evidence that social cohesion, intellectual capital, and governance are the pillars of sustainability that affect domestic lending activity. Results survive several robustness tests concerning samples, variables’ definitions, and estimation procedures. Our results suggest that policies aiming at improving a country’s sustainability contribute to domestic banking sector stability and financial development. Specifically, measures that contribute to social cohesion and solidarity, innovation and value-added industries, and the country’s governance performance, contribute to the smooth functioning of credit markets.

Life after (soft) default

Soft default, defined as a delinquency of 90 days or more, is a relatively common event in the credit market, in 2010 such episodes affected about 3 million individuals. Yet we lack a detailed understanding of what happens afterward. We use credit report data, on approximately 2 million individuals from 2004 to 2020, to shed light on individual trajectories after such event, and document enduring negative impacts. These effects persist for up to ten years post-event and manifest in lower credit scores, reduced total credit limits, lower homeownership rates, lower income, and relocation to less economically active zip codes. It appears that those who are overextended in their mortgage lines, and with larger delinquent amounts, suffer the harshest consequences.

Nash equilibria in greenhouse gas offset credit markets

One approach to reducing greenhouse gas (GHG) emissions is to incentivise carbon capturing and carbon reducing projects while simultaneously penalising excess GHG output. In this work, we present a novel market framework and characterise the optimal behaviour of GHG offset credit (OC) market participants in both single-player and two-player settings. The single player setting is posed as an optimal stopping and control problem, while the two-player setting is posed as optimal stopping and mixed-Nash equilibria problem. We demonstrate the importance of acting optimally using numerical solutions and Monte Carlo simulations and explore the differences between the homogeneous and heterogeneous players. In both settings, we find that market participants benefit from optimal OC trading and OC generation.

Exploring Market Credit Evaluation System of Tourism Enterprises from Tourist Perspective

ABSTRACT This study employs literature review and expert consultation methods to construct dimensions and items for evaluating the market credit of tourism enterprises from tourist perspective. A Hierarchical Analysis Method was used to develop the market credit evaluation system for tourism enterprises. The research findings indicate that the evaluation system comprises 7 dimensions and 37 items, which include: credit capacity, credit regulation, credit foundation, credit behavior, economic credit, employee credit, and integrity culture. The Hierarchical Analysis Method was applied to determine the weight for these dimensions and items. The credit foundation of tourism enterprises was found to have the highest weight, followed by credit regulation, credit capacity, credit behavior, economic credit, employee credit, and integrity culture. Theoretically, this research enriches the theory of tourism enterprise credit and provides a measurement tool for evaluating market credit. Practically, it offers targeted suggestions and strategies for tourism enterprises to enhance their market credit.