Credit Scale Research Articles

Central bank digital currency and corporate debt financing costs: Empirical evidence from China

We investigate whether central bank digital currency (CBDC) affects corporate financing costs. Results from Difference-in-difference (DID) estimation indicate that corporate debt financing costs rise significantly in the presence of China's central bank digital currency (CBDC). Our mechanism analyses suggest that CBDC boosts financing costs through credit channel, specifically by specifically by increasing bank lending rates, reducing the scale of credit, and heightening the challenges associated with securing debt financing. This study offers critical insights for policymakers, shedding light on the consequences of CBDC issuance.

Impact of Digital Finance on Credit Structure and Risk-Taking in Commercial Banks: An Empirical Analysis

With the rapid growth of new technologies such as big data, digital technology is increasingly permeating our daily lives. Financial institutions, particularly commercial banks, are also seizing opportunities in the wave of digital financial development to provide better financial services. However, this development in digital finance has affected the credit structure and risk-taking of banks. This study aims to empirically analyze the impact of digital finance development on the credit structure and risk-taking of commercial banks. Additionally, the study seeks to discuss how the combined effects of digital finance and credit structure influence bank risk-taking. Empirical analysis is conducted using financial data from commercial banks over the past decade. The analytical methods include collecting secondary data, statistical data processing, and regression analysis to evaluate the relationships between digital finance development, credit structure, and bank risk-taking. The empirical analysis results show that the development of digital finance has promoted an increase in the scale of bank credit and the ratio of personal loans to credit loans. Integrating digital finance with banks has proven to reduce the risk burden banks bear. Furthermore, as digital finance continues to develop, adjustments in the bank's credit structure also affect the risk burden borne by the banks. Based on these findings, it is recommended that commercial banks continue to adopt digital financial technologies to increase their credit scale and optimize their credit structure. Additionally, banks should consider developing policies that support integrating digital technologies to reduce risk burdens and enhance financial stability. Further research is also suggested to explore the long-term impact of digital finance on the overall financial performance and risk of banks

The scale effects of agricultural credits, institutional governance and microfinance sustainability in Sub-Saharan African countries

PurposeThe study examines the synthesized influences of institutional governance and the scale effects of agricultural credits on the sustainability of microfinance institutions (MFIs) in Sub-Saharan Africa.Design/methodology/approachUsing a sample of 840 MFIs (300 independent and 540 networked), the study applied Generalized Method of Moments (GMM) and Lewbel’s estimator.FindingsResults indicate positive effects of financial structure, efficiency and agricultural credit scale on sustainability, with a non-linear U-shaped relationship between agricultural credit size and microfinance sustainability. Depending on institutional governance quality, a threshold is identified where agricultural credit scale significantly enhances the quality of Portfolio at Risk (lnPAR) in independent MFIs and Returns on Assets (lnROA) in networked MFIs.Research limitations/implicationsStudy suggests strengthening governance for transparency and operating within optimal size for enduring sustainable performance. While focused on Sub-Saharan Africa, future research could expand to various economies or introduce additional variables for a comprehensive analysis.Practical implicationsMFIs can achieve sustainability by implementing management guided by better institutional norms, innovative financial transformations better suited to financing agricultural activities and techniques and an organizational structure more aligned with their performance targets.Social implicationsBroader and more reliable access to financial services, particularly in the agricultural sector, can stimulate production and alleviate poverty.Originality/valueThe study’s originality lies in its contribution to the literature by examining the role of institutional governance in microfinance institution performance and evaluating microfinance in a broader Sub-Saharan African context, proposing threshold limits where agricultural microcredit compromises performance.

Research on User Default Prediction Algorithm Based on Adjusted Homogenous and Heterogeneous Ensemble Learning

In the field of risk assessment, the traditional econometric models are generally used to assess credit risk. And with the introduction of the “dual-carbon” goals to promote the development of a low-carbon economy, the scale of green credit in China has rapidly expanded. But with the advent of the big data era, due to the poor interpretability of a traditional single machine learning model, it is difficult to capture nonlinear relationships, and there are shortcomings in prediction accuracy and robustness. This paper selects the adjusted ensemble learning model based on the homogeneous and heterogeneous factors for user default prediction, which can efficiently process large quantities of high-dimensional data. This article adjusts each model to adapt to the task and innovatively compares various models. In this paper, the missing value filling method, feature selection, and ensemble model are studied and discussed, and the optimal ensemble model is obtained. When comparing the predictions of single models and ensemble models, the accuracy, sensitivity, specificity, F1-Score, Kappa, and MCC of Categorical Features Gradient Boosting (CatBoost) and Random undersampling Boosting (RUSBoost) all reach 100%. The experimental results prove that the algorithm based on adjusted homogeneous and heterogeneous ensemble learning can predict the user default efficiently and accurately. This paper also provides some references for establishing a risk assessment index system.

THE DIFFERENTIAL EFFECTS OF CREDIT POLICY ON REAL ESTATE PRICES FROM THE PERSPECTIVE OF CLUB CONVERGENCE

This study investigates the differential effects of credit policy in the context of real estate price convergence in China. First, we analyze the real estate price convergence of 35 large and medium-sized cities in China using [Formula: see text] convergence and club convergence methods. Subsequently, based on the convergence situation, we use panel models to compare the heterogeneous effects of the credit policy regulation of different clubs. The findings are as follows. (1) In terms of overall convergence, the findings confirm that there is no [Formula: see text] convergence in China’s real estate prices. Prices in each city do not show a trend of convergence to the total mean. (2) There are currently four convergence clubs and one divergence group in terms of regional convergence. Cities with similar initial price levels have similar structural characteristics and tend to converge to their respective local steady states. GDP per capita and population density are the main driving forces for the formation of a real estate price convergence club. (3) We show that the credit scale has a statistically positive impact on the real estate price, and the credit scales of various convergence clubs have different effects on real estate prices. Clubs with more developed real estate and financial markets are more sensitive to changes in credit policy.

Review of the Impact of Corporate CSRD on the Capital Cost of Debt

With the expansion of credit scale, green credit releases a large number of ecological dividends. CSR reporting is different from tightly regulated financial reporting and there are no uniform standard to regulate and monitor its disclosure. At the same time, because CSR reports mainly contain non-financial information of text, and text is more flexible and easier to manipulate than numbers, compared with financial reports, CSR reports have a large space for subjective manipulation, which runs counter to the original intention of reducing information asymmetry. Existing studies have confirmed that CSR intonation can provide incremental information to external information users, so it is worth further exploring whether creditors will obtain information from CSR reports when making credit decisions. Therefore, this paper tries to take CSR intonation as the entry point, summarize the motivation and consequences of CSRD, the relationship between social responsibility and debt capital cost, discuss the impact of CSRD behavior on the financing ability of enterprises, further improve the theoretical basis and conclusion of CSRD and enterprise financing ability, and promote the sustainable development of enterprises.

Research on the Impact of Green Credit Policies on Green Innovation of Heavy Polluting Enterprises: A Case Study of Sichuan Province

Green credit is an important green financial tool to stimulate enterprise green innovation. Enterprise green innovation is an important driving force for the coordinated development of the environment and economy, and achieving high-quality economic development. This article first analyzes the current development status of green credit in Sichuan Province from two perspectives: the scale and structure of green credit, and analyzes the current status of green innovation in heavily polluting enterprises from both economic and policy perspectives. Secondly, using listed companies in Sichuan Province from 2008 to 2015 as sample data, the total amount of green innovation of enterprises was measured by the number of green patent applications. The double difference model was used to explore the impact and mechanism of green credit policies on green innovation of heavily polluting manufacturing enterprises in Sichuan Province; Once again, conduct a scientific test on the derived results through empirical analysis. Finally, policy recommendations are proposed on how to utilize green credit development to promote green innovation in heavily polluting enterprises.

Does Green Credit Policy Affect Dividend Distribution

Green credit means that banks and financial institutions provide loans and financing to enterprises and projects that contribute to environmental protection in order to support the development of green economy. The development of green credit is not only of great significance to environmental protection and sustainable development, but also has a profound impact on the operation and development of enterprises. This kind of influence is mainly reflected in the business performance and the image reputation of the enterprise, so it will also affect the dividend distribution of the enterprise. Firstly, this paper summarizes the relevant literature at home and abroad, and sorts out the existing literature on the impact of green credit policy on dividend distribution. According to the innovation of the existing literature, this paper discusses the influence mechanism of green credit policy on corporate dividend distribution. Then, this paper empirically tests the dividend data and green credit scale data of A-share listed companies, and finally draws A conclusion. This paper adopts PSM-DID empirical test method and finds that green credit policy has a significant positive impact on dividend distribution of listed companies.

The Impact of Two-pillar Policies on Real Estate Prices in China

Since the turn of the 20th century, China's real estate industry has been expanding, playing an increasingly vital role in fostering the growth of the national economy. On the one hand, rising housing costs can stimulate the growth of linked companies. Nonetheless, it also causes a number of social issues. Through theoretical research, this study examines the impact of two-pillar policies (monetary policy and macroprudential regulations) on real estate values in China. The analysis reveals that quantitative monetary policy influences real estate prices via credit scale, whereas price-based monetary policy influences real estate prices via loan interest rate. However, there is a tension in monetary policy between "boosting the economy" and "stabilizing property prices". When monetary policies govern housing prices, macroprudential policies, particularly LTV instruments, can avert systemic problems and compensate for the spillover effects on the real economy. Consequently, it is imperative to establish and enhance the regulatory framework for two-pillar policies.

The Study of Carbon Neutralization Effects with Green Credit: Evidence from a Panel Data Analysis for Interprovinces in China

Giving full play to carbon emission reduction of green credits is essential to achieve carbon neutrality. According to low-carbon pilot policies and the condition of industrial transfer, this paper first sorts those provinces into different research zones. The zones are as follows: (Ⅰ) the first and second batch of low-carbon municipalities and the first batch of pilot provinces (L1) and other provinces (L2) and (Ⅱ) strong industry transfer-out zone (STR), weak industry transfer-out zone (WTR), and industrial transfer-in area (TIR). Then, we employ a dynamic panel data model and systematic GMM (SYS-GMM) approach to empirically test the impact of green credit and nongreen credit on carbon emissions. Further, this paper analyzes how to coordinate two types of credits to achieve carbon neutrality. The results show that, first, at the national level, the nexus of green credit and carbon emissions with an inverted U-shaped curve and the current impact of green credit is still in the first half of the inverted U-shaped stage. The achievement of carbon neutrality is associated with the ratio structure of green credit to nongreen credit and the scale of green credit. Second, the achievement of carbon neutrality is with regional heterogeneity. The achievement of carbon neutrality is associated with the scale of green credit in L2 and TIR, but also with the ratio structure of nongreen credit to green credit in L2 and STR. However, the carbon neutralization effects with green credit are insignificant in L1 WTR. Finally, based on those conclusions, this paper puts forwards some suggestions to provide references for the policy formulation of green credits and carbon neutrality.

Does the digital transformation of banks affect green credit?

This study explores the relationship between digital transformation and green credit in the banking industry. Based on data from China’s banks from 2010 to 2021, we find that the digital transformation of banks has a positive impact on the green credit scale. Among them, the higher level of bank management digitization is more effective for green credit growth. From the perspective of cooperation and competition banks’ digitization contribute to green credit through exogenous fintech and industry competition. In addition, the facilitating effect of the relationship is more pronounced under state-owned banks, large banks, loose monetary policy, and strong financial supervision.

Agricultural credit scale and agricultural green production efficiency: a Metafrontier-Malmquist-Luenberger and panel Tobit approach

The agricultural credit scale plays a crucial role in improving the agricultural green production efficiency (AGPE) in China. This paper selected the panel data of 30 provinces in China from 2009 to 2020 and used the Metafrontier-Malmquist-Luenberger index to calculate the agricultural green production efficiency. On this basis, this paper uses the Panel Tobit model to analysis the impact of agricultural credit scale on AGPE. The main conclusions are as follows: 1) From 2009 to 2020, the average AGPE in 30 provinces was 4.2%, and agricultural technology progress was the main driving factor for AGPE growth. 2) The agricultural credit scale significantly promotes AGPE, and the impact of the agricultural credit scale on AGPE presents a significant inverted U-shape. 3) The impact of the agricultural credit scale on AGPE in eastern, central, and western regions is significantly heterogeneous. 4) AGPE has significant spatial spillover effects. This paper believes that improving agricultural green production efficiency requires paying attention to the important role played by the scale of agricultural credit.

Digital finance promotes sustainable total factor eco-efficiency: evidence from China

ABSTRACT A super-efficient SBM model was constructed using Chinese provincial panel data from 2011 to 2018 to explore the impact of digital finance on sustainable total factor eco-efficiency (STFEcE) and its mechanisms of action. The results show that digital finance can promote the improvement of STFEcE, and this promotion is heterogeneous. Western regions with more backward financial development, ecologically inefficient regions, and financially weakly regulated regions have more significant eco-efficiency improvements from digital financial services. Digital finance influences STFEcE by expanding the scale of green credit and enhancing the level of green and digital technology innovation. Therefore, the government should support the efficient integration of digital technology and financial services in macro policies, accelerate the infrastructure construction of digital finance, eliminate the digital divide, and create a favourable financial environment for improving STFEcE.

Financing decision of heavy pollution enterprises under green credit policy: Based on the perspective of signal transmission and supply chain transmission

More and more countries have successively promulgated various environmental policies to mitigate climate change and environmental pollution. These policies have become important in promoting low-carbon development and green transformation through enterprise financing. This study employs a difference-in-difference (DID) model to examine how a green credit policy affects the financing choices of highly polluting businesses using the data of A-share listed corporations from 2009 to 2021. The research finds that: (1) The number of bank loans has significantly decreased for highly polluting companies; a green credit policy will also reduce the scale of any non-bank loans. (2) The extent of equity financing and bond financing of highly polluting firms on the capital market decreased due to market constraints and the function of policy signaling. (3) The impact of a green credit policy will spread to upstream and downstream enterprises through trade credit, thus reducing enterprises’ commercial credit scale. (4) The impact of a green credit policy on bank loans is more significant in state-owned enterprises, in regions with a high degree of marketization, and in regions with low intensity environmental regulation. The research results provide targeted policy recommendations for promoting the development of green credit and achieving carbon neutralization.

Can Green Credit Policies Accelerate the Realization of the Dual Carbon Goal in China? Examination Based on an Endogenous Financial CGE Model.

Green credit is an indispensable funding source through which China can achieve its carbon neutrality goal. This paper quantifies the influences of different green credit scales on energy structures, carbon reduction, the industrial economy, and the macroeconomy. It creates a green credit mechanism related to green technology innovation in a Chinese carbon neutrality computable general equilibrium (CGE) model and integrates energy, environmental, economic, and financial (3EF) systems. The green credit scale can influence green technology innovation and hence CO2 emissions. The results show that (1) green credit can accelerate China's achievement of its carbon neutrality goal, and the larger the green credit scale, the less time it takes to achieve goals; (2) the influence of green credit scales confers marginal decreasing effects with realistic policy considerations; (3) using a cost-benefit perspective, 60% is the most appropriate green credit scale to use to achieve dual carbon goals in China; (4) the different green credit scales have a heterogeneous impact on the industry output, and high-carbon-emission producers from nonenergy industries need to pay attention to their green credit risk. This research provides a scientific reference for the policy design of China's future green financial market development.

Research on the mechanism and realization path of digital inclusive finance for rural common prosperity

Digital inclusive finance has an important role to play in promoting common prosperity in the countryside. Firstly, by supporting farmers' innovation and entrepreneurship, it can increase the business income of farmers; secondly, by supporting the revitalisation of rural industries and increasing employment opportunities, it can increase the wage income of farmers; furthermore, by enhancing the marketability of rural areas, it can increase the property income of farmers. The current development of digital inclusive finance in China mainly has shortcomings in terms of lower penetration, narrower application areas, smaller credit scale and more blind spots in supervision. The main paths to enhance the development of digital inclusive finance in China's rural areas are: firstly, to popularise basic financial knowledge so as to enhance the financial literacy of farmers and new agricultural operators; secondly, to strengthen the construction of rural communication infrastructure to improve the network facilities for the development of digital inclusive finance; thirdly, to optimise the digital inclusive finance policy system and strengthen the supervision of rural digital finance.

Analysis on the correlation between credit scale of financial institutions and stock market price data

This paper analyzes the degree of association between credit size of financial institutions and stock market prices in China based on monthly data from November 2006 to November 2016 using impulse response function because of VAR time series model. The results show that there is a two-way Granger causality between the credit size of financial institutions and stock market prices when the lag order is 2. The impact of credit size of financial institutions on stock market price shocks is larger in the short-term, and this effect rapidly decreases to near zero after the med-long term. Conversely, the med-long term shocks to the credit size of financial institutions are larger than the short-term shocks by stock market prices.

Digital Finance, Interbank Market Friction and Credit Channel Transmission of Monetary Policy

At present, China’s digital economy is booming, and the digitization of the financial system is gradually changing the internal structure of macro economy and finance, which has an impact on the first market of monetary policy transmission, the interbank market, and affects the transmission of monetary policy. Based on the case of inter-bank market friction, this paper constructs an IS-LM-CC model to deeply analyze the micro-effect mechanism of digital finance affecting credit channel transmission. The panel data of China’s provincial level from 2011 to 2020 are selected to construct a fixed effect model to empirically test the impact of digital finance on monetary policy through credit channels. Using micro data at the enterprise level, we further test whether the development of digital finance affects the dependence of enterprises on bank credit. The results show that the development of digital finance has alleviated the friction in the interbank market, significantly weakened the transmission effect of monetary policy bank credit, and reduced the dependence of enterprises on bank credit. Therefore, this paper proposes to rationally plan the statistical scope of credit scale and correctly guide the development of digital finance.

A Study on the Credit Scale of Commercial Banks

A Study on the Credit Scale of Commercial Banks

Analysis of the Mediating Effect of Economic Policy Uncertainty Affecting Commercial Bank Credit

<p>We analyze the annual microdata of China's 100 commercial banks from 2007 to 2018 using the mediating effect analysis method, analyze the negative impact of economic policy uncertainty on the credit scale of commercial banks, and then verify the intermediary effects of the operational risks and short-term capital liquidity of commercial banks in the impact of economic policy uncertainty on the scale of commercial bank credit, separately. Moreover, we find that non-state-owned commercial banks, large-scale commercial banks, low-leverage commercial banks, and commercial banks with low profitability are more susceptible to economic policy uncertainty affecting commercial bank credit growth through short-term capital liquidity, and vice versa.</p>