Credit Allocation Research Articles

Distribution of decarbonization costs and externality regulation

The transformation of the economy to a low-carbon level is constrained by a high level of costs and the problem of balancing interests in the distribution of these costs among participants. The paper proposes to use the corporate game theory, in particular the Shapley value, for cost allocation. In contrast to the classical division of additional utility for cooperative games, in this case the costs are divided, and the concave cost function is minimized. The Shapley value coordinates determine the center of gravity of the multidimensional figure of possible cost distributions and are associated with a formal representation of fairness without taking into account financial opportunities and additional, historically established conditions. A comparative analysis of two approaches (carbon tax and carbon credits) to managing negative externalities shows that it is preferable to use the Shapley value for the base allocation of carbon credits. Both approaches to emissions regulation are constrained by institutional barriers to the transformation of the economy: the level of development of national institutions, the achievement of international agreements in the face of economic competition and political confrontation, and the lack of objective information. The authors come to the conclusion that the use of the Shapley value can contribute to the objective formation of quotas and reduce barriers to decarbonization.

EMPIRICAL ANALYSES OF FINANCIAL CREDIT ON SMALLHOLDER FARMER’S PRODUCTIVITY MODELLING FARMERS CREDIT ALLOCATION FROM RURAL BANKS IN SIERRA LEONE

Sierra Leone has experienced an increase in farmers’ accessibility to financial credit facilities in recent time. Financial credit plays a significant role in enhancing productivity and efficiency within the agricultural sector of emerging nations, and Sierra Leone is not exempt from this trend. The present study investigates the allocation of financial credit among farmers and its impact on technical efficiency. A three-stage sampling methodology was employed to gather cross-sectional data from a sample of 500 agricultural producers in Sierra Leone. The objective of this study was to evaluate the influence of financial support on agricultural productivity, with the ultimate goal of enhancing economic and technical efficiency. The evaluation of the effect of allocation techniques on technical efficiency is conducted through the utilization of the random frontiers truncated-normal with the conditional average model. The present study employed the Heckman treatment effect model and stochastic frontier analysis (SFA) to examine the production efficiency of smallholder farmers. The study’s empirical findings indicate that the provision of financial assistance by community banks has a notable and favorable impact on the technical efficiency of farmers. Despite the presence of many constraints, farmers’ access to financial financing remains limited. This is reflected in the total technical efficiency of farmers, which was measured at 0.81 (81%). This indicates that none of the farmers were able to achieve a production threshold of 1 (100%). Nevertheless, it is worth noting that the average disparity in efficiency between individuals who borrowed and those who did not borrow was 0.09, equivalent to a 9% variation. This finding provides further evidence supporting the notion that access to financial credit has a beneficial effect on the efficiency of farmers. This, in turn, leads to a reduction in the severity of poverty and extreme poverty. Despite facing challenges such as pest and disease infestations, financial constraints, and unpredictable weather conditions, the inefficiency model demonstrated that factors such as education, membership in a farmer-based organization, experience, access to credit, and participation in a government-sponsored mass spraying program had a notable and favorable influence on efficiency scores. Hence, it is advisable to propose a policy aimed at enhancing the accessibility of financial services from community and rural banking institutions that includes every group of smallholder farmers in Sierra Leone.

Financial Development, Exchange Rate Stability and Trade in Nigeria

This study examines the impact of financial development, exchange rate stability, economic progress, FDI, and population on trade in Nigeria using the ARDL approach of estimation from the period 1980 to 2022. The outcome of the unit root test indicates that all the variables are stationary at one percent level of significance. Similarly, the bound test also confirms the long-run association among the model variables. The result of the short-run estimates reveals that financial development; exchange rate stability, economic progress and FDI increased the level of trade in Nigeria. However, population is not a determinant factor of trade in the nation. The long-run result shows that financial development, exchange rate stability, economic progress, FDI, and population significantly increase the level of trade performance in the country. Hence, the study suggests financial development policy reform through monetary policy instruments that will enhance the level of credit allocation and maintain the stability of exchange for effective trade and economic growth in the country. Nonetheless, the limitation of the study may consist of the incorporation of other important variables like energy use, industrial growth, and pollution. Accordingly, future studies should consider these factors to improve the policy analysis and recommendations.

Local Government Debt and Bank Credit Allocation: Evidence from China

Local Government Debt and Bank Credit Allocation: Evidence from China

Rethinking Basel III and beyond: a theory model to understand credit allocation and real state bubbles

Rethinking Basel III and beyond: a theory model to understand credit allocation and real state bubbles

Investigating the Finance-Energy-Growth Trilogy in Sub-Saharan Africa: Evidence From the NARDL Framework

This paper analyzes the nexus between energy consumption, financial development, and economic growth in twenty-one (21) sub-Saharan African (SSA) nations by using the nonlinear autoregressive distributed lag (NARDL) framework from 1990Q1 to 2014Q4. First, the study reveals that energy consumption and financial development have asymmetrical impacts on economic growth in most countries in the short and long term. Second, positive shocks to financial development favor economic growth in only a few nations compared to the negative shocks in the short term, whereas they have mixed effects in the long term. Third, we found that adverse shocks to energy consumption boost economic growth in several nations in the short term, unlike the positive shocks, but the scenario has reversed in the long term. We also found that gross fixed capital formation and labor force remain key factors promoting economic growth in many SSA countries, in contrast to the mixed effects of trade openness over time. Accordingly, our study recommends implementing energy-saving policies in specific SSA countries to stimulate sustainable development. Policymakers must embrace an effective credit allocation to the private sector supporting productive investments. Governments should also optimize domestic investments in physical capital, upgrade the labor force, and implement efficient strategies in international trade. These policy recommendations need to be implemented according to the unique socio-economic characteristics of each SSA country.

What is the potential of hybrid cordon pricing policy for reducing and shifting car usage in cities?

As cities need to urgently transition out of unsustainable mobility systems, following the Avoid-Shift-Improve framework, changes in travel behavior have a top priority. Although behavior change in is a complex phenomenon, previous research informs us about the importance of urban road-usage policy measures. One such policy measure is often referred to as congestion pricing (CP). Some cities have successfully implemented CP, showing its effectiveness potential in behavior change, but wide-spread implementation lags due to challenges in societal, organizational, and political acceptance and implementability. Emerging literature on mobility credits (MC), mostly based on experiments, has brought forward the questions of acceptance, showing different possibilities for credit allocation, accumulation and exchange. In addition to behavior change, cities in transition economies might also consider monetary policies as potential solutions to financing issues. This research aims to analyze benefits and challenges of implementing a hybrid scheme that is a combination of CP and MC, developed with an expectation for policy coherence and complementarity. To determine the effects of the proposed hybrid scheme, a comparative analysis of user attitudes on congestion charging was conducted. The research was conducted using an online questionnaire, and the target group consisted of the residents of Belgrade (Serbia). Since these strategies are not implemented in Belgrade, the stated choice approach was used. The survey contained questions about the socio-demographic characteristics of the users, trip characteristics, users’ acceptability of CP and the hybrid scheme, as well as the questions on transport mode usage for commuting trips and for trips with other purposes. Based on statistical and policy analysis, it was determined that the hybrid scheme represents a suitable compromise solution which would reduce passenger car trips in the city center and while increase public acceptance for such normative policies.

Large private shareholders, industrial policies and industrial loans of city commercial banks: Evidence from China.

We show that large private shareholders have an information advantage about their industry; this can alleviate the information asymmetry suffered by banks, and consequently, increase bank lending to these shareholders' industry. Using a sample of Chinese city commercial banks, we show that an increase in the large private shareholders' shareholding of banks increases bank lending to these shareholders' industry. Importantly, using Chinese local government industrial policy as a moderator, we find that industrial policies have a positive and significant moderating effect on the relationship between large private shareholders and banks' industry-specific lending. This relationship strengthens when local industrial policy supports these shareholders' industry. This helps explain why banks prefer the industries to which their large private shareholders belong to and how industrial policy affects bank credit allocation.

Energy saving and emission reduction fiscal policy and corporate green technology innovation.

With the increasing prominence of resource and environmental issues, countries around the world are paying more and more attention to the concept of sustainable development. Under this concept, China started to implement a pilot project of "National Comprehensive Demonstration City of Energy Saving and Emission Reduction Fiscal Policy" in 2011 to protect resources and environment through green and low-carbon development. This paper aims to investigate whether and how the pilot policy induces corporate green technology innovation. Based on the data on Chinese listed firms from 2008 to 2019 and the relevant theories of economics, management and organizational psychology, we find that the pilot policy can promote corporate green technology innovation. This indicates that the pilot policy, as an external force, will encourage firms to improve their adaptability through green technology innovation which is one type of organizational change, thus improving their organizational effectiveness. The heterogeneity analyses reveal that the promotion effect of the pilot policy on green innovation is stronger among firms in high-carbon industries, firms in the mature stage and firms that are not state-owned. The mechanism tests find that the credit allocation effect and innovation compensation effect generated by the pilot policy are the key channels to promote green technology innovation. In addition to enriching the research on the evaluation of the effects of the pilot policy, our paper also expands the literature on organizational psychology and organizational change from the perspective of corporate green innovation, offers practical implications for the low-carbon transition of manufacturing industries under the emission peak and carbon neutrality targets, and provides insights for other emerging economies to achieve better resource and environmental protection through the energy saving and emission reduction fiscal policy.

RESEARCHING ALGORITHMS FOR CREDIT ALLOCATION USING DEEP LEARNING METHODS

RESEARCHING ALGORITHMS FOR CREDIT ALLOCATION USING DEEP LEARNING METHODS

An improved author-topic (AT) model with authorship credit allocation schemes

Authorship credit allocation schemes have attracted considerable research attention. However, no consensus about which one is the best has been attained until now, and limited evidence from practical tasks has been reported. Therefore, this study uses the author interest discovery task as a real-world task case to provide valuable insights into authorship credit allocation schemes and guidelines for further practical applications. For this purpose, a novel model, ATcredit, is proposed to strengthen the Author-Topic (AT) model with an authorship credit allocation scheme, and collapsed Gibbs sampling is used to approximate the posterior and estimate model parameters. Extensive experiments using the SynBio dataset reveal several interesting findings as follows. (a) Any scheme for allocating unequal authorship credits performs better than its equal-credit counterpart with our ATcredit model in terms of perplexity. (b) The fixed versions of four out of the six schemes work better than their flexible counterparts with our ATcredit model, regardless of the hyper-authorship strategy. (c) The variation coefficient of credit awards can serve as a criterion to decide whether the hyper-authorship strategy should be used. (d) When the number of authors in a scholarly article is less than three, the six authorship credit allocation schemes are similar to each other with our ATcredit model in terms of perplexity. (e) The harmonic counting scheme performs the best, followed by the arithmetic counting scheme, and the network-based counting scheme performs the worst with our ATcredit model in terms of perplexity. (f) The arithmetic counting scheme is similar to the harmonic counting scheme in terms of the normalised mutual information (NMI) of discovered interests, but the geometric counting scheme is different from the axiomatic and network-based counting schemes.

Sex, Race, and the Allocation of Credit in Dispersed Teams: Whose Contributions to Team Success Get Noticed and Whose Get Neglected

Abstract When the members of a team work together in pursuit of a collective goal, who stands out? We analyze this question by focusing on how managers allocate credit among a team’s members when employee performance is difficult to observe. We argue that under conditions of incomplete information, managers use whatever information they have readily at hand—even if it is only crudely reflective of individual performance—to make inferences about team members’ contributions to team success. We further argue that these inferences will tend to disadvantage women and persons of color relative to white men. Our information-based perspective points to additional propositions that are theoretically novel: Imperfect information will be more severe when a team member works remotely; consequently, team members who are colocated with their manager will be more likely than non-colocated team members to receive recognition for their contributions to team success. Moreover, we argue that any informational disadvantages attaching to remoteness will vary by team members’ race/sex. We use micro-data on 121,809 federal employees who are nested in 31,188 group award instances, and employ a fixed effects approach to test these and related propositions. Our findings’ key implications for theory are that managers allocating credit among a group’s members will tend to do so suboptimally in demographically diverse, geographically dispersed groups. These managers will tend to overlook the contributions of women and persons of color, and will also tend to overlook the contributions of remote team members.

Green credit policy and investment-cash flow sensitivity: Evidence from a quasi-natural experiment

The green credit policy (GCP) in China aims to achieve green development by reducing credit allocations to heavily polluting enterprises. Using the implementation of the GCP as a shock to the cost of external financing, we conduct a difference-in-differences approach and find that the investment-cash flow sensitivity of heavily polluting enterprises increases significantly after the implementation of the GCP. The effect is more pronounced in firms with high investment opportunities and high financial leverage and in firms without ownership in commercial banks. Our paper provides new insights into the impact of the GCP on financial constraints and contributes to the investment-cash flow sensitivity debate by using an exogenous shock to measure financial constraints. The results suggest that investment-cash flow sensitivity may be a reasonable indicator of financial constraints in the context of China.

Autonomous Vehicle Adoption in Developing Countries: Futurist Insights

In recent years, research into autonomous vehicles (AVs) has become highly popular in industrialized nations due to their importance in the future success of smart cities. Research on this mobility technology and the critical elements affecting its development in developing countries, however, has been rather limited. This paper aims to shed light on the most influential elements of AV adoption in developing nations. A structural analysis approach is used, based on the primary qualitative data—that was gathered via an expert-opinion poll utilizing the fuzzy Delphi with a snowballing method and engaging 25 experts in the field in two rounds—, in accordance with the tradition of futurist research. The analysis has led to the identification of 11 key factors, from the initial factor pool of 54, affecting AV adoption in the case study context of Iran. The results of the analysis revealed the following conclusions, that fall under the policy and legislation domain, and present the most significant issues impacting AV adoption: (a) Future orientation of government—consistency and of accountability of policies, the long-term vision of the government for developing AVs industry; (b) Managing the international sanctions for foreign investment, and; (c) Funding mega projects to enable AVs. The results indicate that the establishment of legislation and the formulation of government policy regarding the provision of infrastructure, investment, and credit allocation are crucial for the development of AVs in Iran and other developing nations with comparable characteristics.

Credit Environment and Small Business Dynamics: Evidence from Establishment-Level Data

Abstract We evaluate how a positive, technology-driven shock to bank liquidity affects small business dynamics across different size distributions. We first show that banks receiving positive liquidity shocks increase lending to relatively larger SMEs, not to the smallest firms. This finding is consistent with the view that a positive liquidity shock enhances bank charter values, thereby reducing risk-taking incentives. Moreover, such disproportionate credit allocation leads to a crowding-out effect on micro firms. When larger SMEs grow faster and exit less because of better access to credit, their expansion stifles the development of micro firms, whose access to credit remains unchanged. (JEL G21, J21, L22)

Does climate change affect bank lending behavior?

We examine how banks adjust credit supply in areas with higher exposure to climate risks by utilizing the province-level air pollution and loan growth data of a large emerging market, Turkey, following the Paris Agreement in 2015. Our results show that banks limit their credit extension to more polluted provinces in the post-agreement interval, implying that banks consider climate change-related risks and adjust their credit provisioning accordingly. Our baseline findings are intact against a myriad of robustness checks. We also find that the shift in the climate risk-credit provisioning nexus is asymmetric depending on the levels of air pollution. • In the Turkish banking sector, banks adjust credit allocation to provinces with air pollution following the Paris Agreement. • This behavior is not only limited to private banks but is also initiated by state-owned banking entities. • The shift in the association between climate risks and loan growth is stronger for commercial loans. • The relationship between climate risks and loan growth is asymmetric contingent on the level of air pollution.

Dynamization Analysis of Capital Inflow, Credit Allocation, and Banking Performance using Panel Vector Autoregressive

The direction of globalization and the integration of the financial system continue to increase, in line with the increasing capital flows, which is the focus of discussion in this research. This study applies panel data analysis to analyze banking behavior in order to improve its performance. The analysis uses panel data from 1991 to 2020 in 39 countries. Return on Equity (ROE) as a measure of the success of banking operations is determined by various interrelated factors. One of the variables closely related to banking performance is the share of non-financial business loans, the share of capital inflows entering the banking sector, and the share of capital inflows entering the non-bank sector. Economic variables that support good banking performance are GDP growth, bank concentration, inflation, leverage, and bank efficiency. This article applies a Panel Vector Autoregressive to capture the dynamization, and heterogeneity. The most exciting results were obtained by dividing the sample into subgroups, which helped the researcher understand each regime's different roles and transmissions. The changes in capital inflows to the non-bank sector will significantly reduce ROE and increase leverage for the next five periods. The results of the study imply that nowadays, bank managers should be aware while the changes in capital inflows change very quickly. Bank managers in countries with high capital inflows must always be aware of changes in capital inflows to the non-bank sector—steps to bank management by diversifying sources of funds efficiently from other parties in the transmission of credit channel.

How to Rate the Financial Performance of Private Companies? A Tailored Integrated Rating Methodology Applied to North-Eastern Italian Districts

This paper contributes to solving the puzzle of assessing the financial performance of private/unlisted companies. The inner characteristics of these companies make the adoption of traditional best practices in estimating risk premia difficult or impossible. Moreover, the lack of market data and comparable information biases the perception of corporate performance and generates the misallocation of credit fundings (both quantities and pricing). Hence, in this paper, we develop an Integrated Rating Methodology (IRM) to estimate a more efficient corporate “return-to-risk” measure. Our IRM is rooted in the seminal “certainty equivalent” model as developed by Lintner in 1965, but we modify it using a shortfall approach, and then compute a “confident equivalent” that is compliant with Fischer Black’s zero-beta model as well as the Basel agreements. An empirical application of the approach is conducted with a sample of 13,583 non-financial SMEs in the north-east regions of Italy, where there is evidence of inefficient bank financing. We back-test our IRM by rating these companies using corporate financial data during the period 2007–2014, which encompasses both the Great Financial Crisis and the European sovereign debt crisis. Our empirical results depict a clear crowding-out effect of credit allocations when we compare our IRM scoring measure with the actual raising ability and the cost of capital relating to these firms. We find that 36% of companies are underfunded, even if they have a superior IRM score, while 27% of them are funded without merit. Interestingly, this last figure is in line with the average non-performing loan ratio provided by official Italian statistics from 2015 to 2020. Therefore, we conclude that our IRM methodology is promising and may be better at estimating risk financing in small private companies (including start-ups) than internal banking models. These initial results will drive our forthcoming research towards creating an IRM 2.0.

The impact of technological innovations on financial deepening: Implications for SME financing in Africa

AbstractThis paper examines whether technological innovations such as information and communication technology infrastructure, mobile phone subscriptions, secure internet servers and the number of automated teller machines and bank branches increased financial deepening in 43 African countries for the period 2010–2019. The study employs panel corrected standard errors, fixed effects and quantile regressions for empirical analysis. The results show that technological innovations have a positive and significant influence on financial deepening in Africa in terms of banks’ mobilisation of deposits and allocation of credit to enterprises. Furthermore, the technological indicators have a strong and positive effect on higher levels of bank credit to the private sector than lower levels. As for bank deposits, only the number of branches was found to have significant and positive effects at a high level of bank deposits compared with a low level. These results imply that African governments and development partners can leverage ICT developments to increase financial deepening and reinvigorate debt financing, which is the primary funding source for small and medium‐size enterprises.

Event-triggered multi-agent credit allocation pursuit-evasion algorithm

Event-triggered multi-agent credit allocation pursuit-evasion algorithm