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We study the relationship between credit expansions, macroeconomic fluctuations, and financial crises using a novel database on the sectoral distribution of private credit for 117 countries since 1940. We document that, during credit booms, credit flows disproportionately to the non-tradable sector. Credit expansions to the non-tradable sector, in turn, systematically predict subsequent growth slowdowns and financial crises. In contrast, credit expansions to the tradable sector are associated with sustained output and productivity growth without a higher risk of a financial crisis. To understand these patterns, we show that firms in the non-tradable sector tend to be smaller, more reliant on loans secured by real estate, and more likely to default during crises. Our findings are consistent with models in which credit booms to the non-tradable sector are driven by easy financing conditions and amplified by collateral feedbacks, contributing to increased financial fragility and a boom–bust cycle. [ABSTRACT FROM AUTHOR]

This paper examines the consequences of Chinese regulators deviating from a long-standing full bailout policy in addressing the distress of a city-level commercial bank. This policy shift led to a persistent widening of credit spreads and a significant decline in funding ratios for negotiable certificates of deposit issued by small banks relative to large ones. Our empirical analysis reveals a novel contagion mechanism driven by reduced confidence in future bailouts (implicit non-guarantee), contributing to the subsequent collapse of other small banks. However, in the longer term, this policy shift improved price efficiency, credit allocation, and discouraged risk-taking among small banks. [ABSTRACT FROM AUTHOR]

We studied the impact of major floods occurring in Turkey between 2005 and 2020 on lending and the allocation of loans between sectors that differ in their CO2 emissions. Our evidence shows that the floods are not significant determinants of lending or the allocation of loans between sectors, even though CO2 emissions contribute to the reallocation of loans from the more polluting to the less polluting sectors. Indeed, risks and returns of the sector remain the main determinants of lending and of the allocation of loans among sectors. The results are robust to alternative estimation methods and specifications of the econometric models. Since in the period of investigation no environmental regulations were implemented in Turkey, and the Paris Agreement was ratified only at end-2021, the evidence suggests that more stringent regulations and green policies are required to accelerate the green transition in Turkey. [ABSTRACT FROM AUTHOR]

The structural effects of monetary policy and these effects impact on credit allocation are crucial facets of monetary policy research. This study initially estimates China's monetary policy based on the GDP growth target and CPI target found in the Chinese Government's Annual Work Report. Subsequently, it quantifies the extent of credit misallocation among Chinese firms using data from listed companies from the years 2013 to 2022. Finally, we empirically investigate the repercussions of expansionary monetary policy shocks on credit misallocation, focusing on micro-firms. Empirical findings reveal that expansionary monetary policy significantly exacerbates credit misallocation, particularly in underfinanced firms. Mechanistic analysis suggests that a preference for loan size in lending behavior constitutes a major factor contributing to credit misallocation among firms. [ABSTRACT FROM AUTHOR]

The tracking framework based on the memory network has gained significant attention due to its enhanced adaptability to variations in target appearance. However, the performance of the framework is limited by the negative effects of distractors in the background. Hence, this paper proposes a method for tracking using Credit Allocation Network to join target and distractor memory. Specifically, we design a Credit Allocation Network (CAN) that is updated online via Guided Focus Loss. The CAN produces credit scores for tracking results by learning features of the target object, ensuring the update of reliable samples for storage in the memory pool. Furthermore, we construct a multi-domain memory model that simultaneously captures target and background information from multiple historical intervals, which can build a more compatible object appearance model while increasing the diversity of the memory sample. Moreover, a novel target–distractor joint localization strategy is presented, which read target and distractor information from memory frames based on cross-attention, so as to cancel out wrong responses in the target response map by using the distractor response map. The experimental results on OTB-2015, GOT-10k, UAV123, LaSOT, and VOT-2018 datasets show the competitiveness and effectiveness of the proposed method compared to other trackers. [ABSTRACT FROM AUTHOR]

This article investigates how cross-selling affects relationship lending using internal data from a large bank and the Swedish credit registry. I show that within a bank–firm relationship, profit earned from non-loan products cross-subsidizes loans and increases (1) credit supply and (2) the likelihood of the bank's pausing or waiving interest payments for delinquent loans (lenience in delinquency). For identification, I exploit the Basel II-induced exogenous variation in products' profitability while holding constant the firm's creditworthiness and relationship informativeness. I find that the average affected firm experienced a decrease of 6 percent ($400,000) in credit supply and 30 percent (9.8 pp) in lenience in delinquency. The results highlight the importance of cross-subsidization as a mechanism through which cross-selling affects bank–firm relationships and inform optimal regulatory design for lenders who multi-produce. [ABSTRACT FROM AUTHOR]

The purpose of this study is to propose an improved credit allocation method that makes the leading author of the paper more distinguishable and makes the deification more robust under malicious manipulations.

Using Vector autoregression (VAR), variance decomposition and Pearson correlation techniques, this study investigates the impact of digital finance on banks' credit allocation in Nigeria between 2009Q1 and 2019Q4. The study specifically aims to examine the impact of digital finance (proxied with value of Automated Teller Machine (ATM), Point of Sales (POS) and web payment (WEBPAY) transactions) on total sectorial credit allocation of deposit money banks in Nigeria. This study finds no long-run relationship between digital finance and credit allocation of deposit of money banks in Nigeria. Furthermore, digital finance and banks' credit allocation were found to have strong and positive correlation in Nigeria. It is also unveiled that, unlike the value of POS transactions which have negative and non-significant impact, the value of ATM and WEBPAY transactions have positive but non-significant impacts on banks' credit allocation in Nigeria. It can therefore be concluded that, though, a strong and positive correlation exists between digital finance and banks' credit allocation but the former (digital finance) does not exert significant impact on the latter (credit allocation function of deposit money banks) in Nigeria in the period of study. There is therefore the need for the current pace of digital finance adoption in Nigeria be intensified in order for it to achieve the desirable impact on banks' credit allocation function in the country. [ABSTRACT FROM AUTHOR]

To obtain high-resolution and high-precision images, the aviation remote sensing stabilization platform (ARSSP) is used, which enables the isolation of unpredictable aerial camera movements during aerial photography. However, because of the interaxle coupling interference and other nonlinear interferences in the ARSSP system, the imaging quality of the aerial camera is adversely affected. Therefore, we derived the dynamic model of moment coupling between shafts to illustrate the problem. On the basis of the former proportion integration differentiation (PID) controller based on cerebellar neural network, a nonlinear cross feedback decoupling scheme is adopted to reduce the adverse effects of these interferences. The cerebellar model articulation controller (CMAC) based on synovial membrane control (SMC) is used to reduce the nonlinear interferences caused by the new cross-decoupling module. To verify the effectiveness of the scheme, simulation, indoor and outdoor experiments were conducted. The results showed that the SMC-CMAC significantly reduced the interaxle coupling effect and effectively suppressed the nonlinear interference, resulting in a good tracking performance of the ARSSP system. [ABSTRACT FROM AUTHOR]

The possibility of creating a state bank has received much recent attention in the USA. In 2021, six states introduced legislation to create a state bank; in 2019, similar legislation was enacted in California for municipal banks. This article develops a framework to evaluate state banking, reviews prior experiences with state banking and related alternatives to traditional private banking, and identifies five questions determining the advisability of creating a state bank. The overall goal is to shed some light on whether a state bank can be a useful tool to further state economic development and the welfare of state residents (JEL codes: G21 (banks), G28 (government policy, financial institutions), and H70 (state and local governments)). [ABSTRACT FROM AUTHOR]

• Evaluate causal effect of government debt reduction on entrepreneurship. • Leverage a revised budget law reform in china as quasi-natural experiment. • Identify optimized land utilization and enhanced access to start-up loans as crucial mechanisms driving new firm creation. • Observe sector-specific effects on lowering entry barriers particularly in unregulated and downstream industries. • Delve into the quantity and quality of entrepreneurship to reveal a more vibrant and resilient entrepreneurial ecosystem. This study evaluates the causal effect of government debt on entrepreneurship. Exploiting New Budget Law reform in China that regulates the scale of local government debt, we find that government debt reduction bolsters entrepreneurial ventures by optimizing land utilization and enhancing access to start-up loans. Consistently, the entrepreneurial effect is more pronounced in unregulated industries and downstream sectors. Furthermore, we demonstrate that government debt reduction also contributes to entrepreneurship quality. It induces smaller entrants with higher survival rates post-reform, resulting in more incumbent enterprises exiting. Our results underscore the benefits of encouraging government debt governance experimentation in lowering entry barriers. [ABSTRACT FROM AUTHOR]

The worldwide financial crisis of 2007–2008 raised serious concerns about the soundness of banks' activities and about the extent to which banking regulation should supervise banks' investment decisions. We contribute to this topic by examining the Spanish case, which has been emblematic of the bubble and burst dynamics in the credit market. In particular, we study the allocation of bank credit among Spanish companies from 1999 to 2014, showing that larger companies accumulated greater amounts of bank loans per unit of total assets, thus leading to a notable concentration. We also find that, during the Spanish boom period, bank loans shifted from the manufacturing to the construction industry, and in particular to the largest companies of the latter sector. This happened in spite of the high leverage of large construction firms, which was increasing also due to their growing debt. We argue that the higher operating benefits, reflecting the increase of the housing price during the boom period, overvalued construction firms as potential borrowers. The bankruptcy of several large construction companies during the Spanish crisis supports the need for monitoring and regulation, to avoid an excessive concentration of bank credit to a few large companies, especially if they belong to a specific sector. [ABSTRACT FROM AUTHOR]

Prior research on collaboration and creativity often assumes that individuals choose to collaborate to improve the quality of their output. Given the growing role of collaboration and autonomous teams in creative work, the validity of this assumption has important implications for organizations. We argue that in the presence of a collaboration credit premium—when the sum of fractional credit allocated to each collaborator exceeds 100%—individuals may choose to work together even when the project output is of low quality or when its prospects are diminished by collaborating. We test our argument on a sample of economists in academia using the norm of alphabetical ordering of authors' surnames on academic articles as an instrument for selection into collaboration. This norm means that economists whose family name begins with a letter from the beginning of the alphabet receive systematically more credit for collaborative work than economists whose family name begins with a letter from the end of the alphabet. We show that, in the presence of a credit premium, individuals may choose to collaborate, even if this choice decreases output quality. Thus, collaboration can create a misalignment between the incentives of creative workers and the prospects of the project. [ABSTRACT FROM AUTHOR]

Credit rationing theory suggests that the impact of bank credit allocation on corporate social responsibility (CSR) has the dual effect of adverse selection and moral hazard. In this study, the impact of credit allocation on CSR and its mechanisms are explored in the context of credit rationing theory based on Chinese listed companies from 2010 to 2019. The results show that the impact of bank credit allocation on CSR exhibits an inverted U‐shaped correlation, and there is a critical point (17.9134) at which the increase in credit allocation will promote the level of CSR until the critical point is exceeded, after which the level of CSR will gradually decrease. Credit allocation can influence CSR through information asymmetry (stock price informativeness, analyst tracking) and managerial overconfidence, respectively. Companies with overconfident managers and low transparency in non‐socially responsible weighting systems are more likely to have an inverted U‐shaped relationship between bank credit allocation and CSR. This study provides new empirical evidence to understand the impact of credit allocation on CSR and expands the theory of credit rationing to a certain extent, thereby providing a reference for CSR maximization. [ABSTRACT FROM AUTHOR]

With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others' scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collaborations is the possibility of unambiguously defining the expertise of other researchers. While some organisations have established database systems to enable their members to manually produce a profile, maintaining such systems is time-consuming and costly. Therefore, there has been a growing interest in retrieving expertise through automated approaches. Indeed, the identification of researchers' expertise is of great value in many applications, such as identifying qualified experts to supervise new researchers, assigning manuscripts to reviewers, and forming a qualified team. Here, we propose a network-based approach to the construction of authors' expertise profiles. Using the MEDLINE corpus as an example, we show that our method can be applied to a number of widely used data sets and outperforms other methods traditionally used for expertise identification. [ABSTRACT FROM AUTHOR]

Scientific communities confer many forms of credit on their successful members. The motivation provided by these forms of credit helps shaping a community's collective attention toward different lines of research. The allocation of scientific credit, however, has also been the focus of long-documented pathologies: certain research questions are said to command more credit then they deserve; and certain researchers seem to receive a disproportionate share of the credit. Here we show that each of these pathologies can actually increase the collective productivity of a community. We consider a model for the allocation of credit, in which individuals pick a project among projects of varying importance and difficulty levels, and compete to receive credit with others who choose the same project. Under the most natural allocation mechanism, in which credit is divided equally among those who succeed at a project in proportion to the project's importance, the resulting selection of projects by self-interested, credit-maximizing individuals will in general be socially sub-optimal. However, we show that there exist ways of allocating credit both out of proportion to the true importance of the projects and out of proportion to the relative contributions of the individuals, that lead credit-maximizing individuals to achieve social optimality. These results therefore suggest how well-known forms of misallocation of scientific credit can in fact serve to channel self-interested behavior into socially optimal outcomes. [ABSTRACT FROM AUTHOR]

To obtain high-resolution and high-precision images, the aviation remote sensing stabilization platform (ARSSP) is used, which enables the isolation of unpredictable aerial camera movements during aerial photography. However, because of the interaxle coupling interference and other nonlinear interferences in the ARSSP system, the imaging quality of the aerial camera is adversely affected. Therefore, we derived the dynamic model of moment coupling between shafts to illustrate the problem. On the basis of the former proportion integration differentiation (PID) controller based on cerebellar neural network, a nonlinear cross feedback decoupling scheme is adopted to reduce the adverse effects of these interferences. The cerebellar model articulation controller (CMAC) based on synovial membrane control (SMC) is used to reduce the nonlinear interferences caused by the new cross-decoupling module. To verify the effectiveness of the scheme, simulation, indoor and outdoor experiments were conducted. The results showed that the SMC-CMAC significantly reduced the interaxle coupling effect and effectively suppressed the nonlinear interference, resulting in a good tracking performance of the ARSSP system.

This paper employs euro area firm‐level data covering the years 2002–18 to examine the impact of cross‐border debt flows on the domestic allocation of credit across firms conditional on their profitability. As only debt flows driven by global push factors are exogenous with respect to domestic credit allocation, I overcome the endogeneity of debt flows by instrumenting them with a measure of global uncertainty (VIX). My results show that debt flows raise the credit growth rates of low performing firms significantly more than those of high performing firms. This result is driven by domestic banking sectors with lower capitalization. [ABSTRACT FROM AUTHOR]

The purpose of this study is to address the critical issue of optimal credit allocation. Predicting a borrower's probability of default is a key requirement of any credit allocation system but turning it into labeled classes leads to problems in performance measurement. In this paper the connection between the probability of default and optimal credit allocation is established through a conceptual construct called the Kelly criterion. Conflicting performance measures in dichotomous classification are replaced with coherent criteria for judging the performance of credit allocation decisions. Extensive testing on peer-to-peer lending data shows that the Kelly strategy enables consistent outperformance and efficiency in processing information relative to alternative credit allocation approaches. [ABSTRACT FROM AUTHOR]

Copyright of Semestre Económico is the property of Sello Editorial de la Universidad de Medellin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, an end-of-life (EOL) model is included in the life cycle energy optimization (LCEO) methodology to account for the energy burdens and credits stemming from a vehicle's EOL processing phase and balance them against the vehicle's functional requirements and production and use-phase energies. The substitution with a correction factor allocation method is used to model the contribution of recycling to the EOL phase's energy. The methodology is illustrated through the optimization of the design of a simplified vehicle subsystem. For the latter, multiple recycling scenarios with varying levels of assumed recycling induced material property degradation were built, and their impact on the vehicle subsystem's optimal solutions was compared to that of scenarios based on landfilling and incineration with energy recovery. The results show that the vehicle subsystem's optimal designs are significantly dependent on the EOL scenario considered. In particular, the optimal designs associated with the recycling scenarios are on average substantially heavier, and less life cycle energy demanding, than their landfilling or incineration with energy recovery-related counterparts, thus demonstrating how the inclusion of EOL modeling in the LCEO methodology can significantly alter material use patterns, thereby effecting the very mechanisms enabling the embodiment of the resulting life cycle energy optimal designs. [ABSTRACT FROM AUTHOR]

We provide an initial assessment of the Federal Reserve's policy response to the COVID‐19 contraction. We briefly review the historical episode and consider the standard textbook treatment of a pandemic on the macroeconomy. We summarize and then evaluate the Fed's monetary and emergency lending policies through the end of 2020. We credit the Fed with promoting monetary stability while maintaining that it could have done more. We argue that the Fed could have achieved stability without employing its emergency lending facilities. Although some facilities likely helped to promote general liquidity, others were primarily intended to allocate credit, which blurs the line between monetary and fiscal policy. These credit allocation facilities were unwarranted and unwise. [ABSTRACT FROM AUTHOR]

This paper investigates how government-led banking liberalization affects credit allocation by banks using as a quasi-natural experiment the establishment of city commercial banks (CCBs) in China. Based on more than three million corporate financial statements spanning over 16 years, we find that the establishment of CCBs led to a 6-14 % drop in debt funding for private firms, as well as a 1-2 % rise in their funding costs. At the same time, private infrastructure firms enjoyed a nearly 6 % increase in debt funding and more than 100-basis-point drop in interest costs despite their inferior credit quality. The debt financing of private firm appears most severely affected in municipalities where officials face high promotional pressures or fiscal constraints. [ABSTRACT FROM AUTHOR]

This paper utilizes a countrywide process of county-to-city upgrading in the 1990s to identify whether extending the powers of urban local governments leads to better firm outcomes. The paper hypothesizes that since local leaders in newly promoted cities have an incentive to utilize their new administrative remit to maximize gross domestic product and employment, there should be improvements in economic outcomes. In fact, aggregate firm-level outcomes do not necessarily improve after county-to-city graduation. However, state-owned enterprises perform better after graduation, with increased access to credit through state-owned banks as a possible explanation. Importantly, newly promoted cities with high capacity generally produce better aggregate firm outcomes compared with newly promoted cities with low capacity. The conclusions are twofold. First, relaxing credit constraints for firms could lead to large increases in their operations and employment. Second, increasing local government's administrative remit is not enough to lead to better firm and economic outcomes; local capacity is of paramount importance.

Copyright of Revista de Estudios Cooperativos is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article studies how credit decisions made by banks affect environmental pollution and the sustainable growth path. Our model suggests that with credit discrimination, the economy may experience a high output and heavy pollution steady state, but there will be welfare losses. Based on the model, we perform an empirical study using panel data from 30 provinces in China. The study results show that credit preference toward highly polluting sectors has an adverse impact on the environment. Arguably, encouraging sustainable banking may help developing countries like China to address environmental challenges. [ABSTRACT FROM AUTHOR]

• Bank credit corruption has a negative influence on the carbon emission reduction innovation. • The impact of bank credit corruption varies across different regions and industries. • The level of market concentration affects the bank credit corruption effects. • Bank credit corruption alters the corporate asset situation. The study investigates the impact of bank lending corruption on enterprises' carbon emission reduction innovation behavior by analyzing data from the 2011–2020 China Enterprise Investment Environment Survey. The empirical findings highlight the significant influence of bank lending corruption on company carbon emission reduction innovation potential. Furthermore, the article focuses on the mechanism by which bank credit corruption affects firms' carbon emission reduction innovation ability, and discovers that bank credit corruption has a considerable impact on firms' assets, undermining firms' carbon emission reduction innovation and traditional energy companies and businesses in highly marketized areas are more negatively impacted by bank loan misconduct. [ABSTRACT FROM AUTHOR]

Copyright of Balkan & Near Eastern Journal of Social Sciences (BNEJSS) is the property of Balkan & Near Eastern Journal of Social Sciences (BNEJSS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Collaboration among researchers plays an important role in scientific discoveries, especially in multidisciplinary research. How to allocate credit reasonably to coauthors of a paper is a long-standing problem in the science of sciences. The collective credit allocation method (CCA method) proposed by Shen, H. W. and Barabási, A. L. provides a novel view to solve this problem, which measures the coauthors' contribution to a paper based on the citation process by the scientific community. Nevertheless, the existing collective allocation method assigns equal weights to citing papers, which is sensitive to the malicious manipulation. In this paper, we propose a nonlinear collective credit allocation method (NCCA method) that assigns different strength to citing papers according to papers' scientific impact when measuring papers' similarity. Compared to the CCA method, we find that the NCCA method assigns more credits to Nobel laureates in the Nobel-winning papers. Moreover, the NCCA method is robust against random perturbations and the malicious manipulation in both Nobel-prize papers and ordinary papers. Furthermore, the collective credit allocation method can also modify h index. [ABSTRACT FROM AUTHOR]

Abstract Credit allocation of each author of a multiauthor paper has been a long standing concern. Regarding to the fact that the credit of each citing paper is not equal and the total credit of paper fades with time, in this paper, we introduce the PageRank algorithm and time parameter, and present an improved dynamic credit allocation method, namely IDCA method. By investigating the effect of the damping factor d of PageRank algorithm and the time parameter γ on the accuracy α of the IDCA method, finally, the two parameter (d , γ) are set (0.85,-3). Then, we validate the method by distinguishing the laureates of the Nobel Prize in Physics from the authors of prize-winning papers in American Physical Society(APS) dataset. Result shows that the IDCA method outperforms the state-of-the-art methods, and the accuracy of identifying the Nobel Prize laureates in Physics is 80.77% for 26 multiauthor prize-winning papers in APS dataset. Furthermore, we test on the real dataset with noise data generated from randomly adding and rewiring edges, and results indicate that the IDCA method still has higher accuracy compared with the state-of-the-art methods. Finally, by studying the temporal evolution of credit among coauthors in the Nobel-winning paper, we find that the effect of the Nobel Prize on credit share is remarkable. This method is not just valid for physics, also valid for any other branch of sciences. Highlights • The credit of multi-authors for each paper could be allocated according to the citing papers. • The PageRank algorithm is introduced to measure the importance of citing paper. • The IDCA method outperforms the state-of-the-art methods for identifying the Nobel Prize authors in Physics. [ABSTRACT FROM AUTHOR]

Since the reform of bank industry, commercial bank has played an critical role in industrial structure transformation and upgrading. From a theoretical point of view, we prove that big commercial banks with cost and size advantage should use their market influence to help companies increase their willingness to invest. By doing this, optimum of the whole economy will be achieved. Empirical tests suggest that commercial banks still have several defects when boosting the efficiency of industry growth, such as the lack of support for private enterprises, no promotion to industry growth and increasing the monopoly, etc. Listed companies of strategic emerging industries still lack credit loans support from banks, especially long-term ones. We then come to conclusion that if commercial banks want to optimize industrial structures, they should better distinguish the ability to allocate credit of different kinds of banks, ensuring the clear-cut of responsibility. [ABSTRACT FROM AUTHOR]

Bank credit plays an important role in economic development. Growth in bank credit can influence the demand for goods and services and is a powerful tool to boost the economy, especially when there is a slowdown. On the other hand, it is important to note that what part of bank credit is extended to each sector over a period of time, so that it will help in understanding how various sectors are expanding and further it helps in analyzing the quality and dimension of growth. It is also a need to analyze whether the bank credit is being extended to the sectors that are part of strategic policy initiatives. This article aims at discussing the Guidelines of the Central Bank of India (RBI) and the credit allocation by scheduled commercial banks of India to various sectors of the economy. [ABSTRACT FROM AUTHOR]

This paper exploits the geopolitical conflict in Eastern Ukraine as a negative shock to banking sector and examines the shock transmission. We find that banks with more loans in the conflict areas during the pre-conflict period face a higher level of bad loans in other markets after the shock. This effect is stronger in the regional markets which are closer to the conflict zone. We also find evidence for the "flight to headquarters" effect in post-conflict lending. Specifically, while more affected banks tend to cut their credit supply, the larger contraction is observed in regional markets located farther from headquarters. [ABSTRACT FROM AUTHOR]

Banking prudence and efficiency to manage their risks in different business cycle and environment would help to alleviate crises and losses. Hence, the effective assessment of credit risk is an essential component of a comprehensive technique to credit risk assessment and critical to the long-run of not only banking institutions but also the economy as a whole. Therefore, it has received a great interest from scholars across finance and economics to investigate such assessments by banks in different countries using diverse theoretical underpinnings and methodologies. Hence, this paper is developed to review analytical conceptualisations of credit risks assessments that have been developed in the academic literature. By means of a systematic review, it provides a comprehensive analysis that encompasses approaches used in research papers. There has been no prior review on analytical conceptualisations in this area. Moreover, this review is done in a systematic manner, i.e. categorising journal articles into different categories such as purposes, perspectives and methodologies through a transparent and thorough process. Thus, it will be able to provide an objective review. Finally, the paper will outline the evolution of methodologies and theoretical underpinnings in credit risk management research and a landscape for possible future research directions. [ABSTRACT FROM AUTHOR]

This study empirically investigates the impact of SARFAESI Act on debt financing by foreign banks in India. Two-way error component model (fixed effect panel) was used for this within-country assessment. Taking advantage of a policy event (Securitization and Reconstruction of Financial Asset and Enforcement of Security Interests in India (SARFAESI), Act, 2002, which improved the creditors' rights (banks) in India; we empirically examined its effect on firms in India. Specifically, we analyse if the entry of a foreign bank in a district, post SARFAESI has improved credit access for the firms. SARFAESI gives the banks a right to liquidate collateral in case of a default, therefore it should encourage lending. The impact was expected to be more in the districts where the foreign bank has entered for the first time compared to other locations where a foreign bank already existed. Theoretical literature suggests that enforcement of the law should encourage more lending. Also, prior studies on credit allocation argue that use of collateral reduces credit rationing. Hence, combining these two strands of literature we can provide empirical evidence of the impact of stronger creditor's rights on reducing information asymmetry. Amount of bank borrowings pre and post event; after controlling for firm-level factors, was the model used for the analysis. The estimates indicate that High tangible firms received a larger share of bank loans, but that on average, younger firms (< 5 years) were less likely to get loans post-event. [ABSTRACT FROM AUTHOR]

The role of the financial system, especially the credit market, in productivity enhancement has interested many researchers. However, how credit allocation affects firms’ productivity in emerging economies remains unanswered. Using data from the Annual Survey of Industrial Firms (ASIF) during 1999-2007, this article examines whether credit allocation impacts Chinese firms’ productivity under financial imperfection. Our results show that the size of credit market has no influence on Chinese firms’ total factor productivity (TFP), while allocating more credit to non-SOEs significantly promotes firm TFP. Our further analysis shows that firms which are less subsidized, smaller, more external financially dependent, and more labor intensive are affected more by credit allocation. As China is the largest emerging economy, our analysis also sheds light on the development of firms in emerging economies. [ABSTRACT FROM AUTHOR]

Scientific collaboration plays an important role in the knowledge production and scientific development. Researchers have investigated numerous aspects of scientific collaboration by constructing scientific collaboration networks. And we can perform node centrality analysis on the scientific collaboration networks to identify important scholars. In these collaboration networks, two scientists are linked if they have coauthored at least one paper and the way of constructing these networks is based on the assumption that each author’s contribution to an article is the same. However, the authors’ contributions to an article are unequal in reality and we should pay attention to the impact of this unequal credit allocation on the understanding of scientific collaboration. In this paper, we regard the first author as the most important contributor to an article and build a directed scientific collaboration network. Then we identify important scholars by analyzing this directed network. For one thing, we investigate the difference between the undirected and directed scientific collaboration network in network properties and centrality analysis. For another, we apply different centrality indices: betweenness, PageRank, SIR and HITS to the directed scientific collaboration network. As a result, we find that each indicator has a different performance and the PageRank algorithm and SIR show highly positive correlation with in-degree. The HITS algorithm also shows better property which can hep us distinguish potential young scholars and identify important collaborators. [ABSTRACT FROM AUTHOR]