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This book's prime audience is government policy-makers. It provides a policy framework for governments to increase micro, small and medium enterprises' access to financial services?one which is based on empirical evidence from around the world. Financial sector policies in many developing countries often work against the ability of commercial financial institutions to serve this market segment, albeit, often unintentionally. The framework guides governments on how to best focus scarce resources on three things: ? developing an inclusive financial sector policy; ? building healthy financial institutions; and ? investing in information infrastructure such as credit bureaus and accounting standards. The book provides examples and case studies of how such a strategy has helped to build more inclusive financial institutions and systems in many countries.

Purpose This study aims to investigate how credit rating agencies and banks, important credit market participants, incorporate corporate social responsibility (CSR)-related information in their assessment of firm’s creditworthiness. Design/methodology/approach The authors collect stand-alone CSR reports published by Fortune 500 companies from 2002 to 2014 and use file size as a readability measure to investigate the impact of stand-alone CSR reports’ readability on firms’ credit ratings and cost of borrowing. Findings The authors find that firms with higher CSR report readability enjoy higher credit ratings and lower costs of bank loans, suggesting that rating agencies and banks perceive lower default risk for firms with more readable CSR reports. Further analysis indicates that the positive association between CSR report readability and credit ratings is more pronounced for firms with high CSR performance. Conversely, the negative association between CSR report readability and bank loan spreads is more pronounced for firms with low CSR performance and credit quality, suggesting complementary roles of rating agencies and banks in their use of CSR reports. Originality/value Overall, the results highlight the importance of improving the textual characteristics of CSR reports, especially readability, in reducing information risk in the credit market.

PurposeThe purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan.Design/methodology/approachThe econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach.FindingsThis study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years.Research limitations/implicationsIn the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well.Originality/valueThis is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

We show that transactions accounts, by providing ongoing data on borrowers' activities, help financial intermediaries monitor borrowers. This information is most readily available to commercial banks, which offer these accounts and lending together. We find that (1) monthly changes in accounts receivable are reflected in transactions accounts; (2) borrowings in excess of collateral predict credit downgrades and loan write-downs; and (3) the lender intensifies monitoring in response. This is evidence on a key issue in financial intermediation-there is an advantage to providing deposit-taking and lending jointly. But this advantage may have fallen as the cost of communication has declined.

There are many methods for explaining why a machine learning model produces a given output in response to a given input. The relative merits of these methods are often debated using theoretical arguments and illustrative examples. This paper provides a large-scale empirical test of four widely used explanation methods by comparing how well their algorithmically generated denial reasons align with lender-provided denial reasons using a dataset of home mortgage applications. On a held-out sample of 10,000 denied applications, Shapley additive explanations (SHAP) correspond most closely with lender-provided reasons. SHAP is also the most computationally efficient. As a second contribution, this paper presents a method for computing integrated gradient explanations that can be used for non-differentiable models such as XGBoost.

Smoked fish is a kind of fisheries product that is processed using smoking technology as a food preservation method. It also has a high economic value due to its high potential demand and cheap production costs. However, smoked fish vendors, particularly in the Kei Islands, are very reliant on the supply of raw materials from local fishermen. So, the seller of smoked fish in the area needs to have good resilience in terms of navigating around the uncertainty of supply of fish from local fishermen. The goal of this study was to find out how different factors affect the performance of local fishermen in the Kei Islands. This research surveyed a total of 231 respondents, all of whom were fishermen in the Kei Islands, using a purposive sample approach. Path analysis using Smart PLS was the analytical technique employed. The findings indicated that cooperation among fishing-related parties, such as between fishermen, between fishermen and sellers, between fishermen and local suppliers, and financing access for fishermen to loans and other forms of finance had a significant effect on the performance of capture fisheries. This is in addition to the fact that selling price and marketing factors must be considered in order to maintain the catch's competitiveness. The competitiveness would have an effect on the performance of smoked fish sellers in this region.

This paper establishes and evaluates the efficiency of three restrictive measures adopted by the government to contain housing prices: restricted bank loan (xiandai), restricted sale price (xianjia) and restricted housing purchase (xiangou). Based on the data envelopment analysis noncontrollable variable model, the efficiency of the three measures to mediating housing prices among 35 major cities are examined. It is found that xiangou is more efficient than xianjia and xiandai to achieve stabilising goals in the housing market. The findings of this research could provide the government with a benchmark to estimate the possible outcome of different restrictive measures containing property prices, in the context of the global overflow of liquidity over the past decade.

The country's macroeconomic conditions, whether directly and indirectly will influence the development of the financial and banking sector. This study aims to determine the effect of macroeconomic and internal company variables consisting of BOPO, ROA, money supply, and the unemployment rate on non-performing loans (NPL) in Indonesian banking, especially Regional Development Banks (BPD). The sampling technique used is purposive sampling technique. There are 20 Regional Development Banks (BPD) that met the requirements determined by the observation period from 2008-2021. The data processing method used is panel data regression. Model selection uses the Chow test, Hausman test and Langgrange Multiplier test (LM Test). Based on this, the appropriate model is the Fixed Effect Model (FEM). Testing the classical assumptions of FEM shows that there is a heteroscedasticity problem, then it is recovered using the Feasible Generalized Least Square (FGLS). The results of the analysis show that the variables BOPO, ROA, money supply, and unemployment rates both simultaneously and individually have a significant positive effect on the NPL of Regional Development Banks.

Banks and enterprises constitute a multilayered, multiattribute, multicriteria credit-related super network due to financial transaction behaviors, such as credit, wealth management, savings, and derivatives. Such a network has become an important channel for credit risk cross-contagion. This study constructs a two-layer network model of credit risk contagion between the bank and corporate counterparties from the perspective that banks do not withdraw loans from enterprises by considering the influence of corporate credit defaults on their counterparties under the credit linkage. This study analyzes the mechanism of influencing the evolution of bank-enterprise counterparty credit risk contagion in the two-tier network through theoretical analysis, including the following: the enterprises’ coping ability, risk preference, influence, level of interenterprise credit risk contagion and its network heterogeneity in the interenterprise credit association network, the risk prevention and control ability, business correlation degree, interbank credit risk contagion and its network heterogeneity in the interbank credit association network, the level of credit risk contagion between bank-enterprise counterparty credit association networks, and other factors in the case that banks do not withdraw loans from enterprises. In addition, this study performs a calculation experiment to analyze the characteristics of the evolution of counterparty credit risk contagion of bank and corporate counterparties under the double-layer network. The following four major conclusions can be drawn from the results. First, in the interenterprise credit-related network, the threshold of credit risk contagion rate is positively correlated with the marginal increase in risk perception and risk leveling ability of the enterprise. By contrast, such threshold is negatively correlated with the marginal decrease in the initial economic impact, leverage level, and influence of the enterprise. Moreover, the scale of corporate counterparty credit risk contagion is negatively correlated with the enterprise’s risk perception level and risk spillover ability but positively correlated with the enterprise’s initial economic shock level, the enterprise’s leverage level, and influence. Second, in the interbank credit association network, the threshold of the rate of credit risk contagion is negatively correlated with the marginal decrease in the degree of interbank business association but positively correlated with the marginal increase in the bank’s risk resistance ability and risk information processing ability. Furthermore, the scale of credit risk contagion of bank counterparties is positively correlated with the degree of interbank business association but negatively correlated with the bank’s ability to resist risks and process risk information. Third, if the heterogeneity of the credit-related network of bank-enterprise counterparties is high, then the rate threshold of credit risk contagion is high and the scale of credit risk diffusion is low. Moreover, the scale of credit risk contagion of bank counterparties is positively correlated with the marginal decrease in the degree of corporate and bank counterparties. Finally, the scale of bank counterparty credit risk contagion is a monotonically increasing convex function of the credit risk contagion rate in the enterprise credit association network and among the bank-enterprise networks.

PurposeIn the midst of the Greek economic and financial crisis, food and beverage firms constitute one of the most dynamic parts of the Greek economy proved resilient in conditions of economic turbulence. The purpose of this paper is to assess the competitiveness of the Greek food and beverage firms within the context of turbulent economic conditions and draw the relevant entailed agricultural policy viewpoints.Design/methodology/approachThe analysis is based on competitiveness measures such as profitability and market share utilizing a sample of 550 firms which published their annual balance sheets the 2008–2012 period. The analysis takes place with the use of a simultaneous equations tobit model.FindingsThe main results show that market share, profitability and capital intensity affect positively both on market share and profitability, while operating costs have a negative and statistically significant effect on profitability. The rate of growth affects positively and statistically significant on profitability while the index of loans does not affect on market share. As the results indicate, food and beverages industry has proven resilient in conditions of economic turbulence without direct policy measures or subsidies.Originality/valueAmong other factors, the evolution of agricultural policy is affecting decisively the competitiveness of agro-food sector (Chaddad and Jank, 2006; Banse et al., 1999). Nevertheless, food competitiveness is significantly shaped and influenced within the broad economic climate of a country, region or the whole world. Thus, the present study tries to assess the competitiveness of Greek food and beverages sector in conditions of macroeconomic turbulence and draw the relevant entailed agricultural policy viewpoints.