Optimal credit guarantee ratio for small and medium-sized enterprises’ financing: Evidence from Asia

Yoshino, Naoyuki; Taghizadeh–Hesary, Farhad

doi:10.1016/j.eap.2018.09.011

Cited by 73 publications

(52 citation statements)

References 17 publications

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“…The fee depends on the project risk rating and the borrower's credit score. Using the same guarantee fee for all borrowers would create a moral hazard [23]. Banks also need to apply to a GCGC for a green credit guarantee, which issues the relevant certificate.…”

Section: Development Of Green Credit Guarantee Schemes To Reduce the mentioning

confidence: 99%

“…In the case of default, the GCGC compensates a portion of the loan amount-the credit guarantee ratio-and subrogates the bank. An adjustment of the optimal credit guarantee ratio is necessary to avoid moral hazard [23]. This means that healthy banks that manage their nonperforming loans and have higher creditworthiness should receive a higher credit guarantee ratio from the government, while unsound banks need a lower guarantee and very risky banks do not obtain a guarantee.…”

Section: Development Of Green Credit Guarantee Schemes To Reduce the mentioning

confidence: 99%

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Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects

2020

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The lack of long-term financing, the low rate of return, the existence of various risks, and the lack of capacity of market players are major challenges for the development of green energy projects. This paper aimed to highlight the challenges of green financing and investment in renewable energy projects and to provide practical solutions for filling the green financing gap. Practical solutions include increasing the role of public financial institutions and non-banking financial institutions (pension funds and insurance companies) in long-term green investments, utilizing the spillover tax to increase the rate of return of green projects, developing green credit guarantee schemes to reduce the credit risk, establishing community-based trust funds, and addressing green investment risks via financial and policy de-risking. The paper also provides a practical example of the implementation of the proposed tools.Energies 2020, 13, 788 2 of 18 technological progress and cost reduction. Thanks to the technological progress, costs of renewable energy technologies reduced drastically. For example, solar PV module prices have reduced by around 80% since the end of 2009 and wind turbine prices have dropped by 30-40%. Although this is good news on one side, it prompts investors to pause to see how much the prices will drop on the other side.All in all, it is important to take the necessary steps for mitigating the risks of green financing to unlock the participation of financial institutions in these projects [4]. One solution is to incentivize non-banking financial institutions (NBFIs), such as pension funds or insurance companies, to engage in green energy projects. The advantages of pension funds and insurance companies over banks are that these institutions pursue asset-liability matching and their resources are long-term (10, 20, or 40 years). Insurance companies or pension funds can finance infrastructure projects, including large green energy projects such as large hydropower, as they are long-term projects (10-20 years). Therefore, it is very important to develop pension funds and insurance companies in developing countries to fill the financing gap of infrastructure projects, including energy and green energy projects [4].A good example of the role of non-banking financial institutions in unlocking green investment comes from Australia. The Powering Australian Renewables Fund (PARF) is a financing initiative that AGL Energy of Australia created and has $2-3 billion funds targeting to unlock the investments in large-scale renewable energy projects by diversifying the risks and reducing the financing costs. A partnership with the Queensland Investment Corporation (QIC) established the fund in 2016 on behalf of its clients, the Future Fund and those investing in the QIC Global Infrastructure Fund. The target is to accelerate Australia's transition to a low-carbon economy with the potential to meet 10% of the Federal Government's Renewable Energy Target (RET).One point that is important to consider is that public fina...

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Section: Development Of Green Credit Guarantee Schemes To Reduce the mentioning

confidence: 99%

Section: Development Of Green Credit Guarantee Schemes To Reduce the mentioning

confidence: 99%

Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects

2020

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“…Next, we have compared and analyzed the evolution of the main ratios. First, the guarantee ratio [44,45], which is calculated by dividing total assets by total liabilities, indicates the ability of the bank to cover all its debt obligations with its assets. Second, the liquidity ratio [46,47], which is calculated by dividing current assets by current liabilities, shows the ability of the bank to meet its short-term obligations; namely, if this ratio is greater than one, the bank will not have liquidity problems in the short-term.…”

Section: Methodsmentioning

confidence: 99%

Sustainable and conventional banking in Europe

2020

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At the end of the 20 th century a new banking model, the so-called ethical banking, emerged becoming the maximum exponent of a socially responsible investment. The financial crisis in 2008 led to a distrust of the conventional financial system and consequently investors began to look with interest this new banking, which only invests in ethical activities and products, with social and environmental criteria, total transparency and a democratic management. The aim of this article is to analyze the economic structure of ethical banking, compared to that of conventional banking, by paying attention to its liquidity, coverage and solvency. Specifically, We compare the financial statements of Triodos Bank, the main European ethical bank belonging to the Global Alliance for Banking on Values, with two of the main conventional banks of each of the five countries in Europe in which it operates. To do this, we apply a financial and economic analysis to the period from 2015 to 2018, the means difference test and analysis of variance on an array of financial ratios and, finally, probit regressions. The results reveal that ethical banking is growing more than conventional banking and it presents greater liquidity and solvency, although, in general terms, its profitability is not higher. In conclusion, both savers and investors have guarantees that their savings are invested not only in a responsible but also in a confident way in ethical banking.

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“…SMEs within the guarantee scheme are 1.17% more likely to default relative to those without guarantees, meaning the enhancement of adverse selection due to lowered liability. Likewise, Yoshino and Taghizadeh-Hesary (2019a) argued that there is a need to adjust guarantee ratios according to each SME to account for heterogeneity across SMEs. Their theoretical model and empirical analysis show that they should vary depending on three factors: (i) public policy; (ii) banks' profit-maximizing strategy; and (iii) the current state of the macroeconomy.…”

Section: Literature Reviewmentioning

confidence: 99%

A model for calculating optimal credit guarantee fee for small and medium-sized enterprises

et al. 2021

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Small and medium-sized enterprises (SMEs) have difficulties in accessing finance because of information asymmetry and a lack of collateral. A credit guarantee scheme is a suitable method to unlock lending to SMEs; however, it involves SMEs paying a fee, which needs to account for their risk. The question is how to calculate the optimal fee. The paper provides a theoretical model for calculating the optimal credit guarantee fee. In the empirical part, this study investigates whether selected macroeconomic variables and the financial health of SMEs have a statistically significant impact on the default risk ratio of SMEs, which is the main determinant of the fee. We use selected macroeconomic variables and the financial profiles of 1,363 SMEs that are customers of an Iranian bank. We use principle component analysis and two vector error correction models, and we provide a robustness test using the generalized method of moments. The empirical results support our hypothesis that the credit guarantee fee should be different for sound (lower) and unsound (higher) SMEs to avoid moral hazard but also according to the macroeconomic state (a decrease in a recession and an increase in a boom).

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Optimal credit guarantee ratio for small and medium-sized enterprises’ financing: Evidence from Asia

Cited by 73 publications

References 17 publications

Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects

Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects

Sustainable and conventional banking in Europe

A model for calculating optimal credit guarantee fee for small and medium-sized enterprises

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