Sovereign Default Forecasting in the Era of the COVID-19 Crisis

The COVID-19 crisis has revealed the economic vulnerability of various countries and, thus, has instigated the systematic exploration and forecasting of sovereign default risks. Multivariate statistical and stochastic process-based sovereign default risk forecasting has a 50-year developmental history. This article describes a continuous, non-homogeneous Markov chain method as the basis for a COVID-19-related sovereign default risk forecast model. It demonstrates the estimation of sovereign probabilities of default (PDs) over a five-year horizon period with the developed model reflecting the impact of the COVID-19 crisis. The COVID-19-adopted Markov model estimates PDs for most countries, including those that are advanced with AAA and AA ratings, to suggest that no sovereign nation’s economy is secure from the financial impact of the COVID-19 pandemic. The dynamics of the estimated PDs are indicative of contemporary evidence as experienced in the recent financial crisis. The empirical results of this article have policy implications for foreign investors, sovereign lenders, export finance institutions, foreign trade experts, risk management professionals, and policymakers in the field of finance. The developed model can be used to timely recognize potential problems with sovereign entities in the current COVID-19 crisis and to take appropriate mitigating actions.

The Impact of Banking Competition on Firm Credit Risk and Leverage

A firm’s default risk is closely related to its macrofinancial stability. As financial reform deepens, banking competition may ease firms’ credit constraints, encouraging them to increase their leverage and default risks. This study uses contingent claims analysis to examine firms’ asset–liability ratio and default distance. We find that companies have low leverage and low overall default risks. Moreover, a pro-cyclical effect exists between leverage and economic growth. As banking competition becomes more intense, the default risk decreases, but firms’ leverage ratio rises significantly. The impact is more prominent for highly leveraged firms. Our findings also indicate that utilizing the contingent claims analysis method to measure firms’ leverage and default risks provides more accurate results. Moreover, we provide empirical evidence of the impact of banking competition on firms’ leverage and credit risks. The results suggest that enhancing financial competition has a positive effect on easing credit constraints and reducing default risks.

SMEs Intervention Programmes in Nigeria: Evaluating Challenges Facing Implementation

To ensure price and economic stability, the central bank of Nigeria has adopted several unconventional monetary policy measure such as MSMEs credit intervention with the aim of boosting credit availability in specific sector of the economy. The intuition is that rise in productive activities/investment will indirectly promotes price stability the core mandate of the bank. Therefore, this study investigated the challenges facing implementation of real sector (MSMEs) intervention programmes of the CBN since year 2000 to 2020. The study employed mixed method using descriptive survey approach to sample 62 intervention programme implementers and 400 Micro, Small and Medium Sized Enterprises (MSMEs). The findings reveal among others that high loan default risks, politicization of programmes, and inadequate infrastructural development are the leading challenges facing programme implementers in Nigeria. Applicants' non-eligibility in programmes applied for, poor business plan or inadequate knowledge in proposed business topped the reasons for failures among applicant MSMEs. Consequently, a need for more public-private partnerships in programme design, monitoring, and evaluation to forestall political interference is advised.

Pengaruh tata kelola perusahaan, kualitas audit, dan konservatisme terhadap persyaratan agunan pinjaman

Debtors and creditors have equal access to information about default risks in competitive credit markets. Loan collateral is less important in credit decision-making in these circumstances. However, in emerging credit markets such as Indonesia, where debtors and creditors do not have equal information about a firm's prospects, the use of collateral to mitigate default risk has become common practice. Despite the strong theoretical framework for the use of collateral to secure creditors from credit risk, some Indonesian firms are exempt from providing collateral for bank debts. This study looks at how the independence of the Board of Commissioners, governance committees, audit quality, and conservatism affect the likelihood of using debt collateral. Around 785 firms listed on the Indonesia Stock Exchange were collected using Slovin's formula, during the sample period of 2017-2020. According to logistic regression analysis, firms with a more independent Board of Commissioners, a separate governance committee, Big 4 auditors, and conservative accounting policies are less likely to provide loan collateral

Herd Behavior of Investors and Default Risks of P2P Online Lending

We examine the impact of investors’ herding on the default risk of P2P online loans. More specifically, we first decompose the number of investors in each loan into two components: the component caused by public information and the component reflecting factors other than public information. Then we investigate the effect of each component on the default risk of loans, using an ordered probit analysis. We use the data on 3,720 loans that were traded through 8percent, a Korean price-posted P2P platform from February 2015 to December 2017. We find the results as follows: First, the number of investors is determined by information that are provided by the platform and macro-economic variables (hereafter public information). Second, the number of investors explained by public information decreases the default risk of the loans. However, the number of investors reflecting factors other than public information increases the default risk of the loans. These results are interpreted as an evidence supporting ‘herding’ hypothesis: Investors follow intentionally other investors’ investment decision. These results suggest that the quantity increasement and quality improvement of public information provided by a P2P platform can improve the efficiency of P2P lending market reducing herding caused by factors other than public information.

Default Risk on Islamic Banking in Indonesia

The problem of default by debtors becomes a primary concern for Islamic banking recently. This study analyzes the effect of economic pressure on the risk of default on Islamic banks, both in the short and long term, the risk response of default, and also other variables' contribution in explaining the diversity of risk of default of Islamic banks. This study used monthly data from 2007 to 2020 by using a vector error correction model. The results show that inflation and exchange rates affect the risk of default in the short term, while inflation, exchange rates, and interest rates affect the risk of default in the long run. Non-performing financing quickly stabilized when responding to the interest rates. The Islamic stock index has the most significant contribution in explaining the diversity of default risks. Islamic banks must be aware of the monetary fluctuation and also careful in analyzing the demand for financing by looking at the future economic prospects.

How Does the Urgency of Borrowing in Text Messages Affect Loan Defaults? Evidence from P2P Loans in China

In P2P loans with information asymmetry, the text information described by the borrower plays an important role in alleviating the information asymmetry between borrowers and lenders. To explore the borrowing described in text information and its relationship with default behavior, this article selects credits from April 2014 to October 2016 as the repayment period and studies default data. This is performed based on the length of the excavated text, purpose of the loan, repayment ability, willingness to reimburse, five text variables, and degree of loan urgency. The empirical results show that text length has a significant negative correlation with the default probability of borrowers. Different loan purposes have different default risks. Interestingly, the more urgent a loan is, the more likely the borrower is to default. However, repayment ability information and repayment willingness information have no significant effect on default behavior. In addition, the Nagelkerke R2 improved by nearly 3% in the logistic regression model with the addition of text variables. In short, fully excavating loan description information is helpful in reducing the risk of loan default.

Mechanisms for Financing Incremental Housing in Nigeria: Case study of Ibadan, Nigeria

Access to housing finance by all income groups is essential for the provision of adequate shelter for all. The study examined the mechanisms for financing incremental housing for the low and moderate income households in Ibadan, Nigeria and their effectiveness with a view to providing information that could inform policy towards effective incremental housing delivery in the study area. Primary data was collected with the use of questionnaire from 742 respondents from 4 randomly selected suburban local government areas of Ibadan, Nigeria. Two sets of questionnaires were used to obtain the data needed for the study. The results of the quantitative data were presented in both descriptive and inferential statistics while qualitative data were contextually reported. The results for housing development of the low and moderate income groups occurred in phases with the incremental process taking as much as 8-12 years for construction while improvement of the existing structure took about five and a half years. Chi-square analysis with values being significant at p<0.05indicated the financing mechanisms for incremental housing construction at the level of foundation (0.007), main structure (0.0005), roofing (0.002) and internal fixtures (0.000) vary significantly with the exception of land purchase and drainage cum sewage stages. Funding for the incremental housing process can be improved if the socio-economic and traditional attributes of the people in the area are promoted. This needs to be encouraged as a way of directing the financing mechanisms devoid of interest rate and default risks to incremental housing.

Resolution of the Min-Max Optimization Problem Applied in the Agricultural Sector with the Estimation of Yields by Nonparametric Statistical Approaches

The ultimate objective of the problem under study is to apply the min-max tool, thus making it possible to optimize the default risks linked to several areas: the agricultural sector, for example, which requires the optimization of the default risk using the following elements: silage crops, annual consumption requirements, and crops produced for a given year. To minimize the default risk in the future, we start, in the first step, by forecasting the total budget of agriculture investment for the next 20 years, then distribute this budget efficiently between the irrigation and construction of silos. To do this, Bangladesh was chosen as an empirical case study given the availability of its data on the FAO website; it is considered a large agricultural country in South Asia. In this article, we give a detailed and original in-depth study of the agricultural planning model through a calculating algorithm suggested to be coded on the R software thereafter. Our approach is based on an original statistical modeling using nonparametric statistics and considering an example of a simulation involving agricultural data from the country of Bangladesh. We also consider a new pollution model, which leads to a vector optimization problem. Graphs illustrate our quantitative analysis.