Abstract
A small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is of importance to finance small enterprises’ activities. Till now, there has not been a multicriteria credit risk model based on the rank sum test and entropy weighting method. In this paper, we try to fill this gap by offering three innovative contributions. First, the rank sum test shows significant differences in the average ranks associated with index data for the default and entire sample, ensuring that an index makes an effective differentiation between the default and non-default sample. Second, the rating equation’s capacity is tested to identify the potential defaults by verifying a clear difference between the average ranks of samples with default ratings (i.e., not index values) and the entire sample. Third, in our nonparametric test, the rank sum test is used with rank correlation analysis made to screen for indices, thereby avoiding the assumption of normality associated with more common credit rating methods.
Highlights
Small enterprises play an integral role in the Chinese economy
In this paper, we utilize the rank sum test and rank correlation analysis using a nonparametric test based on the relative rank of the results to establish a credit rating system that clearly identifies the likelihood of defaults by small enterprises
Credit rating models based on statistical approaches have often relied on parametric statistical tests that assume a normal distribution, which can only be satisfied with a large sample of enterprises that are very difficult for researchers to obtain
Summary
Small enterprises play an integral role in the Chinese economy. do they account for 60% of China’s Gross Domestic Product (GDP), 50% of its national tax revenue, 65% of new patents in China, and over 80% of the country’s new product development, but they serve as a major driver of new employment [1]. In this paper, we utilize the rank sum test and rank correlation analysis using a nonparametric test based on the relative rank of the results to establish a credit rating system that clearly identifies the likelihood of defaults by small enterprises. Credit rating models based on statistical approaches have often relied on parametric statistical tests that assume a normal distribution, which can only be satisfied with a large sample of enterprises that are very difficult for researchers to obtain. This study utilizes the rank sum test and rank correlation analysis by using a nonparametric test based on the relative rank of the results to establish a credit rating system for clearly identifying the likelihood of defaults by small enterprises, thereby avoiding any restriction associated with the need for normal data. We present the establishment of a credit rating model; Section 3 introduces the data and empirical analysis; and Section 4 describes the results
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