Based on actual data of state-owned commercial banks in China, combining with the corporation financial data, and applying Logit regression model, we empirically analyzed corporate default probability. The result shows that Logit model is an ideal tool of forecasting corporate default probability, and that the data and techniques are of practical significance to credit rating and risk management of commercial banks.

Till now, comprehensive and quantitatively meaningful analyses of stock market participation outcomes of retail investors have been limited by data sources in developing countries. This article devised a special questionnaire related to stock investment to measure the financial literacy (FL) and stock investment return (SIR) for the subjects with stockownership in China and to theoretically and empirically study the effects of objective FL, self-assessed FL, and their composite FL on SIR. The results of the comparative analysis showed that self-assessed FL has a greater effect on SIR than objective FL, and the effect is mediated by risk preference. In addition, we found that competent and overconfident respondents have higher SIR, while under confident respondents cannot gain from the stock market. We also found that risk preference has a positive mediating effect in the relationship between competence and overconfidence and SIR, and a negative mediating effect in the relationship between under confidence and SIR. We thus concluded that confident investors can gain more stockholding returns via taking more risks regardless of the level of their actual financial knowledge. Our findings would be a meaningful complement to the studies of stock market participation.

IntroductionUsing survey data to calculate composite financial literacy (CFL), existed studies do not consider the geographical difference of the means of objectively-measured financial literacy and subjectively-perceived financial literacy, i.e., comparative benchmark.MethodsTaking the survey data of National Financial Capability Study (NFCS) for example, we explain why it is more reasonable to use the within-state average rather than the national average of financial literacy as the comparative benchmark to measure CFL. Then we use NFCS 2009, 2012, 2015 and 2018 dataset to comparatively analyze the difference between CFL measured with the two benchmarks.ResultsThe results of statistical analysis show that there is a great difference among the four groups of CFL measured with the two benchmarks, and 10.7% of respondents are categorized as a particular group of CFL incorrectly for all datasets. Additionally, the findings of spatial distribution analysis unveils that 36, 19, 15, and 6 states have respondents miscategorized in the four groups of CFL for 2009, 2012, 2015, and 2018 respectively, in which the highest proportion of the population miscategorized in a state is up to 49.91%. Finally, we find that several groups of CFL measured with the two benchmarks have significantly different effects on stock market participation behavior.DiscussionUsing the national average as a benchmark to determine all the respondents’ relative financial literacy levels for different states is not meaningful, and will lose the practical appeal to tackle the regional inequalities of financial literacy among the households. Therefore, we suggest that the within-state average of financial literacy, not the national average, should be taken as the comparative benchmark for identifying the more precise groups of CFL in survey.

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