Meta-Analysis of the Use of Logit-Probit Models in the Impact of Financial Indicators on Credit Rating

The diversity of tools and measurement methods has created new opportunities in studies, often leading to different results and causing confusion in understanding the overall outcomes. Meta-analysis is a set of statistical methods for integrating the results of various studies and identifying moderating factors in the relationships between financial indicators and credit ratings. In this research, we will use the methodology of meta-analysis (meta-analysis), which is considered a quantitative statistical approach. To implement the meta-analysis method, all studies conducted in the field of research using keywords such as financial ratios, credit rating models; Logit-Probit models, and factors affecting credit rating will be identified and collected from domestic and international journal websites (in the time period from 2008 to 2023) as the statistical population of the research. Finally, out of the total studies collected, 22 studies were analyzed systematically with certain limitations applied. The results of the examination of these studies indicate that most of these studies are heterogeneous. Moreover, the Logit and Probit models accurately and acceptably predict the impact of financial ratios on credit rating. Additionally, it was determined that there is a significant relationship between financial indicators and credit rating.