نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار گروه آمار، دانشکده علوم پایه، دانشگاه ولایت ایرانشهر، ایران
2 استاد گروه آمار، دانشکده علوم ریاضی، دانشگاه فردوسی مشهد، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
This study investigates the relationship between two key economic indicators: income and wealth. Despite apparent similarities in the behavior of these two variables, numerous instances highlight their differences and lack of complete correlation. The main objective of this paper is to analyze the dependency structure between individuals’ income and wealth using advanced statistical tools. To model the dependency between income and wealth, the copula function—an innovative tool in probability theory—has been employed. In this regard, various copula functions are examined, and the Clayton copula family along with the Farlie-Gumbel-Morgenstern (FGM) copula family are identified as the most suitable choices for the studied data. Additionally, the study introduces a new bivariate index based on the Total Time on Test (TTT) transform in the bivariate case, utilizing copula functions. This index is applied to real-world data on the income and wealth of Iranian households, and the results demonstrate a significant relationship between the two variables at the societal level. Therefore, it can be concluded that using this index in economic data reveals that the proposed bivariate TTT index can effectively represent the dependency structure between income and wealth. Furthermore, the use of Clayton and FGM copulas also shows a good fit with the empirical data.
کلیدواژهها [English]
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