An estimation of underground economy in Afghanistan using mathematical fuzzy model based on mean and standard deviation.

Abstract

The underground economy (UE) briefly comprises services, activities, and transactions, which could be legal or illegal. In this paper the size of UE is estimated through mathematical fuzzy model based on fuzzy set, fuzzy logic and constructed a yearly time-series for UE over the period 2001 to 2020 in Afghanistan. Two input variables are used; unemployment rate (UR) and the government regulations (REG). Fuzzification, fuzzy inference and defuzzification; the three steps that are considered for estimating UE in the country, based on mean and standard deviation (SD) for each variable individually. The result indicates four cycles for time series and shows that people were more involved in UE activities over the first and third cycles and less involved over the second and fourth cycles.