Generalized Poisson Regression Model on factors influencing the number of poor people in South Central Timor Regency 2024

Abstract

Poverty remains a major issue in Timor Tengah Selatan Regency (TTS), which has a relatively high poverty rate in East Nusa Tenggara Province. This condition is not only caused by low household income but also reflects limitations in meeting basic needs. The number of poor people is categorized as count data, which in statistical analysis often exhibits overdispersion, making the standard Poisson regression model less appropriate. Therefore, this study applies the Generalized Poisson Regression (GPR) approach to examine the effects of various factors on the number of poor people, using secondary data from 2024 covering 32 sub-districts in Timor Tengah Selatan Regency. The independent variables in this study include the open unemployment rate, total population, labor force, population density, and population growth rate. The results show that all independent variables have a significant effect on the number of poor people. Specifically, the open unemployment rate has a coefficient of -0.07289, total population is 1.11417, labor force is 1.44963, and population density is 0.00094, while population growth rate has a coefficient of -0.03301, indicating that an increase in this variable can reduce the number of poor people by approximately 3.25 percent.