A comparative study of poisson and negative binomial regression models on economic growth in Bali Province - Safitri Pratiwi, Luh Putu; I Made Pasek Pradnyana Wijaya (Universitas Islam Negeri Raden Intan Lampung, 2025)
Economic growth is the main indicator of regional development success and is measured through Gross Regional Domestic Product (GDP). This study aims to determine the best model in explaining the factors that affect economic growth in Bali Province in 2023 using Poisson regression and Negative Binomial regression. Secondary data were obtained from the Central Statistics Agency (BPS) and the Investment Coordinating Board (BKPM), with GDP response variables and predictor variables including labor force participation rate, open unemployment rate, foreign investment, population density, and literacy rate. The results of the analysis showed that the Poisson model was over dispersed, so the Negative Binomial model gave results that were more in line with the Akaike Information Criterion (AIC) value of 174.572. Economically, increasing labor force participation and foreign investment have a positive effect on GDP, while increasing unemployment and low literacy rates reduce economic growth. Thus, the Negative Binomial regression model is considered more appropriate to explain the variation in economic growth in Bali Province because it is able to handle overdispersion and provide more stable estimation results.