Analisis Ketimpangan Antar Daerah dalam Mendorong Pembangunan Ekonomi di Provinsi Papua Pegunungan - Elok Dining Lestari; Elsyan R. Marlissa (Universitas Cenderawasih, 2025)
This study aims to analyze the level of interregional inequality and the influence of population and per capita income on economic development inequality in Papua Mountains Province during the 2018-2022 period. The research method used is associative research with quantitative secondary data obtained from the Central Bureau of Statistics of Yahukimo Regency. Data analysis was conducted using three descriptive tools, namely the Williamson Index to measure the level of inequality, Klassen Typology to classify regions based on economic growth and per capita income, and Location Quotient to identify basic and non-basic sectors. Furthermore, to test the influence of independent variables on inequality, this study applied panel data regression with the help of Eviews 9 software, through a series of model specification tests, classical assumption tests, as well as partial and simultaneous hypothesis tests. The results show that interregional inequality in Papua Mountains Province is classified as high and continues to increase significantly from year to year, with all Williamson Index values falling into the high category. Based on the Klassen Typology, no regency falls into the fast-growing and advanced region category, while Yahukimo and Tolikara Regencies fall into the lagging region category. The Location Quotient analysis results indicate that the agriculture, construction, and various public service sectors are basic or leading sectors. The hypothesis test results prove that population and per capita income, both partially and simultaneously, have a positive and significant effect on economic development inequality. Thus, inequality in Papua Mountains Province is a serious problem triggered by the high population and unequal per capita income, which requires comprehensive and targeted policy interventions. Keywords: Regional Inequality, Economic Development, Population, Per Capita Income