Pengaruh pertumbuhan ekonomi, inflasi dan tingkat pengangguran terbuka terhadap jumlah penduduk miskin di Provinsi Jambi - Arif Rahman; Purwaka Hari Prihanto; Muhammad Safri (e-Jurnal Ekonomi Sumberdaya dan Lingkungan, 2019)
Study aims to: 1) To find out the development of economic growth, inflation and the level of open unemployment in Jambi Province; 2) To analyze the influence of economic growth, inflation and the open unemployment rate on the number of poor people in Jambi Province. This research uses secondary data for the period 2001-2016. The method used in analyzing the data is by using multiple regression analysis. The results of this study indicate that: 1) The poor population in Jambi Province from 2001-2016 has decreased, where the number of poor people in Jambi Province has decreased by 0.46 percent. Economic growth in Jambi Province on the basis of constant prices from 2001-2016 experienced an average fluctuation of 6.23 percent per year. During the period of 2001-2016 the inflation rate in Jambi Province was an average of 12.25 percent. The highest number of unemployed occurred in 2005, amounting to 133,964 people and then in 2016 a decrease of 67,671 people; 2) Every increase in economic growth in Jambi Province is 1 percent, the poverty rate of the population in Jambi Province will decrease by 0.140 percent. The results of this test indicate that economic growth has a negative impact on the number of poverty in Jambi Province. Every increase in the inflation rate by 1 percent, the poverty rate will increase by 0.002 percent and every increase in the unemployment rate in Jambi Province by 1 percent, the poverty rate of the population in Jambi Province will increase by 0.052 percent. Together economic growth, inflation and unemployment have a positive and significant effect on the poverty rate of the population in Jambi Province during the period 2001-2016. Variation in ups and downs the poverty rate of the population in Jambi Province is able to explain economic growth, inflation and unemployment by 35.2 percent, while the remaining 64.8 percent is explained by other variables not included in this research model.