Poverty is a worldwide issue since its effects are widespread. In Indonesia, most pockets of poverty are found in rural or underdeveloped areas. This research is essential as a reference for addressing the issue of poverty in Indonesia's undeveloped regions, as few studies have analyzed the causes of poverty in underdeveloped regions. This study analyses the impact of economic growth, human capital, and public investment on the alleviation of poverty in Indonesia’s undeveloped regions. This study employs panel data from 62 underprivileged regions in Indonesia according to Presidential Decree No. 63 of 2020 with an observation period of 2010-2020. The analytical method used is the ECM panel model. The unit root test indicates that the research data is steady and cointegrated at the first level of differentiation. This study demonstrates that economic growth does not have a substantial influence on poverty levels in underdeveloped areas of Indonesia, although human capital and public investment do, both in the short and long term. Human capital contributes more to reducing poverty in disadvantaged areas, but state investment increases the number of poor in Indonesia's underdeveloped regions.
This is an empirical study of economic measurement of the optimal size of seven cities in West Sumatra region, Indonesia. The empirical findings are quite interesting since the calculated optimal city size does not result in a single measure as mostly previous studies found, but they vary in accordance with the economic approaches used. The optimal city size measured by using the maximum profit approach would have been larger in size compared to those measured by the minimum cost and maximum net benefit approaches. Meanwhile, the cities measured by using the maximum net benefit have larger size than those of the minimum cost. Unlike previous studies, the measurement of optimal city size in this study is performed in terms of population density rather than the total population, in order to consider the influence of land area to the optimal city size. Moreover, by using the population density, the optimal city size becomes a relative index which enables us to compare it with the related size in other regions.
The study aims to analyze the effect of inflation, exchange rate, investment, and labor force participation on the economic growth of member countries in the ASEAN region. This study uses secondary panel data, namely economic data from ten ASEAN member countries from 2000-2020. Sources of data obtained from the publications of the World Bank. The analytical method used is the panel data regression method fixed-effects model approach with a SUR cross-section weighted. This study indicates that the increase in inflation, investment, and labor force participation can encourage economic growth in the ASEAN Region. Meanwhile, the weakening of the value of the domestic currency (depreciation) has corrected the economic growth of ASEAN member countries.
Unemployment still becomes a major developmental challenge in some OIC member countries. Thus, employment determinants in those countries need to be investigated through empirical research. This study analyzes the influences of inflation, GDP, IT advancement, and innovation on unemployment in some OIC member countries. We use the purposive sampling method with criteria of countries with the past decade's average unemployment rate lower than 6%. We employ panel data from 20 countries fulfilling the requirements in 2013-2021. The panel data regression method with a fixed effect approach is used to analyze the influence of independent variables on the dependent variable. The results indicate that inflation and GDP significantly and negatively affect unemployment. On the other hand, innovation and ICT advancement have a negative but insignificant effect on the dependent variable. Regarding the results, we believe it is essential for the government as a policymaker to arrange appropriate regulations allowing industries to enhance their productivity to enlarge job opportunities and alleviate unemployment.
Pertumbuhan ekonomi adalah salah ukuran tingkat pembangunan yang dicapai sebuah daerah. Penentu pertumbuhan ekonomi adalah pembentukan modal fisik dan modal manusia. Penelitian ini menggunakaan metode analisis data panel yang terdiri lima unit cross section dengan interval waktu tahun 2010-2019. Hasil pengujian spesifikasi model memutuskan bahwa model yang terbaik adalah pendekatan Fixed Effect Model (FEM). Ditemukan bahwa human capital yang dihitung dengan rata-rata lama sekolah mampu meningkatkan pertumbuhan ekonomi secara signifikan. Variable pembentukan modal juga mampu mendorong pertumbuhan ekonomi di kepulauan nias secara signifikan, dimana setiap satu persen peningkatan belanja modal yang dilakukan oleh pemerintah daerah mampu mendorong pertumbuan ekonomi sebesar 0,39 persen. Demikian juga variabel partisipasi angkatan kerja mempengaruhi pertumbuhan ekonomi di kepulauan Nias, yaitu setiap peningkatan TPAK sebesar satu persen akan mampu mendorong pertumbuhan ekonomi sebesar 0,03 persen.
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