mirМИР (Модернизация. Инновации. Развитие)MIR (Modernization. Innovation. Research)2079-46652411-796XSchool of Public Administration10.18184/2079-4665.2021.12.1.83-90mir-1123Research ArticleРАЗВИТИЕRESEARCHФакторы неравенства доходов в провинции Бангка БелитунгThe Determinants of Income Inequality in Bangka Belitung ProvinceРедитаН.NeshaR.

Неша Редита - аспирант, Экономический факультет.

30128, Южная Суматра, Палембанг, Илир Барат 1

Nesha Redita, Postgraduate Student, Faculty of Economy.

Barat 1, Palembang, South Sumatera, 30128

nesharedita@gmail.comРобианиБ.BernadetteR.

Бернадетт Робиани - профессор экономики, преподаватель, Экономический факультет/

30128, Южная Суматра, Палембанг, Илир Барат 1

Bernadette Robiani, Professor (Economics), Lecturer at the Faculty of Economy.

Ilir Barat 1, Palembang, South Sumatera, 30128

robiani64@yahoo.comЮлианитаА.YulianitaA.

Юлианита Анна - доктор экономики, преподаватель, Экономический факультет/

30128, Южная Суматра, Палембанг, Илир Барат 1

Yulianita Anna, Doctor (Economics), Lecturer at the Faculty of Economy.

Ilir Barat 1, Palembang, South Sumatera, 30128

annayulia@unsri.ac.idУниверситет Шривиджая (UNSRI)ИндонезияSriwijaya University (UNSRI)Indonesia2021120420211218390Copyright © Редита Н., Робиани Б., Юлианита А., 20212021Редита Н., Робиани Б., Юлианита А.Nesha R., Bernadette R., Yulianita A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.mir-nayka.com/jour/article/view/1123

Целью исследования является анализ условий распределения доходов и факторов низкого коэффициента Джини в областях, которые вносят наибольший вклад в экономику провинции Кепулауан Бангка Белитунг (Индонезия), включая промышленный, сельскохозяйственный и торговый секторы, а также производительность труда в промышленном секторе.

Методы или методология проведения работы. Феномен распределения доходов в провинции Кепулауан Бангка Белитунг в период 2007-2018 гг. стал основой для анализа определяющих переменных распределения доходов, включая промышленный, сельскохозяйственный и торговый секторы, а также производительность труда в промышленности. Индикатор распределения доходов измерялся по значению коэффициента Джини с использованием метода регрессии панельных данных для определения влияния этих переменных на коэффициент Джини во всех округах (городах) провинции Кепулауан Бангка Белитунг Индонезии.

Результаты работы показали, что сельскохозяйственный сектор, промышленный сектор и сектор торговли оказали отрицательное и значительное влияние на коэффициент Джини. Между тем, производительность труда в промышленном секторе оказала существенное положительное влияние на коэффициент Джини. Определяющим фактором распределения доходов был сельскохозяйственный сектор. Дальнейшие результаты подтверждают, что в сельскохозяйственном, промышленном и торговом секторах распределение доходов улучшилось.

Выводы. Представленное исследование подразумевало усилия по повышению ориентации сельскохозяйственного рынка на высокую производительность труда, что было противоположно тому, что производительность труда рабочих в промышленном секторе, как было доказано, снижает распределение доходов. Следовательно, необходима структурная трансформация в направлении индустриализации, а также рыночные усилия сельскохозяйственного сектора.

Purpose

Purpose: this research study focused on analyzing the conditions of income distribution and the determinants of the low Gini coefficient, namely the sectors that have the highest contribution, including the industrial, agricultural and trade sectors and labor productivity in the industrial sector in Kepulauan Bangka Belitung Province.

Methods

Methods: the income distribution phenomenon in Kepulauan Bangka Belitung Province during the 2007-2018 period became the basis for analyzing the determining variables of income distribution including the industrial sector, the agricultural sector, the trade sector and the industrial labor productivity. The income distribution indicator was measured from the Gini coefficient value using the Panel Data Regression approach to determine the effect of these variables on the Gini coefficient in all regencies / cities in the Kepulauan Bangka Belitung Province.

Results

Results: the results showed that the agricultural sector, industrial sector and trade sector had a negative and significant effect on the Gini coefficient. Meanwhile, labor productivity in the Industrial Sector had a significant positive effect on the Gini coefficient. The results showed that the determinant of income distribution was the agricultural sector. Further findings prove that the agricultural, industrial and trade sectors improved the income distribution.

Conclusions and Relevance: this study implied for the efforts to increase the agricultural market orientation towards high productivity which was inversely contrast to the output of workers in the industrial sector proven to reduce income distribution. Therefore, the structural transformation towards industrialization and market-oriented efforts from the agricultural sector were necessary.

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The authors declare that there are no conflicts of interest present.