2018
DOI: 10.1088/1755-1315/157/1/012058
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Impact of life expectancy, literacy rate, opened unemployment rate and gross domestic regional income per capita on poverty in the districts/city in Central Sulawesi Province

Abstract: Research was conducted in several districts/city in Central Sulawesi Province in order to determine the effect of life expectancy, literacy rate, opened unemployment rate, and gross domestic regional income per capita on poverty at the districts/city in the province. The analysis used is Panel Data Regression. The results show that first, life expectancy and gross domestic regional income have a negative and significant impact on the poverty level in the districts/city in the Province. Second, the opened unemp… Show more

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Cited by 10 publications
(12 citation statements)
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“…Alam et al [14] explored poverty's determinants by using the ARDL on a sample period ranging from 1974 to 2018 in India and found the positive and significant impacts of national income, gross domestic savings, and population on poverty while gross capital formation left a negative impact. Tombolotutu et al [15] found that unemployment was responsible for increasing poverty, and the literacy rate showed an insignificant effect. An increase in employment caused a decrease in poverty, and increased employment caused income equality.…”
Section: The Impact Of Macroeconomic Factors On Povertymentioning
confidence: 99%
See 1 more Smart Citation
“…Alam et al [14] explored poverty's determinants by using the ARDL on a sample period ranging from 1974 to 2018 in India and found the positive and significant impacts of national income, gross domestic savings, and population on poverty while gross capital formation left a negative impact. Tombolotutu et al [15] found that unemployment was responsible for increasing poverty, and the literacy rate showed an insignificant effect. An increase in employment caused a decrease in poverty, and increased employment caused income equality.…”
Section: The Impact Of Macroeconomic Factors On Povertymentioning
confidence: 99%
“…We substituted the long-run slope coefficients of the income inequality model mentioned in Table 5, in Equation (2) mentioned in Section 3, to approach Equation (13). Moreover, we put the average values of independent variables in Equation ( 14) and found the estimated value of income inequality in Equation (15 Next, we find the predicted values of income inequality. To serve the purpose, we substituted the mean values of all the independent variables except the mean values of the investment portfolio and democratic accountability in Equation (13).…”
Section: Simulation-based Prediction Of Poverty and Income Inequalitymentioning
confidence: 99%
“…A study conducted by Kartiasih & Pribadi, (2020) stated a significant negative effect of the literacy rate on poverty in Indonesia. Another study conducted by Tombolotutu et al (2018) states that literacy rates positively and significantly affect poverty in districts/cities in Central Sulawesi. Although education does not directly affect the welfare of the population, participation of the poor in education is an essential investment in the long term.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Variabel bebas selanjutnya adalah pengeluaran perkapita dengan hipotesis bahwa pengeluaran per kapita berpengaruh signifikan negatif terhadap tingkat kemiskinan (Hasanah et al, 2021;Suparman et al, 2021). Variabel bebas berikutnya yaitu angka harapan hidup (AHH) dengan hipotesis bahwa variabel angka harapan hidup yang digunakan sebagai indikator kualitas kesehatan berpengaruh negatif signifikan terhadap tingkat kemiskinan di suatu wilayah (Hasanah et al, 2021;Tombolotutu et al, 2018). Variabel bebas terakhir adalah persentase penduduk usia kerja yang terdampak Covid-19 dengan hipotesis bahwa variabel tersebut berpengaruh terhadap kemiskinan tahun 2021 dikarenakan pandemi Covid-19 menyebabkan keterbatasan akses dan mobilitas penduduk yang berdampak terhadap pekerja.…”
Section: Pendahuluanunclassified