Determinants of Poverty in Central Java Province 2013-2018

This study aimed to assess whether there is influence between HDI, GRDP, Unemployment, Investment and Dummy (mainstay and not mainstay areas) on Poverty in Central Java. Based on data from BPS, poverty in Central Java Province in 2013-2018 are in number 2 after DI Yogyakarta in Java. This research u...

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Main Authors: Achyarnis Lilik Andrietya, Amin Pujiati, Andryan Setyadharma
Format: Article
Language:English
Published: Universitas Negeri Semarang 2020-06-01
Series:Journal of Economic Education
Subjects:
hdi
Online Access:https://journal.unnes.ac.id/sju/index.php/jeec/article/view/38671
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spelling doaj-dedf3d84aab943b5bdd2fbe03b85074e2020-11-25T03:41:06ZengUniversitas Negeri SemarangJournal of Economic Education2301-73412020-06-0191818810.15294/jeec.v9i1.3867138671Determinants of Poverty in Central Java Province 2013-2018Achyarnis Lilik Andrietya0Amin Pujiati1Andryan Setyadharma2PT Wijaya Karya (Persero) Tbk, Jakarta, IndonesiaPascasarjana, Universitas Negeri Semarang, IndonesiaPascasarjana, Universitas Negeri Semarang, IndonesiaThis study aimed to assess whether there is influence between HDI, GRDP, Unemployment, Investment and Dummy (mainstay and not mainstay areas) on Poverty in Central Java. Based on data from BPS, poverty in Central Java Province in 2013-2018 are in number 2 after DI Yogyakarta in Java. This research use panel data with a Fixed Effect Model (FEM) approach. Sources of data obtained from the Central Statistics Agency and the Directorate General of Indonesian Financial Balance. The results showed that the variable HDI, GRDP and investment had a negative and significant effect on poverty in Central Java Province. While the Unemployment and Dummy variables (mainstay and non-mainstay areas) have a negative and not significant effect on poverty in Central Java Province. Simultaneously, shows that the overall independent variable can show its effect on poverty. The coefficient of determination R2 of 0.9899 which means 98.99 percent of poverty can be explained by the independent variable. While the remaining 1.01 percent is explained by variables outside the model.https://journal.unnes.ac.id/sju/index.php/jeec/article/view/38671hdigdrppovertyinvestmentdummy
collection DOAJ
language English
format Article
sources DOAJ
author Achyarnis Lilik Andrietya
Amin Pujiati
Andryan Setyadharma
spellingShingle Achyarnis Lilik Andrietya
Amin Pujiati
Andryan Setyadharma
Determinants of Poverty in Central Java Province 2013-2018
Journal of Economic Education
hdi
gdrp
poverty
investment
dummy
author_facet Achyarnis Lilik Andrietya
Amin Pujiati
Andryan Setyadharma
author_sort Achyarnis Lilik Andrietya
title Determinants of Poverty in Central Java Province 2013-2018
title_short Determinants of Poverty in Central Java Province 2013-2018
title_full Determinants of Poverty in Central Java Province 2013-2018
title_fullStr Determinants of Poverty in Central Java Province 2013-2018
title_full_unstemmed Determinants of Poverty in Central Java Province 2013-2018
title_sort determinants of poverty in central java province 2013-2018
publisher Universitas Negeri Semarang
series Journal of Economic Education
issn 2301-7341
publishDate 2020-06-01
description This study aimed to assess whether there is influence between HDI, GRDP, Unemployment, Investment and Dummy (mainstay and not mainstay areas) on Poverty in Central Java. Based on data from BPS, poverty in Central Java Province in 2013-2018 are in number 2 after DI Yogyakarta in Java. This research use panel data with a Fixed Effect Model (FEM) approach. Sources of data obtained from the Central Statistics Agency and the Directorate General of Indonesian Financial Balance. The results showed that the variable HDI, GRDP and investment had a negative and significant effect on poverty in Central Java Province. While the Unemployment and Dummy variables (mainstay and non-mainstay areas) have a negative and not significant effect on poverty in Central Java Province. Simultaneously, shows that the overall independent variable can show its effect on poverty. The coefficient of determination R2 of 0.9899 which means 98.99 percent of poverty can be explained by the independent variable. While the remaining 1.01 percent is explained by variables outside the model.
topic hdi
gdrp
poverty
investment
dummy
url https://journal.unnes.ac.id/sju/index.php/jeec/article/view/38671
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AT aminpujiati determinantsofpovertyincentraljavaprovince20132018
AT andryansetyadharma determinantsofpovertyincentraljavaprovince20132018
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