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Analysis of Spatial Autocorrelation and Causality GRDP and Income Inequality in Java

Efficient: Indonesian Journal of Development Economics · Vol. 6 No. 1 (2023) · hlm. 73–83

DOI
10.15294/efficient.v6i1.57599
ISSN
2655-318X, 2655-6197
Terbit
2023-01-22
Penerbit
Universitas Negeri Semarang
Bahasa
eng

Abstrak

Research on the relationship between GRDP and income inequality shows that there is a spatial autocorrelation, however, empirical data shows that there is still income inequality that differs between regions, so it is necessary to re-examine the relationship. The island of Java is the main pillar of Indonesia's economic cycle, but the income inequality between the provinces is still high. This study aims to identify the magnitude of income inequality in Java. Identify the autocorrelation of GRDP and income inequality spatially, and in clusters and identify the causal relationship between GRDP and income inequality in Java. The analysis method uses the Williamson Index, Moran Index, Local Indicator of Spatial Autocorrelation (LISA) using the LISA Clustermap, and Granger Quality. This study is on the level of income inequality in each province in Java based on the Williamson Index value in the category of high inequality, having a negative autocorrelation value (the pattern tends to spread) and there is no spatial autocorrelation. Autocorrelation based on LISA Clustermap there is a pattern of cluster linkages (clustering and influencing each other) which has a High-Spot value so that there are areas that can be used as areas of cooperation for development.

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30 penulis · 64 tautan kepenulisan bersama · 9 lintas organisasi

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  • State University of Semarang
  • Syarif Hidayatullah State Islamic University Jakarta
  • Sebelas Maret University
  • National Research and Innovation Agency
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Rekan penulisOrganisasiArtikel bersama
Shanty OktaviliaState University of Semarang2
Phany Ineke PutriState University of Semarang2
Danang Dwi SaputroState University of Semarang1
Sonika MaulanaState University of Semarang1
Sava Amanda PuspitasariState University of Semarang1
Shara Meilyanti AnartanyState University of Semarang1
Rosyafa FebiandaniAfiliasi tidak diketahui1
Muhammad Adi Sofyan AnsoriState University of Semarang1
Afina Azka FauziaState University of Semarang1
Fatmawati FatmawatiSyarif Hidayatullah State Islamic University Jakarta1
Dita Nafaliya Dinul HaqiState University of Semarang1
Auladina RizqinaState University of Semarang1
Dwi RahmayaniState University of Semarang1
Elvira Latifa IsnainiState University of Semarang1
Anton SupriyadiState University of Semarang1
Igo Meyfin ArlantarikState University of Semarang1
Aldinovryanto TaherState University of Semarang1
Ola Ranti DewiState University of Semarang1
Nur AisahState University of Semarang1
Grace Natalia MarpaungState University of Semarang1
Prasetyo Ari BowoState University of Semarang1
Sepviana Nur KumalaSebelas Maret University1
Khusnul KhotimahNational Research and Innovation Agency1
Sri UtamiState University of Semarang1
Yozi Aulia RahmanState University of Semarang1
Fafurida FafuridaState University of Semarang1
Sucihatiningsih Dian Wisika PrajantiState University of Semarang1
Dafa Afif PratamaState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/efficient/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">Analysis of Spatial Autocorrelation and Causality GRDP and Income Inequality in Java</dc:title>
	<dc:creator>purwaningsih, Silvia</dc:creator>
	<dc:creator>Suseno, Deky Aji</dc:creator>
	<dc:description xml:lang="en-US">Research on the relationship between GRDP and income inequality shows that there is a spatial autocorrelation, however, empirical data shows that there is still income inequality that differs between regions, so it is necessary to re-examine the relationship. The island of Java is the main pillar of Indonesia's economic cycle, but the income inequality between the provinces is still high. This study aims to identify the magnitude of income inequality in Java. Identify the autocorrelation of GRDP and income inequality spatially, and in clusters and identify the causal relationship between GRDP and income inequality in Java. The analysis method uses the Williamson Index, Moran Index, Local Indicator of Spatial Autocorrelation (LISA) using the LISA Clustermap, and Granger Quality. This study is on the level of income inequality in each province in Java based on the Williamson Index value in the category of high inequality, having a negative autocorrelation value (the pattern tends to spread) and there is no spatial autocorrelation. Autocorrelation based on LISA Clustermap there is a pattern of cluster linkages (clustering and influencing each other) which has a High-Spot value so that there are areas that can be used as areas of cooperation for development.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2023-01-22</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/efficient/article/view/57599</dc:identifier>
	<dc:identifier>10.15294/efficient.v6i1.57599</dc:identifier>
	<dc:source xml:lang="en-US">Efficient: Indonesian Journal of Development Economics; Vol 6 No 1 (2023); 73-83</dc:source>
	<dc:source>2655-318X</dc:source>
	<dc:source>2655-6197</dc:source>
	<dc:source>10.15294/efficient.v6i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/efficient/article/view/57599/23982</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Efficient: Indonesian Journal of Development Economics</dc:rights>
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