Sains Malaysiana 51(11)(2022): 3795-3806

http://doi.org/10.17576/jsm-2022-5111-23

 

Spatial Quantile Autoregressive Model: Case Study of Income Inequality in Indonesia

(Model Autoregresif Kuantil Reruang: Suatu Kajian Kes Ketaksamaan Pendapatan di Indonesia)

 

EVELLIN DEWI LUSIANA^1,2,*, HENNY PRAMOEDYO³ & BARIANTO NURASRI SUDARMAWAN⁴

 

¹Department of Aquatic Resource Management, Faculty of Fisheries and Marine Science, Universitas Brawijaya, Malang, 65145, Indonesia

²Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Brawijaya Malang, 65145, Indonesia

³Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, 65145, Indonesia

⁴Faculty of Economics, Universitas Islam Negeri Maulana Malik Ibrahim, Malang, 65145, Indonesia

 

Diserahkan: 4 Disember 2021/Diterima: 19 Julai 2022

 

Abstract

Substantial economic development in Indonesia has dramatically increased inequality in the last decade. This issue will hinder the country’s long-term economic development as well as creating socioeconomic instability and violence. This study analysed the effects of macroeconomic factors such as gross regional domestic product, investment, unemployment rate, and labour-force participation, on Indonesian provinces’ inequality. Since the economic development in Indonesia is mostly concentrated on Java Island, a spatial based analysis was appropriate. In addition, we also considered a method that enabled a specific level of inequality modelling, since previous studies used a mean-based analysis. Therefore, we proposed a spatial quantile autoregressive (SQAR) technique. The results showed that the Gini index of Indonesian provinces had a significant positive spatial autocorrelation (SA). Regions with similar Gini index values tended to cluster together. In addition, local analysis of the SA showed Java Island as a region that was characterized by high inequality, while Sumatra and Kalimantan Island were not. By contrast, the SQAR model suggested that there were various effects of macroeconomic factors on inequality at different levels of quantile. As a consequence, distinct approaches to handling inequality should be taken for provinces with low, medium, and high Gini index values.

 

Keywords: Gini index; Moran’s I; quantile regression; spatial connectivity

 

Abstrak

Pembangunan ekonomi yang besar di Indonesia telah meningkatkan ketidaksamaan secara mendadak dalam dekad yang lalu. Isu ini akan menghalang pembangunan ekonomi jangka panjang negara serta mewujudkan ketidakstabilan sosioekonomi dan keganasan. Kajian ini menganalisis kesan faktor makroekonomi seperti keluaran dalam negara serantau kasar, pelaburan, kadar pengangguran dan penyertaan tenaga buruh terhadap ketidaksamaan wilayah Indonesia. Memandangkan pembangunan ekonomi di Indonesia kebanyakannya tertumpu di Pulau Jawa, analisis berasaskan reruang adalah sesuai. Di samping itu, kami juga mempertimbangkan kaedah yang membolehkan pemodelan ketaksamaan tahap tertentu, memandangkan kajian terdahulu menggunakan analisis berasaskan min. Oleh itu, kami mencadangkan teknik autoregresif kuantil reruang (SQAR). Keputusan menunjukkan bahawa indeks Gini Wilayah Indonesia mempunyai autokorelasi reruang (SA) positif yang signifikan. Kawasan yang mempunyai nilai indeks Gini yang serupa cenderung berkumpul bersama. Di samping itu, analisis tempatan SA mendedahkan Pulau Jawa sebagai wilayah yang dicirikan oleh ketidaksamaan yang tinggi, manakala Pulau Sumatera dan Kalimantan tidak. Sebaliknya, model SQAR mencadangkan bahawa terdapat pelbagai kesan faktor makroekonomi terhadap ketidaksamaan pada tahap kuantil yang berbeza. Akibatnya, pendekatan berbeza untuk mengendalikan ketidaksamaan harus diambil untuk wilayah yang mempunyai nilai indeks Gini rendah, sederhana dan tinggi.

 

Kata kunci: Indeks Gini; Moran's I; perhubungan reruang; regresi kuantil

 

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^*Pengarang untuk surat-menyurat; email: evellinlusiana@ub.ac.id