Regional Inequality Based on Infrastructure Indicators Using Principal Component Analysis (PCA)

Abstract

This research aimed to identify the development gap among 27 sub-districts in Banyumas Regency based on infrastructure indicators using Principal Component Analysis (PCA). The infrastructure indicators used were the quality of road, lighting, transportation, market, bridges and schools. The data were collected by observation in 27 sub-districts of Banyumas Regency. From the analysis result with PCA, it can be determined that based on infrastructure indicators, the sub-districts in Banyumas Regency were divided into 4 clusters, namely: Cluster I with 1 sub-district; Cluster II with 3 sub-districts; Cluster III with 3 sub-districts, and the remainining 20 sub-districts were in Cluster IV.Keywords: Gap, Infrastructure, Principal Component Analysis (PCA).

Regional development gaps in Argentina: A multidimensional approach to identify the location of policy priorities

“…Meanwhile, Acevedo et al (2019), Borensztein et al (2014), Pardo Beltrán (2014), and Tezanos Vázquez (2012 study the development gaps for some Latin American countries. At a sub-national or regional level, we can also find several studies that examine development gaps between regions (Alberdi, Gibaja, & Parrilli, 2016;Czudec, Kata, & Wosiek, 2019;Niembro, 2015;Onofrei & Cigu, 2017;RIMISP, 2012RIMISP, , 2014Windhani & Hardoyono, 2017), while others provide a multidimensional view of spatial inequalities (Aboal et al, 2018;Antunez, Baccaïni, Guérois, & Ysebaert, 2017;Bin, 2016;Meyer, De Jongh, & Meyer, 2016;Niembro, 2020;Parente, 2019;Quadrado, Heijman, & Folmer, 2001;Quadrado, Loman, & Folmer, 2001).…”

“…Although, as it is common, there can be many alternative methodologies to address the same topic, it is worth mentioning that the combination of PCA and cluster analysis has been very popular throughout the empirical literature (Alberdi et al, 2016;Argüelles, Benavides, & Fernández, 2014;Del Campo, Monteiro, & Soares, 2008;Jindrová, 2015;Nakhaei, Hoseinzadeh Dalir, Ali Khamri, Doosti, & Abbasian, 2014;Niembro, 2017;Quadrado, Loman, et al, 2001;Rasic, 2005;Windhani & Hardoyono, 2017). Other studies propose slightly different methods to obtain a geographic regionalization (Assunção, Neves, Câmara, & da Costa Freitas, 2006;Carvalho, Da Mata, & Resende, 2008;Duque, Anselin, & Rey, 2012;Pereira & Moreira, 2020), with the aim of guaranteeing that the groups or clusters are formed by strictly neighbouring or contiguous spatial units.…”