Unleashing the potential of mobile broadband: Evidence from Indonesia's underdeveloped regions on its role in reducing income inequality

不平等 经济不平等 普通最小二乘法 移动宽带 面板数据 收入分配 经济 宽带 固定效应模型 信息和通信技术 人口 计量经济学 人口经济学 电信 计算机科学 人口学 数学 社会学 万维网 数学分析 无线
作者
Kasmad Ariansyah,Adhityo Nugraha Barsei,Zulfia Hanum Alfi Syahr,Nova Yulanda Putri Sipahutar,Marudur Pandapotan Damanik,Gonang May Perdananugraha,Amri Dunan,Daru Nupikso,Darmanto Darmanto,Dayat Hidayat,Bambang Mudjiyanto,Istiana Hermawati,Muhammad Suryanegara
出处
期刊:Telematics and Informatics [Elsevier]
卷期号:82: 102012-102012 被引量:13
标识
DOI:10.1016/j.tele.2023.102012
摘要

Although numerous studies have explored the relationship between information and communication technology (ICT) and socioeconomic development, limited research has focused on the impact of ICT infrastructure expansion on income distribution. This study aims to fill this research gap by investigating the effect of mobile broadband network coverage on income inequality in underdeveloped regions of Indonesia using unbalanced panel data encompassing 122 second-level subnational regions over the period from 2018 to 2021. This study utilizes map charts to visually depict the disparities in mobile broadband coverage and income inequality across the selected regions and ordinary least squares (OLS) regression on the pooled panel data to estimate the relationship between the two variables. The findings reveal an inverted U-shaped relationship between mobile broadband coverage and income inequality, indicating an adverse effect on inequality during the early stages of network deployment that persists until coverage reaches approximately 60 percent of the population area. Beyond this threshold, the effect becomes favorable in reducing inequality. The findings of this study remain robust even after accounting for potential biases, utilizing fixed and random effect models, and disaggregating the data for the pre- and during-pandemic periods. However, a minor discrepancy in statistical significance is observed when the dataset is disaggregated by the level of regional development. The implications of these findings are discussed, providing theoretical insights and policy/practical implications for addressing income inequality.

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