Does the digitalization crusade a way out of poverty and income inequality? Evidence from developing countries

被引:0
|
作者
Kamalu, Kabiru [1 ]
Ibrahim, Wan Hakimah Binti Wan [1 ]
机构
[1] Univ Sultan Zainal Abidin, Fac Business & Management, Dept Management, Kuala Terengganu, Malaysia
关键词
Poverty; Income inequality; Digitalization; Cointegrating estimators; Developing countries; INTERNET; ICT;
D O I
10.1108/IJSE-08-2023-0586
中图分类号
F [经济];
学科分类号
02 ;
摘要
PurposeThis study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.Design/methodology/approachThe study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.FindingsThe evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).Originality/valueThis study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586
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页数:18
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