ICT dynamics for gender inclusive intermediary education: Minimum poverty and inequality thresholds in developing countries

Abstract

This study examines linkages between information and communication technology (ICT) dynamics, inequality and poverty in order to establish critical masses of poverty and inequality that should not be exceeded in order for ICT dynamics to promote gender inclusive education in 57 developing countries for the period 2012-2016. Poverty is measured with the poverty headcount ratio at national poverty lines (% of the population) while inequality is proxied by the Gini coefficient, the Atkinson index and the Palma ratio. The ICT dynamics are measured with 'internet access in school', 'virtual social network', 'personal computers' 'mobile phone penetration', 'internet penetration' and 'fixed broadband subscriptions'. The empirical evidence is based on interactive Generalized Method of Moments estimators from which thresholds are computed contingent on the validity of tested hypotheses. First, the Gini coefficient should not exceed 0.5618 in order for 'internet access in school' to positively affect inclusive education. Second, the poverty headcount ratio at national poverty lines (% of the population) should remain below 33.6842% in order for 'internet access in school' to favorably influence inclusive education. Third, the Palma ratio should not exceed 3.3766 in order for internet penetration to favorably affect inclusive education. Fourth, for personal computers to increase inclusive education, the Gini coefficient, Palma ratio and poverty headcount (% of the population) should not exceed 0.4781, 3.5294 and 17.7272, respectively. The study confirms the significant role technological deepening plays in advancing inclusive education by means of policies that reduce poverty and income inequality, with potentially wider applicability to other developing economies. The study has provided poverty and inequality levels that should not be exceeded in order for personal computers, internet penetration and 'internet access in school' to promote gender inclusive education.

Poverty in Indonesia: An Application of Error Correction Model (ECM) Approach

“…Thus, if there is an increase in ICT by 1 percent, it will reduce poverty by -0.0043 percent. In the long run, ICT accepts H 2 and rejects H 0 .This result is in line with research Ahmed & Al-Roubaie (2013); Setyaningsih (2017); Nisa & Budiarti (2020); Mushtaq & Bruneau (2019); Mora-Rivera & García-Mora (2021); Asongu et al (2021); Christiani & Nainupu (2021) and Yin et al (2021) which found that ICT had a statistically significant negative effect on poverty. In 2007, it was reported that there were 20 million internet users in Indonesia.…”

“…Mushtaq & Bruneau (2019) conducted a case study by assessing the role of Information and Communication Technology (ICT) in poverty reduction, using a collection of panel data from 62 (sixty-two) countries between 2001-2012. Asongu et al (2021) examined the relationship between ICT dynamics in 57 developing countries from 2012-2016. Ahmed & Al-Roubaie (2013) examines the role of ICT in reducing poverty in Arab countries in achieving sustainable development.…”

Does information and communication technologies affect economic complexity?

“…This ever-growing evolution of ICTs has led policy makers and researchers alike to take a greater interest in the effects of ICTs on different aspects of socio-economic and political life. Thus, it has been demonstrated in the literature, although not exhaustive, that ICTs have positive effects, on employment (Mbongo and de Berquin 2019 ; Kılıçaslan and Töngür, 2019 ), trade (Abeliansky et al 2021 ); industrialisation (Njangang and Nounamo 2020 ); environment quality (Avom et al 2020 ; Asongu et al 2018 ; Higón et al 2017 ); corruption reduction (Sassi and Ali 2017 ; Kanyam et al 2017 ); democracy (Ali 2020 ); health outcomes (Dutta et al 2019 ); education (Asongu et al 2021 ); poverty reduction (Ofori et al 2021 ); income inequality reduction (Asongu and Odhiambo 2019 ), and most importantly economic growth (Sawng et al 2021 ; Appiah-Otoo and Song 2021 ; Hong 2017 ; Ofori and Asongu 2021 ; Ofori et al 2022 ). Despite this dynamic and extensive literature, very few studies have looked at the effect of ICT on economic complexity.…”

Towards inclusive green growth: Does digital economy matter?

“…Data is a new factor of production in the context of the digital economy, which has brought about profound changes in production, consumption, exchange and distribution. The digital economy's scale effect, low transaction cost and wide penetration are the most essential properties that influence the "inclusive" and "green" components ( Asongu et al, 2021;Shahbaz, et al, 2022).…”