The comparative exploration of mobile money services in inclusive development

Energy Exploration & Exploitation

Odhiambo

2020

The study examines nexuses between carbon dioxide (CO2) emissions, renewable energy consumption and inequality in 39 Sub-Saharan African countries for the period 2004–2014. The empirical evidence is based on Quantile regressions. First, in the 25th quantile of the inequality distributions, as long as CO2 emissions metric tons per capita are kept below 4.700 (4.100), the Gini coefficient (Atkinson index) will not increase. These are avoidable CO2 emissions thresholds. Second, renewable energy consumption should be complemented with other policies to: (i) reduce the Gini coefficient when renewable energy consumption is at 50.00% of total final energy consumption and (ii) mitigate the Atkinson index when renewable energy consumption is at 62.500% of total final energy consumption in the bottom quantiles of the Atkinson index distribution and at 50.00% of total final energy consumption in the 75th quantile of the Atkinson index distribution. These are renewable energy consumption thresholds for complementary policies. The novelty of this study in the light of extant literature is fundamentally premised on providing policy makers with avoidable thresholds of CO2 emissions as well as corresponding thresholds of renewable energy consumption for complementary policies, in the nexus between the green economy and inequality.

Section: Methodsmentioning

confidence: 99%

The green economy and inequality in Sub-Saharan Africa: Avoidable thresholds and thresholds for complementary policies

Energy Exploration & Exploitation

Odhiambo

2020

“…The extant empirical literature motivating the choice of variables in the preceding paragraph is as follows: mobile money drivers from the demand side (Muwanguzi and Musambira, 2009; Van der Boor et al , 2014; Demirgüç-Kunt et al , 2015); studies focusing on financial inclusion (Demirgüc-Kunt and Klapper, 2012; Demirgüç-Kunt et al , 2015; Asongu and Asongu, 2018; Asongu and Odhiambo, 2018a, 2018b); supply-side drivers of mobile money (Van der Boor et al , 2014; Mas and Morawczynski, 2009; Demirgüç-Kunt and Klapper, 2013; Gruber and Koutroumpis, 2013; Waverman and Koutroumpis, 2011; GSMA, 2018); and macroeconomic indicators (Murendo et al , 2018; World Bank, 2016; Asongu and Odhiambo, 2022). The corresponding summary statistics and correlation matrix of the variables are provided in Appendices 2 and 3, respectively.…”

Section: Methodsmentioning

confidence: 99%

Telecommunications regulation, mobile money innovations and financial inclusion

2023

JFRC

Self Cite

Purpose This study aims to assess how corporate telecommunication (telecom) policies follow telecom sector regulation in mobile money innovation for financial inclusion in developing countries. Design/methodology/approach Telecom policies are understood in terms of mobile subscriptions, mobile connectivity coverage and mobile connectivity performance, whereas mobile money innovations represent mobile money accounts, the mobile used to send money and the mobile used to receive money. The empirical evidence is based on Tobit regressions. Findings Telecom sector regulation positively influences mobile money innovations. From net influences, mobile subscriptions and connectivity policies moderate telecom sector regulation to positively influence mobile money innovations, exclusively within the remit of mobile money accounts because the corresponding net influences on the mobile used to send money and the mobile used to receive money are negative. The interactive influences are consistently negative, and hence, thresholds for complementary policies are provided to maintain the positive influence of telecom sector regulation on mobile money innovations. Originality/value This study has complemented the extant literature by assessing how corporate telecommunication policies follow telecommunication sector regulation in mobile money innovations for financial inclusion.

“…Second, the corresponding demand factors which are sourced from the GFSD are the number of automated teller machines (ATMs), bank sector concentration, and the “percentage of adults with a bank account in a formal banking institution.” Third, the macro‐level features are: (i) the rule of law from the WGI of the World Bank; and (ii) GDP growth, the GDP per capita, and urbanization rate from the WDI of the World Bank. The selection of these variables is motivated by the attendant literature on financial inclusion (Mas and Morawczynski 2009; Muwanguzi and Musambira 2009; Waverman and Koutroumpis 2011; Demirgüc‐Kunt and Klapper 2012, 2013; Van der Boor, Oliveira and Veloso 2014; Gruber and Koutroumpis 2013; Demirgüc‐Kunt, Klapper and Van Oudheusden 2015; Asongu and Odhiambo 2018b; GSMA 2018; Murendo et al 2018; Asongu and Asongu 2018). With the exceptions of bank concentration and the rule of law, the documented demand, supply, and macro‐level factors are broadly anticipated to promote mobile money innovations.…”

Section: Methodsmentioning

confidence: 99%

The Role of Economic Growth in Modulating Mobile Connectivity Dynamics for Financial Inclusion in Developing Countries

Odhiambo

2022

World Affairs

This study establishes economic growth needed for supply-side mobile money drivers in developing countries to be positively related to mobile money innovations in the perspectives of mobile money accounts, the mobile phone used to send money, and the mobile phone used to receive money. The empirical evidence is based on Tobit regressions. For the negative net relationships that are computed, minimum economic growth thresholds are established above which the net negative relationships become net positive relationships. The following minimum economic growth rates are required for nexuses between supply-side mobile money drivers and mobile money innovations to be positive: (i) 6.109 percent (6.193%) of Gross Domestic Product (GDP) growth for mobile connectivity performance to be positively associated with the mobile phone used to send (receive) money and (ii) 4.590 percent (4.259%) of GDP growth for mobile connectivity coverage to be positively associated with the mobile phone used to send (receive) money.