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The Comparative Economics of ICT, Environmental Degradation and Inclusive Human Development in Sub-Saharan Africa

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Abstract

This study examines how information and communication technology (ICT) could be employed to dampen the potentially damaging effects of environmental degradation in order to promote inclusive human development in a panel of 44 Sub-Saharan African countries. ICT is captured with internet and mobile phone penetration rates whereas environmental degradation is measured in terms of CO2 emissions per capita and CO2 intensity. The empirical evidence is based on fixed effects and Tobit regressions using data from 2000 to 2012. In order to increase the policy relevance of this study, the dataset is decomposed into fundamental characteristics of inclusive development and environmental degradation based on income levels (low income vs. middle income); legal origins (English Common law vs. French Civil law); religious domination (Christianity vs. Islam); openness to sea (landlocked vs. coastal); resource-wealth (oil-rich vs. oil-poor) and political stability (stable vs. unstable). Baseline findings broadly show that improvement in both of measures of ICT would significantly diminish the possibly harmful effect of CO2 emissions on inclusive human development. When the analysis is extended with the above mentioned fundamental characteristics, we observe that the moderating influence of both our ICT variables on CO2 emissions is higher in the group of English Common law, middle income and oil-wealthy countries than in the French Civil law, low income countries and oil-poor countries respectively. Theoretical and practical policy implications are discussed.

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Notes

  1. Fosu (2013a) defines policy syndromes as situations that are detrimental to growth: ‘administered redistribution’, ‘state breakdown’, ‘state controls’, and ‘suboptimal inter temporal resource allocation’. Within the framework of this study, policy syndromes are considered as issues that merit strategic action in order to achieve sustainable and inclusive human development.

  2. There is also an evolving stream of African development literature on the relevance of mobile technologies on inclusive development outcomes that has not focused on the environment (Afutu-Kotey et al. 2017; Asongu and Boateng 2018; Bongomin et al. 2018; Gosavi 2018; Hubani and Wiese 2018; Isszhaku et al. 2018; Minkoua Nzie et al. 2018; Muthinja and Chipeta 2018; Abor et al. 2018).

  3. According to the EKC hypothesis, in the long term, there is an inverted U-shaped relationship between per capita income and environmental degradation.

  4. The 44 countries are: Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo Democratic. Republic., Congo Republic, Cote d'Ivoire, Djibouti, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome & Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Tanzania, Togo, Uganda and Zambia.

  5. Whereas we have provided motivations for the choice of fundamental characteristics in Sect. 2, in this section, we discuss the information criteria used in the selection of underlying fundamental characteristics.

  6. There are four main World Bank income groups: (1) high income, $12,276 or more; (2) upper middle income, $3976-$12,275; (3) lower middle income, $1006–$3975 and (4) low income, $1005 or less.

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Authors and Affiliations

  1. Development Finance Centre, Graduate School of Business, University of Cape Town, Cape Town, South Africa

    Simplice A. Asongu

  2. Department of Economics and Development Studies, Covenant University, Ota, Ogun State, Nigeria

    Simplice A. Asongu

  3. Lancashire School of Business and Enterprise, University of Central Lancashire, Preston, PR2 2HE, UK

    Jacinta C. Nwachukwu & Chris Pyke

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Appendices

Appendix 1

See Table 4.

Table 4 Definitions of variables
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Appendix 2

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Table 5 Summary statistics (2000–2012)
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Appendix 3

See Table 6.

Table 6 Correlation matrix (uniform sample size: 171)
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Appendix 4

See Table 7.

Table 7 Categorization of Countries
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Asongu, S.A., Nwachukwu, J.C. & Pyke, C. The Comparative Economics of ICT, Environmental Degradation and Inclusive Human Development in Sub-Saharan Africa. Soc Indic Res 143, 1271–1297 (2019). https://doi.org/10.1007/s11205-018-2009-x

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