PUBLICATIONS
The AGDI has published substantially in fulfillment of its mission statement of contributing to knowledge towards African development:
IDEAS
http://ideas.repec.org/d/agdiycm.html
ECONSTOR
https://www.econstor.eu/dspace/escollectionhome/10419/123513
Publication List
2020 |
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1. | Asongu, Nicholas Odhiambo Simplice M A International Social Science Journal, 2020. Abstract | Links | BibTeX | Tags: Insurance; Inclusive development; Africa @article{Asongu_87, author = {Nicholas Odhiambo M Simplice A. Asongu}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/issj.12223}, doi = {10.1111/issj.12223}, year = {2020}, date = {2020-03-30}, journal = {International Social Science Journal}, abstract = {In this study, we examine how insurance affects income inequality in sub‐Saharan Africa, using data from 42 countries during the period 2004–2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non‐life insurance. The empirical evidence is based on the Generalised Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non‐life insurance reduces the Gini coefficient and increasing non‐life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (percentage of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non‐life insurance premiums (percentage of GDP) is the threshold required for non‐life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub‐Saharan Africa.}, keywords = {Insurance; Inclusive development; Africa}, pubstate = {published}, tppubtype = {article} } In this study, we examine how insurance affects income inequality in sub‐Saharan Africa, using data from 42 countries during the period 2004–2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non‐life insurance. The empirical evidence is based on the Generalised Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non‐life insurance reduces the Gini coefficient and increasing non‐life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (percentage of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non‐life insurance premiums (percentage of GDP) is the threshold required for non‐life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub‐Saharan Africa. |
2. | Asongu, Nicholas Odhiambo Simplice M A 2020. Abstract | Links | BibTeX | Tags: Insurance; Inclusive development; Africa @unpublished{Asongu_104, author = {Nicholas Odhiambo M Simplice A. Asongu}, url = {http://www.afridev.org/RePEc/agd/agd-wpaper/Insurance-and-Inequality-in-Sub-Saharan-Africa-Policy-Thresholds.pdf}, year = {2020}, date = {2020-02-10}, abstract = {In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa.}, keywords = {Insurance; Inclusive development; Africa}, pubstate = {published}, tppubtype = {unpublished} } In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa. |
3. | Asongu, Nicholas Odhiambo Simplice M A 2020. Abstract | Links | BibTeX | Tags: Insurance; Inclusive development; Africa @unpublished{Asongu_106, author = {Nicholas Odhiambo M Simplice A. Asongu}, url = {http://www.afridev.org/RePEc/agd/agd-wpaper/Insurance-and-Inequality-in-Sub-Saharan-Africa-Policy-Thresholds.pdf}, year = {2020}, date = {2020-02-09}, abstract = {In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa.}, keywords = {Insurance; Inclusive development; Africa}, pubstate = {published}, tppubtype = {unpublished} } In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa. |