Abstract:The transition from Millennium Development Goals (MDGs) to Sustainable Development Goals (SDGs) has substantially shifted the policy debate from growth to inclusive growth. In this short note, we revisit the trust-growth nexus by exploiting a dataset on quality of growth (QG), recently made available to the scientific community. The empirical evidence is based on interactive contemporary and non-contemporary quantile regressions. Inequality and human development modifying variables are used as additional contr… Show more
“…In essence, with QR, parameter estimates are derived at multiple points of the conditional distributions of quality of growth (Koenker & Bassett, 1978). The QR estimation strategy is increasingly being employed in development literature, inter alia in: health (Asongu, 2014), corruption (Billger & Goel, 2009;Okada & Samreth, 2012) and quality of growth (Asongu & Rangan, 2015) studies. Therefore, the techinque enables us to examine the effects of social spending (health and education) on quality of growth with particular emphasis on best-and worst-performing developing countries in terms of growth quality.…”
Section: Methodsmentioning
confidence: 99%
“…In the transition from Millennium Development Goals (MDGs) to Sustainable Development Goals (SDGs), the policy debate has been shifting from growth to growth quality. The relevance of the underlying policy debate has been fuelled by the April 15 th 2015 publication of World Development Indicators which revealed that poverty has been decreasing in all regions of the world, with the exception of Sub-Saharan Africa (Asongu & Kodila-Tedika, 2015;Caulderwood, 2015;World Bank, 2015) in spite of (i) over two decades of growth resurgence that began in the mid-1990s (Fosu, 2015) and (ii) the sub-region hosting seven of the ten fastest growing economies in the world (Asongu & Rangan, 2015).…”
The transition from the Millennium Development Goals (MDGs) to Sustainable Development Goals (SDGs) has shifted the policy debate from growth to 'quality of growth' (QG). We explore a new dataset on QG by the IMF and classify 93 developing countries for the period 1990-2011 in terms of Hopefuls, Contenders and Best Performers. The aims are as follows: (i) to depict the contradiction between high-growth and poor social welfare and (ii) to assess the influence of education and health spending on the QG. We use quantile regressions to articulate least and best QG performers. Two key findings emerge. First, 31 of the 33 countries in the Hopefuls category are in SSA. Second, the effect of health is decreasingly positive from Hopefuls to Best Performers, while the impact of education is increasingly positive. As a main policy implication, it would benefit countries in SSA to invest more in health relative to education now, but decrease such health expenditure and increase education spending as the economies in the sub-region make the transition from Hopeful to Contenders and finally to Best Performers in terms of 'quality of growth'.
“…In essence, with QR, parameter estimates are derived at multiple points of the conditional distributions of quality of growth (Koenker & Bassett, 1978). The QR estimation strategy is increasingly being employed in development literature, inter alia in: health (Asongu, 2014), corruption (Billger & Goel, 2009;Okada & Samreth, 2012) and quality of growth (Asongu & Rangan, 2015) studies. Therefore, the techinque enables us to examine the effects of social spending (health and education) on quality of growth with particular emphasis on best-and worst-performing developing countries in terms of growth quality.…”
Section: Methodsmentioning
confidence: 99%
“…In the transition from Millennium Development Goals (MDGs) to Sustainable Development Goals (SDGs), the policy debate has been shifting from growth to growth quality. The relevance of the underlying policy debate has been fuelled by the April 15 th 2015 publication of World Development Indicators which revealed that poverty has been decreasing in all regions of the world, with the exception of Sub-Saharan Africa (Asongu & Kodila-Tedika, 2015;Caulderwood, 2015;World Bank, 2015) in spite of (i) over two decades of growth resurgence that began in the mid-1990s (Fosu, 2015) and (ii) the sub-region hosting seven of the ten fastest growing economies in the world (Asongu & Rangan, 2015).…”
The transition from the Millennium Development Goals (MDGs) to Sustainable Development Goals (SDGs) has shifted the policy debate from growth to 'quality of growth' (QG). We explore a new dataset on QG by the IMF and classify 93 developing countries for the period 1990-2011 in terms of Hopefuls, Contenders and Best Performers. The aims are as follows: (i) to depict the contradiction between high-growth and poor social welfare and (ii) to assess the influence of education and health spending on the QG. We use quantile regressions to articulate least and best QG performers. Two key findings emerge. First, 31 of the 33 countries in the Hopefuls category are in SSA. Second, the effect of health is decreasingly positive from Hopefuls to Best Performers, while the impact of education is increasingly positive. As a main policy implication, it would benefit countries in SSA to invest more in health relative to education now, but decrease such health expenditure and increase education spending as the economies in the sub-region make the transition from Hopeful to Contenders and finally to Best Performers in terms of 'quality of growth'.
“…Issues of immiserizing growth are clearly apparent in the second point because SSA has been enjoying over two decades of growth resurgence (Fosu, 2015, p. 44) on the one hand, and on the other hand, the sub-region is host to seven of the ten fastest growing economies in the world (Asongu & Rangan, 2016). Hence, the World Bank's position that about 45% of countries in the sub-region are substantially off-track from attaining the Millennium Development Goals (MDGs) extreme poverty target clearly shows that accounting for regional and other specificities documented by Mlachila et al (2014) is relevant for results with more targeted policy implications.…”
Section: Liberalisation Of Information and Communication Technologiesmentioning
confidence: 99%
“…The independent variables of interest or mobile money service indicators from Mosheni-Cheraghlou (2013) In accordance with recent inclusive literature, the control variables entail: education spending, government stability, credit, inflation, foreign direct investment (FDI) and remittances (Anand et al, 2013;Asongu & Rangan, 2016;Odhiambo, 2009Odhiambo, , 2011Odhiambo, , 2010bOdhiambo, , 2013Asongu & Nwachukwu, 2016). A complete definition of the variables is disclosed in Appendix 1.…”
Purpose-We respond to some challenges in the transition to Sustainable Development Goals by examining the correlations between mobile and inclusive development (quality of growth, poverty and inequality) in 93 developing countries for the year 2011.
“…First, the April 2015 World Bank report has revealed that poverty has been decreasing in all regions of the world with the exception of Africa where 45% of countries in sub-Saharan Africa (SSA) are substantially off-track from achieving the MDGs poverty target (Asongu and Kodila-Tedika, 2015). Second, the continent has enjoyed over two decades of growth resurgence (Fosu, 2015) and is currently host to seven of the ten fastest growing economies of the world (Asongu and Rangan, 2015). Third, one of the most important challenges the continent would be confronted with in the post-2015 development agenda is energy crisis (Akinyemi et al, 2015).…”
This study complements existing literature by examining the nexus between energy consumption (EC), CO 2 emissions (CE) and economic growth (GDP) in 24 African countries using a panel ARDL approach. The following findings are established. First, there is a long run relationship between EC, CE and GDP. Second, a long term effect from CE to GDP and EC is apparent, with reciprocal paths. Third, the error correction mechanisms are consistently stable. However, in cases of disequilibrium only EC can be significantly adjusted to its long run relationship. Fourth, there is a long-run causality running from GDP and CE to EC. Fifth, we find causality running from either CE or both CE and EC to GDP and inverse causal paths are observable. Causality from EC to GDP is not strong, which supports the conservative hypothesis. Sixth, the causal direction from EC to GDP remains unobservable in the short term. By contrast, the opposite path is observable. There are also no short-run causalities from GDP, or EC, or EC and GDP to EC. Policy implications are discussed.JEL Classification: C52; O40; O55; Q43: Q50
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