Abstract
This study aims to analyze the role of health, education, energy and pollution in affecting productivity in selected emerging economies. Industrial share to GDP, trade openness and Information Communication and Technology (ICT) are used as control variables. Various dimensions of health and education are explored that include malnutrition, access to clean water, HIV, life expectancy and years of schooling at several levels. A set of Fixed Effect models provide evidence that all of the variables of health and education are critical for productivity. Further, the negative effect of trade openness calls for attention of the policy makers to work out the possibility of technology transfer through integration of economies so that productivity may be enhanced. Another dimension is to revisit the energy mix because the positive effect of energy use is offset by an increase in pollution. Public policy makers should understand the importance of public investment in necessary provisions for improving productivity, economic growth and ultimately the welfare of society, then it can make a difference.
Highlights
This study aims to analyze the role of health, education, energy and pollution in affecting productivity in selected emerging economies
The importance of education as a measure of human capital for determining the total factor productivity (TFP) is well established in the literature
An important insight, this paper shares, is the evidence on how the skillset is relevant for TFP for the selected countries
Summary
This study aims to analyze the role of health, education, energy and pollution in affecting productivity in selected emerging economies. The early empirical literature focused on a single aggregate measure of health like life expectancy and education like average years of schooling (see, for instance, Knowles and Owen, 1995; Bloom et al, 1999; Gallup and Sachs, 2000; Mayer, 2001; Bhargava et al, 2001; Webber, 2002). Though this literature provided useful insights about the relationship between human capital and TFP but lately, it was found limited from policy making perspective at a disaggregated level. Lenkei et al (2018), among a few, has investigated the impact of different levels of education, as indicators of human capital, on economic growth
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