Capturing the drivers of social SDGs: An econometric analysis of the dimensions of health and education.

With the changing policy landscape, the monitoring of human development in terms of the three pillars of sustainability (i.e., economic, social, environmental) has gained considerable traction in recent years. As a tool for conducting economic impact assessments, CGE simulation modelling is a workhorse member of the standard toolbox of modelling applications available to policy-makers, think tanks and academics alike. Notwithstanding, whilst simulation modelling is adept (in differing degrees) at handling issues relating to two of the three dimensions of sustainability, the social dimension remains neglected. Indeed, with their reliance on strictly market driven concepts, the task of including social indicators in economic models relating to, for example, health or education, necessitates a linkage with historical observation and statistical rigour. This paper sets out to provide an initial step toward filling this gap. More specifically, employing panel datasets and econometric model specifications based on searches of the relevant literature, this paper provides parametric linkages between identifiable indices in economic simulation models and a selection of six indicators covering health and education. One of the conclusions drawn from this paper is the significant effect of per capita GDP on health and education indicators. Nevertheless, the impact of other drivers, such as the food intake or the share of the agricultural sector on GDP, have a similar or even a greater magnitude than the income level. We also found a close relationship between health and education, since all health indicators tend to improve as the years of schooling increase. In contrast, the impact of pollution, trade openness and inequality on the selected indicators is much more reduced and, in most cases, not statistically significant

Capturing the drivers of social SDGs: An econometric analysis of the dimensions of health and education.

With the changing policy landscape, the monitoring of human development in terms of the three pillars of sustainability (i.e., economic, social, environmental) has gained considerable traction in recent years. As a tool for conducting economic impact assessments, CGE simulation modelling is a workhorse member of the standard toolbox of modelling applications available to policy-makers, think tanks and academics alike. Notwithstanding, whilst simulation modelling is adept (in differing degrees) at handling issues relating to two of the three dimensions of sustainability, the social dimension remains neglected. Indeed, with their reliance on strictly market driven concepts, the task of including social indicators in economic models relating to, for example, health or education, necessitates a linkage with historical observation and statistical rigour. This paper sets out to provide an initial step toward filling this gap. More specifically, employing panel datasets and econometric model specifications based on searches of the relevant literature, this paper provides parametric linkages between identifiable indices in economic simulation models and a selection of six indicators covering health and education. One of the conclusions drawn from this paper is the significant effect of per capita GDP on health and education indicators. Nevertheless, the impact of other drivers, such as the food intake or the share of the agricultural sector on GDP, have a similar or even a greater magnitude than the income level. We also found a close relationship between health and education, since all health indicators tend to improve as the years of schooling increase. In contrast, the impact of pollution, trade openness and inequality on the selected indicators is much more reduced and, in most cases, not statistically significant