Friday, March 11, 2016

Economic Growth and Global Particulate Pollution Concentrations

I have just posted another working paper in the Trends and Drivers series, this time coauthored with recent Crawford masters student Jeremy van Dijk.

Particulate pollution, especially PM2.5, is thought to be the form of pollution with the most serious human health impacts. It is estimated that PM2.5 exposure causes 3.1 million deaths a year, globally, and any level above zero is deemed unsafe, i.e. there is no threshold above zero below which negative health effects do not occur. Black carbon is an important fraction of PM2.5 pollution that may contribute significantly to anthropogenic radiative forcing and, therefore, there may be significant co-benefits to reducing its concentration. In our paper, we use recently developed population-weighted estimates of national average concentrations of PM2.5 pollution that are available from the World Bank Development Indicators. These combine satellite and ground based observations.

Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications focused on pollution emissions. Yet, previous research suggests that it is more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. We examine the role of income, convergence, and time related factors in explaining changes in PM2.5 pollution in a global panel of 158 countries between 1990 and 2010. We find that economic growth has positive but relatively small effects, time effects are also small but larger in wealthier and formerly centrally planned economies, and, for our main dataset, convergence effects are small and not statistically significant.

Crucially, when we control for other relevant variables, even for this particulate pollution concentration data there is no environmental Kuznets curve, if what we mean by that is that environmental impacts decline with increasing income once a given in sample level of income is passed - the turning point.

The following graph shows the relationship between the average growth rates over 20 years of particulate pollution concentrations and per capita GDP:

The two big circles are of course China and India where both GDP and particulate pollution grew strongly. We can see that there is a positive relationship between these two growth rates, especially when we focus on the larger countries. The main econometric estimate in the paper shows that a 1% increase in the rate of economic growth is associated with a 0.2% increase in the growth rate of particulate pollution. This is much weaker than the effects we found for emissions of carbon and sulfur dioxides. The estimated income turning point is $66k with a large standard error. On the other hand, when we estimate a model without the control variables, we obtain a turning point of only $3.3k with a standard error of only $1.2k. To check the robustness of this result, we estimate models with other data sets and time periods. These yield quite similar results.

We conclude that growth has smaller effects on the concentrations of particulate pollution than it does on emissions of carbon or sulfur. However, the EKC model does not appear to apply here either, casting further doubt on its general usefulness.

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