A new working paper coauthored with Donglan Zha, who is visiting the Crawford School, which will be published in a special issue of Environmental Economics and Policy Studies. Our paper tries to explain recent changes in PM 2.5 and PM 10 particulate pollution in 50 Chinese cities using new measures of ambient air quality that the Chinese government has published only since the beginning of 2013. These data are not comparable to earlier official statistics and we believe are more reliable. We use our recently developed model that relates the rate of change of pollution to the growth of the economy and other factors as well as also estimating the traditional environmental Kuznets curve (EKC) model.
Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications have focused on pollution emissions. Yet, it would seem more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. This is the first application of our new model to such concentration data.
The data show that there isn't much correlation between the growth rate of GDP between 2013 and 2014 and the growth rate of PM 2.5 pollution over the same period:
What is obvious is that pollution fell sharply from 2013 to 2014, as almost all the data points have negative pollution growth. We have to be really cautious in interpreting a two year sample. Subsequent events suggest that this trend did not continue in 2015.
In fact, the simple linear relationship between these variables is negative, though statistically insignificant. The traditional EKC model and its growth rate equivalent both have a U shape curve - the effect of growth is negative at lower income per capita levels and positive at high ones. But the (imprecisely estimated, so not statistically significant) turning point fro PM 2.5 is way out of sample at more than RMB 400k.* So, growth has a negative effect on pollution in the relevant range. When we add the initial levels of income per capita and pollution concentrations to the growth rates regression equation the turning point is in-sample and statistically significant. The initial level of pollution has a negative and highly statistically significant effect. So, there is "beta convergence" - cities with initially high pollution concentrations, reduced their level of pollution faster than cleaner cities did.
So what does all this mean? These results are very different than those we found for emissions of CO2, total GHGs, and sulfur dioxide. In all those cases, we found that growth had a positive and quite large effect on emissions. In some cases, the effect was close to 1:1. Of course, we should be cautious about interpreting this small Chinese data set. But our soon to be released research on global PM 2.5 concentrations, will again show that the effect of growth is smaller for these data than it is for the key pollution emissions data. This confirms early research that suggested that pollution concentrations turn down before emissions do, though it doesn't seem to support the traditional EKC interpretation of the data.
BTW, it is really important in this research to use the actual population of cities and not just the registered population (with hukou). If you divide the local GDP by the registered population you can get very inflated estimates of GDP per capita for cities like Shenzhen.
* The turning point is in-sample for PM 10.
Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications have focused on pollution emissions. Yet, it would seem more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. This is the first application of our new model to such concentration data.
The data show that there isn't much correlation between the growth rate of GDP between 2013 and 2014 and the growth rate of PM 2.5 pollution over the same period:
What is obvious is that pollution fell sharply from 2013 to 2014, as almost all the data points have negative pollution growth. We have to be really cautious in interpreting a two year sample. Subsequent events suggest that this trend did not continue in 2015.
In fact, the simple linear relationship between these variables is negative, though statistically insignificant. The traditional EKC model and its growth rate equivalent both have a U shape curve - the effect of growth is negative at lower income per capita levels and positive at high ones. But the (imprecisely estimated, so not statistically significant) turning point fro PM 2.5 is way out of sample at more than RMB 400k.* So, growth has a negative effect on pollution in the relevant range. When we add the initial levels of income per capita and pollution concentrations to the growth rates regression equation the turning point is in-sample and statistically significant. The initial level of pollution has a negative and highly statistically significant effect. So, there is "beta convergence" - cities with initially high pollution concentrations, reduced their level of pollution faster than cleaner cities did.
So what does all this mean? These results are very different than those we found for emissions of CO2, total GHGs, and sulfur dioxide. In all those cases, we found that growth had a positive and quite large effect on emissions. In some cases, the effect was close to 1:1. Of course, we should be cautious about interpreting this small Chinese data set. But our soon to be released research on global PM 2.5 concentrations, will again show that the effect of growth is smaller for these data than it is for the key pollution emissions data. This confirms early research that suggested that pollution concentrations turn down before emissions do, though it doesn't seem to support the traditional EKC interpretation of the data.
BTW, it is really important in this research to use the actual population of cities and not just the registered population (with hukou). If you divide the local GDP by the registered population you can get very inflated estimates of GDP per capita for cities like Shenzhen.
* The turning point is in-sample for PM 10.
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