Employing hourly data records from 2013 and 2014 in Beijing, we investigate the causal effects of vehicle traffic on air pollution. An arguably exogenous variation in vehicle use that results from the staggered and rotating driving restriction program there, combined with a widespread Chinese superstition about the unlucky number four, allows us to better track causal effects of traffic-induced air pollutants in a generalized 2SLS framework.

We study the optimal and equilibrium distribution of industrial and residential land in a given region. The trade-off between the agglomeration and dispersion forces, in the form of pollution from stationary forces, production externalities, and commuting costs, determines the emergence of industrial and residential clusters across space. In this context, we define two kinds of spatial policies that can be used in order to close the gap between optimal and market allocations.

The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks.