Research

Workers in developing countries waste significant time commuting, and gaps in public transit constrain access to productive jobs. In many cities, privately-operated minibuses provide 50–100% of urban transit, at the cost of long wait times and poor personal safety for riders. Can policymakers improve upon the privatized provision of public transit via subsidies, which leverage increasing returns in wait times, or technological upgrades? I build a micro-founded model of privatized shared transit where minibuses load passengers from a queue. I then estimate the model with newly-collected data on minibus and passenger queues in Cape Town and stated user preferences for exogenously-varied commute attributes. I find that governments should subsidize minibuses and their passengers because neither internalize their beneficial spillovers to wait times. This optimization shortens queues, fills buses faster, and particularly benefits low-skill workers. Government actions to expand minibus stations or improve security bring even more substantial welfare gains.

We propose a theory-inspired measure of the accessibility to a city’s central work location: the size of the surrounding area from which it can be reached within a specific time. Using publicly available optimal-routing software, we compute these ”accessibility zones” for the 100 largest cities in the US and Europe, separately for cars and public transit commutes. Compared with European cities, US cities are half as accessible via public transit and twice as accessible via cars. Car accessibility zones are always larger than public transit zones, so that US cities are accessible from larger areas than European cities. However, population density within the most accessible zones is relatively low in the US, and European cities provide more residents quicker access to their city centers. Moreover, greater car orientation is associated with less green space, more congestion, and worse health and pollution externalities.

Retraining is often hailed as a key policy tool to support workers displaced by import competition, yet there is surprisingly little evidence on whether these policies achieve their intended effects. Using administrative data from Germany, a highly open economy with extensive government-subsidized retraining programs, we provide evidence that workers routinely retrain in response to import competition. To quantify the welfare impact of retraining policies, we propose a search model in which heterogeneous workers may choose to retrain while unemployed. Retraining enables workers to change their job-finding rates and their productivity while employed. We find that retraining increases the gains from trade by 7% in the aggregate. Some worker groups gain five times as much, while others gain virtually nothing.