In countries, such as Singapore, that have implemented vehicle congestion policies, recent years have seen a shift towards motor vehicle taxes based on car use. Ownership taxes reduce the number of cars on the road, leaving the price per trip largely unaffected. Use taxes such as fuel taxes and...

Local governments spend roughly $1.6 trillion per year to provide a variety of public services ranging from police and fire protection to public schools and public transit. However, we know little about public sector's productivity in delivering key services. To understand the productivity both...

We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including unstructured and nontraditional data like text and...

Public transit accounts for only 1% of U.S. passenger miles traveled but nevertheless attracts strong public support. Using a simple choice model, we predict that transit riders are likely to be individuals who commute along routes with the most severe roadway delays. These individuals' choices...

Designing public transport networks involves tradeoffs between extensive geographic coverage, frequent service on each route, and relying on interconnections as opposed to direct service. These choices, in turn, depend on individual preferences for waiting times, travel times, and transfers. We...

We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, as well as identify funds with net-of-fees abnormal returns. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance,...

We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2km and 2.4km (where the average US county has dimension of 55.6km), our model predictions achieve R2 values of 0.85...

A forecasting comparison is undertaken in which 49 univariate forecasting methods, plus various forecast pooling procedures, are used to forecast 215 U.S. monthly macroeconomic time series at three forecasting horizons over the period 1959 - 1996. All forecasts simulate real time implementation,...