We estimate the demand for a videocalling technology in the presence of both network effects and heterogeneity. Using a unique dataset from a large multinational firm, we pose and estimate a fully dynamic model of technology adoption. We propose a novel identification strategy based on...

This paper analyzes the role of heterogeneity and forward-looking expectations in the diffusion of network technologies. Using a detailed dataset on the adoption of a new videoconferencing technology within a firm, we estimate a structural model of technology adoption and communications choice....

We explore the long run dynamic implications of subjecting an imperfectly competitive industry to market-based pollution regulation. We are particularly interested in understanding how the allocation of emissions permits in a cap-and-trade program can influence the evolution of a trade exposed...

We use employee-level panel data from a single firm to explore the possibility that individuals may select insurance coverage in part based on their anticipated behavioral ("moral hazard") response to insurance, a phenomenon we label "selection on moral hazard." Using a model of plan choice and...

We assess the long-run dynamic implications of market-based regulation of carbon dioxide emissions in the US Portland cement industry. We consider several alternative policy designs, including mechanisms that use production subsidies to partially offset compliance costs and border tax...

We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. We derive novel asymptotic properties for several of these models. To improve out-of-sample prediction accuracy and obtain parametric rates of convergence, we propose...

We propose a simple nonparametric mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program...

The random coefficients, multinomial choice logit model has been widely used in empirical choice analysis for the last 30 years. We are the first to prove that the distribution of random coefficients in this model is nonparametrically identified. Our approach exploits the structure of the logit...