Linear Regression Estimation of Discrete Choice Models with Nonparametric Distributions of Random Coefficients by Patrick Bajari, Jeremy T. Fox and Stephen P. Ryan. Published in volume 97, issue 2, pages 459-463 of American Economic Review, May 2007

We use a randomized experiment and a structural model to test whether monitoring and financial incentives can reduce teacher absence and increase learning in India. In treatment schools, teachers' attendance was monitored daily using cameras, and their salaries were made a nonlinear function of attendance. Teacher absenteeism in the treatment group fell by 21 percentage points relative to the control group, and the children's test scores increased by 0.17 standard deviations. We estimate a structural dynamic labor supply model and find that teachers respond strongly to financial incentives. Our model is used to compute cost-minimizing compensation policies.

We assess the static and dynamic implications of alternative market-based policies limiting greenhouse gas emissions in the US cement industry. Our results highlight two countervailing market distortions. First, emissions regulation exacerbates distortions associated with the exercise of market power in the domestic cement market. Second, emissions “leakage” in trade-exposed markets offsets domestic emissions reductions. Taken together, these forces can result in social welfare losses under policy regimes that fully internalize the emissions externality. Market-based policies that incorporate design features to mitigate the exercise of market power and emissions leakage deliver welfare gains when damages from carbon emissions are high.

We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. To improve out-of-sample prediction accuracy, we propose a method of combining the underlying models via linear regression. Our method is robust to a large number of regressors; scales easily to very large data sets; combines model selection and estimation; and can flexibly approximate arbitrary non-linear functions. We illustrate our method using a standard scanner panel data set and find that our estimates are considerably more accurate in out-of-sample predictions of demand than some commonly used alternatives.

The efficiency of publicly-subsidized, privately-provisioned social insurance programs depends on the interaction between strategic insurers and the subsidy mechanism. We study this interaction in the context of Medicare's prescription drug coverage program. We find that the observed mechanism is successful in keeping "raise-the-subsidy" incentives relatively low, acts much like a flat voucher, and obtains a level of welfare close to the optimal voucher. Across a range of counterfactuals, we find that more efficient subsidy mechanisms share three features: they retain the marginal elasticity of demand, limit the exercise of market power, and preserve the link between prices and marginal costs.

We evaluate a program that recruited local entrepreneurs to open and operate new schools in 200 underserved villages in Sindh, Pakistan. School operators received a per student subsidy to provide tuition-free primary education, and half the villages received a higher subsidy for females. The program increased enrollment by 32 percentage points and test scores by 0.63 standard deviations, with no difference across the two subsidy schemes. Estimating a structural model of the demand and supply for school inputs, we find that program schools selected inputs similar to those of a social planner who internalizes all the education benefits to society.

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 medical utilization, we present evidence of heterogeneous moral hazard as well as selection on it, and explore some of its implications. For example, we show that, at least in our context, abstracting from selection on moral hazard could lead to over-estimates of the spending reduction associated with introducing a high-deductible health insurance option.