A Monte Carlo Study of Ranked Efficiency Estimates from Frontier Models

Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimating (a) the conditional mean of inefficiency and (b) probabilities that firms are most or least efficient. Monte Carlo experiments suggest that the efficiency probabilities are easier to estimate (less noisy) in terms of mean absolute percent error when inefficiency has large variation across firms. Along the way we tackle some interesting problems associated with simulating and assessing estimator performance in the stochastic frontier model

2020-3 Optimal Contracting with Altruistic Agents: A Structural Model of Medicare Payments for Dialysis Drugs

We study physician agency and optimal payment policy in the context of an expensive medication used in dialysis care. Using Medicare claims data we estimate a structural model of treatment decisions, in which physicians differ in their altruism and marginal costs, and this heterogeneity is unobservable to the government. In a novel application of nonlinear pricing methods, we theoretically characterize the optimal unrestricted contract in this screening environment with multidimensional heterogeneity. We combine these results with the estimated model to construct the optimal contract and simulate counterfactual outcomes. The optimal contract is a flexible fee-for-service contract, which pays for reported treatments but uses variable marginal payments instead of constant reimbursement rates, resulting in substantial health improvements and reductions in costs. Our structural approach also yields important qualitative findings, such as rejecting the optimality of any linear contract, and may be employed more broadly to analyze a variety of applications

Identification of preferences in network formation games

This paper provides a framework for identifying preferences in a large network under the assumption of pairwise stability of network links. Network data present difficulties for identification, especially when links between nodes in a network can be interdependent: e.g., where indirect connections matter. Given a preference specification, we use the observed proportions of various possible payoff-relevant local network structures to learn about the underlying parameters. We show how one can map the observed proportions of these local structures to sets of parameters that are consistent with the model and the data. Our main result provides necessary conditions for parameters to belong to the identified set, and this result holds for a wide class of models. We also provide sufficient conditions - and hence a characterization of the identified set - for two empirically relevant classes of specifications. An interesting feature of our approach is the use of the economic model under pairwise stability as a vehicle for effective dimension reduction. The paper then provides a quadratic programming algorithm that can be used to construct the identified sets. This algorithm is illustrated with a pair of simulation exercises

Expected Efficiency Ranks from Parametric Stochastic Frontier Models

In the stochastic frontier model we extend the multivariate probability statements of Horrace (2005) to calculate the conditional probability that a firm is any particular efficiency rank in the sample. From this we construct the conditional expected efficiency rank for each firm. Compared to the traditional ranked efficiency point estimates, firm-level conditional expected ranks are more informative about the degree of uncertainty of the ranking. The conditional expect ranks may be useful for empiricists. A Monte Carlo study and an empirical example are provided

Peer Effects in Sexual Initiation: Separating Demand and Supply Mechanisms

<p>Most work on social interactions studies a single, composite effect of interactions within a group. Yet in the case of sexual initiation there are two distinct social mechanisms— peer-group norms and partner availability—with separate effects and different potential interventions. Here I develop an equilibrium search and matching model for first sexual partners that specifies distinct roles for these two mechanisms as part of demand and supply. I estimate the model using a national sample of high school students, with data over time on individual virginity status. The results indicate that peer-group norms have a large effect on the timing of sexual initiation for both boys and girls. Changes in opposite-gender search behavior (i.e., partner availability) also have a large impact on initiation rates for boys, but not for girls.</p

Optimal contracting with altruistic agents: A structural model of Medicare payments for dialysis drugs

We study physician agency and optimal payment policy in the context of an expensive medication used in dialysis care. Using Medicare claims data we estimate a structural model of treatment decisions, in which physicians differ in their altruism and marginal costs, and this heterogeneity is unobservable to the government. In a novel application of nonlinear pricing methods, we theoretically characterize the optimal unrestricted contract in this screening environment with multidimensional heterogeneity. We combine these results with the estimated model to construct the optimal contract and simulate counterfactual outcomes. The optimal contract is a exible fee-for-service contract, which pays for reported treatments but uses variable marginal payments instead of constant reimbursement rates, resulting in substantial health improvements and reductions in costs. Our structural approach also yields important qualitative findings, such as rejecting the optimality of any linear contract, and may be employed more broadly to analyze a variety of applications

Expected efficiency ranks from parametric stochastic frontier models

In the stochastic frontier model, we extend the multivariate probability statements of Horrace (J Econom, 126:335–354, 2005) to calculate the conditional probability that a firm is any particular efficiency rank in the sample. From this, we construct the conditional expected efficiency rank for each firm. Compared to the traditional ranked efficiency point estimates, firm-level conditional expected ranks are more informative about the degree of uncertainty of the ranking. The conditional expected ranks may be useful for empiricists. A Monte Carlo study and an empirical example are provided

Contagion in the European Sovereign Debt Crisis

<p>We use a network model of credit risk to measure market expectations of the potential spillovers from a sovereign default. Specifically, we develop an empirical model, based on the recent theoretical literature on contagion in financial networks, and estimate it with data on sovereign credit default swap spreads and the detailed structure of financial linkages among thirteen European sovereigns from 2005 to 2011. Simulations from the estimated model show that a sovereign default generates only small spillovers to other sovereigns. These results imply that credit markets do not demand a significant premium for the interconnectedness of sovereign debt in Europe.</p

Replication data for: "Subsidies and Structure: The Lasting Impact of the Hill-Burton Program on the Hospital Industry"

Replication data for: "Subsidies and Structure: The Lasting Impact of the Hill-Burton Program on the Hospital Industry