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

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

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

Testing for changes in the SES-mortality gradient when the distribution of education changes too

<p>We develop a flexible test for changes in the SES-mortality gradient over time that accounts for how education, commonly used as the primary marker of SES, is distributed in the population. We implement the test for the period between 1984 and 2006 using microdata from the Census, CPS, and NHIS linked to death records. Using our flexible test, we find that the evidence for a change in the education-mortality gradient is not as strong and universal as previous research has suggested. Our results indicate that the gradient increased for females during this time period, but we cannot rule out that the gradient among males has not changed. Informally, the results suggest that the changes for females are mainly driven by the bottom of the education distribution.</p

The Effects of Pharmaceutical Marketing and Promotion on Adverse Drug Events and Regulation

This paper analyzes the relationship between postmarketing promotional activity and reporting of adverse drug reactions (ADRs) by modeling the interaction between a regulator (the FDA) and a pharmaceutical firm. Promotion-driven market expansions enhance profitability yet may involve the risk of inappropriate drug prescriptions, leading to regulatory actions against the firm. We empirically test the relationship between drug promotion and reporting of ADRs using an innovative combination of commercial data on pharmaceutical promotion and FDA data on regulatory interventions and ADRs. We provide some evidence that increased levels of promotion and advertising lead to increased reporting of ADRs for certain conditions. (JEL L51, L65, M31, M37)