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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.

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.

This paper provides a framework for identifying preferences in a large network where links are pairwise stable. Network formation models present difficulties for identifi cation, especially when links can be interdependent: e.g., when indirect connections matter. We show how one can use the observed proportions of various local network structures to learn about the underlying preference parameters. The key assumption for our approach restricts individuals to have bounded degree in equilibrium, implying a finite number of payoff-relevant local structures. Our main result provides necessary conditions for parameters to belong to the identifi ed set. We then develop a quadratic programming algorithm that can be used to construct this set. With further restrictions on preferences, we show that our conditions are also sufficient for pairwise stability and therefore characterize the identifi ed set precisely. Overall, the use of both the economic model along with pairwise stability allows us to obtain effective dimension reduction.

This paper provides a framework for identifying preferences in a large network where links are pairwise stable. Network formation models present difficulties for identi fication, especially when links can be interdependent: e.g., when indirect connections matter. We show how one can use the observed proportions of various local network structures to learn about the underlying preference parameters. The key assumption for our approach restricts individuals to have bounded degree in equilibrium, implying a finite number of payoff-relevant local structures. Our main result provides necessary conditions for parameters to belong to the identified set. We then develop a quadratic programming algorithm that can be used to construct this set. With further restrictions on preferences, we show that our conditions are also sufficient for pairwise stability and therefore characterize the identified set precisely. Overall, the use of both the economic model along with pairwise stability allows us to obtain effective dimension reduction.

Few studies of the demographics, natural history, and clinical management of inclusion body myositis (IBM) have been performed in a large patient population. To more accurately define these characteristics, we developed and distributed a questionnaire to patients with IBM.A cross-sectional, self-reporting survey was conducted.The mean age of the 916 participants was 70.4 years, the male-to-female ratio was 2:1, and the majority reported difficulty with ambulation and activities of daily living. The earliest symptoms included impaired use and weakness of arms and legs. The mean time from first symptoms to diagnosis was 4.7 years. Half reported that IBM was their initial diagnosis. A composite functional index negatively associated with age and disease duration, and positively associated with participation in exercise.These data are valuable for informing patients how IBM manifestations are expected to impair daily living and indicate that self-reporting could be used to establish outcome measures in clinical trials.

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.

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.

The simultaneous growth in longevity and mounting budget deficits in the U.S. have increased interest in raising the age of eligibility for public health and retirement benefits. The consequences of this policy depend on the health of the near elderly, and on the distribution of health by demographic group. We simulate the work capacity and likely disability experience of near elderly individuals (62-64 year-olds) based on the work, disability, and retirement status of slightly younger people. Our estimates, from two distinct data sets, indicate that work capacity is substantial at this age. Because health deteriorates very slowly from ages 60-65, labor force participation could rise by 15-20 percent for all demographic groups, while overall disability rates would change very little. However, less advantaged groups would face challenges in the labor market. The expected earnings of current non-workers without any college education are lower than similar workers, by 15 to 25 percent, indicating the uneven burden of changes in the age of eligibility

Additional file 1. This file includes all supplemental data/tables referenced in the manuscript.

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.

Additional file 1. This file includes all supplemental data/tables referenced in the manuscript.

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.