The impact of insurer competition on welfare, negotiated provider prices, and premiums in the U.S. private health care industry is theoretically ambiguous. Reduced competition may increase the premiums charged by insurers and their payments made to hospitals. However, it may also strengthen insurers' bargaining leverage when negotiating with hospitals, thereby generating offsetting cost decreases. To understand and measure this trade-off, we estimate a model of employer-insurer and hospital-insurer bargaining over premiums and reimbursements, household demand for insurance, and individual demand for hospitals using detailed California admissions, claims, and enrollment data. We simulate the removal of both large and small insurers from consumers' choice sets. Although consumer welfare decreases and premiums typically increase, we find that premiums can fall upon the removal of a small insurer if an employer imposes effective premium constraints through negotiations with the remaining insurers. We also document substantial heterogeneity in hospital price adjustments upon the removal of an insurer, with renegotiated price increases and decreases of as much as 10% across markets.1 insights are relevant not only when employers change insurance plan menus offered to employees, but also when insurers merge, and when they enter or exit markets.One of this paper's primary contributions is identifying and quantifying the mechanisms by which insurer competition affects negotiated hospital prices in equilibrium. If reducing insurer competition raises premiums via an increase in the remaining insurers' market power, there may be an upward pressure on negotiated prices as hospitals capture part of the increased industry surplus. 4However, there are offsetting effects that arise if insurers consequently have greater bargaining leverage. This can occur if an insurer loses fewer enrollees to a rival insurer upon disagreement with a hospital and if a hospital "recaptures" fewer enrollees through a rival insurer upon disagreement with an insurer. If substantial, these additional effects-variants of countervailing power (Galbraith, 1952)-imply that greater downstream concentration can reduce total hospital payments.Previous papers have examined the relationship between market concentration and medical provider prices, often within a regression framework (c.f. Gaynor and Town, 2012;Gaynor, Ho and Town, 2015). 5 We build on this literature by imposing structure derived from a theoretical model of competition in health care markets in order to uncover heterogeneous responses across firms and markets and conduct counterfactual simulations. Our approach is also related to Gowrisankaran, Nevo and Town (2015) who use a structural model of hospital-insurer bargaining to estimate the impact of hospital mergers on negotiated prices. 6 Our contributions include estimating a model of insurer competition for households in our empirical analysis and incorporating employer bargaining over premiums with insurers. 7 Capturing these interactions is...

The U.S. health-care sector is large and growing—health-care spending in 2011 amounted to $2.7 trillion and 18 percent of GDP. Approximately half of health-care output is allocated via markets. In this paper, we analyze the industrial organization literature on health-care markets, focusing on the impact of competition on price, quality, and treatment decisions for health-care providers and health insurers. We conclude with a discussion of research opportunities for industrial organization economists, including opportunities created by the U.S. Patient Protection and Affordable Care Act. (JEL J15, J24, J71, J81, K31)

This paper provides conditions under which the inequality constraints generated by either single agent optimizing behavior or the best response condition of multiple agent problems can be used as a basis for estimation and inference. An application illustrates how the use of these inequality constraints can simplify the analysis of complex behavioral models. 316 PAKES, PORTER, HO, AND ISHII ferences is distinct from the expected profit difference expressed in the best response assumption. One source of (unobserved) error comes from the difference between the actual returns and the econometrician's measure of returns. The other source of error comes from observing information on realized, rather than expected, returns. The expectational error and possibly part of the approximation error will be mean independent of the agent's information set (and hence of the choice itself). However there may be a component of the agent's perceived difference in expected profits that the econometrician does not control for, and is both a part of the approximation error and a determinant of the choice made. We call this component the structural disturbance.When we can measure profits up to a mean zero measurement error, then there is no structural disturbance. In this case, the proposed identification and estimation algorithm is particularly simple and powerful. When the structural disturbance is nonzero, then a classic selection problem arises. The structural disturbance associated with the observed choice will necessarily come from the possible values that make the observed choice best. As a result, even if the a priori mean of the structural disturbances for any fixed choice is zero, the mean of the structural disturbance corresponding to the returns from the observed choice can be nonzero. To deal with this possibility, we propose a condition that can viewed as generalizing an instrumental variables approach to this inequality setting. The formal assumption provides a "high level" sufficient condition for dealing with selection, and we show a number of ways to satisfy this condition in particular examples. The paper closes with an empirical example: estimating the costs of a nonconvex (or lumpy) investment choice by banks. The example illustrates ways to circumvent problems posed by the structural error in models with and without boundary conditions. The detailed policy implications of the estimates are discussed in Ishii (2004).When there is no structural disturbance the proposed framework is a natural extension of the first-order condition estimator for single agent dynamic problems proposed in Hansen and Singleton (1982), and extended to allow for transaction costs and, hence, inequalities, by Luttmer (1996). Our generalization allows for arbitrary (including discrete) choice sets and interacting agents. Ciliberto and Tamer (2009) provide alternative methods for estimating models with discrete choice sets and interacting agents that only allows for the structural error. The two approaches are not nested, and Pakes (2010) pro...

The impact of insurer competition on welfare, negotiated provider prices, and premiums in the U.S. private health care industry is theoretically ambiguous. Reduced competition may increase the premiums charged by insurers and their payments made to hospitals. However, it may also strengthen insurers' bargaining leverage when negotiating with hospitals, thereby generating offsetting cost decreases. To understand and measure this trade‐off, we estimate a model of employer‐insurer and hospital‐insurer bargaining over premiums and reimbursements, household demand for insurance, and individual demand for hospitals using detailed California admissions, claims, and enrollment data. We simulate the removal of both large and small insurers from consumers' choice sets. Although consumer welfare decreases and premiums typically increase, we find that premiums can fall upon the removal of a small insurer if an employer imposes effective premium constraints through negotiations with the remaining insurers. We also document substantial heterogeneity in hospital price adjustments upon the removal of an insurer, with renegotiated price increases and decreases of as much as 10% across markets.