Assessing consumer gains from a drug price control policy in the United States.

• Author: Santerre, Rexford E.

We use national data from 1960 to 2000 to estimate the demand for pharmaceuticals in the United States. We then simulate consumer surplus gains from a hypothetical drug price control policy that would have limited drug price increases to the rate of inflation from 1981 to 2000. Using a range of values for the real interest rate, coinsurance rate, and own-price elasticity of demand, we find that the consumer surplus gains from this policy equal $472 billion by the end of 2000. According to a recent study, that same policy would have led to 198 fewer new drugs being brought to the U.S. market. Therefore, the average social opportunity cost per drug developed during this period was approximately $2.4 billion. Research on the value of pharmaceuticals suggests that the social benefits of a new drug are far greater than this estimate. Hence, drug price controls could do more harm than good.

JEL Classification: D12, I11, I18, K2, L5

1. Introduction

   The on-going public debate over prescription drug prices represents one of the most contentious issues in the history of U.S. health care politics. The commonly held perception that U.S. drug prices are "too high" has been fueled by the fact that real drug prices in the United States have been rising steadily and at a rate faster than that of the general consumer price index for over two decades. As a result, the pharmaceutical industry has come under intense criticism, with both politicians and special interest groups calling for new legislation making pharmaceuticals more affordable, either through legalized reimportation from price-regulated markets such as Canada and the European Union, or more directly through government-imposed price controls.

   Although these calls for legislative action are not new, the United States does appear to be, for the first time, very close to a major policy change regarding U.S. drug prices. (1) The U.S. government might, like all other industrialized governments around the world, soon begin regulating drug prices. (2) In addition to several reimportation bills currently on the Senate floor, proposed amendments to the recently passed Medicare Modernization Act of 2003 (MMA) also exist that will allow the U.S. government to negotiate directly with drug manufacturers for Medicare prescription drug purchases (the MMA currently has a noninterference clause), which will amount to approximately 60% of all U.S. drug purchases (Santerre, Vernon, and Giaccotto 2006).

   Although regulated drug prices in the United States will undoubtedly improve the public's access to today's medicines, and thus generate both cost savings and improved public health, it will simultaneously reduce firms' incentives to invest in pharmaceutical research and development (R&D) because of lower levels of pharmaceutical profitability. Less investment in pharmaceutical R&D will have a negative effect on the rate of future pharmaceutical innovation. Recent research has documented the considerable benefits of pharmaceutical innovation in terms of improved longevity (Lichtenberg 2002; Miller and Frech 2002), as well as the sensitivity of R&D investment to real pharmaceutical prices (Giaccotto, Santerre, and Vernon 2005) and profits (Vernon 2004). Thus, in addition to the short-run benefits associated with lower regulated drug prices, long-run costs also arise. This is precisely the tradeoff the U.S. patent system tries to balance by awarding limited-term patents to new drug products.

   Even though a policy of regulated drug prices in the United States involves a tradeoff between short-run benefits and long-run costs, the former outcome often receives more attention in policy debates (Scherer 2004). Interestingly, however, efforts to quantify these short-run benefits from a rigorous economic perspective are nonexistent. Therefore, in this article, we attempt to do just that. We also compare our findings with the results from an earlier study by Giaccotto, Santerre, and Vernon (2005)--one that employed the same data and modeling techniques but that measured the economic costs of the same U.S. price control policy--in terms of reduced levels of pharmaceutical innovation. Thus, we are able to weigh the benefits of pharmaceutical price controls (in terms of consumer surplus gains) against the costs (measured in terms of forgone drug discoveries). Although these studies are retrospective in nature (out of necessity), and consider only one type of U.S. price control policy (one that requires pharmaceutical prices grow no faster than the consumer price index), the price control policy simulated is, nevertheless, similar to an actual policy enacted in 1992 for drugs purchased by the government for the Veterans Administration (VA) health system. Moreover, and for the first time, a formal cost-benefit analysis of a particular type of drug price control is possible, and this could offer new insights.

   Our paper proceeds as follows. In section 2 we construct an empirical model of the aggregate consumer demand for pharmaceuticals in the United States. We also outline our empirical strategy and describe the data. Section 3 reports and discusses our empirical estimates. In section 4 we simulate the consumer surplus gains from a hypothetical price control policy in the United States: one that limits the growth rate of pharmaceutical prices to that of the consumer price index from 1981 to 2000. We then assess the net benefit of this policy by comparing the gains of consumer surplus to some fairly plausible estimates of the value of the R&D (and drugs) that would be lost had the policy been enacted. Section 5 provides a summary and offers some conclusions.

2. Conceptual and Empirical Models of the Aggregate Consumer Demand for Pharmaceutical Products

   We begin by assuming a one-period model in which a representative consumer, given her exogenous tastes and preferences, t, derives utility from consuming the units of "health services," s, that flow from her health capital, h, and some composite good, x. Stated mathematically:

   U = U(s, x;t). (1)

   We also make the following standard assumptions about the individual's utility function:

   [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.]

   That is, utility is assumed to increase at a decreasing rate with respect to both health services and the composite good. We further assume that health services are produced with various combinations of prescription drugs, q (e.g., dosages), and medical services, m (such as office visits or inpatient days), conditioned on the representative consumer's initial endowment of health capital, [h.sub.0]. Thus, for ease of exposition, we ignore a set of other health care "goods" and "bads" such as exercise, diet, alcohol and tobacco use, etc., and the consumer's time involved in producing these health care activities. (3) A production function for units of health services can thus be written as

   s = s(q, m; [h.sub.0]), (2)

   where s is assumed to be concave with respect to both q and m.

   Substituting Equation 2 into Equation 1 allows utility to be expressed in terms of the production function for health services and the composite good. It is assumed that expenditures on the two inputs that produce health services, and spending on the composite good, fully exhaust the consumer's income net of insurance premiums, y. The consumer's optimization problem is, therefore, to select the amounts of prescription drugs and medical services and the composite good that maximize her utility subject to the constraints of net income and the out-of-pocket prices for drugs, [P.sub.O]; medical services, [P.sub.M]; and the composite good, [P.sub.X]. Stated more formally, (4)

   Maximize U = U[s(q,m;[h.sub.0]),x;t] s.t. q[P.sub.O] + m[P.sub.M] + x[P.sub.X] = y.

   Use of the method of Lagrange multipliers to find the solution to this constrained optimization problem generates the familiar first-order conditions. Using the first-order conditions, we can solve for the marginal rate of substitution between drugs and the composite good:

   [[[differential]U]/[[differential]s]] x [[[differential]s]/[[differential]q]] [[[[differential]U]/[[differential]x]].sup.-1] = [P.sub.O]/[P.sub.X] (3)

   The first partial derivative in the leftmost bracket captures the marginal utility of good health, whereas the second reflects the marginal productivity of drugs on good health. Equation 3 implies that, in equilibrium, the representative consumer equates the marginal benefit of the last drug consumed with its marginal cost, as reflected by the relative out-of-pocket price of an additional drug.

   For purposes later in the article, it is important to consider here that the marginal benefit of an additional drug dosage is influenced by both the value that the consumer places on being in a state of good health and the marginal product of an additional drug on good health. As a result, the price paid for an additional drug in the marketplace captures the consumer's willingness to pay for a small reduction in the probability of dying, a marginal improvement in her quality of life, or both. This notion becomes particularly important when we use the demand curve to estimate the consumer surplus from a drug price control regime. That is, consumer surplus captures the value of life and the marginal contribution of an additional drug to good health.

   Defining x as the numeraire, it also follows from the utility maximization process that the representative consumer's quantity demanded of prescription drugs can be derived as a function of the relative out-of-pocket drug price, relative out-of-pocket medical price, and her real net income. Expressed generally, the demand function takes the form in Equation 4.

   q = q([P.sub.O]/[P.sub.X], [P.sub.M]/[P.sub.X], Y/[P.sub.X]; t, [h.sub.0]). (4)

   Horizontally aggregating across all consumers, and assuming that the aggregate consumer demand for prescription drugs can be written in log-log form for estimation purposes, the result shown in Equation 5...