`Author(s): Ernst R. Berndt, Linda Bui, David R. Reiley and Glen L. Urban
`Source: The American Economic Review, May, 1995, Vol. 85, No. 2, Papers and
`Proceedings of the Hundredth and Seventh Annual Meeting of the American Economic
`Association Washington, DC, January 6-8, 1995 (May, 1995), pp. 100-105
`Published by: American Economic Association
`
`
`
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`
` Information, Marketing, and Pricing
` in the U.S. Antiulcer Drug Market
`
` By ERNST R. BERNDT, LINDA Bui, DAVID R. REILEY, AND GLEN L. URBAN*
`
` Introduced into the United States in 1977,
` Tagamet was the pioneer product in the
` class of antiulcer drugs known as H2-
` antagonists. By promoting ulcer healing
` through inhibiting acid secretion, Tagamet
` was able to heal ulcers and treat pre-ulcer
` conditions pharmacologically on an outpa-
` tient basis, thereby substituting for more
` costly hospital admissions and surgeries. In
` 1983 another H2-antagonist called Zantac
` entered, and by early 1987 U.S. Zantac sales
` surpassed those of the pioneering Tagamet.
` Today there are four H2-antagonists sold in
` the United States: Tagamet, Zantac, Pep-
` cid, and Axid. Zantac is now the world's
` largest selling prescription drug, having esti-
` mated worldwide sales in 1994 of about $4
` billion. Each of the four H2-antagonists is
` among the top 100 in world drug sales,
` although Tagamet lost U.S. patent protec-
` tion on May 17, 1994.
` In this paper we examine empirically the
` role of information in facilitating and ex-
` plaining growth of the overall antiulcer drug
` market, as well as in shaping the changing
` market shares of the four patented prod-
` ucts. The dissemination of information is
` due largely to the use of marketing chan-
` nels, such as visits by manufacturers' repre-
` sentatives to physicians (called "detailing"),
`
` * Berndt: Sloan School of Management, Mas-
` sachusetts Institute of Technology, Cambridge, MA
` 02142; Bui: Department of Economics, Boston Univer-
` sity, 270 Bay State Road, Boston, MA 02215; Reiley:
` Department of Economics, Massachusetts Institute of
` Technology; Urban: Sloan School of Management,
` Massachusetts Institute of Technology. Financial sup-
` port from the Alfred P. Sloan Foundation is gratefully
` acknowledged, as is data support from Stephen C.
` Chappell of IMS International, J. Stanley Hull of Glaxo
` Pharmaceuticals, Ditas Riad of Merck & Co., and
` William Moore of Lowe & Partners/SMS. Any views
` and opinions expressed here are attributable only to
` the authors.
`
` 100
`
` advertising in medical journals, and most
` recently, by direct-to-consumer advertising.
` We examine these and also explore pricing
` policies, product differentiation, and order-
` of-entry effects.
`
` I. Background
`
` There are two cost conditions that have
` considerable bearing on the structure and
` behavior of the pharmaceutical industry.
` First, sunk costs are very large. In particu-
` lar, the costs of bringing a product to mar-
` ket (doing basic research, winning patent
` approval, engaging in development, per-
` forming clinical trials, and obtaining final
` approval from the Food and Drug Adminis-
` tration [FDA]) are currently estimated at
` about $360 million per drug. Second, for
` most traditional pharmaceutical products,
` the marginal costs of manufacturing are very
` small. Although appropriate cost data are
` not publicly available, it is not uncommon
` for generic drugs to sell at 25-30 percent of
` the pre-patent-expiration price. Informal
` discussions with industry officials suggest
` that for the H2-antagonists, production costs
` are about 10-25 percent of the price.
` These cost conditions have implications
` for pricing. Patent protection gives firms the
` ability to influence price, and to the extent
` one is willing to use the Lerner markup
` relation as a pricing rule of thumb, one
` would expect price and marginal-cost condi-
` tions to approximate (P - MC)/P = - 1/7p,
` where Ep is the demand price elasticity.
` With manufacturing costs at 10-25 percent
` of price (markups 75-90 percent), the im-
` plied demand price elasticity would range
` from - 1.1 to - 1.3. However, elasticities of
` that size contrast with the common percep-
` tion that demand for prescription drugs is
` extremely price inelastic. Peter Temin (1980
` Ch. 5), for example, notes that physicians
`
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` VOL. 85 NO. 2 INFORMATION, EDUCATING, AND MARKETING IN HEALTH CARE 101
`
` traditionally have been relatively unaware
` of drug prices. Other observers have sug-
` gested that moral hazard in the form of
` third-party (insurance) payment practices
` also contributes to low price responsiveness.
` Very little econometric evidence on demand
` elasticities for drugs is available, in part
` because the traditional consumer demand
` paradigm (utility maximization, marginal
` rates of substitution equal to relative
` marginal prices, etc.) cannot be expected to
` describe behavior adequately in a market in
` which principal-agent problems (stemming
` from relationships among physicians, pa-
` tients, and insurers) are widespread.1 In this
` paper we report elasticity estimates viewed
` from the vantage of the firm, not the "con-
` sumer"-whoever that may be.
` Since marginal production costs are small,
` enhancing revenues is essentially the same
` as increasing profits, and thus drug firms
` face strong incentives to shift out the de-
` mand curves. Thus it is not surprising that
` marketing-sales ratios are quite high in the
` pharmaceutical industry. The largest com-
` ponent (70-80 percent) of marketing has
` traditionally involved detailing to physi-
` cians; it consists of a company representa-
` tive providing as much product information
` as possible to physicians, given the typical
` short time of the visit (3-10 minutes) and
` the content regulation enforced by the FDA.
` Medical journal advertising is also carried
` out but is less extensive than detailing. Fi-
` nally, in the last few years, pharmaceutical
` companies have increasingly employed di-
` rect-to-consumer advertising in various
` media.
` The information content of marketing ef-
` forts deals primarily with product differen-
` tiation and nonprice aspects. In the H2-
` antagonists market, five quality attributes
` are of particular importance.2 First, the var-
` ious H 2-antagonists are viewed as being
` roughly similar in efficacy (the four- to six-
`
` week treatment healing rate is about 70-80
` percent for duodenal ulcer patients), al-
` though there is some evidence suggesting
` that Zantac has a significantly lower relapse
` rate than does- Tagamet for patients on duo-
` denal maintenance treated at recommended
` dosages (see K. R. Gough et al., 1984).
` Second, less frequent dosages are thought
` to enhance patient compliance. When Zan-
` tac entered the U.S. market in 1983, its
` twice-daily dosing frequency was considered
` more favorable than the regimen of four
` times a day recommended for Tagamet.
` Tagamet responded with a twice-a-day ver-
` sion in late 1984, after which considerable
` rivalry ensued; today all four H2-antagonists
` have a once-a-day version. A third quality
` attribute involves adverse interactions with
` other drugs. Here Tagamet has been on the
` defensive, for early on it was discovered
` that Tagamet interacted with the liver and
` kidney system in a way that could affect the
` metabolism of other drugs. As of 1994,
` Tagamet had reported to the FDA signifi-
` cant drug interactions with ten other drugs,
` whereas Zantac and Axid had only one re-
` ported drug interaction, and Pepcid had
` none. A fourth quality characteristic in-
` volves side effects. Here again Tagamet has
` been somewhat on the defensive, for condi-
` tions such as mental confusion in the el-
` derly and gynecomastia (breast swelling) for
` males are apparently not as prevalent with
` Zantac, Pepcid, and Axid. Finally, the four
` products compete in terms of medical con-
` ditions (indications) for which the FDA has
` granted treatment approval. Although
` Tagamet was the first to win approval for
` the treatment of duodenal ulcers, duodenal
` ulcer maintenance, and gastric ulcers, in
` 1986 Zantac was the first to obtain approval
` for gastroesophageal reflux disease
` (GERD), a rather common condition that
` ranges from modest heartburn and acid in-
` digestion to being a very serious condition.
` The FDA permits marketing only for ap-
` proved indications. Although Tagamet ob-
` tained FDA approval for GERD in 1991,
` and even though Tagamet had very similar
` effects to Zantac, suggesting that it would
` ISee, however, Michael Baye et al. (1994).
` likely also be effective in treating GERD,
` For more extensive discussion, see Berndt et al.
` not having FDA approval for GERD
` (1994).
`
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` 102 AEA PAPERS AND PROCEEDINGS MAY1995
`
` (whereas Zantac did) may have constituted
` a significant marketplace disadvantage for
` Tagamet.
` In terms of pricing, at entry Zantac was
` priced at an 80-percent premium over Taga-
` met, but by May 1994 this premium had
` gradually declined to 19 percent. In May
` 1994, the price per day's treatment (to drug
` stores) was $2.61 for Zantac, $2.56 for Axid,
` $2.30 for Tagamet, and $2.17 for Pepcid;
` quantity shares for the four products were
` 49 percent, 12 percent, 22 percent, and 17
` percent, respectively.
` To understand the roles of marketing,
` pricing, and quality attributes in explaining
` the growth and changing composition of the
` H2-antagonist market, we now outline an
` econometric model first for the H2-
` antagonist industry as a whole, and then for
` the market shares garnered by the four H2-
` antagonist drugs.
`
` II. An Econometric Model
` of the H2 -Antagonist Market
`
` At the industry level, we expect the quan-
` tity demanded (number of patient days of
` duodenal-ulcer therapy) to depend on price
` per treatment day, various marketing ef-
` forts, and quality attributes. Since market-
` ing efforts provide long-lived information, it
` is important that cumulative information
` stocks be distinguished from current-period
` new information flows. Define the cumula-
` tive marketing information stock St at end
` of month t as
`
` (1) St (l- )St_l+Ft
`
` t
`
` - E (1-a) FJ>
`
` T = o
`
` advertising (DCA).3 It is worth noting that
` the DCA efforts for H2-antagonists did not
` mention any drug by name, but only encour-
` aged viewers to seek advice from their
` physician if they experience heartburn and
` acid indigestion.
` Although such DCA advertising is plausi-
` bly intended to augment overall industry
` demand, when two or more products exist,
` marketing efforts are often only focused on
` a particular brand. During its monopoly era,
` Tagamet recouped all the benefits of its
` marketing efforts (it had 100 percent market
` share).4 However, once Zantac entered,
` even though rivalry between Tagamet and
` Zantac was intense, some of Tagamet's
` marketing efforts might have spilled over to
` the benefit of Zantac, and vice versa. Simi-
` larly, once Pepcid and Axid entered, while
` marketing efforts were typically focused on
` specific brands, spillovers to Zantac and
` Tagamet might have occurred. To allow for
` marketing spillovers affecting industry
` (rather than just product-specific) demand,
` we define the effective industry marketing
` stock S* as a weighted sum of the market-
` ing information stocks originally formed in
` various market structures:
`
` (2) S* = t1SS1t + A2S2t + A3S3t + A4S4t
`
` where S1t is the surviving marketing infor-
` mation stock at end of month t that origi-
` nally accumulated in the Tagamet monopoly
` era, S2t is the similar stock formed during
` the Tagamet-Zantac duopoly, S3t is that
` from the Tagamet-Zantac-Pepcid triopoly,
` and S4t is that from the Tagamet-Zantac-
` Pepcid-Axid rivalry. Since in a monopoly all
` marketing efforts affect industry demand,
`
` where Ft is the flow of new marketing infor-
` 3Target rating points are defined as the target reach
` (the percentage of the over-age-35 population who
` mation efforts during month t, and a is the
` view the message over the course of the ad campaign)
` monthly depreciation rate. Since 8 is un-
` times the frequency, where frequency is the number of
` known, we estimate it econometrically. In
` times the average target individual views the message.
` terms of marketing efforts, we distinguish
` For further discussion, see Philip Kotler (1991 pp.
` 606-8). The proprietary DCA data were kindly pro-
` three channels: the minutes of detailing to
` vided us by Lowe & Partners/SMS in cooperation with
` physicians (DET), the number of pages of
` Glaxo, Inc.
` medical-journal advertising (PJL), and the
` 4The discussion that follows is based in large part
` target rating points of direct-to-consumer
` on Berndt et al. (1994).
`
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`
` VOL.85 NO. 2 INFORMATION, EDUCATING, AND MARKETING INHEALTH CARE 103
`
` pages marketing stocks, LNDTJ1 and
` we normalize the IL's by setting A 1 = 1.
` Several interesting hypotheses involve the
` LNJPJ1; the number of adverse drug inter-
` ,u's. First, if the effectiveness of firms' mar-
` actions for product j relative to Tagamet,
` keting on industry sales is independent of
` LNINTJ1;6 a discrete variable, DSGERD,
` market structure, then u2 = 3 = 4 = 1"
` indicating whether product j has a GERD
` Second, if in the presence of competition
` indication advantage relative to Tagamet (1,
` marketing efforts only affect market shares
` advantage; 0, no advantage; - 1, disadvan-
` and have a zero-sum impact on industry
` tage); an order-of-entry variable, ENTRY,
` demand, then A2 = A= =A4 =0. Finally, if
` taking on the value of 2 for all Zantac
` the industry sales-augmenting effects of
` observations, 3 for Pepcid, and 4 for Axid;
` firms' marketing decline as the number of
` and an AGE variable indicating the number
` products in the industry increases, then 1 >
` of months product j has been in the mar-
` ketplace. Again, an instrumental-variable
` f2 > A3 > A4 > 0.
` For our industry demand equation, we
` procedure is employed to allow for simul-
` specify a log-log model, where Q. is quan-
` taneity.
` Our data sources are described more fully
` tity, P, is CPI-defiated price, DET,*, PJL*,
` and DCA* are the effective industry stocks
` in Berndt et al. (1994).7 The direct-to-con-
` defined in (1) and (2), and DGERD is a
` sumer marketing data are for a campaign
` begun by Glaxo (the manufacturer of Zan-
` dummy variable taking on the value of 1
` following FDA approval for GERD:
` tac) in June 1992, and they extend through
` May 1994.
`
` (3) LNQt = p30 + f31LNPt + 132LNDETt*
`
` III. Econometric Results
`
` + 35DGERDt + Et.
`
` +,83LNPJL*t +,(34LNDCAt
`
` Based on 201 monthly observations from
` September 1977 through May 1994, we esti-
` mated parameters of equation (3) for the
` industry using NL-2SLS. To be parsimo-
` nious in parameters, we constrained the ,'s
` Since the effective industry marketing stocks
` and S's to be the same for the DET and
` depend nonlinearly on the ,u's and 8's, and
` PJL marketing stocks, but allowed a to dif-
` since marketing efforts, pricing, and quan-
` fer for DCA. The preferred model was cho-
` tity demanded are likely to be jointly deter-
` sen based on the lowest value of the tradi-
` mined (see Richard Schmalensee 1972), we
` tional NL-2SLS residual criterion function.
` Our estimated H 2-antagonist industry
` estimate parameters in equation (3) by non-
` price elasticity is - 0.689 (t = 3.80), while
` linear two-stage least squares (NL-2SLS).5
` elasticity estimates for the DET, PJL, and
` Our econometric model of market shares
` DCA surviving stocks are 0.553 (t = 7.52),
` follows Urban et al. (1986) in specifying
` 0.198 (t = 2.79) and 0.008 (t = 2.67).8 Hence,
` variables relative to the incumbent (Taga-
` met). In particular, using a log-log frame-
` industry demand is positively affected by all
` three of the firms' marketing channels, but
` work, we specify that in month t, demand
` DET is most effective; the sum of the three
` quantities of product j relative to the in-
` marketing elasticities is 0.759, suggesting
` cumbent [ln(Qj/Q1) LNQJ1, j = Zantac,
` decreasing returns to scale. In terms of
` Pepcid, Axid] depend on: relative prices,
` LNPRJ1; relative detailing and journal-
`
` 5As instruments, we employ the producer price in-
` dex for intermediate goods, production worker wages
` in the pharmaceutical industry, cumulative marketing
` efforts by the four companies on non-H2-antagonist
` products for each of the three instruments, and time.
`
` 6To accommodate zeros, 1.0 is added to both the
` DCA and the INT variables.
` 7Here we extend the Berndt et al. (1994) data base
` to May 1994. Data on prices, quantities, detailing, and
` journal pages are from IMS International.
` 8The equation R2 is 0.995, and the Durbin-Watson
` statistic is 1.912.
`
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` 104 AEA PAPERS AND PROCEEDINGS MAY 1995
`
` mated monthly depreciation rate for the
` spillovers, the estimates of A2, /3, and /4
` are 0.601 (t = 6.59), 0.924 (t = 5.30), and
` DET and PJL stocks is 0.030 (t = 13.77),
` implying that relative information market-
` 0.410 (t = 4.00); these A's are jointly signif-
` icantly different from 1, and from zero, indi-
` ing stocks deteriorate at about 30 percent
` cating that marketing spillovers occur and
` per year. With respect to quality variables,
` that the effectiveness of firms' marketing
` the DSGERD coefficient is 0.05, while that
` efforts on industry sales depends on market
` on relative adverse drug interactions is
` structure. The extent to which spillovers
` - 0.25, suggesting that Tagamet's market
` occur, however, does not decline monotoni-
` share was significantly negatively affected by
` cally with the number of products in the
` its disadvantages in terms of GERD and
` market. The DGERD dummy variable co-
` adverse drug interactions in the H2-
` efficient is 0.104 (t = 3.20), indicating that
` antagonist market. Finally, the age coeffi-
` FDA approval for GERD increased the size
` cient is positive and significant, implying
` of the H2-antagonist market by about 10
` that, ceteris paribus, longevity in the mar-
` percent. Finally, the NL-2SLS criterion
` ketplace positively affects market shares.9
` function is optimized at the point where 6
` for the DET and PJL stocks is 0.00, while
` that for the DCA stock is 0.15 (t = 0.20),
` implying an annual DCA deterioration rate
` of about 80 percent. Although we are some-
` what surprised that the information stocks
` of DCA and PJL marketing do not depreci-
` ate at all, we note that a similar 8 = 0
` finding in the context of R&D knowledge
` stocks has been reported by Zvi Griliches
` and Frank Lichtenberg (1984).
` Turning now to econometric results based
` on the market-share model, we obtained the
` following NL-2SLS results, based on 291
` monthly observations:
`
` IV. Concluding Remarks
`
` LNQJ1 t -0.427 ENTRY - 0.667 LNPRJ1
` (44.00) (8.95)
`
` We have reported results on factors af-
` fecting the growth and composition of the
` H 2-antagonist drug market. With an H2-
` antagonist industry own-price elasticity of
` -0.69 and between-drug price elasticities
` of -0.66, the implicit brand-specific own-
` price elasticities in May 1994 are - 0.80 for
` Tagamet (SE = 0.08), - 1.03 (SE = 0.12) for
` Zantac, - 0.76 (SE = 0.08) for Pepcid, and
` -0.74 (SE = 0.08) for Axid. Except for
` Zantac, these elasticity estimates are still
` slightly smaller than the - 1.1 to - 1.3 val-
` ues one might expect based on the Lerner
` markup rule of thumb; nevertheless they
` are not far from 1, and clearly differ from 0.
` It is worth noting that when marketing vari-
` ables are omitted from the relative-demand
` + 0.649LNDTJ1, + 0.167LNJPJ1
` equations, price-elasticity estimates fall to
` (19.77) (6.31)
` about half these values.
` We find that marketing information stocks
` positively affect sales, that the sales elastic-
` ity is largest for detailing, followed by jour-
` nal pages of advertising, and is smallest for
` direct-to-consumer advertising. Marketing
` information appears to display overall de-
` creasing returns to scale. We also find that
`
` + 0.052DSGERD, - 0.252LNINTJ1
` (2.17) (9.00)
`
` + 0.010AGE
` (16.65)
`
` with an R2 of 0.983. Order-of-entry effects
` are negative and strong, implying significant
` first-mover advantages, consistent with evi-
` dence from other markets (see Urban et al.,
` 1986). The within-H2-antagonist price-elas-
` ticity estimate is - 0.67 and significant, while
` coefficients on relative stocks of detailing
` (0.649) and journal pages of advertising
` (0.167) are positive and significant. The esti-
`
` Although DCA is arguably intended to affect indus-
` try demand rather than market shares, when the DCA
` information variable is added, shares of Tagamet and
` Axid were positively affected relative to those of Zan-
` tac and Pepcid.
`
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` VOL. 85 NO. 2 INFORMATION, EDUCATING, AND MARKETING IN HEALTH CARE 105
`
` order-of-entry effects are significant, as are
` quality attributes.
`
` REFERENCES
`
` Baye, Michael R.; Maness, Robert and Wiggins,
` Steven N. "Demand Systems and the 'True'
` Cost of Living for Pharmaceuticals."
` Working paper, Department of Eco-
` nomics, Texas A&M University, May
` 1994.
` Berndt, Ernst R.; Bui, Linda; Reiley, David and
` Urban, Glen. "The Roles of Marketing,
` Product Quality and Price Competition in
` the Growth and Composition of the U.S.
` Anti-Ulcer Drug Industry." National Bu-
` reau of Economic Research (Cambridge,
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