Wealth Effect of Drug Withdrawals on Firms and their Competitors

Parvez Ahmed*, 1

John Gardella, MD** Sudhir Nanda*

* Assistant Professor of Finance, School of Business Administration, Pennsylvania State University, Harrisburg. ** Clinical Director, Presbyterian Hospital - Matthews, NC. 1Please direct all correspondence to: Parvez Ahmed Penn State Harrisburg School of Business Administration Middletown, PA 17057-4898. Voice: (717) 948-6162, Fax: (717) 948-6456 email: pahmed@psu.edu

Wealth Effect of Drug Withdrawals on Firms and their Competitors

ABSTRACT

This paper studies the impact of drug withdrawals on shareholder wealth of producers and

competitors. Results show that the wealth loss is conditional on the information content of the

news of a drug withdrawal. Firms withdrawing drugs during advanced clinical investigations

suffer a larger wealth loss than withdrawals during post-marketing surveillance. The wealth loss

is inversely related to the market capitalization and is smaller in case multiple firms withdraw the

same type of drug. Moreover, reports of adverse drug reactions that sometimes precede the

eventual withdrawal of a drug lead to significant loss in shareholder wealth. Finally,

shareholders of the direct competitors gain only during the five-day post-event period.

JEL Classification: G3 Keywords: Product Recall, Product Withdrawal, Competitors, Event Study

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Wealth Effect of Drug Withdrawals on Firms and their Competitors

The news of a product recall usually receives considerable market attention. Following

the news of the withdrawal of Firestone tires in August 2000, Bridgestone (parent of Firestone)

lost over 45% of its stock value.1 For pharmaceutical drugs, the high public scrutiny is usually

not just limited to issues of safety but extends to the effectiveness of the products. Previous

studies on recalls and withdrawals of products present conflicting evidence. Hoffer, Pruitt, and

Reilly (1988), and Bromiley and Marcus (1989) report insignificant wealth losses, while Pruitt

and Peterson (1986) show a significant decline in shareholder wealth around a product recall.

This paper focuses on the wealth effects of drug withdrawals. There are meaningful economic

differences between a product recall and a withdrawal. A recalled product is likely to be

reintroduced after some modifications. In contrast, a withdrawn product results in the

elimination of a revenue source since most products are never reintroduced. The loss in expected

cash flows should be higher for withdrawals than recalls. Davidson and Worrell (1992) show a

higher loss in shareholder wealth for product withdrawals than for product recalls.2 Thus,

limiting the study to drug withdrawals alone makes the sample more homogeneous and limits the

confounding of wealth effects.

Jarrell and Peltzman (1985), using a sample of drug recalls (such as recall of Tylenol to

fix tampering of packages) and drug withdrawals (such as withdrawal of MER-29, a cholesterol

reducer, linked to blindness and baldness), find significant shareholder wealth losses around the

1 Additionally, with 88 deaths attributed to the defective tires, the firm faces a plethora of product liability damages and possibility of bankruptcy. Source: Atlanta Constitution Journal, September 1, 2000. 2 Their study suffers from a very small sample size (27) and does not control for the type of product being withdrawn. The revenue loss from the withdrawal of an electric appliance or a toy will be much lower than that from a medical drug. This is mainly for two reasons - higher R&D cost for drugs and each drug being a large proportion of overall firm sales.

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announcements. In contrast, Dranove and Olsen (1994) find significant but lower shareholder

wealth losses around the announcement of drug withdrawals only. Both studies span a very

small period of time primarily in the 1970s and early 1980s. The sample of drug withdrawals

does not exceed five in either study, which limits generalization of their results.

This study examines the wealth effects of drug withdrawals from 1966-1998. The longer

time period and a larger sample allow us to make more generalized inferences on the extent of

wealth losses from drug withdrawals. The larger sample also allows tests on subsamples

stratified by the information content of the news of a drug withdrawal. Specifically, this study

examines the impact of the following; (i) availability of substitutes for withdrawn drug, (ii)

simultaneous withdrawal of a class of drugs by multiple firms versus a withdrawal affecting only

one firm, (iii) reason for the withdrawal, and (iv) stage of drug withdrawal. Additionally, the

study examines wealth effects from unintended but severe side effects know as adverse drug

reactions (ADR). In instances where a drug withdrawal is preceded by an ADR, the total wealth

loss is the sum of wealth losses at the announcement of the ADR and the eventual withdrawal.

Finally, the study examines wealth effects for direct competitors of firms withdrawing drug.

The results show that stockholders of drug producers incur substantial losses at the time

of a drug withdrawal. The losses are higher in cases in which a drug has no available substitute.

Losses are also higher in instances when a single firm was required to withdraw a drug as

compared to the simultaneous withdrawal of a class of drugs by multiple producers. Withdrawal

of drugs that caused deaths or severe medical side effects resulted in higher wealth losses than

withdrawals resulting from ineffectiveness of the drug. However, the impact of cause of

withdrawal was subsumed by the other variables in multivariate tests. Smaller firms suffered

significantly higher losses than the large well diversified firms. Additionally, firms withdrawing

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drugs during post-marketing surveillance suffered lower wealth losses. This study also finds

significant negative returns at the announcement of adverse drug reactions (ADRs). The results

for a matched sample of ADRs and corresponding withdrawals suggest that the previous studies,

which examine only withdrawals, understate losses to the firm. Finally, competitors do not gain

in the event period, but show significant positive returns in the five-day post-event period.

The rest of the paper is organized as follows. In Section I we provide the context for this

study from recent events, discuss the literature, and issues examined in this paper. Section II

describes the data and the event study methodology. Section III presents the empirical results

and discusses their implications. Finally, Section IV provides some concluding remarks.

I. Discussion and Research Issues

The safety of consumer products in the United States is ensured through a combination of

ex-ante and ex-post regulation (Marino, 1997). Ex-ante, products are required to meet minimum

safety standards, and ex-post their safety is monitored by various regulatory agencies. In

addition to random ex-post audits, producers may be liable for any significant harm from the use

of their products. The Food and Drug Administration (FDA) approves the marketing of all

pharmaceuticals and monitors their safety. Figure 1 provides a schematic overview of the

process of drug development, approval, and post-marketing monitoring. The FDA has the

power, vested in it by the United States Congress, to order the withdrawal of a drug that causes

any harmful side effects or is ineffective.3

The withdrawal of a product involves direct and indirect costs. Direct costs are easily

measurable as they arise from the cost of fixing a defect and loss in future revenue. The

3 Welling (1991) asserts that a ‘social planner’ such as the FDA, will issue a recall announcement if the social benefit from the recall exceeds the total cost.

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permanent loss in revenue results in higher direct costs for product withdrawals than for product

recalls. Indirect costs are more difficult to determine, as they are usually attributable to loss in

goodwill or reputation. The loss of goodwill or social reputation can affect a firm's sales

(Hersch, 1991). Consumers, employees or suppliers may also punish a firm for its failure to

honor their implicit contracts. Such punitive measures impact future cash flows and in turn

affect current share prices.

Dowdell, Govindraj, and Jain (1992) show that following the much publicized Tylenol

poisoning incident in 1982, Johnson and Johnson (JNJ), the makers of Tylenol, lost 29% or

$2.31 billion in shareholder wealth. Recent stories on some drug withdrawals provide an

illustration of the context of this study and how the information content results in different

market reactions. On May 20, 2000 The Wall Street Journal reported the withdrawal of the drug

Vanlev during advanced clinical trials by Bristol Myers Squibb (BMS). At the time of this

announcement, BMS stock fell by 23% leading to a total wealth loss of approximately $30

billion. Similarly, Johnson and Johnson lost 11% or approximately $10 billion of its market

value following its decision to stop the marketing of Propulsid, which was linked to several cases

of patient death and irregular heartbeats. Such large losses in shareholder wealth seem to go

beyond any reasonable direct costs of recall or expected losses in direct future revenue. The

expected revenue from a moderately successful drug is currently $66 million per year (Kellogg

and Charnes, 2000).4 Dowdell et al. (1992), Rubin et al. (1988), and Jarell and Peltzman (1985)

attribute such perplexingly high wealth losses from catastrophic events to lower expected future

cash flows due to a loss in goodwill.

4 A marketed drug has a 60% chance of being of average quality and it takes a drug two years to reach its peak revenue. Assuming a profit margin of 25%, the net present value of an average drug is approximately $110 million if the cash flows are assumed to be perpetual and are discounted at 15%. Only 8% of all drugs launched reach annual sales of $350 million (Sauer, 1998).

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Warner Lambert's share price declined by only 2% around the withdrawal of Rezulin.

While this loss is lower than in the previous examples, the total loss over all previously reported

ADRs (Rezulin was linked to 63 deaths over the previous three years) and the subsequent

withdrawal is close to the losses sustained by other drug manufacturers. Additionally, media

reports indicated that the withdrawal of Rezulin might help Warner's competitor Eli Lilly by

boosting its revenues by "hundreds of millions of dollars" from the sale of a competing drug

called Actos (Swiatek, 2000).

Negative publicity or withdrawal of a product can have a 'positive spillover' effect on

direct competitors (those with available substitute products) by improving their market share or

reputation or both. Bosch, Eckard and Singal (1998) report a 'negative spillover' effect on

competitors in the period surrounding an airline crash. They suggest that stakeholders, such as

consumers and insurers, out of concern for the overall efficacy of air safety exact a price for this

negative sentiment. However, the wealth effects for direct competitors will be positive if the

gain in market share outweighs any concern for the systemic safety of pharmaceutical drugs.

The previous examples illustrate the rich information content in each news release, which

causes the market to react differently in each circumstance. The impact of the information

content of the news is studied by stratifying the sample. The producers of drugs without

substitutes are likely to suffer a greater loss in shareholder wealth than producers marketing

drugs with available substitutes. This is mainly because drugs without substitutes enjoy a

monopoly for a number of years, which allows them to earn higher returns.

The FDA sometimes instructs multiple producers to simultaneously withdraw a class of

drugs, such as antibiotics in the 1970s.5 On finding a health risk from a certain chemical

5 On the other hand, after the antihistamine Terfenadine (Seldane) was found to have potentially fatal side effects, its removal action did not restrict the sale of other antihistamines

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compound, all drugs containing the compound in question are ordered withdrawn. When

multiple firms withdraw similar drugs, no firm gains a competitive advantage and market shares

are likely to remain approximately the same following a withdrawal. Additionally, being

identical in chemical composition, these drugs are likely to be priced competitively resulting in

lower loss in expected revenues and profits. Thus, withdrawals by multiple producers should be

accompanied by lower wealth losses than those experienced by a single producer withdrawing a

drug.

As firms are expected to deliver safe products, deaths caused by drugs result in a

significant violation of implicit contracts, and increase the probability of lawsuits. The violation

of implicit contracts can also lead to the institution of costly procedures by stakeholders for

monitoring of their implicit contracts (Hersch, 1991). The additional costs from litigation and

the accompanying negative publicity can lead to higher losses in shareholder wealth.6

New pharmaceutical firms usually have few products. Being small, any single drug

would constitute a large proportion of overall cash flows for such firms. The withdrawal of such

drugs is expected to cause a more severe wealth loss than for large well-diversified firms.

Finally, the stage of a drug withdrawal can also have an impact on the level of abnormal return.

Given the high probability of success (66%) at Phase 3 and beyond, failure at the clinical trial

level is a severe disappointment to investors. Additionally, drugs withdrawn during post-

marketing surveillance should suffer a lower loss in net present value. Since the drug was

already producing some revenue the firm had a chance to recover some cost of development.7

6 "Warner Lambert was facing the possibility of litigation from people who suspect their use of Rezulin led to severe liver damage for themselves, or the death of family members" - March 22, 2000, AFX News Limited. 7 According to FDA's Center for Drug Evaluation and Research, the average R&D cost for a drug before being submitted for clinical trials is over $300 million.

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Even before the withdrawal of a drug, major newspapers frequently report safety and

side-effect problems associated with its use. The recently instituted MedWatch program of the

FDA (reported on the FDA website) provides a list of such adverse drug reactions (ADR).8 An

ADR does not alter any explicit contracts nor does it affect a firm's ability to deliver the final

product. Thus, the news of an ADR will primarily affect a firm’s reputation or goodwill.9 In

instances where an ADR does lead to the withdrawal of a drug, the total wealth loss is the

cumulative loss from all preceding adverse drug reactions and the actual withdrawal.

Additionally, this study tests for differences in abnormal returns and return volatility of ADR

subsamples with and without an eventual drug withdrawal. Lack of any significant difference

between the subsamples would support the assertion that the market is unable to accurately

predict the eventual withdrawal of a drug following an ADR.

II. Data and Methodology

Drugs could be withdrawn during post-marketing surveillance or during advanced

clinical trials in humans (Figure 1). In either instance, withdrawals are reported in major

newspapers. In a majority of cases drugs withdrawn during advanced clinical trials were already

assigned a brand name. This is not surprising as 66% of drugs that make it to Phase 3 trials are

approved. The withdrawal of drugs in pre-marketing stages could result from the FDA Advisory

8 An ADR represents any noxious and unintended effect of a drug, which occurs in humans despite proper dosing (World Health Organization, 1966). Despite elaborate involvement of the FDA in the drug approval process it is unreasonable to expect them to be perfect. Drugs cannot be tested in all possible conditions of use and the final phase of drug testing reveals only the most overt risks. Many important side effects become apparent only when the new drug appears on the market, as less common risks escape early detection. 9 Other studies that report significant negative stock market returns from "loss in reputation" include Hersch (1991) on Equal Employment Opportunity violations; Davidson, Worrell, and Cheng (1989), and Fry and Lee (1989) on OSHA violations; and Reichert, Lockett, and Rao (1996) on corporate white collar crimes. Chauvin and Guthrie (1994) report significant gains to shareholders of firms cited as best employers in Working Mother magazine.

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Committee rejecting a New Drug Application (NDA), or from a voluntarily withdrawal by a firm

due to a major adverse reaction or ineffectiveness.

This study identifies news of ADRs and withdrawal of drugs (post-marketing and in

advanced clinical trials) during the period 1966 to 1998 from the Wall Street Journal (WSJ).

The Physicians Desk Reference (PDR) identifies the competitors and availability of substitutes.

The sample of direct competitors only includes firms that were producing a substitute drug. In

contrast, most previous studies consider all firms in the industry as competitors. The day the

WSJ reports an ADR or a drug withdrawal is the event day (day 0).

The initial sample consisted of 162 withdrawals. Forty-three withdrawals by non-U.S.

manufacturers were excluded. Another 11 observations were eliminated due to either

insufficient historical return data or other contemporaneous news contaminating the actual event.

Reports in the WSJ also identify 617 instances of an adverse drug reaction. After applying

restrictions similar to those for drug withdrawals only 400 ADRs are considered for the final

sample. Of these, 196 observations make up the first report of an ADR while the remaining 204

observations were reports subsequent to the first ADR. In 44 instances the first report of an

ADR led to a withdrawal of the drug. The average (median) time between the first reported

ADR and the withdrawal of the drug is approximately 18 (13) months. We identified 81 direct

competitors from the Physician's Desk Reference of which 57 enter the final sample. The final

sample consists of 108 withdrawals, 400 ADRs, and 57 competitors. A firm withdrawing a drug

in one transaction is not included as a competitor in another transaction around the same date.

Table I shows that of the 108 withdrawals, 47 were by a single firm, in seven cases the

withdrawn drug did not have any available substitutes, and 42 withdrawals were related to death

or significant organ damage. In 84 withdrawals the drugs were in the post-marketing surveillance

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phase and the remaining 24 were in the advanced clinical (human) trial phase. The sample of

firms withdrawing a drug had a mean market cap of $5.43 billion.10

The event study methodology is similar to that in Dodd and Warner (1983). Specifically,

for each security j, the excess return, or prediction error, for period t is computed as the

difference between the actual return, Rjt,, and the expected return. The expected return is

obtained from the market model. The market return, Rmt, in the market model is the return on the

CRSP value-weighted index on day t. The parameter estimates for the market model are

estimated from an ordinary least square regression using return data from days -200 to -51 in

relation to the announcement day (t = 0). The results remain similar when the CRSP equally-

weighted index is used as a proxy for market return. For transactions in which multiple firms

withdrew similar drugs on one day, event-day portfolios are used as one observation. For

withdrawals, 70 portfolios were formed, whereas for the competitors the number of portfolios

was 31. No portfolios were necessary for the sample of ADRs. This method mitigates any

biases in tests of significance from lack of independence among the observations.

III. Results

A. Wealth Effects of Drug Withdrawals

Panel A of Table II reports the cumulative mean abnormal return from day -1 to 0, +1 to

+5 and +1 to +50 for all firms withdrawing a drug. The abnormal return from day –1 to 0 of -

7.85%, with 71% of the firms reporting negative abnormal returns, is significant at the 1% level.

Panel A of Figure II plots the daily abnormal returns from day -5 to +5. The most significant

10 The current (year 2000) market value of drug manufacturers is computed using 15% annual compounding (the average annual market return from 1971 to 1999 is 15.28% when using the Wilshire 5000 index). The current mean value for the market cap is approximately $61 billion.

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market reactions take place on days -1 and 0. Returns in the post-announcement period from

days +1 to +5 and +1 to +50 are statistically insignificant. The results confirm previous findings

that shareholders suffer significant wealth losses around the announcement of a drug withdrawal.

The magnitude of losses in this sample is higher than the 3.9% loss reported by Dranove

and Olsen (1994) over an equivalent event period. These results support the findings of Jarrell

and Peltzman (1985) who report a wealth loss of 12.82% in the ten-day interval from day -4 to

+5 (their withdrawal sample had only five firms). The results also show that the wealth loss

resulting from drug withdrawals is much larger than that for other product recalls or catastrophic

events. For non-pharmaceutical products, Davidson and Worrell (1992) report a shareholder

wealth loss of 4.54% over the period -1 to +1, while Bosch, Eckard, and Singal (1998) show that

stockholders in airlines suffer a 2.67% loss at the time of an air crash.

Examining the loss in dollars provides another perspective on the wealth effects of drug

withdrawals. Panel B of Table II presents the mean and median excess dollar returns. From day

-1 to 0, the median loss in wealth for a firm withdrawing a drug is $58.2 million. For most firms,

a single drug will not account for a large proportion of overall sales. However, the median dollar

losses translate to approximately 9% of annual sales in the year of the withdrawal. From day -1

to 0, the mean (median) dollar loss in current value terms is $441 ($154) million. The current

(year 2000) value of the dollar loss is calculated by using annual compounding and a constant

market return of 15%. Considering the fact that the peak revenue of an average drug is only $66

million, the dollar losses are fairly high.

Comparing the variance and beta of each firm between its pre-event period of days -200

to -11 and post-event period from days +11 to +200 allows us to test for changes in the firm's

risk due to a significant event (Marcus, Swidler, and Zivney, 1987). A F-value tests for

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significance in the ratio of variance between pre- and post-event periods. Results indicate that

the cross-section of firms exhibit statistically insignificant changes in average variance after the

withdrawal of a drug. Similar inferences are made when comparing the betas of the firms.

Barber and Loeffler (1993) indicate that abnormal performance of a stock following an event is a

result of either price pressure or true information. In an efficient market, perfectly informed

revaluation can occur without any significant trading. However, a significant change in volume

confirms the presence of informed trading. The abnormal trading volume is calculated by

subtracting the expected from the actual trading volume. Expected trading volume is the average

daily trading volume over days -200 to -11. Results show that trading volume on average

increased by 240% and 295% on day -1 and 0 respectively, indicating the presence of informed

trading due to a fundamental change in the value of the firm. Part A of Figure II overlays the

abnormal volume on the abnormal return from days -5 to +5. The significant abnormal return is

backed by statistically significant increase in trading volume.

B. Information Content in the News of Drug Withdrawals

To determine the most significant factors that explain the cross-sectional difference in

abnormal returns for the drug producers, the following regression is run:

AR = α + β1· DSUBSTITUTE + β2· DREASON + β3· DSINGLE + β4· LMV + β5· DSTAGE+ ε

where, AR = abnormal return from day -1 to 0 for a firm withdrawing a drug.

DSUBSTITUE = 1 if the drug being withdrawn has an available substitute, 0 otherwise.

DREASON = 1 if withdrawal news has significant negative information content such as death,

birth defects, organ damage and psychiatric problems, and equals 0 if the drug was withdrawn

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for being ineffective.

DSINGLE = 1 if only one drug producer withdraws a drug, 0 otherwise.

LMV = log of market value of firm six days before the news of drug withdrawal.

DSTAGE = 1 if drug was withdrawn during clinical trials, 0 if withdrawn during post-marketing

surveillance.

Table III presents the results for the multivariate regression. The results in Panel A show

that the factors DSINGLE, LMV, and DSTAGE are significant. The negative coefficients for

DSINGLE and DSTAGE show higher losses for single firm withdrawals and for withdrawals

during clinical trials. The positive coefficient for firm size, LMV, shows that losses are inversely

related to size.

Univariate tests of difference in mean abnormal returns between samples stratified by the

information content of the news are in Table IV. On 23 occasions the FDA ordered more than

one drug producer to withdraw a type of drug. These 23 orders affected a total of 61 firms. In

this subsample, 52% of firms have a negative abnormal return, with the mean excess returns of -

0.36% from day -1 to 0 being statistically insignificant. In contrast, for a single drug withdrawal,

the wealth loss is significantly higher with a mean abnormal return of -11.51%. In the subsample

of single withdrawals, 77% of the firms report a negative abnormal return (Table IV, Panel B).

The difference in mean abnormal return between subsamples of single and multiple withdrawals

is 10.30% and is statistically significant at the 1% level. The results indicate that the magnitude

of wealth loss is conditional on the number of firms (DSINGLE) withdrawing drugs on one day.

The stage of the drug withdrawal is a significant factor for the extent of wealth loss.

Firms withdrawing drugs during advanced clinical trials suffered a 18.69% loss in shareholder

wealth, while withdrawals during post-marketing surveillance resulted in only a 1.83% loss

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(TableIV, Panel D). Both returns are significant at the 1% level. The difference in mean

abnormal returns between subsamples based on stage of withdrawal (DSTAGE) is statistically

significant at the 1% level.

The two variables that were not significant in the multivariate regression were

DSUSBTITUTE and DREASON. The producers of seven drugs that did not have a substitute,

on average, lost half their market values with a cumulative abnormal return of -48.57% from day

-1 to 0 (Table IV, Panel A). In contrast, the abnormal return for firms withdrawing drugs with

substitutes is much lower at -3.81%. Both abnormal returns are significant at the 1% level.

Moreover, the difference in the mean abnormal returns between the two subsamples is

statistically significant at the 1% level. The large wealth loss for the small number of firms

withdrawing drugs without any substitute could be partially due to confounding effects of firm

size and lack of product diversification. Insights into this issue are gained by comparing the

mean (median) market size of the firms withdrawing drugs with and without available

substitutes. The market value of the firms withdrawing drugs with available substitutes is

significantly larger [mean (median) of $7,524 ($975) million)] than firms withdrawing drugs

without any substitute [mean (median) of $600 ($401) million)]. The median annual sales of the

seven firms withdrawing drugs without any substitutes is $17 million, while the firms

withdrawing drugs that had an available substitute are significantly larger with median sales of

$2,362 million. Further, six out of these seven firms operated in one business segment and had

no principal product with sales greater than $20m. Thus, it is possible that in addition to the lack

of substitutes, the difference in share price reaction is a function of firm size.

Firms reporting significant medical reaction as the cause of withdrawal suffered high

losses in shareholder wealth with a mean cumulative abnormal return of -9.34% from day -1 to 0

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(Table IV, Panel C). Additionally, 81% of such firms had a negative abnormal return. In

contrast, producers withdrawing a drug for being ineffective suffered smaller losses in

shareholder wealth with a mean cumulative abnormal return of -6.45% from day -1 to 0. Only

61% of firms withdrawing an ineffective drug report an abnormal loss. The difference in mean

return between the two subsamples is statistically insignificant indicating that the reason for a

drug withdrawal is not a significant factor in explaining the differences in abnormal returns.

Since the seven firms that withdrew drugs that lacked a substitute lost almost half their

market value, which can overstate wealth losses in small samples, the multivariate regressions

were rerun after eliminating these seven firms. Results in Panel B of Table III show that the

three variables DSINGLE, LMV, and DSTAGE remain significant at the 1% level. Thus, it can

be concluded that the following information primarily explains the difference in the abnormal

returns for drug withdrawals, (i) number of producers withdrawing a drug, with withdrawals by

single producers on average having higher wealth losses, (ii) firms with larger market value

suffer lower wealth losses, and (iii) firms withdrawing drugs during post-marketing surveillance

suffer lower wealth losses.

C. Adverse Drug Reaction (ADR)

The economic interpretation of the wealth effect of an ADR is that it should primarily

affect the reputation of the firm as no explicit contracts are violated and no direct costs are

incurred. Results in Table V indicate that the first report of an ADR is associated with a

significantly negative stock price reaction. For the 196 firms affected by an ADR, the

cumulative abnormal return from day -1 to 0 is -2.44%. For the 204 reports subsequent to the

first ADR, the abnormal reaction is much smaller at -0.72% but is statistically significant at the

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1% level. Consistent with previous work on the economic impact of loss of reputation, the result

here lends support to the pricing of reputation. Although an ADR that leads to a drug withdrawal

has a higher negative abnormal return than an ADR that does not lead to a withdrawal, the

difference is statistically insignificant. Additionally, there is no significant difference in average

post-event variance or average beta between the subsamples of ADR that lead to a drug

withdrawal and those that do not. Thus, at the time of reporting of an adverse drug reaction the

market cannot anticipate if the ADR will lead to a withdrawal.

In 44 instances the first report of an ADR was followed by the eventual withdrawal of the

drug. In 18 cases there were additional ADR announcements prior to the withdrawal. The

average abnormal return at the announcement of the first ADR (44 instances) is -2.87%, which is

significant at the 5% level. The reports of subsequent ADRs produce a smaller stock price

reaction with an abnormal return of -1.10% for day -1 to 0, which is statistically insignificant.

The abnormal return to these 44 firms at the time of the drug withdrawal was -3.49%. The

cumulative abnormal return over all preceding announcements of an ADR and the drug

withdrawal is -6.63%. This indicates that the wealth loss over all preceding ADRs and the actual

withdrawal is substantially higher than the loss at the time of the drug withdrawal.

D. Impact of Drug Withdrawals on Competitors

Table VI presents the results for the 57 competitors that produced a substitute for the

withdrawn drug. The day -1 to 0 abnormal return to competitors is -0.34%, which is statistically

insignificant. Sixty-five percent of competitors have a negative abnormal return. This small but

statistically insignificant change in wealth is backed by an insignificant change in trading volume

(Figure II, Panel B). The insignificant wealth loss for the competing pharmaceutical firms is in

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contrast to results reported by Bosch, Eckard, and Singal (1998), who show that following an

airplane crash there is a ‘negative spillover’ effect out of concern for overall safety of all

products in the industry. Additionally, according to them investors anticipate increases in costs

of regulatory compliance affecting all firms in the industry.

Following the withdrawal of a drug, the competitors gain over the period from days +1 to

+5. The cumulative abnormal return of 1.65% from day +1 to +5 is significant at the 1% level

and exceeds the losses sustained over the period -1 to 0. Sixty-eight percent of the competing

firms report a positive abnormal return. These results are significantly different from those in

other studies, which show the presence of a negative spillover in post-event periods (Bosch,

Eckard, and Singal, 1998; Jarrell and Peltzman, 1985). The positive post-event share price

reaction in our sample is also backed by a small increase (almost 21%) in trading volume. The

gains to competitors indicate that the increase in market share is more important to investors than

any concern for the systemic safety of drugs.

IV. Conclusions

Using a larger sample than in any previous study, this paper shows the impact of the

news of a drug withdrawal on the shareholder wealth of its producer and its competitors. In

many instances a drug withdrawal is preceded by one or more announcements of adverse drug

reactions. Most previous studies underestimate the total loss from the withdrawal of a drug by

not fully taking into account the wealth effects during preceding adverse drug reactions. This

paper shows that the combined loss from an ADR and subsequent withdrawal is substantially

higher than the loss at the time of the withdrawal announcement.

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The results in this paper lend support to the earlier findings (Jarrell and Peltzman, 1985;

Dranove and Olsen, 1994) that large wealth losses result from the announcement of a drug

withdrawal. The results are also consistent with explanations in Marcus, Swidler and Zivney

(1987) and Jones and Rubin (1999), who suggest that the large loss in shareholder wealth is due

to a combination of expected loss in direct future revenue and lower indirect cash flow as a result

of loss in goodwill (reputation). The longer time period of the study allows data stratification on

the information content of the news of withdrawal. Withdrawals of the same product by multiple

firms and withdrawals of marketed drugs have lower losses as compared to withdrawals by

single firms and of drugs in advanced clinical trials, respectively. The losses are also higher for

smaller firms.

The findings in this study differ from previous work (Dowdell, Govindraj, and Jain,

1992; Bosch, Eckard, and Singal, 1998) on the wealth impact for competitors. While an airline

crash leads to significant negative spillover effect on the competitors, drug withdrawals did not

produce a negative spillover. An explanation for the difference is that the withdrawal of a drug

indicates failure of the firm but not of the overall system that governs the safety and efficacy of

pharmaceutical drugs.

Following the recent withdrawal of a very popular drug called Rezulin, Gilbert Ross,

Medical Director of the American Council on Science and Health wrote in the March 29, 2000

edition of the Wall Street Journal, "Actually, Rezulin's withdrawal shows that the FDA approval

process works exactly as it should. Just because a drug is withdrawn does not mean it should not

have been approved in the first place……. All drugs have risks, especially new drugs, and we

often need the data from post-marketing surveillance to detect them."11

11 “Rezulin Proves the System Works,” Wall Street Journal, March 29, 2000, A22.

18

References

Barber, B.M. and D. Loeffler, 1993, “The 'Dartboard' Column: Second Hand Information and Price Pressure, ” Journal of Financial and Quantitative Analysis 28, 273-284. Bosch, J.C., E. W. Eckard, and V. Singal, 1998, “The Competitive Impact of Air Crashes: Stock Market Evidence,” The Journal of Law and Economics, 41, 2(1) 503-519. Bromiley, P. and A. Marcus, 1989, “The Deterrent to Dubious Corporate Behavior: Profitability, Probability and Safety of Recalls,” Strategic Management Journal, 233-250. Chauvin, K.W. and J.P. Guthrie, 1994, “Labor Market Reputation and the Value of the Firm,” Managerial and Decision Economics, 543-552. Davidson, W. N. and D.L. Worrell, 1992, “The Effect of Product Recall Announcements on

Shareholder Wealth”, Strategic Management Journal, 467-473. Davidson, W.N., D. Worrell, and L.T. Cheng, 1994, “The Effectiveness of OSHA Penalties: A Stock-Market Based Test,” Industrial Relations, v. 33 283-296. Dodd, P. and J.B. Warner, 1983, “On Corporate Governance: A study of Proxy Contests,” Journal of Financial Economics, v. 11, 401-438. Dowdell, T.D., S. Govindaraj, and P.C. Jain, 1992, “The Tylenol Incident, Ensuing Regulation

and Stock Prices,” Journal of Financial and Quantitative Analysis, v.27, 283-301. Dranove, D. and C. Olsen, 1994, “The Economic Side Effect of Dangerous Drug

Announcements”, Journal of Law and Economics, v37, 323-348. Fry, C.L. and I. Lee, 1989, “OSHA Sanctions and the Value of the Firms,” The Financial Review, v.24 599-610. Hersch, J., 1991, “Equal Employment Opportunity Law and Firm Profitability,” Journal of Human Resources, v26. 139-153. Hoffer, G. E., S. Pruitt, and R.J. Reilly, 1988, “The Impact of Product Recalls on the Wealth of

the Sellers: A Reexamination”, Journal of Political Economy, v96 no. 3, 663-670. Jarrell, G. and S. Peltzman, 1985, “The Impact of Product Recalls on the Wealth of the Sellers,”

Journal of Political Economy, v93, no. 3, 512-536. Jones, K. and P. Rubin, 1999, “Effects of Harmful Environmental Events on Reputations of Firms, ” Emory University Working Paper.

19

Kellogg, D. and J.M. Charnes, 2000, “Real-Options Valuation for a Biotechnology Company,” Financial Analysts Journal, 56:3 76-84

Marcus, R. D., S. Swidler, and T.L. Zivney, 1987, “An Explanation of Why Shareholders’

Losses are so Large After Drug Recalls,” Managerial and Decision Economics, v8. 295-300.

Marino, A., 1997, “A Model of Product Recalls with Asymmetric Information,” Journal of

Regulatory Economics, 12: 245-265. Pruitt, S.W. and D.R. Peterson, 1986, “Security Price Reactions Around Product Recall

Announcements,” The Journal of Financial Research, 9:2 113-122. Reichert, A.K., M. Lockett, and R.P. Rao, 1996, “The Impact of Illegal Business Practice on Shareholder Returns,” The Financial Review, v.31 67-85. Rubin, P.H., R.D. Murphy, and G. Jarrell, 1988, “Risky Products, Risky Stock,” Regulation, 35-39. Sauer, P., 1998, “Finding the Next Blockbuster Drug,” Chemical Market Reporter v.254, n.21 Nov 23, 1998 FR3-FR6. Swiatek, J., 2000, “Rezulin's Withdrawal Could Benefit Eli-Lilly Marketed Drug,” The

Indianapolis Star, March 23. Welling, L, 1991, “A Theory of Voluntary Recalls and Products Liability,” Southern Economic

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Geneva, World Health Organization, Technical Report Series Number 425.

20

FIGURE I. The New Drug Development Process Pre-Clinical Research

Clinical Studies Human Testing

New Drug Application Review by Advisory Board

Post-Marketing Surveillance

STAGE 1 STAGE 2 STAGE 3 STAGE 4 R&D by Firm 1. Synthesis and Purification 2. Animal Testing

Phase 1: Sufficient information about the drug's pharmacokinetics and pharmacological effects should be obtained to permit the design of well-controlled, scientifically valid, Phase 2 studies. Probability of Success - 70%. Phase 2: Includes the early controlled clinical studies conducted to obtain some preliminary data on the effectiveness of the drug. Probability of Success - 47% of drugs approved at Phase 1. Phase 3: Expanded controlled and uncontrolled trials. They are performed after preliminary evidence suggesting effectiveness of the drug. Probability of Success - 66% of drugs approved at Phase 3.

After a New Drug Application (NDA) is received by the agency, it undergoes a technical screening generally referred to as a completeness review. Much of the primary review process involves reviewer attempts to confirm and validate the sponsor's conclusion that a drug is safe and effective for its proposed use. The review is likely to involve a reanalysis or an extension of the analyses performed by the sponsor and presented in the NDA. Once the reviewers and their supervisors reach an approval recommendation, the decision must be evaluated and agreed to by the director of the applicable drug review division or office. Once the division director (or office director, as appropriate) signs an approval action letter, the product can be legally marketed starting that day in the United States.

FDA conducts "post-marketing surveillance of medical products to identify safety concerns and take necessary actions. The MedWatch program is one such surveillance instrument. It depends on doctors, dentists, nurses, pharmacists and others to pass on to FDA details of serious adverse drug reactions (ADR).

NOTE. - Adapted from Federal Drug Administration's Center for Drug Evaluation and Research (CDER) Handbook.

21

FIGURE II. Daily Abnormal Return and Volume from Days -5 to +5 Market model parameters for calculating abnormal return were estimated from days -200 to -51. Abnormal volume is the percentage change in volume, which was estimated by subtracting the average daily volume during the period from days -200 to -11 from each day’s volume. Day 0 is the date the Wall Street Journal reported the withdrawal.

A. Firms withdrawing a drug

B. Direct Competitors

-20

-10

0

10

20

30

-5 -4 -3 -2 -1 0 1 2 3 4 5

Day

Pe

rce

nt

Ch

an

ge

in

Vo

lum

e

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

Abn

orm

al

Re

turn

(%

)

Volume Abnormal Return

0

100

200

300

400

-5 -4 -3 -2 -1 0 1 2 3 4 5

Day

Pe

rce

nt

Ch

an

ge

in

Vo

lum

e

-5

-4

-3

-2

-1

0

1

Abn

orm

al

Re

turn

(%

)

Volume Abnormal Return

22

TABLE I. Descriptive Statistics for Sample of Drug Withdrawals and Adverse Drug Reactions from 1966 to 1998

Description of sample of firms withdrawing drugs and reporting adverse drug reactions (ADR) between 1966 and 1998. News of drug withdrawals and ADRs was obtained from the Wall Street Journal. To be included in the sample, a firm had to be publicly traded on U.S. stock exchanges and meet additional criteria of data availability. The sample stratification is based on the information content of the news. Event-date portfolios are formed if multiple firms announce a drug withdrawal on the same day. The numbers in the table provide counts of event-date based portfolios in the sample. Market capitalization is measured at the end of the sixth day prior to the announcement date. The current (year 2000) value of the market capitalization is computed using 15% annual compounding. Total number of firms withdrawing drugs 108 Single or multiple withdrawals on one day Multiple 61 Single 47 Substitutes Available 44 Unavailable 7 Indeterminate 57 Reason for withdrawal Ineffective 59 Death/Organ Damage/Birth Defect/Psychiatric 42 Other 5 Stage of Drug Withdrawal Post-Marketing Surveillance 84 Advance Clinical Trials (Phase 3 and beyond) 24 Adverse Drug Reactions (ADR) All reported ADR 400 First ADR 196 ADRs leading to subsequent withdrawal of the drug 44 Number of direct competitors 57 Market capitalization of firms at the time of a drug withdrawal Mean $5.43 billion Mean present value (year 2000) of market cap $61.00 billion

23

TABLE II. Abnormal Returns to Firms Withdrawing Drugs This table presents the abnormal returns, Z-statistic for significance of mean abnormal return, and proportion of the sample (in percentage) with negative abnormal returns for all firms withdrawing a drug. For instances where several firms withdraw a drug on the same date, an event-date based equally-weighted portfolio is formed and treated as a single observation. NP is the total number of unique portfolios formed. Day 0 is the date on which the Wall Street Journal reports the news of drug withdrawal. Market model parameters were estimated from days -200 to -51. The percentage abnormal returns are in Panel A, and the dollar abnormal returns are in Panel B. For dollar abnormal return calculation, the full sample was used and event-date portfolios were not formed. A sign rank test is employed to test for significance of median dollar abnormal return. *, **, *** denote significance at the 1%, 5%, 10% levels respectively.

Interval Abnormal Return Z-Statistic Percentage of Negative Abnormal Returns

Panel A. Percentage Abnormal Return (Np = 70)

-1, 0 -7.85*

-13.95 71

+1, +5 -0.25

-0.05 46

+1, +50 1.59

0.29 54

Panel B. Dollar Abnormal Return (N=108)

Median Return $ million

p-value Mean Return $ million

-1, 0 -58.2**

0.042 -114.4

+1, +5 26.0

0.506 -128.4

+1, +50 -26.5

0.925 -108.8

24

TABLE III. Regressions of Abnormal Return on Information Content of News Regressions of abnormal returns on variables representing information content of the news of a drug withdrawal. AR = α + β1· DSUBSTITUTE + β2· DREASON + β3· DSINGLE + β4· LMV + β5· DSTAGE+ ε AR = abnormal return from day -1 to 0. Dummy variable DSUBSTITUE = 1 if the drug being withdrawn has an available substitute, 0 otherwise. Dummy for reason for withdrawal, DREASON = 1 if reason for withdrawal has significant negative information content such as death, birth defects, organ damage and psychiatric problems, and 0 if the drug was withdrawn for being ineffective. Dummy variable DSINGLE = 1 if only one drug producer withdraws a drug, 0 if multiple firms withdraw a similar drug on the same day. LMV = log of market capitalization of firm six days before the news of drug withdrawal. DSTAGE = 1 if drug was withdrawn during clinical trials, 0 if withdrawn during post-marketing surveillance. t-statistics are in parentheses below the coefficient estimates. *, **, *** denote significance at the 1%, 5%, 10% levels respectively.

PANEL A PANEL B Interval

Days -1, 0

Days -1, 0

Sample All Withdrawals Withdrawals excluding the seven firms without substitutes

Sample size

N = 108

N = 101

Intercept -0.4720*

(-3.51)

-0.2428* (-3.44)

DSUBSTITUTE

0.0520 (1.45)

DREASON

-0.0016 (-0.05)

-0.0243 (-1.41)

DSINGLE

-0.1030* (-2.81)

-0.0583* (-3.11)

LMV

0.0352* (3.53)

0.0194* (3.77)

DSTAGE -0.1445* (4.14)

-0.0472* (-2.44)

F- Value 9.60*

7.10*

Adjusted R2 0.3839

0.2823

25

TABLE IV. Cumulative Abnormal Returns for Subsamples of Firms Withdrawing a Drug Percentage abnormal returns, Z-statistic for significance of mean abnormal return, and percentage of negative abnormal returns for subsamples of drug withdrawals. For instances where several firms withdrew a drug on the same date, an event-date based equally-weighted portfolio is formed and treated as a single observation. NP is the total number of unique portfolios formed. Day 0 is the date on which the Wall Street Journal reports the news of the withdrawal. Market model parameters were estimated from days -200 to -51. The square brackets give the t-statistics for tests of difference of means. *, **, *** denote significance at the 1%, 5%, 10% levels respectively.

Interval

Percentage Abnormal Return Difference

Panel A. Availability of Substitutes

Available

(1) Np = 32

Available or indeterminate

(2) Np = 63

Not available

(3) N = 7

(1) and (3)

(2) and (3)

-1, 0 -3.81*

(-6.68, 75) -3.33**

(-7.86, 68) -48.57*

(-20.53, 100)

-44.76* [-9.37]

-45.23* [-10.87]

Panel B. Number of Firms Withdrawing Drug

Multiple

(1) Np = 23

Single excluding drugs

without substitutes

(2) Np = 47

(1) and (2)

-1, 0 -0.36

(-0.46, 52)

-11.51* (-16.71, 81)

-11.15** [-2.66]

Panel C. Reason for Withdrawal

Severe medical reaction

(1) Np = 36

Ineffective

(2) Np = 34

(1) and (2)

-1, 0 -9.34*

(-2.81, 81) -6.45*

(-2.59, 61)

-2.89 [-0.70]

Panel D. Stage of Withdrawal

Advanced Clinical Trials

(1) Np = 25

Post-Marketing Surveillance

(2) Np = 45

(1) and (2)

-1, 0 -18.69*

(-3.75, 76) -1.83*

(-2.81, 69)

-16.86 [-4.44]

26

TABLE V. Cumulative Abnormal Returns at the Announcement of an Adverse Drug Reaction (ADR)

This table reports the abnormal returns in percentage, Z-statistics and proportion (in percentage) of the sample with negative abnormal returns for a sample of adverse drug reactions. N is the total number of firms. Day 0 is the date on which Wall Street Journal reports the news of a drug withdrawal or an ADR. Market model parameters were estimated from days -200 to -51. The square brackets give the t-statistics for tests of significance. *, **, *** denote significance at the 1%, 5%, 10% levels respectively.

Interval All First ADRs

All Subsequent

ADRs

ADR Sample Matched With Subsequent Drug Withdrawal

(1)

N = 196

(2)

N = 204

Withdrawal of Drugs

(3)

N = 44

First ADR

(4)

N = 44

Subsequent ADR

(5)

N = 18

Total of ADR and

withdrawal (3+4+5)

N = 62

-1, 0 -2.44*

(-10.30, 67) -0.72*

(-4.87, 57) -3.49* (-1.78)

-3.90* (-5.80, 72)

-1.10 (-1.00, 54)

-6.63** [1.86]

+1, +5 0.05

(0.65, 50) 0.60**

(2.17, 46) 0.60

(0.56) -0.01

(-1.01, 40) 0.74

(-0.01, 40) 0.59

[0.56]

27

TABLE VI. Cumulative Abnormal Returns to Competitors of Firms Withdrawing Drugs This table reports the abnormal returns in percentage, Z-statistics and proportion (in percentage) of the sample with negative abnormal returns for competitors of firms withdrawing drugs. For instances where several announcements took place on the same date, an event-date based equally-weighted portfolio is formed and treated as a single observation. The sample size NP equals 31, and is the total number of unique portfolios formed. Day 0 is the date on which the Wall Street Journal reports the news of drug withdrawal. Market model parameters were estimated from days -200 to -51. *, **, *** denote significance at the 1%, 5%, 10% levels respectively.

Interval Abnormal Return Z-Statistic Percentage of Negative Abnormal Returns

-1, 0

-0.34

-1.54 65

+1, +5

1.65*

3.20 32