Shareholder’s Sensitivity to the Unethical
Behaviour of Pharmaceutical Firms: An
Exploratory Review 2009-2014
Master Thesis
Faculty of Economics and Business University of Groningen
June 2016
Name: Owen Molloy Student number: s2838826 Degree program: MSc. Finance
Abstract: This research paper utilises event study methodology to
investigate (i) whether the shareholders of pharmaceutical firms enforce a punishment in the financial markets upon the announcement of an unethical act or behaviour, (ii) if firms are punished more so for acts directly related to consumer welfare than those in relation to procedure and regulation, and (iii) if shareholders punish firms for Kickbacks. Our results indicate that there is a penalty inflicted on the day immediately following the announcement. Similarly, for a number of different event windows surrounding the announcement day there are negative Cumulative abnormal returns. Overall, the industry’s sensitivity to punishing Unlawful Promotion is more so than that of punishing Kickbacks, where we find no significant negative abnormal returns.
ACKNOWLEDGEMENT
1. Introduction
Punishing unethical behaviour has become more relevant in the last decade, as shareholders seek to inflict penalties on firms who have not always acted as they should have. Institutional changes and more regulations have set the norm higher and higher, forcing firms to be held to higher standards, which has lead to more severe penalties when these standards have not been kept (Almashaat & Wolfe, 2012, Gagnon, 2013). The increased availability of information and technological advances pushes these allegations into mainstream media coverage, making the argument that a certain amount of unethical behaviour could now be expected within certain firm types/industries. The idea of unethical behaviour benefiting firms raises many questions relating to shareholders, namely: if a firm is experiencing more profits or growth from this behaviour, do shareholders still punish them, or do they become less sensitive to the action. Similarly, if the behaviour is considered to be the norm within the industry, should we expect shareholders to still inflict a penalty? The pharmaceutical industry is engulfed by ethically questionable corporate practices; Kickbacks, Concealing Findings, Unlawful Promotion and even Pricing itself (Spinello, 1992, Parker-Lue et al., 2015, Bieglar, 2014 & 2015). Literature surrounding these issues calls for sensible and reasonable governing by all parties. But with a significant amount of fines sometimes running into the billions of dollars, and unethical behaviour at an all time high, do shareholders inflict an additional penalty in the financial markets?
investigation, it has become a move away from the older method of correction and compliance, and towards punishment (Girard, 2008). This is normally because the company seeks to accept a settlement quickly in order to not initiate any further investigations that could freeze assets or finances, and result in products being held. More importantly, the firm seeks to settle the case immediately in order to avoid the potential losses of being excluded from being able to have their products reimbursed under the federal health care programs (Girard, 2009). This change in tactic allows us to investigate if pharmaceutical firms are seeing an additional penalty in their share price, and also plays a pivotal role in the construction of our methodology and how we will approach our hypotheses.
paper to determine if certain unethical actions deserve more punishment than others.
Our research question centres on the concept of shareholders punishing firms for unethical behaviour through the financial markets, and by extending this to the pharmaceutical industry we hope to address the current trend of increased unethical behaviour by these firms in recent years, and examine the extent to which their shareholders are also penalising them in the financial markets. The paper will be arranged as follows; section 2 will provide a concise examination of the literature relating to ethics, financial markers and later our industry. Section 3 will establish and lay out our chosen methodology, with information surrounding our data also being presented. Our results will be stated and briefly analysed in section 4, before finally moving onto section 5 where we will provide more discussion around our findings, along with potential limitations, and highlighting the direction in which we believe future research should take.
2. Literature Review
done so, frame the most appropriate methodology to address our hypotheses and overall research question.
2.1. Ethics and Expectations
It is important to briefly explore the ambiguity of ethics itself, in order to understand and appreciate the complexity of the issue, and what corporations may face when dealing with an ethical decision, but also to determine what is expected - in an ethical sense - from companies. Sometimes it is easier to describe what ethics is not, rather than to attempt to attach just one definition. As discussed by James Pasztor (2015), ethics and behaviour can be described as deeply personal. This does not mean that they are the same as feelings, depicted by law, religion or science, or should be modeled solely on accepted practices, norms, and rules.
This approach would then suggest that shareholders of a company might truly believe that their company has behaved unethically, however not unlawfully. Therefore the firm would not receive a financial penalty from governing bodies, but instead perhaps some form of penalty from shareholders, or indeed some stakeholders. This raises the question if shareholders judge their firms ethical behaviour/actions from a principle-based approach or purely rule-based approach (Gibson, 2007). Thus, corporations face a difficult situation in order to meet the ethical expectations of all their stakeholders, as ethics can be described as something changeable and individualistic:
Velasquez, Andre, Shanks, Meyer, (revised 2010) - originally ‘Issues in Ethics’ IIE V1 N1 (Fall 1987).
Drawing from this, it can be considered unreasonable to expect an organisation to try and uphold all the deeply personal moral and ethical expectations of every one of its shareholders all at once. As they are constantly evolving, it is then better to adopt the alternative view; following the law fulfills the moral requirements of a business, as set out in the rule-based approach (Gibson, 2007). This Theory suggests that as a business, one should do anything one can to maximize returns – including polluting or bribing officials if necessary – while never breaking the law. Compliance being the objective, a company should then only go beyond the legal minimum if there is a financial incentive to be gained, a concept often associated with Milton Friedman (1962, 1970). However, the issue with using the law as an ethical yardstick is that the company must accept that all laws are equal and must be upheld. Similarly, they must assume that their shareholders also believe this, and therefore will only be punished when the law is broken, something we discuss later that is not always the case given the research.
Do stakeholders support the rule-based approach to the ethical standards set out by their firms, or a principal-based approach? We can evaluate this by looking at how shareholders react to the company’s actions and general behaviour, although naturally this highlights a potential issue: do all stakeholders actually act on their attitude towards the behaviour in the first place? In the paper by Boulstridge & Marrigan (2000) the attitude-behaviour gap is highlighted, and how there appears to be a number of conflicting reports surrounding this theory is acknowledged. Although this paper centers on corporate reputation and stakeholders reacting to good or bad behaviour, the finding is easily extendable to ethics, and is done so within the paper itself, when the authors make reference to the findings of Creyer & Ross (1997); consumers do expect their companies to exert ethical behaviour, and are willing to pay more in order to reward them. The paper also finds that unethical firm’s products are still purchased despite their behaviour, but the products are expected to be cheaper. We can draw from this finding that there is effectively a price reward put on ethical behaviour by stakeholders, but not necessarily a price penalty for unethical behaviour. The attitude-behaviour gap is also found in the study of Carrigan & Attalla (2001), where they find that although the respondents to the survey had socially responsible attitudes, in the last year only 20% had purchased a product because it was associated with a good cause. So although we assume that stakeholders expect ethical behaviour, they do not always act on this. Another way of punishing a firm for unethical behaviour is through the financial markets.
2.2. Financial Markets and Punishment Efficiency
(i.e. more sustainable) is institutionalized as the norm, the more negative the reaction of eco-harmful behaviour (punished for not following the norm) and the less the reward is for firms for engaging in eco-friendly initiatives. Thus she argues that there is a decreasing marginal return from environmental Corporate Social Responsibility (CSR), although companies with larger stocks of environmental resources may experience a smaller loss from eco-harmful events, as they are better ‘insured’ against such events.
2.3. The Pharmaceutical Industry and Ethics
The pharmaceutical industry is responsible for the supply and manufacturing of drugs and medicines with billions of dollars in sales. The top 20 pharmaceutical corporations in the U.S. had total sales of over $275 billion last year (Statista, 2015). The pricing of essential products like medicine can be especially complex and controversial, as addressed in Spinello (1992). The paper highlights a key argument often discussed within ethics. Every business is entitled to reasonable profits, but when do profits become unreasonable? Or can profits ever be considered unreasonable? Indeed, judging the ethical status of such profits can be problematic. On one hand, the corporation has a fiduciary responsibility to its shareholders to maximize profits and portray long-term sustainability, but on the other hand if these premium prices are judged to be unethical or unreasonable, there may be some type of punishment in the financial markets similar to other industries. Therefore there must be balance between key financial targets and ‘justice’ regarding pricing in the industry, although this cannot be obtained without uniform cooperation between the biggest firms and government (Spinello, 1992). Parker-Lue, Santoro, Koski (2015) find similar results in a review of the literature surrounding the ethics and economics of pharmaceutical pricing. They explain the general theme of the review to be one where the issues of pricing are much more complex than they first appear, and call for greater cross-disciplinary interaction among economists, ethicists and physicians. If there is a general acceptance that this entrenched dilemma cannot be easily resolved, the question arises whether shareholders even punish the firms for this unethical profit making.
pharmaceutical industry have many implications, and if we were to extend the previous body of research to the industry we would then expect to see a series of share price fluctuations every time an ethically questionable act is committed. When it comes to corporate ethics ratings, there are no pharmaceutical firms mentioned on The Ethisphere Institute’s list of “The World’s Most Ethical Companies 2015”, a well-recognised ratings agency operating for almost a decade (Forbes, 2015). A 2012 report by Almashat & Wolfe looking at over 20 years of settlements ($1 million or greater), regarding violations and financial penalties within the pharmaceutical industry, shows a worrying trend in illegal and, more often than not, unethical activity. Indeed, nearly all of the largest fines ever given out within the industry have been in the last decade, as seen in the report by Almashat & Wolfe (2012). Their research shows that between 1991-2012 the seven largest settlements and judgments all occurred in the previous six years, and individually ranged from $950 million to $3.4 billion. Six out of the seven were for the same violation of unlawful promotion i.e. the off-label promotion of drug products or other deceptive marketing practices (e.g. downplaying health risks of a product). Over the 21-year period of the report, there have been 64 violations of unlawful promotion (totaling $10.5 billion), with nearly 30% of the violations (18) taking place between November 2010 and July 2012 (totaling $4.45 billion). In fact, from the analysis we can see that even though the study period is 21 years long, over 30% of all violations actually occurred within the final 21 months of the study. This shows not only a significant trend of increased illegal and unethical activity from within the industry, but also increased level of fines.
financial penalties since 1991 in the pharmaceutical industry comes to less than half the profits made by the 10 largest U.S. drug companies made in 2009 alone (Gagnon, 2013). Another unintended consequence is the raising of insurance premiums, which acts as a barrier to entry for the industry. As fines are normally covered by the company’s insurance, higher fines means increased risk premiums. The paper goes on to explain that competition is reduced within the industry as a result, and recommends a mixture of cautious fine increases along with criminal prosecutions.
Paul Biegler (2014 & 2015) discusses the ‘tricks of the trade in drug promotion’ – stating the ethical view of even promoting the use of drugs could be viewed as a tricky one itself. Encouraging the use of prescription drugs to consumers is prohibited in Australia, while in the U.S. the FDA limits the use of distracting imagery while the adverse effects are being read out. However, the promoting to prescribers in general includes some form of non-propositional content, including “Images, music or other things in advertising that persuade, but cannot be judged true or false in the same way that statements or ‘propostions’ can” according to Bieglar. The aim is to build positive emotional associations with the drug, and the article explains how health professionals may be vulnerable to this emotional persuasion. In 2005, drug companies in the U.S. spent just under half a billion dollars on advertising in medical journals. According to Biegler (2014), this returned approximately five dollars for every one dollar invested; therefore the persuasive intent of drug advertising does indeed alter prescribing patterns. The author calls for regulation, research surrounding the persuasive impact and for professions to adopt an analytical approach.
1.0. Combined with our previous discussion, the below can be seen to be highly unethical acts and behaviours, and these definitions will form the basis from which we will classify our events. Table 1.0 – List of violation definitions
Type of Violation Description
Overcharging
Government Health Programs
Inflating the average wholesale price of products, failing to give the lowest market price to government health programs, or failing to pay required rebates to any government health program
Unlawful Promotion Off-label promotion of drug products or other deceptive marketing practices (e.g., downplaying health risks of a product)
Monopoly Practices Unlawfully attempting to keep monopoly patent pricing privileges on products, or collusion with other companies
undertaken with the purpose of increasing the market share of a particular product
Kickbacks Kickbacks (e.g., monetary payments) to providers, hospitals, or other parties to influence prescribing patterns in favor of the company
Concealing Study Findings
Concealing results of company-sponsored studies from the federal or state
governments or the general public, or falsifying data submitted to the federal government
Poor Manufacturing Practices
Environmental Violations
Clean Air Act and Clean Water Act violations, or failing to meet federal emissions standards
Financial Violations Accounting or tax fraud, or insider trading
Illegal distribution Distributing an unapproved pharmaceutical product
As we move forward and examine the many ethically questionable acts and violations within the industry, naturally the following question arises – do the shareholders of pharmaceutical companies punish firms through the financial markets, and if so, is there a more extreme punishment for a specific type of act? This forms our first hypothesis, and by extension, the reasoning for our second and third.
H1: Shareholders punish pharmaceutical firms in the financial markets for unethical behaviour.
was experienced on the announcement of a product recall. Cheah, Chan & Chieng (2007) investigate the reaction of U.S. and U.K. investors specifically to product recalls within the pharmaceutical industry. Product recalls can significantly damage a company’s reputation, profitability and brand integrity. However, the act of the recalling can itself be viewed as a positive (ethical) effort at corporate responsibility and accountability, and could therefore reduce the mentioned negative effects of the recall. Similar to the insurance effect already discussed in Godfrey et al. (2009), they find that the level of CSR activism in both countries matters when it comes to the reaction. U.S. investors penalized firms according to the severity of product defects, while U.K. investors were indifferent. CSR active firms in the U.K. were punished for product recalls, while in the U.S. they were rewarded, meaning there may be a different emphasis put on (or understanding of) CSR in the U.S. and U.K. markets when it comes to the pharmaceutical industry. Thus highlighting the potential importance of acting beyond the legal minimum requirements set out by governing bodies. This action was directly related to the well being of consumers, and in the U.S., such a correction experienced a positive reaction in the financial markets, thus leading to our second hypothesis:
H2: Pharmaceutical firms are penalised more for behaviour or actions directly related to the welfare of their consumers than those related to procedure or regulations.
“criminal law that prohibits any person from knowingly paying or offering any remuneration in exchange for or to induce the referral or recommendation of any item or service”. They also comment on how a reform to the statute now provides for a person not needing to have knowledge of the statute or even the intent to be present. As outlined by Bansal & Das (2005), firms interact with doctors in order to enter a mutually beneficial relationship, where drug companies promote their medical products and doctors are compensated adequately. The authors conclude that this relationship must be contained within acceptable boundaries, as a globally observed practice of prescribing and promoting unnecessary drugs in order to obtain a monetary gain. An extreme view is that of Margolis (1991), who states that acceptance of any gift in any form is a fundamental violation of physician’s duties of “fidelity, justice and self-improvement”, even gifts of small office items like pens or pads are unacceptable. Das & Bansal use an example of doctors in remote areas that depend heavily on the drug companies for product information and even education. They concede the only ethical solution is to not accept anything of financial value from the pharmaceutical companies. Indeed, there has been much debate around the ethics of such a relationship, and what guidelines to one should look like. Whether a relationship should be based around the beliefs of members of the public was examined in Macneill et al. (2010), and the study found them to have a more liberal attitude to gift giving, while still having overall similar attitudes to the acceptance of ‘most’ gifts as the medical specialists. One of the main conclusions of the paper is that ethical judgments about the appropriateness of gift giving and gift receiving should give more weight to important values, and not popular support, noting that 80% of the general public found it appropriate for a doctor to accept an ECG machine as a gift.
an understanding of necessary behaviour in order to ensure important products/practitioners receive the appropriate training - meaning it will not translate into a penalty in the financial markets for pharmaceutical firms. When considering the potential reaction of the public to a firm engaged in questionable relationships with practitioners and other firms we arrive at the following hypothesis:
H3: Shareholders don’t punish pharmaceutical firms for kickbacks.
We will now seek to test this, discuss the chosen methodology, and gauge the level at which pharmaceutical companies are being punished in the financial markets for unethical behaviour while analysing the results in the following sections.
3. Methodology & Data
periods and expected returns models, as model specific biases are not as extreme for shorter studies.
Brown and Warner (1985) write extensively on the benefits of short-horizon (and even small sampled) event studies. They find that with daily data (which we will be using) a market adjusted returns and OLS market model have similar power. Fama (1991) also states that short-horizon tests are the most straightforward way of judging a market’s efficiency, which we also expect to play a role in determining our realised abnormal returns. Therefore our event window will consist of a window of only 10 days prior (t=-10, -9, -8, etc.) to the event date (t=0) in order to capture any information leaks prior to publication, followed by 10 days after (t=+1, +2, +3, etc.) in which to capture any delayed reaction to the public press release or releases taking place outside of trading periods. We would expect a relatively efficient market given the way in which the announcements are agreed and published, and feel the event window will capture all abnormal returns as a result of the event. However, as a precaution enough time prior to the event has been given in case of insider information.
explained in Girard (2009), the fear of exclusion, and loss of significant amounts of revenue, forces the pharmaceutical firms to settle as soon as possible, and therefore we would not expect to see similar issues as discussed in previous literature.
Following our review of previous studies, the calculations of abnormal returns (AR) and average abnormal returns (AARs) will be carried out using the following formulae:
In both cases, the single market and a two-factor model (Gunthorpe, 1997, Xu et al., 2014) expected return on day t is taken away from the actual realised stock return on day t using each models expected returns, resulting in a figure for our abnormal return on day t. This is carried out for each stock across the full 21-day event window, and a t statistic is obtained to determine if the abnormal returns are statistically significant.
As explained in the literature review, not all reactions to the announcement occur on the event day (t=0). Therefore, cumulative abnormal returns (CARs) and cumulative average abnormal returns (CAARs) are calculated for the full event window to capture the impact on shareholder value during the period, using the following formula:
As mentioned in our literature review, an analysis by event classification will be conducted to address our hypotheses, along with a secondary analysis of the events being broken down by total penalty experienced in a High-Low analysis.
included these in our main analysis and comment in the results section when not including these events. Any repeat offenders were also given their own event date and treated as their own separate event.
Penalty Characteristics – Showing total figures for financial penalties collected 2009-2014 for repeat offenders and single offenders during the period.
Repeat offender Total no.
Millions ($)
Non-financial
Johnson & Johnson 7 2,439 -
Pfizer Inc. 5 18 - Abbott Laboratories 5 2,371 2 Omnicare Inc. 4 226 1 CVS Health 4 33 - Novartis AG 4 496 1 Sanofi SA 3 227 -
Teva Pharmaceutical Industries
Ltd. 3 44 -
Tenet Healthcare Corp 3 45 -
Forest Laboratories Inc. 3 477 1
Mylan Inc. 2 398 -
Amgen Inc. 2 787 -
Boston Scientific Corporation 2 326 -
AstraZeneca PLC 2 523 1
GlaxoSmithKline PLC 2 3,750 -
McKesson Corp 2 2,200 -
Novo Nordisk A/S 2 34 -
4. Results
In this section the results of whether or not shareholders punish pharmaceutical firms for unethical behaviour will be presented, with a number of robustness tests included throughout each section. The results and outputs of both the Market Model and the Two-Factor Model will be included for comparison purposes. Firstly, our main event study of the announcement dates will be put forward, followed by the degree of punishment by event classification (based on our definitions outlined in section 2.3. of this paper). Finally, a High-Low investigation will be conducted, relating to the financial fine experienced on the event date by each pharmaceutical firm.
4.1. Announcement effects: Event Study
Table 2.0 – Event Study – shows results for the full sample, with Average Abnormal Returns (AARs) significance *10%, **5% & 1%*** on day (t) shown for both models used. Cumulative Average Abnormal Returns (CAARs) are shown for both models over the event period.
Day Market Model Two-Factor Model Market Model Two-Factor Model Market Model Two-Factor Model
(t) AAR CAAR T-Stat
10 -0.22% -0.25% -1.11% -0.81% -1.7404 * -2.0938 ** 9 -0.18% -0.15% -0.89% -0.56% -1.4544 -1.1905 8 -0.02% 0.05% -0.71% -0.41% -0.1455 0.3833 7 -0.02% 0.04% -0.69% -0.46% -0.1008 0.2762 6 -0.27% -0.25% -0.67% -0.50% -1.4272 -1.3718 5 -0.04% 0.02% -0.40% -0.25% -0.2245 0.1336 4 -0.23% -0.18% -0.37% -0.27% -1.3023 -1.0153 3 0.36% 0.36% -0.13% -0.09% 2.5275 ** 2.6939 *** 2 0.00% 0.04% -0.49% -0.45% 0.0030 0.2499 1 -0.61% -0.58% -0.49% -0.50% -1.7372 * -1.7204 * 0 -0.16% -0.12% 0.11% 0.08% -0.5080 -0.4015 -1 -0.03% -0.03% 0.27% 0.20% -0.2499 -0.2641 -2 -0.04% -0.13% 0.30% 0.23% -0.3897 -1.1769 -3 0.19% 0.28% 0.35% 0.36% 1.1624 1.7915 * -4 0.05% 0.07% 0.15% 0.08% 0.3288 0.5057 -5 0.12% 0.02% 0.10% 0.01% 0.8097 0.1143 -6 -0.04% -0.11% -0.02% -0.01% -0.2172 -0.6557 -7 0.13% 0.14% 0.02% 0.10% 0.7034 0.7642 -8 -0.01% 0.06% -0.11% -0.04% -0.1005 0.4736 -9 -0.08% -0.08% -0.09% -0.10% -0.5696 -0.6020 -10 -0.01% -0.03% -0.01% -0.03% -0.0339 -0.0818
Figure 1.0 – Shows the AARs & CAARs from Table 2.0 for the Two-Factor Model only
Figure 2.0 – Shows the AARs & CAARs from Table 2.0 for the Market Model only
Both our models realise negative CAARs across all event windows (Table 3), with the Market Model consistently showing the more negative of the two across all four additional windows. This would be in line with our first hypothesis, if not only for the period surrounding the event instead of on the actual event date.
(-1, +1) -0.79% -0.73%
4.2. Unethical action classification
In this piece of secondary analysis we took three of the terms/definitions from section 2, Table 1.0, and sought to investigate how event classification could impact on the degree of punishment experienced. The three terms chosen were as followed: ‘Unlawful Promotion’, ‘Kickbacks’, and ‘Overcharging Government Health Programs’.
4.2.1. Unlawful Promotion
We can see positive AARs on the event day (t=0), although statistically insignificant. AARs for both models never exceed +/- 0.73% throughout the entire event window. Both models pick up statistically significant negative AARs on days t=6 0.73%, -0.64%) and t=10 (-0.33%, -0.35%) at the 0.05 level. Our Two-Factor Model again captures significant AARs not done so by the Market Model, t=-6, t=-4, significant at the 5% level. In Table 4 the CAARs for both models remain negative throughout the event window. On t=0, CAARs are similar to that of t=-10 meaning most of the momentum driving the negative CAARs of -3.25% & -2.57% occurs post event.
Table 4.0 – 42% of total events in sample contained Unlawful Promotion, below show Average Abnormal Returns (AARs) significance *10%, **5% & 1%*** on day (t) shown for both models used. Cumulative Average Abnormal Returns (CAARs) are shown for both models over the event period.
Day Market Model Two-Factor Model Market Model Two-Factor Model Market Model Two-Factor Model
(t) AAR CAAR T-Stat
10 -0.33% -0.35% -3.25% -2.57% -2.0039 ** -2.2867 **
9 -0.15% -0.13% -2.92% -2.22% -0.6340 -0.5625
8 -0.14% -0.04% -2.77% -2.09% -0.6699 -0.2175
7 -0.25% -0.18% -2.64% -2.06% -1.0179 -0.8565
5 -0.22% -0.14% -1.66% -1.24% -1.0142 -0.8321 4 -0.17% -0.07% -1.44% -1.10% -0.6948 -0.2633 3 0.25% 0.23% -1.28% -1.04% 1.0516 1.1033 2 -0.19% -0.16% -1.52% -1.26% -0.6079 -0.4877 1 -0.38% -0.26% -1.33% -1.11% -1.3055 -1.2211 0 0.16% 0.24% -0.95% -0.85% 0.2329 0.3694 -1 -0.13% -0.20% -1.11% -1.09% -0.6274 -1.1792 -2 0.02% -0.10% -0.98% -0.89% 0.1091 -0.6541 -3 0.33% 0.50% -1.00% -0.80% 1.0796 1.7720 * -4 -0.28% -0.26% -1.32% -1.29% -1.5667 -2.1261 ** -5 0.07% -0.02% -1.04% -1.04% 0.3486 -0.1151 -6 -0.22% -0.40% -1.11% -1.01% -1.1808 -2.2606 ** -7 -0.13% -0.09% -0.89% -0.61% -0.6855 -0.5374 -8 0.10% 0.23% -0.76% -0.52% 0.3628 0.9705 -9 -0.16% -0.07% -0.85% -0.75% -0.7492 -0.3677 -10 -0.69% -0.68% -0.69% -0.68% -1.0320 -1.0213
Both our models realise negative CAARs across all but one of the event windows (Table 5), with the Market Model again showing the more negative of the two.
Table 5.0 – Unlawful Promotion - States multiple Event Window Cumulative Average Abnormal Returns (CAARs) for both models used on Unlawful Promotion sample, ranging from (t-10, t+10) down to (t-1, t+1).
CAAR Market Model Two-Factor Model (-10, +10) -3.25% -2.57% (-7, +7) -1.88% -1.54% (-5, +5) -0.55% -0.23% (-3, +3) 0.05% 0.26% (-1, +1) -0.35% -0.22% 4.2.2. Kickbacks
Table 6.0 – 33% of events in sample contained Kickbacks, below show Average Abnormal Returns (AARs) significance *10%, **5% & 1%*** on day (t) shown for both models used. Cumulative Average Abnormal Returns (CAARs) are shown for both models over the event period.
Day Market Model Two-Factor Model Market Model Two-Factor Model Market Model Two-Factor Model
(t) AAR CAAR T-Stat
10 -0.12% -0.07% 0.04% -0.01% -0.5036 -0.3506 9 -0.19% -0.18% 0.15% 0.05% -0.9407 -0.8437 8 0.06% 0.09% 0.34% 0.23% 0.2735 0.4535 7 0.24% 0.22% 0.28% 0.14% 0.8504 0.7836 6 -0.20% -0.21% 0.04% -0.08% -0.5133 -0.5590 5 0.22% 0.17% 0.24% 0.13% 1.2075 0.9522 4 -0.33% -0.39% 0.02% -0.04% -0.7710 -0.9492 3 0.37% 0.36% 0.35% 0.35% 1.4500 1.4068 2 0.20% 0.25% -0.03% -0.01% 0.7984 0.9694 1 -0.34% -0.30% -0.22% -0.26% -0.9053 -1.2550 0 -0.56% -0.46% 0.12% 0.05% -1.6572 * -1.4988 -1 0.23% 0.30% 0.68% 0.51% 1.2823 1.5006 -2 -0.08% -0.11% 0.45% 0.21% -0.3313 -0.4631 -3 0.28% 0.41% 0.52% 0.32% 1.1672 1.6930 * -4 0.36% 0.29% 0.24% -0.10% 1.3956 1.1528 -5 0.05% -0.06% -0.12% -0.39% 0.2227 -0.2483 -6 -0.34% -0.35% -0.17% -0.33% -0.8710 -0.9570 -7 0.07% 0.08% 0.17% 0.02% 0.3655 0.3476 -8 -0.17% -0.13% 0.10% -0.06% -1.1118 -0.9252 -9 0.28% 0.14% 0.27% 0.06% 1.2382 0.7997 -10 -0.01% -0.08% -0.01% -0.08% -0.0341 -0.3160
CAAR (-1, +1) in table 7 shows a negative relationship, with all others displaying positive CAARs. These results would seemingly prove our third hypothesis of there being no punishment for kickbacks in the financial markets.
Table 7.0 – Kickbacks - States multiple Event Window Cumulative Average Abnormal Returns (CAARs) for both models used on Kickbacks sample, ranging from (t-10, t+10) down to (t-1, t+1)
CAAR Market Model
(-10, +10) 0.04% -0.01%
(-7, +7) 0.18% 0.20%
(-5, +5) 0.41% 0.46%
(-3, +3) 0.11% 0.45%
(-1, +1) -0.67% -0.46%
4.2.3. Overcharging Government Health Programs
We can see positive AARs on the event day (t=0), although statistically insignificant, followed by the largest one day AAR (-1.55%) of our analysis, despite being insignificant on all levels. Both models pick up statistically significant positive AARs on days t=3 (0.59% & 0.51%) at the 0.05 level.
Table 8.0 – 32% of events in sample contained Overcharging Government Health Programs, below show Average Abnormal Returns (AARs) significance *10%, **5% & 1%*** on day (t) shown for both models used. Cumulative Average Abnormal Returns (CAARs) are shown for both models over the event period.
Day Market Model Two-Factor Model Market Model Two-Factor Model Market Model Two-Factor Model
(t) AAR CAAR T-Stat
-6 -0.04% -0.09% 0.71% 0.72% -0.1871 -0.4030
-7 0.32% 0.36% 0.75% 0.81% 0.6483 0.7244
-8 0.19% 0.20% 0.42% 0.45% 0.5396 0.5824
-9 -0.25% -0.28% 0.24% 0.25% -0.8328 -0.9120
-10 0.49% 0.52% 0.49% 0.52% 1.5113 1.8234 *
In Table 9 the CAARs for both models remain positive for event windows, except (-1 +1). On t=0, CAARs are 1% higher than t=10, mostly driven by the -1.55% AAR immediately following the announcement date.
Table 9.0 – Overcharging Government Health Programs - States multiple Event Window Cumulative Average Abnormal Returns (CAARs) for both models used on Overcharging Government Health Programs sample, ranging from (t-10, t+10) down to (t-1, t+1) CAAR Market Model Two-Factor Model (-10, +10) 0.78% 0.74% (-7, +7) 0.65% 0.51% (-5, +5) 0.22% 0.17% (-3, +3) 0.03% -0.07% (-1, +1) -1.20% -1.17%
Combining our results from 4.2 we see that (as per hypothesis two) pharmaceutical firms appear to see a penalty from shareholders for behaviour directly related to consumer behaviour (unlawful promotion) and relatively no significant penalty for actions not directly related to the consumer (overcharging government health programs & kickbacks).
5. Discussion, Limitations & Future Research
are also in a position to comment of the efficiency of the pharmaceutical industry. The relevance of our aim centres on a recent change in the approach of tackling illegal and unethical behaviour within the industry, potentially leading to a cost-benefit approach to penalties and fines (Girard, 2008). From our results we can begin to address our hypotheses outlined in section 2 in more detail, along with some of the topics surfacing in light of our results, potential limitations, and finally what future research could address in light of our paper.
The classification of unethical actions under our ‘Violations Definitions’ in Table 1.0 allowed us to analyse by act, how shareholders react to different types of announcements. Hypothesis two sought to address if firms are penalised more so for behaviour directly related to the welfare of their consumers than procedural violations related to regulations. Unlawful Promotion directly endangers consumers, and we found large negative CAARs (-3.25% & -2.57%) for these events using both our models, in which AARs remain negative following an announcement. If we compare these figures to the results found analysing the CAARs of Kickbacks (0.04% & -0.01%) or Overcharging Government Health Programs (0.78% & 0.74%) over the same event window, there is a stark contrast. From our findings in section 4.2. we can infer that shareholders do tend to punish firms more so for unethical behaviour directly related to consumer’s wellbeing like Unlawful Promotion.
on confirmation of the settlement to the public there could be some uninformed shareholder reaction. Xu et al. (2014) show how the degree of media coverage has an impact on the market values of firms, and that those with a lot of media coverage see greater losses in shareholder wealth after an environmental violation. This may also play a role in our results; the degree of public awareness to these unethical actions is not examined across the six years, and data limitations prevents us from speculating further. But one could suggest that the unethical act of promoting off-label uses of drugs (and the related damage on a societal level) could see more media coverage and therefore see greater losses in shareholder wealth, in line with our findings.
It goes beyond the scope of this paper to investigate whether firms in the pharmaceutical industry preemptively time the release of such announcements or not, but it is not unreasonable to speculate this may happen for certain announcements, and could be investigated in future research. There is of course the possibility that the sensitivity to unethical behaviour within the pharmaceutical just is not as high when compared to other studied industries. During the paper by Gunthorpe (1997), the author found that allegations of unethical business practices were not confined to specific industries where they could be considered standard business practices. We do find differences in our unethical behaviours.
non-existent. Future research could seek to expand on the data issues, and similarly the event day selection process. One could utilise the frequently used method of adapting the first date the event is mentioned in the WSJ. Although, one could argue that sometimes these are only ‘speculative information’ articles and not official publications (like those from the DOJ or the company themselves). Nonetheless, it is reasonable to assume, and supported by the literature, that shareholders react to even the allegation of unethical actions and therefore testing using this method would indeed provide more insight into the industry and ethics.
negative news in the pharmaceutical industry could show interesting findings.
6. Appendix
Full Penalty Characteristics – Showing by year (descending) company name (parent company if applicable), confirmed event date, type of unethical act and total figures for financial penalties collected 2009-2014. Company name, unethical act and penalty figure confirmed through Department of Justice press release portal (or company press release where applicable).
Company Name Event
Date Unethical Act
Penalty (millions $)
Eli Lilly & Co 15/01/09 Unlawful Promotion 1,415
Johnson & Johnson 19/02/09 Unlawful Promotion Complaint
Forest Laboratories Inc. 25/02/09 Kickbacks & Unapproved Use Complaint
Quest Diagnostics inc 15/04/09 Unlawful Promotion 302
Novo Nordisk A/S 11/05/09 Kickbacks 9
Sanofi SA 28/05/09 Overcharging Gov Health
Programs 95.5
Pfizer Inc. 02/09/09 Unlawful Promotion 2,300
Mylan Inc. 19/10/09 Overcharging Gov Health
Programs 118
AstraZeneca PLC 19/10/09 Overcharging Gov Health
Programs 2.6
Johnson & Johnson 19/10/09 Overcharging Gov Health
Programs 3.4
Omnicare Inc. 03/11/09 Kickbacks 98
Teva Pharmaceutical
Industries Ltd. 03/11/09 Kickbacks 14
Spectranetics Corp 29/12/09 Unlawful Promotion, Illegal Dist,
Overcharging Gov. 5
Johnson & Johnson 15/01/10 Kickbacks Complaint
Atricure Inc. 02/02/10 Unlawful Promotion,
Overcharging Gov 3.76
Novartis AG 22/02/10 Overcharging Gov Health
Programs 3.5
Boston Scientific
Corporation 25/02/10 Concealing Study Findings 296
AstraZeneca PLC 27/04/10 Unlawful Promotion 520
Johnson & Johnson 29/04/10 Unlawful Promotion 81
Novartis AG 04/05/10 Unlawful Promotion 72
Forest Laboratories Inc. 15/09/10 Unlawful Promotion, Illegal Dist,
Overcharging Gov. 313
Overcharging Gov, Kickbacks
GlaxoSmithKline PLC 26/10/10 Poor Manufacturing Practices 750
Abbott Laboratories 07/12/10 Unlawful Promotion, Kickbacks 41
Abbott Laboratories 07/12/10 Overcharging Gov Health
Programs 126.5
Mylan Inc. 20/12/10 Overcharging Gov Health
Programs 280
St. Jude Medical Inc. 20/01/11 Kickbacks 16
Forest Laboratories Inc. 02/03/11 Unlawful Promotion, Illegal
Distribution 164
Johnson & Johnson 08/04/11 Kickbacks & Foreign Payments 70
CVS Health 15/04/11 Overcharging Gov Health
Programs 17.5
Cardinal Health inc. 21/04/11 Kickbacks 8
Merck KGaA 04/05/11 Kickbacks 44.3
Novo Nordisk A/S 10/06/11 Off-Label promotion 25
Johnson & Johnson 05/10/11 Off-Label Use 85
Pfizer Inc. 21/10/11 Unlawful promotion 14.5
Merck Sharp & Dohme 22/11/11 Unlawful promotion 950
Medtronic Inc. 12/12/11 Kickbacks 23.5
GE Healthcare Inc. 29/12/11 Overcharging Gov Health
Programs 30
Tenet Healthcare Corp 10/04/12 Overcharging Gov Health
Programs 42
Walgreens Pharmacy 20/04/12 Overcharging Gov Health
Programs 7.9
McKesson Corp 26/04/12 Overcharging Gov Health
Programs 190
Abbott Laboratories 07/05/12 Unlawful Promotion 1,500
GlaxoSmithKline PLC 02/07/12 Unlawful promotion, reporting,
false pricing 3,000
Pfizer Inc. 07/08/12 Foreign Bribery & Accounting
practices 60
Abbott Laboratories 02/10/12 Unlawful Promotion 699
CVS Health 15/10/12 Overcharging Gov Health
Programs 5
Pfizer Inc. 12/12/12 Off-Label Use 55
Sanofi SA 19/12/12 Kickbacks 109 Teva Pharmaceutical
Industries Ltd. 14/03/13 Environmental 2.25
Amgen Inc. 16/04/13 Kickbacks 24.9
Novartis AG 26/04/13 Kickbacks Complaint
Pfizer Inc. 30/07/13 Illegal Distribution, Unlawful
Promotion 490.9
PharMerica Corp. 09/08/13 Overcharging Gov Health
Programs Filed Suit
Boston Scientific
Corporation 17/10/13 Concealing Study Findings 30
Johnson & Johnson 04/11/13 Off-Label Marketing & Kick backs 2,200
CVS Health 02/12/13 Overcharging Gov Health
Programs 4.25
Sanofi SA 20/12/13 Overcharging Gov Health
Programs 22.28
Abbott Laboratories 27/12/13 Kickbacks 5.475
CareFusion Corp. 09/01/14 Kickback & Off-label Promotion 40.1
Tenet Healthcare Corp 19/02/14 Kickbacks Investigation
Endo Pharmaceuticals Inc. 21/02/14 Off-Label Marketing 192.7
Omnicare Inc. 27/02/14 Kickbacks 4.19
Teva Pharmaceutical
Industries Ltd. 11/03/14 Kickbacks 27.6
Astellas Pharma Inc 16/04/14 Illegal Promotion 7.3
Tenet Healthcare Corp 06/05/14 Overcharging Gov Health
Programs 2.5
Omnicare Inc. 25/06/14 Kickbacks 124.24
McKesson Corp 08/08/14 Poor Manufacturing Practices 18
Shire Pharmaceuticals LLC 24/09/14 Off-Label Marketing 56.6
CVS Health 26/09/14 Overcharging Gov Health
Programs 6
Vascular solution Inc. 13/11/14 Unlawful Promotion, Illegal
Distribution & Overcharging Gov Charged
Stryker Corp 08/12/14 Illegal Distribution 80
Table 10.0 – High-Low analysis – States multiple Event Window Cumulative Average Abnormal Returns (CAARs) for both models used on both High and Low samples, ranging from (t-10, t+10) down to (t-1, t+1)
High (>100m) Low (<100m) CAAR Market Model Two-Factor Model Market Model Two-Factor Model (-10, +10) -1.42% -1.09% -0.97% -0.68% (-7, +7) -1.51% -1.34% -0.15% 0.01% (-5, +5) -0.45% -0.26% -0.36% -0.23% (-3, +3) -0.38% -0.17% -0.24% -0.17% (-1, +1) -1.02% -0.94% -0.69% -0.62%
Table 11.0 – High-Low analysis - shows results for the High and Low samples, with Average Abnormal Returns (AARs) significance *10%, **5% & 1%*** on day (t) shown for both models used. Cumulative Average Abnormal Returns (CAARs) are shown for both models over the event period.
High (>100m) Day Market Model Market Model Two-Factor Model Two-Factor Model Market Model Two-Factor Model
(t) AAR T-Stat AAR T-Stat CAAR CAAR
10 -0.37% -2.4202 ** -0.44% -2.9634 *** -1.42% -1.09% 9 -0.17% -0.6496 -0.20% -0.8068 -1.05% -0.65% 8 0.20% 0.6495 0.30% 1.0888 -0.88% -0.45% 7 -0.49% -2.1102 ** -0.24% -1.2526 -1.08% -0.75% 6 -0.46% -1.4254 -0.56% -1.7907 * -0.59% -0.52% 5 0.06% 0.2577 -0.02% -0.1244 -0.13% 0.04% 4 -0.02% -0.0882 0.01% 0.0496 -0.19% 0.06% 3 0.46% 2.0130 ** 0.50% 2.7133 *** -0.17% 0.05% 2 -0.03% -0.1052 -0.03% -0.1426 -0.63% -0.46% 1 -0.15% -0.7327 -0.10% -0.5919 -0.60% -0.42% 0 -0.84% -1.5313 -0.70% -1.4050 -0.45% -0.32% -1 -0.03% -0.1223 -0.14% -0.7279 0.39% 0.38% -2 -0.01% -0.0704 -0.06% -0.4226 0.42% 0.52% -3 0.22% 0.7432 0.36% 1.3829 0.43% 0.58% -4 0.16% 0.6847 0.17% 0.7804 0.21% 0.22% -5 -0.27% -1.2722 -0.25% -1.1484 0.05% 0.05% -6 -0.01% -0.0391 -0.19% -1.0392 0.32% 0.30% -7 -0.11% -0.5560 -0.10% -0.5460 0.32% 0.49% -8 0.24% 0.6734 0.32% 0.9500 0.43% 0.59% -9 -0.17% -0.8159 -0.07% -0.3783 0.19% 0.26% -10 0.35% 1.0553 0.33% 0.9528 0.35% 0.33% Low (<100) Day Market Model Market Model Two-Factor Model Two-Factor Model Market Model Two-Factor Model
(t) AAR T-Stat AAR T-Stat CAAR CAAR
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