International Journal of Health and Economic Development, 1(2), 14-27, July 2015 14 Returns to shareholders in Acquisitions into the U.S. Pharmaceutical Companies Samra Chaudary Lahore School of Economics, Pakistan ch.samra@gmail.com Asif Sarwar American Bangladesh University, Bangladesh racky440@yahoo.com Abstract The paper unearths the shareholders wealth due to mergers and acquisitions of the acquirer U.S. pharmaceutical companies during the period of 2003-2008. This period is well known by sixth wave merger period of U.S. market. The study includes the sample size of 20 companies and employed event study (market model) methodology and positive approach to calculate the abnormal returns. The overall results suggest that, there are no significant abnormal returns for shareholders. The study also proposes the managerial and investors implications to identify if pharmaceutical companies do or do not create wealth for shareholders which is eventually helpful in decision-making. Keywords: Cross-border mergers and acquisitions, event study, acquirers returns Introduction Mergers and acquisition (M&A) have gained fame due to liberalization, globalization, technological developments& intense competitive business environment. U.S. pharmaceutical industry is one of the highly developing industries and has great effect on financial market. United States is one of the best and lucrative markets to start a research on mergers and acquisition.us pharmaceutical industry has advanced technology to use in their research and to make best quality medicine of the world. The giant pharmaceutical industry is mainly dominated by multinational companies and has larger and frequent alliance activities. This industry is growing faster because of U.S. government is helping pharmaceutical industry by rapid approval process and
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 15 helping for the basic research. According to US pharmaceutical industry report 2008-2009, in 2007 its total revenue was US$ 315 billion. Due to competition and patent threat pharmaceutical companies are merging for cost reduction and to extend their distribution channel and to invest more in research and development. The sixth merger wave is from 2003 and 2008. In 2006 more than $1 trillion expensed on M&A. Private equities and leverage mostly used in financing. Premiums paid during the sixth merger wave were significantly lower than in the past, implying more rational acquisition decisions. This merger wave ended in late 2007, because investors and corporate managers were worried about the mortgage backed security and credit markets. Also, because it could impact the economy and recession started in 2008 which also affected this wave. The study attempts to unearth the impact of M&A on shareholder s wealth and financial performance of the U.S. pharmaceutical companies. Moreover it will also compare the pre and post effect of firms performance of acquiring with the help of performance measurements tools to see if the companies were able to improve their R&D performance. The study can help shareholders for decision making whether to invest in pharmaceutical. Investment companies and advisory firms will also be benefitted to advice their clients to make investments on the right times. Managers of the pharmaceutical companies will be aware about different effects, which might effect to their financial performance after merging with another company. Literature Review Extensive researches have been carried out whether acquisitions are wealth creating or wealth reducing events for acquiring shareholders and different empirical studies have shown different results. Target companies have positive effects on their financial performance due to M&A and there are negative abnormal returns or no returns on acquirer pharmaceutical companies (Hassan et al., 2007). Frederikslust et al. (1999) 52% of the bidding companies from their Dutch sample shows positive reaction to the shareholders wealth. On the other hand, 82% of the target companies have the positive impact on the share price. The research emphasis that 93% horizontal merger of the sample is the root cause of these results. Wong and Yin (2009),
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 16 found negative impact for target companies and positive results for bidder companies by analysing Asian companies. Rawani et al. (2010) found positive market reaction after M&A announcement for both target and bidding shareholders. However, the target shareholders earn significantly higher CAARs than bidding shareholders. Mann and Kohli (2011) found that, both domestic acquisitions and cross-border acquisitions have created value for the target company shareholders on the announcement. Bassen et al. (2010) examined German acquisitions in the U.S. from 1990 to 2004 and found positive effect of cross-border mergers and acquisition on the acquiring companies. Dunbolt (1999) while using six different models found significant evidence for target companies in cross-border acquisitions. Hassan et al. (2007) conducted a research on U.S. Pharmaceutical industry with the event window of 341 trading days; 240 days as estimation period, and 61 days as test period (30 days before and after the announcement). The empirical results include some evidence for short term and long term cumulative abnormal returns for the U.S. based targets and foreign based target. The positive shareholders wealth s results were not significant in short term. Overall results indicate that there are no abnormal returns for the U.S. pharmaceutical acquiring firms that merge with U.S. based target and foreign based target for both long term and short term. The study also examined the impact of mergers and acquisition on the profitability and operating performance in the long term. The data was analysed for ten years (5 years before and 5 years after the M&A). Improvement was found in ROA and cash flows. However they showed that greater profitability and improved efficiency are more likely to be achieved through acquisition than through mergers. Mishra and Chandra (2010) conducted research on Indian pharmaceutical companies in the period of 2000-2008and found no significant impact of mergers and acquisition in the profitability of the pharmaceutical companies. In addition, there is impact on in-house R&D and the profitability of a firm depends directly on its size, selling efforts and exports and imports intensities but inversely on their market share and demand for the products. Bhabra and Huang (2013) found no change in operating performance from pre to post acquisition period for the bidders. Andrade et al. (2001) found that mergers improve efficiency and that the gains to
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 17 shareholders at announcement accurately reflect improved expectations of future cash flow performance. But, the underlying sources of gains from mergers have not been identified. Hall (1999) also found that, those companies who usually merged with other companies gets a boost in their growth compare to those companies who did not merge. Capron and Pistre (2002) found that acquirer companies get abnormal returns when they transfer their resources to the target companies. On the other hand, there are no abnormal returns when these acquirer companies receive resources from the target companies. Franks et al. (1997) suggest that shareholders in acquired companies have enjoyed abnormal returns averaging 26% during the four months prior to the completion of a merger. Evidence also showed that when a firm merged with another company their overall performance goes up. Danzon et al. (2007) found that for large pharmaceutical firms that merged, they experienced slower operating profit growth after the second year. Agrawal et al. (1992) in U.S. markets also found negative impact on acquiring firms due to mergers about 10% over the five-year post merger period. Data & Methodology The announcement dates of the Pharmaceutical companies were extracted from the database; Thomson one Banker. Since Thomson One Banker does not enclose financial data, therefore the data was then extracted from the Datastream. Furthermore, only completed M&A deals have been included in the sample. The criteria to finalise the sample is to check data availability in the Datastream which narrows down the number of acquisitions to 20 acquirer companies from 2003-2008 (during sixth U.S. merger wave). Among them 17 (85%) target companies are U.S. based and 3 (15%) of them are foreign companies. S&P 500 index and share prices were collected from Yahoo finance. The objective of this paper is to find the abnormal returns through the acquisitions into the U.S. Pharmaceutical companies hence the research question is; If there are any abnormal returns for the acquirers through acquisitions into the U.S. Pharmaceutical companies?
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 18 Event study methodology is employed which attempts to measure the abnormal returns in the stock prices of the publicly traded companies that occur in conjunction with an event (Warner and Brown, 1980, 1985). Strong (1992) proposed that the market model has probably been the most well-liked model and is used as a point of reference in event studies. The intention of the event study methodology is to evaluate observed returns of the stock around the announcement period with the performance of the market index. The increase of security prices after the announcement of a merger thus shows how positive the market evaluates the effects of the merger on the profitability of the firm (Aiginer and Tichy 1990). The event window decides the number of days for which the abnormal return can be measured that is caused by the event. If the event window is too short, there is possibility of not catching the consequence of the event. The event window in this research is set to sixty one; thirty days prior to and thirty days after the announcement date. Daily stock returns are calculated for the event window of sixty one days. The estimation period is used to assess the values of alphas and betas of the stocks. Hence the period should be sufficiently long to produce a representative measure of returns and also to reduce the biasness but too long estimation period can also bring biasness in the estimation with information from other events or changes in the general situations of the firms (MacKinlay, 1997). The estimation period of the study is kept to 150 trading days whereas the weekends are excluded and the thirty days of the event window are kept separate from the estimation period. This is done to make sure that the normal returns do not get affected by event related returns. Hence the timeline of the event study is set equal to 211 days. Where -180 days to -31 total 150 days is the estimation period and 30 days before the merger announcement (-30 days), merger announcement date, which is t=0 and 30 days after the merger announcement date (+30) total 61 days is the test period. t= 0 represents the announcement date, T1-T2= Event Window and T0-T1= Estimation Period of 150 days. The computation of daily return for each company and for the market index is calculated as follows: R it = ClosingSharepriceofthecurrentdate Closingsharepriceofthepreviousday ClosingSharepriceofthePreviousdays
R mt = International Journal of Health and Economic Development, 1(2), 14-27, July 2015 19 ClosingMarketpriceofthecurrentdate ClosingMarketpriceofthepreviousday ClosingMarketpriceofthePreviousdays The abnormal return is the actual ex-post return of the share over the window period subtracted the normal return of the firm over the same window period. The normal return can be defined as the expected return without conditioning on the event taking place (MacKinlay, 1997). The market model parameters are obtained in the estimation period and used in the event period to determine the expected return. The abnormal returns ARit can now be possibly calculated in the event window by deducting the actual return Rit, with the expected return, as shown in the equation below; For any firm i and event date t the abnormal return is AR it = R it E(R it ) (i) Where AR it represents abnormal return in the event window at day t, R it represents actual return and E (R it ) represents normal returns. The assumption of market model is the linear relation between the market return and the share return. The model's linear design follows the assumption of joint normality of asset returns. Practically it is a well-built assumption and normally not likely to create any inconvenience since the assumption is empirically sound and the implication of the normal return models likely to robust to diverge from the assumption (Mackinlay 1997). An OLS regression has been executed to estimate the model parameters estimates of αi, βi the intercept and slope respectively, for each stock at every day in the estimation period. For any given security i the market model is R it = α i + β i R mt + ε it (ii) Where Rit= Returns on security i on day t, Rmt= Return on the market portfolio in the period t, ε it = the zero mean disturbance term, αi and βi are the parameter of the market model and are estimated by running an ordinary least-square regression over the estimation window. S&P 500 index is used for the market portfolio because it will enable to make a fair comparison between the required returns and the returns from top 100 companies. The market model signifies more perfection over the constant mean return model. By eliminating the section of the return that is associated with the
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 20 variation in the market's return, the variance of the abnormal return is decreased. This consecutively can lead to increase the capability of model to uncover the impact of event. This study uses the market model because it incorporates all three models i.e. mean adjusted model, market adjusted model and also constant mean return model. The advantage from using the market model will rely upon the value of R 2 of the market model regression. Higher the R 2 the greater is the variance reduction of the abnormal return, and the larger is the gain (MacKinlay, 1997). The notion of cumulative abnormal return (CAR) over the event window is employed in the study for the purpose of an overall conclusion of abnormal return in the event window. CAR (t1, t2) is the cumulative abnormal return (CAR) from t1 to t2. The CAR from t1 tot2 is the sum of the included abnormal returns, CAR i (t 1, t 2 ) = τ2 τ1=τ2 AR it (iii) For any period in the event window, CAR(t 1, t 2 ) = t 2 t=t 1 AR t (iv) The average cumulative abnormal returns are then calculated over the sub periods(-30, -1) (0, +30) (-30, +30)(- 25, +25) (-20, +20) (-15, + 15) (-10, +10) (-5, +5) and (-1, +1) and over the entire event window using the same method as that used to compute the CARs. Analysis and Results Abnormal returns for 20 acquiring pharmaceutical firms have been calculated for 30 days before the announcement, day of announcement and 30 days after the announcement. Then average abnormal returns have been taken for all of the companies for each of the days of the event window. Figure 1 depicts the average abnormal returns for the event window.
t-30 t-28 t-26 t-24 t-22 t-20 t-18 t-16 t-14 t-12 t-10 t-08 t-06 t-04 t-02 t0 t+2 t+4 t+6 t+8 t+10 t+12 t+14 t+16 t+18 t+20 t+22 t+24 t+26 t+28 t+30 International Journal of Health and Economic Development, 1(2), 14-27, July 2015 21 2.00% Average Abnormal Returns of the firms 1.00% 0.00% -1.00% -2.00% Average Abnormal Returns of the firms Figure-1: Average Abnormal returns of the Firms Table 1 summarizes the results of the abnormal returns achieved by the shareholders of acquiring pharmaceutical firms. First column represents the day starting from (t-30) to (t+30) days, second column represents the average abnormal returns of every day, and third column represents the significance of the results. Table1: Abnormal returns data for 61 days. Day Average Abnormal returns (AAR) P-value t -30 0.23% 0.672 t -29 0.55% 0.354 t -28-0.64% 0.149* t -27 0.67% 0.337 t -26 0.36% 0.544 t -25 0.95% 0.472 t -24-0.01% 0.983 t -23-0.13% 0.629 t -22 0.23% 0.273 t -21-0.80% 0.044** t -20 0.80% 0.088 t -19 0.57% 0.175* t -18-0.12% 0.672 t -17-0.20% 0.537 t -16-0.33% 0.281 t -15-0.96% 0.229 t -14-0.31% 0.492 t -13 0.32% 0.522 t -12-0.31% 0.465
t -11 0.43% 0.487 t -10-0.87% 0.024** t -09-0.43% 0.339 t -08 0.02% 0.962 t -07 0.69% 0.118 t -06 0.02% 0.967 t -05-0.31% 0.525 t -04-0.37% 0.297 t -03-0.06% 0.849 t -02 0.20% 0.664 t -01-0.05% 0.880 t 0 0.07% 0.920 t +1 0.29% 0.705 t +2-0.66% 0.174 t +3-1.37% 0.091 t +4-0.78% 0.107 t +5 0.13% 0.808 t +6 0.42% 0.333 t +7 0.95% 0.129 t +8 0.68% 0.198 t +9-0.06% 0.890 t +10-0.23% 0.469 t +11-0.24% 0.472 t +12-0.32% 0.356 t +13-0.56% 0.264 t +14 0.33% 0.462 t +15 0.00% 0.996 t +16 0.71% 0.135 t +17-0.13% 0.797 t +18 0.42% 0.265 t +19 0.63% 0.047** t +20-0.23% 0.489 t +21 0.28% 0.340 t +22 0.01% 0.981 t +23 0.07% 0.819 t +24 0.14% 0.737 t +25-0.25% 0.417 t +26-0.15% 0.712 t +27-0.48% 0.129* t +28 0.66% 0.438 t +29-0.20% 0.569 t +30-1.05% 0.182* International Journal of Health and Economic Development, 1(2), 14-27, July 2015 22
t-30 t-27 t-24 t-21 t-18 t-15 t-12 t-09 t-06 t-03 t0 t+3 t+6 t+9 t+12 t+15 t+18 t+21 t+24 t+27 t+30 International Journal of Health and Economic Development, 1(2), 14-27, July 2015 23 According to Table 1, pharmaceutical acquiring companies of U.S. got 0.07% return on the date of announcement,0.29% abnormal returns one day after the announcement which are not statistically significant. Abnormal return of 0.95% on (t+7) was observed which is highest abnormal return. 1.37% was the lowest level of abnormal returns in the event period that shareholder of the pharmaceutical companies as a whole got in (t+3) after the announcement date. Both the highest and lowest returns are insignificant. Taken as a whole the shareholders of U.S. pharmaceutical companies did not get abnormal returns during the event windows. It can be noted that except the seven days; (t-28), (t -21), (t-19) (t -10), (t+19), (t+27), (t+30) all the results are not significant in the test period. Overall It is proven that there are no abnormal returns for the acquiring pharmaceutical companies. Cumulative Abnormal Returns Analysis: In accordance with methodology cumulative abnormal returns has been calculated from abnormal returns data. Figure 2 represents the cumulative abnormal returns for the U.S. pharmaceutical companies for the 61 days event period. 0.04 0.03 0.02 0.01 0 Cumulative Abnormal Return -0.01-0.02-0.03 Figure-2: Cumulative Abnormal Returns
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 24 As seen from the figure the CAR movement is fluctuating. Starting from (t-30) to (t+1) there is a positive CAR which is fluctuating. CAR went down under zero on (t+1), which means negative until (t+18) of the event period. Highest level of CAR can be seen in (t+19), which is 2.78% in the entire event period. Then (t +4) is carrying -2.31% (after the announcement) which is the lowest CAR in the event period. After observing the cumulative abnormal returns of the event period it be said that merger announcement did not make any effect on share price after the announcement. It made abnormal returns on (t-20) of the announcement. Cumulative abnormal return for different sub-period and standard deviation has been calculated, which is given in Table 2. Table2: CARS of Event Sub-Periods Day CAR P- Value (-30) to (-1) 0.14% 0.939 (0) to (+30) -1.00% 0.736 (-30) to (+30) -0.79% 0.843 (-25) to (+25) -0.73% 0.838 (-20) to (+20) -1.22% 0.713 (-15) to (+15) -3.33% 0.254 (-10) to (+10) -1.71% 0.509 (-5) to (+5) -2.90% 0.113* (-1) to (+1) 0.32% 0.397 Notes: The above table reports CAR for bidder banks over for different set of event windows. Abnormal returns are estimated using the market model;ar it = R it E(R it ). For any given security i the market model is R it = α i + β i R mt + ε it, where α i and β i are estimated by running an OLS regression over the estimation window.car was calculated through CAR i (t 1, t 2 ) = τ2 τ1=τ2 AR it. *, **, and *** indicate statistical significance at 90%, 95% and 99% level of significance, respectively.
International Journal of Health and Economic Development, 1(2), 14-27, July 2015 25 First column of the Table 2 shows the sub-periods of the entire period. Second column depicts cumulative abnormal returns for the share of the average pharmaceutical companies followed by the significance of the CARs. It can be observed that considering sub periods (-30, +1) and from (-1, +1) the cumulative abnormal returns are insignificant positive, that means there are abnormal returns which are 0.14% and 0.32% respectively. Sub-period of (-15, +15) shows highest insignificant negative abnormal return. Overall statistical results support that there is no evidence of abnormal returns to the shareholders wealth creation of acquirer pharmaceutical companies as no significance can be seen in all the subsets. Discussion and Conclusion: This study was intended to find out the effect of mergers and acquisitions on acquiring pharmaceutical companies of U.S. during the sixth wave merger 2003-2008. The results indicate that there is no impact on acquiring pharmaceutical shareholders wealth. The overall results are not significant. The results of this study are consistent with the previous event study of Hassan et al. (2007) that, there is no impact on shareholders wealth of acquiring pharmaceutical industry of U.S. Braggion et al. (2009) also found the same results for acquirer companies of banking industry. Therefore it can be said that there is no abnormal returns in pharmaceutical industries of U.S. due to announcement of M&A. The trends of the deals of pharmaceutical companies show that they merged with other pharmaceutical companies, biotechnology companies and equipment & supply companies to increase their shareholders value, increase investment in research & development cost to invent new product, to increase market strength, to increase immediate revenue, to repay debt or pay dividend to shareholders, increase expertise. However, the announcement of the acquiring pharmaceutical companies does not increase shareholders value in the short term period. So further study need to be conducted based on long term effect of M&A and other key factors need to be explored behind this effect on pharmaceutical companies. With this study it is believed that it has contributed a better understanding of the pharmaceutical industries, as there are only a few studies have been done so far. So it can be use as a base for further research on pharmaceutical industry and also might be helpful for other industry research as well.
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