Takeover Protection and Firm Value
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Christian Andres
Abstract
We examine firm value consequences of anti-takeover regulation, exploiting the staggered announcement and implementation of an anti-takeover regulation in the U.K. We show that, on average, takeover protection increases firm value. This effect is partly driven by innovative firms expanding their R&D activities. However, the anti-takeover regulation also increases the value of less productive firms. Anti-takeover regulation could thus constrain highly productive firms from taking over low-productivity firms. Our results imply that, while takeover protection may stimulate innovation, it can distort the allocation of funds by preventing market share from moving from less efficient to more efficient firms.
Acknowledgements
For helpful comments and suggestions, we thank Christoph Engel (the Editor), an anonymous referee, Nihat Aktas, Yakov Amihud, Ettore Croci, Eliezer Fich, Marc Goergen, Garen Markarian, Patrick McColgan, Felix von Meyerinck, Maximilian Müller, Zinian Zhang, and seminar participants at the 25th Annual Meeting of the German Finance Association in Trier, the 2018 Conference on Empirical Legal Studies in Europe (CELSE) in Leuven, at Strathclyde Business School, at WHU – Otto Beisheim School of Management, at the HVB (UniCredit) finance seminar in Eltville, and at the PhD Workshop of the 24th Annual Meeting of the German Finance Association in Ulm.
Appendix A: Timeline of the events that led to the U.K. anti-takeover regulation
| February 9, 2010 | Kraft announces it is closing the Somerdale factory. |
| Speech by Roger Carr (former chairperson of Cadbury) | |
| urging more protection for U.K. firms. | |
| June 1, 2010 | The U.K. Takeover Panel announces the start of a |
| consultation period with respect to a potential anti-takeover regulation and explains that it is open minded on the issues. At this time, an anti-takeover regulation is unlikely to be announced or implemented (Shearman & Sterling LLP 2010). | |
| October 21, 2010 | Announcement of the anti-takeover regulation by the Takeover Panel. This is the first time a U.K. anti-takeover regulation is likely to be implemented (Gibson, Dunn & Crutcher LLP, 2010; Shearman & Sterling LLP, 2010; Gibson, Dunn & Crutcher LLP, 2011). |
| Total number of firms in cohort 1:670 | |
| Number of treated firms in cohort 1:485 | |
| Number of control firms in cohort 1: 185 | |
| July 21, 2011 | Final form of the anti-takeover regulation is published. This final form of the anti-takeover regulation is close to the initial announcement on October 21, 2010. |
| September 19, 2011 | U.K. anti-takeover regulation is implemented. |
| July 5, 2012 | Announcement of the expansion to all AIM-listed and |
| U.K.-incorporated firms (cohort 2). | |
| Total number of firms in cohort 2: 225 | |
| Number of treated firms in cohort 2: 70 | |
| Number of control firms in cohort 2: 155 | |
| May 15, 2013 | Final form of the expansion is published. |
| September 30, 2013 | The expansion to all AIM-listed and U.K.-incorporated |
| firms is implemented. |
| Incorporated in the U.K. | Not incorporated in the U.K. | ||
|---|---|---|---|
| Managed in the U.K. | Not managed in the U.K. | ||
| Main Market | Treated | Treated | Control |
| AIM | Treated | Control | Control |
| Incorporated in U.K. | Not incorporated in U.K. | ||
|---|---|---|---|
| Managed in U.K. | Not managed in U.K. | ||
| Main Market | – | – | Control |
| AIM | – | Treated | Control |
Appendix B: Variable definitions
| Independent variables | Intangibles | Intangible Assets/lagged Total Assets, such as goodwill, patents, copyrights, trademarks, licenses. |
| R&D | R&D expenses/lagged total assets. | |
| Innovative Firm | Dummy variable that equals 1 if the firm is smaller than the median firm and has positive R&D expenses and 0 otherwise. | |
| Target Takeover Probability | Likelihood of the takeover of a target firm, following Cremers et al. (2009). We model the probability of a firm becoming a target the next year via a logit specification. This specification is estimated by using several independent variables at the end of the previous year, such as Tobin’s Q, PPE, cash, block ownership, market capitalization, leverage, and return on assets. | |
| Sales Growth | One-year growth in sales. | |
| Acquirer in past 3 years | Dummy variable that equals 1 if the firm was an acquirer within the last three years and 0 otherwise. | |
| Ln(Assets) | Natural logarithm of Total Assets. | |
| Overinvestment | Dummy variable that equals 1 if a firm is prone to overinvestment and 0 otherwise. We follow Biddle et al. (2009) as well as Cheng et al. (2013) and use the magnitude of the residuals obtained from a firm-specific regression of investment on sales growth as a proxy for overinvestment. Firms are classified as overinvesting if their residual is larger than twice the standard deviation of their industry peers. | |
| High Productivity | We follow prior literature (Chemmanur et al., 2010, Cappellari et al., 2012, Kim and Ouimet, 2014, Krishnan et al., 2015) and define firm-level total factor productivity as the residual of a log-linear Cobb–Douglas production function. For each two-digit SIC code industry–year group, we regress value added (EBITDA+labor) on capital and labor proxied by fixed assets and wage expenses, respectively. Firms whose average residuals over 2 years are above the median of each 2-digit SIC code industry–year group are categorized as high-productivity firms. | |
| Outcome variables | Announced Bid | Dummy variable that equals 1 if there is a bid for a firm in the respective year and 0 otherwise. |
| Hostile Bid | Dummy variable that equals 1 if the bid is classified as hostile and 0 otherwise. | |
| All Cash Bid | Dummy variable that equals 1 if the method of payment is solely cash and 0 otherwise. | |
| Takeover Premium | Final offer for the target stock price four weeks prior to the M&A announcement, as reported by SDC Platinum, following Field and Karpoff (2002) and Officer (2003). | |
| Transaction Value/Total Assets | Transaction value to total assets of the fiscal year before the M&A announcement. | |
| CAR(−1, 1) | CAR for the event window (−1, 1), calculated from the Fama-French three factor model plus Carhart momentum factor |
This table defines our main variables. All continuous variables are winsorized at 1 % and 99 %.
Appendix C: Sample selection
| No. of Obs. after query | Query Description | |
| Cohort 1: | 2,239 2,115 | All LSE-listed firms with ordinary shares |
| Cohort 2: | ||
| Cohort 1: | 1,817 1,770 | Match to the Thomson Datastream/Worldscope sample based on ISIN. We drop closed-ended funds, equity exchange-traded funds, and global depository receipts. |
| Cohort 2: | ||
| Cohort 1: | 1,606 1,558 | We drop investment trusts and duplicate observations based on the Worldscope Permanent ID |
| Cohort 2: | ||
| Cohort 1: | 1,205 1,158 | We drop missing fiscal years, missing total assets, and missing firm age |
| Cohort 2: | ||
| Cohort 1: | 1,005 971 | We drop financial firms (SIC codes 6000–6999) |
| Cohort 2: | ||
| Cohort 1: | 878 859 | We drop firms with less than $10 million in total assets |
| Cohort 2: | ||
| Cohort 1: | 670 696 | We drop firms with missing stock price information or that are thinly traded (more than 50 % missing returns or more than 75 % returns of zero within the estimation window) |
| Cohort 2: | ||
| Cohort 1: | 670 225 | We drop observations of cohort 2 if they were treated in cohort 1 |
| Cohort 2: | ||
This table reports our sample selection process. Column (1) reports the number of observations after each query step. Column (2) describes the query step.
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Supplementary Material
The online version of this article offers supplementary material (DOI:https://doi.org/10.1515/rle-2018-0048).
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