«Ye Cai Xuan Tian and Han Xia Journal of Economics & Management Strategy, Forthcoming August 2015 * Cai is with Leavey School of Business at Santa ...»
Location, Proximity, and M&A Transactions
Journal of Economics & Management Strategy, Forthcoming
Cai is with Leavey School of Business at Santa Clara University; Tian is with Kelley School of Business at Indiana
University and PBC School of Finance at Tsinghua University; Xia is with Jindal School of Management at the
University of Texas at Dallas. We thank the editor, Daniel Spulber, an anonymous coeditor, and two anonymous referees for valuable comments that helped to greatly improve our paper. We are grateful for Eitan Goldman, Robert Hauswald, Matthias Kahl, Anzhela Knyazeva, Merih Sevilir, Fei Xie, Ed Van Wesep, Jun Yang, and conference participants at the 2010 Financial Management Association meetings and 2010 Conference on Financial Economics and Accounting for helpful comments and discussions. We thank Ying Zhao for her able research assistance. This paper was previously circulated under the titles of “Does Firms’ Geographic Location Affect Its Takeover Exposure?” and “Firm Locations and Takeover Likelihood.” We are responsible for all errors and omissions.
Location, Proximity, and M&A Transactions
Key words: geographic location, proximity, takeover exposures, acquirer announcement returns, soft information JEL Classifications: G14, G30, G34
1. Introduction Takeover transactions represent a large and increasingly important economic activity, especially in recent years. According to Thomson Reuters, the mergers and acquisitions (M&As) announced in 2013 amount to a total transaction volume of $2.4 trillion.1 The large number of transactions in the takeover market has been puzzling given that M&As do not always create value for bidders (see, e.g., Moeller, Schlingemann, and Stulz, 2004; Betton, Eckbo, and Thorburn, 2008).
Why then do takeovers happen? The existing theoretical literature has proposed a range of agency, industrial organizational, and behavioral arguments that explain firms’ incentives to pursue takeover activities. These explanations include market power, empire building, market timing, operating efficiency enhancement, asset complementarity, acquisition of growth option, and hubris (e.g., Jensen, 1986; Roll, 1986; Jovanovic and Rousseau, 2002; Shleifer and Vishny, 2003; Rhodes-Kropf and Robinson, 2008; Levine, 2012).2 Given the prevalence of takeover transactions, an equally important question is which firms are more likely to become takeover targets and to get acquired. A number of studies explore various firm characteristics, including size, profitability, market valuation, insider ownership, institutional holdings, and banking relationships, that could influence a firm’s probability of becoming a takeover target (e.g., Stevens, 1973; Dietrich and Sorensen, 1984;
Palepu, 1986; Mikkelson and Partch, 1989; Ambrose and Megginson, 1992; Ivashina et al., 2009; Bayar and Chemmanur, 2012). In this paper, we focus on a previously untested firm characteristic—a firm’s geographic location—to explore how a firm’s urban (as opposed to rural) location affects its probability of becoming a takeover target and completing a takeover transaction. We further examine upon a takeover occurring, how the urban location of a target firm affects the acquirer’s shareholder wealth.
A firm’s geographic location plays an important role in M&As because acquisition deals involve a large amount of soft-information production and transmission (Coff, 1999). Better communication of soft information can help the acquirer and the target to mutually discover information-based synergies (e.g., collaborative research and development ventures) and hence See, for example, http://www.pwc.es/es/servicios/transacciones/assets/thomson-reuters-mergers-and-acquisitionsreview-2013.pdf.
A large number of empirical papers provide evidence testing the predictions of various theoretical models. For a comprehensive survey of this literature, see Betton, Eckbo, and Thorburn (2008) and Eckbo (2014).
create higher values for both parties (Uysal, Kedia, and Panchapagesan, 2008; Kang and Kim, 2008). However, unlike hard information that is largely tangible and easy to verify and communicate, soft information is difficult to codify and transmit (Petersen, 2004). The communication of soft information, such as evaluations of knowledge-based assets and managerial skills, demands an acquirer’s intensive interpersonal interactions with the target in social, civic, and business occasions (Uysal, Kedia, and Panchapagesan, 2008). This feature of soft information, in turn, makes the acquirer location and the target location important as they determine the accessibility between the two parties in an M&A transaction.
While the existing literature has examined the effect of geographical distance between an acquirer and a target on acquirer returns (e.g., Uysal, Kedia, and Panchapagesan, 2008), we focus on the target’s and the acquirer’s urban versus rural location. This focus is motivated by the notion that although proximity can affect the accessibility between the two parties, it is not the only determinant. A firm’s physical location (i.e., urban or rural areas), which determinates the easiness of transportation, can play an additional role in enhancing or hindering accessibility. We illustrate this intuition using the following example. Consider an acquirer located in Dallas, Texas, and two potential targets located in New York City (urban) and Topeka, Kansas (rural), respectively. Even though New York City is significantly farther away from Dallas (i.e., 1,548 miles) than from Topeka (i.e., 487 miles), New York’s urban location makes it much easier to travel for the Dallas acquirer.3 This easy access, in turn, facilitates the transmission of soft information and can generate a higher value for the Dallas acquirer, making the New York firm a more attractive target in despite of its longer distance. Hence, the role of the target’s urban location can function on top of the effect of proximity to affect the acquiring firm’s acquisition decisions and value creation.
In line with this intuition, we show that firms located in an urban area are more likely to receive a takeover bid and complete a takeover transaction as a target, and takeover deals involving an urban target create larger values for the acquirer (i.e., higher acquirer announcement returns), after controlling for the proximity between the target and the acquirer. More importantly, an urban location of the target firm significantly attenuates the negative effect of a Indeed, a typical aircraft flight from Dallas to Topeka requires at least one connection and lasts up to eight hours.
On the other hand, a nonstop flight from Dallas to New York City takes approximately 3.5 hours.
long distance between the target and the acquirer on value creation for the acquirer, a fact that is documented in the existing studies (see, e.g., Uysal, Kedia, and Panchapagesan, 2008).
In the above example, we further consider two scenarios: (1) the Dallas acquirer is located in the metropolitan area with easy access to Dallas’s major airline hubs, and (2) the Dallas acquirer is located in a Dallas suburb, which is a one-hour drive from the major airline hubs. It is intuitive that the advantage of the New York target’s urban location (in bringing easier access between the two parties) is more valuable in the second scenario than in the first, in which case the acquirer may already have easy access to the target to begin with. Consistent with this intuition, we find that the positive effect of the target’s urban location is indeed more pronounced when the acquirer’s location does not permit easy transportation to the target.
Taken together, these findings suggest a significant role of both the target and the acquirer locations in a takeover transaction, and this role functions on top of the effect of proximity. The economic magnitudes of these effects are also sizable. For example, a firm located in an urban area is 41.2% more likely to receive a takeover bid compared to a nonurban firm, and the acquirer’s five-day announcement abnormal returns with an urban target are 27 basis points higher than those with a nonurban target. In addition, while a one-standard-deviation increase (810 miles) in the proximity of the two parties lowers the acquirer announcement returns by 130 basis points, the target’s urban location attenuates this negative effect by 93%.
This attenuation effect is even more pronounced when the acquirer does not already have convenient access to the target.
Our paper is related to two strands of the literature. First, our paper contributes to the burgeoning literature on the role of geographic proximity and firm location in corporate finance.
This research has shown that geographic distance matters in various financial phenomena, such as bank lending (Petersen and Rajan, 2002; Berger et al., 2005), venture capital investment (Bengtsson and Ravid, 2009; Tian, 2011), capital structure and cash policy (Loughran, 2008;
Almazan et al., 2010), payout policy (John, Knyazeva, and Knyazeva, 2011), analyst coverage (Malloy, 2005; Bae, Stulz, and Tan, 2008), patenting (Jia and Tian, 2015), feedback along the supply chain (Chu et al., 2014), board information gathering (Alam et al., 2014), and board monitoring and advising services (Bennett, 2013).4 In the context of M&As, Uysal, Kedia, and Panchapagesan (2008) find that acquirer returns in local transactions are more than twice as high as those in nonlocal transactions. Kang and Kim (2008) show that block acquirers have a strong preference for local targets, and local block acquirers create synergies as they are more likely to engage in post-acquisition governance improvement. In addition to examining the role of geographic proximity between acquirers and targets, our paper reveals that a previously underexplored force—firm location, either urban or rural—can impact takeover transactions.
Second, our work adds to the recent literature that explores the determinants of a firm’s likelihood of being taken over. For example, Ivashina et al. (2009) investigate the effects of bank lending relationship on the probability of a borrowing firm becoming a takeover target.
Bodnaruk, Massa, and Simonov (2009) introduce the role of the stake of bidder’s advisory investment bank into this literature. Bayar and Chemmanur (2012) focus on private firms and find that certain firm and industry characteristics (e.g., industry competitiveness, opaqueness, private benefits of control, and venture capital backing) are related to a private firm’s acquisition likelihood. Our paper extends this stream of literature by showing that a firm’s geographic location is another important dimension of takeover determinants.
Our findings suggest that the effect of proximity on acquisition decisions and value creation shown in previous studies might not be monotonic. This effect could change interactively with the firm’s urban location or access to transportation. This implication could be extended to areas other than the setting of M&As (e.g., capital structure, payout policy, analyst coverage, venture capital investment, and bank lending).
The rest of the paper is organized as follows. Section 2 discusses the sample selection and summary statistics. Section 3 analyzes how the location of firms affects their likelihood of becoming an attempted and completed takeover target. Section 4 examines how the location of firms impacts value creation for acquirers, as well as for targets. Section 5 concludes.
Our paper is also broadly related to the literature that studies the role of board busyness, experience, monitoring, and advising based on both soft and hard information production (e.g., Coles, Daniel, and Naveen, 2008; 2012;
Faleye, Hoitash, and Hoitash, 2011, 2013; Fich and Shivdasani, 2006; Field, Lowry, and Mrktchyan, 2013).
2. Data and Sample Description Our sample comes from several different data sources. We obtain the initial sample of firm-year observations between 1990 and 2009, from the Compustat Industrial Annual Files. We exclude firms in financial and regulated utility industries (SIC 6000–6999 and SIC 4900–4999), as well as firms located outside of the United States. We then collect firm stock return data from CRSP, financial statement information from Compustat, analyst coverage data from the Institutional Brokers Estimate Systems (I/B/E/S), institutional ownership and blockholder data from the Thomson Financial 13F institutional holdings database, and corporate governance proxy variables from the RiskMetrics database. Next, we obtain information on mergers and acquisitions from the Securities Data Company (SDC) database. Throughout the paper, we refer to these transactions as either takeover transactions or M&A transactions and use the words “takeovers” and “M&As” interchangeably.