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Erschienen in: Review of Quantitative Finance and Accounting 2/2017

12.09.2016 | Original Research

When do managers listen to the market? Impact of learning in acquisitions of private firms

verfasst von: Inga Chira, Luis García-Feijóo, Jeff Madura

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 2/2017

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Abstract

We study the influence of market signals and agency problems on the decision to cancel an announced acquisition. We find major differences between deals involving private vs. public targets. First, controlling for the value of expected synergies, acquisitions are less likely to be cancelled when the target is private rather than public. This finding supports learning rather than the alternative common-information hypothesis. Second, better manager-shareholder interest alignment makes the cancellation of a “bad” deal more likely only when the target is a private firm. This suggests bidder agency problems have a greater influence on acquisition outcome (i.e., learning) when the target is private. Third, cancellation is more likely for private targets when their post-announcement abnormal returns are low, especially if the method of payment includes stock. This indicates that it is important to control for bidder overvaluation when testing the managerial learning hypothesis. Overall, both the learning and agency hypotheses help explain observed differences in deal completion by target type.

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Fußnoten
1
Managerial ownership is commonly higher in private rather than publicly-traded firms, which reduces agency problems. In a sample of 51 acquisitions of private targets, Mantecon (2008) finds no connection between insider ownership in private targets and bidder announcement returns, except when the analysis is done at the CEO level. We focus on the impact of agency problems affecting publicly-traded bidders.
 
2
The literature does not control for post-announcement abnormal returns (Kau et al. 2008; Liu and McConnell 2013; Masulis et al. 2009). The exception is Luo (2005) who contends that proper control variables should increase the power of tests of the learning hypothesis. He uses post-announcement stock returns to control for bidder and target private information and for deal valuation changes between announcement and completion/cancellation. Luo’s sample excludes private targets.
 
3
Kau et al. (2008) do not report results separately by target status.
 
4
The broader literature has also investigated whether managers learn information from their peer firms’ valuation (Foucault and Fresard 2014) or whether managers rely more on the market information following a cross-listing (Foucault and Fresard 2012). A related, but different, strand of research investigates sequential acquirers’ “learning by doing” of (e.g., Aktas et al. 2013).
 
5
Ang and Kohers (2001) note that acquisitions of private targets are more likely to be perceived as value-enhancing probably because they are less driven by adverse managerial incentives.
 
6
Bond et al. (2010) also predict managers follow a cost-benefit analysis when deciding to take a corrective action and cancel a “bad” deal.
 
7
Luo (2005) estimates SYNERGY from the combined announcement abnormal return using an iterative process. Theoretically, estimating SYNERGY is important to distinguish the learning hypothesis from the hypothesis that the market announcement reaction is influenced by investors’ estimate of the deal completion probability (“probability-feedback”). In our case, however, we do not follow Luo’s approach for two reasons. First, Kau et al. (2008) argue that the approach of including control variables is more appropriate than the iterative approach when examining other hypotheses besides learning (e.g., agency problems). Second, from a practical standpoint, one of the two merging companies in our sample is not publicly traded. Thus, we measure SYNERGY using the announcement abnormal returns for the publicly-traded bidder. This approach has been commonly used in the related literature. We acknowledge our results cannot distinguish between learning and the probability-feedback hypothesis.
 
8
We do not include financial firms because the industry is heavily regulated and hence both the nature of the acquisitions and the learning process is likely to be different from the rest, less heavily regulated industries. Fuller et al. (2002) and Liu and McConnell (2013) also exclude financial firms and utilities.
 
9
Table 1, Panel A, reports statistics based on the sample we use in the subsequent regression analysis. For the initial sample of announced deals in SDC (without any filters), 6.58 % of deals involving a publicly traded target and 3.40 % of deals involving a private target were canceled. Proportions for the two samples are significantly different at the 1 % level using both parametric and non-parametric (i.e., Wilcoxon rank-sum) tests.
 
10
SIC codes 3571, 3572, 3575, 3577, 3578 (computer hardware), 3661, 3663, 3669 (communications equipment), 3674 (electronics), 3812 (navigation equipment), 3823, 3825, 3826, 3827, 3829 (measuring and controlling devices), 4899 (communication services), or 7370, 7371, 7372, 7373, 7374, 7375, 7379 (software).
 
11
We do not include variables measuring the presence of a Toehold or a formal pre-merger agreement because the variables only affect the public target subsample.
 
12
We also collect data on institutional ownership of bidder’s shares and investigate the impact of adding the variable INSTITUTIONAL as an alternative/additional control variable. We find that INSTITUTIONAL is never significant, as an additional control or when used as an alternative to MONITOR.
 
13
We thank an anonymous reviewer for suggesting we perform the model comparison.
 
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Metadaten
Titel
When do managers listen to the market? Impact of learning in acquisitions of private firms
verfasst von
Inga Chira
Luis García-Feijóo
Jeff Madura
Publikationsdatum
12.09.2016
Verlag
Springer US
Erschienen in
Review of Quantitative Finance and Accounting / Ausgabe 2/2017
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-016-0599-4

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