Valuation waves and merger activity: The empirical evidence

Valuation waves and merger activity: The empirical evidence

Matthew Rhodes-Kropf, David T. Tobinson, S. Viswanathan

Journal of Financial Economics 77 (2005) 561-603

Presenter: Fangzhou "Ark" Shi


This paper test the empirical predictions of Rhodes-Kropf and Viswanathan (2004, henceforth RKV) and Shleifer and Vishny (2003, henceforth SV), and find strong support for the idea that misevaluation shapes merger activity. They show that misevaluation affects the level of merger activity, the decision to be an acquirer or target, and the transaction medium. To guard against the possible alternative interpretations for their findings, they run a battery of empirical horse races between misevaluation and standard neoclassical explanations of takeover.

[Theoretical Background]

Misevaluation has a market- or sector-wide component as well as a firm-specific component. The target’s and bidding firm’s private information tells them whether they are over- or undervalued, but they can not separately identify the sources of the misevaluation. A rational target correctly adjusts bids for potential overvaluation but, as a Bayesian, puts some weight on high synergies as well. When the market-wide overvaluation is high, the estimation error associated with the synergy is high, too, so the offer is more likely to be accepted. Thus, when the market is overvalued, the target is more likely to overestimate the synergies because it underestimates the component of misevaluation that it shares with the bidders.

Inefficient capital markets and differences in managerial time-horizons are the key drivers of merger activity. They hypothesize that short-run managers sell their firm for stock in a long-run manager’s firm when both firms are overvalued, even though the transaction price gives the short-run manager less than he knows his firm will be worth in the long run. The short run manager then sells his stock. The market is assumed to be irrational and therefore does not react to this deception or exploitation.


The sample includes all merger activity between publicly traded bidders and targets listed on the Securities Data Corporation (SDC) Merger and Acquisition Database between 1978 and 2001.

Table 1 reports the time series of merger announcements over our sample.
Table 2 provides a comparison of these summary statistics based on whether or not a firm was involved in a merger and, if so, whether it was an acquirer or a target. The market to book ratios for firms involved in mergers are considerably higher than those for non merger firms. M/B is significantly higher for acquirers than for targets. However, average M/B ratios for targets are statistically large r than for nonmerger firms.
Table 3 shows verbal descriptions along with firm counts and aggregate valuation and merger statistics. The firm-counts indicate that sector-year regressions do not suffer from small sample problems.


1.Decomposing market to book

Both SV and RKV implicitly suggest that:

Market to book ≡ Market to value + Value to book
m – b ≡ (m – v) + (v - b) expressed in logarithms
RKV takes the breakdown of m – b further to equation (3)
The first term is the difference between market value and fundamental value conditional on time t and sector j valuation effects.
The second component is time-t fundamental value to long-run value. Call this time-series sector error, because the function captures sector-specific valuation that does not vary over time.
The final component is the difference between long-run value and book.

2.Decomposing market to book

The strategy is to impose identifying restrictions on equation (6)
Model 1
Expected future ROE is a constant multiple of expected future discount rates.
Book equity is expected to grow at a constant rate over time.
Firms are priced against the average multiples for firms in that industry-year.
equation (7), (8), (9), (10)

Model 2
Expected future ROE is a constant multiple of expected future discount rates.
Book value and net income are expected to grow at a constant rate over time.
Firms are priced against the average multiples for firms in that industry-year.
equation (11), (12), (13), (14)

Model 3
Expected future ROE is a constant multiple of expected future discount rates.
Book value and net income are expected to grow at a constant rate over time.
Firms are priced against the average multiples for firms in that industry-year.
Firms with higher or lower than industry-average leverage have a different cost of capital, forcing them to differ from industry average multiples.
equation (15)

Table 4 Summary
There is less time-series volatility in the loadings on accounting variables for each industry than on the α0 terms, however, which suggests that while discount rates and growth rates vary a great deal across industries, they are less variable within industries over time.

[Prediction and test]

1.Relative value predictions

In both SV and RKV models, overvaluation leads to mergers.

SV: The overvalued short-run managers wish to sell out while their stock is overvalued. The acquirer is also overvalued because only long-run managers whose companies are more overvalued have room in their stock price to overpay for a target that is also overvalued and still make money in the long run.

RKV: If the bidding firm has a large firm-specific overvaluation then it is more likely to win because the target cannot fully distinguish between a large synergy and a large firm-specific error. Furthermore, if the market or sector is overvalued, then the target is more likely to accept an offer because, although the target makes the correct adjustment for potential market or sector overvaluation, as a Bayesian, the target puts some weight on high synergies as well. Therefore, an overvalued market leads to an overestimation of the synergies.

Empirical Prediction 1 Overvalued firms use stock to buy relatively undervalued firms when both firms are overvalued.
Empirical Prediction 2 Overall merger activity will be higher in overvalued markets. On average, firms in overvalued sectors should use stock to buy firms in relatively less overvalued sectors.

SV: Firms should use only cash to buy an undervalued firm because there is no role for true synergies. Stock-financed deals are more likely to be completed when acquirers are more overvalued, therefore cash acquirers on average should be less overvalued than stock acquirers.

RKV: Cash targets should be less overvalued than stock targets but could still be overvalued if high synergies outweigh the overvaluation. Stock-financed deals are more likely to be completed when acquirers are more overvalued, therefore cash acquirers on average should be less overvalued than stock acquirers.

Overall the theories suggest that cash mergers are driven by undervaluation or synergies or both, while stock mergers are driven by overvaluation.

Empirical Prediction 3 Cash targets are more undervalued than stock targets. Cash acquirers are less overvalued than stock acquirers.

Firm specific error should be lower for targets than acquirers. But the total of firm-specific and time-series sector error for firms in mergers should be greater than firms not involved in mergers. Cash targets should be more undervalued than stock targets, and cash acquirers should be less overvalued than stock acquirers.

Table 6 provides strong support for the central predictions of SV and RKV. It shows that merger firms are more overvalued than nonmerger firms, that bidders are more overvalued than targets, and that method of payment determines whether a target is over- or undervalued. In cash acquisitions, targets are undervalued on average. In stock acquisitions, targets are overvalued. These latter findings support the idea that correlated misvaluation leads overvalued targets to accept takeover bids from overvalued bidders precisely because they overestimate the expected synergies.

New findings: high M/B buys low M/B, but low long-run value to book buys high long-run value to book.

Table 7 Robustness check
Table 8 Additional robustness checks by showing that results hold across all transaction size. Also, the table removes the possibility that the decomposition results follow mechanically from differences in m-b across targets and bidders.

2.Merger intensity prediction


Merger activity should be more likely conditional on high valuation errors.
SV: The greater a firm’s overvaluation, the more likely it is to win the bidding for a target.
RKV: The greater a firm’s overvaluation, the more likely it is to win the bidding for a target. The probability of being a target should increase with sector overvaluation.
Firm Level:
Empirical Prediction 4 Increasing misvaluation increases the probability that a firm is in a merger, is the acquirer, and uses stock as the method of payment.
Sector Level:
Empirical Prediction 5 Increasing sector misvaluation increases merger activity, and the use of stock as method of payment, in that sector.

Table 9
Panel A: No matter which model they use, firm-specific error and time-series sector error have a positive and statistically significant effect on the probability that a firm is involved in a merger, while long-run value to book has a negative, significant effect. Introducing year fixed effects eliminates the significance of the sector valuation error, but neither the firm-specific error nor the long-run value to book is affected. These findings hold across each of the three models.
Panel B: A firm is much more likely to be an acquirer if it has higher firm-specific or time-series sector error. Increasing long-run value to book decreases the probability that a firm is an acquirer. These results are highly statistically significant across each of the three models. Decomposition produces much stronger results.
Panel C: High ln(M/B) firms are more likely to use stock. Each element of the decomposition has a positive, significant affect on this probability. This supports the findings of Martin (1996), which relates q to method of payment. It also supports the predictions of RKV and SV.

Above all, these findings show that positive firm-level deviations from industry pricing increase the probability that a firm is involved in a merger, that a firm is an acquirer, and that the acquisition is financed with stock. Thus, this table offers strong support for Empirical Prediction 4.

Table 10
Panel A: We cannot rule out the alternative explanation that some external factor such as deregulation or industry consolidation is responsible for both changes in overall ln(M/B) and changes in merger activity. While there are spikes in overall, economy-wide merger activity, these spikes do not explain away the relation between sector-level merger activity and sector-level valuation error. Fixed effects are capturing more than just localized spikes in merger activity.
Panel B: The results largely mirror the findings from Panel A. Results indicate that industries experience valuation-specific merger waves that differ from the overall, economy-wide trends in merger activity.

[Horse Race between Competing Theories of Merger Activity]

New Classical Explanation:
Mergers are an efficient response to reorganization opportunities that arise as a result of some underlying economic event. The economic shock in question could come from a variety of sources: industry overcapacity, the advent of a new technology, changing regulatory attitudes, or changes in access to capital markets that alter the optimal operating scale of firms. Explanations along these lines could account for some of our findings if mergers cluster when opportunities for reorganization are rich, which in turn are periods of high valuation because markets bid up prices in anticipation of the restructuring.

1.Comparing failed and successful mergers.

Misvaluation: We expect misvaluation levels to be higher in completed deals, and lower in failed deals.

Table 11:
The Q difference between bidder and target is higher in failed deals, not in successful deals. However, the absolute valuation levels are lower in failed deals. Failed deals have lower misvaluation, not higher misvaluation. Long-run q is higher in failed deals than in successful deals.
This cross-sectional horse race speaks against two alternatives.
1. Efficient asset redeployment is unlikely to be responsible for our findings, because Q dispersion is higher in failed deals than in successful ones. Instead, misvaluation seems to be at work, because overall valuation levels are higher in successful than in failed bids, and more of the level is attributable to misvaluation in successful deals as well.
2. It seems unlikely that our analysis is simply capturing ex ante valuation differences that vanish between the announcement and consummation of the merger, because the overall misevaluation level is higher in deals that go through than in ones that are withdrawn.

2.Merger intensity

Tobin's Q
If the reorganization story were at work, we would expect Q dispersion to predict merger intensity and to drive out our measures of misvaluation.

Table 12
The short-run valuation dynamics that our decomposition captures are not being driven by the fact that the market anticipates reorganization opportunities and compounds them into prices.
Q dispersion predicts merger activity only in the low valuation subsample.
While Q dispersion could reflect some underlying economic force that drives merger activity, many mergers occur during periods of high misvaluation that are unrelated to these forces. The large and statistically significant loadings on sector misvaluation suggest that misevaluation drives merger activity. The fact that Q dispersion works in times of low misvaluation, but not high misvaluation, indicates that misvaluation is not simply capturing liquidity.

Economic Shocks
To examine whether the misvaluation measures continue to explain mergers once we control for this classification.

Table 13
Panel A: Merger waves are being driven by much more than just sector-level misvaluation.
Panel B: The quintile of the most overvalued firms is responsible for 42% of merger transactions and an even larger fraction (47%) of stock-financed transactions. This quintile is responsible for nearly 60% of the dollar volume of merger transactions.
Panel C: Repeat Panel B but focus only on the transactions that occur during Harford (2005) merger waves. Almost 50% of the transactions, and over 65% of the dollar volume, comes from acquirers in the top misvaluation quintile. The top misvaluation quintile is responsible for over one-half of stock-financed merger activity during periods of economic shocks.

Above all, while sector misvaluation is an important determinant of merger waves, many other factors are also important. Misvaluation is by no means the whole story at the sector level. Yet at the firm level, misvaluation is critical for understanding who participates in these merger waves. Even when the merger is part of a merger wave that is being driven by neoclassical considerations, most merger activity is the work of misvalued firms.


1. Acquirers with high firm-specific error use stock to buy targets with relatively lower firm-specific error at times when both firms benefit from positive time-series sector error.
2. Cash targets are undervalued relative to stock targets. Cash acquirers are less overvalued than stock acquirers.
3. Merger intensity is highly positively correlated with short-run deviations in valuation from long-run trends, especially when stock is used as the method of payment. This holds for individual firms, as well as at the aggregate level.
4. After controlling for firm-specific and time-series sector error, we find that low long-run value-to-book firms actually buy high long-run value-to-book targets.

Findings support misvaluation theories based either on behavioral explanations or on asymmetric information between otherwise rational managers and markets. Economic shocks could well be the fundamental drivers of merger activity, but misvaluation affects how these shocks are propagated through the economy. Misvaluation affects who buys whom, as well as the method of payment they use to conduct the transaction.

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