Aggregate Merger Activity Research Articles

Economic shocks, M&A advisors, and industry takeover activity

The paper examines the role of M&A advisors in propagating takeover activity following economic shocks that affect industry conditions. M&A advisors constitute an important intermediary in the market for corporate control by enhancing M&A success at a transaction level. We posit that, at an industry level, M&A advisors also play a significant role in propagating aggregate merger activity in the wake of an industry shock. The empirical results show a positive, significant relationship between the presence of M&A advisors and industry takeover activity, and offer evidence supporting the incremental role of M&A advisors following industry shocks. The results are robust to empirical strategies aimed at alleviating endogeneity concerns, including using a legislative change as an exogenous shock to M&A advisors and exploring reverse causality. Our evidence offers novel insights on the collective role of M&A advisors in the takeover market.

From micro to macro: Aggregate accruals, mergers, and returns. A discussion of Heater, Nallareddy and Venkatachalam (2021)

Heater, Nallareddy, and Venkatachalam (2021), hereafter HNV, find that aggregate merger and acquisition (M&A) activity explains the ability of aggregate accruals to predict market-wide returns. In this discussion, we delineate HNV's contribution to accounting literature and provide a review of the emerging stream of micro-to-macro accounting research. We also discuss HNV's findings in relation to research beyond accounting, including the literature on aggregate return prediction and mergers and acquisitions. Our discussion draws parallels between HNV's results and prior empirical evidence pertaining to aggregate investment and merger waves and identifies several puzzling inconsistencies. These inconsistencies highlight the lack of a clearly specified mechanism behind the return-predictive ability of aggregate M&A accruals. Finally, we point out the challenges posed by the small sample size and noisy measures of M&A accruals that may affect HNV's inferences. We conclude by suggesting several directions for future research.

Aggregate accruals and market returns: The role of aggregate M&A activity

Extant literature documents that aggregate accruals positively predict future market returns and attributes this relation to either changes in discount rates or systematic earnings management. We offer an alternative explanation: aggregate merger and acquisition (M&A) activity drives this relation. M&A activity affects the magnitude of accruals, which in turn drives the market return predictability of aggregate accruals. We find that the ability of both aggregate accruals and discretionary aggregate accruals (a measure of systematic earnings management) to predict market returns disappears after controlling for aggregate M&A activity. Furthermore, aggregate M&A activity predicts future market returns, consistent with a price response to improvements in macroeconomic outcomes due to aggregate M&A activity.

From Micro to Macro: Aggregate Accruals, Mergers, and Returns. A Discussion of Heater, Nallareddy and Venkatachalam (2021)

Heater, Nallareddy, and Venkatachalam (2021), hereafter HNV, find that aggregate merger and acquisition (M&A) activity explains the ability of aggregate accruals to predict market-wide returns. In this discussion, we delineate HNV’s contribution to accounting literature and provide a review of the emerging stream of micro-to-macro accounting research. We also discuss HNV’s findings in relation to research beyond accounting, including the literature on aggregate return prediction and mergers and acquisitions. Our discussion draws parallels between HNV’s results and prior empirical evidence pertaining to aggregate investment and merger waves and identifies several puzzling inconsistencies. These inconsistencies highlight the lack of a clearly specified mechanism behind the return-predictive ability of aggregate M&A accruals. Finally, we point out the challenges posed by the small sample size and noisy measures of M&A accruals that may affect HNV’s inferences. We conclude by suggesting several directions for future research.

Aggregate Accruals and Market Returns: The Role of Aggregate M&A Activity

Extant literature documents that aggregate accruals positively predict future market returns and attributes this relation to either changes in discount rates or systematic earnings management. We offer an alternative explanation: aggregate merger and acquisition (M&A) activity drives this relation. M&A activity affects the magnitude of accruals, which in turn drives the market return predictability of aggregate accruals. We find that the ability of both aggregate accruals and discretionary aggregate accruals (a measure of systematic earnings management) to predict market returns disappears after controlling for aggregate M&A activity. Furthermore, aggregate M&A activity predicts future market returns, consistent with a price response to improvements in macroeconomic outcomes due to aggregate M&A activity.

On the Effect of Merger Waves on Long-Term Aggregate Stock Market Valuation

In this study, we investigate the effect of merger waves on the long-term valuation of aggregate stock market. Our empirical test shows significant positive relationship between the intensity of past, with four years lag, aggregate merger activity and the valuation of aggregate stock market.

Does the Stock Market Aggregate State Reflect Upcoming Merger Activity?

The study introduces empirical evidence that there are statistically significant relationships between intensity of upcoming aggregate merger activity and the present values of the factors HML and SMB in the Fama-French three-factor model of assets pricing.

The impact of the macroeconomic environment on merger activity: evidence from US time-series data

This article investigates the dynamic impact of the macroeconomic environment on aggregate merger activity in the US economy obtained from firm–level data during the period from January 1980 to December 2004. Applying time–series econometric tools to US Mergers and Acquisitions (M&A) data, we find: First, there is a long–run equilibrium relationship between the set of macroeconomic variables and four alternative measures of merger activity, implying that the macroeconomic factors plays an important role in determining the trend of aggregate merger activity in the US economy. Second, the most important macroeconomic variables in determining M&A volume include real income for the frequency-based measure of US merger activity, and stock market conditions and monetary policy for transaction value based measures of aggregate mergers. The ascending phase of business cycle provides the most favourable environment for more mergers for all four measures of merger activity. Our subsample period study provides evide...

Mergers and CEO Power

I propose a model of mergers in which synergies and CEO power play a crucial role. A merger is modeled as a bargaining game between the acquiring and the target board of directors, with the gains from a merger divided according to the generalized Nash bargaining solution. The model's implications are consistent with the available empirical evidence on stock returns, and yield some new untested implications that are mainly related to the relationship between CEO power, corporate governance, and mergers. Finally, the model sheds light on the relationship between aggregate merger activity, synergies, and CEO power.

Valuation waves and merger activity: The empirical evidence

To test recent theories suggesting that valuation errors affect merger activity, we develop a decomposition that breaks the market-to-book ratio ( M / B ) into three components: the firm-specific pricing deviation from short-run industry pricing; sector-wide, short-run deviations from firms’ long-run pricing; and long-run pricing to book. We find strong support for recent theories by Rhodes-Kropf and Viswanathan [2004. Market valuation and merger waves. Journal of Finance, forthcoming] and Shleifer and Vishny [2003. Stock market driven acquisitions. Journal of Financial Economics 70, 295–311], which predict that misvaluation drives mergers. So much of the behavior of M / B is driven by firm-specific deviations from short-run industry pricing, that long-run components of M / B run counter to the conventional wisdom: Low long-run value to book firms buy high long-run value-to-book firms. Misvaluation affects who buys whom, as well as method of payment, and combines with neoclassical explanations to explain aggregate merger activity.

Valuation Waves and Merger Activity: The Empirical Evidence

To test recent theories that suggest valuation errors affect merger activity, we develop a decomposition that breaks M/B into three components: the firm-specific pricing deviation from short-run industry pricing; sector-wide, short-run deviations from firms' long-run pricing; and long-run pricing to book. We find strong support for recent theories by Rhodes-Kropf and Viswanathan (2003) and Shleifer and Vishny (2003), which predict that misvaluation drives mergers. So much of the behavior of M/B is driven by firm-specific deviations from short-run industry pricing, that long-run components of M/B run counter to the conventional wisdom: Low long-run value to book firms buy high long-run value to book firms. Misvaluation affects who buys whom, as well as method of payment, and combines with neoclassical explanations to explain aggregate merger activity.

Aggregate Merger Activity: New Evidence on the Wave Hypothesis

The conventional opinion is that aggregate merger activity occurs in waves. An early proponent of this view was Nelson [13; 14] who concluded that merger behavior could be described by bursts of high activity followed by long periods of low activity. Numerous other authors have advanced similar interpretations of the data, including Scherer and Ross [16], Blair, Lane and Schary [1] and Golbe and White [7]. In fact, some have argued that merger waves remain an important but as yet not totally resolved puzzle (Brealey and Myers [2], Weston, Chung and Hoag [21]). Figure 1 presents a plot of the annual number of U.S. mergers over the period 1895-1994. It is not difficult to see from the figure how the popular belief about merger waves arose. The view that mergers come in waves has been the subject of considerable interest since Nelson's work first appeared.' However, the formal statistical evidence regarding the wave hypothesis is mixed. Shughart and Tollison [17] examine several time series of merger activity and generally do not reject the null hypotheses that each of the series examined follows either a random walk or an AR(1) process with first order autocorrelation close but not equal to 1.0. They argue that such processes are not consistent with the wave hypothesis. Golbe and White [7] on the other hand fit a sine wave based model to a similar aggregate merger series and conclude that there is a close correspondence between the data and their specification. In this paper we examine the issue of waves in merger activity through formal tests of the hypothesis that aggregate merger activity follows a stationary regime switching process. Specifically, we argue that shifts in an unobservable state variable ignite shifts in the characteristics of the process driving mergers. The appeal of this specification is threefold. First, it provides an intuitively plausible model which generates waves in merger activity. Second, as we show later, it provides an explanation for the results in Shughart and Tollison while at the same time providing an interpretation of the data which adds content to the findings of Golbe and White, thus reconciling the evidence within an intuitive framework. Third, the model also provides a foundation for further considerations of the factors which might ignite merger waves.2

Aggregate Merger Activity: New Evidence on the Wave Hypothesis*

Aggregate Merger Activity: New Evidence on the Wave Hypothesis*

On the relationship between aggregate merger activity and the stock market: some further empirical evidence

This letter presents the results of an econometric investigation relating two measures of merger activity in the UK and the London stock market index. The study shows that “real” stock market prices “Granger cause” both numbers and real values of mergers.

A time series analysis of causality between aggregate merger and stock prices: the case of Canada

It is widely agreed that a positive relationship exists between measures of aggregate merger activity and measures of stock market performance, at least for the USA. Evidence from other countries is relatively sparse. in this paper we pursue the causality question using Canadian data. Most of the previous studies used only a bivariate system (merger and stock prices). We have extended the analysis to trivariate system (merger, stock prices and interest rate) to better reflect the capital market conditions argument for changes in merger activity. The results suggest a bidirectional causality between mergers and stock prices.

The determinants of aggregate-merger activity?Before and after Celler-Kefauver

Regression analysis was used to determine the significant determinants of aggregate merger activity before and after 1950. This study found that stock prices were positively related to merger activity both before and after 1950. However, interest rates were positively related to merger activity prior to 1950, and negatively related to merger activity after 1950. This may have been the result of the Treasury Accord of 1951, which stopped pegging of interest rates. The unemployment rate was negatively related to mergers before 1950, but insignificantly related to mergers after 1950. The decreased significance of the unemployment rate could be the result of the passage of the Celler-Kefauver amendment to the Clayton Act. Tightened regulation may have caused businesses to take a longer run view of merger activity and decreased the business cycle effect. In conclusion, changes in both the regulatory environment and monetary policy have influenced the level of merger activity since 1950.

The impact of financial and economic conditions on aggregate merger activity

AbstractA model of aggregate merger activity is developed by integrating the literature on aggregate investment in fixed capital into a microfinance framework. Mergers are viewed as the result of firms capital budgeting processes, and two major categories of explanatory variables emerge: (1) cost of capital and related financial effects, and (2) output effects. Regressions, estimated to explain the number of large mining and manufacturing mergers over the sample period 1956–1978, provide evidence consistent with this view. In addition, the model explains the high level of merger activity during the conglomerate boom of 1967–9.

On the relationship between aggregate merger activity and the stock market

This paper presents substantial evidence to show that the well documented correlation between aggregate merger activity and indices of share prices is unstable, and thus of little predictive value. Further, Granger causality testing suggests that such correlations are spurious, reflecting other more fundamental forces which jointly determine movements in both series.

A Time Series Analysis of Aggregate Merger Activity

THE study of merger activity has been of long-standing interest to economists as well as the financial community. References to merger activity in American industry generally acknowledge three major merger movements. The first one occurred during the turn of the century, the second one during the 1920s. Stigler (1950) describes the second merger wave as being for oligopoly in contrast with the earlier for monopoly movement. Increased market power through consolidation and corporate concentration and operating economies of scale were identified as motives for mergers during these two waves. Horizontal mergers (i.e., mergers between direct competitors) were relatively more important during the first merger wave with vertical mergers (i.e., mergers between firms with prior buyer-seller relationships) being significant in the second wave.' Currently the United States is in the midst of its third major merger wave which began after the end of World War II. This has become known as the conglomerate merger wave because of the emphasis on mergers between unrelated firms or firms seeking product extension objectives (i.e., mergers between firms functionally related in terms of distribution and/or production facilities but whose products are not directly competing).2 The direction of the current merger wave can be partially explained by the fact that the Celler-Kefauver amendment to the Clayton Act in 1950 discourages horizontal and vertical mergers. While many authors have engaged in the study of mergers in the United States, the empirical examination of changes in aggregate merger activity has been limited both as to type and time period covered. Nelson (1959) first examined changes in quarterly merger activity during the 1895-1920 period and found a high positive correlation between changes in merger activity and changes in stock prices, and a positive but lower correlation between mergers and industrial activity. Further study by Nelson, however, showed that for the 1919-1954 period the relationship between mergers and stock prices was considerably weaker. In a follow up study, which extended aggregate merger data through 1962, Nelson (1966) concluded that merger activity exhibited a positive and highly consistent response to changes in business activity (as measured by the reference or business cycle). In addition to the efforts by Nelson, Weston (1961) examined annual changes in merger activity during the interwar period (between World War I and World War II). Using a multiple regression model, Weston found merger activity to be significantly related to stock prices but not significantly related to industrial production activity. Previous studies provide only limited insights into the structural (especially lead-lag) relationships between aggregate merger activity and macroeconomic/market factors. The literature is particularly void of empirical studies which investigate such relationships during the current merger period.3 It is this subject which we address in this paper. We employ a data-based multiple time series approach to develop an explanatory model for describing changes in the incidence of Received for publication July 14, 1981. Revision accepted for publication December 17, 1982. * University of Colorado, University of Iowa, and University of Denver, respectively. Computer facility support from the University of Iowa along with multiple time series programs provided by the University of Wisconsin-Madison are gratefully acknowledged. We also wish to thank the referees for their helpful comments. ' These two merger waves or movements were extensively studied, either separately or together, by Eis (1969), Markham (1955), Nelson (1959), Stigler (1950), Thorp (1941), and Weston (1961), as well as others. 2 The current merger movement, either separately or in conjunction with the earlier movements or waves, was analyzed by Lintner (1971), Lynch (1971), Markham (1973), Nelson'(1966), Reid (1968), and Steiner (1975). 3 International investigation of aggregate merger activity during the 1960s and 1970s is reported in Mueller (1980). Visual examination of the movement of mergers, GNP, and stock prices in Belgium suggested generally positive relationships. Aggregate merger activity was compared individually against economic activity (GDP), gross fixed investment, and share prices in West Germany. During the 1960s mergers tended to move in step with changes in economic activity and investment while lagging share prices. However, in the 1970s merger activity tended to lead the other aggregate measures. The best overall relationship was between merger activity and share prices.