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Do the reduced agency costs of debt affect shareholders’ value
of cash acquisitions in the euro area?
Student name: Ai Guo Student number: s2311933 Thesis supervisor: Dr. Henk von Eije
Master thesis of Finance
University of Groningen, Faculty of Economics and Business
Abstract
This paper investigates the 261 cash-financed acquisitions in the euro Area between 2004 and 2012 to study the effect of agency cost on the acquirers’ shareholders’ value around the announcement date. The results reveal that reduced agency costs as a result of debt are not observed, so that higher debt ratios do not create value for bidder’s stockholders. These results remain unchanged, even in the crisis period of 2007 to 2010, though acquisitions in the crisis period itself increase shareholder value in comparison to acquisitions outside the crisis if I use a relative long event window.
JEL code: G01, G14,G34
2 / 25 1. Introduction
Mergers and acquisitions (M&A) have been very important during the last decades. In the United States only, thousands of acquisitions were announced in the 1980s and in 1998 there were 12,356 deals (Rappaport and Sirower, 1999). One major issue in the literature is whether or not value is created by the acquisition. Though target firms generally show positive returns, the literature on acquirers is less positive, though acquisitions are very important for firms to implement a growth strategy.
The change in stock value of acquirers around M&A announcement dates is determined by various factors, one of which is the payment method. Many previous papers are devoted to deals by cash payments. While some authors find positive results (Jain, Yadav and Rani, 2012; Emery and Switzer, 1999), some authors find negative results (Smith and Watt, 1992; Martin, 1996). Another factor that may affect the shareholders’ value is agency costs. Low agency costs are likely to increase shareholders value in acquisition. In this context, I mainly test whether the major determinant of agency costs (the debt ratio of the acquirers) influence the abnormal returns of cash payment acquisitions.
In this line of reasoning, I perform four tasks. First of all, I test whether the cash payment deals create positive values in short term using the standard event study methodology. Secondly, for the cash payment deals, I test the general effect of debt level on the shareholders’ value around the acquisition announcement date. Third, this paper studies whether the financial crisis in 2007-2010 has an impact on cash payment acquisition. Many researchers indicate that a company’s capital and liquidity play important role during the crisis. However, there are no papers that investigate the impact of the crisis in the context of manufacturing industry acquisitions with cash payment. Finally, I check whether the financial crisis makes any influence of debt holdings on acquisitions stronger.
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reserve currency after the United States dollar, trade has been stimulated1 within the euro zone and had influence on European financial integration. Furthermore, ‘Cross-border investment and mergers and acquisition activity are the most dynamic factors driving integration in today’s Internal Market’, according to the European Commission2. There are currently 18 member states in the euro zone, which out of 28 European Union countries have adopted the euro as their common currency. At the beginning of introduction of euro, 11 countries make up the euro area in 1999, namely Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, The Netherlands, Portugal and Spain3. The other 7 member states joined afterwards, for example, Greece has joined in 2001, Malta has joined in 2008 and Latvia has joined in 2014. Because of the continuity and accuracy of the data in the analysis, I mainly focus on the initial 11 countries of the euro area.
This research makes several contributions to the literature. Firstly, the results of this paper show significant positive abnormal returns of the cash-financed acquisitions, which confirm the findings of Jain, Yadav and Rani (2012) and Emery and Switzer (1999). Secondly, the debt ratio is not a vital determinant of extra returns in the event windows in both the crisis and non-crisis period. Thirdly, while most of the existing literature only considers banking and financial industry in the crisis (Beltratti and Paladino, 2013; Beltratti, Stulz, 2012), this paper analyze the impact of acquisitions of manufacturing firms with cash payment in the crisis. Positive abnormal returns around the announcement dates are for these firms higher in the crisis period than in the non-crisis period. This is different from the results of previous papers at the banking sector. Fourthly, the effects of the debt ratio are not stronger in the crisis.
These findings might be relevant to institutional investors or global active fund managers especially when they seek to exploit mispricing and to capture positive alphas. Minahan (2006) argues that good fund managers have beliefs regarding the security pricing
1
"The euro's trade effects" (PDF).(2009) http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp594.pdf)
2
Economic Reform: Report on the Functioning of Community Product and Capital Markets. COM, Brussels, 26 final ) http://ec.europa.eu/internal_market/economic-reports/docs/cardiff00anx_en.pdf
3
Interactive map of euro area between 1999 and 2014 by European Central Bank
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mechanism and what causes a security to be mispriced and this paper shows that it is the cash acquisition but not the debt holdings of the firms acquiring with cash. This can be used as a reference with guidelines as to how the European market prices the acquirers’ stocks around cash acquisitions and to improve their beliefs at the time M&A announcements are made. In particular, the level of debt financing of the acquirers, does not signal to the investors whether or not to buy or sell a company’s stock around an announcement, while such a positive relation might be expected.
The remainder of this paper is organized as follows: Section 2 discusses the theoretical framework and develops the hypotheses; Section 3 explains the data collection, the variables and the methodology; Section 4 highlights the results; Section 5 provides conclusions, limitations and suggests further analysis.
2. Literature review
2.1 Cash Payment produces better performance
In general, there are three kind of payment method in M&A deals, which are cash, stock and the combination of cash and stock. Many studies find that cash financed acquisitions positively affect the short-term acquiring firm’s stock returns (Fuller, Netter and Stegemoller 2002;Emery and Switzer, 1999; Travlos, 1987; Loughran and Vijh, 1997; Draper and Paudyal, 1999).
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Fuller, Netter and Stegemoller (2002) supports the signaling hypothesis, when the target’s value is uncertain to acquiring firm. The acquirer wants to share the risk of overvaluation with the target shareholders after acquisition deals.
Such a theory has been corroborated by other empirical findings. For example, Travlos (1987) found that the returns to cash acquisition bidders were positive but insignificant whereas that the returns to stock acquisition bidders were significantly negative. Another study by Emery and Switzer (1999) hypothesize that bidders can forecast and choose the payment method which may provide a higher abnormal return. They find that bidders with cash financed deals received significantly higher abnormal return than what if they announced an acquisition by stock payment. Also Loughran and Vijh (1997) and Draper and Paudyal (1999) find positive returns for cash financed acquisitions.
Based on these findings I hypothesize that:
Hypothesis 1. Cumulative average abnormal returns to bidders which acquire by cash payments are positive.
2.2 Debt ratio
The debt ratio measures the extent of companies’ financial leverage and defined as the ratio of total debt to total assets. An acquirer has a higher level of debt during the period of acquisition activity implies bidder probably financed acquisition fund by issuance of debt instead of stock. Companies are inclined to issuing debt rather than shares because the sale of shares to outsiders reduces existing shareholders’ interest, and may generate higher agency cost of equity (Jensen and Meckling, 1976). Thus, a higher debt ratio can be representative of lower agency cost.
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of debt, the more money should be payout for the interest payments and installments which drain the firm’s cash. This will decrease the managers’ opportunity to act in detrimental to shareholders by spending it wrongly. Jensen (1986), Hart and Moore (1995), and Zwiebel (1996) suggest that debt repayment obligations help to prevent overinvestment of free cash flow by self-interest managers. Flannery (1986) and Diamond (1991) argue that even a management group does not have a salient conflict, it allows debt to create value by information asymmetry between managers and outsiders, because it provides management with an opportunity to signal its willingness to payout cash flows or be monitored by lenders or both. In this regard, I propose the following hypothesis.
Hypothesis 2. Acquirers with a higher level of debt generate higher abnormal returns for their cash payment acquisition
2.3 Crisis period
Beltratti and Paladino (2013) propose in their studies of acquisitions by banks that positive abnormal returns should be more easily detected in crisis years than in normal years because of the increasing chances to acquire the target at a lower price. However, the most recent financial credit crisis during 2007 to 2010 has largely been a liquidity crisis. Cash-financed acquisition may negatively affect the cumulative abnormal returns during the financial crisis period since marginal value of cash is enhanced due to liquidity shrinkage (Beltratti and Paladino, 2013). They find that the cash acquisition depletes the acquirer’s liquidity buffer. Their event study shows that the return to an acquirer paying by cash is 1.6% lower in the crisis period than that of an acquirer that does not use cash.
Therefore, in the context of financial crisis period, the market may consider a cash offering acquisitions less favorably.
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Furthermore, it would be interesting to detect whether the level of debt has a different impact on cash payment acquisitions during the crisis. Credit is tightened and a high level of debt may reduce the firm’s liquidity during the crisis. As a firm’s liquidity is vital, therefore, liquid firms have opportunities to improve their market share through acquisitions and to achieve the benefits of acquisitions at lower prices during crises (Beltratti and Paladino, 2013). They find that abnormal returns smaller for banks with more leverage. From this point of view, the expected positive impact of debt may be smaller during the crisis period.
Hypothesis 4. The impact of debt on the cumulative average abnormal returns to bidders who pay by cash will be smaller during the crisis period.
2.4 Major control variables
Public/private Target
Existing literature reveals that the performance of acquiring a public or private target with different payment methods is interrelated. For example, Chang (1998) introduces the monitoring hypothesis that acquiring a private target using equity payment creates small amount of outside blockholder and results in an increase firm value because those blockholders’ monitor managerial performance effectively.
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Therefore, in the context of cash offering acquisitions, I expect public company as a target to be more favorable for the acquirers.
Cross-border acquisitions
Dutta, Saadi and Zhu (2013) find that cross border acquisitions have a negative effect on cash financed deals. Acquiring firm investors in cross border takeover deals prefer stock payments mainly because information asymmetry problems between the acquiring and target firms are likely to be more pronounced in cross border acquisition deals. This information asymmetry leads target’s value unclear. In order to avoid overvaluing, acquirers would like to share this risk with target by stock financed. Another study by Faccio and Masulis (2005) observed from Western Europe. They studied the payment method in cross-border acquisition deals and concerned with investors have a home country bias4. Their results consists with Dutta, Saadi and Zhu (2013) that domestic deals in support of cash and stock are more favorably be used in cross border deals. Therefore, I therefore expect that the cross border acquisition may destroy bidder’s value in context of cash payment acquisition.
3. Data and Methodology
3.1 Data collection
The sample starts by 2,563 listed firm acquisitions with cash payment deals in the 11 initial euro area countries from January 1, 2004 to December 31, 2012. I required the rumor date equals the announcement date. This is because the possible of information leakage can have occurred between the rumor date and the announcement date. I also require that the amount of deal value is at least €100 million in order to have deals that are important for the bidders. Moreover, I exclude bidders engaged in the financial industry and the companies for
4
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which we are unable to retrieve stock return over the estimation window of 210 days before the acquisition announcement. In the end, there are 261 acquisition deals left. The acquisition samples used for this study are constructed from the Zephyr database of Bureau Van Dijk. The company information is achieved from Orbis database and the daily stock return indices of every sample are taken form DataStream. Table 1 show that the selection strategy of the acquisition deals.
Table 1 Sample selection
Criterion Search result
Methods of payment: Cash 528,857
Deal Type: Acquisition 123,318
Listed/Unlisted Acquirers: Listed 45,274
Acquirer Country: AT, BE, FI, FR, DE, IE, IT, LU, NL, PT, ES
4,136
Time Period: 01/01/2004 – 31/12/2012 2,563
Acquisition date=Rumor Date 1439
Deal Value (mil EUR): min>=100 712
Excluding Financial Sector 267
Excluding no return information acquirers over estimation window
261
In applications, EURO STOXXX 50 Index is used for the market portfolio. It is collected from DataStream and the adjusted for stock splits and dividends index (which is so called return index, RI) is used.
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within the euro area (11 EU countries), whereas cross border targets represent a target location outside the 11 EU countries. Panel D indicates the relative sizes of the acquisitions, which is the ratio of transaction value and the market value of the acquiring firm’s equity. The relative size of the majority of acquisitions is above 25%.
Table 2 Characteristics of the dataset
The table presents the descriptive features of the firms that announced cash payment acquisitions between 2004 and 2012. The sample consists of 261 acquisition observations.
Number % (as percentage)
Panel A: Acquisition Year
Ordinary year 177 67.81
Crisis year 84 32.19
Total 261 100
Panel B: Target Type
Public 22 8.43
Private 198 75.86
Other 41 15.71
Total
Panel C: Target Country Domestic
Cross-border Total
Panel D: Relative Size Less than 5%
5% to 25% More than 25%
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3.2 Measuring abnormal performance
This paper is based on the event study approach, and therefore I follow the standard event study methodology introduced by Brown and Warner (1985), and use both the market adjusted model and the market and risk adjusted model, to calculate abnormal returns and cumulative abnormal returns.
Before we go to the abnormal return calculations, the daily stock return is shortly described. The daily stock return indices of every sample are taken from DataStream. The stock return on the trading days is calculated as followed:
Ri,t =Ln (RIi,t)-Ln (RIi,t−1) (1) Where Ri,t =the return of bidder’s stock i at trading day t
RIi,t = the return index of stock i at trading day t
RIi,t−1 = the return index of stock i at one day before trading day t-1
I calculate the expected return on both models in an estimation window of 200 trading days, which starting from 211 days before the announcement date (t-211) to 11 days before the announcement date (t-11). The event window in this paper is 21 trading days, which implies 10 days before the event announcement date, and 10 days after the announcement date.
According to Brown and Warner (1985), the Market Adjusted Model assumes the market return as the expected return of stock i:
E(Ri,t) = E(Rm,t) (2)
Therefore, the abnormal return for security i can be calculated by the difference between realized return on the date t and return on market portfolio on the date t, that is,
AR(i,t)= Ri,t− Rm,t (3)
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following formula:
E(Ri,t) = αi+ βiRm,t+ εi,t (4)
Where 𝐸(𝑅𝑖,𝑡)= the expected return of the estimation period of bidder’s stock i at time t, 𝑅𝑚,𝑡 = the market return on trading day t
𝛼𝑖 = the model’s intercept 𝛽𝑖 = the slope coefficient ε
i,t= the error term
In applications, the EURO STOXXX 50 Index is used for the market portfolio. And it is collected from DataStream.
The market and risk adjusted return model introduces two parameters, which are α and β. Those parameters can be obtained through regressing returns on stocks of each event and market returns in the estimation period.
The formulas are displayed below:
βi =COV (RVAR (Ri,t,Rm ,t)
m ,t) (5)
αi = E(Ri,t) − βRm,t (6)
Where Rm,t is the market return on trading day t and E(Ri,t )=the return of bidder’s stock i at trading day t.
I measure the abnormal return over the event period of 21 days, which implies 10 days before the event announcement date, and 10 days after the announcement date. However, because I focus on the short term effects, I refrained from using 21 trading days as the event window. Hence, in this paper, the abnormal returns for event i are observed over an event window of 3 days (-1 to 1 trading days) and of 5 days (-2 to 2 trading days) respectively.
The abnormal return can be measured as followed:
ARi,t= Ri,t− E Ri,t = Ri,t− 𝛼𝑖− βiRm,t (7)
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abnormal returns over the even period.
CARk = kt=1ARt (8)
Where k stands for length of event windows, which are 3 days (-1 to +1 trading days) and 5 days (-1 to +1 trading days)
And the cumulative average abnormal returns (CAAR) for event windows are calculated by averaging the CAR over all of the acquisition events. Finally, a test-statistic is calculated to identify whether the CAR is significantly different from zero.
tk =σ CARk
(CAR k)/ n−1 (9)
Where CARk is the cumulative abnormal return (CAR) for event i; σ is the standard deviation which is estimated through estimation window (t-211 to t-11); n stands for the numbers of events, thus n-1 is 260 here. Hypothesis 1 then can be tested by whether the CARs of the acquisition deals are significantly larger than zero.
3.3 Cross-section analysis
To investigate the effect of the acquiring firms’ shareholder return, I use the following OLS regression model.
CAR𝑖= α+β1*DEBT_RATIO𝑖 + β2*CRISIS𝑖+β3*C_DEBT𝑖+ β4*PUBLIC𝑖 + β5*CROSS_B𝑖 + β6*Ln(REL)𝑖 + β7*Ln(MCAP)𝑖 + εi,t (10)
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and otherwise it is 0. CROSS_B𝑖 is a dummy variable. It is 1 if the target is outside the region of euro area (of the initial 11 countries), otherwise it is 0. Ln(REL)𝑖 is the natural logarithm of relative size, implies the ratio of transaction value to the market value of the bidder’s equity. Ln(MCAP)𝑖 is the natural logarithm of the market capitalization of the acquiring firms. εi,t is the error term.
This test is used for testing the hypotheses in section 2.4. Due to the hypotheses 2 and 3, I expect there are a significant and positive sign with the variable of debt ratio; and a significant negative sign with the variable of crisis dummy. For the hypotheses 4, I cannot reject if there is significant negative sign with the variable of C_DEBT.
Table 3 Summary of exogenous variables
The table presents the summary statistics of exogenous variables. There are three variables in the table, the rest of them are all dummy variables which either 1 or 0.
Exogenous Variables Mean Medium St.Dev Max Min
Debt Ratio Crisis Crisis_Debt Public Cross_B 0.155 0.678 0.151 0.100 0.590 0.186 1 0.182 0 1 0.207 0.468 0.215 0.301 0.493 0.952 1 0.952 1 1 -1.030 0 -0.921 0 0 Ln_MCap Ln_Relsize 15 -1.763 16 -1.581 1.762 1.606 18 2.156 9 -3.319
15 / 25 4. Main findings and results
4.1 Evidence on cumulative abnormal returns
Table 4 Descriptive statistics of the CAR
The table shows summary statistics of the CAR of the cash acquisition. The sample size is 261 for all acquisition deals. CAR (-1, +1) is the test under Market Adjusted Model, with alpha and beta are defined as 0 and 1 for an event windows of 3 trading days. CAR (-1, +1)* and CAR (-2, +2)* are the tests under Market and Risk Adjusted Model, which alpha and beta are estimated by the market and risk adjusted model over the estimation period t−211 to t−11. CAR results are reported in decimals not in percentage.
CAR (event period): CAR (-1, +1) CAR (-1,+1)* CAR (-2, +2)*
Panel A: Cumulative abnormal returns for all acquisition events
Mean 0.005 0.005 0.007 Minimum -0.126 -0.144 -0.117 Maximum Standard Deviation t-test stat. 0.251 0.044 2.499 0.249 0.044 7.264 0.263 0.047 13.121 Panel B: Cumulative abnormal returns for non crisis period acquisitions
Mean Minimum 0.004 -0.126 0.003 -0.144 0.014 0.006 Maximum 0.251 0.249 0.037 Standard Deviation t-test stat. 0.042 1.741 0.041 1.419 0.005 5.203 Panel C: Cumulative abnormal returns for crisis period acquisitions
Mean 0.009 0.010 0.019
Minimum -0.096 -0.095 0.008
Maximum 0.199 0.196 0.052
Standard Deviation 0.049 0.047 0.008
t-test stat. 4.095 4.534 7.038
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Table 4 exhibits the results of cumulative abnormal returns of the bidders of total 261 cash-financed acquisitions for 3-day and 5 day event window. As shown in Panel A, the mean of cumulative abnormal returns of the risk adjusted model in each event windows are 0.005, 0.05 and 0.007 respectively and they are all significant when comparing their t-statistics to 1.96. The results of market-adjusted model in 3-day window coincide with those of risk adjusted model (mean of abnormal return is significantly positive, 0.005). The results are consistent with Jain, Yadav and Rani (2012) and Emery and Switzer (1999) suggesting that the cash payment method in acquisition exerts a positive impact on the shareholders’ value of the bidders.
Panel B and Panel C of Table 4 split the total number of events in terms of two different periods which are non crisis years and crisis years (from 2007-2010) in the sample period. As can be seen, for the non-crisis period, the mean of cumulative abnormal returns are 0.004, 0.003 and 0.014 for each event window and the return of 0.014 is significant (t=5.203). In the crisis years, the bidders of the cash-financed deals are able to earn extra returns of 0.009, 0.010 and 0.019 for each event window and all of the returns are significant. The cash-financed deals in both periods demonstrate positive effects on the bidders’ shareholder value. In addition, the crisis period is likely to generate higher values than the non-crisis period because the mean of cumulative abnormal returns in the crisis years are higher than those of the non-crisis years. Thus, I calculate the difference between the mean in both periods for the three event windows, which are 0.005, 0.007 and 0.005, and then test their significance using the difference test of the two independent populations as shown in the followings: ) ( ) ( 1 2 D S x x t ) 1 1 ( 2 ) 1 ( ) 1 ( ) ( 2 1 2 1 2 2 2 2 1 1 n n n n s n s n D S df n1n22
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are samples in each period,
s
12 and 2 2s
is the variance of the cumulative abnormal returns in the estimation window for each period. The result shows significant differences between the cumulative abnormal returns of the two periods meaning that the bidders can earn significantly higher extra returns in crisis period than in non-crisis period (difference t- statistics are 10.58, 14.23 and 7.17 for each event window). Such a conclusion is in sharp contrast to hypothesis 3 that the crisis period has a negative impact on cash financed acquisition deals. It may be because in the buyer’s market associated with a crisis period, the purchase prices of the target firms are much cheaper than in normal periods.4.2 Evidence from the cross-section analyzes
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Table 5 Cross-sectional OLS regression
The table gives the results of OLS regression that test the effect of those exogenous variables on the returns. CAR (-1, +1) of the Market Adjusted model, and CAR (-1, +1) and CAR (-2, +2) of the Market and Risk Adjusted model are used as the dependent variable respectively. DEBT_RATIO represents the level of debt which is total debt over total assets. CRISIS is a dummy variable, when the value is 1 which means the acquisition in between 2007 and 2010; otherwise the value is 0. C_DEBT is a variable that shows the interaction of the debt level with the crisis period. The rest of the exogenous variables are control variables. Ln_MCAP represents market capitalization; Ln_RELSIZE is relative size, which is a ratio of the deal value to the acquiring firm’s equity value; PUBLIC represents a dummy where the public target is 1, otherwise is zero and CROSS_B are dummy variables where “home country” is 1, otherwise is zero.
Model:
CAR (event period):
Market Adj. CAR (-1, +1)
Market and Risk CAR (-1, +1)*
Market and Risk CAR (-2, +2)*
Exogenous variables Coef. Prob. Coef. Prob. Coef. Prob.
DEBT_RATIO -0.045 0.144 -0.014 0.649 0.001 0.864 CRISIS 0.014 0.065* 0.014 0.155 0.004 0.013** C_DEBT -0.002 0.862 -0.038 0.347 0.003 0.619 Ln_MCAP Ln_RELSIZE PUBLIC CROSS_B -0.003 0.000 0.019 -0.007 0.202 0.995 0.073 0.339 -0.002 -0.000 0.019 -0.007 0.348 0.960 0.050 0.315 -0.001 -0.000 0.003 0.001 0.000*** 0.427 0.039** 0.230 C 0.054 0.097* 0.039 0.205 0.034 0.000*** Observations F-test 155 1.615 0.071 155 1.542 0.068 155 5.978*** 0.222 R-squared
Note: * indicates statistical significant at 10% level ** indicates statistical significant at 5% level *** indicates statistical significant at 1% level
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are 0.019, 0.19 and 0.003 and one of them is 5% significant. This result is consistent with Chang (1998) and Faccio, McConnell and Stolin (2006). Secondly, the coefficient of market capitalization in the 5-day event window is significantly negative suggesting that higher acquirers’ sizes hurt the value of the shareholders. In 3-day event window for market adjusted model and market risk adjusted model, the size of the bidders also seems to be detrimental to abnormal returns even though it is not significantly so..
4.3 Robustness test
Table 6 Cross-sectional OLS regression of Net debt ratio
The table gives the results of OLS regressions that test the effect of the exogenous variables on the returns. CAR (-1, +1) of the Market Adjusted model, and the CAR (-1, +1) and CAR (-2, +2) of the Market and Risk Adjusted model are used as the dependent variable respectively. NET_DEBT represents the level of net debt over total assets. CRISIS is a dummy variable, with a value of 1 in 2007 to 2010; otherwise the value is 0. CD_NETDEBT is a variable that shows the interaction of the net debt level with the crisis period. The rest of exogenous variables are control variables.
Model:
CAR (event period):
Market Adj. CAR (-1, +1)
Market and Risk CAR (-1, +1)*
Market and Risk CAR (-2, +2)*
Exogenous variables Coef. Prob. Coef. Prob. Coef. Prob.
NET_DEBT -0.005 0.643 -0.005 0.869 0.003 0.500 CRISIS 0.009 0.483 0.011 0.244 0.447 0.001*** CD_NETDEBT -0.010 0.908 -0.013 0.759 -0.005 0.448 Ln_MCAP Ln_RELSIZE PUBLIC CROSS_B -0.004 -0.000 0.016 -0.008 0.156 0.978 0.146 0.320 -0.004 -0.000 0.018 -0.008 0.152 0.895 0.090 0.308 -0.002 -0.000 0.004 0.002 0.000*** 0.230 0.011** 0.100 C 0.068 0.067* 0.062 0.075 0.040 0.000*** Observation F-test (prob.) 155 0.229 0.067 155 0.157 0.076 155 0.000*** 0.254 Note: * indicates statistical significant at 10% level
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Total debt is defined as net debt plus cash and cash equivalents. The net debt ratio (excluding cash and cash equivalents) may be stronger effect in reducing agency costs. Thus, I conduct the tests with exactly same methodology but this time with net debt ratio. The yearly net debt ratio is defined as the net debt divided by total assets, which are retrieved from Orbis database.
The results of such test in Table 6 reveal similar outcomes. The debt ratio is never significant so that there are no real improvements in outcomes for firms with high (net) debt ratios. The crisis period exerts positive effect on abnormal returns in 5-day event window of the risk-adjusted model because its coefficient of 0.447 is 1% significant. In 3-day event window in the both models the impact of crisis period also seems to be positive although it is not significantly so. In addition, the impact of debt in the crisis period is still not observed when the net debt ratio replaces the total debt ratio since none of the coefficients of CD_NETDEBT are significant in all event windows.
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Table 7 Cross-sectional OLS regression of net weighted debt ratio
The table gives the results of OLS regressions that test the effect of the exogenous variables on the returns. CAR (-1, +1) of the Market Adjusted model, and the CAR (-1, +1) and CAR (-2, +2) of the Market and Risk Adjusted model are used as the dependent variable respectively. NET_DEBT_W represents the level of weighted net debt over total assets. CRISIS is a dummy variable, with a value of 1 in 2007 to 2010; otherwise the value is 0. CD_NETDEBT_W is a variable that shows the interaction of the net debt level with the crisis period. The rest of exogenous variables are control variables. Model:
CAR (event period):
Market Adj. CAR (-1, +1)
Market and Risk CAR (-1, +1)*
Market and Risk CAR (-2, +2)*
Exogenous variables Coef. Prob. Coef. Prob. Coef. Prob.
NET_DEBT_W -0.011 0.729 -0.008 0.785 0.002 0.373 CRISIS 0.008 0.490 0.010 0.237 0.005 0.000*** CD_NETDEBT_W -0.005 0.901 -0.010 0.807 -0.003 0.665 LN_MCAP LN_RELSIZE PUBLIC CROSS_B -0.003 0.000 0.016 -0.008 0.151 0.979 0.155 0.320 -0.003 -0.000 0.017 -0.007 0.157 0.929 0.092 0.313 -0.002 -0.001 0.005 0.002 0.000*** 0.245 0.010** 0.102 C 0.068 0.065* 0.062 0.076 0.040 0.000*** Observation F-test (prob.) 155 0.220 0.068 155 0.156 0.076 155 0.000*** 0.253 R-squared
Note: * indicates statistical significant at 10% level ** indicates statistical significant at 5% level *** indicates statistical significant at 1% level
5. Conclusion
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the crisis period. The results lead to the following conclusions.
In the first place, the results are consistent with those of, e.g. Jain, Yadav and Rani,(2012) and Emery and Switzer (1999) and show that the acquirers’ cash-financed deals earn significantly positive returns. Secondly, I also find that the debt ratio almost plays no role in determining the abnormal returns, so reduced agency cost generated by a larger debt ratio do not influence the outcome of cash-financed deals. Thirdly, there are some indications that the crisis period exerts a positive influence on the abnormal returns. Finally, I find that a high debt ratio still has no positive impact on the cumulative abnormal returns of the acquirers in the crisis period. Overall, it can be concluded that reduced agency costs measured by a higher debt ratio are not considered to be relevant in this case: a higher debt ratio does not create value to the acquirers’ shareholders in the recent cash-financed deals in the euro zone.
23 / 25 Reference
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