The estimation of control premium remains one of the concerns of the financial literature: different approaches are taking into consideration the synergy effects, agency problems, the bargaining power of different agents, liquidity issues, etc. We have estimated the level of control premium for Romanian listed companies in the period 2000-2011. Using a linear regression model, we found that the determinants of control premium for Romanian listed companies are similar to those putted in evidence by the financial literature. Control premium was directly related to the percent of share purchased in the transaction and to the ownership concentration. Also, if the acquired company was acting in Commerce, control premium was higher. Control premium was indirectly related to the size of the acquired company, the liquidity of the shares, the power in negotiation of the buyer, and to the fact that the acquirer already owned some of the target's shares.
The estimation of control premium [1] remains one of the concerns of the financial literature. The reasons behind the large number of studies with this topic are related to the numerous applications in corporate finance, business valuation, control stake valuation, corporate governance, etc. (see Barclay and Horderness, 1989; Nenova, 2003; Dyck and Zingales, 2004, among others). Regarding the control premium determinants, different approaches are taking into consideration the synergy effects, agency problems, the bargaining power of different agents, liquidity issues, etc. From this viewpoint, it could be interesting to find out which are the determinants of control premium for the case of a Post Communist East-European country, respectively Romania [2] .
Practitioners, but also academics are interested in estimating an average control premium for different countries or for different industries, but also for identifying its determinants. For instance, control premium can be reliable proxy for synergy effects [3] , but also a clue for analyzing the level of agency problems in connection to minority shareholders protection.
In this study we show that, among other factors already discussed in the literature (liquidity, the buyer's power in negotiation, size of the company, sector, ownership structure), the stake purchased in the transaction can have also an impact on control premium.
There are many approaches in estimating the determinants of control premium. Our paper brings together these different approaches in explaining the level of control premium. Our approach is applied for a Post Communist East-European country, Romania. Such single-country studies can complement the case of multi-country ones (Ødengaard, 2007). As far we know this is the first study for the case of Romania that is analyzing the determinants of control premium.
The remainder of the paper is structured as follows. The next section presents briefly the main findings of related studies and the hypothesis tested. Section 3 describes the database and methodology. Section 4 presents and discusses the main empirical results. The final section contains the concluding remarks.
2. Theoretical background and tested hypothesis
The control premium [4] can be defined as the total value of benefits derived from holding a number of shares that provide a controlling position (Nenova, 2003). In general, these benefits can result from an improvement in the value of the acquired company, but also from the expropriation of the other shareholders: for Dyck and Zingales (2004), control premium is explained by two factors: the increase in company value due to the new management team and the private benefits that the new shareholder will have after gaining control over the company [5] .
Positively, a high level for control premium can be explained by increasing synergy effects resulted from the acquisition of company by a strategic investor. In this context, synergies can be due to increases in revenues, cost savings, tax reductions or to a decrease of the cost of capital (Ross, Westerfield and Jaffe, 2005) [6] . These approaches are the subject of large number of studies in business valuation.
On the other hand, the control premium can be interpreted as an estimator of the benefits that controlling shareholders can obtain by expropriating the other ones. It is possible that control premium to be explained by the stress of the non-controlling shareholders of losing a part of their wealth invested through the behaviour of controlling ones [7] (see Jensen and Meckling, 1976). Previous studies for Romanian companies have revealed the presence of agent problems in different contexts (see, for instance, Dragotă et al., 2009a). Moreover, the benefits of a controlling shareholder are not always expressed in monetary units. For example, these benefits can be given by an interest in gaining higher social positions, the improvement of the personal image or political campaigns.
The explanations for the control premium size are sometimes more complex for companies listed on emerging and or financial markets (see Atanasov, 2005; Filatotchev, Wright and Bleaney, 1999, etc.) [8] . As such, the phenomena can be easily affected by psychological factors (i.e.: greed) creating overreaction and, as result, a large variation in control premium from case to case.
From macroeconomic point of view, M&A phenomenon is seen as having a positive effect on overall economy. However, taking control does not always create added value for an economy as in some cases, the reasons behind M&A transaction can be purely financial and in the sole interest of specific stakeholders. For example, some companies in Romania were acquired at lower prices, afterwards being closed. In most cases, this was due to the corporate restructuring that followed the financial crisis from 2008 (for example, company Bunge, which operates in the oil market, liquidated the factory Unirea Iași only 6 years after the acquisition. Kraft Foods, after acquisition, liquidated the Chocolate Factory from Brașov in a process of reorganization, etc.). Besides the fact that a company takes advantage of mismanagement of companies acquired, another possible explanation could be eliminating a potential competitors. Thus, the potential growth of these companies can be often difficult to estimate by an external observer, which can lead to high variability of the control premium size. Additionally, if politics interferes significantly in defining economic strategies (see Romania before 1989, the year of the anti-communist revolution), anomalies will arise (i.e.: artificial development of certain industries or certain regions specializing in unviable industries) and substantial variability between profitability of the companies. The large variability of the control premium may be explained also by social and political pressures on economic decisions [9] .
By definition, the control premium is the amount overpaid (conventionally expressed as a share price change) to gain control of the company. As a result, the most convenient expression will be given by direct estimation (Zingales, 1994; Zingales, 1995; Nenova, 2003; Dyck and Zingales, 2004; Caprio and Croci, 2008), based on the difference between the price for voting shares and the price for non-voting shares. Of course, this method assumes that such different classes of shares are traded on the capital market, which is also liquid. These conditions are rarely found in the case of less developed financial markets [10] .
If such dual-class shares do not exist on capital markets, as Romania's case, it could be accepted the estimation of control premium based on the difference between Offer Price (in a Tender bid) and the share prices before this offer (Dragotă et al., 2007) [11] . Theoretically, control premium (GCP) can be estimated as a percentage change between the price paid in the case of a tender bid aiming in buying the proper number of shares which gives the control over company's decision (Po,t), and the shares' price on the market before the bidding moment (Pt-1) (see relation 1):
(1)
This control premium is a gross (empirical) control premium. This one can be used as an approximate estimator for control premium. However, this relation implies that the offer price is a good proxy for the value of the business in the hypothesis of having control (in this case, it includes the synergy effects but also the private benefits of control [12] ). Also, this price is assumed to be unbiased by the capacity of the partners (in the case, the buyer) to negotiate a favourable transaction. Regarding the price before the announcement, this relation assumes also that the market is efficient (in this case, the price should reflect the status of business value of the company as long as no change of control should be made). If the market is not efficient [13] , the price on the market has two components - one related to the fair market value, and one related to the behaviour of noisy traders. There is another issue that can have an influence on both prices, respectively the liquidity. These influences are depicted in Figure 1.
Figure 1: The difference between offer price and the price from the market is a proxy for control premium. However, control premium is function of some unobservable factors, some of them biasing the real control premium (bargaining power, lack of liquidity, noisy traders).
The unbiased indicators that have an influence on control premium are not observed (see Figure 1). Each of them is somehow biased and, moreover, they can be manipulated. We will discuss further all of these variables and the implications on estimation of the control premium.
Observable variables, respectively the offer price and the price on the market, are somehow biased due to the lack of liquidity, persistent on Romanian capital market, especially on the Romanian over the counter market (RASDAQ). For this reason, some studies simply were forced to ignore the lack of liquidity (see Dragotă et al, 2007) [14] . Liquidity is taken into account as an explanatory factor in other studies (see Caprio and Croci, 2008, Gaspar et al, 2005, etc.). In this study, we have taken as proxy for the liquidity two indicators: (1) the number of days in which the stock was traded in the analyzed period (trading days, TD); (2) the number of days from the last day when the shares were traded and the day of the offer (non-trading days, NTD) (the last one is a proxy for non-liquidity). Based on these considerations, the first hypothesis tested in this study is:
H1: Liquidity has a negative impact on control premium.
The alternative tested hypothesis is:
H1bis: The lack of liquidity has a positive impact on control premium.
All these indicators are not only drivers of the control premium, but also they influence the share price of the company. We expect that a company share price evolution around the time of an M&A transaction to be as shown in Figure 2. But the Romanian capital market is proved to be not efficient and among these there is a major lack of liquidity on the market, so these will affect our expectations.
Figure 2: The expected evolution of the price around an M&A transaction as long as the market is liquid. (a) in the case of an efficient market (the theoretical case); (b) in the case of a lag in the integration of information in the stock price.
However, due to lack of informational efficiency of the Romanian capital market and to the lack of relevant data, it is very difficult to estimate the synergy effects and the private benefits of control for Romanian listed companies, because the estimated gross control premium also includes a bias due to the informational efficiency. Consequently, we have not included in our study factors to account for the lack of market efficiency and/or for investors' behaviour. This is a limit of our study. However, Bradley (1980) considered the stock price two months before the announcement day in order to eliminate information leakage.
We should not ignore the negotiation skills of the transaction parties when explaining the size of control premium. Therefore, it is equally important to understand the psychological typologies or the bargaining power of the buyer and/or the seller that can lead to a change in company's control (Varaiya, 1987; Massari, Monge and Zanetti, 2006). The hypothesis of different negotiating skills can not be excluded, especially when privatization transactions are analyzed, as trading prices may be questionable and can be skewed to lower levels. Moreover, an initial higher stake owned by the investor launching the offer can explain also a smaller control premium. For this reason, we have tested the second hypothesis as:
H2: An increase in negotiation power of the buyer will determine a lower gross control premium.
We have used as proxy for the buyer's negotiation power the stake owned by him or her before the announcement day (PBA), like in Walkling and Edmister (1985) and Dyck and Zingales (2004). The acquirer and the seller have not a perfect equal negotiation power. Transaction price, according to the Romanian legislation, is regulated towards the lowest level (see Section 3). An acquirer, who owns a stake in the targeted company, will have voting rights, and more inside information about the company compared with an outsider. This will lead to a lower premium (Albuquerque and Schroth, 2010). Also, it is possible that shareholders to be more likely to sell some of their shares to someone who know and not to an unknown investor. Based on these considerations, the third tested hypothesis is:
H3. The fact that the acquirer already owns a stake in the targeted company (he or she is an active investor) has a negative impact on control premium size.
Whether it is an active investor or an unknown investor for that company, the number of shares purchased can influence the control premium size. Shareholders will be willing to sell shares at a lower price if the buyer wants to purchase a smaller stake. On the other hand, if she wants to purchase a higher stake, the price will be higher and the size of a control premium will be higher too. Based on these considerations, the fourth tested hypothesis is:
H4: The stake purchased in the transaction has a positive effect over the control premium.
Both large and small companies are subject of transactions on the M&A market. It is expected that the ownership structure is more dispersed as the company is larger. In case of small companies, ownership can be more concentrated (in our case, 2-3 shareholders holding more than 60% of the share capital of the company) and less willing to give up their shares. They often do not have investments in other businesses, so they will be willing to sell their shares only at a significantly higher price than their actual price on the market. This factor is used in most of the studies regarding the control premium. However, the relationship between the firm size and private benefits of control is ambiguous (Massari, Monge and Zanetti, 2006). As proxy for the size of the company we can use the total capitalization before the transaction (Nenova, 2003, Gaspar et al, 2005) or the total assets of the company (Dyck and Zingales, 2004, Albuquerque and Schroth, 2010). Based on these considerations, the fifth tested hypothesis is:
H5: The size of the company is negatively related with control premium size.
We investigated the effect of ownership over the control premium (see Dyck and Zingales, 2004, Duggal and Millar, 1999). As a proxy we took the percentages of common shares owned by the largest shareholders and we determined an ownership concentration index using the sum of the square of the percents owned by the shareholders that held more than 5% of shares. This is very similar to the Herfindahl-Hirschman index used to determine the competition dimension in an industry using the market shares of the companies (see Luypaert and Huyghebaert, 2007). We expect that this index to have a positive effect on the amount of control premium. If a company is owned by fewer shareholders, they will be harder to be convinced to sell their shares, so the buyers would pay a higher premium to obtain the control. Based on these considerations, the sixth tested hypothesis is:
H6. Ownership concentration has a positive effect on the control premium.
It can be possible that some industries to have an impact on control premium. However, it is possible that others to have not such an impact. We wanted to test whether, in our case, the industry sector has an influence over the size of the control premium (as in Dyck and Zingales, 2004, Atanasov, 2005, Gaspar et al, 2004). Based on these considerations, the seventh tested hypothesis is:
H7. The industry has an impact on control premium.
Further, we present our database and the methodology of the study.
3. Database and methodology
The control premium can be estimated as the difference between the offer price and the stock market price immediately before the transaction is announced on the market (Dyck and Zingales, 2004) [15] . Buying a certain number of shares by launching a takeover bid offer does not imply nor preclude the possibility for the bidder to take effective control of the company. Thus, it can be noted that for certain companies control can be achieved with a 5% of the total shares issued by the company (see the companies with dispersed ownership structure), while for other companies having 49% is not enough (if another shareholder owns a bit more than 50%).
We have used data of the purchase (PPO) and tender offers (TO) [16] to estimate the control premium for the Romanian listed companies [17] . Tender offer (operations) have been regulated in Romania starting with 2002 [18] , so the database will contain several transactions that finished with a change in control that were made ​​through simple purchase offers for the period January 2000 - March 2002. Since 2004, Romanian legislation regulated also the acquisitions price for the PPO and the TO [19] , in the sense that it must be at least equal to the highest prices between the price paid by the buyer for the shares in the past 12 months and the weighted average prices of the traded shares of the issuer in the past 12 months. Our study took into account all operations on the BSE (Bucharest Stock Exchange) and RASDAQ (the Romanian equivalent for NASDAQ) during 2000-2011.
On BSE were launched 77 public purchasing offers in the period 2000-2011, but we have included in our database only 39 observations, due lack of data on several transactions [20] . Regarding RASDAQ, in the same period, there were recorded 1438 public purchase offers, but we included in the database only 1329 observations [21] .
We classified the PPO and TO according to the following four situations: (1) the bidder had the control of the company (more than 50% of the voting rights) and wanted to consolidate control, (2) the tenderer had no control (less than 50% of the voting rights) and aimed to gaining control but he could not obtain it, (3) the tender's aim was not the gaining of control and (4) the tenderer has no control, but obtained it after the transaction (see table 1).
Table 1. The number of the PPO and TO in Romania in the period 2000-2011.
The table presents the number of the purchase offers and tender offers from both BSE and RASDAQ markets classified according to the result of the operation in terms of the change in ownership.
BSE
RASDAQ
PPO or TO where the bidder gain control
4
PPO or TO where the bidder gain control
223
PPO or TO where the bidder had already control
25
PPO or TO where the bidder had already control
647
PPO or TO where the bidder have not gain control
5
PPO or TO where the bidder have not gain control
178
PPO or TO where the bidder's aim was not the gain of control
5
PPO or TO where the bidder's aim was not the gain of control
281
Total
39
Total
1329
In this table: PPO = purchase offer, TO = tender offer.
The bids have focused mostly on small stakes below 20%, although in about 28% of cases, investors focused on buying a majority stake of over 50% of the company's share capital (see figure 3).
Figure 3. The packages of shares, related to the company's share capital, that the bidder aimed to acquire.
However, the number of shares acquired in PPO and TO is much lower than the one from the offer. In more than 70% cases, investors have acquired less than 20% of the company's share capital and only in about 11% of cases they acquired more than 50% of the voting rights [22] (see figure 4).
The number of transactions fell significantly after 2004, from an average of over 200 transactions in the years 2000-2004, to an average of 50 transactions after 2005 (see figure 5). This is mainly due to the privatization of a large number of companies in the early 2000s, but it is possible that the regulations on the transaction price since 2004 to be another reason.
The aim of this study is to investigate the PPO and TO that led to a change in control of a company. For the period 2000-2004 there were a total of 227 operations in which bidders have acquired control (more than 50% of total voting rights). Investors have purchased stakes of different values ​​to secure their position in the company and in almost 40% of cases this meant a stake of less than 50% of the shares (see Figure 6).
Out of the 227 cases, 34 transactions have been completed mainly between 1999 and 2002 for companies that were listed for no more than 2 years and after the change of control, the new ownership decided to delist and to transform them in closed businesses.
We have analyzed the evolution of the control premium size between 2000 and 2011 and for the entire period. We have calculated the mean and median of the control premium in each year (see Table 2). It can be observed that is difficult to notice a pattern in its trend. Romanian economy has experienced major structural changes between 2000 and 2004 due to extended privatization process run these years. Thus, this "rush" in completion of privatization process might have triggered higher control premium than in the next years when the process was slowed down a little bit.
Table 2: Control premium evolution in time for the Romanian listed companies.
Year
No. of observations
Mean
Median
2000
30
97.06%
27.02%
2001
46
143.97%
18.33%
2002
22
149.48%
25.00%
2003
27
167.96%
40.63%
2004
22
43.17%
25.48%
2005
11
80.07%
45.24%
2006
5
37.39%
18.69%
2007
5
84.34%
9.41%
2008
1
6.94%
6.94%
2009
1
133.33%
133.33%
2010
1
12.50%
12.50%
2011
2
3.70%
3.70%
Total
173
115.36%
25.00%
The distribution of the control premium is depicted in Figure 7. Overall, the gross control premium for the Romanian capital market has a mean value of 115% with a median of 25%.
Figure 7. Distribution of the control premium. Control premium is not normally distributed and has a positive Skewness which reveals the fact that there are many premiums larger than the mean value. Mean value: 115.36%. Median: 25%. Minimum: -66.67%. Maximum: 1050%.
In 18 cases the control premium was negative. Even apparently strange, the phenomenon is present on other markets, too: Ødegaard (2007) reported negative control premium for the case of Norwegian companies. A simple explanation could be that the target firm was in financial distress. Another explanation could be that the seller feels negative benefits from retaining control of the target firm and he or she expects that from transferring the control of the target to a new shareholder, some positive benefits can appear (Kruse et al., 2006).
First, the gross control premium was estimated, based on relation (1). To limit the influence of outliers, this database was reduced by removing 5% of the inferior and upper limit of the database (5-95%), so the main database for this study consists in 173 transactions, which have been finalized with a change of control. Secondly, we have tested the hypothesis presented in Section 2. From a practical point of view, we have used a regression analysis, in which gross control premium (GCP) was the dependent variable. The explanatory variables are described in Table 3 [23] .
Table 3. Explanatory variables used in the model.
Relevant studies which considered these variables are also presented.
Indicator
Explanation
Relevant studies
TD
Trading days - the number of days in which the share was traded in the analyzed period
Dyck and Zingales (2004), Gaspar et al (2005)
NTD
Non-trading days - the number of days from the last day when the shares were traded and the day of the offer (liquidity proxy)
Gaspar et al (2005), Caprio and Croci (2006)
PBA
Stake owned before the announcement day - proxy for the power in negotiation
Walkling et al (1985), Dyck and Zingales (2004)
PSP
Percent of share purchased in the transaction
Barclay and Holderness (1989), Walkling et al (1985), Dyck and Zingales (2004)
AINV
Active investor - dummy variable (1 if the acquirer already owns some of the shares of the target-company; 0 if not)
Albuquerque and Schroth (2010)
CAP
The total capitalization (million RON) of the target-company before the transaction
Nenova (2003), Dyck and Zingales (2004), Massini et al (2006), Gaspar et al (2005)
TA
The total assets (million RON) of the target-company before the transaction
Albuquerque and Schroth (2010), Dyck and Zingales (2004)
HHI
Ownership concentration index
Dyck and Zingales (2004), Duggal and Millar (1999)
DSEC
Industry sector - dummy variable (1 for a firm in a industry, 0 in other industry) - a total of 12 industries
Dyck and Zingales (2004)
Some summary statistics for the variables used in the model are depicted in Table 4. We have tested, also, for identifying multi-colliniarity. The correlation matrix for these is presented in Table 5.
Table 4. Dependent variables summary statistics
This table summarizes the characteristics of the determinants of the control premium function. Most of these variables are specific to the target company or to the acquirer. The sample consists of all transaction made to acquire control on the Romanian capital market between 2000 and 2011.
Variables
Mean
Standard deviation
Median
Min
Max
Gross control premium (%)
115.36%
216.3
25.00
-66.67
1050.00
Percent of shares before the announcement day (%)
19.80
19.30
14.33
0.00
49.91
Percent of shares purchased in the transaction (%)
50.97%
26.80
51.91%
0.50%
99.26%
Non - Trading days from the last day when the shares were traded
60.66
120.18
14.00
1.00
813.00
Target's capitalization (million RON)
4.325
18.512
0.423
0.011
168.303
Trading days between 2000-2012
254.71
456.78
82.00
2.00
2929.00
Active investor
0.64
0.481
1.00
0.00
1.00
Ownership concentration index
0.31
0.208
0.27
0.01
0.92
Table 5: Correlation matrix between the tested variables.
PBA
PSP
CAP
TD
AINV
TA
HHI
NTD
PBA
1
PSP
-0.82
1
CAP
-0.04
0.15
1
TD
0.20
-0.23
0.41
1
AINV
0.77
-0.65
-0.03
0.09
1
TA
0.00*
0.12
0.86
0.51
-0.02
1
HHI
-0.30
0.43
-0.01
-0.09
-0.38
0.09
1
NTD
-0.02
0.07
-0.11
-0.19
-0.06
-0.16
0.05
1
Note: * a level of 0.00857 was recorded.
Overall, the percent of the shares owned before the transaction by the acquirer was around 20% and to gain the control of the company he or she purchased 51%. The mean from the active investor variable is higher than 0.5 so we can say that mainly the acquirer was already a shareholder of the company. Also, as the non-trading days and the sum of the trading days between 2000 and 2012 can reveal that there is a lack of liquidity, persistent on Romanian capital market.
We divided our database in 12 major industry sectors and we used industry dummies (for the industry of the target-firm). The statistics for the control premiums for each of these industries are presented in table 6.
Table 6: Control premium in different industries
This table summarizes the characteristics of the control premium for the 173 trades in our sample. We determined the average and median control premium for every major industry sector in Romania as well as the standard deviation recorded. The sample consists of all transaction made to acquire control on the Romanian capital market between 2000 and 2011.
Industry
No. Firms
Mean
Median
Standard deviation
Agriculture
7
52.47%
16.78%
0.8688
Clothing
12
136.63%
16.44%
2.6973
Commerce
25
198.94%
34.29%
3.2538
Construction
9
34.40%
12.50%
0.4637
Real Estate
15
159.82%
73.91%
2.0873
Food industry
22
46.41%
7.18%
1.4207
Chemical industry
8
35.16%
5.46%
0.5385
Machinery and equipment
6
223.34%
156.25%
2.6913
Manufacturing
23
109.07%
16.67%
2.4490
Services
30
105.72%
42.06%
1.7344
Transport
7
169.33%
6.87%
2.3699
Tourism
9
84.68%
49.25%
1.3362
Total market
173
115.36%
25.00%
2.1629
4. Results and discussion
In order to test the hypotheses presented in section 2, we have employed a linear regression model to estimate the control premium determinants. Consistent with our hypotheses, the regression results in Table 7 highlight that the variables used in the model have the expected effect on the control premium.
Table 7. The determinants of the control premium. Linear regression model.
This table reports regressions of specific determinants of the takeover control of a company on the control premium. The determinants are: firm's capitalization - target total capitalization before the transaction (logarithm in regression) (L_CAP), trading days - the number of days in which the stock was traded in the analyzed period (liquidity proxy) (TD), percent of shares held before the announcement day - power in negotiation of the buyer (PBA), Percent of share purchased in the transaction (PSP), active investor - dummy variable - AINV (1, if the acquirer already owns some of the target's shares, 0, if not), ownership concentration index (HHI), and by the sector (if the company is acting in Commerce, dummy variable DCOM = 1). Each regression uses 173 observations. t-statistics are in parentheses. The symbols *, **, *** denotes statistical significance at the 10%, 5%, and 1% levels, respectively.
(1)
(2)
(3)
(4)
Variable
C
4.89***
3.72***
4.76***
(4.46)
(3.45)
(4.28)
L_CAP
-0.26***
-0.30***
-0.31***
(-3.24)
(-3.87)
(-3.83)
PBA
-2.00**
(-2.46)
PSP
1.55***
1.36***
(2.49)
(2.63)
AINV
-0.58*
(-1.70)
HHI
1.80**
2.14***
1.51*
(2.24)
(2.69)
(1.91)
TD
-0.00058*
(-1.82)
DCOM
0.93**
0.80*
0.90*
0.87*
(2.10)
(1.88)
(2.07)
(2.00)
R-squared
11.57%
17.93%
16.33%
12.11%
All the tested hypotheses were supported. According to H1, the number of trading days in the analyzed period (TD) is inversely related to control premium (see Equation 4): liquidity is inversely related to control premium. However, it can be noted that the other proxy for liquidity (non-trading days before the offer) was not statistically significant. The result can be interpreted cautiously as long as the trend of the market in this period was an upward trend up to the crisis inception (2008). For this reason, in a methodology regarding the estimation of control premium with the objective to estimate a fair market value, this variable could be ignored. Our results are in accordance with the results of Gaspar et al. (2005).
In accordance with H2, the negotiation power of the buyer, quantified through the percent of shares held before the announcement day, is inversely related to the level of control premium (see Equation 1). The investor who has a higher percent of the target company shares will benefit from this position in decreasing the price paid in the offer. Our results are in accordance with the results of Walkling et al. (1985) and Dyck and Zingales (2004).
Also, in accordance with H3, the fact that the buyer has a number of shares before the announcement implies a decrease in control premium (see Equation 3). In a methodology for estimation of control premium in a business valuation with the objective to estimate a fair market value, these two variables should be ignored.
In accordance with H4, the percent of shares bought in the transaction (PSP) is directly related to control premium, as in Barclay and Holderness (1989).
As expected (see H5), the size of the company is inversely related to control premium. The result is also in accordance with other studies: Barclay and Holderness (1989), Nenova (2003), Albuquerque and Schroth (2010), Gaspar et al. (2004).
Ownership concentration (HHI) has a positive impact on control premium.
Regarding a potential impact of the industry, we have found out that only in the case of the company that are acting in commerce there is a positive impact on control premium. The same results were obtained by Dyck and Zingales (2004), Atanasov (2005), Massari et al. (2006).
The levels of the variables have to be interpreted cautiously (see, for instance, the high levels for the intercepts of the regressions). We have some doubts about the predictive capacity of the regression [24] . However, the signs for variables can be useful for practitioners in order to estimate a control premium in business valuation. As such, a relation for the estimation of gross control premium can be written as:
(1)
For a practitioner, according to all the standards in valuation, in estimation of a market value, control premium should not count for the lack in liquidity, agency problems and also it is consider an equal power in negotiation for the seller and for the buyer (IVSC, 2008). Based on relation (1), we can determine an adjusted control premium (ACP), taking into account the restrictions imposed by this standard, as:
(2)
Relations (1) and (2) links directly the level of control premium with the number of shares acquired (PSP).
5. Conclusions
The determinants of control premium for Romanian listed companies are similar to those putted in evidence by the financial literature. Control premium is directly related to the percent of share purchased in the transaction and to the ownership concentration. Also, if the acquired company is acting in Commerce, control premium seems to be higher. Control premium is indirectly related to the size of the acquired company, the liquidity of the shares, the power in negotiation of the buyer, and to the fact that the acquirer already owns some of the target's shares.
