The regulatory process of merger control

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• Contents
• Introduction
• 1. Institutional Framework
• 1.1 Merger Control: the Necessity and Complexity of Enforcement
• 1.2 Procedure of Regulation
• 1.3 The Scope of Intervention
• 2. Literature Review
• 3. Research Design
• 4. Methodology
• 5. Data
• 6. Empirical Results
• 6.1 Initial Merger Announcement
• 6.2 Decision Announcement
• 6.3 The Relationship between Generated CAR
• 6.4 Endogeneity and Self-Selectivity6.5 Robustness Check
• 7. Discussion of Results
• Conclusion
• References
• Appendices


Introduction

The merger control is an essential component of competition policy. Mergers can reduce competition and lead to higher prices or inefficiency in production. On the other hand, merger can cause positive effects, for example, in the form of economies of scale. Therefore, a competition authority should act as a judge prohibiting anticompetitive combinations and clearing procompetitive ones, so encouraging economic growth. The problem related to competition enforcement is that potential benefits and risks of a merger are difficult to assess before a merger takes place. This may lead to so-called type I and type II errors made by a competition authority. Type I error occur when an authority prohibits procompetitive mergers, whereas type II errors imply outright clearance of anticompetitive mergers that should have been prohibited or challenged by remedies. Consequently, the decisions of a competition authority need to be revised and analyzed in order to reveal their weaknesses and inconsistencies and to eliminate them. merger control expertise

In the last three decades, there has been growing interest in merger control assessment. Although the topic is quite well researched, there is no unified approach applied to this research topic. The majority of studies focus on investigation of factors influencing the competition authorities' decision or on the stock market reaction to initial merger proposals and further authorities' decisions announcements. Although all of these studies are devoted to evaluation of merger regulation, they serve for different goals and looking for answers to different research questions. The first group of studies aim to understand the actual logic of a competition authority by identification of factors influencing its decision and to compare their findings with economic reasons for merger control (e.g. Khemani, R. and Shapiro, D., 1992; Bergman, M., Jakobsson, M. and Razo, C., 2005). Another bundle of papers investigates the impact of merger events on the competition level by observing the investors' response (Eckbo, E., 1983; Aktas, N., Bodt, E. and Roll, R., 2004).

Despite a variety of existing studies dedicated to the appraisal of merger regulation, little attention has been paid to possible policy implementation of gained results. Duso, T., Neven, D. and Roller, L. (2007) and Duso, T., Gugler, K. and Yurtoglu, B. (2011) presented a clear framework for analysis of effectiveness of regulation by identifying the type I and type II errors made by the competition authorities.

As for the Russian studies, there is a strong lack of qualitative examinations devoted to Russian merger regulation. Several Russian researchers addressed this research question using a qualitative analysis. For example, Avdasheva, S. and Kalinina, M. (2012) performed a comparative analysis, where they examined decision made by the FAS and the European Commission on similar cases. Other studies are of methodological nature and discuss the existing problems in Russian procedure of merger control and possible ways to deal with them (Shastitko, A., 2011; Shastitko, A., 2012; Sushkevich,A., 2012). To our knowledge, there is the single study containing econometric analysis of Russian merger processes. Using the so-called event study methodology, Tsytsulina, D. (2012) examined the stock market response to merger announcements among Russian steel companies. However, this paper did not consider the effect of the competition authority's actions.

Our study possess several distinct features. First of all, it applies econometric techniques to Russian data on merger control. Secondly, we do not concentrate on the single industry and analyze a broader range of transactions. Furthermore, we focus on economic effects of Russian antimonopoly body's decision.

The aim of the present paper is to assess Russian merger regulation using the event study approach. Particularly, the effect of using remedies in merger control will be investigated. To reach the goal, a series of question needs to be addressed: How does the stock market react to the initial merger announcements? How does the Federal Antimonopoly Service's (FAS) decision influence the investors' anticipations about transactions? Does the FAS take into consideration the stock market reaction to the initial merger proposals? Do remedies in Russia truly reduce the anticompetitive effects of mergers?

Although the event study methodology is quite complicated, it has several advantages compared to others. First, the stock market provides objective reaction to the events. Additionally, while the use of stock market data allows separating the merger and the decision announcement effect, data on accounting profits present only the net effect (Duso, T., Gugler, K. and Yurtoglu, B.,2011).

On the first step of the research, we analyzed the effect of initial merger announcements on both participating companies and their rivals. Our data revealed no reaction to the announcements in general case.

The next step included the investigation of effect of the antimonopoly body's decisions announcements. The main findings are the positive reaction of merging companies to outright clearance and negative response of both merging firms and their competitors.

This reaction was revised during the third stage of our analysis, which showed that negative reaction relates to only nonsystematic costs of remedies imposed to merging companies. Finally, we investigated the problem of possible endogeneity.

The dataset for the empirical analysis was constructed based on the Zephyr database that contains the initial merger announcements dates. The sample comprises 230 transactions that took place in Russia between 2005 and 2014.

The outcomes of the present research may be valuable for Russian competition authority because they highlight the flaws in the current merger control enforcement, so stimulating to find the ways for improving and refining of the existing procedure of regulation. Moreover, our study is an essential step in the process of Russian merger regulation assessment.

The paper is organized as follows: firstly, institutional framework of merger control in Russia is presented. After that, existing relevant studies are reviews. Next section present design of our research. Then, the methodology is discussed. This one is followed by the description of data and data collection process. After that, results of empirical analysis are presented. The final chapter discusses the obtained results and concludes the paper.



1. Institutional Framework

This paper aims to assess the merger control in Russia. However, we firstly need to discuss why mergers have to be regulated and why this regulation is worth being assessed. Furthermore, we should have a clear vision of how the merger regulation is put into practice in the Russian Federation. Thus, this section considers the general complications that any antimonopoly body faces during the merger control implementation and provides a legal context of Russian merger regulation procedure.

1.1 Merger Control: the Necessity and Complexity of Enforcement

Mergers, acquisitions, and other types of business combinations are subject to a high extent of antitrust scrutiny. The reason is that a merger can cause both negative and positive effects. Companies merge for variety of reasons, and not all of them have anticompetitive nature. The main benefit from a merger is the synergy effect, which may take several forms. A deal may result in economies of scale and further cost efficiency. For other companies, a merger can reduce transaction costs. Moreover, many companies see in a merger a way to diversify, reduce operational risks and cost of capital (Trautwein, F. 1990; Amihud, Y. 1986). Avdasheva, S., Shastitko, A. and Kalmychkova, E. (2007) indicated a Russia-specific incentive for business combinations. This motive is connected with relative underdevelopment of Russian economic law. According to researchers, many companies prefer to arrange business agreements due to poorly protected property rights and very high costs related to this protection. As a result, this fact negatively affects the investment attractiveness of many companies.

Although benefits from mergers gained by the participating companies may transform into benefits for consumers in the form of lower prices, a wider range of products or higher quality of goods, mergers may also lead to deadweight losses and reduced consumer surplus. Some estimates showed that the deadweight losses might reach a very high level of 6% of GDP (Avdasheva, S., Shastitko, A. and Kalmychkova, E. 2007). Williamson, O. (1968). There is a bunch of theoretical studies, which shows the possible negative effects of mergers and acquisitions. Most researchers concluded that horizontal mergers lead to higher prices and lower output, so decreasing the social welfare (Gaudet, D. and Salant, S., 1988; Perry, M. and Porter, R., 1985; Salant, S., Switzer, S. and Reynolds, R, 1983). The losses might be even higher if the industry deviates from the Cournot oligopoly (Farrell, J. and Shapiro, C., 1990). Salinger, M. (1988), on the other hand, analyzed vertical agreements and concluded, that although the monopolization due to vertical combination might be not very obvious, it would lead to the price increase.

The simultaneous existence of both positive and negative consequences of a merger reveal the necessity of merger regulation: negative effects should be prevented, whereas positive ones need to be fulfilled. Williamson, O. (1968) developed an analytical model, which stated that there should be a trade-off between cost savings and a price increase caused by a merger. Therefore, a competition authority should act as a judge prohibiting anticompetitive combinations and clearing procompetitive ones, so encouraging economic growth. It needs to weigh possible benefits and risks of a transaction. From this point of view, Motta, M. (2004) provided an excellent definition of a competition policy by emphasizing its economic goals: “the set of policies and laws which ensure that competition in the marketplace is not restricted in such a way as to reduce economic welfare”. However, the competition authority has to carry out its analysis before a merger or acquisition takes place. As a results, the errors may occur and negatively affect the competition level. For this reason, the merger control is worth being revised and investigated in details.

1.2 Procedure of Regulation

The merger control in Russia is conducted by the Federal Antimonopoly Service (FAS), which activity is governed by the regulations that were first implemented in 1991. In 2006, the new Federal Law № 145-FZ “On Protection of Competition” was passed. This law is still valid today and defines the transactions subject to state control over economic concentration and the procedure of this control. Further, we will use “merger control” instead of “control over economic concentration”.

According to the Federal Law, the transactions subject to the state investigation may be divided into three groups:

ѕ mergers, i.e. transactions resulting in combination of several companies into new one;

ѕ transactions with voting shares, including acquisitions, when a bidder company gains control over a target company;

ѕ transactions with assets, which book value exceeds 25% of the total assets of a selling company.

Despite the different nature of the above-mentioned transactions, we will call them mergers and acquisitions, since they have similar economic consequences.

The law also defines conditions for transactions that have to receive a prior FAS's consent. Currently, the main thresholds are as follows: a merger or acquisition of several commercial organizations needs to be approved beforehand if the aggregate value of assets according to the balance sheet at the latest reporting date exceeds seven billion rubles or if the aggregate revenues from sale of commodities of such organizations for the calendar year preceding the merger exceed ten billion rubles, or where one of the organizations is included into the Register of economic entities.

Figure 1 describes the general procedure of Russian merger control. Article 33 of the Federal Law № 145 specifies that the FAS has 30 days to make its decision on a transaction. Based on the performed analysis, it can either clear a transaction unconditionally or clear and give remedies, or block a deal or prolong the period of examination. If the FAS decides to prolong, it has two month more to make the final solution.

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Figure 1. The procedure or merger control in Russia

Remedies are usually defined as special conditions developed by the competition authority to remove the concerns identified during the investigation. There are two basic groups of remedies: structural and behavioral (Balto, D. and Parket, R., 2000; Merger Remedies Study, 2005). Structural remedies refer primarily to the divestiture, i.e. alienation of assets in order to restore the competition level in an industry. Behavioral remedies constrain the behavior of merging companies after the completion of transaction. Article 23 of the Federal Law “On Protection of Competition” enumerates examples of possible remedies; so these may be: to grant a right to facilities of industrial property protection, to transfer the property rights, to preliminary inform the antimonopoly body about intention to fulfill actions provided for in the determinations, to sell particular volume of products through commodity exchange.

At a first glance, Russian merger control procedure is similar to the European one: in both cases, the value of assets and revenues act as a threshold determining the subjectivity of a deal to prior state approval. Moreover, the definitions of negative consequences of a merger are also alike. There are, however, differences as well. The European regulation implies a two-stage procedure (Duso, T., Gugler, K. and Yurtoglu, B., 2011). At the end of the Phase I, the EC may proceed the examination if a transaction seems dangerous to competition. However, the EC cannot block a deal after the first stage. This is the crucial difference between Russian and European procedures. Although Russian law states that prolongation may be a result of dangerous transaction, the FAS usually decides to prolong in case the information provided by the merging companies is not sufficient.

A distinctive feature of Russian merger control is that, unlike the European legislation, there is no unified instruction about conducting a merger analysis. The only existing document that allows supposing of how this analysis is performed is Order № 108 «On Approval of the Proceedings of Analysis and Assessment of Competition Environment on Goods Markets». According to this document, the study of competition environment can be divided into following steps:

ѕ to establish the geographical and product borders of a goods market;

ѕ to estimate market capacity, market shares of entities, and concentration level;

ѕ to define the entry barriers;

ѕ to assess the competition environment and possible risks due to transaction.

However, these stages are generic and do not relate directly to the merger control. Therefore, they only enable to hypothesize the logic of Russian antimonopoly body.

1.3 The Scope of Intervention

The dynamics of cases processed by the FAS is quite variable. Figure 2 demonstrates the total number of applications and decisions on them during the period between 2007 and 2012. The information about other years is not publicly available. As the bar chart presents, the total number of applications considered by the FAS decreased more than twice during the particular period. This is caused mainly by several amendments of the assets and revenues thresholds. As a result, the FAS's overload decreased due to higher values of the thresholds and a lower number of applications processed. However, the quantity of applications remains very high comparing with the number of applications notified to the European Commission (EC). For example, during the same period, the EC considered 1875 cases and only 283 notifications in 2012.

Figure 2. Number of applications considered by FAS. Source: the FAS's annual reports

Figure 3 shows the structure of decisions made by the FAS. First of all, there is a growing trend in frequency of remedies. Talking about the type of remedies given, behavioral remedies prevail over structural ones. In 2007, behavioral remedies accounted for 96% of total number of remedies given by the FAS. This is opposite to the Europe, where more than 80% of remedies were structural (Avdasheva, S., Shastitko, A. and Kalmychkova, E., 2007).

Another remarkable fact is a lower and quite stable rate of prohibitions, which fluctuates about 2% of total number of decisions. It is interesting that the EC's decisions are characterized with the same low rate of rejections (Aktas, N., Bodt, E. and Roll, R., 2004; Duso, T., Gugler, K. and Yurtoglu, B., 2011). However, unlike the EC, Russian FAS usually blocks transactions due to missing documents or insufficient amount of information provided along with the application, rather than due to negative economic consequences.

To conclude, Russian merger control has several features similar to the European one. It allows for use of remedies and is also characterized by a low number of prohibitions. However, unlike the EC regulation, it lacks for clear and unified instructions on conducting merger analysis, so creating difficulties in the process of assessment the FAS's activity.

Figure 3. The structure of decisions



2. Literature Review

There is a great variety of studies covering the assessment of merger regulation in the European Union, the United States and Canada. Existing studies may be divided into three categories according to the classification presented by Bougette, P. and Turolla, S. (2006) and based on the applied approach. They are the cost-benefit analysis, the discrete choice models approach and the event study approach.

The cost-benefit analysis. This group of studies are based on weighing the benefits and costs of mergers. The first studies in this field were carried out by Long, W., Schramm, R. and Tollison, R. (1973), Asch, P. (1975) and Siegfried, J. (1975). Their aim was to quantitatively assess the welfare effects related to the antitrust regulation. These effects were primarily linked to the deadweight losses (“Harberger's triangle”, Harberger, A., 1954). For example, Long et al. estimated a linear regression model to examine the factors affecting antitrust activity. Costs in this model consisted of litigation costs initiated by the government. The results showed the quadratic relationship between concentration level and the number of filed cases. Another study was conducted by Postema, B., Goppelsroeder, M. and Bergeijk, P. (2006). Using the applied game theoretic approach and Monte-Carlo simulations (Crooke, P., Luke, F., Tschantz, S. and Werden, G., 1999), the authors estimated the net annual welfare gains resulted from merger regulation in the Netherlands, which amounted to 100 million euros. They also concluded that the gross gain over the analyzed period between 1998 and 2002 was about 770 million euros. However, cost-benefit analysis is a very complicated and often inaccurate technique, since it is difficult to provide strong evidence of selecting appropriate proxy for benefits and costs of a merger.

The discrete choice models approach. This approach involves the use of econometric models with discrete dependent variable, such as probit- or logit-models and their ordered and multinomial modifications. The approach allows identification of important factors explaining a competition authority's decisions. One of the most cited research was carried out by Khemani, R. and Shapiro, D. (1993). Using Canadian data for running the ordered probit model, the authors found that the most important factors were market shares, concentration index and barriers to entry. Their results were close to the conclusions of Coate, M., Higgins, R. and McChesney, F. (1992), who applied the same approach to the American data. They also emphasized a low predictive power of ordered models due to low rate of prohibitions in the sample. Weir, C. (1992) used the UK's data and obtained different results: the post-merger market shares did not influence the authority's decisions. Williams, F. (2003) analyzed the European merger cases by estimating a probit-model. They concluded that the post merger market share and the increase in market share significantly increased the probability on a merger to be prohibited. Bergman, M., Jakobsson, M. and Razo, C. (2005) found that market share was an important determinant of an authority's decisions. Moreover, they included several political variables, such as nationality of merging companies and the identity of the commissioner. However, these variables appeared to be insignificant. In contrast, Bougette, P. and Turolla, S. (2006), using the multinomial logit-regression, concluded that the probability of giving remedies increased when the acquirers were from the U.S. or France. Moreover, the authors identified that the pattern changed when Mario Monti took up a post of the commissioner. They also found the inter-industries differences, e.g. energy and communication sectors were subject to “stricter” decisions, i.e. remedies, while the retail trade increased the probability of an outright acceptance. They did not try, however, to implement the ordered probi- model, which could be more suitable for their analysis, since the EC's decisions can be naturally ranked depending on their “severity”. Nevertheless, important contribution of this paper was the use of artificial neural networks, which allows for in-depth study of factors influencing the EC's decision. Andreasson, J. and Sundqvist, C. (2008) studied the effect of EC merger control before and after 2004. Their main conclusion was that the post-merger market share became less significant after the alterations in the EU regulations.

The event study approach. This approach is based on the efficient markets hypothesis, which enables to examine market reaction to the merger and authority's decisions announcements. Ellert, J. (1976) presented one of the pioneering studies using event study in the analysis of antitrust regulation. However, this study did not investigate the reaction of rivals to the merger events. Later, Eckbo, E. (1983) addressed this question on his research. The analysis of stock market data of Canadian companies showed that both merging parties demonstrated positive and statistically significant abnormal return after merger announcement. After the blocking decision these returns turned negative, which meant efficiency of regulation. However, in some cases the abnormal returns of rival firms remained positive even after the blocking decision. After that, Eckbo, E. and Wier, P. (1985) found again that rivals generated positive abnormal returns around a merger announcement date. Authors rejected the collusion hypothesis in favor of their information hypothesis. Simpson (2001) received similar results. Solvin M., Sushka, M. and Hudson, C. (1991), however, obtained opposite results. They analyzed 42 horizontal mergers in the airline industry and concluded that the Civil Aeronautics Board promoted the collusion among existing market players. Brady and Feinberg (2000) examined the effects of the change in the EU merger enforcement regime on the market indices and individual companies. They found that the indices did not demonstrate a significant reaction, while many companies did. On the contrary, Aktas, E. and Derbaix, A. (2003) analyzed the automobile sector and found that neither participating companies nor their competitors demonstrated any significant reaction to the initial merger announcement, while several customers showed significant and negative reaction.

Aktas, N., Bodt, E. and Roll, R. (2004) analyzed the stock market reaction to the European Commission's (the EC) announcements. The authors concluded that actions of the EC were consistent with its antimonopoly goals, and there was a clear evidence that shareholders took into consideration the decisions of the EC. Moreover, the authors showed that the probability of the EC's intervention did not depend on acquirers' nationality. However, the market expected a more costly operation when an acquirer was outside the EU. This study was the first attempt to address the problem of endogeneity in merger analysis.

A great contribution to the merger analysis based on the event study methodology has been made by Duso and his colleagues. Duso, T., Gugler, K. and Yurtoglu, B. (2010) addressed the problem of usefulness of event study for merger analysis. Specifically, they considered the relationship between generated abnormal returns and the ex-post profitability (Gugler, K. and Siebert, R., 2004) of merging companies. The results showed a strong and significant dependence between these variables, especially for a long pre-announcement windows (-25;+5) and (-50;+5). On the contrary, McAfee, R.P., Williams, M.A. (1988) asserted that event studies are not able to detect anticompetitive mergers. However, their analysis lacked for theoretical reasoning and was based on the simple case. Moreover, Fridolfsson, S. and Stennek, J. (2009) showed that anticompetitive merger might reduce the rivals' share prices just like McAfee and Williams observed.

Duso, T., Neven, D. and Roller, L. (2007) combined the event study approach and the discrete choice analysis. Estimating the abnormal returns, they identified type I and type II errors made by the competition authority. Type I errors occur when an authority prohibits a procompetitive merger, while type II errors take place when an authority clears an anticompetitive merger. They defined type II error as the clearance of a transaction, which generated positive abnormal returns for rivals at the announcement date. However, this definition is questionable. In many studies competitors demonstrated positive reaction to merger announcement (Eckbo, E.,1983; Simpson, J., 2001), but no one related this directly to the anticompetitive nature of a deal. After that, authors estimated binary choice models to identify determinants of the frequency of errors. Eventually, they concluded that institutional and political factors did matter and influenced the error occurrence.

Duso, T., Gugler, K. and Yurtoglu, B. (2011) presented a new view on this problem and tried to econometrically assess the effectiveness of European merger control using stock market data on companies involved in business combinations during 1990-2002. They looked at the relationship between companies' abnormal returns around the merger and antitrust decision announcements. They concluded that outright prohibition eliminated completely the rents generated around the merger announcement. However, remedies seemed to be only half-efficient. Furthermore, outright clearance led to the increase in rivals' profitability, which indicated the possible type II-errors.

As for Russia, there is a lack of quantitative examination of merger regulation. Avdasheva, S. and Kalinina, M. (2012) presented a comparative study analyzing decisions of Russian and European competition authorities on similar transactions. They found that many Russian behavioral remedies just replicated the law. Nevertheless, they concluded that the FAS conducted an in-depth analysis of markets borders. Shatitko, A. (2011, 2012) and Suchkevich, A. (2012) analyzed existing issues and flaws of Russian merger control and suggested adopt several procedures from the European law. The only published Russian study was performed by Tsytsulina, D. (2012). She analyzed the market reaction to merger announcements of Russian metal companies. She found that Russian participants did not demonstrate significant reaction, while both foreign and local competitors reacted negatively to these announcements. She also considered separately effects of vertical and horizontal mergers and concluded that vertical mergers did not cause significant reaction. She did not, however, investigate market reaction to decisions of the FAS.

To sum up, although the topic is quite well researched by American, Canadian and European authors, “there is almost no systematic econometric evidence on whether merger policy achieves what it is supposed to achieve” (Duso, T., Gugler, K. and Yurtoglu, B., 2011). The choice of a particular approach depends on the hypotheses that are to be tested and will be discussed in the next chapter.



3. Research Design

This section describes the framework of this research and the hypotheses that need to be tested. Our study is focused on the assessment the merger regulation in Russia. As it was mentioned in the literature overview, different approaches could be used to investigate this research topic. We use the event study analysis to evaluate the FAS's decisions through the stocks reaction. This approach has several strong advantages. First of all, stock market provides an independent assessment of the events (Duso, T., Neven, D. and Roller, L., 2007), which means that the evaluation is exogenous to the antimonopoly body's decisions. In Addition, the stock market data are prospective, so they allow capturing dynamic effects of the observed events on companies' performance (Aktas, E. and Derbaix, A., 2003).

The present research will be carried out in four major steps. The first step is to investigate the stock market reaction to initial merger announcements, the second one is analyze the response to the FAS's actions. Then, based on results of the first two stages, the examination of the relationship between these reaction will be done to gain conclusions about the effectiveness of the FAS's activity. And finally, the test for possible endogeneity should be performed in order to discuss the reliability of the results.

Implementation of first two steps is complicated due to simultaneous existence of two basic hypotheses: the Market Power Hypothesis (MPH) and the Economic Efficiency Hypothesis (EEH) (Eckbo, E., 1983; Eckbo, E. and Wier, P., 1985; Aktas, E. and Derbaix, A., 2003). The MPH is derived from the oligopoly theory (Stigler, G.,1950; Salant, S., 1983) and states that a merger provides companies with opportunity to restrict the competition and gain benefits. At the same time, it is possible to consider two sub-hypotheses within the MPH. The first one is the Collusion Hypothesis, which implies higher probability of collusion among fewer number of companies after the merger. In this case, both merging and rival companies benefit from the higher post-merger prices, while the consumer surplus would decrease. This fact should be reflected in higher stock prices around the merger announcement. The second sub-hypothesis is associated with the Predatory Pricing Model, according to which a new bigger firm is able to decrease its costs and start the price war (Eckbo, E. and Wier, P., 1985). Under this sub-hypothesis, rivals' share prices should fall due to their inability to win this war.

The EEH consists of two effects. The productivity effects implies the ability to reach economy of scale after the merger. As a result, a merged company would decrease its average costs and product price, and rivals' stock prices would fall. Because of the information effect rivals get able to use the merged company's technology, so the rivals' market value increases.

Results of the first two steps enables one to test a set of following hypotheses.

H_1: Merging companies demonstrate positive and significant reaction to merger announcement and outright clearance of the FAS.

As both the EEH and the MPH regardless of their sub-hypotheses imply higher profitability for participating companies, market anticipation should be reflected in higher current stock prices when a merger is announced and the antimonopoly body gave unconditional permission to complete the transaction. The second event is important because it allows the fulfilling of previously expected profitability increase. The similar hypotheses have been tested by many researchers (e.g., Aktas, N., Bodt, E. and Roll, R., 2004, 2004; Eckbo, E., 1983). However, the results vary considerably from highly significant and positive reaction (Eckbo, E. and Wier, P., 1985; Duso, T., Neven, D. and Roller, L., 2007) to insignificant (Aktas, E. and Derbaix, A., 2003). Significance also varied across different windows of estimation and a country of origin of participating companies (Tsytsulina, D., 2012). We will also anticipate diverse results depending on the estimated window.

H_2: Reaction of competitors to both merger announcement and the FAS's clearance has the same sign.

It is difficult to assume the exact sign of market response due to a complicated nature of the MPH and the EEH discussed before. Nevertheless, it is still reasonable to suppose that the sign should not alter after the FAS's outright decision just for the same reason as in case of previous hypothesis: this decision does not change the market conditions, it only fulfils either the benefits or the threatens for rivals. Duso, T., Gugler, K. and Yurtoglu, B. (2011) obtained the same signs, which, however, were insignificant.

H_3: Reaction of merging companies to the decision of giving remedies is negative.

This hypothesis refers to the fact that remedies are supposed to restore the pre-merger level of competition in the market. On the one hand, decision with remedies does not prevent from gaining benefits of a merger, but it causes extra costs and restrictions, so decreasing the gains of merging companies. Therefore, more costly merger should be reflected in negative anticipations of investors. The similar hypothesis was also suggested by Duso, T., Gugler, K. and Yurtoglu, B. (2011).

Unfortunately, it is impossible to estimate the effect of prohibitions due to non-availability of data. For further clarifications, see the data description chapter.

H_4: There is a difference in reaction among vertical/conglomerate and horizontal transactions. Vertical mergers demonstrate lower significance.

This hypothesis has been addressed by many authors (e.g. Tsytsulina, D., 2012; Eckbo, E., 1983). It is linked to the theoretical studies (Salinger, M., 1988), which assert that negative influence of vertical mergers on competition is less than of the horizontal ones. Empirical studies confirm that reaction to initial merger announcement depends on the nature of a transaction (Eckbo, E. and Wier, P., 1985; Duso, T., Gugler, K. and Yurtoglu, B., 2011).

Although abnormal return estimations might give some insights about market's perception of merger events in Russia, they are not able to draw conclusions about the quality of regulation. Hence, to make inferences about the effectiveness of control, we implement the methodology developed by Duso, T., Gugler, K. and Yurtoglu, B. (2011). This is the third step of the present research.

The idea is based on the underlying assumption that the market power effects generated by a merger can be partially separated from its efficiency effects. Therefore, the analysis of relationship between the rents generated around the decision and merger announcement may make sense. For example, if the merger announcement generated positive rents for both rivals and merging companies, which is consistent with the MPH, then the effective merger control should eliminate this rent. It should be reflected in negative reaction when a decision is announced. Furthermore, there should be a systematic negative relationship between these rents around two events. Thus, the core idea of this approach is to investigate the phenomena of rent reversion. This approach allows one to assess the antimonopoly body's decisions. To tackle this question, authors proposed to estimate the “degree of effectiveness” by running the following regression separately for competitors and participating companies:

, (1)

where: X is a vector of exogenous control variables (e.g. industry-dummies);

Р denotes the rents generated around particular event of interest.

The subscript i denotes merging (M) or rival (R) firms, the subscript j stand for the transaction. The subscript d denotes the FAS's decision (C=clearance; R=remedies). The upper index A stands for the merger announcement event, while D - for the authority's decision announcement. This technique is able to provide more robust results since it employs the regression analysis, rather than analysis of significance of the rents.

Regressions results can be used to test a set of hypotheses concerning the sings of slope coefficients and the intercepts. These hypotheses are generalized in Table 1.



Table 1

Expected Coefficients¹

Decision	Predictions
	Rivals (i=R)	Merging companies (i=M)
Clearance (d=C)
Remedies (d=R)

¹Source: Duso, T., Gugler, K. and Yurtoglu, B., 2011

Let us provide several comments on the Table 1. In case of clearance decision, it is quiet straightforward that no systematic relationship should exist. As was mentioned above, the outright clearance does not change the industry circumstances, therefore coefficients are assumed to equal zero. In case of remedies implementation, the slope coefficients for both merging firms and their rivals is supposed to be negative, as it indicates the rent reversion. The intercept for competitors became negative, because it means the shift occurring because of the eradication of the market power rents.

To conduct first three steps of the research, we will use the event study technique. An in-depth review of this methodology will be presented in the next section. In brief, this approach enables one to separate the effect of a merger or decision announcements from the “normal” performance of a company's shares. The main object of event studies is the abnormal returns, which is the difference between actual and normal returns. Hence, if the abnormal return is significant, it means that event does really influence the market's anticipation about company's future performance.

In order to be able to carry out the event study analysis, we need primarily three sorts of data. First of all, dates of initial merger announcements are required. Since there is no specific Russian database containing them, we should turn to the foreign sources, such as the Zephyr database collected by the Bureau van Dijk. Secondly, we need the FAS's decision announcements dates. These can easily be extracted from the official Website of the Federal Antimonopoly Services, which contains a publicly available decisions database. However, despite a legal obligation to place all the decisions texts on the Internet, it is occasionally impossible to find several cases. Finally, the event study technique requires the quotations of companies' shares. There are several specialized stock data sources, but the Finam is one of the most complete and conveniently accessed databank. A more detailed overview of the data collection process will be presented later in the data section.

After obtaining the results on market reaction to various merger events and inferences about the quality of merger regulations, it is highly important to assess the reliability of gained results. It is the final step of our study. One of the most common and dangerous phenomena, which might negatively affect the validity of results, is the problem of endogeneity. To our knowledge, only few studies devoted to event study applications addressed this question directly (Eckbo, E., 1990; Aktas, N., Bodt, E. and Roll, R., 2004). To accomplish a test for endogeneity, we use the discrete choice models analysis. The idea of this test is to examine the behavior of two parties of a merger control process: investors and the FAS. We will firstly study whether investors take into account the probability of the FAS's decision to impose remedies. Next, we will examine whether the FAS considers the initial investors' reaction to a merger proposal. If both of these questions appear can be answered positively, then the endogeneity does really exist and the results of previous steps cannot be treated as reliable.



4. Methodology

As was stated previously, the present study concentrates on the stock market reaction to Russian merger events. This reaction can be analyzed using the event study approach. The event study came originally from the finance (Myers, J. and Bakay, A., 1948; Fama, E.F., Fisher, L., M.C. Jensen and Roll, R. , 1969; Brown, S. and Warner, J., 1985) and is based on the efficient markets hypothesis (the EMH), specifically on its semi-strong form (Fama, E., 1970). According to this form of the EMH, current stock market prices reflect all the publicly available information. This allows using current prices and their changes as reliable indicators of future profitability. In terms of the present paper, the events are the merger and antitrust decision announcements. Therefore, assuming that semi-strong EMH holds, it is possible to assess the merger control by examining the reaction of the efficient market.

A question of applicability of the event study analysis to the Russian stock market data needs to be discussed at a basic level. Frankly speaking, today there is no direct evidence of the semi-strong efficiency of Russian stock market despite several attempts to conduct the event study using data on Russian public companies (Pogozheva, A., 2013; Tsytsulina,D., 2012). However, emerging markets, to which Russia refers according to the International Monetary Fund's list, draw interest of many researchers. For example, Griffin, J., Hirschey, N. and Kelly, P. (2008) concluded that the difference in reaction of emerging and developed markets did really exist. Main reasons for that were enumerated, such as investors inattentiveness, poor informational environment, and possible insider trading leading to the leakages. Nevertheless, those findings did not imply he prohibition to conduct event study for emerging market data. Later, Griffin, J., Kelly, P. and Nardari, F. (2010) found that traditional efficiency tests might give misleading results. Taking into account the transaction costs, which investors of emerging markets face, and the speed of information incorporation, these markets cannot be regarded as considerably less efficient than the developed markets. The study of Hall, S., Urga, G. and Zalewska-Mitura, A. (1998) used the data on Russian stock market indices and found the Russian market was inefficient, however, it would become efficient in about two years. Today, more than 10 years have passed since then. Thus, the present paper is based on the assumption that the event study approach is an appropriate and feasible technique for Russian data.

The main idea of the event study is to assess the impact of an event using the abnormal return. The abnormal return is the difference between the actual ex post return of a stock and its normal return. The normal return is the expected return without conditioning on the event taking place. So, for company i and the event date ф the abnormal return is:

, (2)

where , , are the abnormal, actual and normal returns respectively for the period ф. stands for the information set for the normal return model. For further clarification, Figure 4 presents the timeline for an event study.

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Figure 4. The timeline for an event study

The choice of the normal return model has been discussed in several studies (e.g. MacKinlay, A., 1997) and varies from the constant return model to the multi-factor models. However, none of the researchers used the Fama-French model. The majority estimated the market model (Eckbo, E., 1983; Duso, T., Gugler, K. and Yurtoglu, B., 2011) and used the constant return model to perform the robustness check (Aktas, N., Bodt, E. and Roll, R. 2004). The market model implies the dependence of a stock daily return from the market portfolio daily return :

, (3)

where: is the sensitivity of a company's return to the market return.

The slope should not be estimated using the Ordinary Least Squares (OLS) technique due to the nonsynchronous data. Otherwise, the inconsistent and biased estimated will be obtained. The problem of nonsynchronous trade has been addressed by many researchers (Brady, U. and Feinberg, R., 2000). This problem is associated with the fact that closing prices of stocks cannot be observed every day at the exactly same time. Fortunately, Scholes, M. and Williams, J. (1977) solved this problem and introduced another way to estimate beta. Let us consider this technique closer.

The simple OLS estimate of beta, which is inconsistent with the nonsynchronous data, can be written as:

, (4)

where: stands for covariance;

is the variance.

For the consistent estimate, however, we need to consider two auxiliary coefficients:

, (5)

. (6)

After that, it is possible to estimate the consistent beta and the intercept:

, (7)

, (8)

where: the the estimated first-order autocorrelation coefficient of the market return.

To catch the effect of event, the cumulative abnormal return (CAR) for every company and its average (CAAR) for the whole sample should be estimated:

, (9)

, (10)

where: is the sample size.

Under the null hypothesis that the event has no impact on the stock returns and the zero mean of the market model's disturbances, the abnormal return is supposed to be normally distributed . If this conditions holds, the cumulative abnormal return should also follow the normal distribution (MacKinlay, A., 1997): . Therefore, it is possible to implement the t-test in order to estimate the significance of the cumulative abnormal returns.

The null hypothesis is as follows:

. (11)

The formula for statistic then takes the form:

, (12)

where: is the unbiased estimate of the standard deviation of the cumulative abnormal returns.

We also investigate the problems of self-selectivity bias, which were first addressed by Eckbo, E.B., Maksimovic, V. and Williams, J. (1990) and then developed by Aktas, N., Bodt, E. and Roll, R. (2004). Eckbo et al. (1990) stated that if an events, such as merger or acquisition, results from voluntary decision, then rational managers will proceed only those transactions that are expected to be profitable and value creating. As a result, such a self-selection leads to a truncation of the distribution of the cumulative abnormal returns. Therefore, it may make sense to consider the truncated regression model (Green, W., 2003):

, (13)

where: is the dependent variable;

is the vector of explanatory variables;

is the normal density function;

is its cumulative function;

a is the truncation threshold;

is the standard deviation of the regression errors;

is the set of coefficients.

The model is estimated by the Maximum Likelihood Estimation (MLE). If the significance of the coefficients estimated by the MLE differs from those obtained after the OLS procedure, then the selectivity bias does exist and influences the results.

The problem of endogeneity implies the simultaneous dependence of the cumulative abnormal returns and the probability of the antimonopoly body to intervene, i.e. to give remedies or to prohibit a deal. It means that investors initially, when a merger is announced, take into account the possible probability of intervention, but at the same time the competition authority may take into consideration the initially generated rents and then decide whether to intervene or not. To deal this problem, we will firstly estimate the relationship between the FAS's decision, several independent factors and the estimated cumulative abnormal returns. The common technique is to run a probit- or logit-regression. Please find a detailed overview of these models in the Appendix 1.

The estimated cumulative abnormal returns as the instrument for the cumulative returns will also be included as a possible predictor. This procedure is called the two-stage instrumental variables estimation and described by Aktas, N., Bodt, E. and Roll, R. (2004). To obtain the instrument, it is necessary to estimate the dependence of CAR from the same set of variables as for the decision probability. After running this regression, the predicted CAR can be obtained and included into the probit- and logit- models described above.

The next step is to predict the probability of intervention and run a regression of the actual CAR generated around the merger announcement on this probability of intervention. The idea is similar to the Heckman's lambda (Heckman, J., 1979). If the coefficient of the probability is positive, then the endogeneity problem does exist. Moreover, the last model will be estimated by both OLS and truncated techniques in order to investigate the problem of self-selectivity discussed above.



5. Data

To analyze the reaction of Russian stock market on merger events, a sample based on the Zephyr (Bureau van Dijk) search strategy was constructed. The main advantage of Zephyr database is the availability of merger announcements dates. First of all, all the mergers, acquisitions, and minority stakes that had taken place, been announced or been withdrawn between 2005 and 2014 years were chosen. The next step was to select those transactions, in which at least one of the participated companies was Russian company. After that, at least one of the merging firms needed to be a public stock company in order to do the event study technique applicable. Finally, the number of transactions was limited by only those ones, which were scrutinized by the Federal Antimonopoly Service, because vast number of deals were not subject to control of the FAS. As a result, the sample includes 230 observations. The timing distribution of the transactions based on the year of completion of a deal is presented in the Table 2.

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