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MERGERS AND ACQUISITION

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1

Proceedings

of the 7
th

International Conference

ACCOUNTING AND MANAGEMENT

INFORMATION

SYSTEMS

AMIS 2012

June 13-14, 2012
Bucharest University of Economic Studies

Piaţa Romana, No. 6, Sector 1

Bucharest, Romania

ISSN 2247-6245

ISSN-L 2247-6245

THE BUCHAREST

UNIVERSITY OF ECONOMIC

STUDIES

FACULTY OF ACCOUNTING

AND MANAGEMENT INFFORMATION

SYSTEMS

754

THE ANALYSIS OF COMPANIES’ ACCOUNTING

PERFORMANCE RATIOS FROM MERGERS AND

ACQUISITION

Florentin CALOIAN, Laura BRAD
1
, Radu CIOBANU and Anca STAICU

Bucharest University of Economic Studies, Romania

ABSTRACT

This study measures the impact of mergers and acquisitions (M&As) on the performance of

companies in Romania. To achieve this, we analysed the pre-merger and post-merger

financial rates for companies listed on Bucharest Stock Exchange who made at least one

merger or acquisition in the period 2006-2011. A set of three rates (ROA, ROE and ROS) was

analysed in order to measure the economic performance of companies before and after the

M&A announcement was made. Moreover, a logit model was realized where the influence of

ROA, ROE and ROS was observed. In many cases, results showed that the performance of

companies it could be significantly influenced by the M&A announcement. Moreover, a

conclusion about the value of the company can be subtracted by analysing the results obtain

in our logit model.

KEY WORDS: Acquisitions, Mergers, Financial ratios, Economic performance

INTRODUCTION

Acquisitions and mergers are a mechanism by which companies gain access to new

resources, increase their incomes and reduce their costs. The success of M&A

activities can be pointed out through the economic potential which the M&A

transaction develop, resulting in increased financial performance of the company.

The European market is getting through a continuous development over the past

20 years, integrating more and more economies that were mostly characterized

through a centralized socialist economy before 1989. During that period, most

European companies have limited their activity to their national borders compared to

the U.S. that were developed abroad. Due to this reason, the value of M&A activities

realized in Europe was reduces and the capital transfer was limited to state borders.

(Campa and Hernando, 2004). With the liberalization of markets and with the IPO

process of several companies that were controlled by the state, the number of M&A

activities increased and large companies from developed countries were attracted by

the possibility of realizing new investments. Foreign investors were attracted by the

possibilities of development in the countries of Central and Eastern Europe due to low

price of M&A transactions and of labour force that could lead to significant gains

from these activities.

1
Correspondence address: Laura BRAD, Bucharest University of Economic Studies, Piata Romana,

nr. 6, Bucharest, FABBV Department, Room 1104, email: laura_brad2004@yahoo.com

755

The M&A market in Central and Eastern Europe was characterized in the early 1990s

by privatizations. In Romania, the privatization of companies owned by the State

Ownership Fund, which was achieved in the last decade of last century, is mainly

characterized by takeovers of those companies. According to some researches these

transactions haven’t been characterized by positive performance, due mainly to a

capital market not well developed and due to a lack of legal regulations regarding

capital markets and mergers and acquisitions process. (Pop, D 2006).

Using the financial ratios analysis, the study attempt to investigate the performance

changes for companies that are involved in M&A activities in the past 5 years in

Romania. We focus on the empirical evidence of the performance from acquisitions

and takeovers of all the companies listed on the Bucharest Stock Exchange (BSE) as

few studies were realized upon this market. A takeover may be a friendly or a hostile

process, depending on the acquiring firm approach. It may be affected through

agreements between the acquirer and the majority shareholders, through the purchase

of shares from the open market, or by making an offer for acquisition of the acquirer’s

shares to the entire body of shareholders. Acquisitions can take place either by

acquisition of shares of the target company, either by acquisition of assets and

liabilities of the target company.

The paper is structured as follows: the next section gives a brief overview of the

related studies in this field, Section 3 presents the database and the methodology used,

Section 4,outlines the approaches to the measurement and estimation of performance

change and Section 5 is dedicated to discusses and conclusions.

1. LITERATURE REVIEW

The influence of macroeconomic environment upon the performance obtained by

companies cannot be denied as they quickly react to each modification. As a fact,

during a financial crisis, important changes can be observed, especially in the mergers

& acquisitions area. As they highly influence the performance acquired in different

economic branches, the measurement of their performance is definitely important.

Two ways of quantifying the performance obtained in the mergers & acquisition

sector are mainly studied in the present foreign literature: on one side, the market

share price using event studies (Sudarsanam,S. and Mahate, A.A’s (2006)

Moeller,S.B., Schlingemann, F.P.,Stulz,R.M. (2004) and on the other side, the

accounting measures of performance. Several studies focus either on the market

performance, either on the accounting measurements, but most of them use both of

these techniques. From this point of view, Kabir,R, Roosenboom,P.F.J (2003) realized

a connection between the stock market and the operating performance of several

enterprises as the first was able to anticipate the changes in operating performance of

the issuing companies. Moreover, they discovered no connection between stock

market reaction, financial ratios and the favorable macroeconomic conditions. On the

other side, Tuch, C.& O’Sullivan,N. (2007) discovered that there is no evidence of

higher performance in the short term using event studies, but a negative one on the

long term event study, while the accounting measures offers a mixt conclusion.

The problem of performance in mergers and acquisitions is not new; as many

researchers tried to develop different solution on how better performance

756

measurement is provided. They used not only the classical ratios that represents a

company’s performance, but also some calculated indicators generated by

manipulating the financial statements. As a fact, Healy , P. , Palepu, K. G. , Ruback,

R.S. (1990) studied if merged firms had increased their post-merger operation cash

flow relative to the pre-merger values. They use a cash flow indicator upon 50 largest

acquisitions between 1979-1983, which was not affected by goodwill or depreciation

and discovered that there was a high increase in their asset productivity. Opposite

results were subtracted from their study by Sharma,D.S.&Ho,J(2002) who realised

that the post-merger performance measured either by cash flows, either by accounting

ratios like ROA, ROE, EPS and PM got worsen than the performance achieved before

the merger process. Same results were obtained by others researchers like Fowler K,

Schmidt D (1989) who concluded that the acquisition process decreases the

performance of the company if it is measured by return on assets, while Marimuthu,

M. (2008) revealed that there is no significance difference between the low and high

sales growth companies in terms of performance after the acquisition was made, as

sales growth rate is an insignificant performance measure.

On the other hand, mixt results about the performance that the acquirer and the taken

company were found by Selcuk, E. A & Yilmaz, A. A (2011) who analyzed the

impact of M&A on the performance of 62 acquired Turkish companies that were

traded on Istanbul Stock of Exchange. They discovered that while significance

performance could be observed on long terms event studies, ROA and ROS value

from the intercept model were significantly lower than those of pre-acquisition ones.

Similar opinions were formulated by Agorastos, K, Pazarskis, M, Karagiorkos, T

(2011) as they realized a research upon post mergers financial performance using

companies listed on the Athens Stock Exchange between 1998 and 2002. The

performance was quantified using 5 main groups of financial ratios and the results

shows that conglomerate mergers performance are above the bench market when

liquidity ratios and financial structure ratio are concerned.

As performance can be measured using non-financial and non-economic variables, we

consider that Gantumur, T & Stephan, A (2011) is quite important. They proved

insights that M&A determined an important growth in innovation performance in the

telecommunication industry due to post mergers R&D charges and also to weakness

of internal technological capabilities that acquired companies had before merger.

Besides, with a high level of consistency, comparative studies provide a further

consideration on the performance gained in the mergers and acquisitions domain.

Martinova&Renneboog (2006) realized a European study on 28 countries, including

Romania, and discovered that several variables like the takeover kind, the size of the

companies, the financial structures of enterprises affect the performance in the post-

merger period.

In the same direction goes Gruici,B.C., Constantin, L.G., Iamandi. I.E (2010)

comparative study during the recent financial crisis. Their conclusion is that the

Romanian Mergers and acquisition market is quite undeveloped as the failure

characteristic of this process is still present. On the other side, Romanian companies

report better post merger performances during the financial crisis as they consider

merger a proper way to raise capital and why not to create future development

oportunnies.

757

As there are many contradictions on the main literature about mergers and acquisition

performance, and as there are no significant studies in the Romanian literature, we are

interested in quantifying the impact of this process upon financial and accounting

ratios.

2. DATABASE AND METHODOLOGY

2.1. The performance measured by accounting ratios

The purpose of this article is to identify if there have been movements in the

performance obtained by the companies that were supposed to a takeover offer

process in the 5 years period. In order to realize the analysis and to determine the

performance obtain in the acquisition process, we analysed three return ratios like

return on equity, return on assets and return on sales. The idea can be justified by the

fact that first off all classical measurement of the performance should be done, as

no

proper conclusion about recent period was undertaken. Moreover, the event study

methodology is actually based on the market reaction at the announcement of the offer

and cumulative abnormal returns are calculated. As this perspective is based more on

the efficiency market hypothesis and not on the financial and accounting expectation,

we consider that return ratios are a better measurement for the performance obtained

by the company. Additionally, we can calculate several other ratios in order to point

out if they have an important influence upon the acquisition process. Our research is

based on a sample formed initially from all the take-over bids activities from 2006 to

2011 that took place on the Bucharest Stock of Exchange (BSE), with a number of 27

companies.

For each company we extracted financial information from their financial statements,

as we wanted to show the performance acquired due to the acquisition process. The

following formulas were used in order to quantify the performance obtained by the

companies:

One explication for formula used for return on equity and return on assets is that we

wanted to illustrate the result obtained due to initial values of material assets and

shareholder’s equity and to evaluate the performance gained with primary resources.

On the other hand, dividing results from the current period to resources from the

previous one generates some ratios that can be compared with the inflation rate or the

interest rate. Regarding the third indicator, it measures the profitability obtained due

to current companies activity, as the profit of the company was generated by the sales

realised between the beginning and the ending of a financial period. The performance

of the companies using the three return ratios was determined before and after the

758

takeover process. Our intention was to compare and analyse the company

performance for two years before and two years after the takeover process in order to

see whether the M&A transaction improves performance or not. Due to some

limitations to financial statement information mainly for the companies that are no

longer listed on the BSE, this purpose could not have been properly fulfilled for all

the firms in the database.

2.2. The logit model

In practice, the classical regression model does not offer proper solution to the

researchers’ requirements, as frequently dependent variables have a binary

evolution.

Consequently, other solutions were developed as no relevant results are

provided

using the OLS model. Moreover, the estimated values are not permanently range

between 0 and 1 and no proper estimation can be realised. As a fact, binary models

were developed (logit and probit models), in which the negative effect of the classical

model is eliminated, as the variable is generated using the distribution of the residual

term. As many variables do not have a normal distribution, the logit models, based on

the cumulative distribution of errors, offers more consistently and robust results.

Moreover, the logit model is based on maximize the likelihood which is unbiased and

which minimizes the variance of a large number of variables. In practice, the logit

model it is frequently used in the banking sector in order to establish which

companies can obtain financial support from banks.

The model used has is based on the following model:

where y is the dependent variable, …, are the independent variables, and
is the error term, them in a regression based on the logit model, the probability of

changing the dependent variable is

where p is the probability and it has a value between 0 and 1 (  ),

The importance of the model comes from the fact that the model is constructed on

using the cumulative istribution of the residual form.

Taking this facts into consideration, we realised a logit model for each type of offer.

Basically, we have a selling (S symbol) a buying (B) and a taking over bid

(purchasing offer P) , so the dependent variable the specific kind of offer. Even

though we do not have similar proportion for each value of the dependent variable, as

759

logit model assumption are for obtaining better results, we think that logit models can

offer better results than the OLS estimation.

2.3. The logit model interpretation

Due to its non-linear distribution, the logit model is analysed in a particular manner. If

the coefficients’ sigh and the way of accepting them are similar with those from the

classical regression model, when we talk about economical results they have a totally

different signification. In particularly, the absolute value of the coefficients is entirely

different from that resulted from a linear probability model. Consequently, the logit

coefficients are more dynamically as the changing probability of the estimated value

to be 1, caeteris paribus, will fluctuate as it reaches 1.

In order to mark out the economic impact, an approximation for each coefficient can

be used. Generally, they are multiply by 0.25 or are divided by 4 in order to be similar

with the values from the classical regression method. The problem is that the size of

our sample is quite low, and basically, even an approximation method cannot generate

equivalent coefficients from both regression models.

Regarding the present study, firstly the numbers of selling, buying and taking offers

was quantified as they are going to represent the dummy variables in the model

analysed. After that, different indicators were calculated such as the average before

the date of takeover bid for return on equity, return on sales and return on assets. Not

only the average values were determined, but also the previous value before the data

of anouncement was taken into consideration. Finally, in order to point out the

performance obtained by the companies that were suppose to a takeover offer, several

logit models were realised. The purpose was to determine how the variable included

in the study can influence the type of takeover in Romania.

3. RESULTS

3.1. Results on the accounting performance ratios

As we have mentioned, for each company that was subject of performance analysis,

we calculated three profitability ratios, taking into account their financial statements.

The reaction of the market can be pointed out if the performance of the company is

marked by a severely jump: even an important increase, even a drastically decrease.

This reaction proves that the market reaction can be similar with the semi-strong

efficient market hypothesis.

On the other hand, several companies do not have pre-takeover process and post-

takeover process performance information as this event took place even in 2010, so

financial information were not provided, even in the past where no financial

information was founded. As a consequence, we can only analyse the performance

obtained before or after the takeover offer and anticipate how the market will react or

have reacted to this process.

Firstly, we realised a summary of the performance obtained by the companies.

760

Table 1. The evolution of companies performance after the takeover process

Year Nr. S B T ROA ROE ROS

2005 1 1 mixt results

mixt results

mixt results

2006 6 2 4

drastically

falls

Jump /

constant

evolution

drastically
falls

2007 5 1 4

important

jumps
mixt results

constant

values

2008 2 1 1

no
important

modification

mixt results mixt results

2009 5 2 3 mixt results

drastically

falls,

constant
values
mixt results

2010 5 2 3

no

information

provided
no
information
provided
no
information
provided

2011 2 1 1

no
information
provided
no
information
provided
no
information
provided

As it can be seen there are cases when the market reaction is marked by an important

fall or a severely jump, but in general mixed evolution can be identified. At a closer

look, macroeconomics connections can be observed, as important jumps are typically

for the boom period, while drastically falls can be measured in the recession economic

cycle.

At a closer analyse, the mixed results can be spread into severely falls and important

jumps, constant evolution and uncertain decisions. Looking at return on assets, we

identify that ROLAST has the worst performance as its return on assets falls more

than 40%. Same evolution, but with a smaller impact can be observed upon UPS and

Kandia, while positive jumps can be illustrated on ALU and POLICOLOR.

When we talk about the return on equity, same results can be observed as ROLAST is

still on the last position when its performance is measured, while huge expectations

are obtained by SCD. The last ratio, which measures the impact of profitability on

sales, is in the same direction as the others indicators’ evolution was. Actually, the

results can be justified by the fact that same amount is divided by different accounting

elements, so the modification it should be made by those, but generally, there are also

other factors that influence the profitability obtained by the company. Nonetheless, we

cannot omit the evolution of macroeconomic environment as financial crisis affected

the Romanian market and as companies felt the negative effect of the macroeconomic

evolution.

The results are somehow in the manner that we expected them to be, as no constant

evolution is obtained by the company and as they are sensitive to the market reaction.

The impact of takeover process can be consequently analysed in several ways. For

example, important jumps or severely falls can be a way of stakeholders’

understanding the takeover process. As a fact, if better influence and benefits of the

takeover process can be identified, then the market reacts in a positive way and the

profitability ratios set down a positive evolution. On the other way, if takeover is

concerned as a reorganization process, if stakeholders do not anticipate positive

evolution of the company due to the takeover process, then the performance is marked

761

by a drastic fall. Besides that, we have a sample of enterprises that are characterised

by no significant modifications in their financial measurement performance. The

reason of this unobserved modification can be explained by the fact that no benefits or

problems can be identified by the companies, as there is no real reasons to doubt

about the plans that the company realize for next years.

In conclusion, the performance gained by recent takeovers bid offer cannot be

classified in a single evolution, as mixed results were obtained during the Romanian

market. Nonetheless, the severely falls or important jumps obtained in the profitability

of a company should be connected not only with the previous performance, but also

with the macroeconomic environment evolution which can influence the company’s

behaviour on the market.

3.2. The logit results

The logit model form and its particular interpretation is quite important as economic

conclusion about the value of the companies can be formulated.

After establishing the research methodology, several economic models were realised

using the economical program Eviews. As independent variables included in the

analyse are not uncorelated, as they should be, better results were obtained by using

unifactorial logit regression. As a consequnce, the selling offer was influenced

individually by the average of return on equity, the average of return on assets, while

the buying offer was influenced by the return on assets, average of return on equity,

and the previous value of the return on sales before the date of announcement.

Unfortunately, no relevant correlation could have been detected for the taking over

bid, as the significance value of the coefficients was not economically different from

zero. More than 50 simulations were realized in order to find the better correlation

between the independent variables and the binary one. Several results are summarized

in the next table.

Table 2. The decision type of several logit models

binary variable independent variables Results

S average of ROE, ROS, ROA
coefficients are not significantly

different from zero

S average of ROA probability of error 17,81%

S average of ROE the model is correctly defined

S last ROE, Last ROS the model is correctly defined

P average of ROE
coefficients are not significantly

different from zero

P average of ROE, ROS, ROA
coefficients are not significantly

different from zero

P average of ROE, ROS probability of error 18,72%

P last ROE, ROA, ROS
coefficients are not significantly

different from zero

B average of ROA the model is correctly defined

B average of ROE the model is correctly defined

B last ROA, last ROS probability of error 16,7%

B last ROA, Last ROE, Last ROS
coefficients are not significantly

different from zero

The previous table encounters only a few simulations that were made. Different

conclusion can be formulated by analyzing it. Firstly, better results are provided when

only an independent variable is included in the study research. Secondly, generally,

762

even though the coefficient of the constant resulted is not significantly different from

zero, the models cannot be rejected as they are properly formulated. Thirdly, multiple

factor influence cannot be observed as the independent variables are connected by the

net profit obtained in the current financial year.

Even though the model provided looks like a linear one, none should analyze it as a

classical regression model. Particular interpretation is conferred to the nonlinear

model, where the value of is not relevant for the entire model validation as the
value of it is divided in a few ratios (McFadden R-squared) Actually, for a better

understanding of the logit model, several steps have to be done.

Firstly, the coefficent sign can be analysed as the interpretation of z-test is similar

with t- test, the one from the classical regression model. In order to accept that

coeficients are significantly different from zero, it is recomanded that the value of z-

test to be under 5%. Due to a small number of variables used, the validation criteria

can be modified by increasing the value accepted for the z-tes up to 10-15%. It is

generally accepted that the higher the z-value is, major errors can be done. On the

other side, the relevance of the model is quantified by the practical and statistical

coefficient signification. The model is approved if the probability of the likelihood

ratio is less than 5%.

In order to point out the importance of coefficient value, several logit models were

realised as it is seen in the next table.

Table 3. The results obtained in the logit model using a single independent variable

Dependent variable Independent variable coefficient’s value probability

S average of ROE 7,2664 0,0556

T average of ROE -0,1119 0,965

B average of ROE -8,3782 0,0446

S average of ROA 9,3052 0,1461

T average of ROA 4,5897 0,4116

B average of ROA -26,5948 0,0298

S average of ROS 3,6227 0,4681

T average of ROS 9,4704 0,1022

B average of ROS -24,7924 0,0462

S ROE last value 5,7284 0,0635

T ROE last value -0,4376 0,8459

B ROE last value -5,4801 0,0675

S ROA last value 7,5906 0,1781

T ROA last value 1,4012 0,7744

B ROA last value -10,4304 0,0854

S ROS last value -1,4017 0,6566

T ROS last value 2,7554 0,4105

B ROS last value -1,4669 0,661

In the first example, the raise of the average of return on equity with one per cent

determines a modification of the probability for a selling takeover bid with 7,26%,

while a similar raise decreases the modification probability of a buying offer with

8,37%. As it is shown above, the looking to change probability for a selling takeover

bid is significantly influence by previous return on equity values. When the

modification is due to almost each ratios analysed, without the last year ROS value,

there is a high probability to have a takeover buying offer. In the last case, the

increase with 1% in the average of return on sales influence the looking to change

probability of an take over process with 9.47% if higher risk is assumed, as the

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probability of making mistakes is greater than 10%. If the classical regression model

would have been realised, than the average of return on equity coefficient would have

been 1.816 when the approximation model is used. Consequently, a 1% increase in

the average of ROE would have generated a 1.8% modification of dependent variable.

The logit model can also provide information about the percentage of takings over

process that were necessary to be realized. In order to this, forecasting values obtain

using 50% information criteria (the possibility of being or not a similar process with

that analysed). The conclusions point out that more than 70% for taking offers, buying

offers and selling offers is justified by the economical background of the company.

Moreover, even though no multiple models were realized, the economic interpretation

has to be provided. Using the logit model, we can formulate an opinion about the

value of the company when the selling, buying or the taking over process is taking

place. As a fact, if the company is having a selling offer that we can say that is

overvalue by the market, while a company that is having a buying offer it could be

undervalue by the market. Nonetheless, a company suppose at a takeover process it is

consider to be properly value by the market itself.

Further research can be made using monthly data as better ways of quantifying the

performance can be obtained. More specifically, not only accounting data it should be

used, but also financial and non-financial data as the performance of the company in a

takeover process can be drastically influence by the macroeconomic environment.

DISCUSSION AND CONCLUSION

This paper aims to identify a correlation between some accounting performance’s

measurements and the takeover bid offer, a buying offer or a selling one on a sample

of 27 enterprises from the Romanian Market between 2006 and 2010. As a fact, the

study was divided into two sections: the first one, measures the performance gained

by the company using three accounting ratios: return on equity, return on sales and

return on assets, while the second one points out the economic importance of mergers

and acquisitions using a logit model.

The results obtained offer mixt interpretation and can be correlated with other M&A’s

studies. On one hand, there are companies who obtain a better performance

(quantified by ROA, ROE like SCD, ALU) after the takeover bid offer was

announced. Similar results were obtained by Verde, S. (2007) regarding the M&A’s in

Europe in the energy industry. On the other hand, there were companies than

decreased value and lost financial performance after the announcement was made. As

a fact, we have severally falls in companies like Rolast. These results can be

connected with Rau, P, R and Vermaelen, T (1998) who concluded that the companies

over extrapolate the bidders past performance.

Regarding the methodology used, problems were encounter as no adequate financial

data were provided for all our companies. Actually, because we used annual data, not

a proper evaluation of the performance obtained by companies could have been

established, especially when the process analysed was at the beginning or at the end of

our study period. Another problem comes from the way we choose to calculate the

accounting ratios. For a further study an average between the beginning and the end

764

value of financial elements can be calculated as the net result can be generated not

only by past performance, but also by present financial turnover.

On the other hand, the second study points the economic background of mergers and

acquisition using a logit model. The results points out that the probability of being

change from 0 to 1 for the takeover buying, selling, and taking process is influence by

our independent variables as follow: return on equity generally influence the selling

offer, the taking process is generated by return on sales, while return on assets, on

sales and on equity affects the likelihood of change in a buying takeover process.

Nevertheless, several problems were identified as the sample was quite small, as our

independent variables were correlated, so no multiple models could have been

realised. For a further research, we recommend more financial indicators to be

calculated as they can provide better information about the mergers and acquisition

process. Consequently, the goodwill gained by the company can be analysed, other

financial element like cash flows or profitability ratios can be calculated in order to

obtain better relevance of the macroeconomic environment influence upon the

performance of companies implied in a M&A process.

In conclusion, we proved that the M&A announcement influence generally positive

the performance obtained on Romania Market.

ACKNOWLEDGEMENT

This work was co-finaced from the European Social Fund through Sectoral

Operational Programme Human Resources Development 2007-2013, project number

POSDRU/107/1.5/S/77213 „Ph.D. for a career in interdisciplinary economic research

at the European standards”.

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Appendix

The company used in our study

Number Company Type of offer

1 ALU S

2 CBC S

3 COMI T

4 COTR S

6 ELECTROCERAMICA B

7 FAUR T

8 KANDIA DULCE T

9 MPN T

10 POLICOLOR -1 T

11 POLICOLOR -2 B

12 PPL T

13 PTR T

14 ROLAST B

15 RRC T

16 SCD – 1 B

17 SCD – 2 T

18 SILCOTUB B

19 SNO S

20 SNP S

21 SOCP T

22 SRT S

23 STZ B

24 TEL S

25 UPS B

26 VESY – 1 S

27 VESY – 2 S

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• Proceedings AMIS 2012