St. Petersburg University
Graduate School of Management
Master in Management Program
THE EFECTS OF M&A DEALS ON THE COMPANY
PERFORMANCE: THE CASE OF OIL AND GAS
Master‘s Thesis by the 2nd year student
Concentration — Management
Olga. R. Verkhovskaya
ЗАЯВЛЕНИЕ О САМОСТОЯТЕЛЬНОМ ХАРАКТЕРЕ ВЫПОЛНЕНИЯ
ВЫПУСКНОЙ КВАЛИФИКАЦИОННОЙ РАБОТЫ
Я, Красноруцкая Юлия Вячеславовна, студент второго курса магистратуры
направления «Менеджмент», заявляю, что в моей магистерской диссертации на тему
«Эффекты сделок слияний и поглощений на финансовые результаты компаний: пример
нефтегазовой индустрии», представленной в службу обеспечения программ магистратуры
для последующей передачи в государственную аттестационную комиссию для публичной
защиты, не содержится элементов плагиата.
Все прямые заимствования из печатных и электронных источников, а также из
защищенных ранее выпускных квалификационных работ, кандидатских и докторских
диссертаций имеют соответствующие ссылки.
Мне известно содержание п. 9.7.1 Правил обучения по основным образовательным
программам высшего и среднего профессионального образования в СПбГУ о том, что
«ВКР выполняется индивидуально каждым студентом под руководством назначенного
ему научного руководителя», и п. 51 Устава федерального государственного бюджетного
государственный университет» о том, что «студент подлежит отчислению из СанктПетербургского
квалификационной работы, выполненной другим лицом (лицами)».
____________________________________ (Подпись студента)
STATEMENT ABOUT THE INDEPENDENT CHARACTER OF
THE MASTER THESIS
I, Krasnorutckaia Iuliia, (second) year master student, ______program «Management»,
state that my master thesis on the topic «The effects of M&A deals on the company
performance: the case of oil and gas industry», which is presented to the Master Office to be
submitted to the Official Defense Committee for the public defense, does not contain any
elements of plagiarism.
All direct borrowings from printed and electronic sources, as well as from master theses,
PhD and doctorate theses which were defended earlier, have appropriate references.
I am aware that according to paragraph 9.7.1. of Guidelines for instruction in major
curriculum programs of higher and secondary professional education at St.Petersburg University
«A master thesis must be completed by each of the degree candidates individually under the
supervision of his or her advisor», and according to paragraph 51 of Charter of the Federal State
Institution of Higher Education Saint-Petersburg State University «a student can be expelled
from St.Petersburg University for submitting of the course or graduation qualification work
developed by other person (persons)».
Название магистерской диссертации
Описание цели, задач и основных
Красноруцкая Юлия Вячеславовна
Эффекты сделок слияний и поглощений на
финансовые результаты компаний: пример
Высшая школа менеджмента
Сталкиваясь с регулярными трудностями и
нефтегазовые компании погружаются в
поглощениям как один из способов укрепить
свои позиции, что, однако, не всегда приносит
установление и анализ конкретных эффектов,
характеристики сделок слияний и поглощений
на финансовые результаты компаний в
нефтегазовой индустрии. Сначала были
собранны данные по компаниям и сделкам, и
литература по данному предмету. Затем была
потенциальной взаимосвязи между факторами
сделок и последующими финансовыми
результатами компаний. После этого был
произведен анализ результатов и даны
На основе существующей теоретической
литературы по данному предмету, следующие
характеристики сделок по слиянию и
поглощению были выбраны в качестве
покупаемой компании; 2) способ оплаты; 3)
размер купленной доли; и 4) тип интеграции.
показателями ROA, ROE, Debt-to-Equity и
наличие положительного эффекта размера
компании и оплатой акциями на показатель
ROA и отрицательного эффекта на показатель
Слияния и поглощения, финансовые
результаты, нефтегазовая индустрия
Master Student's Name
Master Thesis Title
Main field of study
Academic Advisor‘s Name
Description of the goal, tasks and main
The effects of M&A deals on the company
performance: the case of oil and gas industry
Graduate School of Management
O. R. Verkhovskaya
Facing constant challenges and competition in the
industry, oil and gas companies dive into M&A
activity as one of the ways to strengthen their
positions, which, however, does not always bring
the aimed result.
The goal of this research paper is to reveal and
analyze particular effects that M&A deals
characteristics can have on the financial
performance of companies in oil and gas industry.
Firstly, the companies and deals data set was
collected and the existing literature on the subject
was analyzed. Secondly, a model for revealing a
potential relationship between deals factors and
companies subsequent performance will be built.
Thirdly, the analysis of the results was made and
practical recommendations were elaborated on the
basis of the research outcomes.
Suggested by the existing theoretical literature on
the subject, the following characteristics of M&A
deals were chosen as independent variables: 1) size
of a target company; 2) method of payment; 3) size
of the acquired stake; and 4) type of integration.
The financial performance was measured by ROA,
ROE, Debt-to-Equity, and Price-Earnings ratios.
The findings of the study suggest a positive effect
of the size of the target company and of payments
made with stock on the ROA ratio, and a slightly
negative effect of the latter on P/E ratio.
Mergers and acquisitions, financial performance,
oil and gas industry
1. THEORETICAL BACKGROUND OF THE STUDY……………………………………………...............8
1.1. Relationship between M&A deals and company performance………………………………….…8
1.2. Mergers and acquisitions in oil and gas industry…………………………………………………......14
Oil and gas industry value chain and trends……….......................................................14
Motivation for M&A of oil and gas companies……………………………………………19
1.3. Conclusion and research gap…………………………………………………………………………………..23
2. THEORETICAL FRAMEWORK AND HYPOTHESES…………………………………....................25
Determinants of M&A success in O&G industry……………………………………......................25
3. RESEARCH METHODOLOGY………………………………………………………………………………...30
Sample and Data collection …………..…………………………………………………………………....30
Method of analysis and model specifications……………………………………………..………...31
Description of variables………………………………………………………………………….…………..32
4. RESULTS AND DISCUSSION………………………………………………………………………………….37
Results of the empirical study…………………………………………………………………................37
Practical and theoretical implications……………………………………………………………….…42
Limitations and future research…………………………………………………………………….……43
Appendix 1. Financial performance indicators………………………………………………………….…..49
Appendix 2. Academic research on M&A-Performance relationship (extract)………….……..50
Appendix 3. Statistical model outputs………………………………………………………………………..…51
With the ongoing competition in the oil and gas industry, the recent drop in oil prices along with
the increasing interest in new unconventional resources is expected to drive another wave in
mergers and acquisitions among petroleum companies.
Mergers and acquisitions deals historically account for a high market turnover annually, and with
the acceleration of globalization, changes in international economic and regulatory
environments, competition, strong economic growth in several regions of the world and
maturation of a number of emerging markets are increasing firms‘ competitive pressures
(KPMG, 2016). With the aim to face these competitive pressures, many companies have realized
they need to go global in trying to maintain a competitive edge.
Statement of the problem and its relevance
Although managers in companies across the world usually claim their M&A decisions are
strategically important for increasing the value of the company, at the same time, according to
different researches, up to 62 per cent of all M&A deals turn out to be either disappointing, or
complete failures (McKinsey&Company, 2015). This suggests an increasing importance of
understanding the reasons behind particular financial results of M&A deals.
The following patterns determine the relevance of the research:
the volumes of M&A deals in oil and gas industry are expected to grow in the nearest
future due to: 1) the economic changes making it tighter to hold profit margins at the
previous levels; 2) development of the unconventional resource market and the need to
get competitiveness in the new field;
a big proportion of M&A deals are considered unsuccessful and the reasons for those
effects are not always known and investigated for;
there is a lack of research aimed to identify particular characteristics of M&A that can
cause positive or negative results for the financial performance.
Goal and objectives
This paper aims to identify what factors of M&A deals can increase or decrease subsequent
financial performance of acquiring companies in oil and gas industry.
To achieve the goal, the following objectives have been set:
make a review of existing literature on the topic: to understand if the relationship of
M&A on the companies‘ performance in general has been identified;
to have an
overview of the value chain of oil and gas industry; to identify any features of M&A
deals within the industry;
make a review of existing theories on possible explanations for post-M&A financial
performance and formulate the hypotheses;
develop the model to be used for the analysis of the data and gather the necessary data;
analyze and discuss the obtained results and their business applicability.
Structure of the study
Following the tasks, the structure of the present paper will include the following parts. The first
chapter will provide a literature review with a focus on M&A-performance relationship, value
chain and trends of the oil and gas industry, and M&A drivers within the industry. In the end, the
conclusion and research gap will be discussed. In the second chapter, theoretical justification and
corresponding hypotheses will be formulated. The third chapter includes the development of the
model and provides the description of the sample and data collection. Further, in the fourth
chapter the results of the empirical study will be presented and discussed. In the end, conclusions
will be made and practical contribution of the study will be explained.
THEORETICAL BACKGROUND OF THE STUDY
The present chapter examines existing literature on the topic. In the first subchapter, the previous
studies determining existence of particular financial impact of mergers and acquisitions are
analyzed. The literature is organized and grouped by criteria of scientific approach, obtained
results, and deal factors under consideration. The second subchapter presents literature review on
specificity of mergers and acquisitions in oil and gas industry, and explains the value chain and
important aspects of oil and gas industry itself. Based upon the review, the knowledge gap is
discussed, theory and corresponding hypotheses are formulated.
Relationship between M&A deals and company performance
As most of mergers and acquisitions are fulfilled with the aim of improvement of subsequent
performance of the companies in one or another way, the existence of implied connection
between M&A and financial results receives an essential importance. Multiple studies exist on
the topic, aiming to investigate if there is any effect M&A have on financial performance and if
those effects correspond to managers‘ expectations or if they fail to be successful.
Authors‘ research interests vary in terms of methods, geographical borders, time periods,
observations, and, what is most interesting, results. Several of the most important research works
that contributed to the development of the topic were done by Straub et al. (2012), Gugler at al.
(2003), Rani et al. (2015), Bruner (2003), Bertrand and Betschinger (2011), Liargovas (2011).
In terms of research approaches, the existing literature can be divided into four major groups:
event studies, accounting studies, case, or clinical, studies, and surveys of executives.
In event-studies, researches primarily look at acquiring firms‘ long-term abnormal returns (e.g.
Liargovas, 2011 and Yuce and Ng, 2005). The logic behind this is to compare the return earned
by a company to it required rate of return, that is, the return that the company could expect to
earn if it used other investment opportunities of similar risk instead of M&A. (Bruner, 2003) The
company return for a specific day is estimated as the change in the share price of the company
and dividends paid divided by the share price as of the previous day. The abnormal return is
calculated as the difference between the received raw return and the return that was required on
the market by Capital Asset Pricing Model (CAPM) or a return in a market index, such as
Bruner (2003) emphasizes that it is important to distinguish between total received return and
return that is enough for the M&A transaction to be considered successful. When the received
return is compared to the required return, one of the three conclusions regarding the overall
financial result can be made: that the value was created, destroyed, or conserved. Value is
created when the returns after the deal are higher than the required returns what means that net
present value for shareholders is positive. In case the return is lower than it could have been from
other investment opportunities, the value is destroyed. If both levels of return are equal and net
present value is zero, this is not considered a failure. If the acquiring company requires a return
of 15% and after M&A it earns it, it is as well not considered an additional value as it could be
earned in other ways.
In accounting based studies, authors examine financial results of the companies before and after
M&A transactions in order to check how the overall trend has changed. See, for example,
Thanos and Papadakis (2012), Ahmed (2014), Rao-Nicholson et al. (2016), where authors
compare the performance taking time periods of three years before the transaction and three
years after it to check for results in the long-run. Paired sample t-test statistics is used to check
for the difference in the ratios. The most widely used financial measures refer to profitability,
operating efficiency, liquidity, and solvency ratios.
The best structured studies within this approach include matched-sample comparisons of the
results (Yaghoubi et al., 2016). That is, based on the industry and the firm size, special control
groups are created, and the performance of merging firms is compared to that of non-merging
firms as a benchmark to see how different it is after M&A.
Some authors also combine the above mentioned methods in their research. For example,
Liargovas (2011) identifies significant positive cumulative average abnormal returns received in
the banking industry after the banks had undertaken M&A deals. Besides, the author examines
operating performance of the banks by analyzing twenty financial ratios. By comparing the
performance to that of the control group, the author comes to a conclusion that operating
performance of the banks on average does not improve.
Another group of research studies focuses on quantitative methods and implies conducting
surveys among executive management of companies whether the performance has improved or
not after mergers or acquisitions. (Bruner, 2003) After the results are obtained, some
generalization can be made across the industry or country. Joash and Njangiru (2015) used 14
companies as a sample for their study. First they conducted survey gathering information about
firms‘ subsequent performance, and then incorporated the information into a multiple regression
model. The findings showed that mergers and acquisitions raised shareholders‘ value and
profitability of the firms.
Moctar and Xiaofang (2014) and Ivaldia and Verboven (2005) use a case study approach to
determine if there is any effect of M&A on the financial performance of companies. The
research is based on one transaction or a small set of those. By investigating deeply the details
and background of the deals, researchers can come up with new insights that can better explain
the performance aspects.
The existing research literature is contradictory in terms of particular effects that M&A deals
bring to companies‘ performance. All studies can be divided according to the results they
demonstrate into several groups: those that find positive relationship between M&A and
financial performance, those that find a negative relationship, studies that find no effect
attributed to M&A at all, and works that provide mixed conclusions depending on different
aspects of the deals.
One of the most significant works that contributes to the research question is Robert F. Bruner‘s
―Does M&A Pay?‖ (2003). The author examines 100 scientific studies on results of mergers and
acquisitions as well as 14 informal surveys from 1971 to 2001. The author finds that the main
reason for disputes over the positive or negative effects of M&A arises from the way in which
positive returns are measured by acquiring firms. If the positive gains are compared to the
require rate of return of companies it can happen that there is no additional value added as the
company only earned its cost of capital. However, if the positive gains are measured in absolute
values and not compared to the return benchmark, the evidence suggests that in most cases M&A
deals create value. Based on his findings, Bruner concludes that mergers and acquisitions do pay.
However, as he noted, successful M&As require much of planning, and significant cost-savings
and value creation can be hard to realize.
Among authors whose findings as well suggest positive impact of M&A on a company‘s
financial performance are Rani et al. (2015), Joash and Njangiru (2015), Grigorieva and Troickiy
(2012), and Kling (2006).
According to Rani et al. (2015) there is a significant improvement in the long-term profitability
of acquiring firms after M&A deals. The study examined the sample of 305 transactions that
happened in the period between 2003 and 2008 in India. On the side of financial performance,
the researchers primarily focused on such dimensions as profitability, efficiency and liquidity.
The analysis showed that in post-M&A period, the ratios improved, especially, in terms of profit
generated per unit sales. Authors come to a conclusion that an increase in EBIT indicator was
primarily due to better operating margins as M&A allowed for an improvement in cost
Joash and Njangiru (2015) investigated the effects of M&A on shareholders‘ value in acquiring
companies. The sample consisted of 14 commercial banks in Kenya that had undergone mergers
or acquisitions over the period from 2000 to 2014. The authors, as it was mentioned before, used
questionnaires and regression to collect and analyze the information. The results showed that
M&A deals could help increase shareholders‘ value in acquiring banks.
Yuce and Ng (2005) also found that M&A resulted in increased returns for companies, however,
they pointed out that the returns were higher for companies if they acquired private firms rather
than public ones if the payment was made with stock. The wide sample represented all mergers
and acquisitions of Canadian firms from 1994 to 2000 that included 1361 acquirers, 242 targets,
and 38 industries, including oil and gas. In the study, the market-based event-study method was
used. In their findings, Yuce and Ng argue not only that the abnormal return was generated as a
result of M&A, but also that it was the case for both acquirers and target companies. However,
one of the main disadvantages of the study is that it examined only a 40 day period to determine
the influence on financial performance. In other words, it did not check for any long-term effect
to determine if the positive short-term increase would be outweighed by a negative long-term
Although using a different approach in a more recent study, based on accounting measures,
Grigorieva and Troickiy (2012) came to a similar conclusion that M&A transactions have a
positive impact on operating efficiency of the BRIC countries and EBITDA/Sales indicators
increased in a two year period after the deals.
The opposite results on the matter of relationship between M&A and financial performance are,
however, also quite numerous. Researchers can accept different limitations for the purpose of
their research, depending on the sample, time period, location, financial measures, and
explanatory variables. Taking this into account, the corresponding difference in the results
Bertrand and Betschinger (2011) examine how particular deal, firm and industry level factors
influence financial performance of acquirers in Russia. The sample consists of more 600
companies acquiring both domestically and abroad for the period between 2000 and 2008. Using
a multiple regression model, Bertrand and Betschinger test dependence of companies ROA ratio
on such factors as target firm size, ownership form, market share, number of previous
acquisitions, etc. The scholars argue that as a result of M&A, performance of acquirers was
reduced compared to that of non-acquiring companies. Furthermore, the authors make a
conclusion that the reason behind the destroying effect of M&A was in lack of experience and
resources of Russian companies, especially when it came to cross-border transactions.
It is also should be considered that mergers and acquisitions can have a different impact when
acquirers and target companies are examined separately. For example, M&A can enhance the
performance of the smaller company that has been acquired, while it can dilute the value of the
deal for the acquirer itself. In their study, Siegel and Simons (2010) conduct an analysis of 9400
acquirers and 16000 firms and plants that have been acquired in Sweden. The study was aimed to
determine the effects of M&A on the performance of acquiring companies and on that of the
companies under control. While the researches do not register any positive impact on the first
group of companies, they suggest that the plants that were acquired still could increase their
Adjusting the performance results by industry criteria can also show more negative effects than
the overall research would present (Liargovas, 2011). In the study by the international consulting
company, firms demonstrating healthy performance prior to the deal, generated significantly
lower cumulative shareholder return after the deal. In the period of two years after M&A, 60
percent of the acquirers registered a drop in return on average of 10 percent (L.E.K. Consulting,
The majority of studies, however, cannot give unequivocal answers about the dependence of
companies‘ financial performance on preceding M&A deals. As analysis of the literature shows,
even in those cases when the relationship is identified, it can have different impact, positive or
negative, depending on particular performance indicators (e.g. Bruner, 2003, Kalakkar, 2013,
Gugler et al., 2003, Moctar and Xiaofang, 2014).
Some M&A deals can result, for instance, in increases in certain accounting indicators, but
reductions in others (Gugler et al., 2003). In a study of mergers and acquisitions taking place
around the world for a 15 years period, the effects that M&A have are analyzed by comparing
financial indicators of merging companies with those of the control group of non-merging
companies. According to the results, the acquiring companies experienced on average higher
profits, but the sales were reduced after the deal. Further, when domestic mergers were compared
with cross-border ones and manufacturing companies were compared with service companies, no
significant difference was found regarding the prior results. To explain the difference in profit
change, Gugler et al. examine the relative proportion of the deals that decrease profitability and
those that decrease it in the sample. M&A that reduced profits and efficiency accounted for the
larger share than the deals resulting in market power increase. The authors suggest that a larger
amount of value destroying deals can be explained by the big relative size of the companies
participating in them, while the small share of positive effects – by small sized companies.
The effects of M&A can be different depending on whether they are being studied in a shortterm or long-term period. Moctar and Xiaofang (2014) argue that in terms of efficiency and
investment valuation variables, M&A deals have a significant negative effect short-term, but a
positive effect in the long-run. However, in terms of liquidity the performance improved both
short-term and long-term. The study was carried out with a sample representing merging and
acquiring companies across Economic community of West African States (ECOWAS). For
financial performance measuring, the ROA, ROA, EPS and liquidity ratio were adopted as
indicators. The authors compared the two groups of merging and non-merging banks before and
after the mergers. The three financial dimensions were then analyzed to reveal the differences in
performance that could be explained by the M&A both right after the deals and three years later.
A broad study of factors influencing the success of mergers and acquisitions was done by
Kalakkar (2012) with a sample of 109 deals from 2009 to 2011. The author examined the most
suitable financial performance indicators according to the previous literate and chose return on
assets, return on equity, profit per employee, income growth rate as dependent variables. On the
side of explanatory factors the following ratios were collected: dividend payout ratio, total debt
to capital ratio, long term debt, GDP growth, market Share, credit to deposit ratio, investment to
deposit ratio, business per employee. The results of the regression analysis confirmed positive
effect only on income growth rate. However, no other relationships were supported by the
Many studies that focus on developing markets also demonstrate mixed results. Ahmed (2014)
points out the difference between effects on profitability, liquidity and efficiency after M&A
deals. Thus, on the basis of the analysis of M&A deals in Pakistan from 2000 till 2009, it is
concluded that liquidity and profitability significantly increase in post-merger period, whilst
efficiency levels deteriorated. The overall performance was considered as having improved. In
research on Indian M&As and its effects on companies performance, there were also mixed
results observed by Leepsa and Mishra (2012); Kumar (2009); and Sinha et al. (2010).
Most scholars further suggest that in evaluating the success of financial performance after
mergers and acquisitions particular deal characteristics should be taken into account (Bruner,
2003). Bertrand and Betschinger (2011) argue that despite the overall conclusion that M&A deal
do pay, in practice, to achieve real gains, it implies many aspects that have to be fulfilled. Thus,
the primary importance is in identifying what particular deal factors can make them pay.
Based on the current analysis of the existing literature, it becomes evident that in most cases
scholars manage to identify the relationship between M&A and companies‘ performance in later
years. This relationship can be positive, negative, or controversial, however, it is more frequently
observed than no relationship at all. Besides, the possibility to create value itself is attributed to
the deals background and factors as well as characteristics of the involved companies (Dutta and
Mergers and Acquisitions and Oil and Gas Industry
While the main trends in M&A dynamics are determined by the overall economic activity level,
the specificity of M&A in oil and gas industry is dependent on the factors attributable to the
energy sector in general and oil and gas market in particular. In the present subchapter, we will,
first, provide an overview of oil and gas industry, discuss its features, value chain and current
trends, and then, examine the current state of M&A activity, its dynamics and motives with
regard to the current situation in oil and gas industry.
Oil and gas industry value chain and trends
Oil and gas industry, in its sense, includes all processes that are connected with exploration,
extraction, transportation, refining, and selling oil, gas, and their subproducts. Oil and gas
together provide the world population with approximately 60 percent of its daily energy demand.
Oil accounts for the larger part of consumption among all petroleum products and represents on
average 32 percent for Europe and Asia, 40 percent for North America and 53 percent for the
Middle East. Nowadays, as petroleum products constitute the base raw resources for many
producing companies worldwide, over 200 countries have invited oil producing companies to
explore their territory to determine if there are oil reserves there (IHRDC, 2015).
To understand the main challenges faced by oil and gas companies and the motives behind their
M&A activity, we will analyze their value chain. As it was popularized by Porter (1985), the
value chain is a set of activities following one another that are required to bring the product from
initial stages of creating the concept and organizing the process, through different steps of
production to the final product or service that will be delivered to the customer.
All operations in oil and gas industry are divided into three major sectors: upstream, midstream
and downstream. However, some authors include midstream into the downstream sector.
Upstream sector includes such activities as exploration of the underwater and underground fields
for identification of potential oil and gas reserves, development of hydrocarbon reserves and
subsequent extraction (production) of oil and gas (the World Bank, 2010). Upstream sector is
also usually referred to as the exploration and production (E&P) sector. This sector is considered
the core field in all oil and gas value chain and accounts for the biggest share in all M&A deals
in terms of both number of deals and their volumes.
The proved oil and gas resources are the main assets by which companies in this industry
typically compete. According to the Petroleum Resources Management System approved by
Society of Petroleum Engineers (SPE) Board, reserves are ―quantities of petroleum anticipated to
be commercially recoverable by application of development projects to known accumulations
from a given date forward under defined conditions. Reserves must further satisfy four criteria:
they must be discovered, recoverable, commercial, and remaining based on the development
projects applied‖ (SPE, 2007).
On the side of costs, the upstream stage requires significant upfront investments from the
companies. This is so because due to the strict regulations, in order for oil or gas to be
recognized as reserves, the detailed information about those reserves needs to be provided, and
this often means additional expenses to the company.
Midstream sector activities primarily consist from transportation and storage of petroleum
products. Transportation from production sites to refinery plants and afterwards to the
distributors is typically done by pipelines, rails, barges, oil tankers or trucks. Those ways of
transportation represent another concern in strategic planning and cost structure of producing
companies. Most authors separate midstream sector from upstream and downstream, however,
midstream often can include some operations from upstream and downstream sectors, for
example, it can include plant processing of the natural gas as well as its transportation (PWC,
2011). For this reason, midstream sector is often included into the downstream and its activities
are classified as downstream.
Downstream sector in the oil and gas industry involves refining of crude oil and processing and
purifying of natural gas. It also includes marketing and distribution activities for obtained
petrochemical products, such as petrol, gas, fuels, kerosene, asphalt, liquefied natural gas (LNG)
Maintaining the downstream activities in the value chain requires high capital investments from
the companies (PWC, 2011). The main facilities necessary for processing and distribution of oil
and gas products include refineries, LNG facilities, pipeline and transportation networks as well
as retail distribution stations (UNEP FI, 2013).
Companies that operate in oil and gas industry are classified in literature by different criteria.
Correspondingly to the industry value chain, there are upstream, midstream and downstream
companies. Among the largest companies from the first and third groups in terms of production
are, for instance, Saudi Aramco, NIOC, ExxonMobil, PetroChina, BP, Royal Dutch Shell,
Pemex and Chevron. The midstream is represented by such companies as Aux Sable, Bridger
Group, DCP Midstream, Enbridge Energy Partners, Enterprise Products Partners, Genesis
Energy and other companies.
Besides the classification mentioned above, there are companies whose primary operations are
oil field services. Such companies do not do exploration, transportation or production of oil and
gas but provide professional services to these companies. Oil field services can include special
facilities construction, providing and maintenance of drilling equipment and other assistance. Oil
and gas companies that operate in all of the mentioned sectors are called integrated majors. The
most frequently cited example is Exxon Mobil as it makes the whole set of work in extraction,
transportation and distribution. As a rule, such companies focus on upstream and downstream
activities, outsourcing the middle stages from more specialized companies.
The whole value chain in oil and gas industry is connected with various risks, both internal and
First of all, unlike producers in many other industries, oil and gas companies do not directly
control the prices for their products. Rather, it is global demand and supply and economic
conditions that influence the oil prices. Financial performance of the companies in this industry
to a big extent depends on the spot prices for oil and thus reflects its market fluctuations.
Therefore, the financial results to a certain extent also depend on the overall market conditions.
The primary factors that influence oil prices are: global supply and demand; macroeconomic
situation, financial markets; US dollar exchange rate, and geopolitics (Lukoil, 2013).
In terms of market demand and supply, the oil and gas industry has undergone several changes
over the last period. On the demand side, the sharp decrease in the growth of energy demand was
an unexpected change for the oil companies. While the total demand for gas and other sources of
energy is expected to grow fast enough, the growth in demand for oil, especially if a form of
automobile fuel, is starting to decrease. The global oil supply, however, is increasing and
continued to growth during 2015, partially due to the production activity of OPEC countries (up
to 1 million barrels per day) and the US (approximately 0,8 million barrels per day) (Deloitte,
2016). According to the estimations of the US Energy Information Administration (EIA) (2015),
the global oil supply increased almost twice as much as its consumption.
The most significant change occurred with the sharp drop in oil prices at the end of 2015. The
price fell below historical points – below US $40 per barrel which was more than 60 percent
from the price as of summer 2014 (Bloomberg, 2016). In 2012 the US Energy Information
Administration published its estimations regarding the oil prices forecast that included several
scenarios: for the high oil price, low price and the reference price that the organization was
expecting to see on the market (EIA, 2015). The Figure 1 demonstrates that the actual drop in oil
price that occurred in 2014-2016 was even lower than the projections for the low-price scenario
made by the organization.
Even before the collapse with prices, oil companies experienced pressure in achieving returns
and growth. This sharp decline creates additional challenges for the companies as well as
changes the structure of the industry (Deloitte, 2015). According to Bloomberg (2016), due to
the lower oil prices, in 2015 US oil and gas companies lost more than $300 billion in their
market value. Today oil and gas producers have to adjust to the market imbalance taking into
account the new circumstances.
Figure 1. Projected and observed Brent oil prices
Projected and Observed Oil Prices
High Oil Price
Low Oil Price
Actual Oil Price
Source: author‘s estimations based on EIA‘s forecast and data retrieved from Bloomberg. Energy
Apart from the situation with the oil price, another global shift in the industry began with the
development of unconventional resources extraction. The most important examples are
represented by shale gas and shale oil. From the beginning of 2000s, oil and gas companies,
especially those in the US, began to pay more attention to the nonconventional resources. As a
result, by 2012 production of shale gas led to such a big decrease in gas prices, that it fell below
the level of production costs. With the decline in prices, companies that were previously heavily
investing into the exploration and extraction facilities for the shale resources had to reduce their
volumes of production. Among the countries with the highest reserves of technically recoverable
shale gas are: China, Argentina, Algeria, United States, Indonesia, Canada, Mexico, South
Africa, Australia, Russia, and Brazil (EIA, 2013).
Among the other issues that oil and gas companies face are such question as taxation and
environmental concerns. Taxation is traditionally one of the most critical considerations
mentioned in the literature (e.g. the World Bank, 2010, Mitchell, 2012). Taxation regime of
petroleum companies in many countries is one of the heaviest in comparison with that in other
industries. In upstream oil and gas sector the tax levels depending on a country‘s policy vary
from 40 up to 90 percent (Johnston, 2007). These high levels affect operational incentives,
contractual agreements, assets allocation, strategic decisions as well as financial performance.
Tax rates are, in turn, controlled by states with regard to current economic conditions. Therefore,
the performance of oil and gas companies is affected both by internal and external decisions.
Regarding to the environmental concerns, petroleum companies, especially in the midstream
sector, are also subject to restrictions and sanctions when their activity results in air pollution, oil
spills or other environmental damage (the World Bank, 2010).
International consulting and research companies (e.g. AtKearney, 2015) outline the following
trends in the oil and gas industry for the future years:
The global energy demand is expected to continue growing as the consumer class will
reach up to 50 percent of population. However, the growth in demand for gas and
unconventional energy resources is expected to be higher than declining growth in oil
Countries leading in oil production will agree to limit the overall oil production to allow
the prices to be at the necessary levels. For example, countries from the Organization of
Petroleum Exporting Countries (OPEC) and non-OPEC oil suppliers have conducted
meetings to negotiate the appropriate volumes of oil production (Carlson, 2016).
Unconventional resources driven by development in technologies will continue to grow
in share, however, the production will be limited to prevent further drops in gas and oil
To overcome the refining crisis in Europe resulting from the decline in the industry,
companies will have to shut down a part of their refining facilities producing
approximately 1.5 million barrels per day.
Stricter regulations on environmental protection are to come into force. Limitations for
using sulphur in international bunkering will push the midstream sector towards
alternative ways of transportation, which will result in additional costs, or alternative
sources of energy like liquefied natural gas or LNG.
In the context of macroeconomic and industry specific changes, oil and gas companies will have
to consider ways to optimize their processes to achieve competitive positions. England (2016)
argues that one way to do it is through cutting capital expenditures and postponing large scale
capital projects, cutting operating expenditures and number of employees or negotiating with
suppliers for better prices.
Furthermore, the decrease in oil prices may cause many oil and gas companies to focus on gas as
it can become a more important source of revenue. If the situation does not change for the oil
sector, companies are expected to expand their portfolios and be more active in gas market as
they will want to maintain their positions and become the gas industry leaders in future (Parry,
2015). For M&A activity, it will mean that more deals can be made in the gas sector than it used
to be previously.
Thus, looking for potential cost reductions and production efficiency, oil and gas companies are
also expected to look for business integration options and to go global to maintain the
competitive edge. M&A activity of oil and gas companies, therefore, will be also driven forward.
Motivation for M&A of oil and gas companies
The sharp decline in oil prices has reduced profit margins of oil and gas companies and made
capital expenditures and ability for refinancing and raising new debt more tough questions. The
price changes have reduced the asset value of and negatively affected overall valuation of many
companies (Deloitte, 2015).
Scheck and Raice (2014) argue that in the new market situation, companies will need to find
solutions to improve their returns on capital. The timeframe of recovery in oil market are not
determined, therefore, the main challenge for both conventional and shale oil and gas companies
will be to adjust to the new situation and to cut costs and improve operational efficiency. One of
the ways to achieve this may be in mergers and acquisitions.
According to a range of scholars, economists and international companies, the pressure that oil
and gas companies now face can cause a new wave of mergers and acquisitions aimed at cost
optimization and improvement of competitive positions (e.g. KPMG, 2016, Corrigan and Doshi,
2015, Clark et al., 2016). M&A deals have a wavy pattern depending on economic conditions
that influence companies‘ stability. The general trend is that with increasing pressure on
companies‘ profitability, the number of M&A deals also tends to grow.
The discussed findings are supported by the information in Figure 2, where it can be seen that
the overall number of deals among oil production and service companies started to increase with
the decline in oil prices.
Figure 2. M&A volumes and oil prices
Source: Deloitte (2015)
However, the first reaction to the decrease in the oil prices was negative. Because of the unstable
situation companies are reluctant to undertake additional risks. According to IHS, the analytical
company providing statistical information in petroleum industry, there is a difference in
dynamics between high and low value deals. Thus, the overall trend in the number of small and
mid-size deals the during 2015 was negative and the total transaction volumes for global
upstream M&A deals in 2015 declined 22 percent to $143 billion from $184 billion in 2014
(IHS, 2016). However the dynamics is different for high value M&As. Indeed, a few deals with a
high deal value have been announced since the prices decreased, for example M&A between
Shell-BG, Halliburton-Baker Hughes, Schlumberger-Cameron, or ETP-Williams (Deloitte,
The difference in the reaction can be explained by the two things. First, the growth in deals
volumes is caused by several big-scale transactions where major companies want to achieve an
even stronger position by acquiring other big players paying premium for them. This is
especially common for the US market, where the new race for unconventional shale oil and gas
can determine the financial future of petroleum companies, and thus, require big investments
form their side. For example, in the second quarter of 2015, one deal between Shell and BG
accounted for approximately 80 percent of the total value in M&A deals in the US.
Second, the relative decline in M&A‘s count is explained by weakened positions of many small
and medium companies. Scheck and Raice (2014) suggest that low oil prices have put small and
medium companies under the pressure and either make them reduce their property to refill their
cash reserves, or to sell out completely.
Figure 3. Oil and gas M&A deals by value and count
Source: Deloitte (2016)
Indeed, according to AtKearney‘s research (2015), companies that were initially stronger, are
now willing to use such an opportunity to optimize their own efficiency and costs through
mergers and acquisitions. The historical overview of the M&A waves in relation to oil prices
made by Scheck and Raice (2014) shows that, indeed, companies are more inclined to buy their
competitors when their assets are under the market pressure. For example: in 2001 when the
price fell down to $45,8/B, Chevron acquires Texaco; in 2005 with oil price at the level of
$36,7/B, ConocoPhillips buys Burlington Resources; Exxon Mobil acquires XTO in 2009 when
the price fell again down to $35,5/B; in 2012 with the oil price at $55,4/B Rosneft buys a stake in
TNK-BP from BP; further, after the latest drop in 2014 down to $38,7/B Halliburton wants to
acquire Baker Hughes (Scheck and Raice, 2014).
The patterns discussed above suggest that with the recent drop in the oil price, a new wave of
M&As can be expected. Even though the market uncertainty can slow down the M&A activity in
the beginning, in a long-run it can be used as an opportunity to grow. Looking at the three
sectors separately can show that in the midstream sector, deals are growing both in terms of
numbers and volumes. Thus, only shale producers increase the global midstream sector M&A
activity 16 percent compared to the previous period.
The reasons for mergers and questions have been examined by many authors and firms (e.g.
Dismas, 2013; Picardo, 2014; Oberg and Tarba, 2014). They can be connected with entering new
markets, diversifying a customer base, achieving efficiency and synergy and so on. However,
particular motives that drive M&A deals in each separate industry are different and depend on
specific situation common to that market.
Capstone (2013) examines the main drivers for mergers and acquisitions in oil and gas industry.
According to the research made by the company the main motives are as follows:
Obtaining natural resources. The financial success in oil and gas industry depends on the
amount of natural resources a company possesses and the corresponding amount of
resources that it can receive its revenue from after selling them. Therefore, companies
constantly need to replenish them. One way to add proven reserves to their own balance
sheets is by making deals with other companies. Another advantage is that big producing
companies can avoid the risks of exploration of new fields by acquiring already explored
but undeveloped fields.
Development of existing fields. While big oil companies, such as integrated majors, can
afford integration forward and backwards, small and medium-sized companies usually
focus on one or two value chain areas and cannot achieve the same profit margins. For
example, exploration-oriented companies often cannot turn it into a successful revenuegenerating asset. Therefore, such companies are interested in selling some assets or being
merged with larger companies.
Geographic diversification. Companies‘ revenues depend on both the quality of oil and
gas and the costs that are associated with their production. These two characteristics vary
across countries and depend on local factors. For instance, the total price, apart from the
rest, depends on proximity of refineries, quality of the transportation pipelines and local
train infrastructure, as well as local supply and demand factors. The study conducted by
Kimmeridge Energy firm (2013) examines such factors shows that oil in gas industry in
the US is influenced by then depending on different regions in the country. Capstone
(2013) argues that companies can minimize the risks by spreading their portfolios across
different geographical locations.
Acquiring know-how. Oil and gas companies have different core competences across the
industry, for instance, some of them are more professional in deep-water exploration and
drilling, some in horizontal drilling and others in deep-shale development. Given the
importance of technological processes for the companies and the overall high costs of inhouse research, many producers prefer to acquire those companies who possess the
Adjusting to taxes and regulations. The tax rates imposed on oil and gas companies are
traditionally high, usually starting from 40 percent, therefore companies‘ perception of
future changes in taxes and other regulations can also drive M&A transactions. On the
contrary, if the prospects of future tax rates are negative, investors can close their
announced deals (Capstone, 2013).
Summing up, mergers and acquisitions among oil and gas companies are driven not only by
common to all industries factors, but much more by market situation within the industry itself.
The recent drop in oil prices has slowed down the M&A activity globally. On the other hand, it
has made companies look for cost optimization and scale increasing opportunities. The
development of shale oil and gas extraction also reinforces the competition among petroleum
companies. Understanding of the industry specific reasons for M&A discussed above can
contribute to the further discussion of factors that lead to the success of M&A transactions.
Conclusion and research gap
The review of the literature was aimed to provide an understanding of the state-of-the-art
knowledge scope on the subject. The analysis was divided into several steps. First, a broad
studying of papers on the existence of a relationship between M&A and financial performance
was done. Second, business literature was analyzed to provide an overview of oil and gas
industry in order to understand its specific aspects that can be used further for conducting the
empirical research. Third, M&A activity was studied within the frame of oil and gas industry.
The questions of relationship between M&A deals and subsequent company performance have
long been within scholars‘ attention. The existing literature employs different methods of
analysis, the most widely accepted from which are event studies, accounting studies, case
studies, and qualitative methods such as surveys of executives.
There are four types of papers depending on the conclusions that authors made: studies that
found a positive relationship between M&A and financial performance; studies that found that
financial performance deteriorated; studies that provided mixed results depending on a variable
tested; and papers where no relationship at all was identified.
Research articles providing evidence for the positive and for the mixed results represent the
biggest group by quantity. Authors could identify, for instance, that M&A deals can accelerate
sales or profitability, however, decrease other performance parameters.
Another feature of the literature analyzed is that authors suggest further research to determine
what particular factor affect the results, and imply that specific deal characteristics should be
studied (e.g., Bertrand and Betschinger, 2011). However, not many papers that would study this
question at an academic level could be found. The few works on this subject were presenting
confusing results because the primary objective there was to determine if any relationship exists,
and particular factors were not of a primary interest. Besides, those works were typically based
on an example of one country limiting the implications of the results.
Summing up, based on the literature review, we can conclude that the question of the effects of
particular deal factor on financial performance still represents a knowledge gap, which the
present research paper is aimed to cover.
Further in the second chapter, we proceed with literature review and existing theories in order to
formulate our research hypotheses to be tested.
THEORETICAL FRAMEWORK AND HYPOTHESES
The reasons of particular financial results of mergers and acquisitions in oil and gas industry
have been discussed by DePamphilis (2013), Christensen et al. (2011), Schreiber (2013), Bruner
(2003), Bertrand and Betschinger (2011) and others. In many studies the authors conclude that
besides the motives and economic situation that strengthen financial performance after M&A, it
is specific deal- and company-level factors that can affect the result. Therefore, in the given part
of literature review, different conditions mostly with regard to companies‘ background and terms
of deals will be analyzed.
Factors influencing post-M&A performance
Probably the biggest contribution to the topic development was made by Thomas Straub (2007).
In his work ―Reasons for frequent failure in Mergers and Acquisitions: A comprehensive
analysis‖, the author made a wide research looking at the problem not from an angle of some
particular determinant but from different perspectives. Thus, it was argued that for a deal to be
successful, the following key success factors should be taken into account: strategic logic,
organizational integration, and financial perspective. Strategic logic is reflected by six
determinants: market similarities, market complementarities, operational similarities, operational
complementarities, market power, and purchasing power. Organizational integration is reflected
by: acquisition experience, relative size, cultural compatibility. Financial / price perspective is
reflected by: acquisition premium, bidding process, and due diligence. All 12 variables are
presumed to affect performance either positively or negatively. Besides that, the author
determines three measuring criteria for post-M&A performance: synergy realization, relative
performance (compared to competition), and absolute performance.
Yaghoubi and Yaghoubi (2016) suggest dividing possible factors into five different groups,
namely: acquirer characteristics, target characteristics, bid characteristics, industry characteristics
and macro-environment characteristics. Besides, different authors suggest that primarily bid
characteristics are able to strengthen or weaken the value from mergers and acquisitions (e.g.
Ismail et al., 2011).
Summarizing the existing research, below are presented characteristics that are most often cited
as being important for consideration in M&A process.
Target company size
According to the returns to scale theory, the more companies increase the scale of their
production, the more likely they achieve cost efficiency due to the higher volumes of output.
Scholars believe that acquiring bigger targets, oil and gas companies can increase their assets and
outputs, and thus, increase their market power. The rule of increasing returns to scale states that
if the total output grows more than the corresponding change in inputs, then an increased return
to scale is achieved (Seth, 1990).
When the market powers of two companies are combined in one, there is likelihood that it will
create synergy between them (Viverita, 2008). According to different authors (e.g. Straub et al.,
2012, Tuch and O‘Sullivan, 2007) the difference between relative sizes of acquiring and target
companies is one of the main conditions of synergies and successful financial performance after
M&A transactions. For example, Homberg et al. (2009) examined a number of mergers and
acquisitions and made a conclusion that in order to realize the planned synergies, it is necessary
that the acquirer is bigger than the target company, but the latter should be closer to the acquirer
in terms of absolute and relative size.
Besides, one of the assumptions of the q-theory states that as the target size increases, the
potential synergy gains also increase. Thus theory looks at M&A deals from the financial
perspective. The effect is so because the higher value the target company represents the easier
and faster the acquirer can achieve financial advantages compared to other competitors in the
market (Lucas, 1978). Filipovic (2012) and Tuch and O‘Sullivan (2007) suggest that bigger
targets are associated with superior subsequent performance and that the smaller the ratio
between the companies sizes is, the more successful their following performance can be.
Therefore, the target company size is assumed to have an impact on the following financial
performance. Besides, as the size of the target company is primarily associated with effects on
outputs and variable costs of the company, we exclude the solvency measures from this analysis.
Based on the discussion of the given theories, we derive the first hypotheses of the research:
Hypothesis 1a: The bigger the size of a target company, the higher the acquirer‘s ROA ratio.
Hypothesis 1b: The bigger the size of a target company, the higher the acquirer‘s ROE ratio.
Hypothesis 1c: The bigger the size of a target company, the higher the acquirer‘s P/E ratio.
Hypothesis 1d: The bigger the size of a target company, the higher the acquirer‘s D/E ratio.
Method of payment
The two main methods of payment in M&A deals are payment with cash or with stock.
According to Shleier‘s and Vishny‘s (2003) theory of stock market driven acquisitions, the
reason behind many stock driven acquisitions is an irrational overvaluation of the acquiring
company‘s stock. That is, when company managers realize that the market share price is above
its fair value, they are more inclined to use that excessive money on expanding the business
through mergers and acquisitions. The theory implies that to serve the interests of the
stockholders, managers use the overvalued stock to buy companies whose assets are less
overvalued compared to their own assets. Shleier‘s and Vishny‘s argue that in the long-run, the
market makes corrections of the acquirers‘ stock which leads to negative long-run returns to the
acquirers. However, Lehn and Zhao (2006) conclude that stock deals can benefit acquiring firms
because the overvalued stock enables acquisition of such hard assets that probably would not be
bought with cash, and this, in turn, can prevent even more negative long-run returns.
To assess the validity of these assumptions we formulate the next hypotheses:
Hypothesis 2a: Deals where stock is used as a method of payment are positively associated with
the acquirer‘s ROA ratio.
Hypothesis 2b: Deals where stock is used as a method of payment are positively associated with
the acquirer‘s ROE ratio.
Hypothesis 2c: Deals where stock is used as a method of payment are positively associated with
the acquirer‘s P/E ratio.
Hypothesis 2d: Deals where stock is used as a method of payment are negatively associated with
the acquirer‘s D/E ratio.
Acquired stake size
The control by a parent company implies a better applicability of the new managerial rules and
processes. Those processes can directly affect the performance of the merged company and that
is why the parent company might be interested in establishing a higher degree of control in the
company that it bought. Such control is achieved when the management of the acquirer has the
majority of voting rights while making strategic decisions. Therefore, buying a bigger stake can
be considered a way of improving the influence of the parent company and, therefore, the
Hypothesis 3a: The bigger the acquired stake, the higher the acquirer‘s ROA ratio.
Hypothesis 3b: The bigger the acquired stake, the higher the acquirer‘s ROE ratio.
Hypothesis 3c: The bigger the acquired stake, the higher the acquirer‘s P/E ratio.
Hypothesis 3d: The bigger the acquired stake, the higher the acquirer‘s D/E ratio.
Type of Integration
Authors distinguish two major types of M&A deals on the basis of product and market. Thus, a
merger is called horizontal when the two firms are operating and competing on the same type of
product market and with the same geography. A vertical merger is a combining of companies
that typically operate as a supplier and a customer to one another. Further, a backward vertical
merger is viewed as an acquisition by a customer of his supplier, whereas in a forward vertical
merger the supplier buys his customer, that is a way to new outlets (Dismas, 2013).
Vertical integration is considered a prominent feature of mergers and acquisitions in oil and gas
industry (Luciani and Salustri, 1998; Bindemann, 1999). There are two major results of such
integration: financial and operational. Financial vertical integration occurs when all stages of
production in the value chain are controlled by one holding company that manages their cash
flows. Operational vertical integration implies that there is a physical flow of commodities
between different stages, for example, when crude oil and gas or ready products move In
between of those stages. Key motivation for both financial and operational vertical integration
are typically in securing the resources supply, to increase entry barriers for competitors, to
maintain tax efficiency, to eliminate fees charged by intermediates or to exploit price
discrimination advantages (The World Bank, 2010).
With the high capital intensity of oil and gas industry, vertical integration can be especially
useful in maintaining cost efficiency and profit margins (Gugler, 2003). Ismail et al. argues that
only those M&As should be undertaken by companies with high capital load that are made
within the same industry, and that unrelated transactions can destroy value. Taking into account
that in oil and gas industry, there are three separate sectors with their own production cycles, it is
reasonable to assume that within those sectors vertical mergers and acquisitions can have a more
positive effect on companies‘ financial performance.
Hypothesis 4a: Vertical integration is, more than horizontal integration, positively associated
with acquirer‘s ROA ratio.
Hypothesis 4b: Vertical integration is, more than horizontal integration, positively associated
with acquirer‘s ROE ratio.
Hypothesis 4c: Vertical integration is, more than horizontal integration, positively associated
with acquirer‘s P/E ratio.
Hypothesis 4d: Vertical integration is, more than horizontal integration, positively associated
with acquirer‘s D/E ratio.
The overall model for testing the developed hypotheses is depicted in Figure 4 and reflects the
potential relationship between independent, dependent and control variables.
Figure 4. Theoretical model for hypotheses testing
In the next chapter we proceed with the research methodology and choice of the variables for our
The present chapter is aimed to explain the analytical technique used in the empirical study. The
analysis of the effects of M&A deals factors on a company‘s financial performance will be based
on the following steps: first, the data sample will be presented and analyzed and data collection
and description methodology will be explained, second, the model that will be used for the
analysis will be presented, and finally, the set of variables chosen for the model will be
Sample and Data Collection
To test for the relationship between deals characteristics and subsequent performance of the
companies, the data for M&A deals for the last 15 years has been collected. The initial dataset
includes 1,132 deals made in oil and gas industry for the period from 01, January 2000 until 31,
December 2015 over Europe and North America. After the list was adjusted for the missing data
in key variables, the final sample consists of 110 M&A deals and companies. The sample
includes international companies represented globally and, together for acquirers and targets,
represents 21 different countries.
The required data on the deals characteristics was collected with the use of Zephyr database and
Thomson Reuters Datastream. Information about companies‘ financial performance was
gathered in Thomson Reuters Advanced Analytics database and, for some cases, companies‘
financial reports. The search strategy included filtering the data in several steps within the
following limitations: the type of the deal was set to exclusively mergers and acquisitions; the
status of the deal should be completed-confirmed; time period of the deals was chosen on and
after 01/01/2000 and up to and including 31/12/2015; the industry in which companies operate
should be Oil and gas extraction (with a primary code 13 according to US SIC industry
classification); the status of an acquiring firm should be a publicly traded company; deal value
was set not less than 10 mil USD; and European Union and North America were chosen as a
geographical region. Regarding, the last three filters, we limited the type of the company to only
listed companies due to unavailability of many types of financial and other data for private
companies. The minimum size of the deal was set in order to ensure that the investments that are
made by companies represent purchases that are significant enough to make any financial
difference. Finally, we had to limit the geographical scope of our research because the
differences in economic development in different parts of the world could result in different
outcomes for the companies situated in those countries. Namely, as oil and gas industry is
usually affected by external factors, to which companies may have different reactions depending
on the country, to avoid biased interpretations of the results countries with close economic
positions were chosen.
Method of analysis and model specifications
The choice of the statistical model for the given research is based on the analysis of prior studies
and refers to the methods applied by the authors in papers on similar problematics. To determine
whether particular characteristics could affect financial performance of the companies, in
majority of the analyzed works, the multiple regression models were applied (e.g., Barrera-Rey,
1995; Levin, 2981; Isaksen et al., 2007; Lahiri, Narayanan, 2013 and others). While conducting
the studies, it was assumed that there is a linear relationship between explanatory and dependent
variables. Thus, in our work, we also assume a linear relationship between financial performance
and the selected parameters of M&A deals.
As the model that we will apply is the multiple regression model, the general regression equation
will look as follows:
Y = β0 + β1X1 + β2X2 + ⋯ + βnXn + εt ;
Y – dependent variable;
X1, X2…Xn – independent variables;
β0 β1…βn – unknown parameter of the model;
n=1, 2…N – number of an independent variable;
εt – random error.
The given equation is further adjusted according to particular parameters chosen for each of the
For the purposes of the research, testing of the independent variables will be conducted both by
including all of the variables into a multiple regression model (except for dummy variables that
divide the sample into two groups each) and, in case where the combination of particular
variables would be incompatible and leading to insignificance of the overall model (leaving
significant only one or several variables), the effects of the independent variables on the financial
indicators will be tested in separate regression models. Such a choice is also explained by the
fact that certain variables will represent primary interest for our research in terms of their impact
on particular indicators compared to other independent factors that are less supported by the
theory and, thus, should not affect the analysis of the other hypotheses.
Description of Variables
Identifying appropriate financial measures for dependent variables is essential for the correct
testing of the proposed hypotheses. After having analyzed additional literature on the financial
performance measurement, we conclude that there are several dimensions of financial
performance that are typically considered by scholars. Financial performance measures are split
into the following categories:
liquidity and solvency;
market investor ratios.
In Appendix 2, the list of financial indicators most frequently used by scholars is presented.
Based on the purpose of use of each indicator and on the aspects of oil and gas industry, several
indicators that will be presented further in this chapter were chosen to be used in the research.
There is an important consideration regarding the methods of using these measures that should
be taken into account.
We cannot choose to work with absolute accounting-based measures such as EBITDA or net
income since these measures can be influenced by the accounting methods or the financing of the
studied M&A deals. The problem with such measures is that after M&A deal was completed, the
target company is included into the acquirer‘s business. In case of full acquisitions and mergers,
companies begin to prepare consolidated financial reports where the results of the acquired
company are already included. Indeed, when a random list of companies was checked by the
author, and figures from pre- and post-deal reports were compared, it turned out that the growth
or decrease in the acquirer‘s numbers in many cases was similar to the difference between their
separate figures before the M&A deal. Therefore, we suggest that using absolute accounting
numbers for the acquiring company after the deal and checking if those numbers were caused by
the fact of M&A, will not introduce reliability to the present study. For example, if we test our
hypothesis that the size of the target company can influence acquirer‘s post-deal profitability
indicators, we would get the most likely result that it did affect it only because the total size has
increased. For this reasons, we will use such relative measures that would be able to include both
increasing and decreasing value sides of acquirers and targets.
Another justification of variables selection method needs the following to be considered as well.
In order to determine whether there was a particular influence of deals on the resulting financial
performance, it is necessary to view those financial performance indicators under a dynamic
perspective. That is, we need not only to find the post-deal performance indicators, but to
measure how M&A deals affected the changes that occurred in those indicators. To provide an
example, if we take some final profitability indicator of post-deal performance such as ROA, and
then run a regression to determine the role of one of the independent variables in it, we will only
find the relationship between the size, or the volume of profits, and the variable. However, it will
not help us determine whether the actual ROA was growing or falling over that period. That is,
in case if the M&A deal actually resulted in a decrease of profitability or efficiency, but in the
post-deal records the value of the indicator is still big enough, it can lead to a wrong conclusion
about the effectiveness of the deal itself. As it is impossible to know whether the financial
performance improved or deteriorated without knowing the pre-deal values, the percentage
change in the corresponding figures over time should be determined. Therefore, we will base our
analysis on the actual changes between pre- and post-deal company performance.
Summing up, the two criteria for the dependent variables have been introduced: first, they should
not be based solely on accounting measures of acquirers where the financial results of targets
have been incorporated; and second, the difference between pre-deal and post-deal performance
in all of the selected indicators should be used in order to understand both the effects of deals
characteristics and the actual result of the deals themselves.
Return on Assets (ROA)
Return on Assets is one of the important profitability ratios and measures in terms of relationship
between assets and net profits. ROA shows how profitable a company is relative to its total
assets and how efficient management is in using its total assets to generate earnings. As a ratio,
ROA is useful both for managers and investors as it shows how well the company can convert
the investments made into its assets into profits ("Financial Performance Indicators", 2016).
ROA comprises earnings that are available to owners and interest to creditors, because assets are
financed by both owners and creditors. Therefore, this ROA can be computed with the formula
ROA = (Net income / Total assets) × 100
Return on Equity (ROE)
Return on Equity is a measure that shows how effectively a company's management uses
investors' funds. Increasing ROE means that the company management is growing its value at an
acceptable rate. ROE is calculated in the following way:
Return on Equity = Net Income/Shareholder's Equity
Although both ROA and ROE measure a return, or an ability to generate earnings from the
investments, they do not exactly have the same meaning. The key factor that separates ROE and
ROA is financial leverage, or debt. According to the balance sheet fundamental equation: assets
= liabilities + shareholders' equity. This equation indicates that if a company carries no debt, its
shareholders' equity and its total assets will be the same. It follows then that their ROE and ROA
would also be the same. However, if that company takes on financial leverage, ROE would rise
above ROA. So the rule is as follows: when debt increases, equity contracts, and since equity is
the ROE's denominator, ROE, in turn, shoes an increase. At the same time, when a company
takes on debt, the total assets - the denominator of ROA - increase. Therefore, debt increases
ROE in relation to ROA ("Financial Performance Indicators", 2016).
Price-Earnings Ratio (P/E)
The Price-Earnings ratio is one of the most widely used market ratios for determining whether
shares are ―correctly‖ valued in relation to one another. As the name implies, to calculate the
P/E, it is needed to take the current stock price of a company and divide by its earnings per share
P/E Ratio = Market Value per Share / Earnings per Share
A company with a low P/E ratio indicates that the market perceives it as higher risk or lower
growth or both as compared to a company with a higher ratio. A stock's P/E shows how much
investors are willing to pay per dollar of their earnings. Another interpretation of the P/E ratio is
a reflection of the market's optimism concerning a firm's growth prospects (Kaplan, 2012).
Debt-to-Equity Ratio (D/E)
Debt-to-Equity ratio is used to measure a company's financial leverage and is calculated by
dividing a company‘s total liabilities by its stockholders' equity. The D/E ratio indicates how
much debt a company is using to finance its assets relative to the amount of value represented in
shareholders‘ equity. A high debt/equity ratio generally means that a company has been
aggressive in financing its growth with debt. Aggressive leveraging practices are often associated
with high levels of risk which can decrease the attractiveness of the company for potential
investors. The formula for calculating D/E ratios is represented in the following way:
Debt-to-Equity Ratio = Total Liabilities / Shareholders' Equity
Below the selected measures for explanatory variables will be presented. The variables were
chose according to the purpose of the research, that is, with the focus on deal-related
characteristics, and within the limitations of data available for the research.
Size of the target company
The size of the target company will be measured not in absolute, but rather in relative terms. It is
necessary to reflect the relationship between the size of acquirer‘s investments and the resulting
performance. As a measure for the size of the companies their pre-deal capitalization figures will
be used. The two values will be used to estimate the corresponding coefficient in each particular
case. Capitalization is determined as the market stock price times the number of shares
Capitalization = Market price for a stock × Number of outstanding shares
Method of payment
The two primary methods of payment in M&A deals are payments with cash and with stock.
Therefore, the sample of companies will be split into two groups: those where the deal was
financed with stock and those where the acquirer paid with cash.
The special case is represented by the deals where the deal value was split and paid in different
parts, with stock and cash. Therefore, we should not use a dummy variable to describe the
method of payment. Instead, the percentage rates will be used. Thus, the amount of money that
was paid with stock will be represented by the ratio from 0 to 1.
Acquired stake size
For the variable representing the size of the bought stake, we will use the percentage values
retrieved from the Zephyr database.
Type of Integration
Vertical integration occurs when companies buy such assets that are related to the production of
the other value chain steps than the one that an acquirer operates in. Horizontal integration
implies buying assets that are similar by type to those of an acquirer or its core competitors.
In the sample that we retrieved, the information about industry and business of acquirers and
targets is available. Therefore, if the industry subtype of a buying company is the same as that of
the target company, then the deal will be considered a horizontal transaction. Consequently, if
the deal subtypes are different, the integration will be considered vertical.
A dummy variable will take the value of 1 if the integration is vertical and a value of 0 if the
integration is horizontal.
The independent variables introduced before represent characteristic of M&A primarily on the
deal, company or industry level. To control for these specific characteristics, introducing
additional variables that will control for the external factors, such as changes in the industry or
economy, is necessary.
Composite Leading Indicators
To control for the most influential outside effects on the side of global demand and supply, we
introduce Composite Leading Indicators (CLI) as a control variable. Composite Leading
Indicators is a system developed by OECD in order to register and evaluate the ongoing situation
in the global economy. CLI are used with regard to business cycles, that is, when the CLI indices
decline from the long-term trend, it means that the economic declines can be expected. CLI in
most cases follow the economic indicators, and frequently predict the subsequent increases or
declines (OECD, 2016). The data for the European and US markets was retrieved from the
RESULTS AND DISCUSSION
In the present chapter, the results of the data analysis are presented and interpreted. First, the
focus will be on the variables explaining the impact of a target size company, of the amount of
shares acquired, of the method of payment, and of the type of integration grouped for all
dependent variables. Afterwards, the discussion of the effects showing statistical significance
will follow. Based on the prior discussion, the corresponding conclusions will be derived.
Finally, limitations and practical implication of the study results will be discussed.
According to the developed set of hypotheses and the adapted model, 16 linear regressions were
run. The significance of the models and variables was tested at the 95% confidence level. As all
the variables were set as coefficients rather than absolute numbers, the resulting effects should be
interpreted correspondingly, that is, the slope is also represented in coefficients in all cases.
Table 1 below summarizes the results obtained when the effects of the size of a target company
were tested against the difference in companies‘ performance before and after the M&A deal.
Table 1. Relationship between target company size and financial indicators
The target size relative to the size of the acquirer as an independent variable is significant as its
p-value falls within the threshold of .05. The variable has a positive coefficient (.27) which
means that with an increase of the size of the target each 10 percent, the Return on Assets is
expected to increase 2,7 percent as well. The results for the ROE, P/E, and D/E financial ratios
failed to be statistically significant.
Therefore, we can accept the Hypothesis 1a, and reject the Hypotheses 1b-d.
Table 2 presents the results for the second independent variable, the method of payment relative
to the financial performance indicators.
Table 2. Relationship between the method of payment and financial indicators
The stock as a source of payment proved significant at the 95% confidence level for two
dependent variables, namely ROA and Price-earnings ratios. Therefore the stock method
argument holds for the two dependent variables. The variable has a positive slope in case of
impact on ROA (.37) and a negative slope in case of Price-Earnings dependence (.19). For the
ROE and Debt-to-Equity variables, the results have a p-value higher than .05 which makes them
Based on these results, we can accept the next two Hypotheses, 2a and 2c, and reject the
Hypotheses 2b and 2d.
In the Table 3, the results for the type of integration as an independent variable are summarized.
Table 3. Relationship between the type of integration and financial indicators
The third, dummy, variable showed to be insignificant at the threshold of 95% level. Although
the coefficients of the variable are higher than 10 percent in each case, the overall effect was too
contradicting to determine any significant relationship. Therefore, the Hypotheses 3a-d do not
hold and should be rejected.
Table 4 presents the results for the fourth explanatory variable, namely the size of acquired
stock. Like the previous case, this variable does not prove to be statistically significant at
explaining or predicting the changes in financial performance following M&A deals.
Table 4. Relationship between acquired stake size and financial indicators
In the following subchapter, we continue with these results, discussing the effects that proved
significant as a result of data analysis.
The obtained results provide a vast field for discussion as they not only approved several of the
formulated hypotheses, but also opened up some issues previously not included into the study.
The primary focus in the discussion of the results below will be placed on the statistically
significant relationships, however, those hypotheses that were not significant will also be
Regarding the predictive relationship between the size of the companies that acquirers buy or
invest into, and the following companies‘ performance, the positive result was identified for the
changes in ROA ratio. This finding is in line with the previous theories and scholars‘ views (e.g.,
Seth, 1990). As argued by Leland (2007), to offer a sufficient level of potential, the acquisition
should be of a substantial ―critical mass‖ relative to the size of the acquirer‘s business. Indeed, as
our findings imply, small enough companies could not contribute to companies‘ returns as it was
done by bigger targets. Moreover, from a managerial point of view, M&A deals with smaller
companies may receive not sufficient attention from management of the company and, therefore,
the potential benefit of the deal would remain unrealized (Ravenscraft and Scherer, 2011).
There can be several possible explanations to the reason why the relative size of the target can
cause, even though to a limited extent, the increase in the acquiring company‘s Return on Assets
If we look at the composition of the financial ratios, it becomes apparent that in order for any
increase to be observed, either the profitability of the company should grow, or the amount of
assets should decrease relative to the earnings. According to the returns of scale and synergy
theories, the bigger size of two companies can help achieve higher returns than if the two
companies were operating separately (Tuch and O‘Sullivan, 2007). According to Healy et al.
(1992) companies that were merged have significant improvements in their efficiency and
productivity after the M&A deal. Therefore, one of the reasons of the increase can be in the
achieved efficiency and economies of scale.
Another explanation for the positive slope is in the difference between ROA ratios of acquiring
and target companies. In a situation, when a company buys another company whose Return on
Assets is significantly higher than that of the acquirer, then the resulting common return will be
increasing making a figure between pre-deal targets‘ and acquirer‘s returns. To make a ROA of a
target company positive, which can attract investors, it takes its return to be high. As the return is
composed from a company‘s revenues and expenditures, most frequently, it means that the target
company maintained an effective cost management system. And the latter, is often what an
acquiring oil and gas company is looking for.
Regarding the effects of the company size on the ROE ratio, contrary to the theoretical
expectations (Bruner, 2004; Ismail et al., 2011), the outcome effect showed to be insignificant.
The result can be explained by the different structure of ROA and ROE indicators both acquirers
and targets. Whereas ROA reflects the return on both liabilities and shareholders‘ equity, ROE
shows returns relative only to the equity. So the effect on ROA and ROE can be different in case
when the Equity side was affected compared to the Total Assets. If the return and liabilities are
unchanged and the equity increased, the Return on Equity obviously increases. So when two
companies merge, in accounting terms, the initially bigger equity of the target can increase the
overall amount of equity of the combined firm, and thus prevent the ROE ratio from growing.
Indeed, as it was noted by HIS (2016) in oil and gas industry targets with relatively high equity
ratios are more attractive as high leverage can be especially risky to undertake.
The size of the target company as an explanatory variable also did not hold within the 95%
confidence level when tested with Price-to-Earnings and Debt-to Equity ratios. As P/E ratio is a
market ratio, it represents the reaction of the investors to the news about the M&A deal.
According to the widely-known market efficiency theory elaborated by Eugene Fama (1970), the
assets prices in the market reflect all the available information about those assets. It also suggests
that prices can self-adjust reacting to the new information. So one of the explanations of the
negative result can be that in case of M&A deals the prices in P/E ratio have already reacted to
the future potential earnings and, thus, did not increase significantly after the deal. This is
especially the case when rumors about the deal appear long before the official announcement.
The theoretical assumption regarding the D/E ratio was that paying for the share in a bigger
company can require many companies to increase their leverage taking new loans. Indeed,
sometimes acquirers undertake transactions with targets that are even bigger than themselves
(Ahern, 2010). However, the long term performance does not show any significant deterioration
in the D/E ratio.
Method of payment
Choosing a source of payment represents an interesting case when a company can affect its
balance sheet and stock market performance by actions that are not connected with their primary
business. The results of the regression models show a positive relationship between paying with
a company‘s stock and its future ROA ratio (.37) and a negative one between stock payments
and company‘s Price-Earnings ratio (-.19).
The positive result for the ROA ratio suggests that the prior assumptions about its impact on
profitability were correct. In general, this result falls into the rules of accounting. As it is known,
the balance sheet of companies contains assets of the company on its left side, and liabilities and
shareholder funds on its right side (Kaplan, 2012). The core accounting equation is as follows:
total assets = liabilities + equity. So when oil and gas producers want to buy another company
they have a choice either to pay with its cash, that is, the assets side, or with its stock, that is its
equity and liabilities side. Therefore, when acquirers pay for the ownership in target companies,
giving away their stock, the right side of their balance sheet decreases on the amount money
equal to the price paid for the stock of the target company.
However, this practice turns out to have a drawback reflected in the market reaction. According
to the theory of stock market driven acquisitions (Shleier‘s and Vishny, 2003), M&A deals are
often financed with stock to some extent because acquiring managers believe that the shares of
their company are overvalued. Further, if acquirers‘ stock is overvalued before the M&A deal,
then at some point the market corrects its price. When it happens, the value of the company‘s
assets, in particular its stock, decrease proportionally. Consequently, the decrease in the assets
part of the ROA ratio brings it to a bigger value.
Contrary to the theoretical expectations, the effects of the method of financing on ROE and D/E
ratios did not prove significant at the 95% confidence level. According to the observations in the
existing literature, when companies pay in cash rather than in stock, they have to take additional
loans because many of them do not have sufficient cash reserves especially for big deals and
because using those reserves would decrease their current ratios (Rappaport and Sirower, 1998).
Therefore, payments with stock would have an inverse effect to that of payments in cash.
However, the result did not support this hypothesis
Size of acquired stake and Type of integration
The degree of corporate control reflected in the size of the stake that is acquired was assumed to
be positively correlated with and affect the subsequent financial performance (e.g. Rani et al.,
2015). In general companies look to acquire sufficiently big stakes to gain a certain degree of
operating control and thus improve the performance (Bain, 2015).
However, the explanatory variable in the corresponding models did not show significant effect
on the ration. Such a result can be connected to the specificity of oil and gas industry, namely,
that managerial issues can be less reflected in the financial performance than they are in other
industries. Oil and gas industry refers to ‗heavy production‘ and resource dependent business.
This implies that more than on the extent of organizational influence the financial performance
depends on the external factors, which was reflected by the insignificant coefficients in the
models. To support this idea, the chosen control variable representing global economic changes
was significant and positively related to the changes in most of the models.
Regarding the type of integration, the theoretical assumption as well did not prove realistic.
According to Isaksen (2011), this may be a result of the fact that in oil and gas industry there is
the subdivision into the three sectors (upstream, midstream and downstream) that are sometimes
behaving like separate industries within one, compared to other industries previously discussed
Practical and theoretical implications
The present study provides results that are applicable to the current M&A issues in the oil and
gas industry that need a managerial solution. The study also provides the existing theory with
new question that should be considered, for instance, in research on management strategy of
integrating companies. The analysis made in the present paper can be useful for the following
categories of users:
First of all, executive and operational management of oil and gas companies who are
considering mergers or acquisitions of other oil and gas firms. Knowing the effects of
particular options that they choose with the contracting party on the future financial ratios
can first, help avoid undesired risks and smoothen some negative effects, and second,
achieve a better effect in their financial performance.
Second, outside investors for whom it would be useful to realize more about the changes
in the accounting ratios of oil and gas companies that occur after mergers and
The following recommendations can be given to oil and gas company management who consider
participation in M&A deals:
All else being equal, consider acquiring relatively large targets compared to your own
company size and the one that has a higher efficiency ratios.
Return to scale can be bigger depending on the size of the business as well as on the
ability of the target firm to manage its costs.
All else being equal, choose stock financed method of payment if you have reasons to
believe that your company‘s share price is being overvalued.
Paying with stock when the share price is undervalued can result in a situation when an
acquirer actually has to give away more than it could. The market efficiency theory may
be not always working perfectly, however, the market can adjust its prices according to
the new incoming information, and in this case, the acquirer‘s P/E ratio can experience
the corresponding decline in future.
Limitations and future research
The present study was followed by certain limitations, especially on the stages of data gathering.
The first limitation of the study results from the fact that a big part of the M&A deals involved
private companies as targets. As it is knows, financial assessment of the performance of private
companies is especially tricky because legally they are not obliged to provide their financial
information for a public access. As a result, the data for the chosen sample of deals over the
period from 2000 to 2015 was not available for most of the target companies. In many cases, no
accounting or market value data for those private companies could be found. Therefore, taking
into account the number of required variables, the initial sample of 1,132 deals has shrinked to
Another limitation follows from the previous one and is connected to data gathering issues.
Namely, the range of independent variable that could be considered for the study was limited to
the amount of information that could be gathered. This resulted, in part, in relatively low R
square which could be higher in case if more characteristics were included into the model.
Based, on the limitations of the present study, there is a room for the future scientific research to
be done with regard to different industries, wider samples or different countries. One of the
suggestions is to look more closely on the range of variables and to consider such strategically
oriented decisions as, for example, replacement of the executive management of the target
company after the deal, or exchange rate fluctuations resulting in opportunities or threats for
Present research paper was aimed to determine the relationship between mergers and
acquisitions deals on financial performance of acquiring companies. As a result of the literature
analysis, it was found that among the studies on this topic the results are contradicting and, while
some of them identify a certain positive or negative relationship, the majority of them provide
mixed results depending on the variables that are tested. Regarding particular factors that can
affect the financial results, the following ones are supported by the corresponding theory. First,
the size of the target company was assumed to influence financial performance positively due to
returns-to-scale. Second, the method of payment, and more specifically, stock, was assumed to
increase financial ratios compare to cash payments. Third, vertical integration was assumed to
result in higher efficiency and increase financial indicators. And fourth, the size of acquire stake
was assumed to result more effective governance due to a higher control and thus improve the
performance. Based on the chosen variables, and formulated hypotheses, 16 linear regression
models were constructed and implemented.
The results of the empirical study allowed to confirm three hypotheses. Namely, the target
company size has a positive impact on ROA ratio; stock as a source of payment also showed to
have a positive effect on ROA whereas a negative impact on P/E ratio. After the results were
obtained and explained both relative to the initial theory and practical implementation.
Managerial applicability was explained and several of the recommendations were to choose
stock as a method of financing if the company‘s stock is overvalued, and to target relatively big
companies as it has a potential of creating additional returns to scale. Finally, the research
limitations and the scope for future research were also discussed.
Ahern, Kenneth R. "Q-theory and acquisition returns." In AFA 2008 New Orleans Meetings
Ahmed, Muhammad, and Zahid Ahmed. "Mergers and Acquisitions: Effect on Financial
Performance of Manufacturing Companies of Pakistan." Middle-East Journal of Scientific
Research 21, no. 4 (2014): 689-699.
Alexandridis, George, Christos F. Mavrovitis, and Nickolaos G. Travlos. "How have M&As
changed? Evidence from the sixth merger wave." The European Journal of Finance 18, no. 8
Bertrand, Olivier, and Marie-Ann Betschinger. "Performance of domestic and cross-border
acquisitions: Empirical evidence from Russian acquirers."Journal of Comparative
Economics 40, no. 3 (2012): 413-437.
Bruner, Robert F. "Does M&A pay? A survey of evidence for the decision-maker." Journal of
Applied Finance 12, no. 1 (2002): 48-68.
Deloitte. Oil & Gas Mergers and Acquisitions Report – 2015 Update: Adjusting to the new
EIA. U.S. Energy Information Administration | Annual Energy Outlook. 2015
EY. 2015. Global Oil And Gas Transactions Review 2015.
Fama, Eugene F., and Michael C. Jensen. "Separation of ownership and control." The Journal of
Law & Economics 26, no. 2 (1983): 301-325.
Ferrer, R. C. ―The Impact of Merger and Acquisition, Financial Ratios on Stock Price among the
Industrial Firms in the Philippines. De La Salle University, Manila, Philippines‖. (2012).
"Financial Performance Indicators (Fpis)". 2016. Kfknowledgebank.Kaplan.Co.Uk.
Gelles, Gregory M., and Douglas W. Mitchell. "Returns to scale and economies of scale: Further
observations." The Journal of Economic Education 27, no. 3 (1996): 259-261.
Hambrick, Donald C. "Upper echelons theory: An update." Academy of management review 32,
no. 2 (2007): 334-343.
Healy, Paul M., Krishna G. Palepu, and Richard S. Ruback. "Does corporate performance
improve after mergers?." Journal of financial economics 31, no. 2 (1992): 135-175.
Homberg, Fabian, Katja Rost, and Margit Osterloh. "Do synergies exist in related acquisitions?
A meta-analysis of acquisition studies." Review of Managerial Science 3, no. 2 (2009): 75-116.
Iriyama, Akie, Jason W. Park, Franky Supriyadi, and Haibin Yang. "Integrating Relative
Standing and Market Discipline: A Complexity Theory Perspective of Post-Merger and
Acquisition Executive Departure." Advances in Mergers and Acquisitions (Advances in Mergers
and Acquisitions, Volume 11) Emerald Group Publishing Limited 11 (2012): 181-197.
Isaksen, J. R., Dreyer, B., & Grønhaug, K. (2011). Vertical integration and performance: The
impact of measurements and industry. Økonomisk Fiskeriforskning, 21(1), 41-59.
Ismail, Tariq H., Abdulati A. Abdou, and Radwa M. Annis. "Review of literature linking
corporate performance to mergers and acquisitions." The Review of Financial and Accounting
Studies 1 (2011): 89-104.
Johnston, David. "How to evaluate the fiscal terms of oil contracts."Escaping the resource
curse 68 (2007).
Kalakkar, Sudeep. "Key Factors in Determining the Financial Performance of the Indian
Banking Sector." Available at SSRN 2121351 (2012).
KPMG. U.S. Executives On M&A: Full Speed Ahead In 2016. 2016.
Krishnakumar, Dipali, and Madhvi Sethi. "METHODOLOGIES USED TO DETERMINE
MERGERS AND ACQUISITIONS'PERFORMANCE."Academy of Accounting and Financial
Studies Journal 16, no. 3 (2012): 75.
Leland, Hayne E. "Financial synergies and the optimal scope of the firm: Implications for
mergers, spinoffs, and structured finance." The Journal of Finance 62, no. 2 (2007): 765-807.
Leepsa, N. M., and Chandra Sekhar Mishra. "An Examination of Success of Mergers and
Acquisitions in Manufacturing Sector in India Using Index Score." (2014).
Levin, Richard C. "Vertical integration and profitability in the oil industry."Journal of Economic
Behavior & Organization 2, no. 3 (1981): 215-235.
Liargovas, Panagiotis, and Spyridon Repousis. "The impact of mergers and acquisitions on the
performance of the Greek banking sector: An event study approach." International Journal of
Economics and Finance 3, no. 2 (2011): 89.
Malkiel, Burton G., and Eugene F. Fama. "Efficient capital markets: A review of theory and
empirical work." The journal of Finance 25, no. 2 (1970): 383-417.
MBOROTO, STEPHEN NJUGUNA, and IN FINANCE. "THE EFFECT OF MERGERS AND
ACQUISITIONS ON THE FINANCIAL PERFORMANCE OF PETROLEUM FIRMS IN
KENYA." Signature 63 (2012): 72503.
McKinsey&Company,. 2015. Capturing Value From M&A In Oil And Gas: Implications For
Menz, Markus, and Christine Scheef. "Chief strategy officers: Contingency analysis of their
presence in top management teams." Strategic Management Journal 35, no. 3 (2014): 461-471.
Moctar, B. N., and Chen Xiaofang. "The Impact of Mergers and Acquisition on the financial
performance of West African Banks: A case study of some selected commercial
banks." International Journal of Education and Research 2, no. 1 (2014).
Oduro, I. M., and S. K. Agyei. "Mergers And Acquisition and Firm Performance: Evidence from
the Ghana Stock Exchange." Research Journal of Finance and Accounting 4, no. 7 (2013): 99107.
Rahman, Mahabubur, and Mary Lambkin. "Creating or destroying value through mergers and
acquisitions: A marketing perspective." Industrial Marketing Management 46 (2015): 24-35.
Rani, Neelam, Surendra S. Yadav, and P. K. Jain. "Financial performance analysis of mergers
and acquisitions: evidence from India." International Journal of Commerce and Management 25,
no. 4 (2015): 402-423.
Rappaport, Alfred, and Mark L. Sirower. "Stock or cash? The trade-offs for buyers and sellers in
mergers and acquisitions." Harvard business review 77, no. 6 (1998): 147-58.
Ravenscraft, David J., and Frederic M. Scherer. Mergers, sell-offs, and economic efficiency.
Brookings Institution Press, 2011.
Seth, Anju. "Value creation in acquisitions: A re‐examination of performance issues." Strategic
Management Journal 11, no. 2 (1990): 99-115.
Siegel, Donald S., and Kenneth L. Simons. "Assessing the effects of mergers and acquisitions on
firm performance, plant productivity, and workers: newl evidence from matched employer‐
employee data." Strategic Management Journal 31, no. 8 (2010): 903-916.
Straub, Thomas, S. Brozillo, and Gilbert Probst. "A Decision-Making Framework to Analyze
Important Dimensions of M&A Performance."Advances in Mergers and Acquisitions 11 (2012):
Thanos, Ioannis C., and V. Papadakis. "Unbundling acquisition performance: How do they
perform and how can this be measured?." Handbook of Mergers and Acquisitions, Oxford
University Press, Oxford UK (2012a).
Thanos, Ioannis C., and Vassilis M. Papadakis. "The use of accounting-based measures for
measuring M&A performance: A review of five decades of research." Advances in Mergers and
Acquisitions 10 (2012b): 103-120.
The World Bank Group. 2009. THE PETROLEUM SECTOR VALUE CHAIN.
Viverita, L. "The Effect of Mergers on Bank Performance: Evidence From Bank Consolidation
Policy In Indonesia." In International Business Research Conference. 2008.
Wolf, Christian OH. "The Petroleum Sector Value Chain." Available at SSRN 1514593 (2009).
Appendix 1. Financial performance indicators
(Revenue - Operating Expenses)
(Revenue - Expenses + Tax, Interest,
Depreciation and amortization)
(Gross profit / Revenue)
(Net income / Revenue)
(Net income / Total assets)
(Net income / Total equity)
(Net profit / Capital employed)
(Current assets / Current liabilities)
(Current assets - Inventories / Current
Gearing (Total debt / Total equity); or
(Total debt / Total assets)
(EBIT / Interest paid)
(Market share price / Earnings per share)
EPS (Net income - Dividends / Number of
Gugler et al., 2003; Thanos, Papadakis, 2010,
2012; Rani et al., 2015
Siegel, Simons, 2010
Rahman, Lambkin, 2015
Bertrand, Betschinger, 2011; Kalakkar, 2012;
Moctar, Xiaofang, 2015
Bruner, 2004; Mboroto, 2013
Rani et al., 2015
Krishnakumar, Madhvi, 2012
Ferrer, Tang, 2012; Bertrand, Betschinger,
Viverita, 2008; Kalakkar, 2012
Aybar, A. Ficici, 2009; Moctar, Xiaofang,
Gelles, Douglas, 1996; Joash, Njangiru, 2015
Source: author‘s compilation based on the literature review
Appendix 2. Academic research on M&A-Performance relationship (Extract)
D.S. Siegel K.L.
N. Rani, S.S. Yadav,
Robert. F. Bruner
O. Bertrand M.-A.
K. Gugler, D.C.
Mueller, B. Burcin
Increase in performance of the
Increase in performance of the plant;
A partial acquisition leads to a higher
performance than a full acquisition
Increase in financial performance by
Investment returns from M&A are
higher than the required returns
16,000 plants, 9,400 Regression
Improvement in the economic
Mergers result in significant increases
Mergers result in significant increases
Increase in financial performance
T-tests, event study
No effect confirmed
12 surveys and 120 Qualitative
(Target - sizable positive market
returns; bidders, with exceptions, –
zero adjusted returns; bidders and
targets combined – positive adjusted
G.O. Joash, M.J.
R.C. Ferrer, A. Tang
Increase in shareholders‘ value in 14 banks, 2000-2014 Interviews, regression
Positive impact on financial indicators 26 banks, 1996- Paired t-tests
Effects on stock price
94 companies, 2006- Panel data regression
N.B. Moctar, C.
Effects on liquidity, performance and 4 banks
No effect confirmed
Value created (Income growth)
Value deteriorated (others)
Value created (Asset turnover,
P/E, Dividend payout)
No (all others)
Source: author‘s compilation based on the literature review
Appendix 3. Statistical model outputs
Size of the target company and ROA ratio
Method of payment and ROA ratio
Acquired stake and ROA ratio
Type of integration and ROA ratio
Size of the target company and ROE ratio
Method of payment and ROE ratio
Acquired stake and ROE ratio
Type of integration and ROE ratio
Size of the target company and P/E ratio
Method of payment and P/E ratio
Acquired stake and P/E ratio
Type of integration and P/E ratio
Size of the target company and D/E ratio
Method of payment and D/E ratio
Acquired stake and D/E ratio
Type of integration and D/E ratio