Production Efficiency of Firms under Mergers and Acquisitions:
The Indian Experience
Beena S
Ph D Student
Centre for Development Studies
Prasanth Nagar, Ulloor, Thiruvananthapuram
Kerala, India Pin: 695 011
Email: [email protected]
May 2010
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Production Efficiency of Firms under Mergers and Acquisitions:
The Indian Experience
Beena VS
This study is an examination of one of the long debated issues in merger literature, that is
whether mergers and acquisitions enhance production efficiency or not. This argument cannot
be separated from the market power effect of mergers and acquisition. In fact, it is the trade off
between market power and efficiency makes it a hot debate. Interestingly, majority of these
studies are based on developed country context. Here we examine the argument of Williamson
(1968) of a net efficiency gain from mergers and acquisitions, separately for cross-border and
domestic deals. As a first step in this paper, we have examined the technical efficiency of the
firms using stochastic frontier production function and also applied inefficiency effects as
suggested by Battese and Coelli (1995). Our examination of technical efficiency and
inefficiencies lead to the conclusion that, even though merger reduces the inefficiency effects,
technical efficiency of the firms show a downward trend after getting into mergers and
acquisitions. This is true for majority of the sectoral cases also. Both domestic and cross-border
deals have an inefficiency reducing effect. In addition we have also seen that if we are taking
profitability and cost as efficiency indicators, the former decline and later increased during the
post merger period. This our results are in accordance with the findings of Ajit Singh, Meeks etc.
In a developing country context like India, it has got important implications for policy
formulation.
………………………………………….
Acknowledgements: Expressing my sincere gratitude to my Guru, Prof. P Mohanan Pillai, to whom I owe this and
everything. Prof. KK Subrahmanian, remains like a messenger of God, showed the path and disappeared…Prof. K
Pushpangadan, Prof. N Shanta, Prof. Pulapre Balakrishnan, Prof. Bishwanath Goldar, Prof. Sunil Mani, Prof. KJ
Joseph, Prof. NS Siddharthan, Dr. Beena PL, Dr. M Parameswaran, Dr. Anup Bhandari and Prof. Uday Bhanu Sinha
helped me at different stages of this work.
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Production Efficiency of Firms under Mergers and Acquisitions
Production Efficiency of Firms under Mergers and Acquisitions:
The Indian Experience
I) Mergers and the Theory of the Firm
This has been one of the most discussed issues in merger literature, and still the debate is
continuing among the economists under a disequilibrium status. Mergers are expected to
generate more efficiency through three grounds. First is through the re-organisation of
production, second, more efficient allocation of inputs, especially in the case of vertical mergers
it enables to get the inputs at lower prices, and third by providing more strengthened sales and
distribution network. A single strengthened network may function efficiently comparing the
previously operated two separate networks (Pesendorfer, Martin, 2003). As we mentioned in the
last chapter, most of the early studies on mergers and acquisitions were concentrating on the
developed counties, especially USA and UK mergers. That time, emphasise was on the
relationship of mergers to changes in the market structure and its consequences for the allocation
of resources. It is to be mentioned in this context that separating the efficiency effects of merger
is very difficult. It is the nexus between efficiency and market concentration makes this a hot
debate1. This can be understood from the observations of Meeks (1977). According to him, the
advocates of laissez-faire economists faced a dilemma over the state policy on mergers. Two
groups of conflicting views can be distinguished. One argues that merger undermines the
competitive conditions which are required if laissez-faire to achieve allocative efficiency. For
instance, Rowley and Peacock (1975) emphasized, mergers is certainly against the conditions of
perfect competition in which the laissez-faire ideals would be best fulfilled. So they supported
the outright ban on mergers and acquisitions. The others argued against the state interference in
the merger process, not only on political grounds but also on economic grounds saying that
merger will be in the public interest. Lord Robbins (1973) says that, “…my feeling about policy
relating to mergers and takeovers is that there is a certain presumption against preventing people
from buying or selling such property as seems them to be desirable (see Meeks, 1977 for details).
It can be seen that those who supported mergers based their argument on the efficiency defense,
whereas the others raised the issue of market power, which the mergers are likely to create.
1
However, in this chapter our attempt is to capture the efficiency aspects. The latter will be discussed in the next
chapter.
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Production Efficiency of Firms under Mergers and Acquisitions
Moreover, these arguments are much more related with the theories of the growth of the firm
since merger is expected to bring a structural change or disequilibrium in the market, which is
essentially an outcome of the growth strategy of the firms.
Hindley (1973) was one among those argued for allowing mergers and acquisitions. He based his
argument on the expected gains in economic efficiency and cost reduction through mergers and
acquisitions. According to him, a transaction occur only if the buyer has higher expected returns
and if it is satisfied, higher private profitability will be associated with social gains such as
reduction in the cost of production per unit of output. It is also argued that when there is excess
capacity in an industry, output will be concentrated in existing least cost firms. The level of
exiting least cost can be reduced since the merger enable firms to invest in new low cost
equipments due to the lesser uncertainty in post merger regime. Again, the concentration of
output in the hands of a single producer also enables the firms to derive potential economies of
scale. Further, mergers also help to make the efficient management of the existing firms due to
the hostile merger/takeover threat (Meeks, 1977).
The neo-classical assumption of profit maximization, which is central to the neo-classical theory
and the rest of the neo-classical analysis, has been subjected to a great deal of criticism from a
number of different quarters especially from the new theories of the firm. Amongst them, the
names of Oliver E. Williamson, Robin Marris and William J. Boumol to be mentioned. Marris
(1964) in the book The Economic Theory of Managerial Capitalism argued that modern
corporations are characterized by salaried managers, who are less interested in profit
maximization, rather they are more interested in growth of the firms. They have also other goals
such as power, prestige etc, which are more related with the size of the firm rather than profit.
Moreover, the managerial promotions usually take place through the bureaucratic and political
process within the corporation, which force them to concentrate on the size of the firm rather
than profit (Singh, Ajit, 1971). Berle and Means (1932) also favoured this argument and says that
this type of multiple goals will not allow the firm to realize the maximum potential output, or the
actual production will be always below the production possibility frontier. When these managers
face competition, they try to avoid it without taking risk or face it through interpersonal relations.
Here a merger or takeover offered prospects for high profitability either through reduction in the
cost of production or through improved trading of the combined firm. Moreover, it is also
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Production Efficiency of Firms under Mergers and Acquisitions
relaxation of effort on the part of management from taking risk in a competitive environment,
that is, an increase in X-inefficiency as termed by Leibenstein, 1966 (Meeks, 1977). However,
the economic natural selection due to A Alchian, M Friedman, G Becker and others pointed out
that the separation of ownership and control, bureaucracy etc are unimportant from the economic
point. Under competition, firms are forced to make profit for survival. This debate continued and
Marris2 and J K Galbraith argued against the neo-classicals that the process of selection will
drive out those who maximize profit and leave those who maximize growth. According to them
it will happen due to the rise of management controlled large corporations to the dominant
position in the economy, which alter the fundamental nature of economic environment and hence
the dynamics of the selection process. To Galbraith the danger of involuntary takeover is
negligible in the management calculations of the large firm and diminishes with the growth and
dispersal of stock ownership (Singh, Ajit, 1971). Cyert and March (1963) views mergers and
acquisitions as an opportunity to overcome the higher cost associated with the cyclical upswings
through the enhanced market power from mergers (Meeks, 1977).
From the above discussion, it is clear that even though the economists are not in a consensus, it
seems merger can lead to an increased efficiency via the reduction in various costs, which
increase the market power of the firms, and a consequent rise in prices can be expected. The
economists raised the question of ‘trade-off’ especially in the context of US, as part of
implanting the merger policies. Williamson (1968) favoured the net efficiency gains and says,
“even then the cost differential is too low; the net benefits will offset the losses”. Here we will
discuss the simple model developed by Williamson (1968) and later extension by Shapiro and
Willig (1990)3, which forms the broad framework of our study.
The Naïve Tradeoff Model of Williamson (1968) and its Extension
Williamson first introduced it for the horizontal deals and later extends to other types. This is a
partial equilibrium model, which intends to analyse the resource allocation effect of a merger
that yields economies but extends market power as well. From the Figure 1, it can be seen that
the initial level of average cost of the two (or more) firms which are going for merger, before
2
Marris (1968).
The article is in the context of joint ventures, which we are applying to mergers and acquisitions with some minor
changes.
3
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Production Efficiency of Firms under Mergers and Acquisitions
combination is AC1 and AC2 represents the post merger level of average cost. P1 is the pre
merger price and is equal to k (AC1). Here k is an index of pre merger market power and is
greater than or equal to unity. The post merger price is P2 and is assumed to exceed P1. If
P2<P1, then the economic benefits of merger is strictly positive. It simply reveals that market
power is only a necessary and not a sufficient condition for undesirable price effect to exist. The
shaded areas in the figure A1 and A2, shows the approximate net welfare effects. A1 shows the
dead-weight loss that can occur if the prices were increased from P1 to P2 assuming the cost
remains the same. However, since the merger reduces the average cost from AC1 to AC2, the
area A2 represents cost saving, must also taken into account. The net allocation effect is given by
the difference A2-A1. Thus if the cost reduction effect exceeds the dead-weight loss then the net
effect is positive and vice versa. According to Williamson, if the decimal fraction deduction in
the average cost exceeds the square of the decimal fraction increase in the price multiplied by
one half k times the elasticity of demand, the allocative effect of merger will be positive, that is,
Figure 1Williamson's Model
Source: Williamson (1968)
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Production Efficiency of Firms under Mergers and Acquisitions
 ( AC ) k  P 
 
 0
AC
2  P 
2
If this difference is zero, then merger is neutral and if inequality reversed, the effect of merger is
negative. Here  is the elasticity of demand.
Shapiro, D and Robert D Willig (1990) made smaller extension to the above model. Here we are
assuming a perfectly competitive industry (see Figure 2). Prior to the consolidation move the
firm was producing ‘Q0’ quantity of output at ‘C0’ marginal cost and ‘P0’ price, which is implicit.
If consolidation is taking place at this point and suppose that both the firms are producing their
previous level of output, then the cost of production will reduce from ‘C0’ to ‘C1’ (i.e. C0 >C1).
Here the firm increases the efficiency by reducing production costs and the area DE shows this
improved efficiency.
Figure 2 The Effect of Consolidation on Price, Output and Efficiency
Source: Shapiro, D and Robert D Willig (1990)
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Production Efficiency of Firms under Mergers and Acquisitions
Now the firm has three options. One is to sell their product at previous level of price (P0) second
at a reduced price (P1) and third at a higher price (Pm) using their increased market power4. In
the first case there will not be any change in prices and the firm will get the profit equal to the
area D+E that is, Q (OC0-OC1). In the second case, the firm can capture the entire market
through a small marginal reduction in prices. The net increase in welfare would be similar to the
area D+E that is, Q (OC0-OC1), which is the sum of profits and consumer surplus. Here the
consumers would appropriate the area E through the price reduction offered by the firm. Under
the third case, allowing for an increase in the market power of the firm and restricted entry, firm
can set the prices at the profit maximizing level of a monopolist, say Pm in our figure, which will
enable them to achieve a higher level of profit given the cost of production, C1<C0. The
consumers will be harmed due to the price hike and their loss would be equal to the area A+B
and the profit for the monopolist would be similar to the area A+D5. The net welfare impact
would be similar to the area D - B, where D represents the cost saving due to merger and B is the
deadweight loss arising out of monopoly pricing.
Thus the trade off between these two has been an evergreen topic of debate in merger literature
as we discussed earlier. In this paper, our attempt is to study the first part of this figure that is the
change from C0 to C1 and Q0 to Q1. Before getting down to the analysis, we shall brief the status
of manufacturing productivity literature in India.
II) Manufacturing Sector Productivity in India
Much has been discussed about the productivity of the firms in India especially the eighties and
nineties. Even though these studies were mainly concentrating on the impact of economic
reforms on the productivity performance, they underwent serious discussion on the underlying
methodological issues. The first generation productivity literature in India starts with the study
by PR Brahmananda (1982), followed by Bishwanadh Goldar (1986) and Ishar Judge Ahluwalia
(1991). Among this, Ahluwalia’s contribution is considered to be the most notable
(Balakrishnan, P, 2004). It was Balakrishnan, P and Pushpangadan (1994), who pointed out that
this study lacks the need for a double deflator instead of single deflator, which is significantly
4
5
It will also depend on the number of firms in the industry, elasticity of demand etc.
Since the firms were not getting profit (normal profit only) prior to merger.
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Production Efficiency of Firms under Mergers and Acquisitions
affecting the result. They pointed out that TFPG in the 1980s is actually slower than that in the
1970s, which is against the findings of Ahluwalia’s study. This can be treated as a turning point.
With the publication of this study, a series of articles published, debating the methodology used
for estimating productivity6. The major issues raised by these studies are the following. Price
index used for deflation: according to Goldar (2002) in reply to Balakrishnan, P and K
Pushpangadan (2002), the TFP estimates are sensitive to the selection of base year. Selection of
an appropriate indicator for labour input is another issue. Here the question is how far the
available data can represent this adequately. This becomes especially important when we
consider the quality of labour (OECD, 2002). Needless to say capital stock estimation is
confronted with many issues particularly relating to the calculation of the replacement cost of
capital. Majority of the studies used Perpetual Inventory Method (PIM) for estimating this. The
available data impose great amount of arbitrariness in doing this. After selecting the variables,
one can think of both econometric as well as growth accounting framework for the estimation of
productivity. Both have its limitation. Recently studies are concentrating on the econometric
methodology instead of growth accounting framework (see for example, Balakrishnan, P, K
Pushpangadan and Suresh Babu (2002); Srivastava et.al (2001) etc), owing to the limitations of
the latter as well as due to the advancement of software packages available, which made the
former easier comparing the early periods.
Regarding the merger related productivity studies in India, most of them were concentrating on
the profitability as the major indicator and found a declining trend in profitability after getting
into mergers7.
III) Measurement of Efficiency: The Concept and the Basic Model
Full Efficiency in an engineering sense means that a production process has achieved the
maximum amount of output that is physically achievable with current technology, and given a
fixed amount of inputs. Thus technical efficiency gains are a movement towards “best practices”
6
See for example, Balakrishnan, P and K Pushpangadan (1995, 1996, 1998), Balakrishnan, P, K Pushpangadan and
Suresh Babu (2000), Rao, JM (1996), Pradhan and Barik (1998), Trivedi, P, A Prakash, D Sinate (2000), Goldar, B
(2000), Unel, B (2003) etc., for related debates.
7
For eg., Beena, PL, 2004; 2008 etc.
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Production Efficiency of Firms under Mergers and Acquisitions
or elimination of technical and organizational inefficiencies8 (OECD, 2001). Mehta, MM (1950)
says that broadly there are three standard measures of industrial efficiency. They are, 1) Earning
or Profit making capacity of different units 2) Labour productivity per man hour and 3) Cost of
production per unit of output. The lower the cost, the greater is the efficiency. Most of the
merger- productivity studies in the international context as well as India concentrated on the first
measure that is profitability9. However profitability as a measure of economic efficiency is
criticized due to the fact that profitability may be the outcome of multiple factors, efficiency is
only one among them. It is not wholly correct to establish any correlation between rate of profit
earned and the standard of efficiency attained by different units (Mehta, MM, 1950). Moreover,
in the merger context, profitability can also reflect the market power effect resulted from merger,
which lead to higher profit10.
According to Farrel (1957), economic efficiency can be classified into technical and allocative
(see Coelli et.al, 2005). Technical efficiency (TE) is defined as the ability of the firms to get
maximum or potential level of output, given the inputs constant. Whereas, allocative efficiency
(AE) is the ability of the firm to equate its marginal value product to its marginal cost. Our
earlier discussion follows that merger affect both the technical and allocative efficiency. The
concepts are explained with the help of a figure (see figure 3). Here we are assuming that the
maximum or potential level of output a firm can produce is Y1 using X1 inputs and deriving П1
level of profit. The firm will be in equilibrium at B where the price line PP1 matches the
production possibility frontier FF1, the maximum level of production. But due to various reasons
the firm will be always producing below the point B, say at the point A which shows the
‘inefficiency or inability’ of the firm to attain the maximum level and achieving only П2 level of
profit and Y2 output. Here the firm will find the new equilibrium at AA1 frontier, which is at
point C, where it will be producing Y3 output using X1 inputs and deriving a lower level of
profit П3. Here the movement from B to A can be treated due to technical inefficiency and that
from A to C is due to the allocative inefficiency. A firm will be achieving the highest possible
output Y1 only if there is no inefficiency. This is a very rare situation in practice. Another
8
This is the major difference between productivity and efficiency. Productivity refers to the amount of output that
can be produced from a given level of input. It seldom talks about the maximum amount of production. Thus
productivity is a measure of efficiency. Efficiency is a broader concept than productivity.
9
See Meeks (1977), Singh (1971) etc and found a decline in the post merger profitability.
10
This logic can also be applied to technical efficiency as well. We recognize the fact that the existing efficiency
indicators are unable to capture this type of complex issues.
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Production Efficiency of Firms under Mergers and Acquisitions
interesting thing to be notice here is that, when the firm is facing such inefficiencies, undergoing
a merger or acquisition is expected to generate synergies and derive economics of scale, which
will enhance the firm to achieve a better equilibrium such as D, where the firm can produce Y4
level of output using X3 inputs and derive П4 level of profit.
However, in the Indian context, measurement of allocative efficiency is not common due to the
non-availability of the price data of various inputs used for production. Hence, the studies
concentrate on the measurement of Technical Efficiency alone. We are also following the same.
Thus from the above discussion, Technical Efficiency is defined as the ratio of Actual Output to
Potential Output. Here arises another problem. We can get the data on Actual Output; however,
we don’t have information on the Potential Output. Several methods used different proxies for
this. Recently, different statistical packages estimate it via linear programming method
(Kalirajan and Shant, 1994).
Figure 3 The Concept of Technical and Allocative Efficiency
Source: Kalirajan, KP and RT Shant (1994)
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Production Efficiency of Firms under Mergers and Acquisitions
III.A) The Stochastic Production Function Approach: There are four major methods of
estimating efficiency. They are Least Square Econometric Production Models, TFP Indices, Data
Envelopment Analysis (DEA) and Stochastic Frontiers11 (Coelli et.al, 2005). We have used the
Stochastic Frontier Production function (SFP) independently proposed by Aigner, Lovell and
Schmidt (1977) and Meeusen and van Broeck (1977) and later expanded and improved by many
scholars to measure efficiency (see Battese and Coelli, 1995). We have used this approach due to
two major reasons. First, the alternative tools available such as the non-parametric Data
Envelopment Analysis (DEA) is not free from limitations and comparing DEA, the SFP is
considered to be yielding better results. DEA is more vulnerable to extreme values and data
errors (Kalirajan and Shant, 1994). Moreover, SFP assumes the existence of technical
inefficiency in producing a particular level of output. Many of the studies measure this
inefficiency using a two-stage approach, in which the first stage involves the specification and
estimation of the stochastic production frontier and the prediction of the technical efficiency
effects, under the assumption that these inefficiency effects are identically distributed. The
second stage is the specification of the regression model for the predicted technical inefficiency
effect, which is against the assumption of identically distributed inefficiency effects in the
stochastic frontier12. In order to overcome this limitation, Battese and Coelli (1995) proposed a
model for technical inefficiency effects in a stochastic frontier production function for panel
data. This model allows the estimation of both the technical change in the stochastic frontier and
time varying technical inefficiencies. Recently, many studies in the Indian context are widely
using this method (for eg. Parameswaran, 2002; Natarajan and Rajesh Raj, 2007 etc).
Further, we have used production function rather than cost function considering the availability
of data. Production function itself we can measure through different specifications such as Cobb
Douglass, Constant Elasticity of Substitution (CES), Transcendental Logarithmic Function,
commonly called Translog Production Function etc. depending on the assumptions/conditions
we are putting. We have applied the Translog production function, which is well-known for its
less restrictive assumptions. Unlike some other specifications, it is not based on the assumptions
11
Of which the first two methods assumes same technical efficiency for all firms, whereas the latter assumes the
opposite. Among this the first and fourth methods involves the econometric estimation of the parametric functions
while second and third do not. Therefore the 1st and 4th is called Parametric and others known as Non-parametric
methods.
12
In the Indian context, Balakrishnan, P, K Pushpangadan and Suresh Babu (2000) used this approach.
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Production Efficiency of Firms under Mergers and Acquisitions
of constant elasticity of substitution, Hicks-neutral technical progress and constant returns to
scale. This enables us to have more realistic results.
III.B) Variables Construction
Output: Output is measured in terms of its value. However, recently, PROWESS is not giving
information on the value of output directly as it was doing earlier. So, we have calculated it using
the data on firm level sales and changes in the stock of finished and unfinished goods. This
amount is deflated by each years sector-wise Wholesale Price Index13 to avoid the influence of
inflation.
Labour: One major constraint for using PROWESS data is it is not giving information on
mandays generated by each firm, instead it gives information on the number of employees. Here
separation between part time and full time employees is not made, which inflates the labour
counts. So we have followed Srivastava (1996), methodology to arrive at the actual labour hours
employed for measuring labour content. For this, we have used Annual Survey of Industries
(ASI) for calculating the average wages paid per labour hour at two digit level14. This rate is
applied to the corresponding industrial classification of PROWESS, CMIE to get the firm level
value15.
Capital Stock: Hashim, SR and MM Dadi (1973) cautions that there are several problems
associated with the definition and measurement of capital stock. First of all capital stock is a
“composite commodity”, which consist of different types of goods and this will change over the
years. The changing composition of capital over time makes the measurement of capital stock a
difficult task. Also the capital stock existing at any time has no linkage with current market
valuations. The available data on capital stock is expressed in terms of historic prices. Each firm
has to undergo several restructuring and replacement of its capital assets due to depreciation and
other unexpected damages. If we are taking the value expressed in historic prices, we may be
underestimating these expenses incurred over the years. Here arises the need for calculating the
13
WPI base year used is 1993-94.
ASI provides mandays worked and total emoluments paid. From this, we have calculated emoluments paid per
labour hour (man hours is, mandays multiplied with 8 hrs). However, ASI data is only up to 2005-2006. We have
used the compound growth rates up to 2005-2006 for predicting the values for later years. We have followed 1987
National Industry Classification (NIC) for doing this.
15
We have taken the above mentioned average wages from ASI to apply with the amount of compensation paid as
in PROWESS and calculated the labour hours worked.
14
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Production Efficiency of Firms under Mergers and Acquisitions
replacement value of capital in order to give importance to the replacement value incurred in the
production process. Moreover, the productivity of the capital stock is not constant during its
lifespan, which makes the measurement of capital in relation to its original cost difficult. This
raises the controversy over the methods of depreciation and the concept of replacement cost etc.
Majority of the studies on manufacturing sector productivity depend on the Perpetual Inventory
Method (PIM) to construct the capital stock (see Srivastava, 1996; Balakrishnan, P,
Pushpangadan, K and M Suresh Babu, 2000; Parameswaran, M, 2002 etc). We have also
followed the methodology used by Srivastava (1996).
One major step involved in this is to find out the Replacement Cost of Capital. Replacement Cost
of Capital is defined as the Revaluation factor (RG) multiplied with the Value of Capital Stock at
Historic Cost. Replacement Cost of Capital measurement is discussed here. It is important to
note that Srivastava (1996) agrees that “…there is no perfect way of doing this and any method
used is, undoubtedly, an approximation…” RG is defined as16,
RG 
1 g1 1
………… (1)
g1
Where ‘g’ is the growth rate of investment and ∏ is the change in the price of capital. Growth
rate of Investment can be obtained by using the formula, g= It/It-1-1. Here our assumption is that
Investment (I) increased for all firms. Change in the price is measured through, ∏=Pt/Pt-1-1. Here
Pt is obtained by constructing capital formation price indices17 from the series for Gross Fixed
Capital Formation in Manufacturing using various issues of National Accounts Statistics of
India.
Here more realistically, our assumption is that capital stock does not dates back infinitely, but its
earliest vintage is ‘t’ period, then the above equation becomes,
1 g 11  1 g1  1 …….. (2)
R =
g1 g1  1
t 1
G
t
t 1
16
See Srivastava (1996), Balakrishnan, P, Pushpangadan, K and M Suresh Babu, (2000) Parameswaran (2002) for
details.
17
Price is equal to Gross Fixed Capital Formation at Current prices divided with the same at constant prices.
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Production Efficiency of Firms under Mergers and Acquisitions
We have assumed that the lifespan of capital stock is 20 years following the Report of Machine
Tools-1986 (NAS, 1989; Pillai, Mohanan P and J Srinivasan 1987). We have selected 1999-2000
as the base year owing to the largest number of mergers and acquisitions during this year. So
following Srivastava, no firm has any capital stock in the year 1999-2000 of a vintage earlier
than 1979-80. In the case of firms incorporated before 1979-80, it is assumed that the earliest
vintage capital in their capital mix dates back to the year of incorporation. As Srivastava notes,
for some firms the vintage of the oldest capital in the firm’s asset mix and incorporation year
may not coincide. Since no other better alternative is available, we are also following this
methodology. After getting the Revaluation factor (RG), we have deflated it with the Wholesale
Price Index (WPI) for machinery and machine tools (Source: Office of the Economic Advisor,
Ministry of Commerce & Industry, GOI, Various Years) with the base year 1999-2000. As we
mentioned earlier, we calculated the Replacement Cost of Capital from the Revaluation factor
(RG) and the Value of Capital Stock at historic cost. We have used Gross Fixed Assets of the
firms for the estimation. This enabled us to apply the Perpetual Inventory Method to construct
the capital stock. This is defined as,
kt1  kt  It1
kt kt1 It
kt2  kt  It  It1 and so on.
Intermediary Inputs: Following Goldar (2004) and Balakrishnan, P and Pushpangadan, K
(1994), we have taken the sum of the deflated values of raw material cost, power and fuel, and
other intermediate inputs for measuring it. In order to deflate into real value of inputs, we have
calculated the weighted average price indices. For this, the study used Input Output Transaction
Table 2003-2004 published by CSO, GOI (2008) and the respective sector’s Wholesale Price
Indices published by the Office of the Economic Advisor, Ministry of Commerce & Industry,
GOI. We have expressed the prices in 1993-94 prices. Weights are assigned considering the
respective share of each inputs in the total inputs used. We have added the purchase of materials
done by 68 sectors in the manufacturing sector from various other sectors, which includes the
purchase of materials made by one industry to another as well as the inter-industry transactions.
This data is used to construct the weight of each sector. Then the corresponding WPI is used to
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Production Efficiency of Firms under Mergers and Acquisitions
prepare Weighted Price Index. Similarly, we have created separate series for Energy input. For
deflating we have used fuel power light and lubricants price index18 based on 1999-2000 prices.
Next is the services purchased by the industrial units such as outsourced professional jobs,
insurance premiums paid etc, which makes a good proportion of the other input costs (Goldar
2004). So we have calculated another deflated series for this. This is done by taking the service
cost incurred by each sector from the Input Output Transaction Table and implicit deflator
calculated from the Gross Domestic Product (GDP) at current and constant prices using National
Accounts Statistics19.
Variables in the Inefficiency Model
R&D Intensity (RD): It is defined as the ratio of R&D to sales. It is expected to reduce the
inefficiency effects by strengthening the already available technology.
Payments made for Royalties and Technical Knowhow (royal): This is also taken as percentage
of sales of the firm. It indicates the import of technology, which is considered to enhance the
efficiency of the domestic firms since under normal conditions, technology is imported only if it
result in increased production.
Export Intensity (export): Firms trading with other countries always necessitates the firm to
become more competitive, which may pressurize the firm to operate more efficiently.
Raw Materials Import Intensity (rawimp): The need for importing raw materials arises when the
domestic market is facing supply shortage for perfect substitutes or if the prevailing price in the
domestic market is higher than that of the international prices. In addition, the higher quality raw
materials can enhance the efficiency of production.
Age of firm (firmage): Age of firm indicates the extent of experience a firm owns, which is
expected to reduce the inefficiency. But it can become the other way if it leads to outdated
machineries etc for production.
Year Dummy of Merger (yeardum): A dummy variable added to understand whether the
inefficiencies declined after getting into merger. This will take the value ‘0’ up to the year of
merger and after that, it will become ‘1’.
Domestic Mergers (domestic): This is to understand the influence of domestic deals on
inefficiencies. As we have been discussing from the beginning, mergers expected to make the
18
This is based on coal mining, mineral oils and electricity (GOI, Various years).
Implicit deflator is calculated using the ratio of GDP at current and constant prices. The weights are based on the
flows from service to the manufacturing sector. Base year of GDP used is 1999-2000.
19
16
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
firms more efficient by using the resources more efficiently. It is expected to generate more
labour productivity, because when two firms integrate their operation, it will get an opportunity
to re-arrange their existing labour force, which will result in better productivity of the labour.
Similarly, as we said in the beginning, capital and intermediaries utility also increases due to the
scale operation and synergy creation. Number of domestic deals is used to capture this effect, the
logic being that when more mergers occur, the inefficiency might tend to reduce.
Cross-border Mergers (cbdeals): This is same as domestic mergers. Here also number of crossborder deals used to account for this. When a cross-border merger occurs, it is argued that
normally they acquire those firms, which are already efficient comparing the other firms in the
same sector (Griffit, et.al (2004) as in Schiffbauer et.al (2009)). In addition to that, foreign firms
assumed better performance will bring more efficient operation of the firm.
Time Variables (t and t2): This is in order to allow the inefficiency effects to change with respect
to time. However, this is different from the time variable included in the stochastic frontier,
which accounts for the Hicks neutral technological change20.
We have specified the model like this,
ln it   k k it   l l it   m mit   t t it  1 / 2  kk k it k it  1 / 2  ll l it l it  1 / 2 mm  1 / 2  tt t it t it   kl k it l it 
 km k it mit   kt k it t it   lm lit mit   lt lit t it   mt mit t it  Vit  U it ......(1)
The technical inefficiency effects are assumed to be defined by
U it   0   1 RD   2 royal   3 exp ort   4 rawimp   5 t   6 t 2   7 firmage 
 8 yeardum   9 domestic   10 cbdeals  W it .......... ( 2 )
Where i denote the ith firm, t is tth year, k is capital stock, l is labour unit, m is material inputs
used in the production process, t is time trend included in the model to allow the frontier to shift
over time. Vit is independently and identically distributed random errors of the Uits with mean
zero and variance σv2. Uit is the non-negative random variable associated with technical
inefficiency of production, which are assumed to be independently distributed, such that it is
obtained by truncation (at zero) of the normal distribution with mean zit  and variance σ2. zit is a
20
The distributional assumptions on the inefficiency effects permit the effect of technological change and time
varying behavour of the inefficiency effects to be identified, in addition to the intercept parameters β0 and  0
(Battese and Coelli, 1995).
17
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
(1 × m) vector of explanatory variables associated with technical inefficiency of production of
firms over time and  is (m ×1) vector of unknown coefficients. Wit id defined by the truncation
of the normal distribution with zero mean and variance σ2 such that the point of truncation is zit  that is, Wit ≥ - zit  (see Battese and Coelli, 1995 for details).
The technical efficiency of production for the ith firm at the tth year is defined as,
TEit  exp(U it )  exp( z it   Wit )..........(3)
IV) Empirical Estimation Results
For the analysis, we have taken mergers that occurred in the years 1994, 1997, 2002 and 200421
and then prepared unbalanced panel consisting of 20 years from 1988-89 to 2007-08. We have
used FRONTIER version 4.1c software package for doing the analysis. First we have tested the
usual assumptions behind the frontier and inefficiency model in order to understand the
adequacy of the model specified. First assumption is regarding the production function. Our
hypothesis is that Cobb-Douglass form best suit the data, given the translog form. As it can be
seen from the Table 1, the generalized likelihood ratio-tests (LR statistic)22 reject this hypothesis,
which indicates that the input elasticity and substitution relationships are not constant across the
firms. Thus our translog form best suit the data. The next hypothesis that the inefficiency effects
are not linear function of the explanatory variables specified in the model is also rejected, which
implies that the joint effect of these variables on the inefficiency of production is significant even
if the individual effect of one or more of variables may not be statistically not significant. From
the table it can be further seen that the assumption of no time effect is also rejected. The next
hypothesis that inefficiency effects are absent from the model is also strongly rejected, which
indicates that the production function is not same as the traditional average response function
which can be estimated efficiently by ordinary least square method. The value of variance
parameter, γ is close to one in all the years except 2004, which indicates that inefficiency effects
are likely to be highly significant in the analysis of production except for 2004 mergers.
21
Logic is being the number of mergers, data availability and distance between the years selected.
LR statistic   2log Likelihood H 0   log Likehihood H 1   . It has a chi-square distribution (or a
mixed chi-square distribution) with degrees of freedom equal to the difference between the parameters in the
alternative and null hypothesis.
22




18
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Table 1 Testing of Hypothesis in the Battese and Coelli Model of Stochastic Frontier
Hypothesis (H0)
Cobb-Douglass Production Function
 1   2  ...   10  0
5  6  0
   1   2  ...   10  0
1994
888.29
1997
1460
2002
698.9
2004
470.5
Critical value*
21.03
109.72
65.79
60.73
26.88
16.274
24.94
14.16
41.32
11.35
5.99
99.94
-116.82
37
60.53
-19.67
18
17.67**
468
229
53.96
121.13
-202.80 -313.98
38
63
LLF1
No of firms
Total no of observations
in the unbalanced panel
587
773
th
*Critical value corresponds to the 95 percentile for the corresponding chi-square distribution.
**Critical value is taken from Kodde, David A and Franz C. Palm (1986).
Another test to be carried out to prove that our production function is well behaved is the
assumption of monotonicity. This ensure that majority of the firms are having non-negative input
elasticity. The following table shows that in all cases more than 70 percent of the firms have nonnegative input elasticity.
Table 2 Percent of Firms with Positive Input Elasticity: Monotonicity Test
Year of Merger
1994
1997
2002
2004
Capital
87
73
76
72
Labour
100
100
100
100
Material
100
100
100
100
Our estimation results of the inefficiency model yields the following results (see the Table 3). As
we expected the spending on R&D induces a negative pressure on inefficiency. However, it is
statistically significant only for 1997 mergers. This is important since our own earlier study
found that merger induces more spending on R&D. Here we get the result that not only the
spending increases, but also it helps reducing the hindrances to achieve efficient utilization.
Regarding the payments made for royalties and technical know-how, for firms which went for
mergers in 1994, it is positive and significant and in majority of the other cases it is showing
positive trend, which indicates that the import of technology is not leading to decline in
inefficiencies related to production. Import of raw materials was also expected to reduce the
inefficiencies related to production. It is positive and significant in the case of mergers occurred
in 2002 and 2004. In order to understand it better, we have decomposed the technical efficiency
19
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
of firms, for which spending on technology increased during the post merger period23. Here also
the same trend of declining efficiency after getting into merger can be observed except for 2004
mergers (see Table 4). In the case of R&D spending it can be seen that even though the merger
exert a negative pressure on inefficiency, it is not enough to enhance the overall technical
efficiency during the post merger period. Interestingly, the export performance of the firms is
not helping them to reduce inefficiencies. Similarly, age of firms is also an inefficiency
enhancing factor indicating the lack of modernisation.
The merger variables yield the following observations. All the three variables shows negative
pressure on inefficiency related to production. However it is significant only in the case of 1994
mergers. Here the cross-border deals have a strong negative pressure, whereas domestic is not
significant anywhere. Thus we can infer that even though both cross-border and domestic deals
exert negative pressure, like the R&D effects we discussed above; it is not enough to overcome
all production inefficiencies, which will be clear from the subsequent analysis.
23
Pre and post four year average has been taken .
20
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Table 3 Estimation Results of the Stochastic Frontier and Inefficiency Model
Constant
βk
βl
βm
βt
0.5βkk
0.5βll
0.5βmm
0.5βtt
βkl
βkm
βkt
βlm
βlt
βmt
Constant
R&D
Royalties
Export
Import Rawm.
Time (t)
t2
Firm age
Merger dummy
Domestic deals
Cross-border
σ2 = σ u2+σ v 2
γ = σ u2 /σ v2+σ u2
LR test of one
sided error
LLF1
Mean TE
1994
coefficient t-ratio
9.14
8.24
-0.04
-0.83
-0.46
-2.40
2.03
8.37
-0.11
-1.99
0.00
-1.06
0.04
2.45
0.15
4.09
0.01
2.97
0.01
2.59
0.01
2.09
0.00
-2.93
-0.12
-6.41
0.01
1.81
-0.01
-1.74
-2.58
-2.64
-0.01
-0.66
9.66
2.48
0.37
2.18
-0.80
-1.91
0.40
2.93
-0.01
-2.44
0.15
1.70
-0.71
-2.28
0.00
-0.10
-0.22
-3.29
0.19
5.81
0.68
9.21
114.78
-202.80
0.69
1997
coefficient t-ratio
9.08
13.61
0.06
1.79
-0.59
-5.10
1.76
16.13
-0.05
-1.17
0.00
4.79
0.08
7.12
0.16
17.81
0.00
1.26
-0.01
-3.41
-0.01
-1.96
0.00
1.06
-0.07
-7.16
0.00
1.14
-0.01
-3.01
-3.14
-3.90
-0.33
-3.50
-2.83
-1.66
0.04
1.02
0.00
-0.90
0.16
1.75
0.00
-0.97
0.36
3.14
0.06
0.33
-0.01
-0.34
-0.05
-0.95
0.36
9.41
0.80
25.63
89.39
-313.98
0.78
2002
coefficient t-ratio
6.97
7.46
0.03
0.71
-0.10
-0.61
1.10
5.12
-0.22
-2.81
0.01
4.93
0.02
1.10
0.00
0.17
0.04
2.63
0.00
0.08
-0.01
-1.27
0.00
0.90
-0.04
-2.16
0.00
1.53
0.00
-0.92
-1.74
-2.69
-0.01
-0.55
2.59
0.99
0.19
1.93
0.87
3.95
0.12
1.01
0.01
0.99
0.00
-0.02
-0.04
-0.51
-0.01
-0.29
-0.03
-0.96
0.12
11.69
0.57
7.39
60.73
-116.82
0.43
2004
coefficient t-ratio
5.55
5.62
-0.01
-0.15
0.14
0.72
0.97
4.52
0.00
0.05
0.01
6.46
-0.02
-0.73
0.10
4.24
0.00
-1.36
0.00
-0.18
-0.03
-6.38
0.00
-0.51
-0.01
-0.39
0.01
1.55
0.00
0.08
-0.07
-0.55
-0.05
-4.76
0.74
0.75
0.54
4.97
0.21
3.31
0.06
3.27
0.00
-4.15
-0.03
-1.38
0.00
0.00
-0.07
-1.90
0.01
0.15
0.07
10.78
0.00
6.57
26.88
-19.67
0.89
21
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Table 4 Average Technical Efficiency of Firms for which Technology Spending Increased Post merger
Merger year
1994
Category
Domestic
Merger
Pre
Post
Cross-border Pre
Post
1997
Domestic
Pre
Post
Cross-border Pre
Post
2002
Domestic
Pre
Post
Cross-border Pre
Post
2004
Domestic
Pre
Post
Cross-border Pre
Post
* Spending on Royalties and Technical Know-how
R&D Intensity
0.86
0.61
0.88
0.75
0.83
0.74
0.86
0.75
0.78
0.09
0.76
0.09
0.86
0.92
0.87
0.98
Royalties*
0.84
0.62
0.87
0.71
0.82
0.73
0.85
0.77
0.74
0.09
0.75
0.11
0.87
0.96
0.88
0.97
The Table 5 shows the mean technical efficiency of firms, which are going for mergers in
selected years. It is evident that during the post merger period24, the technical efficiency of
domestic as well as cross-border firms declined except for 2004 mergers. The sector-wise
analysis also shows similar results, the technical efficiency declined for majority of the cases
during the post merger period (see Table 6). This decline in technical efficiency is matching with
the findings of another study in the Indian context done by Parameswaran, (2002), for analyzing
the impact of reforms on productivity for selected sectors. This may be pointing out the overall
decline in technical efficiency after the reforms for selected sectors. However, the technical
efficiency of the cross-border firms remained higher than that of domestic firms for majority of
the cases. In the case of drugs and pharmaceutical industry, the technical efficiency of domestic
firms increased during the post merger period for 1997 mergers. In the case of 2004 mergers, it
improved in all cases.
24
Pre and post merger is defined in terms of the year of first merger. Pre merger constitute 1988-89 to the year of
merger and post merger period constitute the year thereafter.
22
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Table 5 Pre and Post Merger Technical Efficiency of Firms
Domestic
Merger year
1994
1997
2002
2004
pre
0.84
0.82
0.74
0.87
post
0.62
0.73
0.09
0.96
Cross-border
pre
post
0.87
0.71
0.85
0.77
0.75
0.11
0.88
0.97
All
pre
0.85
0.83
0.74
0.87
post
0.64
0.75
0.1
0.96
Source: calculated
D
C
2002
D
C
2004
D
C
0.84
0.63
0.87
0.87
0.83
0.74
0.85
0.78
0.51
0.12
0.77
0.12
0.92
0.99
0.88
0.96
0.64
0.89
0.63
0.72
0.65
0.85
0.77
0.68
0.08
0.73
0.09
0.88
0.96
0.86
0.82
0.62
0.89
0.79
0.86
0.76
0.76
0.09
-
Textiles
Machinery
Drugs &
Pharmaceuti
cal
Chemicals
0.87
0.64
0.86
0.58
0.83
0.74
0.85
0.76
0.80
0.09
0.76
0.10
0.85
0.96
0.86
0.99
0.74
0.52
0.86
0.77
0.77
0.72
0.88
0.76
0.77
0.10
0.93
0.98
-
Transport
Equipments
1997
0.91
0.68
0.91
0.66
0.89
0.92
0.87
0.75
0.24
0.09
0.05
0.83
0.78
-
Food&
beverages
C
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Nonmetallic
D
Metals&
Minerals
1994
Merger
Year of
Merger
Category
Table 6 Pre and Post Merger Mean Technical Efficiency of Firms
0.83
0.54
0.79
0.55
0.86
0.71
0.83
0.75
0.62
0.08
0.67
0.11
0.91
0.99
0.81
0.65
0.85
0.75
0.87
0.83
0.75
0.07
0.31
0.20
0.86
0.94
0.88
0.97
Note: D denotes domestic deals and C denotes cross-border deals.
We have also calculated the pre and post merger technical efficiency of horizontal and vertical
deals to understand it closely. We have calculated the pre and post merger average technical
efficiency. The results show that (see appendix Table 1) except for the 2004 mergers, the
technical efficiency declined for horizontal and vertical deals for both cross-border and domestic
deals. This result is interesting because as we told earlier the theoretical prediction say horizontal
and vertical deals creates more synergies, which enhance the efficiencies after getting into
mergers. However the results not validate this prediction, which may be indicating the absence of
adequate synergies after getting into mergers. Further, for majority of the years the technical
23
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
efficiency of the cross-border firms (both horizontal and vertical deals) remained above than that
of domestic deals.
Table 7 Average Input Elasticity
Year of Merger
1994
1997
2002
2004
capital
0.12
0.00
0.02
0.01
labour
0.46
1.83
0.16
1.60
material
0.52
1.20
0.64
0.98
The estimated input elasticity25 with respect to output arrives at some interesting observations.
As it can be seen from the Table 7, in majority of the cases labour is contributing more to the
production. In many instances mergers unwelcomed by the trade unions due to their fear or job
cut or more efficient utilization (increased work burden) of the existing labour. Our results
suggest that no other input is as elastic as compared to labour. Materials come next, while capital
is the least contributor. It may be reflecting the fact that in many cases firms may not be able to
utilize the capital to the maximum capacity owing to two reasons. One is, the operation of
synergies reduces the amount of capital required for the existing level of production. Secondly, it
leads to the excess capacity, if production is undertaking at the same production possibility
frontier that is no expansion in production after mergers. Added to this, earlier we have seen that
the age of firm is increasing production inefficiencies.
V) Profitability and Cost as Efficiency Indicators
As we mentioned earlier, the other two simple indices of efficiency are profitability as well as
cost per unit of output (Mehta, MM, 1950). We have attempted that too, since most of the merger
studies in India concentrated on these measures. In order to understand the profit rate, we have
used the ratio, profit/ sales, which give the amount of profit per unit of sales. We have calculated
the average for four years pre and post merger as well as all years post merger. Interestingly, this
ratio declined for majority of years (see Appendix Table 2). This is true for both cross-border as
25
The elasticity of each input in translog production function is defined as following.
LnQ
  k   kk LnK   kl LnL   km LnM   kt LnT
LnK
LnQ
  L   lk LnK   ll LnL   lm LnM   lt LnT
LnL
LnQ
  m   mk LnK   ml LnL   mm LnM   mt LnT
LnM
24
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
well as domestic firms. However, there are sector wise variations. For example, in the case of
machinery, it increased for some year mergers (see Appendix Table 3). Our own earlier study
found that the profitability of pharmaceutical industry mergers (see Beena, S, 2008) increased
during the post merger period, however the present study, with a different methodology arrive at
the conclusion that either it remained the same or declined. It is in accordance with most of the
merger studies in India as well as international context (Meeks, 1971; Ajit Singh, 1977;
Ravenscraft and Scherer, 1988 etc). One major question arises here is why post merger profit
declined. This is not in consensus with the theoretical prediction that merger can lead to
reduction in various costs, which will increase profitability. We feel it may be due to either of
four reasons such as, acquisition of loss making or less efficient firm; decline in capacity
utilization during the post merger period due to the lack of proper post merger integration of the
firms; overall macro economic determinants and the problems associated with the financing of
acquisition. If the firm borrowed money to finance acquisition and the interest payments exceeds
the expected earnings, then also it can happen.
Another measure is the cost per unit of output. We have used the ratio Total Cost/Value of
Output in the absence of a comparable input quantity across the firms and products26. It shows a
mixed picture but general trend is increasing cost after getting into mergers (see appendix Table
2). Inter-sectoral cases also show the same trend (see appendix Table 4). It validates the findings
regarding profitability. It may be indicating the increasing cost of acquisition, when merger
comes to operation.
V) Concluding Observations
This paper attempted to address the question, whether mergers and acquisitions actually leading
to more efficiency in production as debated by the economists. The logic behind this argument
being that merger leads to cost reduction due to the operation of synergies. In order to understand
it in a developing country context like India, we have used stochastic frontier production
function along with inefficiency effects introduced by Battese and Coelli, 1995. Our results
reaches the conclusion that though mergers and acquisitions helped reducing the inefficiency
effects, the technical efficiency of the firms involved declined for majority of the firms. It has
important implications, since our own earlier research pointed out an increased spending on
26
Majority of the firms are multi-product firms, difficult to capture unit of production.
25
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
R&D and royalties etc after getting into mergers. Here it proves that it not only helps to increase
spending on technology, but also helps to reduce inefficiencies associated with production.
Paradoxically, the technical efficiency of majority of the firms declined during the post merger
period, this is true for sector-wise analysis also. Reading together the frontier and inefficiency
effects, we can argue that the amount of negative pressure exerted by merger is not enough to
overcome the production inefficiencies in general. We can also think it in a different way that
firms are entering into mergers to overcome the decline in manufacturing sector technical
efficiency during the post reform period, which has been established by other studies in the
Indian context. Technical efficiency of both horizontal as well as vertical deals declined during
post merger time. It was expected that for these deals the synergy creation is more and there-by
efficiency enhancement will be higher due to the increased scope for post merger operation. Our
examination of the profitability and cost of production also show that there is substantial
reduction in the former and expansion in the latter after entering into mergers. This is also true
for both cross-border and domestic deals. This result is in consensus with the earlier findings on
post merger profitability of the firms both in the Indian and international context. Added to this,
elasticity of factor inputs shows that even though merger leads to more efficient utilization of
labour, capital case is different. This may be reflecting that during the post merger period, firms
are not able to derive the expected synergies in capital usage. From this it is clear that merger is
leading to the efficient utilization of the labour, whereas under utilization of capital. Even this
increased ulilisation of labour is not enabling to overcome the inefficiencies associated with
production. This may be due to the increasing cost of mergers and acquisition or due to the
acquisition of loss making counterpart, lack of proper integration of the firms during post merger
period or it may be reflecting the increased interest payments after undertaking huge investment
for mergers and acquisitions.
26
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
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28
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
Appendix
Table 1 Pre and Post Merger Technical Efficiency of Horizontal/Vertical Deals
Merger year Category
Merger Horizontal Vertical
1994
Domestic
Pre
0.84
0.84
Post
0.62
0.6
Cross-border Pre
0.88
0.86
Post
0.66
0.8
1997
Domestic
Pre
0.8
0.85
Post
0.72
0.76
Cross-border Pre
0.85
0.85
Post
0.78
0.75
2002
Domestic
Pre
0.74
0.24
Post
0.09
0.09
Cross-border Pre
0.6
0.75
Post
0.1
0.11
2004
Domestic
Pre
0.86
0.97
Post
0.95
0.9
Cross-border Pre
0.87
0.88
Post
0.99
0.96
Table 2 Pre and Post Merger Mean Profit and Cost of Firms
Merger year
1994
Category
Domestic
Cross-border
1997
Domestic
Cross-border
2002
Domestic
Cross-border
2004
Domestic
Cross-border
Merger
Pre
Post four
post merger
Pre
Post four
post merger
Pre
Post four
post merger
Pre
Post four
post merger
Pre
Post four
post merger
Pre
Post four
post merger
Pre
Post four
Pre
Post four
PAT/Sales Expenses/Value of Output
0.06
0.96
0.06
1.17
-0.22
1.37
0.04
0.99
0.05
0.98
0.02
1.05
2.35
16.45
-0.36
2.44
-0.75
2.27
0.6
13.81
0.56
17.44
0.17
10.15
0.03
1.21
0.05
0.99
0.06
1.11
0.05
0.98
0.07
1.24
0.06
0.97
0.06
0.9
0.01
0.99
0.00
1.31
0.03
7.87
29
September 11, 2009
Production Efficiency of Firms under Mergers and Acquisitions
C
2002
D
C
2004
D
C
0.01
-0.01
0.02
0.01
0.09
0.04
0.10
0.05
3.48
3.54
0.04
0.05
0.11
0.08
0.07
0.07
0.06
0.05
0.02
0.08
-3.08
0.07
0.01
0.06
0.06
0.03
0.11
Transport
0.07
0.06
.
.
0.06
-0.19
0.06
0.02
Food
0.05
-0.04
0.02
0.00
0.14
0.42
0.07
0.08
-0.04
0.10
0.05
0.08
0.07
0.04
0.07
0.05
Metals
0.08
0.03
0.01
0.07
8.97
-0.11
0.08
-0.02
0.04
0.06
0.06
0.07
0.05
Textiles
D
0.09
0.07
0.05
0.05
0.13
0.13
0.11
0.00
0.09
-0.02
.
-0.02
0.05
Nonmetallic
1997
Machinery
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
C
Chemicals
D
Drugs
1994
Merger
Year of
Merger
Category
Table 3 Sectoral Pre and Post Merger (four years) Profit to Sales
0.05
0.01
0.02
0.03
0.05
0.02
0.05
0.04
0.01
-0.03
0.00
0.07
0.09
0.05
0.04
0.03
0.07
0.09
-0.05
.
-0.06
0.03
0.00
0.03
-0.02
C
2002
D
C
2004
D
C
0.83
1.18
6.32
1.00
0.94
0.99
0.81
0.82
84.67
108.08
0.98
1.00
0.90
0.94
0.97
0.94
0.95
.
.
0.66
1.07
1.01
1.03
Textiles
Nonmetallic
0.97
1.11
1.01
1.03
1.61
3.27
0.94
0.94
2.70
1.19
0.99
1.04
0.79
0.92
3.15
12.60
Metals
0.95
1.01
1.02
0.96
61.65
1.13
0.93
1.04
0.99
0.97
0.96
0.95
0.87
0.96
0.98
0.97
0.99
1.13
8.48
0.94
1.08
0.98
1.49
0.98
0.92
Transport
D
0.93
1.01
0.96
0.98
0.94
0.91
0.93
1.04
1.18
1.03
.
1.04
0.93
Food
1997
Machinery
C
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Pre
Post
Chemicals
D
Drugs
1994
Merger
Year of
Merger
Category
Table 4 Sectoral Pre and Post Merger (four years) Expenditure per unit of Output
0.98
1.05
1.01
0.99
0.96
0.99
0.96
0.97
1.02
1.05
1.00
0.96
0.92
0.95
0.72
0.67
0.95
0.93
1.06
.
1.19
0.92
11.11
1.19
1.77
30