Description
The purpose of this paper is to examine the impact of partial privatization on performance
of state-owned banks using data from the Indian banking industry during the period 1986-2003, and
test the hypothesis that privatization leads to improvement in performance even when the government
retains controlling stakes
Journal of Financial Economic Policy
Partial privatization and bank performance: evidence from India
Subrata Sarkar Rudra Sensarma
Article information:
To cite this document:
Subrata Sarkar Rudra Sensarma, (2010),"Partial privatization and bank performance: evidence from India",
J ournal of Financial Economic Policy, Vol. 2 Iss 4 pp. 276 - 306
Permanent link to this document:http://dx.doi.org/10.1108/17576381011100838
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Donald J . Mullineaux, Mark K. Pyles, (2010),"Bank marketing investments and bank performance", J ournal
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Mohammad Alipour, (2013),"Has privatization of state-owned enterprises in Iran led to improved
performance?", International J ournal of Commerce and Management, Vol. 23 Iss 4 pp. 281-305 http://
dx.doi.org/10.1108/IJ CoMA-03-2012-0019
Mauricio J ara-Bertin, J osé Arias Moya, Arturo Rodríguez Perales, (2014),"Determinants of bank
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Partial privatization and bank
performance: evidence from India
Subrata Sarkar
Indira Gandhi Institute of Development Research, Mumbai, India, and
Rudra Sensarma
University of Hertfordshire Business School, Hat?eld, UK
Abstract
Purpose – The purpose of this paper is to examine the impact of partial privatization on performance
of state-owned banks using data from the Indian banking industry during the period 1986-2003, and
test the hypothesis that privatization leads to improvement in performance even when the government
retains controlling stakes.
Design/methodology/approach – Employing the technique of stochastic frontier analysis,
bank-speci?c estimates of total factor productivity were obtained, because they can be considered
as a measure of performance, along with four accounting measures. Panel regression models were
employed to assess the impact of partial privatization on these performance indicators.
Findings – Partial privatization was found to result in signi?cant improvement in performance of
state-owned banks. This ?nding is robust to alternative model speci?cations and different techniques
for controlling potential selection bias.
Research limitations/implications – The paper focuses on the impact of partial privatization on
operational and ?nancial performance of banks. Future work could consider the effects on other
aspects such as wages and ?nancial development.
Practical implications – The results suggest that faced with political opposition to full
privatization, even if the government does not relinquish control, the exposure to market discipline
through partial privatization may be an effective way of improving performance of state-owned banks.
Originality/value – This is the ?rst work to examine the effects of partial privatization in the
context of Indian banks and one of the very few to study this issue for any banking industry.
Keywords India, Banks, Privatization, Stochastic processes, Organizational performance
Paper type Research paper
1. Introduction
Several studies have empirically examined the effect of privatization on ?rm
performance. Studies have concentrated on various aspects of this issue such as the
mode and extent of privatization, sources of public sector inef?ciency, measures of ?rm
performance and the various econometric issues therein. However, the evidence on
whether privatization leads to improvement in performance is mixed. A survey by
Vining and Boardman (1992) found that out of 87 papers considered only 28 reported
performance improvement after privatization. Even when privatization does work it is
not clear whether it is a feasible approach in many contexts. For instance, political
opposition to privatization may prevent outright sale of state-owned enterprises. Faced
with such political hurdles, governments may often resort to partial privatization as an
alternative.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
The authors are grateful to two anonymous referees for useful comments. The usual disclaimer
applies.
JFEP
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Journal of Financial Economic Policy
Vol. 2 No. 4, 2010
pp. 276-306
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381011100838
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Partial privatizationmay lead to improvements in ?rmperformance if the managerial
viewof privatization holds. This viewemphasizes the monitoring and disciplining roles
of stock markets and the consequent bene?ts of improved managerial incentives even
when the privatization is only partial (Holmstromand Tirole, 1993). On the other hand a
political view of privatization opines that there may not be any performance gains from
partial privatization if the government retains control of the ?rms after privatization. In
such a situation political interference would continue to hamper the performance of
state-owned ?rms and the privatization would not yield any bene?ts (Shleifer and
Vishny, 1997). Which of these two effects would ultimately dominate in the case of
partially privatized ?rms is not clear from the theoretical literature. There are other
bene?ts of privatization such as improved access to external resources as creditors
might perceive a privatized ?rm to be more credit-worthy than a state-owned ?rm that
would receive political protection in case it defaults. Privatized ?rms would in general
face lower costs of raising funds and are expected to potentially bene?t from foreign
direct investment and associated transfer of technology.
According to Gupta (2005), most studies on ownership and performance that ?nd
performance of ?rms improving after privatization consider cases where management
control is transferred to private owners, but not much is known about the effectiveness
of partial privatization. We attempt to examine this issue in the context of Indian
banks, which have undergone a programme of partial privatization since the launch of
banking reforms in the early 1990s. Indian banking offers a unique case study as it is
characterized by the presence of public sector banks (i.e. fully state-owned as well as
partially privatized banks) and private sector banks (domestic and foreign) thus
covering the entire range of ownership types. Most studies have found that banks in
India exhibited improvement in performance over the last two decades (Kumbhakar
and Sarkar, 2003; Sensarma, 2006). This has been attributed to the economic reforms of
1991, which engendered a series of measures such as interest rate deregulation and
branch de-licensing. While the private banks outperformed the public sector banks in
the earlier years, in recent years the latter have been able to bridge the gap by taking
advantage of the deregulatory measures (Bhaumik and Dimova, 2004; Sensarma,
2006). However, the public sector banks have been considered as a single group in
these studies and no distinction was made between those banks that were partially
privatized and those that remained fully state-owned.
India is an emerging economy where a shift from government control to a more
liberalized economy in the 1990s meant that private participation in the economy has
become signi?cant. On the other hand, because of its vibrant democracy a strong
political opposition exists that has prevented full privatization of many state-owned
enterprises. This is especially true for state-owned banks due to their underlying social
objectives, which are perceived by the political opposition to be under threat if the banks
were to be privatized. Owing to the political opposition to bank privatization, India has
followed a piecemeal approach where the government has been relinquishing some of its
stakes in one or a few banks every year. We study this partial privatization programme
by examining bank performance over a long period of 1986-2003[1] which allows us to
evaluate whether the managerial view or the political view has dominated in the case of
Indian banks. In particular, we are able to separately examine the roles of listing on the
stock exchange and the magnitude of privatization. The very act of listing a state-owned
bank on the stock exchange can generate market discipline as the Indian stock market
Partial
privatization
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regulator imposes strict disclosure norms on all listed entities. On the other hand the
degree of divesture could in?uence the performance of banks as it proxies the extent of
monitoring and disciplining the bank is subjected to by private shareholders.
Measurement of bank performance is a contentious issue in itself and there is an
ongoing debate over what is a good measure. The productivity literature suggests that
total factor productivity (TFP) can be a useful measure of performance as it is not
in?uenced byaccounting practices. This is a popular approachin banking as TFPcan be
computed based on the cost function and it is often argued that cost based measures are
more appropriate for analyzing public sector units which may be more concerned with
cost minimization rather than pro?t maximization (Kumbhakar and Sarkar, 2003).
We assume that banks minimize costs by choosing the output level and therefore we
adopt a cost based indicator of productivity de?ned using the Divisia index. In addition,
we employ a host of accounting indicators of pro?tability and ef?ciency of banks. These
indicators are justi?ed on the grounds that one of the stated goals of banking sector
reforms in India was to achieve improvement in pro?tability and ef?ciency. We study a
total of four accounting indicators of pro?tability and ef?ciency to complement the
Divisia index of TFP in our analysis of partial privatization.
Analyzing data over the period 1986-2003, we ?nd that partial privatization led to an
improvement in performance of Indian state-owned banks with the effect being more
persistent for TFP than for accounting indicators. On an average, partially privatized
banks experienced an increase of 3 and 4 percent in TFP growth. These ?ndings are
robust to many alternative model speci?cations and controls for potential selection bias.
The rest of this paper is organized as follows. Section 2 provides a review of the
relevant empirical literature. Section 3 presents a brief overview of the banking sector
in India and the partial privatization programme. Section 4 discusses the data and the
methodology employed. Section 5 contains the main empirical ?ndings and their
discussion. Section 6 highlights the robustness of the ?ndings to alternative ways of
accounting for potential endogeneity and Section 7 concludes the paper.
2. Literature review
The empirical literature on privatization has found signi?cant performance gains from
privatizing former state-owned ?rms. Boardman and Vining (1989) examined the
performance of large non-US corporations in 1983 to conclude that private ?rms are more
ef?cient than their public counterparts. Megginson et al. (1994) and D’Souza and
Megginson (1999) compared pre- and post-privatization performance of a large number of
?rms from industrialized as well as developing countries to show that privatization
resulted in signi?cant gains in pro?tability, sales and ef?ciency. Inthe context of transition
economies, Frydman et al. (1999) studied 200 ?rms fromthe Czech Republic, Hungary and
Poland to show that for state-owned ?rms that are sold to outsiders (i.e. not managers or
employees), privatizationyields signi?cant improvement in performance. Furthermore, the
performance gains appear to be interms of revenue enhancements rather thancost savings.
However, the empirical literature speci?c to the banking industry does not provide
unanimous evidence on the question of whether privatization helps to improve
performance. Megginson (2005) provides an excellent survey of the empirical literature on
bank privatization. Based on a review of a large number of studies he concludes that
private banks are usually more ef?cient than state-owned banks. However, in case of
partial privatization, the effects on performance depend on institutional and regulatory
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environments. Bonin et al. (2005) studied cost and pro?t ef?ciency of 59 banks from six
advanced transition countries and provide evidence in support of privatization. The
analysis revealedthat banks that are soldto a strategic foreignowner earlyinthe periodof
the privatization programme exhibit better performance than state-owned banks and
those banks that are privatized later. Boubakri et al. (2005) analyzed the privatization
experience of 81 banks from22 developing countries. Analysis of accounting indicators of
performance revealed that the poor performers were selected for privatization and the
impact of privatization on performance was ambiguous. While pro?tability increased,
the impact on ef?ciency, risk exposure and capitalization largelydependedonwhether the
control of the privatized bank rested with the government, foreign investors, local
industrial groups or individuals.
To cite some country speci?c studies, Nakane and Weintraub (2005) estimated TFPfor
242 Brazilian banks and concludedthat state-ownedbanks were less productive thantheir
private counterparts and that privatization increased their productivity. Beck et al. (2005)
studied the Nigerian banking systemusing data on accounting indicators of performance
for 69 banks. They concluded that privatization led to performance improvement and
those banks that continued to have minority government ownership performed worse
than the fully privatized banks. On the other hand privatization has been shown to have
negative effects inChina (Chen et al., 2005) and inPakistan(Bonaccorsi di Patti and Hardy,
2005). Experience from Mexico suggests that bank privatization may fail unless there are
strong institutions and well de?ned property rights (Haber, 2005). In fact Mexico’s ?rst
experiment in privatization led to insolvency of the banks and the second experiment
produced a risk-averse banking system. While most of these papers are concerned with
whether privatization led to improvement in bank performance, the issue of partial
privatization and bank performance has been scarcely studied.
Gupta (2005) studied the impact of partial privatization on ?rm performance.
Employing data on Indian state-owned ?rms belonging to the manufacturing and the
non-banking services sectors, she investigated the impact of partial privatization on
performance. The performance variables considered were accounting indicators of
pro?tability, productivity and investment. The analysis revealed that partial
privatization did lead to improvement in performance. Since the government retained
management control of these ?rms even after the partial privatization exercise, the
improvement in performance could not be attributed to the elimination of political
interference. Gupta (2005) attributed it to the amelioration of the agency problem
associated with government ownership that got reduced with the stock market now
enforcing managerial discipline and corporate control. In the case of Indian banks,
Kumbhakar and Sarkar (2003) studied the impact of deregulation on the productivity of
Indian banks and found that while productivity of private banks improved, public sector
banks did not respond to deregulation. The issue of partial privatization of public sector
banks was not considered by them. Mohan (2005) and Sathye (2005) used difference of
means tests to conclude that ?nancial parameters of performance for partially privatized
banks in India were superior to those of public banks. However, both these studies used
only ?ve years of data and did not consider the determinants of performance.
3. Overview of Indian banking
The banking sector plays a crucial role in fostering economic growth, especially in an
emerging economy such as India. Banks play an important role, inter alia, in the
Partial
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mobilization of savings and capital formation whose importance for an emerging
economy cannot be overemphasized. The dominant presence of banking in the Indian
economy can be gauged from the fact that aggregate deposits stood at 48 percent of
gross domestic product (GDP) in 2002-2003 and bank credit to the government and
commercial sector stood at 26 and 33 percent of GDP, respectively, in 2002-2003. Thus,
in terms of size, banking occupies an important position in the economy. Prior to 1992,
the banking sector in India was highly regulated and dominated by the public sector
banks. With the developmental objectives of providing adequate credit, there were
severe constraints on operational decisions. In addition, the banks were impeded by
regulations on the pricing of ?nancial products imposed by the banking regulator,
namely, the Reserve Bank of India (RBI).
However, towards the early nineties the government realized that an excessive focus
on quantitative achievements was making many banks inef?cient, unpro?table and
under-capitalized. Recognizing these problems, the RBI launched the banking sector
reforms in 1992 on the recommendations of the ?rst Narasimhamcommittee on ?nancial
sector reforms (RBI, 1991). This led to the deregulation of entry, interest rates, branch
de-licensing and allowed public sector banks to access the capital markets for raising
equity. At the same time, there were a number of changes in statutory norms, namely, a
gradual reduction of the cash reserve ratio and the statutory liquidity ratio, setting up of
a minimum 8 percent capital to risk-weighted assets ratio (CRAR), and an imposition of
stringent income recognition and provisioning norms. The second round of reforms in
the banking sector followed the report of the second Narasimhamcommittee (RBI, 1998)
that laid stress on prudential measures like higher CRAR, allowing for market risk on
government securities, stricter non-performing assets norms, introduction of
assets-liabilities management and risk management guidelines.
The banking sector reforms in India, initiated in 1992, were intended to impart
enhanced ef?ciency, productivity and pro?tability into the system. One key element
of the reforms process was the partial privatization of public sector banks. While
the government retained controlling stakes, up to 49 percent of equity was sold
to investors. However, this was done in a piece-meal manner, with one or two banks
getting listed in every year after 1993. Table I presents the timeline and extent of
privatization of the public sector banks. Table II denotes the resulting shareholding
pattern of the banks which suggests that while ownership is fairly diversi?ed, foreign
institutions ended up holding large stakes in the public sector banks and could act as
an important source of market discipline.
Even though the government continues to hold controlling stakes due to political
reasons, it was felt that subjecting public sector banks to market discipline through
stock exchange listing was an effective way of improving their performance as it
provided a method of alleviating the agency problem arising out of government
ownership. The stock market regulator has elaborate disclosure norms for newissues as
well as continuing disclosures ranging from ?nancial information to dividend policy,
business risks and corporate governance requirements[2]. Banks intending to get listed
on the stock exchange have to provide the auditor’s report on their ?nancial statements
along with the management’s discussion and analysis of ?nancial conditions and results
of operations. The business strategies as well as risks categorized as company speci?c
and general factors have to be disclosed. Other requirements of the regulator include a
due diligence certi?cate from a lead merchant banker, grading details from a credit
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rating agency, appointment of a compliance of?cer and details of outstanding
litigations. Corporate governance requirements include details of management and
shareholding structure, compensation of directors, information on audit committee,
shareholder/investor grievance committee, etc.
Listed banks are therefore subject to stringent disclosures facilitating monitoring
by investors which provides an alternative governance mechanism to the RBI’s
monitoring. The two are different in many aspects, e.g. the RBI’s focus is on prudential
regulation and its compliance (and the information is not released to the public) rather
than ?nancial details and corporate governance (readily accessible by investors) which
is a primary focus of the stock exchange disclosures. The Basel-II accord acknowledges
that market discipline is an important governance mechanism, which can complement
the industry regulations and supervisory processes. Such disclosure norms and the
consequent market discipline have made the public sector bank managements more
cognizant of the market consequences of their activities, which may have led to the
improvement in the performance of these banks (Mohan, 2006). On the other hand it
may be argued that listing alone may not produce the desired effects unless a bank is
fully privatized. This is because of the moral hazard generated by the implicit
government guarantee in a partially privatized bank, which could weaken the
Partial privatization details
Name of bank Year sold Percentage of equity sold
State Bank of India and its associates
State Bank of India 1994 33.7
a
State Bank of Bikaner and Jaipur 1998 25.0
State Bank of Travancore 1998 25.0
Nationalized banks
Oriental Bank of Commerce 1995 33.5
Bank of Baroda 1997 33.8
Bank of India 1997 30.7
Dena Bank 1997 29.0
Corporation Bank 1998 42.8
Syndicate Bank 2000 26.5
Andhra Bank 2001 33.4
Indian Overseas Bank 2001 25.0
Vijaya Bank 2001 30.0
Punjab National Bank 2002 20.0
Allahabad Bank 2003 28.8
Canara Bank 2003 26.8
Union Bank 2003 39.1
Notes:
a
A further 6.6 percent of equity was sold in the year 1997; this table shows the timeline of
partial privatization till 2003, i.e. the last year of our period of analysis. Out of the 27 public sector
banks in India, the 16 banks shown in this table were partially privatized and the remaining 11 were
not (the names of the 11 banks that were not partially privatized are: State Bank of Hyderabad, State
Bank of Indore, State Bank of Mysore, State Bank of Patiala, State Bank of Saurashtra, Bank of
Maharashtra, Central Bank, Indian Bank, Punjab and Sind Bank, UCO Bank, United Bank of India).
State banks refer to those that were always state-owned namely the State Bank of India and its
associate banks. Nationalized banks refer to those that were taken into government ownership during
the nationalization programmes in 1969 and 1980
Source: RBI
Table I.
Timeline of partial
privatization of public
sector banks till 2003
Partial
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Table II.
Shareholding pattern
of public sector banks
(end-March 2005)
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monitoring efforts of shareholders. The managers too are aware that the government
may bail them out especially if the state is a large shareholder (Megginson, 2005).
Therefore, the effects of partial privatization and listing on performance are hardly
unambiguous. It is against this backdrop that we empirically examine the impact of the
partial privatization programme on bank performance in India.
4. Empirical methodology and data
4.1 Total factor productivity
We use TFP as our ?rst measure of bank performance as “productivity gains are the
dominant factor in post privatization outcomes” (La Porta and Lopez-de-Silanes, 1999).
Following Kumbhakar and Lovell (2000), we estimate three components of TFP
growth, namely, those attributable to technical progress, returns to scale and ef?ciency
change and then aggregate them as:
TF
_
P ¼ TF
_
P
1
þ TF
_
P
2
þ TF
_
P
3
ð1Þ
Until very recently, econometric models of TFP growth had ignored the last term,
i.e. the role of ef?ciency change. However, as Kumbhakar and Lovell (2000)
purposefully argue, when individual production units vary greatly in terms of their
cost or productive ef?ciency, ignoring this component is likely to give biased estimates
of productivity growth. While the ?rst two components of TFP growth, i.e. technical
progress and returns to scale, can be estimated from a standard cost function, the last
component, i.e. ef?ciency change, requires the estimation of a cost frontier. Since the
production technologies of banks are unknown a priori, we estimate ef?ciency as
the deviation from the ef?cient cost frontier where the best-practice banks operate.
To do that we consider the following stochastic cost frontier:
ln E ¼ ln CðY; W; tÞ þ U þ V ð2Þ
where, E ¼ WX is total expenditure, X ¼ (x1, . . . , xN)’ is a (N £ 1) vector of inputs,
W ¼ (w1, . . . , wN)’ is a (N £ 1) vector of input prices, Y ¼ (y1, . . . , yM)’ is a (M £ 1)
vector of outputs, t is a time trend that proxies technical change, C(Y, W, t) is the
deterministic kernel of the stochastic cost frontier, U $ 0 is the one-sided cost
inef?ciency term, and V is a random variable with zero mean. Appendix 1 explains
how the TFP growth in equation (1) can be arrived at based on the stochastic cost
frontier in equation (2).
4.2 Estimation procedure
To arrive at the measure of TFP growth based on its three components we ?rst need to
estimate the stochastic cost frontier given in equation (2). This requires the speci?cation
of the random terms U and V and a functional form for the deterministic kernel C
(Y, W, t). We assume that the inef?ciency term u
it
follows a truncated normal
distribution with mean m and constant variance, while the random term v
it
follows
the usual normal distribution with a zero mean and constant variance[3]. Speci?cally, we
assume, u
it
, iidN
þ
ðm; s
2
u
Þ and v
it
, iidNð0; s
2
v
. For the deterministic kernel we
employ the translog (transcendental logarithm) speci?cation. The translog function
(Christensen et al., 1975) can be viewed as a second order approximation of any unknown
function and it provides ?exibility to a parametric functional form. Combining the error
terms and the deterministic kernel, the cost frontier function is speci?ed as:
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ln C
it
¼a
0
þ
m
X
a
m
ln y
mit
þ
j
X
b
j
ln w
jit
þb
t
t
þ
1
2
m
X
l
X
a
ml
ln y
mit
ln y
lit
þ
j
X
k
X
b
jk
ln w
jit
ln w
kit
þb
tt
t
2
8
<
:
9
=
;
þ
m
X
j
X
a
mj
ln y
mit
ln w
jit
þ
m
X
a
mt
ln y
mit
t þ
j
X
b
jt
ln w
jit
t þu
it
þv
it
ð3Þ
where w
jit
denotes the price of input j and y
mit
denotes the amount of output mproduced
by bank i in period t, respectively. The dependent variable, operating cost, is the sum of
establishment expenses and physical capital expenses[4]. We impose the standard
restrictions of symmetry and linear homogeneity for estimating the parameters of
equation (3):
a
ml
¼ a
lm
and b
jk
¼ b
kj
;
j
X
b
j
¼ 1;
j
X
b
jk
¼ 0 ;k;
j
X
a
mj
¼ 0 ;m;
j
X
b
jt
¼ 0:
A widely debated issue in the banking literature is the de?nition of banking inputs and
outputs, and more speci?cally the classi?cation of deposits in this respect. The two
alternative approaches to determining what constitutes inputs and outputs of banks are
the production approach and the intermediation approach (Sealey and Lindley, 1977).
The production approach considers labor and capital as inputs and number of processed
accounts as outputs. The intermediation approach considers deposits as inputs and
de?nes loans and investments as outputs. We adopt the production approach, which has
been the most used approach in the Indian context (Kumbhakar and Sarkar, 2003), and
thereby consider deposits to be an output of a bank. Finally, we also include the number of
branches as an output variable. Branches are expected to control for many immeasurable
attributes of a bank, e.g. quality of services and number of accounts serviced (Berg et al.,
1993; Grifell-Tatje and Lovell, 1996)[5]. Accordingly, in this study, banks are modeled as
multi-product ?rms that produce six outputs (?xed, saving and current deposits[6], loans,
investments and branches) and employ two inputs (labor and capital).
The price of labor is de?ned as the ratio of established expenses to the total number of
employees. The price of capital is measured as the ratio of physical capital expenses to
?xed assets which is then used to normalize costs and input prices in order to impose the
linear homogeneity restrictions. All the variables are de?ned in details in the Appendix
Table AI. The parameters of equation (3) are then estimated by the Maximum-Likelihood
method using the FRONTIER (version 4.1) software developed by Coelli (1996).
The log-likelihood function of this model is available fromKumbhakar and Lovell (2000).
4.3 Estimable partial privatization regression
Once the cost frontier is estimated and TFP growth is computed, we construct an index
of TFP for every year and every bank as:
TFP
it
¼ TFP
iðt21Þ
1 þ TF
_
P
it
 Ã
:
The value of the index is set to 100 for the ?rst year for all banks. De?ning the
logarithm of TFP index values as our ?rst measure of performance, we regress it on the
partial privatization variable as follows:
Performance
it
¼ a þd
t
þbPP
it
þgX
it
þ1
it
ð4Þ
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This equation is estimated using the ?xed effects panel regression (within effects)
model (Wooldridge, 2002), where i indexes banks, t indexes years, a is the intercept, d
t
is a year-speci?c ?xed effect, b is the coef?cient of the partial privatization variable PP,
g is the coef?cient of a control variable X. We do not allow for bank-speci?c ?xed
effects as they lead to multicollinearity problems arising from the presence of a private
sector dummy which we include in the model to control for those banks that belong to
the private sector throughout our sample period.
We use various proxies to represent partial privatization (PP) that we explain in details
while presenting our empirical ?ndings. In addition to TFP, we replace the performance
variable in equation (4) with four different accounting ratios, namely, operating pro?t ratio
(OPR), net interest margin (NIM), operating cost ratio (OCR) and staff expense ratio (SER).
These variables are de?ned in the Appendix Table AI. OPR is a simple measure of
pro?tabilityas it indicates howa bankis able to generate revenues over andabove its costs.
NIM is a measure of a bank’s competence in generate income from its core businesses, i.e.
interest bearing assets. Therefore, OPR and NIM offer us two metrics of a bank’s
performance in terms of its revenue generating abilities. OCR measures the extent of
resources used by a bank and SER indicates its ef?ciency in labor usage. These two
variables are suitable measures of operating ef?ciency. Therefore, in all we have ?ve
performance measures for estimating equation (4).
The year speci?c ?xed effects account for unobserved year speci?c changes. This is
particularly relevant in our case since the banking sector in India continues to undergo
policy changes over the years. Moreover, the ?xed effects would also help to control for
competition effects that build up over time. Over the years as the banking sector
experiences liberalization, intensi?ed competition from private incumbents and the
entry of de novo banks may affect performance of public sector banks. We expect the
year speci?c ?xed effects to capture such bank-invariant effects.
In equation (4) the main coef?cient of interest is b that is attached to the partial
privatization variable PP. It indicates the effects on performance that is attributable to
partial privatization over and above those caused by other regulatory changes and
bank speci?c attributes. As for the sign of this coef?cient, that would get determined
by whether the managerial view (Holmstrom and Tirole, 1993) or the political view
(Shleifer and Vishny, 1997) dominates. For instance, if the former outweighs the latter,
i.e. if market discipline and incentives are strong even for partially privatized banks, then
we can expect the coef?cient to have a positive sign for the productivity and pro?tability
measures. In other words, partial privatization would yield improvement in productivity
and pro?tability. For OCRand SERwe would then expect the coef?cient to be negative as
partial privatizationwouldleadtocost savings for these banks. However, inall the cases of
partial privatization of Indian banks the government has so far retained control. This
might mean that the political view dominates as political interference might continue to
sti?e the performance of the former state-owned banks.
Finally, we include control variables X
it
to account for other sources of variations in
performance. These include SIZE(logarithmof total assets) whichproxies for the abilityof
smaller banks to respond more quickly to changes in market conditions in which case its
coef?cient would be negative in the partial privatization regressions. The proportion of
rural branches (PROP_RUR) is considered as a proxy for the business opportunity,
or the lack of it, faced by a bank in rural areas. Its coef?cient would determine whether the
investment in rural areas has been rewarding for banks. The proportion of non-interest
Partial
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income to total income (PROP_INT) controls for banks’ diversi?cation activities whichare
expected to bene?t them through higher productivity and pro?tability.
4.4 Data source
The accounting data of banks is taken from various issues of Financial Analysis of
Banks and Performance Highlights of Banks published by the Indian Banks’
Association. The ownership and listing data is taken from various issues of Report on
Trends and Progress of Banking in India published by the RBI. Among the 27 public
sector banks operating in India, we include all but three in our analysis. We exclude
those three banks, which got listed in the last year of the sample period (Table I).
We include the domestic private banks as a control group to enable us to isolate the
effects of partial privatization. There were 26 private banks during the sample period
but incomplete information was available for private banks in some years leading to an
unbalanced panel. We excluded new private banks, which started operating in 1996
and hence cannot be a good control group like the older private banks. Moreover, we do
not include foreign banks as they operate in India as branches of their parent entities
and are not listed on Indian stock exchanges like other private banks. Therefore, they
are not comparable with the Indian public sector and private banks when it comes to
analyzing the impact of stock exchange listing on performance. A time period of
18 years is taken for each bank from the year 1986 to 2003[7].
Table III presents the share of banking assets that each bank group holds.
Clearly, the public sector banks are the dominant group with over 75 percent share of
banking assets. But its share has been declining over the sample period while those
of the private groups have been rising. Table IV presents the descriptive statistics for
Year Public Private Foreign New private
1986 92.37 3.82 3.81 –
1987 91.84 3.89 4.27 –
1988 91.96 3.86 4.19 –
1989 92.00 3.49 4.51 –
1990 91.21 3.48 5.32 –
1991 90.25 3.65 6.10 –
1992 88.54 4.21 7.25 –
1993 87.11 4.73 8.16 –
1994 87.08 5.31 7.61 –
1995 86.23 6.43 7.34 –
1996 84.57 6.08 7.83 1.52
1997 82.35 6.52 8.74 2.39
1998 81.42 6.92 8.38 3.28
1999 80.86 6.90 8.16 4.09
2000 79.74 7.12 7.75 5.38
2001 79.32 6.29 8.21 6.17
2002 75.99 6.03 6.51 11.47
2003 75.83 6.20 6.75 11.21
Notes: For new private banks prior to their entry (new private banks are those that started operations
in 1996); values reported are percentages; this table shows the share of total assets held by each
banking group in India during our period of analysis
Source: RBI
Table III.
Share of banking assets
held by bank groups,
1986-2003
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the bank characteristics used in our empirical work. It appears that public sector banks
are the larger group compared to private banks in terms of assets, deposits and loans.
However, among the public sector banks, those banks which were partially privatized
are larger than those which were never partially privatized. Interestingly, the former
had a higher proportion of rural and semi-urban branches suggesting that they did not
enjoy larger urban presence than the banks which were never partially privatized.
Bank characteristics Mean SD Median Maximum Minimum
Log (TFP)
Public banks 4.86 0.25 4.78 5.68 4.57
PP banks 4.87 0.25 4.79 5.63 4.59
Never PP banks 4.86 0.26 4.78 5.68 4.57
Private banks 4.76 0.19 4.70 5.51 4.51
Operating pro?t ratio
Public banks 0.09 1.17 0.20 1.76 28.02
PP banks 0.26 0.97 0.26 1.63 26.67
Never PP banks 20.10 1.35 0.15 1.76 28.02
Private banks 0.46 1.22 0.44 16.37 28.51
Net interest margin
Public banks 2.52 0.81 2.60 5.73 24.45
PP banks 2.53 0.77 2.62 4.73 24.45
Never PP banks 2.51 0.86 2.52 5.73 0.48
Private banks 2.80 1.87 2.74 35.31 26.90
Operating cost ratio
Public banks 2.68 0.48 2.66 4.36 1.41
PP banks 2.60 0.49 2.57 3.77 1.41
Never PP banks 2.77 0.45 2.72 4.36 1.73
Private banks 3.07 3.69 2.80 72.82 0.00
Staff expense ratio
Public banks 1.97 1.13 1.92 23.65 0.85
PP banks 1.83 0.42 1.81 3.03 0.85
Never PP banks 2.13 1.59 2.01 23.65 1.17
Private banks 1.99 0.93 1.93 11.23 0.30
Proportion of rural branches (%)
Public banks 66.53 5.78 67.29 80.81 46.35
PP banks 66.61 6.87 67.53 80.81 46.35
Never PP banks 66.43 4.15 66.62 76.47 55.61
Private banks 59.59 16.92 63.30 84.38 0.00
Proportion of non-interest income (%)
Public banks 11.38 5.49 11.12 94.70 4.60
PP banks 11.29 6.64 10.93 94.70 4.61
Never PP banks 11.50 3.71 11.22 23.64 4.60
Private banks 10.48 34.83 11.38 34.32 2.94
Size
Public banks 9.90 10.57 9.17 12.84 6.40
PP banks 10.23 10.83 9.42 12.84 6.89
Never PP banks 9.26 9.19 8.92 10.95 6.40
Private banks 7.46 7.81 6.56 9.73 1.92
Notes: Size is natural logarithm of total assets (at 1993-1994 prices). PP refers to partially privatized;
this table presents the descriptive statistics for the ?ve performance indicators and the control
variables used in the regression models
Table IV.
Descriptive statistics
Partial
privatization
and performance
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But at the same time their proportion of non-interest income was higher indicating that
they were focused on fee based activities and earnings from trading.
5. Empirical ?ndings
We begin our discussion with the behavior of the TFP index and the accounting indicators
as shown in Figure 1. The graphs indicate that public sector banks as well as private banks
underwent improvement in productivity over the sample period. The period also witnessed
improvement inpro?tabilityand ef?ciency as indicated by the increase in OPRand decline
in OCR and SER. The improvements are particularly pronounced for the private banks
relative to the public sector banks. However, NIM remained stable for both bank groups.
Using the ?ve performance measures of the individual banks in each year,
we estimate ?ve partial privatization regressions based on equation (4). We use three
speci?cations for the partial privatization (PP) variable. These are:
(1) a trend variable that operates after a bank gets listed (LIST_TREND);
(2) a continuous variable to denote the extent of private ownership (PRIV_SHARE);
and
Figure 1.
Performance indicators for
public sector and private
sector banks
5.50
5.40
5.30
5.20
5.10
5.00
4.90
4.80
4.70
4.60
4.50
Public sector Private sector
Log (TFP)
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
1.5
1
0.5
0
–0.5
–1
–1.5
–2
Public sector Private sector
OPR
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Public sector Private sector
Public sector Private sector
NIM
SER
Notes: The figure presents a comparison of public and private sector banks based on the five performance
indicators. TFP is the index of total factor productivity estimated from a stochastic cost frontier; OPR is
operating profit ratio; NIM is net interest margin; OCR is operating cost ratio; SER is staff expense ratio
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
3.5
3
2.5
2
1.5
1
0.5
0
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Public sector Private sector
OPR
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
JFEP
2,4
288
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(
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(3) a dummy variable for stock exchange listing (LIST_DUM) that takes the value
one once a bank gets partially privatized.
These variables are designed to differently capture the roles of listing and ownership
share. The variable LIST_TREND provides a way of examining whether there is
persistence in the effect of partial privatization on performance. PRIV_SHARE is
constructed to analyze whether performance is related to the extent of share ownership
that is privately owned. LIST_DUM is designed to capture the average effect of the
partial privatization programme on performance.
To address the concern of multicollinearity we present a correlation matrix of all the
proposedindependent variables inTable V. While the three PPvariables seemtobe highly
correlated, there is very low correlation among the control variables and between the
control and PP variables. We do not include all the three PP variables in the same model
but use them in two combinations as described in the next paragraph. In any case we
checked the variance in?ation factors for each variable in each model; in none of the cases
did the VIF turn out to be .3 thereby indicating that our models did not suffer from
multicollinearity problems. We correct for heteroscedasticity in all the models by
estimating standard errors based on the Huber-White Sandwich estimator of variance.
For each performance measure we estimate two variants of equation (4) using the
alternative de?nitions of the PP variable. The estimation results for these two models are
presented in Tables VI and VII. In Table VI, we present the results from regressing
performance on PRIV_SHARE and LIST_TREND. We include a dummy variable
PRIV_SECTOR for the private banks group along with the other control variables. The
results reveal that the coef?cient of PRIV_SHARE is positive for the TFP, OPR and NIM
regressions and negative for the OCR and SER regressions. This indicates that higher
divesture was associated with improved productivity (higher TFP) and pro?tability
(higher OPR and NIM) while the ef?ciency effects (in terms of OCR and SER) are not
statistically signi?cant. In the TFPregression the coef?cient of IV_SHAREis 0.0007 and is
signi?cant onlyat 10 percent level of signi?cance. Onthe other handthe effects of the extent
of private ownership on OPRand NIMare stronger. Inthe OPRregression the coef?cient of
PRIV_SHARE is 0.0218 which is signi?cant at the 1 percent level of signi?cance while in
the NIM regression the coef?cient of PRIV_SHARE is 0.0194 which is signi?cant at the
5 percent level. In sum we ?nd statistically signi?cant evidence of improved performance
owing to higher divesture in the case of productivity and pro?tability.
The coef?cient of LIST_TRENDis statistically signi?cant only in the TFP regression
where it takes a positive value of 0.0220. This indicates that in the years subsequent to
their divesture, listed banks continued to exhibit higher productivity comparedto unlisted
banks. This suggests that improvement in productivity was not a one-off phenomenon or
simplya “listingeffect” (Gupta, 2005) but that the impact onproductivityfollowing partial
privatizationwas permanent andsustained. Finally, comparingthe relative magnitudes of
the coef?cients of PRIV_SHARE and LIST_TREND we observe that even though the
number of signi?cant coef?cients is more for ownership share than for listing trend, the
latter effect appears to be stronger in the only case where it is statistically signi?cant. In
the TFP regression the coef?cient of LIST_TRENDis 0.0220 while that of PRIV_SHARE
is 0.0007. It seems that while the magnitude of divesture may have been important in
improving productivity and pro?tability, the very effect of listing on the stock exchange
played a stronger disciplining role in improving productivity.
Partial
privatization
and performance
289
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1
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3
9
2
4
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a
n
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a
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2
0
1
6
(
P
T
)
P
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7
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9
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7
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2
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7
6
3
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2
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0
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2
1
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N
o
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e
:
T
h
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a
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p
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r
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g
r
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s
s
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n
m
o
d
e
l
s
Table V.
Correlation matrix of
independent variables
JFEP
2,4
290
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(
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(
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2
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9
N
o
.
o
f
o
b
s
.
8
2
8
8
4
1
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1
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4
1
8
4
1
N
o
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e
s
:
S
t
a
t
i
s
t
i
c
a
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l
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i
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i
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c
a
n
t
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f
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e
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1
0
,
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5
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n
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1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
h
e
?
v
e
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e
r
f
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m
a
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i
n
d
i
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t
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o
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l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
v
a
r
i
a
b
l
e
t
h
a
t
o
p
e
r
a
t
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s
a
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a
t
r
e
n
d
o
n
c
e
a
b
a
n
k
i
s
l
i
s
t
e
d
(
L
I
S
T
_
T
R
E
N
D
)
.
P
R
I
V
_
S
E
C
T
O
R
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
f
o
r
b
a
n
k
s
i
n
t
h
e
p
r
i
v
a
t
e
s
e
c
t
o
r
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
Table VI.
Partial privatization and
bank performance: roles
of listing trend and
ownership share
Partial
privatization
and performance
291
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R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
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_
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E
2
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4
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6
)
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(
0
.
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9
)
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(
0
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)
L
I
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T
_
D
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0
.
1
6
6
3
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*
(
0
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0
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)
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3
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(
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)
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R
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2
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0
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0
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0
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*
(
0
.
0
9
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)
P
R
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P
_
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U
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.
0
9
3
7
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*
(
0
.
0
4
0
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)
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.
6
7
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4
(
0
.
5
1
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1
.
8
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0
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)
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0
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)
1
.
7
3
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0
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*
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(
0
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2
4
9
2
)
P
R
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P
_
N
I
N
T
0
.
0
0
0
0
(
,
0
.
0
0
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1
)
0
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0
0
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9
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(
0
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0
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0
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2
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0
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0
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0
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0
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7
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0
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0
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3
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0
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3
6
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*
(
0
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0
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3
)
S
I
Z
E
2
0
.
0
1
1
5
*
*
(
0
.
0
0
4
1
)
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.
0
5
4
2
(
0
.
0
4
8
0
)
2
0
.
3
3
2
8
*
*
*
(
0
.
0
6
9
6
)
2
0
.
2
0
3
7
(
0
.
1
7
8
0
)
2
0
.
2
7
0
4
*
*
*
(
0
.
0
3
1
2
)
I
N
T
E
R
C
E
P
T
4
.
8
3
4
1
*
*
*
(
0
.
0
2
3
6
)
2
0
.
7
0
3
1
*
(
0
.
3
7
3
4
)
2
.
7
8
0
9
*
*
*
(
0
.
2
2
6
5
)
2
.
8
5
0
3
*
*
*
(
0
.
5
1
1
1
)
2
.
0
6
5
2
*
*
*
(
0
.
1
1
3
8
)
R
2
0
.
1
9
1
2
0
.
0
4
9
1
0
.
0
8
2
3
0
.
0
1
4
2
0
.
1
0
1
4
N
o
.
o
f
o
b
s
.
8
2
8
8
4
1
8
4
1
8
4
1
8
4
1
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
d
u
m
m
y
v
a
r
i
a
b
l
e
t
h
a
t
i
n
d
i
c
a
t
e
s
w
h
e
t
h
e
r
a
b
a
n
k
i
s
l
i
s
t
e
d
o
r
n
o
t
(
L
I
S
T
_
D
U
M
)
.
P
R
I
V
_
S
E
C
T
O
R
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
f
o
r
b
a
n
k
s
i
n
t
h
e
p
r
i
v
a
t
e
s
e
c
t
o
r
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table VII.
Partial privatization and
bank performance: roles
of listing effect and
ownership share
JFEP
2,4
292
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Moving to the control variables, we focus on those coef?cients which are
statistically signi?cant in the estimations. First we observe that the coef?cient of the
private sector dummy in the TFP regression is 20.1008 which is statistically signi?cant
at the 1 percent level. This suggests that public sector banks had higher productivity
thanthe private banks duringthe sample period[8]. The coef?cient of this dummyvariable
is also signi?cant inthe OPR, NIMandSERregressions takingthe values 0.6460, 20.3569
and 20.5722, respectively. These values indicate that private banks had higher
pro?tability and ef?ciency than the public sector banks. The proportion of rural branches
seems to adversely impact costs as indicated by its positive and statistically signi?cant
coef?cients of 1.1983 and 1.7585 in the OCR and SER regressions, respectively. However,
the additional expenditure owing to rural branches appears to have paid rewards through
higher pro?tability andproductivity as evidenced bythe NIMand TFPregressions where
the coef?cients of PROP_RUR are 1.7970 and 0.1000, respectively.
The proportion of non-interest income is associated with higher ef?ciency as
the coef?cients of PROP_NINT are negative and statistically signi?cant for the OCR
and SER regressions (the coef?cients are 20.0036 in both cases). However, non-interest
income seems to be associated with lower NIM (the corresponding coef?cient
being 20.0022) which is not surprising since banks with higher income from non-core
businesses may have less focus on lending activities. Finally, the coef?cients of SIZE
suggest that bigger banks are less productive (the coef?cient is 20.0135 in the TFP
regression) and have lower spreads (the corresponding coef?cient is 20.3309). It seems that
smaller banks were better able to take advantage of the changingmarket conditions leading
to higher productivity and interest income. However, bigger banks are more ef?cient as
indicated by the negative coef?cients on SIZE in the SER regression which is 20.2732.
In Table VII, we present the estimates of models comparing the roles of listing effect
and ownership share by including the LIST_DUM variable along with PRIV_SHARE.
The ?ndings for PRIV_SHARE are similar to the previous results for pro?tability.
For the SER regression we ?nd that the coef?cient of PRIV_SHARE is 20.0139 which
is statistically signi?cant at the 5 percent level. This suggests that the extent of
divesture has a negative association with staff expenses. In case of LIST_DUM the
only statistically signi?cant coef?cient appears in the TFP regression. Here, it takes
the positive value of 0.1663 and is signi?cant at the 1 percent level. This indicates that
the effect of listing was to improve the productivity of public sector banks and as
before this effect appears to dominate the magnitude of divesture. The results for the
control variables are similar to those obtained in the previous estimations in Table VI.
6. Endogeneity of partial privatization
In the previous section, we have estimated a variety of regressions to examine the impact
of partial privatization on bank performance. However, it could be argued that the
improvements inperformance suggestedbyour results were not the result of privatization
but because the better performing banks were the ones to undergo divestment. In other
words there could have been a selectionbias inidentifying which banks to privatize which
in econometric terms would amount to endogeneity of our partial privatization variables.
In this section we re-examine our results while controlling for potential selection bias.
In order to do that, we start by re-estimating the partial privatization regressions but now
consider only those banks that were partially privatized (Tables VIII and IX). Thus, these
regressions are similar to the “before and after” privatization analyses that are often found
Partial
privatization
and performance
293
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
0
.
0
0
0
2
(
0
.
0
0
0
4
)
0
.
0
1
7
9
*
*
*
(
0
.
0
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3
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)
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0
0
9
5
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(
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)
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(
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)
2
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(
0
.
0
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)
L
I
S
T
_
T
R
E
N
D
0
.
0
1
9
4
*
*
*
(
0
.
0
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2
0
)
2
0
.
0
5
2
9
(
0
.
0
4
4
4
)
2
0
.
0
2
5
4
(
0
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1
8
2
)
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2
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(
0
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0
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7
3
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(
0
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0
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9
)
P
R
O
P
_
R
U
R
0
.
6
2
5
9
*
*
*
(
0
.
0
8
5
4
)
0
.
0
4
2
4
(
0
.
5
6
8
8
)
2
0
.
0
5
3
4
(
0
.
2
8
6
2
)
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.
9
9
6
8
*
*
*
(
0
.
2
2
4
3
)
1
.
3
4
2
6
*
*
*
(
0
.
1
7
5
0
)
P
R
O
P
_
N
I
N
T
0
.
0
1
3
8
(
0
.
0
2
3
6
)
2
0
.
0
5
4
7
(
0
.
1
4
2
3
)
2
7
.
9
4
2
1
*
*
*
(
0
.
4
6
6
8
)
0
.
9
4
4
9
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*
*
(
0
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3
1
8
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)
0
.
8
4
7
5
*
*
*
(
0
.
2
3
8
3
)
S
I
Z
E
2
0
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0
1
5
4
*
*
*
(
0
.
0
0
4
1
)
2
0
.
0
2
5
0
(
0
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0
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0
6
)
2
0
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2
4
6
3
*
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(
0
.
0
5
6
0
)
2
0
.
1
6
4
3
*
*
*
(
0
.
0
4
2
5
)
2
0
.
1
0
5
2
*
*
*
(
0
.
0
3
2
7
)
I
N
T
E
R
C
E
P
T
4
.
5
0
9
0
*
*
*
(
0
.
0
3
9
1
)
0
.
2
2
9
8
(
0
.
3
8
9
0
)
3
.
6
4
8
4
*
*
*
(
0
.
2
4
4
9
)
2
.
8
6
9
6
*
*
*
(
0
.
2
4
3
3
)
1
.
6
0
8
5
*
*
*
(
0
.
2
0
0
9
)
R
2
0
.
4
2
6
6
0
.
0
3
6
5
0
.
4
7
9
7
0
.
2
0
8
3
0
.
2
1
4
3
N
o
.
o
f
o
b
s
.
2
3
4
2
3
4
2
3
4
2
3
4
2
3
4
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
v
a
r
i
a
b
l
e
t
h
a
t
o
p
e
r
a
t
e
s
a
s
a
t
r
e
n
d
o
n
c
e
a
b
a
n
k
i
s
l
i
s
t
e
d
(
L
I
S
T
_
T
R
E
N
D
)
.
T
h
e
s
a
m
p
l
e
f
o
r
t
h
i
s
e
s
t
i
m
a
t
i
o
n
c
o
n
s
i
s
t
s
o
f
o
n
l
y
t
h
o
s
e
b
a
n
k
s
t
h
a
t
w
e
n
t
o
n
t
o
b
e
p
a
r
t
i
a
l
l
y
p
r
i
v
a
t
i
z
e
d
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table VIII.
Partial privatization and
bank performance (only
partially privatized
banks): roles of listing
trend and ownership
share
JFEP
2,4
294
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
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Table IX.
Partial privatization and
bank performance (only
partially privatized
banks): roles of listing
effect and ownership
share
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in this literature. We ?nd that all the results from these regressions are qualitatively
similar to our earlier results obtained using the full sample.
In addition to the above regressions, we employ a variety of other techniques to
control for potential selection bias. First, we compare the performance of the partially
privatized banks and the non-privatized banks using the t-test for difference in means
and the Wilcoxon Z-test for difference in medians (Appendix Table AII). The data for
the partially privatized banks in these tests are restricted only to the pre-privatization
years. The results indicate that while the partially privatized banks had lower SER, the
non-privatized banks had higher productivity. In terms of the rest of the performance
measures there does not seem to have been any statistically signi?cant difference
between the two groups. As a result, we can infer that there is no indication of selection
bias in the partial privatization programme.
Second, we employ the technique of instrumental variable estimation to control for the
potential endogeneity of the partial privatization process. We use lags of OPR, NIM, OCR
and SER as instruments for PRIV_SHARE in the TFP regression. Similarly for each
regression we use the lags of the other performance measures as instruments. From the
results we observe that even after allowing for endogeneity of PRIV_SHARE our ?nding
that greater private share in ownership is associated with better performance continues to
hold (Appendix Table AIII). The statistically signi?cant coef?cients of PRIV_SHARE in
the OPR and SER regressions suggest that greater divesture led to improved pro?tability
as well as lower costs. Next, we employ an alternative method for estimating instrumental
variables through a two-stage procedure. First the decision to privatize is estimated as a
probability (by regressing LIST_DUM on a set of instruments) which is then used to
compute ?tted values of privatization share. This is then used as the instrumental variable
in the panel data regression. Other than the lagged performance variables, ?scal de?cit
and a stock exchange index (the Bombay Stock Exchange Sensitive Index) are used as
instruments in this set of estimations. The results are presented in Table AIV. The
coef?cients of PRIV_SHARE in the OPR and SER regressions (0.0620 and 20.0482,
respectively) are statistically signi?cant at conventional levels as before. This shows that
evenafter controllingfor endogeneityusingthe two-stage procedure, we ?ndthat partially
privatized banks experience improvements in pro?tability and ef?ciency.
Finally, we address the issue of endogeneity in an alternative fashion. Following
Bartel and Harrison (2005), we use placebo leads for the share of partial privatization
variable in order to control for any endogeneity present in this variable. We do this by
adding a lead of PRIV_SHARE to the above estimated regressions (Appendix
Table AV). We ?nd that the lead variable is statistically insigni?cant in all but one case
and our original result regarding the positive and statistically signi?cant association
between productivity and partial privatization remains robust. The only exception is the
OPR regression where privatization may have been preceded by higher pro?tability.
However, in view of the results from all the alternative tests we have conducted, on
balance we conclude that our main results are not affected by endogeneity problems.
7. Conclusion
The partial privatization programme in Indian banking since the early nineties
was undertaken to improve the performance of public banks. While there have been
a number of studies on bank performance in India, none so far have looked at the
relationship between performance and partial privatization (other than examining
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the mean differences in performance as in Mohan (2005) and Sathye (2005)). Partial
privatization refers to the government divesting stakes in the public ?rm without
relinquishing management control. Given political opposition to outright privatization,
this has emerged as a feasible alternative for achieving some bene?ts of privatization.
However, the implications of partial privatization for performance are not very clear in
policy debates as well as in the privatization literature.
In this context, the present paper employs the method of stochastic frontier analysis
to study performance in Indian banking over a long time horizon of eighteen years that
encompasses the government’s partial privatization programme. We estimate TFP
from a stochastic cost frontier and employ it as a measure of bank performance.
In addition to TFP we employ four accounting indicators as alternative measures of
performance. Using these ?ve measures of performance, we study the impact of partial
privatization on bank performance through panel regression models.
The results may be summarized as follows. Public banks in India have exhibited
improving performance during the period 1986-2003. A part of this improvement in
performance can be attributed to partial privatization. We ?nd that on an average, listed
banks have signi?cantly outperformed unlisted banks. This result corroborates the ?ndings
of Sarkar et al. (1998) who foundthat listedprivate banks inIndia outperformunlistedprivate
banks, which in turn perform better than public banks. Here, we have obtained a similar
listing effect for public banks. Moreover, we ?nd that the effect of listing on performance is
not a temporary phenomenon and is in fact persistent beyond the year of listing. Thus,
performance of partiallyprivatizedbanks continues toimprove further after listing. Bhaumik
and Dimova (2004) had noted a recent narrowing of the performance gap between public and
private banks in India. Therefore, our results can be construed to suggest that the narrowing
of the performance gap can be partly attributed to partial privatization of public banks. Our
results also suggest that the extent to which government reduced its stakes in the public
banks hada direct signi?cant impact onthe banks’ performance. Thus, higher is the extent of
privatization better is the performance. These results support the managerial view of
Holmstromand Tirole (1993) which suggests that even if the government partially privatizes
state-owned ?rms, the forces of market discipline and consequent managerial incentives
would be suf?cient to bring about an improvement in performance. Our results are also
con?rm the ?ndings of Mohan (2005) and Sathye (2005) who ?nd improved performance of
partially privatized banks by examining difference of means.
We control for potential endogeneity of partial privatization in a number of
alternative ways. First we estimate the partial privatization regressions only for those
banks that were eventually partially privatized. Next we compare the performance of
the partially privatized banks with the rest of the banks. Then we use instrumental
variables to allow for potential endogeneity in partial privatization. Finally, we use
placebo leads to account for the endogeneity. Based on our results, we conclude that
even after accounting for endogeneity our results remain robust.
Governments across the globe have at various times taken recourse to privatizing
state-owned ?rms for the purpose of revenue generation as well as for achieving
increase in ef?ciency and competition. While in most developed countries this has
taken the form of outright sale to private bidders (e.g. privatization in the UK in the
1980s), the political and social idiosyncrasies of developing countries might not permit
such type of privatization. There is often strong political opposition to what is viewed
as “selling the family silver”. Even the government of the day may not be willing to let
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go of control over state-owned ?rms especially in an industry like banking which has
traditionally been a tool for achieving developmental goals. In such instances partial
privatization may be the only viable option as in the case of India’s public sector banks.
The ?ndings of this paper suggest that the post-privatization success of the partial
privatization programme in India is clearly evidenced by improvements in
performance. Our results add to the existing body of evidence on privatization by
providing insights into the partial privatization in the banking industry of an emerging
economy. We document that even when politicians might continue to exert some
control over privatized banks, market pressures can reshape managerial incentives
leading to increase in productivity, pro?tability and ef?ciency.
Notes
1. Was the ?rst year of partial privatization in Indian banking. Therefore, the time period
1986-2003 offers us a suitable sample period for a before and after comparison. We have eight
years data (1986-1993) before the partial privatization programme began and ten years data
after (1994-2003).
2. The disclosure guidelines are available on the regulator’s web site at: www.sebi.gov.in/
guide/dip2009.pdf
3. The subscript i which stands for individual banks, and the subscript t which stands for years
were omitted from equation (2) earlier to preserve clarity of notations. Also, the random
variables are now speci?ed in lowercase to refer to the error terms for individual banks.
4. Establishment expenses refer to the wage bill for of?cers, clerks and other support staff.
As wages are jointly bargained by the bank employees association in India, we do not expect
the endogeneity of wages to be a serious problem in estimating the cost function.
5. We may also note that all estimations with the inclusion of branches yield higher values of
the log likelihood function as compared with the case when branches are dropped.
6. Kumbhakar and Sarkar (2003) argue against clubbing the three categories of deposits
together. We too feel that since bank policies regarding each category are different and the
ratio of these three categories has been varying over time, it is important to treat them as
separate variables in the cost function.
7. The starting year is chosen as 1986 to coincide with the shift of the bank accounting system
in India from that based on calendar year to ?nancial year. Starting with 1986, the ?nancial
year covers the period from April of one year to March of the following year. Thus, the
?nancial year 1986 covers the period from April 1985 to March 1986.
8. While this result is consistent with Mohan (2005) it appears to contradict the ?ndings of
Kumbhakar and Sarkar (2003). However, the latter used a sample till 1997 whereas we
consider six additional years during which public sector banks considerably outperformed
private banks in terms of TFP (Figure 1).
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Sarkar, S., Sarkar, J. and Bhaumik, S.K. (1998), “Does ownership always matter? Evidence from
the banking industry”, Journal of Comparative Economics, Vol. 26 No. 2, pp. 262-81.
Sathye, M. (2005), “Privatization, performance, and ef?ciency: a study of Indian banks”, Vikalpa:
The Journal for Decision Makers, Vol. 30 No. 1, pp. 7-16.
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depository ?nancial institutions”, Journal of Finance, Vol. 32 No. 4, pp. 1251-66.
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and foreign banks in India”, Economic Modelling, Vol. 23 No. 4, pp. 717-35.
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No. 2, pp. 737-83.
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enterprise”, Public Choice, Vol. 73 No. 2, pp. 205-39.
Wooldridge, J.M. (2002), Econometric Analysis of Cross Section and Panel Data, The MIT Press,
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Further reading
Indian Banks’ Association (1985-1986 to 1994-1995), Financial Analysis of Banks, Indian Banks’
Association, Mumbai, various issues.
Indian Banks’ Association (1995-1996 to 2002-2003), Performance Highlights of Banks,
Indian Banks’ Association, Mumbai, various issues.
RBI (1994-1995 to 2002-2003), Report on Trends and Progress of Banking in India, Reserve Bank
of India, Mumbai, various issues.
About the authors
Subrata Sarkar has a PhD in Economics from the University of Southern California (USC). He has
worked for the RAND Corporation and taught at the USC before joining IGIDR, Mumbai where
he is currently a Professor. His research interests are in the areas of applied econometrics,
corporate ?nance and productivity studies. He has published in journals such as the Journal of
Money, Credit and Banking, Journal of Economics and Management Strategy, Journal of
Comparative Economics and Review of Development Economics.
Rudra Sensarma has a PhD in Economics from IGIDR, Mumbai. He has worked at the
University of Birmingham, the Indian Institute of Management and the Reserve Bank of India
before joining the University of Hertfordshire, UK where he is currently a Senior Lecturer. His
research interests are in ?nancial economics, banking and applied econometrics. His work has
appeared in journals such as the Journal of Economics, Applied Economics, Economic Modelling
and the Journal of Policy Modeling. Rudra Sensarma is the corresponding author and can be
contacted at: [email protected]
JFEP
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300
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D
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A
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1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Appendix 1
Following Kumbhakar and Lovell (2000), the Divisia index of TFP growth for multiple outputs
can be written as:
TF
_
P ¼
_
Y 2
_
X ¼
m
X
R
m
_ y
m
2
j
X
S
j
_ x
j
ðA:1Þ
where, R
m
¼ p
m
y
m
/R is the observed revenue share of output y
m
, p
m
is the price of output y
m
and
R ¼ S
m
p
m
y
m
is total revenue. Likewse, S
j
¼ w
j
x
j
/C is the observed cost share of input x
j
, w
j
is
the price of input x
j
, and C ¼ S
j
w
j
x
j
is total cost. Here a “.” over a variable indicates its growth
rate, i.e. _ x
j
¼ › ln x
j
=›t.
Equation (A.1) is hard to estimate especially in the case of banks due to unavailability of price
information and so it needs to be transformed into an estimable form. Consequently, we consider
the following stochastic cost frontier:
ln E ¼ ln C ðY; W; tÞ þ U þ V ðA:2Þ
where, E ¼ WX is total expenditure, X ¼ (x
1
, . . . ,x
N
)’ is a (N £ 1) vector of inputs,
W ¼ (w
1
, . . . ,w
N)’
is a (N £ 1) vector of input prices, Y ¼ (y
1
, . . . ,y
M
)’ is a (M £ 1) vector of
outputs, t is a time trend that proxies technical change, C(Y, W, t) is the deterministic kernel of
the stochastic cost frontier, U $ 0 is the one-sided cost inef?ciency term, and V is a random
variable with zero mean.
Totally differentiating equation (A.2), we obtain the following expression:
_
E ¼ 1ðY; W; tÞ
m
X
R
m
_ y
m
þ
n
X
S
n
_ w
n
þ
_
CðY; W; tÞ þ
›U
›t
Solving this for
m
P
R
m
_ y
m
, substituting it in equation (A.1) and using the fact that
_
E 2
n
P
ðw
n
x
n
=EÞ_ x
n
¼
n
P
ðw
n
x
n
=EÞ _ w
n
, leads to the following expression:
T
_
FP ¼ 2
_
CðY; W; tÞ þ ½1 21ðY; W; tÞ?
_
Y
C
2
n
X
½S
n
2S
n
ðY; W; tÞ? _ w
n
þ ðY 2
_
Y
C
Þ 2
›U
›t
where
_
Y ¼
m
P
1
m
ðY; W; tÞ=1ðY; W; tÞ is a measure of output growth, 1
m
ðY; W; tÞ is cost
elasticity of the mth output and 1ðY; W; tÞ ¼
m
P
1
m
ðY; W; tÞ. Here ð_ y 2 _ y
C
Þ captures the impact
on productivity change of departures from marginal cost pricing and along with
n
P
½S
n
2S
n
ðY; W; tÞ? _ w
n
, gives a measure of input allocative ef?ciency change. Assuming
allocative ef?ciency yields the following estimable expression for TFP growth:
TF
_
P ¼ 2
_
CðY; W; tÞ þ ½1 21ðY; W; tÞ?
_
Y
c
2
›U
›t
ðA:3Þ
De?ning returns to scale as the inverse of 1ðY; W; tÞ, expression (A.3) provides a
decomposition of TFP into the following components: contribution of technical change
measured by cost diminution (2
_
CðY; W; tÞ), contribution of scale effect (½1 21ðY; W; tÞ?
_
Y
c
),
and contribution of ef?ciency (2›U=›t). Denoting these three components by TF
_
P
1
, TF
_
P
2
and TF
_
P
3
respectively, we can de?ne TFP growth as a sum of its three components:
TF
_
P ¼ TF
_
P
1
þ TF
_
P
2
þ TF
_
P
3
Partial
privatization
and performance
301
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P
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:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Appendix 2
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r
a
b
a
n
k
i
s
l
i
s
t
e
d
o
r
n
o
t
P
R
I
V
_
S
E
C
T
O
R
A
d
u
m
m
y
v
a
r
i
a
b
l
e
f
o
r
b
a
n
k
s
i
n
t
h
e
p
r
i
v
a
t
e
s
e
c
t
o
r
N
o
t
e
:
T
h
i
s
t
a
b
l
e
d
e
?
n
e
s
a
l
l
t
h
e
v
a
r
i
a
b
l
e
s
u
s
e
d
i
n
t
h
i
s
s
t
u
d
y
Table AI.
Description of variables
JFEP
2,4
302
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
M
e
a
n
o
f
n
e
v
e
r
P
P
b
a
n
k
s
(
M
e
d
i
a
n
o
f
n
e
v
e
r
P
P
b
a
n
k
s
)
M
e
a
n
o
f
P
P
b
a
n
k
s
(
M
e
d
i
a
n
o
f
P
P
b
a
n
k
s
)
t
-
s
t
a
t
s
f
o
r
d
i
f
f
e
r
e
n
c
e
i
n
m
e
a
n
(
p
-
v
a
l
u
e
)
W
i
l
c
o
x
o
n
–
Z
f
o
r
d
i
f
f
e
r
e
n
c
e
i
n
m
e
d
i
a
n
(
p
-
v
a
l
u
e
)
L
o
g
(
T
F
P
)
4
.
8
6
0
7
(
4
.
7
7
8
6
)
4
.
7
3
1
6
(
4
.
6
9
7
8
)
5
.
7
2
(
,
0
.
0
0
0
1
)
2
3
.
0
2
5
7
(
0
.
0
0
1
2
)
O
P
R
2
0
.
1
0
2
5
(
0
.
1
5
0
0
)
0
.
0
0
3
6
(
0
.
1
7
0
0
)
2
0
.
8
2
(
0
.
4
1
2
7
)
1
.
1
6
3
8
(
0
.
1
2
2
2
)
N
I
M
2
.
5
1
1
3
(
2
.
5
2
5
0
)
2
.
3
6
8
9
(
2
.
4
2
0
0
)
1
.
5
8
(
0
.
1
1
4
8
)
2
1
.
1
1
8
2
(
0
.
1
3
1
7
)
O
C
R
2
.
7
7
2
4
(
2
.
7
2
5
0
)
2
.
7
0
6
8
(
2
.
7
2
0
0
)
1
.
3
4
(
0
.
1
8
0
4
)
2
0
.
1
8
6
4
(
0
.
4
2
6
0
)
S
E
R
2
.
1
3
4
4
(
2
.
0
1
5
0
)
1
.
9
0
5
2
(
1
.
9
1
0
0
)
1
.
7
9
(
0
.
0
7
4
3
)
2
2
.
8
2
5
4
(
0
.
0
0
2
4
)
N
o
t
e
:
T
h
i
s
t
a
b
l
e
p
r
e
s
e
n
t
s
s
t
a
t
i
s
t
i
c
a
l
t
e
s
t
s
o
f
d
i
f
f
e
r
e
n
c
e
s
b
e
t
w
e
e
n
p
u
b
l
i
c
b
a
n
k
s
t
h
a
t
w
e
r
e
n
e
v
e
r
p
r
i
v
a
t
i
z
e
d
a
n
d
t
h
o
s
e
t
h
a
t
w
e
n
t
o
n
t
o
b
e
p
a
r
t
i
a
l
l
y
p
r
i
v
a
t
i
z
e
d
b
a
s
e
d
o
n
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
Table AII.
Performance
comparisons of
non-privatized banks and
partially privatized (PP)
banks but considered
only before the listing
year
Partial
privatization
and performance
303
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
2
0
.
0
0
1
0
(
0
.
0
0
2
5
)
0
.
1
1
4
5
*
*
*
(
0
.
0
3
7
7
)
0
.
0
9
4
0
(
0
.
0
8
2
3
)
2
0
.
2
3
1
8
(
0
.
1
5
0
4
)
2
0
.
1
2
9
1
*
*
*
(
0
.
0
4
0
9
)
P
R
I
V
_
S
E
C
T
O
R
2
0
.
1
0
2
6
*
*
*
(
0
.
0
1
8
7
)
0
.
6
8
9
3
*
*
*
(
0
.
1
9
9
1
)
2
0
.
4
6
4
5
*
(
0
.
2
3
8
3
)
2
0
.
2
9
2
5
(
0
.
4
2
6
7
)
2
0
.
7
2
6
5
*
*
*
(
0
.
1
1
1
4
)
P
R
O
P
_
R
U
R
0
.
0
8
4
3
*
(
0
.
0
4
4
7
)
0
.
5
8
8
4
(
0
.
5
5
7
8
)
1
.
5
1
9
4
*
*
*
(
0
.
2
0
0
6
)
1
.
3
3
0
0
*
*
(
0
.
5
3
6
4
)
1
.
6
6
6
4
*
*
*
(
0
.
2
4
9
1
)
P
R
O
P
_
N
I
N
T
2
0
.
0
0
0
1
(
,
0
.
0
0
0
1
)
0
.
0
0
0
7
*
(
0
.
0
0
0
3
)
2
0
.
0
0
2
2
*
*
*
(
0
.
0
0
0
4
)
2
0
.
0
0
3
5
*
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
4
*
*
*
(
0
.
0
0
0
2
)
S
I
Z
E
2
0
.
0
0
8
7
*
*
(
0
.
0
0
3
9
)
0
.
0
5
5
3
(
0
.
0
5
1
7
)
2
0
.
3
8
9
7
*
*
*
(
0
.
0
9
7
0
)
2
0
.
2
2
6
8
(
0
.
1
6
9
3
)
2
0
.
3
1
6
2
*
*
*
(
0
.
0
2
2
3
)
I
N
T
E
R
C
E
P
T
4
.
8
4
6
6
*
*
*
(
0
.
0
2
6
1
)
2
0
.
9
5
2
6
*
(
0
.
4
5
0
5
)
3
.
0
3
1
2
*
*
*
(
0
.
6
6
4
4
)
3
.
5
8
5
1
*
*
*
(
0
.
2
5
4
5
)
2
.
7
4
4
7
*
*
*
(
0
.
1
4
0
1
)
R
2
0
.
1
5
0
9
0
.
0
6
2
4
0
.
0
8
7
4
0
.
0
3
0
7
0
.
1
3
3
2
N
o
.
o
f
o
b
s
.
8
2
1
8
2
1
8
2
1
8
2
1
8
2
1
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
i
n
s
t
r
u
m
e
n
t
v
a
l
i
d
i
t
y
w
a
s
a
s
c
e
r
t
a
i
n
e
d
b
y
c
h
e
c
k
i
n
g
t
h
a
t
t
h
e
i
n
s
t
r
u
m
e
n
t
s
a
r
e
h
i
g
h
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
P
R
I
V
_
S
H
A
R
E
b
u
t
w
e
a
k
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
t
h
e
r
e
s
i
d
u
a
l
s
.
N
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
–
w
h
i
c
h
f
o
r
e
a
c
h
r
e
g
r
e
s
s
i
o
n
i
s
i
n
s
t
r
u
m
e
n
t
e
d
u
s
i
n
g
l
a
g
s
o
f
o
t
h
e
r
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
,
?
s
c
a
l
d
e
?
c
i
t
a
n
d
s
t
o
c
k
m
a
r
k
e
t
i
n
d
e
x
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table AIII.
Partial privatization and
bank performance:
instrumental variables
(1987-2003)
JFEP
2,4
304
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
0
.
0
0
4
8
(
0
.
0
0
4
7
)
0
.
0
6
2
0
*
*
*
(
0
.
0
2
1
4
)
0
.
0
7
7
1
*
(
0
.
0
4
5
0
)
2
0
.
1
3
7
6
(
0
.
0
9
2
8
)
2
0
.
0
4
8
2
*
(
0
.
0
2
4
8
)
P
R
I
V
_
S
E
C
T
O
R
2
0
.
0
0
4
7
*
*
*
(
0
.
0
2
0
7
)
0
.
7
1
0
5
*
*
*
(
0
.
2
0
9
6
)
2
0
.
3
7
8
2
*
(
0
.
2
0
2
2
)
2
0
.
2
6
7
3
(
0
.
4
6
3
2
)
2
0
.
6
7
7
9
*
*
*
(
0
.
1
1
2
1
)
P
R
O
P
_
R
U
R
0
.
0
9
9
4
*
(
0
.
0
4
8
6
)
0
.
6
4
0
7
(
0
.
5
8
1
5
)
1
.
7
6
4
9
*
*
*
(
0
.
2
7
8
1
)
1
.
3
6
1
5
*
*
(
0
.
5
2
7
7
)
1
.
8
6
2
9
*
*
*
(
0
.
2
9
1
1
)
P
R
O
P
_
N
I
N
T
2
0
.
0
0
0
1
*
(
,
0
.
0
0
0
1
)
0
.
0
0
0
7
*
(
0
.
0
0
0
3
)
2
0
.
0
0
2
3
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
5
*
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
5
*
*
*
(
0
.
0
0
0
3
)
S
I
Z
E
2
0
.
0
1
0
8
*
*
(
0
.
0
0
4
0
)
0
.
0
6
3
4
(
0
.
0
5
3
9
)
2
0
.
3
4
2
1
*
*
*
(
0
.
0
7
9
8
)
2
0
.
2
1
9
2
(
0
.
1
7
7
7
)
2
0
.
2
9
0
0
*
*
*
(
0
.
0
2
7
1
)
I
N
T
E
R
C
E
P
T
4
.
8
4
3
2
*
*
(
0
.
0
3
1
8
)
2
0
.
8
6
2
6
*
(
0
.
4
5
1
9
)
2
.
6
8
0
1
*
*
*
(
0
.
3
2
8
8
)
3
.
2
7
2
9
*
*
*
(
0
.
3
7
9
4
)
2
.
2
3
9
0
*
*
*
(
0
.
1
1
6
6
)
R
2
0
.
8
1
0
1
0
.
1
7
2
2
0
.
1
3
3
9
0
.
0
5
2
1
0
.
1
7
4
4
F
t
e
s
t
f
o
r
n
o
?
x
e
d
e
f
f
e
c
t
s
1
1
1
.
9
4
*
*
*
4
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Table AIV.
Partial privatization and
bank performance:
instrumental variables
with two stage estimation
(1987-2003)
Partial
privatization
and performance
305
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Table AV.
Partial privatization and
bank performance:
placebo leads (1986-2002)
JFEP
2,4
306
D
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This article has been cited by:
1. Dhananjay Bapat, Deepa Mazumdar. 2015. Assessment of business strategy: implication for Indian banks.
Journal of Strategy and Management 8:4, 306-325. [Abstract] [Full Text] [PDF]
2. Mohammad Alipour. 2013. Has privatization of state-owned enterprises in Iran led to improved
performance?. International Journal of Commerce and Management 23:4, 281-305. [Abstract] [Full Text]
[PDF]
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doc_274023951.pdf
The purpose of this paper is to examine the impact of partial privatization on performance
of state-owned banks using data from the Indian banking industry during the period 1986-2003, and
test the hypothesis that privatization leads to improvement in performance even when the government
retains controlling stakes
Journal of Financial Economic Policy
Partial privatization and bank performance: evidence from India
Subrata Sarkar Rudra Sensarma
Article information:
To cite this document:
Subrata Sarkar Rudra Sensarma, (2010),"Partial privatization and bank performance: evidence from India",
J ournal of Financial Economic Policy, Vol. 2 Iss 4 pp. 276 - 306
Permanent link to this document:http://dx.doi.org/10.1108/17576381011100838
Downloaded on: 24 January 2016, At: 21:39 (PT)
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of Financial Economic Policy, Vol. 2 Iss 4 pp. 326-345http://dx.doi.org/10.1108/17576381011100856
Mohammad Alipour, (2013),"Has privatization of state-owned enterprises in Iran led to improved
performance?", International J ournal of Commerce and Management, Vol. 23 Iss 4 pp. 281-305 http://
dx.doi.org/10.1108/IJ CoMA-03-2012-0019
Mauricio J ara-Bertin, J osé Arias Moya, Arturo Rodríguez Perales, (2014),"Determinants of bank
performance: evidence for Latin America", Academia Revista Latinoamericana de Administración, Vol. 27
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D
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Partial privatization and bank
performance: evidence from India
Subrata Sarkar
Indira Gandhi Institute of Development Research, Mumbai, India, and
Rudra Sensarma
University of Hertfordshire Business School, Hat?eld, UK
Abstract
Purpose – The purpose of this paper is to examine the impact of partial privatization on performance
of state-owned banks using data from the Indian banking industry during the period 1986-2003, and
test the hypothesis that privatization leads to improvement in performance even when the government
retains controlling stakes.
Design/methodology/approach – Employing the technique of stochastic frontier analysis,
bank-speci?c estimates of total factor productivity were obtained, because they can be considered
as a measure of performance, along with four accounting measures. Panel regression models were
employed to assess the impact of partial privatization on these performance indicators.
Findings – Partial privatization was found to result in signi?cant improvement in performance of
state-owned banks. This ?nding is robust to alternative model speci?cations and different techniques
for controlling potential selection bias.
Research limitations/implications – The paper focuses on the impact of partial privatization on
operational and ?nancial performance of banks. Future work could consider the effects on other
aspects such as wages and ?nancial development.
Practical implications – The results suggest that faced with political opposition to full
privatization, even if the government does not relinquish control, the exposure to market discipline
through partial privatization may be an effective way of improving performance of state-owned banks.
Originality/value – This is the ?rst work to examine the effects of partial privatization in the
context of Indian banks and one of the very few to study this issue for any banking industry.
Keywords India, Banks, Privatization, Stochastic processes, Organizational performance
Paper type Research paper
1. Introduction
Several studies have empirically examined the effect of privatization on ?rm
performance. Studies have concentrated on various aspects of this issue such as the
mode and extent of privatization, sources of public sector inef?ciency, measures of ?rm
performance and the various econometric issues therein. However, the evidence on
whether privatization leads to improvement in performance is mixed. A survey by
Vining and Boardman (1992) found that out of 87 papers considered only 28 reported
performance improvement after privatization. Even when privatization does work it is
not clear whether it is a feasible approach in many contexts. For instance, political
opposition to privatization may prevent outright sale of state-owned enterprises. Faced
with such political hurdles, governments may often resort to partial privatization as an
alternative.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
The authors are grateful to two anonymous referees for useful comments. The usual disclaimer
applies.
JFEP
2,4
276
Journal of Financial Economic Policy
Vol. 2 No. 4, 2010
pp. 276-306
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381011100838
D
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Partial privatizationmay lead to improvements in ?rmperformance if the managerial
viewof privatization holds. This viewemphasizes the monitoring and disciplining roles
of stock markets and the consequent bene?ts of improved managerial incentives even
when the privatization is only partial (Holmstromand Tirole, 1993). On the other hand a
political view of privatization opines that there may not be any performance gains from
partial privatization if the government retains control of the ?rms after privatization. In
such a situation political interference would continue to hamper the performance of
state-owned ?rms and the privatization would not yield any bene?ts (Shleifer and
Vishny, 1997). Which of these two effects would ultimately dominate in the case of
partially privatized ?rms is not clear from the theoretical literature. There are other
bene?ts of privatization such as improved access to external resources as creditors
might perceive a privatized ?rm to be more credit-worthy than a state-owned ?rm that
would receive political protection in case it defaults. Privatized ?rms would in general
face lower costs of raising funds and are expected to potentially bene?t from foreign
direct investment and associated transfer of technology.
According to Gupta (2005), most studies on ownership and performance that ?nd
performance of ?rms improving after privatization consider cases where management
control is transferred to private owners, but not much is known about the effectiveness
of partial privatization. We attempt to examine this issue in the context of Indian
banks, which have undergone a programme of partial privatization since the launch of
banking reforms in the early 1990s. Indian banking offers a unique case study as it is
characterized by the presence of public sector banks (i.e. fully state-owned as well as
partially privatized banks) and private sector banks (domestic and foreign) thus
covering the entire range of ownership types. Most studies have found that banks in
India exhibited improvement in performance over the last two decades (Kumbhakar
and Sarkar, 2003; Sensarma, 2006). This has been attributed to the economic reforms of
1991, which engendered a series of measures such as interest rate deregulation and
branch de-licensing. While the private banks outperformed the public sector banks in
the earlier years, in recent years the latter have been able to bridge the gap by taking
advantage of the deregulatory measures (Bhaumik and Dimova, 2004; Sensarma,
2006). However, the public sector banks have been considered as a single group in
these studies and no distinction was made between those banks that were partially
privatized and those that remained fully state-owned.
India is an emerging economy where a shift from government control to a more
liberalized economy in the 1990s meant that private participation in the economy has
become signi?cant. On the other hand, because of its vibrant democracy a strong
political opposition exists that has prevented full privatization of many state-owned
enterprises. This is especially true for state-owned banks due to their underlying social
objectives, which are perceived by the political opposition to be under threat if the banks
were to be privatized. Owing to the political opposition to bank privatization, India has
followed a piecemeal approach where the government has been relinquishing some of its
stakes in one or a few banks every year. We study this partial privatization programme
by examining bank performance over a long period of 1986-2003[1] which allows us to
evaluate whether the managerial view or the political view has dominated in the case of
Indian banks. In particular, we are able to separately examine the roles of listing on the
stock exchange and the magnitude of privatization. The very act of listing a state-owned
bank on the stock exchange can generate market discipline as the Indian stock market
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regulator imposes strict disclosure norms on all listed entities. On the other hand the
degree of divesture could in?uence the performance of banks as it proxies the extent of
monitoring and disciplining the bank is subjected to by private shareholders.
Measurement of bank performance is a contentious issue in itself and there is an
ongoing debate over what is a good measure. The productivity literature suggests that
total factor productivity (TFP) can be a useful measure of performance as it is not
in?uenced byaccounting practices. This is a popular approachin banking as TFPcan be
computed based on the cost function and it is often argued that cost based measures are
more appropriate for analyzing public sector units which may be more concerned with
cost minimization rather than pro?t maximization (Kumbhakar and Sarkar, 2003).
We assume that banks minimize costs by choosing the output level and therefore we
adopt a cost based indicator of productivity de?ned using the Divisia index. In addition,
we employ a host of accounting indicators of pro?tability and ef?ciency of banks. These
indicators are justi?ed on the grounds that one of the stated goals of banking sector
reforms in India was to achieve improvement in pro?tability and ef?ciency. We study a
total of four accounting indicators of pro?tability and ef?ciency to complement the
Divisia index of TFP in our analysis of partial privatization.
Analyzing data over the period 1986-2003, we ?nd that partial privatization led to an
improvement in performance of Indian state-owned banks with the effect being more
persistent for TFP than for accounting indicators. On an average, partially privatized
banks experienced an increase of 3 and 4 percent in TFP growth. These ?ndings are
robust to many alternative model speci?cations and controls for potential selection bias.
The rest of this paper is organized as follows. Section 2 provides a review of the
relevant empirical literature. Section 3 presents a brief overview of the banking sector
in India and the partial privatization programme. Section 4 discusses the data and the
methodology employed. Section 5 contains the main empirical ?ndings and their
discussion. Section 6 highlights the robustness of the ?ndings to alternative ways of
accounting for potential endogeneity and Section 7 concludes the paper.
2. Literature review
The empirical literature on privatization has found signi?cant performance gains from
privatizing former state-owned ?rms. Boardman and Vining (1989) examined the
performance of large non-US corporations in 1983 to conclude that private ?rms are more
ef?cient than their public counterparts. Megginson et al. (1994) and D’Souza and
Megginson (1999) compared pre- and post-privatization performance of a large number of
?rms from industrialized as well as developing countries to show that privatization
resulted in signi?cant gains in pro?tability, sales and ef?ciency. Inthe context of transition
economies, Frydman et al. (1999) studied 200 ?rms fromthe Czech Republic, Hungary and
Poland to show that for state-owned ?rms that are sold to outsiders (i.e. not managers or
employees), privatizationyields signi?cant improvement in performance. Furthermore, the
performance gains appear to be interms of revenue enhancements rather thancost savings.
However, the empirical literature speci?c to the banking industry does not provide
unanimous evidence on the question of whether privatization helps to improve
performance. Megginson (2005) provides an excellent survey of the empirical literature on
bank privatization. Based on a review of a large number of studies he concludes that
private banks are usually more ef?cient than state-owned banks. However, in case of
partial privatization, the effects on performance depend on institutional and regulatory
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environments. Bonin et al. (2005) studied cost and pro?t ef?ciency of 59 banks from six
advanced transition countries and provide evidence in support of privatization. The
analysis revealedthat banks that are soldto a strategic foreignowner earlyinthe periodof
the privatization programme exhibit better performance than state-owned banks and
those banks that are privatized later. Boubakri et al. (2005) analyzed the privatization
experience of 81 banks from22 developing countries. Analysis of accounting indicators of
performance revealed that the poor performers were selected for privatization and the
impact of privatization on performance was ambiguous. While pro?tability increased,
the impact on ef?ciency, risk exposure and capitalization largelydependedonwhether the
control of the privatized bank rested with the government, foreign investors, local
industrial groups or individuals.
To cite some country speci?c studies, Nakane and Weintraub (2005) estimated TFPfor
242 Brazilian banks and concludedthat state-ownedbanks were less productive thantheir
private counterparts and that privatization increased their productivity. Beck et al. (2005)
studied the Nigerian banking systemusing data on accounting indicators of performance
for 69 banks. They concluded that privatization led to performance improvement and
those banks that continued to have minority government ownership performed worse
than the fully privatized banks. On the other hand privatization has been shown to have
negative effects inChina (Chen et al., 2005) and inPakistan(Bonaccorsi di Patti and Hardy,
2005). Experience from Mexico suggests that bank privatization may fail unless there are
strong institutions and well de?ned property rights (Haber, 2005). In fact Mexico’s ?rst
experiment in privatization led to insolvency of the banks and the second experiment
produced a risk-averse banking system. While most of these papers are concerned with
whether privatization led to improvement in bank performance, the issue of partial
privatization and bank performance has been scarcely studied.
Gupta (2005) studied the impact of partial privatization on ?rm performance.
Employing data on Indian state-owned ?rms belonging to the manufacturing and the
non-banking services sectors, she investigated the impact of partial privatization on
performance. The performance variables considered were accounting indicators of
pro?tability, productivity and investment. The analysis revealed that partial
privatization did lead to improvement in performance. Since the government retained
management control of these ?rms even after the partial privatization exercise, the
improvement in performance could not be attributed to the elimination of political
interference. Gupta (2005) attributed it to the amelioration of the agency problem
associated with government ownership that got reduced with the stock market now
enforcing managerial discipline and corporate control. In the case of Indian banks,
Kumbhakar and Sarkar (2003) studied the impact of deregulation on the productivity of
Indian banks and found that while productivity of private banks improved, public sector
banks did not respond to deregulation. The issue of partial privatization of public sector
banks was not considered by them. Mohan (2005) and Sathye (2005) used difference of
means tests to conclude that ?nancial parameters of performance for partially privatized
banks in India were superior to those of public banks. However, both these studies used
only ?ve years of data and did not consider the determinants of performance.
3. Overview of Indian banking
The banking sector plays a crucial role in fostering economic growth, especially in an
emerging economy such as India. Banks play an important role, inter alia, in the
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mobilization of savings and capital formation whose importance for an emerging
economy cannot be overemphasized. The dominant presence of banking in the Indian
economy can be gauged from the fact that aggregate deposits stood at 48 percent of
gross domestic product (GDP) in 2002-2003 and bank credit to the government and
commercial sector stood at 26 and 33 percent of GDP, respectively, in 2002-2003. Thus,
in terms of size, banking occupies an important position in the economy. Prior to 1992,
the banking sector in India was highly regulated and dominated by the public sector
banks. With the developmental objectives of providing adequate credit, there were
severe constraints on operational decisions. In addition, the banks were impeded by
regulations on the pricing of ?nancial products imposed by the banking regulator,
namely, the Reserve Bank of India (RBI).
However, towards the early nineties the government realized that an excessive focus
on quantitative achievements was making many banks inef?cient, unpro?table and
under-capitalized. Recognizing these problems, the RBI launched the banking sector
reforms in 1992 on the recommendations of the ?rst Narasimhamcommittee on ?nancial
sector reforms (RBI, 1991). This led to the deregulation of entry, interest rates, branch
de-licensing and allowed public sector banks to access the capital markets for raising
equity. At the same time, there were a number of changes in statutory norms, namely, a
gradual reduction of the cash reserve ratio and the statutory liquidity ratio, setting up of
a minimum 8 percent capital to risk-weighted assets ratio (CRAR), and an imposition of
stringent income recognition and provisioning norms. The second round of reforms in
the banking sector followed the report of the second Narasimhamcommittee (RBI, 1998)
that laid stress on prudential measures like higher CRAR, allowing for market risk on
government securities, stricter non-performing assets norms, introduction of
assets-liabilities management and risk management guidelines.
The banking sector reforms in India, initiated in 1992, were intended to impart
enhanced ef?ciency, productivity and pro?tability into the system. One key element
of the reforms process was the partial privatization of public sector banks. While
the government retained controlling stakes, up to 49 percent of equity was sold
to investors. However, this was done in a piece-meal manner, with one or two banks
getting listed in every year after 1993. Table I presents the timeline and extent of
privatization of the public sector banks. Table II denotes the resulting shareholding
pattern of the banks which suggests that while ownership is fairly diversi?ed, foreign
institutions ended up holding large stakes in the public sector banks and could act as
an important source of market discipline.
Even though the government continues to hold controlling stakes due to political
reasons, it was felt that subjecting public sector banks to market discipline through
stock exchange listing was an effective way of improving their performance as it
provided a method of alleviating the agency problem arising out of government
ownership. The stock market regulator has elaborate disclosure norms for newissues as
well as continuing disclosures ranging from ?nancial information to dividend policy,
business risks and corporate governance requirements[2]. Banks intending to get listed
on the stock exchange have to provide the auditor’s report on their ?nancial statements
along with the management’s discussion and analysis of ?nancial conditions and results
of operations. The business strategies as well as risks categorized as company speci?c
and general factors have to be disclosed. Other requirements of the regulator include a
due diligence certi?cate from a lead merchant banker, grading details from a credit
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rating agency, appointment of a compliance of?cer and details of outstanding
litigations. Corporate governance requirements include details of management and
shareholding structure, compensation of directors, information on audit committee,
shareholder/investor grievance committee, etc.
Listed banks are therefore subject to stringent disclosures facilitating monitoring
by investors which provides an alternative governance mechanism to the RBI’s
monitoring. The two are different in many aspects, e.g. the RBI’s focus is on prudential
regulation and its compliance (and the information is not released to the public) rather
than ?nancial details and corporate governance (readily accessible by investors) which
is a primary focus of the stock exchange disclosures. The Basel-II accord acknowledges
that market discipline is an important governance mechanism, which can complement
the industry regulations and supervisory processes. Such disclosure norms and the
consequent market discipline have made the public sector bank managements more
cognizant of the market consequences of their activities, which may have led to the
improvement in the performance of these banks (Mohan, 2006). On the other hand it
may be argued that listing alone may not produce the desired effects unless a bank is
fully privatized. This is because of the moral hazard generated by the implicit
government guarantee in a partially privatized bank, which could weaken the
Partial privatization details
Name of bank Year sold Percentage of equity sold
State Bank of India and its associates
State Bank of India 1994 33.7
a
State Bank of Bikaner and Jaipur 1998 25.0
State Bank of Travancore 1998 25.0
Nationalized banks
Oriental Bank of Commerce 1995 33.5
Bank of Baroda 1997 33.8
Bank of India 1997 30.7
Dena Bank 1997 29.0
Corporation Bank 1998 42.8
Syndicate Bank 2000 26.5
Andhra Bank 2001 33.4
Indian Overseas Bank 2001 25.0
Vijaya Bank 2001 30.0
Punjab National Bank 2002 20.0
Allahabad Bank 2003 28.8
Canara Bank 2003 26.8
Union Bank 2003 39.1
Notes:
a
A further 6.6 percent of equity was sold in the year 1997; this table shows the timeline of
partial privatization till 2003, i.e. the last year of our period of analysis. Out of the 27 public sector
banks in India, the 16 banks shown in this table were partially privatized and the remaining 11 were
not (the names of the 11 banks that were not partially privatized are: State Bank of Hyderabad, State
Bank of Indore, State Bank of Mysore, State Bank of Patiala, State Bank of Saurashtra, Bank of
Maharashtra, Central Bank, Indian Bank, Punjab and Sind Bank, UCO Bank, United Bank of India).
State banks refer to those that were always state-owned namely the State Bank of India and its
associate banks. Nationalized banks refer to those that were taken into government ownership during
the nationalization programmes in 1969 and 1980
Source: RBI
Table I.
Timeline of partial
privatization of public
sector banks till 2003
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Table II.
Shareholding pattern
of public sector banks
(end-March 2005)
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monitoring efforts of shareholders. The managers too are aware that the government
may bail them out especially if the state is a large shareholder (Megginson, 2005).
Therefore, the effects of partial privatization and listing on performance are hardly
unambiguous. It is against this backdrop that we empirically examine the impact of the
partial privatization programme on bank performance in India.
4. Empirical methodology and data
4.1 Total factor productivity
We use TFP as our ?rst measure of bank performance as “productivity gains are the
dominant factor in post privatization outcomes” (La Porta and Lopez-de-Silanes, 1999).
Following Kumbhakar and Lovell (2000), we estimate three components of TFP
growth, namely, those attributable to technical progress, returns to scale and ef?ciency
change and then aggregate them as:
TF
_
P ¼ TF
_
P
1
þ TF
_
P
2
þ TF
_
P
3
ð1Þ
Until very recently, econometric models of TFP growth had ignored the last term,
i.e. the role of ef?ciency change. However, as Kumbhakar and Lovell (2000)
purposefully argue, when individual production units vary greatly in terms of their
cost or productive ef?ciency, ignoring this component is likely to give biased estimates
of productivity growth. While the ?rst two components of TFP growth, i.e. technical
progress and returns to scale, can be estimated from a standard cost function, the last
component, i.e. ef?ciency change, requires the estimation of a cost frontier. Since the
production technologies of banks are unknown a priori, we estimate ef?ciency as
the deviation from the ef?cient cost frontier where the best-practice banks operate.
To do that we consider the following stochastic cost frontier:
ln E ¼ ln CðY; W; tÞ þ U þ V ð2Þ
where, E ¼ WX is total expenditure, X ¼ (x1, . . . , xN)’ is a (N £ 1) vector of inputs,
W ¼ (w1, . . . , wN)’ is a (N £ 1) vector of input prices, Y ¼ (y1, . . . , yM)’ is a (M £ 1)
vector of outputs, t is a time trend that proxies technical change, C(Y, W, t) is the
deterministic kernel of the stochastic cost frontier, U $ 0 is the one-sided cost
inef?ciency term, and V is a random variable with zero mean. Appendix 1 explains
how the TFP growth in equation (1) can be arrived at based on the stochastic cost
frontier in equation (2).
4.2 Estimation procedure
To arrive at the measure of TFP growth based on its three components we ?rst need to
estimate the stochastic cost frontier given in equation (2). This requires the speci?cation
of the random terms U and V and a functional form for the deterministic kernel C
(Y, W, t). We assume that the inef?ciency term u
it
follows a truncated normal
distribution with mean m and constant variance, while the random term v
it
follows
the usual normal distribution with a zero mean and constant variance[3]. Speci?cally, we
assume, u
it
, iidN
þ
ðm; s
2
u
Þ and v
it
, iidNð0; s
2
v
. For the deterministic kernel we
employ the translog (transcendental logarithm) speci?cation. The translog function
(Christensen et al., 1975) can be viewed as a second order approximation of any unknown
function and it provides ?exibility to a parametric functional form. Combining the error
terms and the deterministic kernel, the cost frontier function is speci?ed as:
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ln C
it
¼a
0
þ
m
X
a
m
ln y
mit
þ
j
X
b
j
ln w
jit
þb
t
t
þ
1
2
m
X
l
X
a
ml
ln y
mit
ln y
lit
þ
j
X
k
X
b
jk
ln w
jit
ln w
kit
þb
tt
t
2
8
<
:
9
=
;
þ
m
X
j
X
a
mj
ln y
mit
ln w
jit
þ
m
X
a
mt
ln y
mit
t þ
j
X
b
jt
ln w
jit
t þu
it
þv
it
ð3Þ
where w
jit
denotes the price of input j and y
mit
denotes the amount of output mproduced
by bank i in period t, respectively. The dependent variable, operating cost, is the sum of
establishment expenses and physical capital expenses[4]. We impose the standard
restrictions of symmetry and linear homogeneity for estimating the parameters of
equation (3):
a
ml
¼ a
lm
and b
jk
¼ b
kj
;
j
X
b
j
¼ 1;
j
X
b
jk
¼ 0 ;k;
j
X
a
mj
¼ 0 ;m;
j
X
b
jt
¼ 0:
A widely debated issue in the banking literature is the de?nition of banking inputs and
outputs, and more speci?cally the classi?cation of deposits in this respect. The two
alternative approaches to determining what constitutes inputs and outputs of banks are
the production approach and the intermediation approach (Sealey and Lindley, 1977).
The production approach considers labor and capital as inputs and number of processed
accounts as outputs. The intermediation approach considers deposits as inputs and
de?nes loans and investments as outputs. We adopt the production approach, which has
been the most used approach in the Indian context (Kumbhakar and Sarkar, 2003), and
thereby consider deposits to be an output of a bank. Finally, we also include the number of
branches as an output variable. Branches are expected to control for many immeasurable
attributes of a bank, e.g. quality of services and number of accounts serviced (Berg et al.,
1993; Grifell-Tatje and Lovell, 1996)[5]. Accordingly, in this study, banks are modeled as
multi-product ?rms that produce six outputs (?xed, saving and current deposits[6], loans,
investments and branches) and employ two inputs (labor and capital).
The price of labor is de?ned as the ratio of established expenses to the total number of
employees. The price of capital is measured as the ratio of physical capital expenses to
?xed assets which is then used to normalize costs and input prices in order to impose the
linear homogeneity restrictions. All the variables are de?ned in details in the Appendix
Table AI. The parameters of equation (3) are then estimated by the Maximum-Likelihood
method using the FRONTIER (version 4.1) software developed by Coelli (1996).
The log-likelihood function of this model is available fromKumbhakar and Lovell (2000).
4.3 Estimable partial privatization regression
Once the cost frontier is estimated and TFP growth is computed, we construct an index
of TFP for every year and every bank as:
TFP
it
¼ TFP
iðt21Þ
1 þ TF
_
P
it
 Ã
:
The value of the index is set to 100 for the ?rst year for all banks. De?ning the
logarithm of TFP index values as our ?rst measure of performance, we regress it on the
partial privatization variable as follows:
Performance
it
¼ a þd
t
þbPP
it
þgX
it
þ1
it
ð4Þ
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This equation is estimated using the ?xed effects panel regression (within effects)
model (Wooldridge, 2002), where i indexes banks, t indexes years, a is the intercept, d
t
is a year-speci?c ?xed effect, b is the coef?cient of the partial privatization variable PP,
g is the coef?cient of a control variable X. We do not allow for bank-speci?c ?xed
effects as they lead to multicollinearity problems arising from the presence of a private
sector dummy which we include in the model to control for those banks that belong to
the private sector throughout our sample period.
We use various proxies to represent partial privatization (PP) that we explain in details
while presenting our empirical ?ndings. In addition to TFP, we replace the performance
variable in equation (4) with four different accounting ratios, namely, operating pro?t ratio
(OPR), net interest margin (NIM), operating cost ratio (OCR) and staff expense ratio (SER).
These variables are de?ned in the Appendix Table AI. OPR is a simple measure of
pro?tabilityas it indicates howa bankis able to generate revenues over andabove its costs.
NIM is a measure of a bank’s competence in generate income from its core businesses, i.e.
interest bearing assets. Therefore, OPR and NIM offer us two metrics of a bank’s
performance in terms of its revenue generating abilities. OCR measures the extent of
resources used by a bank and SER indicates its ef?ciency in labor usage. These two
variables are suitable measures of operating ef?ciency. Therefore, in all we have ?ve
performance measures for estimating equation (4).
The year speci?c ?xed effects account for unobserved year speci?c changes. This is
particularly relevant in our case since the banking sector in India continues to undergo
policy changes over the years. Moreover, the ?xed effects would also help to control for
competition effects that build up over time. Over the years as the banking sector
experiences liberalization, intensi?ed competition from private incumbents and the
entry of de novo banks may affect performance of public sector banks. We expect the
year speci?c ?xed effects to capture such bank-invariant effects.
In equation (4) the main coef?cient of interest is b that is attached to the partial
privatization variable PP. It indicates the effects on performance that is attributable to
partial privatization over and above those caused by other regulatory changes and
bank speci?c attributes. As for the sign of this coef?cient, that would get determined
by whether the managerial view (Holmstrom and Tirole, 1993) or the political view
(Shleifer and Vishny, 1997) dominates. For instance, if the former outweighs the latter,
i.e. if market discipline and incentives are strong even for partially privatized banks, then
we can expect the coef?cient to have a positive sign for the productivity and pro?tability
measures. In other words, partial privatization would yield improvement in productivity
and pro?tability. For OCRand SERwe would then expect the coef?cient to be negative as
partial privatizationwouldleadtocost savings for these banks. However, inall the cases of
partial privatization of Indian banks the government has so far retained control. This
might mean that the political view dominates as political interference might continue to
sti?e the performance of the former state-owned banks.
Finally, we include control variables X
it
to account for other sources of variations in
performance. These include SIZE(logarithmof total assets) whichproxies for the abilityof
smaller banks to respond more quickly to changes in market conditions in which case its
coef?cient would be negative in the partial privatization regressions. The proportion of
rural branches (PROP_RUR) is considered as a proxy for the business opportunity,
or the lack of it, faced by a bank in rural areas. Its coef?cient would determine whether the
investment in rural areas has been rewarding for banks. The proportion of non-interest
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income to total income (PROP_INT) controls for banks’ diversi?cation activities whichare
expected to bene?t them through higher productivity and pro?tability.
4.4 Data source
The accounting data of banks is taken from various issues of Financial Analysis of
Banks and Performance Highlights of Banks published by the Indian Banks’
Association. The ownership and listing data is taken from various issues of Report on
Trends and Progress of Banking in India published by the RBI. Among the 27 public
sector banks operating in India, we include all but three in our analysis. We exclude
those three banks, which got listed in the last year of the sample period (Table I).
We include the domestic private banks as a control group to enable us to isolate the
effects of partial privatization. There were 26 private banks during the sample period
but incomplete information was available for private banks in some years leading to an
unbalanced panel. We excluded new private banks, which started operating in 1996
and hence cannot be a good control group like the older private banks. Moreover, we do
not include foreign banks as they operate in India as branches of their parent entities
and are not listed on Indian stock exchanges like other private banks. Therefore, they
are not comparable with the Indian public sector and private banks when it comes to
analyzing the impact of stock exchange listing on performance. A time period of
18 years is taken for each bank from the year 1986 to 2003[7].
Table III presents the share of banking assets that each bank group holds.
Clearly, the public sector banks are the dominant group with over 75 percent share of
banking assets. But its share has been declining over the sample period while those
of the private groups have been rising. Table IV presents the descriptive statistics for
Year Public Private Foreign New private
1986 92.37 3.82 3.81 –
1987 91.84 3.89 4.27 –
1988 91.96 3.86 4.19 –
1989 92.00 3.49 4.51 –
1990 91.21 3.48 5.32 –
1991 90.25 3.65 6.10 –
1992 88.54 4.21 7.25 –
1993 87.11 4.73 8.16 –
1994 87.08 5.31 7.61 –
1995 86.23 6.43 7.34 –
1996 84.57 6.08 7.83 1.52
1997 82.35 6.52 8.74 2.39
1998 81.42 6.92 8.38 3.28
1999 80.86 6.90 8.16 4.09
2000 79.74 7.12 7.75 5.38
2001 79.32 6.29 8.21 6.17
2002 75.99 6.03 6.51 11.47
2003 75.83 6.20 6.75 11.21
Notes: For new private banks prior to their entry (new private banks are those that started operations
in 1996); values reported are percentages; this table shows the share of total assets held by each
banking group in India during our period of analysis
Source: RBI
Table III.
Share of banking assets
held by bank groups,
1986-2003
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the bank characteristics used in our empirical work. It appears that public sector banks
are the larger group compared to private banks in terms of assets, deposits and loans.
However, among the public sector banks, those banks which were partially privatized
are larger than those which were never partially privatized. Interestingly, the former
had a higher proportion of rural and semi-urban branches suggesting that they did not
enjoy larger urban presence than the banks which were never partially privatized.
Bank characteristics Mean SD Median Maximum Minimum
Log (TFP)
Public banks 4.86 0.25 4.78 5.68 4.57
PP banks 4.87 0.25 4.79 5.63 4.59
Never PP banks 4.86 0.26 4.78 5.68 4.57
Private banks 4.76 0.19 4.70 5.51 4.51
Operating pro?t ratio
Public banks 0.09 1.17 0.20 1.76 28.02
PP banks 0.26 0.97 0.26 1.63 26.67
Never PP banks 20.10 1.35 0.15 1.76 28.02
Private banks 0.46 1.22 0.44 16.37 28.51
Net interest margin
Public banks 2.52 0.81 2.60 5.73 24.45
PP banks 2.53 0.77 2.62 4.73 24.45
Never PP banks 2.51 0.86 2.52 5.73 0.48
Private banks 2.80 1.87 2.74 35.31 26.90
Operating cost ratio
Public banks 2.68 0.48 2.66 4.36 1.41
PP banks 2.60 0.49 2.57 3.77 1.41
Never PP banks 2.77 0.45 2.72 4.36 1.73
Private banks 3.07 3.69 2.80 72.82 0.00
Staff expense ratio
Public banks 1.97 1.13 1.92 23.65 0.85
PP banks 1.83 0.42 1.81 3.03 0.85
Never PP banks 2.13 1.59 2.01 23.65 1.17
Private banks 1.99 0.93 1.93 11.23 0.30
Proportion of rural branches (%)
Public banks 66.53 5.78 67.29 80.81 46.35
PP banks 66.61 6.87 67.53 80.81 46.35
Never PP banks 66.43 4.15 66.62 76.47 55.61
Private banks 59.59 16.92 63.30 84.38 0.00
Proportion of non-interest income (%)
Public banks 11.38 5.49 11.12 94.70 4.60
PP banks 11.29 6.64 10.93 94.70 4.61
Never PP banks 11.50 3.71 11.22 23.64 4.60
Private banks 10.48 34.83 11.38 34.32 2.94
Size
Public banks 9.90 10.57 9.17 12.84 6.40
PP banks 10.23 10.83 9.42 12.84 6.89
Never PP banks 9.26 9.19 8.92 10.95 6.40
Private banks 7.46 7.81 6.56 9.73 1.92
Notes: Size is natural logarithm of total assets (at 1993-1994 prices). PP refers to partially privatized;
this table presents the descriptive statistics for the ?ve performance indicators and the control
variables used in the regression models
Table IV.
Descriptive statistics
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But at the same time their proportion of non-interest income was higher indicating that
they were focused on fee based activities and earnings from trading.
5. Empirical ?ndings
We begin our discussion with the behavior of the TFP index and the accounting indicators
as shown in Figure 1. The graphs indicate that public sector banks as well as private banks
underwent improvement in productivity over the sample period. The period also witnessed
improvement inpro?tabilityand ef?ciency as indicated by the increase in OPRand decline
in OCR and SER. The improvements are particularly pronounced for the private banks
relative to the public sector banks. However, NIM remained stable for both bank groups.
Using the ?ve performance measures of the individual banks in each year,
we estimate ?ve partial privatization regressions based on equation (4). We use three
speci?cations for the partial privatization (PP) variable. These are:
(1) a trend variable that operates after a bank gets listed (LIST_TREND);
(2) a continuous variable to denote the extent of private ownership (PRIV_SHARE);
and
Figure 1.
Performance indicators for
public sector and private
sector banks
5.50
5.40
5.30
5.20
5.10
5.00
4.90
4.80
4.70
4.60
4.50
Public sector Private sector
Log (TFP)
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
1.5
1
0.5
0
–0.5
–1
–1.5
–2
Public sector Private sector
OPR
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Public sector Private sector
Public sector Private sector
NIM
SER
Notes: The figure presents a comparison of public and private sector banks based on the five performance
indicators. TFP is the index of total factor productivity estimated from a stochastic cost frontier; OPR is
operating profit ratio; NIM is net interest margin; OCR is operating cost ratio; SER is staff expense ratio
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
3.5
3
2.5
2
1.5
1
0.5
0
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Public sector Private sector
OPR
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
8
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
2
0
0
0
2
0
0
1
2
0
0
2
2
0
0
3
JFEP
2,4
288
D
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e
d
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C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
(3) a dummy variable for stock exchange listing (LIST_DUM) that takes the value
one once a bank gets partially privatized.
These variables are designed to differently capture the roles of listing and ownership
share. The variable LIST_TREND provides a way of examining whether there is
persistence in the effect of partial privatization on performance. PRIV_SHARE is
constructed to analyze whether performance is related to the extent of share ownership
that is privately owned. LIST_DUM is designed to capture the average effect of the
partial privatization programme on performance.
To address the concern of multicollinearity we present a correlation matrix of all the
proposedindependent variables inTable V. While the three PPvariables seemtobe highly
correlated, there is very low correlation among the control variables and between the
control and PP variables. We do not include all the three PP variables in the same model
but use them in two combinations as described in the next paragraph. In any case we
checked the variance in?ation factors for each variable in each model; in none of the cases
did the VIF turn out to be .3 thereby indicating that our models did not suffer from
multicollinearity problems. We correct for heteroscedasticity in all the models by
estimating standard errors based on the Huber-White Sandwich estimator of variance.
For each performance measure we estimate two variants of equation (4) using the
alternative de?nitions of the PP variable. The estimation results for these two models are
presented in Tables VI and VII. In Table VI, we present the results from regressing
performance on PRIV_SHARE and LIST_TREND. We include a dummy variable
PRIV_SECTOR for the private banks group along with the other control variables. The
results reveal that the coef?cient of PRIV_SHARE is positive for the TFP, OPR and NIM
regressions and negative for the OCR and SER regressions. This indicates that higher
divesture was associated with improved productivity (higher TFP) and pro?tability
(higher OPR and NIM) while the ef?ciency effects (in terms of OCR and SER) are not
statistically signi?cant. In the TFPregression the coef?cient of IV_SHAREis 0.0007 and is
signi?cant onlyat 10 percent level of signi?cance. Onthe other handthe effects of the extent
of private ownership on OPRand NIMare stronger. Inthe OPRregression the coef?cient of
PRIV_SHARE is 0.0218 which is signi?cant at the 1 percent level of signi?cance while in
the NIM regression the coef?cient of PRIV_SHARE is 0.0194 which is signi?cant at the
5 percent level. In sum we ?nd statistically signi?cant evidence of improved performance
owing to higher divesture in the case of productivity and pro?tability.
The coef?cient of LIST_TRENDis statistically signi?cant only in the TFP regression
where it takes a positive value of 0.0220. This indicates that in the years subsequent to
their divesture, listed banks continued to exhibit higher productivity comparedto unlisted
banks. This suggests that improvement in productivity was not a one-off phenomenon or
simplya “listingeffect” (Gupta, 2005) but that the impact onproductivityfollowing partial
privatizationwas permanent andsustained. Finally, comparingthe relative magnitudes of
the coef?cients of PRIV_SHARE and LIST_TREND we observe that even though the
number of signi?cant coef?cients is more for ownership share than for listing trend, the
latter effect appears to be stronger in the only case where it is statistically signi?cant. In
the TFP regression the coef?cient of LIST_TRENDis 0.0220 while that of PRIV_SHARE
is 0.0007. It seems that while the magnitude of divesture may have been important in
improving productivity and pro?tability, the very effect of listing on the stock exchange
played a stronger disciplining role in improving productivity.
Partial
privatization
and performance
289
D
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n
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o
a
d
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d
b
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P
O
N
D
I
C
H
E
R
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A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
P
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7
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9
8
2
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7
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1
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2
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4
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2
6
7
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1
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0
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0
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5
3
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3
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3
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2
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1
1
N
o
t
e
:
T
h
i
s
t
a
b
l
e
p
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e
n
t
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t
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e
p
a
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r
-
w
i
s
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e
l
a
t
i
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f
?
c
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a
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d
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a
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t
h
e
r
e
g
r
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s
s
i
o
n
m
o
d
e
l
s
Table V.
Correlation matrix of
independent variables
JFEP
2,4
290
D
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n
l
o
a
d
e
d
b
y
P
O
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(
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9
N
o
.
o
f
o
b
s
.
8
2
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1
N
o
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e
s
:
S
t
a
t
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c
a
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i
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i
?
c
a
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t
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f
?
c
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e
n
t
s
a
t
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
h
e
?
v
e
p
e
r
f
o
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m
a
n
c
e
i
n
d
i
c
a
t
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e
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r
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s
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d
o
n
t
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e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
v
a
r
i
a
b
l
e
t
h
a
t
o
p
e
r
a
t
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s
a
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a
t
r
e
n
d
o
n
c
e
a
b
a
n
k
i
s
l
i
s
t
e
d
(
L
I
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_
T
R
E
N
D
)
.
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R
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S
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C
T
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R
i
s
a
d
u
m
m
y
v
a
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i
a
b
l
e
f
o
r
b
a
n
k
s
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n
t
h
e
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r
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a
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s
e
c
t
o
r
.
P
a
n
e
l
r
e
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r
e
s
s
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o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
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e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
Table VI.
Partial privatization and
bank performance: roles
of listing trend and
ownership share
Partial
privatization
and performance
291
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
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U
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t
2
1
:
3
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2
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r
y
2
0
1
6
(
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T
)
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o
g
(
T
F
P
)
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3
7
3
4
)
2
.
7
8
0
9
*
*
*
(
0
.
2
2
6
5
)
2
.
8
5
0
3
*
*
*
(
0
.
5
1
1
1
)
2
.
0
6
5
2
*
*
*
(
0
.
1
1
3
8
)
R
2
0
.
1
9
1
2
0
.
0
4
9
1
0
.
0
8
2
3
0
.
0
1
4
2
0
.
1
0
1
4
N
o
.
o
f
o
b
s
.
8
2
8
8
4
1
8
4
1
8
4
1
8
4
1
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
d
u
m
m
y
v
a
r
i
a
b
l
e
t
h
a
t
i
n
d
i
c
a
t
e
s
w
h
e
t
h
e
r
a
b
a
n
k
i
s
l
i
s
t
e
d
o
r
n
o
t
(
L
I
S
T
_
D
U
M
)
.
P
R
I
V
_
S
E
C
T
O
R
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
f
o
r
b
a
n
k
s
i
n
t
h
e
p
r
i
v
a
t
e
s
e
c
t
o
r
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table VII.
Partial privatization and
bank performance: roles
of listing effect and
ownership share
JFEP
2,4
292
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Moving to the control variables, we focus on those coef?cients which are
statistically signi?cant in the estimations. First we observe that the coef?cient of the
private sector dummy in the TFP regression is 20.1008 which is statistically signi?cant
at the 1 percent level. This suggests that public sector banks had higher productivity
thanthe private banks duringthe sample period[8]. The coef?cient of this dummyvariable
is also signi?cant inthe OPR, NIMandSERregressions takingthe values 0.6460, 20.3569
and 20.5722, respectively. These values indicate that private banks had higher
pro?tability and ef?ciency than the public sector banks. The proportion of rural branches
seems to adversely impact costs as indicated by its positive and statistically signi?cant
coef?cients of 1.1983 and 1.7585 in the OCR and SER regressions, respectively. However,
the additional expenditure owing to rural branches appears to have paid rewards through
higher pro?tability andproductivity as evidenced bythe NIMand TFPregressions where
the coef?cients of PROP_RUR are 1.7970 and 0.1000, respectively.
The proportion of non-interest income is associated with higher ef?ciency as
the coef?cients of PROP_NINT are negative and statistically signi?cant for the OCR
and SER regressions (the coef?cients are 20.0036 in both cases). However, non-interest
income seems to be associated with lower NIM (the corresponding coef?cient
being 20.0022) which is not surprising since banks with higher income from non-core
businesses may have less focus on lending activities. Finally, the coef?cients of SIZE
suggest that bigger banks are less productive (the coef?cient is 20.0135 in the TFP
regression) and have lower spreads (the corresponding coef?cient is 20.3309). It seems that
smaller banks were better able to take advantage of the changingmarket conditions leading
to higher productivity and interest income. However, bigger banks are more ef?cient as
indicated by the negative coef?cients on SIZE in the SER regression which is 20.2732.
In Table VII, we present the estimates of models comparing the roles of listing effect
and ownership share by including the LIST_DUM variable along with PRIV_SHARE.
The ?ndings for PRIV_SHARE are similar to the previous results for pro?tability.
For the SER regression we ?nd that the coef?cient of PRIV_SHARE is 20.0139 which
is statistically signi?cant at the 5 percent level. This suggests that the extent of
divesture has a negative association with staff expenses. In case of LIST_DUM the
only statistically signi?cant coef?cient appears in the TFP regression. Here, it takes
the positive value of 0.1663 and is signi?cant at the 1 percent level. This indicates that
the effect of listing was to improve the productivity of public sector banks and as
before this effect appears to dominate the magnitude of divesture. The results for the
control variables are similar to those obtained in the previous estimations in Table VI.
6. Endogeneity of partial privatization
In the previous section, we have estimated a variety of regressions to examine the impact
of partial privatization on bank performance. However, it could be argued that the
improvements inperformance suggestedbyour results were not the result of privatization
but because the better performing banks were the ones to undergo divestment. In other
words there could have been a selectionbias inidentifying which banks to privatize which
in econometric terms would amount to endogeneity of our partial privatization variables.
In this section we re-examine our results while controlling for potential selection bias.
In order to do that, we start by re-estimating the partial privatization regressions but now
consider only those banks that were partially privatized (Tables VIII and IX). Thus, these
regressions are similar to the “before and after” privatization analyses that are often found
Partial
privatization
and performance
293
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
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V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
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N
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(
0
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)
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7
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(
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D
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9
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(
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9
(
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8
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(
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)
P
R
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P
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.
6
2
5
9
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*
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(
0
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0
8
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)
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4
2
4
(
0
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5
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8
8
)
2
0
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3
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(
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2
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)
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.
9
9
6
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(
0
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2
2
4
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)
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.
3
4
2
6
*
*
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(
0
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1
7
5
0
)
P
R
O
P
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N
I
N
T
0
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0
1
3
8
(
0
.
0
2
3
6
)
2
0
.
0
5
4
7
(
0
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1
4
2
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)
2
7
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4
2
1
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(
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4
6
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)
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4
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(
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(
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S
I
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5
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*
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(
0
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0
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0
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(
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1
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(
0
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0
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2
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0
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1
0
5
2
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*
*
(
0
.
0
3
2
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)
I
N
T
E
R
C
E
P
T
4
.
5
0
9
0
*
*
*
(
0
.
0
3
9
1
)
0
.
2
2
9
8
(
0
.
3
8
9
0
)
3
.
6
4
8
4
*
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(
0
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2
4
4
9
)
2
.
8
6
9
6
*
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(
0
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2
4
3
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)
1
.
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0
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5
*
*
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(
0
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2
0
0
9
)
R
2
0
.
4
2
6
6
0
.
0
3
6
5
0
.
4
7
9
7
0
.
2
0
8
3
0
.
2
1
4
3
N
o
.
o
f
o
b
s
.
2
3
4
2
3
4
2
3
4
2
3
4
2
3
4
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
a
n
d
a
v
a
r
i
a
b
l
e
t
h
a
t
o
p
e
r
a
t
e
s
a
s
a
t
r
e
n
d
o
n
c
e
a
b
a
n
k
i
s
l
i
s
t
e
d
(
L
I
S
T
_
T
R
E
N
D
)
.
T
h
e
s
a
m
p
l
e
f
o
r
t
h
i
s
e
s
t
i
m
a
t
i
o
n
c
o
n
s
i
s
t
s
o
f
o
n
l
y
t
h
o
s
e
b
a
n
k
s
t
h
a
t
w
e
n
t
o
n
t
o
b
e
p
a
r
t
i
a
l
l
y
p
r
i
v
a
t
i
z
e
d
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table VIII.
Partial privatization and
bank performance (only
partially privatized
banks): roles of listing
trend and ownership
share
JFEP
2,4
294
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
0
.
0
0
0
7
(
0
.
0
0
0
8
)
0
.
0
2
7
5
*
*
*
(
0
.
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5
4
)
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(
0
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8
7
)
2
0
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0
2
3
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*
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(
0
.
0
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6
7
)
2
0
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2
9
8
*
*
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(
0
.
0
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5
9
)
L
I
S
T
_
D
U
M
0
.
0
2
4
7
(
0
.
0
3
2
1
)
2
0
.
4
5
1
3
(
0
.
3
0
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3
)
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2
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8
(
0
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7
)
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)
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(
0
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3
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)
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0
.
6
1
8
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*
*
*
(
0
.
0
9
7
7
)
0
.
2
8
7
9
(
0
.
6
2
2
9
)
2
0
.
1
8
1
6
(
0
.
3
9
6
9
)
0
.
6
7
3
3
*
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(
0
.
2
6
8
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)
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.
9
4
5
2
*
*
*
(
0
.
2
0
9
1
)
P
R
O
P
_
N
I
N
T
0
.
0
3
2
9
*
*
(
0
.
0
1
2
5
)
2
0
.
1
2
7
9
(
0
.
1
0
3
0
)
2
7
.
9
5
4
4
*
*
*
(
0
.
4
6
2
9
)
0
.
9
3
7
6
*
*
*
(
0
.
3
2
7
9
)
0
.
8
3
9
4
*
*
*
(
0
.
2
4
9
5
)
S
I
Z
E
2
0
.
0
1
0
3
*
*
*
(
0
.
0
0
3
5
)
2
0
.
0
5
2
7
*
*
*
(
0
.
0
1
8
9
)
2
0
.
2
4
4
7
*
*
*
(
0
.
0
5
9
2
)
2
0
.
1
5
4
2
*
*
*
(
0
.
0
4
7
0
)
2
0
.
0
9
2
6
*
*
(
0
.
0
3
7
3
)
I
N
T
E
R
C
E
P
T
4
.
4
9
4
2
*
*
*
(
0
.
0
4
9
9
)
0
.
1
9
7
6
(
0
.
4
0
1
4
)
3
.
7
1
2
1
*
*
*
(
0
.
2
2
8
2
)
3
.
0
0
1
4
*
*
*
(
0
.
2
1
0
3
)
1
.
7
7
0
5
*
*
*
(
0
.
1
6
7
9
)
R
2
0
.
3
4
1
3
0
.
0
3
4
2
0
.
4
7
7
3
0
.
2
1
0
4
0
.
2
1
8
6
N
o
.
o
f
o
b
s
.
2
3
4
2
3
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Table IX.
Partial privatization and
bank performance (only
partially privatized
banks): roles of listing
effect and ownership
share
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in this literature. We ?nd that all the results from these regressions are qualitatively
similar to our earlier results obtained using the full sample.
In addition to the above regressions, we employ a variety of other techniques to
control for potential selection bias. First, we compare the performance of the partially
privatized banks and the non-privatized banks using the t-test for difference in means
and the Wilcoxon Z-test for difference in medians (Appendix Table AII). The data for
the partially privatized banks in these tests are restricted only to the pre-privatization
years. The results indicate that while the partially privatized banks had lower SER, the
non-privatized banks had higher productivity. In terms of the rest of the performance
measures there does not seem to have been any statistically signi?cant difference
between the two groups. As a result, we can infer that there is no indication of selection
bias in the partial privatization programme.
Second, we employ the technique of instrumental variable estimation to control for the
potential endogeneity of the partial privatization process. We use lags of OPR, NIM, OCR
and SER as instruments for PRIV_SHARE in the TFP regression. Similarly for each
regression we use the lags of the other performance measures as instruments. From the
results we observe that even after allowing for endogeneity of PRIV_SHARE our ?nding
that greater private share in ownership is associated with better performance continues to
hold (Appendix Table AIII). The statistically signi?cant coef?cients of PRIV_SHARE in
the OPR and SER regressions suggest that greater divesture led to improved pro?tability
as well as lower costs. Next, we employ an alternative method for estimating instrumental
variables through a two-stage procedure. First the decision to privatize is estimated as a
probability (by regressing LIST_DUM on a set of instruments) which is then used to
compute ?tted values of privatization share. This is then used as the instrumental variable
in the panel data regression. Other than the lagged performance variables, ?scal de?cit
and a stock exchange index (the Bombay Stock Exchange Sensitive Index) are used as
instruments in this set of estimations. The results are presented in Table AIV. The
coef?cients of PRIV_SHARE in the OPR and SER regressions (0.0620 and 20.0482,
respectively) are statistically signi?cant at conventional levels as before. This shows that
evenafter controllingfor endogeneityusingthe two-stage procedure, we ?ndthat partially
privatized banks experience improvements in pro?tability and ef?ciency.
Finally, we address the issue of endogeneity in an alternative fashion. Following
Bartel and Harrison (2005), we use placebo leads for the share of partial privatization
variable in order to control for any endogeneity present in this variable. We do this by
adding a lead of PRIV_SHARE to the above estimated regressions (Appendix
Table AV). We ?nd that the lead variable is statistically insigni?cant in all but one case
and our original result regarding the positive and statistically signi?cant association
between productivity and partial privatization remains robust. The only exception is the
OPR regression where privatization may have been preceded by higher pro?tability.
However, in view of the results from all the alternative tests we have conducted, on
balance we conclude that our main results are not affected by endogeneity problems.
7. Conclusion
The partial privatization programme in Indian banking since the early nineties
was undertaken to improve the performance of public banks. While there have been
a number of studies on bank performance in India, none so far have looked at the
relationship between performance and partial privatization (other than examining
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the mean differences in performance as in Mohan (2005) and Sathye (2005)). Partial
privatization refers to the government divesting stakes in the public ?rm without
relinquishing management control. Given political opposition to outright privatization,
this has emerged as a feasible alternative for achieving some bene?ts of privatization.
However, the implications of partial privatization for performance are not very clear in
policy debates as well as in the privatization literature.
In this context, the present paper employs the method of stochastic frontier analysis
to study performance in Indian banking over a long time horizon of eighteen years that
encompasses the government’s partial privatization programme. We estimate TFP
from a stochastic cost frontier and employ it as a measure of bank performance.
In addition to TFP we employ four accounting indicators as alternative measures of
performance. Using these ?ve measures of performance, we study the impact of partial
privatization on bank performance through panel regression models.
The results may be summarized as follows. Public banks in India have exhibited
improving performance during the period 1986-2003. A part of this improvement in
performance can be attributed to partial privatization. We ?nd that on an average, listed
banks have signi?cantly outperformed unlisted banks. This result corroborates the ?ndings
of Sarkar et al. (1998) who foundthat listedprivate banks inIndia outperformunlistedprivate
banks, which in turn perform better than public banks. Here, we have obtained a similar
listing effect for public banks. Moreover, we ?nd that the effect of listing on performance is
not a temporary phenomenon and is in fact persistent beyond the year of listing. Thus,
performance of partiallyprivatizedbanks continues toimprove further after listing. Bhaumik
and Dimova (2004) had noted a recent narrowing of the performance gap between public and
private banks in India. Therefore, our results can be construed to suggest that the narrowing
of the performance gap can be partly attributed to partial privatization of public banks. Our
results also suggest that the extent to which government reduced its stakes in the public
banks hada direct signi?cant impact onthe banks’ performance. Thus, higher is the extent of
privatization better is the performance. These results support the managerial view of
Holmstromand Tirole (1993) which suggests that even if the government partially privatizes
state-owned ?rms, the forces of market discipline and consequent managerial incentives
would be suf?cient to bring about an improvement in performance. Our results are also
con?rm the ?ndings of Mohan (2005) and Sathye (2005) who ?nd improved performance of
partially privatized banks by examining difference of means.
We control for potential endogeneity of partial privatization in a number of
alternative ways. First we estimate the partial privatization regressions only for those
banks that were eventually partially privatized. Next we compare the performance of
the partially privatized banks with the rest of the banks. Then we use instrumental
variables to allow for potential endogeneity in partial privatization. Finally, we use
placebo leads to account for the endogeneity. Based on our results, we conclude that
even after accounting for endogeneity our results remain robust.
Governments across the globe have at various times taken recourse to privatizing
state-owned ?rms for the purpose of revenue generation as well as for achieving
increase in ef?ciency and competition. While in most developed countries this has
taken the form of outright sale to private bidders (e.g. privatization in the UK in the
1980s), the political and social idiosyncrasies of developing countries might not permit
such type of privatization. There is often strong political opposition to what is viewed
as “selling the family silver”. Even the government of the day may not be willing to let
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go of control over state-owned ?rms especially in an industry like banking which has
traditionally been a tool for achieving developmental goals. In such instances partial
privatization may be the only viable option as in the case of India’s public sector banks.
The ?ndings of this paper suggest that the post-privatization success of the partial
privatization programme in India is clearly evidenced by improvements in
performance. Our results add to the existing body of evidence on privatization by
providing insights into the partial privatization in the banking industry of an emerging
economy. We document that even when politicians might continue to exert some
control over privatized banks, market pressures can reshape managerial incentives
leading to increase in productivity, pro?tability and ef?ciency.
Notes
1. Was the ?rst year of partial privatization in Indian banking. Therefore, the time period
1986-2003 offers us a suitable sample period for a before and after comparison. We have eight
years data (1986-1993) before the partial privatization programme began and ten years data
after (1994-2003).
2. The disclosure guidelines are available on the regulator’s web site at: www.sebi.gov.in/
guide/dip2009.pdf
3. The subscript i which stands for individual banks, and the subscript t which stands for years
were omitted from equation (2) earlier to preserve clarity of notations. Also, the random
variables are now speci?ed in lowercase to refer to the error terms for individual banks.
4. Establishment expenses refer to the wage bill for of?cers, clerks and other support staff.
As wages are jointly bargained by the bank employees association in India, we do not expect
the endogeneity of wages to be a serious problem in estimating the cost function.
5. We may also note that all estimations with the inclusion of branches yield higher values of
the log likelihood function as compared with the case when branches are dropped.
6. Kumbhakar and Sarkar (2003) argue against clubbing the three categories of deposits
together. We too feel that since bank policies regarding each category are different and the
ratio of these three categories has been varying over time, it is important to treat them as
separate variables in the cost function.
7. The starting year is chosen as 1986 to coincide with the shift of the bank accounting system
in India from that based on calendar year to ?nancial year. Starting with 1986, the ?nancial
year covers the period from April of one year to March of the following year. Thus, the
?nancial year 1986 covers the period from April 1985 to March 1986.
8. While this result is consistent with Mohan (2005) it appears to contradict the ?ndings of
Kumbhakar and Sarkar (2003). However, the latter used a sample till 1997 whereas we
consider six additional years during which public sector banks considerably outperformed
private banks in terms of TFP (Figure 1).
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Further reading
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Association, Mumbai, various issues.
Indian Banks’ Association (1995-1996 to 2002-2003), Performance Highlights of Banks,
Indian Banks’ Association, Mumbai, various issues.
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of India, Mumbai, various issues.
About the authors
Subrata Sarkar has a PhD in Economics from the University of Southern California (USC). He has
worked for the RAND Corporation and taught at the USC before joining IGIDR, Mumbai where
he is currently a Professor. His research interests are in the areas of applied econometrics,
corporate ?nance and productivity studies. He has published in journals such as the Journal of
Money, Credit and Banking, Journal of Economics and Management Strategy, Journal of
Comparative Economics and Review of Development Economics.
Rudra Sensarma has a PhD in Economics from IGIDR, Mumbai. He has worked at the
University of Birmingham, the Indian Institute of Management and the Reserve Bank of India
before joining the University of Hertfordshire, UK where he is currently a Senior Lecturer. His
research interests are in ?nancial economics, banking and applied econometrics. His work has
appeared in journals such as the Journal of Economics, Applied Economics, Economic Modelling
and the Journal of Policy Modeling. Rudra Sensarma is the corresponding author and can be
contacted at: [email protected]
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Appendix 1
Following Kumbhakar and Lovell (2000), the Divisia index of TFP growth for multiple outputs
can be written as:
TF
_
P ¼
_
Y 2
_
X ¼
m
X
R
m
_ y
m
2
j
X
S
j
_ x
j
ðA:1Þ
where, R
m
¼ p
m
y
m
/R is the observed revenue share of output y
m
, p
m
is the price of output y
m
and
R ¼ S
m
p
m
y
m
is total revenue. Likewse, S
j
¼ w
j
x
j
/C is the observed cost share of input x
j
, w
j
is
the price of input x
j
, and C ¼ S
j
w
j
x
j
is total cost. Here a “.” over a variable indicates its growth
rate, i.e. _ x
j
¼ › ln x
j
=›t.
Equation (A.1) is hard to estimate especially in the case of banks due to unavailability of price
information and so it needs to be transformed into an estimable form. Consequently, we consider
the following stochastic cost frontier:
ln E ¼ ln C ðY; W; tÞ þ U þ V ðA:2Þ
where, E ¼ WX is total expenditure, X ¼ (x
1
, . . . ,x
N
)’ is a (N £ 1) vector of inputs,
W ¼ (w
1
, . . . ,w
N)’
is a (N £ 1) vector of input prices, Y ¼ (y
1
, . . . ,y
M
)’ is a (M £ 1) vector of
outputs, t is a time trend that proxies technical change, C(Y, W, t) is the deterministic kernel of
the stochastic cost frontier, U $ 0 is the one-sided cost inef?ciency term, and V is a random
variable with zero mean.
Totally differentiating equation (A.2), we obtain the following expression:
_
E ¼ 1ðY; W; tÞ
m
X
R
m
_ y
m
þ
n
X
S
n
_ w
n
þ
_
CðY; W; tÞ þ
›U
›t
Solving this for
m
P
R
m
_ y
m
, substituting it in equation (A.1) and using the fact that
_
E 2
n
P
ðw
n
x
n
=EÞ_ x
n
¼
n
P
ðw
n
x
n
=EÞ _ w
n
, leads to the following expression:
T
_
FP ¼ 2
_
CðY; W; tÞ þ ½1 21ðY; W; tÞ?
_
Y
C
2
n
X
½S
n
2S
n
ðY; W; tÞ? _ w
n
þ ðY 2
_
Y
C
Þ 2
›U
›t
where
_
Y ¼
m
P
1
m
ðY; W; tÞ=1ðY; W; tÞ is a measure of output growth, 1
m
ðY; W; tÞ is cost
elasticity of the mth output and 1ðY; W; tÞ ¼
m
P
1
m
ðY; W; tÞ. Here ð_ y 2 _ y
C
Þ captures the impact
on productivity change of departures from marginal cost pricing and along with
n
P
½S
n
2S
n
ðY; W; tÞ? _ w
n
, gives a measure of input allocative ef?ciency change. Assuming
allocative ef?ciency yields the following estimable expression for TFP growth:
TF
_
P ¼ 2
_
CðY; W; tÞ þ ½1 21ðY; W; tÞ?
_
Y
c
2
›U
›t
ðA:3Þ
De?ning returns to scale as the inverse of 1ðY; W; tÞ, expression (A.3) provides a
decomposition of TFP into the following components: contribution of technical change
measured by cost diminution (2
_
CðY; W; tÞ), contribution of scale effect (½1 21ðY; W; tÞ?
_
Y
c
),
and contribution of ef?ciency (2›U=›t). Denoting these three components by TF
_
P
1
, TF
_
P
2
and TF
_
P
3
respectively, we can de?ne TFP growth as a sum of its three components:
TF
_
P ¼ TF
_
P
1
þ TF
_
P
2
þ TF
_
P
3
Partial
privatization
and performance
301
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
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R
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I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Appendix 2
L
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Table AI.
Description of variables
JFEP
2,4
302
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
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2
0
1
6
(
P
T
)
M
e
a
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f
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b
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p
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f
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4
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4
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7
8
6
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6
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4
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6
9
7
8
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.
7
2
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,
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0
1
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2
3
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0
2
5
7
(
0
.
0
0
1
2
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P
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2
0
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1
0
2
5
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0
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1
5
0
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0
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0
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3
6
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0
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1
7
0
0
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2
0
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8
2
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0
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4
1
2
7
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1
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1
6
3
8
(
0
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1
2
2
2
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N
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M
2
.
5
1
1
3
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2
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5
2
5
0
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2
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3
6
8
9
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2
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4
2
0
0
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1
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5
8
(
0
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1
1
4
8
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2
1
.
1
1
8
2
(
0
.
1
3
1
7
)
O
C
R
2
.
7
7
2
4
(
2
.
7
2
5
0
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2
.
7
0
6
8
(
2
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7
2
0
0
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1
.
3
4
(
0
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1
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0
4
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2
0
.
1
8
6
4
(
0
.
4
2
6
0
)
S
E
R
2
.
1
3
4
4
(
2
.
0
1
5
0
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1
.
9
0
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(
1
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9
1
0
0
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1
.
7
9
(
0
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0
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4
3
)
2
2
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8
2
5
4
(
0
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0
0
2
4
)
N
o
t
e
:
T
h
i
s
t
a
b
l
e
p
r
e
s
e
n
t
s
s
t
a
t
i
s
t
i
c
a
l
t
e
s
t
s
o
f
d
i
f
f
e
r
e
n
c
e
s
b
e
t
w
e
e
n
p
u
b
l
i
c
b
a
n
k
s
t
h
a
t
w
e
r
e
n
e
v
e
r
p
r
i
v
a
t
i
z
e
d
a
n
d
t
h
o
s
e
t
h
a
t
w
e
n
t
o
n
t
o
b
e
p
a
r
t
i
a
l
l
y
p
r
i
v
a
t
i
z
e
d
b
a
s
e
d
o
n
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
Table AII.
Performance
comparisons of
non-privatized banks and
partially privatized (PP)
banks but considered
only before the listing
year
Partial
privatization
and performance
303
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
2
0
.
0
0
1
0
(
0
.
0
0
2
5
)
0
.
1
1
4
5
*
*
*
(
0
.
0
3
7
7
)
0
.
0
9
4
0
(
0
.
0
8
2
3
)
2
0
.
2
3
1
8
(
0
.
1
5
0
4
)
2
0
.
1
2
9
1
*
*
*
(
0
.
0
4
0
9
)
P
R
I
V
_
S
E
C
T
O
R
2
0
.
1
0
2
6
*
*
*
(
0
.
0
1
8
7
)
0
.
6
8
9
3
*
*
*
(
0
.
1
9
9
1
)
2
0
.
4
6
4
5
*
(
0
.
2
3
8
3
)
2
0
.
2
9
2
5
(
0
.
4
2
6
7
)
2
0
.
7
2
6
5
*
*
*
(
0
.
1
1
1
4
)
P
R
O
P
_
R
U
R
0
.
0
8
4
3
*
(
0
.
0
4
4
7
)
0
.
5
8
8
4
(
0
.
5
5
7
8
)
1
.
5
1
9
4
*
*
*
(
0
.
2
0
0
6
)
1
.
3
3
0
0
*
*
(
0
.
5
3
6
4
)
1
.
6
6
6
4
*
*
*
(
0
.
2
4
9
1
)
P
R
O
P
_
N
I
N
T
2
0
.
0
0
0
1
(
,
0
.
0
0
0
1
)
0
.
0
0
0
7
*
(
0
.
0
0
0
3
)
2
0
.
0
0
2
2
*
*
*
(
0
.
0
0
0
4
)
2
0
.
0
0
3
5
*
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
4
*
*
*
(
0
.
0
0
0
2
)
S
I
Z
E
2
0
.
0
0
8
7
*
*
(
0
.
0
0
3
9
)
0
.
0
5
5
3
(
0
.
0
5
1
7
)
2
0
.
3
8
9
7
*
*
*
(
0
.
0
9
7
0
)
2
0
.
2
2
6
8
(
0
.
1
6
9
3
)
2
0
.
3
1
6
2
*
*
*
(
0
.
0
2
2
3
)
I
N
T
E
R
C
E
P
T
4
.
8
4
6
6
*
*
*
(
0
.
0
2
6
1
)
2
0
.
9
5
2
6
*
(
0
.
4
5
0
5
)
3
.
0
3
1
2
*
*
*
(
0
.
6
6
4
4
)
3
.
5
8
5
1
*
*
*
(
0
.
2
5
4
5
)
2
.
7
4
4
7
*
*
*
(
0
.
1
4
0
1
)
R
2
0
.
1
5
0
9
0
.
0
6
2
4
0
.
0
8
7
4
0
.
0
3
0
7
0
.
1
3
3
2
N
o
.
o
f
o
b
s
.
8
2
1
8
2
1
8
2
1
8
2
1
8
2
1
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
i
n
s
t
r
u
m
e
n
t
v
a
l
i
d
i
t
y
w
a
s
a
s
c
e
r
t
a
i
n
e
d
b
y
c
h
e
c
k
i
n
g
t
h
a
t
t
h
e
i
n
s
t
r
u
m
e
n
t
s
a
r
e
h
i
g
h
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
P
R
I
V
_
S
H
A
R
E
b
u
t
w
e
a
k
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
t
h
e
r
e
s
i
d
u
a
l
s
.
N
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
–
w
h
i
c
h
f
o
r
e
a
c
h
r
e
g
r
e
s
s
i
o
n
i
s
i
n
s
t
r
u
m
e
n
t
e
d
u
s
i
n
g
l
a
g
s
o
f
o
t
h
e
r
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
,
?
s
c
a
l
d
e
?
c
i
t
a
n
d
s
t
o
c
k
m
a
r
k
e
t
i
n
d
e
x
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table AIII.
Partial privatization and
bank performance:
instrumental variables
(1987-2003)
JFEP
2,4
304
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
0
.
0
0
4
8
(
0
.
0
0
4
7
)
0
.
0
6
2
0
*
*
*
(
0
.
0
2
1
4
)
0
.
0
7
7
1
*
(
0
.
0
4
5
0
)
2
0
.
1
3
7
6
(
0
.
0
9
2
8
)
2
0
.
0
4
8
2
*
(
0
.
0
2
4
8
)
P
R
I
V
_
S
E
C
T
O
R
2
0
.
0
0
4
7
*
*
*
(
0
.
0
2
0
7
)
0
.
7
1
0
5
*
*
*
(
0
.
2
0
9
6
)
2
0
.
3
7
8
2
*
(
0
.
2
0
2
2
)
2
0
.
2
6
7
3
(
0
.
4
6
3
2
)
2
0
.
6
7
7
9
*
*
*
(
0
.
1
1
2
1
)
P
R
O
P
_
R
U
R
0
.
0
9
9
4
*
(
0
.
0
4
8
6
)
0
.
6
4
0
7
(
0
.
5
8
1
5
)
1
.
7
6
4
9
*
*
*
(
0
.
2
7
8
1
)
1
.
3
6
1
5
*
*
(
0
.
5
2
7
7
)
1
.
8
6
2
9
*
*
*
(
0
.
2
9
1
1
)
P
R
O
P
_
N
I
N
T
2
0
.
0
0
0
1
*
(
,
0
.
0
0
0
1
)
0
.
0
0
0
7
*
(
0
.
0
0
0
3
)
2
0
.
0
0
2
3
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
5
*
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
5
*
*
*
(
0
.
0
0
0
3
)
S
I
Z
E
2
0
.
0
1
0
8
*
*
(
0
.
0
0
4
0
)
0
.
0
6
3
4
(
0
.
0
5
3
9
)
2
0
.
3
4
2
1
*
*
*
(
0
.
0
7
9
8
)
2
0
.
2
1
9
2
(
0
.
1
7
7
7
)
2
0
.
2
9
0
0
*
*
*
(
0
.
0
2
7
1
)
I
N
T
E
R
C
E
P
T
4
.
8
4
3
2
*
*
(
0
.
0
3
1
8
)
2
0
.
8
6
2
6
*
(
0
.
4
5
1
9
)
2
.
6
8
0
1
*
*
*
(
0
.
3
2
8
8
)
3
.
2
7
2
9
*
*
*
(
0
.
3
7
9
4
)
2
.
2
3
9
0
*
*
*
(
0
.
1
1
6
6
)
R
2
0
.
8
1
0
1
0
.
1
7
2
2
0
.
1
3
3
9
0
.
0
5
2
1
0
.
1
7
4
4
F
t
e
s
t
f
o
r
n
o
?
x
e
d
e
f
f
e
c
t
s
1
1
1
.
9
4
*
*
*
4
.
9
2
*
*
*
3
.
4
2
*
*
*
1
.
4
3
*
2
.
0
1
*
*
*
N
o
.
o
f
o
b
s
.
8
2
1
8
2
1
8
2
1
8
2
1
8
2
1
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
y
e
a
r
?
x
e
d
e
f
f
e
c
t
s
w
e
r
e
i
n
c
l
u
d
e
d
i
n
a
l
l
r
e
g
r
e
s
s
i
o
n
s
b
u
t
a
r
e
n
o
t
r
e
p
o
r
t
e
d
t
o
c
o
n
s
e
r
v
e
s
p
a
c
e
.
I
n
s
t
r
u
m
e
n
t
v
a
l
i
d
i
t
y
w
a
s
a
s
c
e
r
t
a
i
n
e
d
b
y
c
h
e
c
k
i
n
g
t
h
a
t
t
h
e
i
n
s
t
r
u
m
e
n
t
s
a
r
e
h
i
g
h
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
P
R
I
V
_
S
H
A
R
E
b
u
t
w
e
a
k
l
y
c
o
r
r
e
l
a
t
e
d
w
i
t
h
t
h
e
r
e
s
i
d
u
a
l
s
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
–
w
h
i
c
h
f
o
r
e
a
c
h
r
e
g
r
e
s
s
i
o
n
i
s
i
n
s
t
r
u
m
e
n
t
e
d
u
s
i
n
g
l
a
g
s
o
f
o
t
h
e
r
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
,
?
s
c
a
l
d
e
?
c
i
t
a
n
d
t
h
e
B
S
E
i
n
d
e
x
.
A
t
w
o
-
s
t
a
g
e
e
s
t
i
m
a
t
i
o
n
p
r
o
c
e
d
u
r
e
i
s
u
s
e
d
f
o
r
t
h
e
i
n
s
t
r
u
m
e
n
t
a
l
v
a
r
i
a
b
l
e
b
y
m
o
d
e
l
i
n
g
t
h
e
p
r
i
v
a
t
i
z
a
t
i
o
n
d
e
c
i
s
i
o
n
i
n
t
h
e
?
r
s
t
s
t
a
g
e
a
n
d
t
h
e
q
u
a
n
t
u
m
o
f
p
r
i
v
a
t
i
z
a
t
i
o
n
i
n
t
h
e
s
e
c
o
n
d
s
t
a
g
e
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table AIV.
Partial privatization and
bank performance:
instrumental variables
with two stage estimation
(1987-2003)
Partial
privatization
and performance
305
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
o
g
(
T
F
P
)
O
P
R
N
I
M
O
C
R
S
E
R
P
R
I
V
_
S
H
A
R
E
(
L
E
A
D
)
0
.
0
0
0
9
(
0
.
0
0
0
6
)
0
.
0
2
4
1
*
*
*
(
0
.
0
0
6
5
)
0
.
0
2
0
7
(
0
.
0
1
3
9
)
0
.
0
0
1
2
(
0
.
0
0
4
2
)
0
.
0
0
0
8
(
0
.
0
0
5
2
)
P
R
I
V
_
S
H
A
R
E
0
.
0
0
1
7
*
*
*
(
0
.
0
0
0
4
)
2
0
.
0
0
8
3
(
0
.
0
0
5
8
)
2
0
.
0
0
2
8
(
0
.
0
0
5
6
)
2
0
.
0
0
4
9
(
0
.
0
0
7
5
)
2
0
.
0
0
2
3
(
0
.
0
0
5
1
)
P
R
I
V
_
S
E
C
T
O
R
2
0
.
0
9
4
1
*
*
*
(
0
.
0
1
7
2
)
0
.
6
7
3
9
*
*
*
(
0
.
1
9
6
6
)
2
0
.
3
3
7
1
*
(
0
.
1
8
1
6
)
2
0
.
0
6
0
8
(
0
.
5
4
9
3
)
2
0
.
5
8
0
9
*
*
*
(
0
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0
9
5
5
)
P
R
O
P
_
R
U
R
0
.
1
0
4
5
*
*
(
0
.
0
4
3
1
)
0
.
5
8
6
5
(
0
.
5
3
1
7
)
1
.
8
3
6
4
*
*
*
(
0
.
2
1
3
3
)
1
.
2
0
6
9
*
(
0
.
6
0
4
7
)
1
.
7
8
3
3
*
*
*
(
0
.
2
6
1
0
)
P
R
O
P
_
N
I
N
T
0
.
0
0
0
0
(
,
0
.
0
0
0
1
)
0
.
0
0
0
9
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
2
1
*
*
*
(
0
.
0
0
0
3
)
2
0
.
0
0
3
6
*
*
*
(
0
.
0
0
0
4
)
2
0
.
0
0
3
6
*
*
*
(
0
.
0
0
0
3
)
S
I
Z
E
2
0
.
0
1
3
7
*
*
*
(
0
.
0
0
4
2
)
0
.
0
5
5
0
(
0
.
0
5
0
2
)
2
0
.
3
4
4
2
*
*
*
(
0
.
0
7
0
7
)
2
0
.
2
0
8
6
(
0
.
1
8
6
2
)
2
0
.
2
8
0
7
*
*
*
(
0
.
0
3
0
5
)
I
N
T
E
R
C
E
P
T
4
.
8
1
0
6
*
*
*
(
0
.
0
2
4
1
)
2
0
.
7
1
8
2
*
(
0
.
3
9
2
8
)
2
.
7
5
0
3
*
*
*
(
0
.
2
3
4
2
)
2
.
8
6
5
4
*
*
*
(
0
.
5
2
6
2
)
2
.
0
8
7
9
*
*
*
(
0
.
1
2
1
2
)
R
2
0
.
1
8
3
0
0
.
0
5
5
0
0
.
0
8
7
4
0
.
0
1
4
3
0
.
1
0
1
4
N
o
.
o
f
o
b
s
.
7
8
8
7
9
9
7
9
9
7
9
9
7
9
9
N
o
t
e
s
:
S
t
a
t
i
s
t
i
c
a
l
l
y
s
i
g
n
i
?
c
a
n
t
c
o
e
f
?
c
i
e
n
t
s
a
t
l
e
v
e
l
s
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
,
r
e
s
p
e
c
t
i
v
e
l
y
;
n
u
m
b
e
r
s
i
n
p
a
r
e
n
t
h
e
s
e
s
a
r
e
r
o
b
u
s
t
s
t
a
n
d
a
r
d
e
r
r
o
r
s
(
H
u
b
e
r
-
W
h
i
t
e
)
;
t
h
e
?
v
e
p
e
r
f
o
r
m
a
n
c
e
i
n
d
i
c
a
t
o
r
s
a
r
e
r
e
g
r
e
s
s
e
d
o
n
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
s
h
a
r
e
s
h
e
l
d
b
y
t
h
e
p
r
i
v
a
t
e
o
w
n
e
r
s
(
P
R
I
V
_
S
H
A
R
E
)
–
c
o
n
s
i
d
e
r
e
d
c
o
n
t
e
m
p
o
r
a
n
e
o
u
s
l
y
a
s
w
e
l
l
a
s
p
l
a
c
e
b
o
l
e
a
d
s
v
i
z
.
t
h
e
v
a
l
u
e
o
f
t
h
e
v
a
r
i
a
b
l
e
i
n
t
h
e
n
e
x
t
p
e
r
i
o
d
.
P
a
n
e
l
r
e
g
r
e
s
s
i
o
n
t
e
c
h
n
i
q
u
e
(
w
i
t
h
i
n
e
f
f
e
c
t
s
)
i
s
e
m
p
l
o
y
e
d
t
o
e
s
t
i
m
a
t
e
t
h
e
m
o
d
e
l
Table AV.
Partial privatization and
bank performance:
placebo leads (1986-2002)
JFEP
2,4
306
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
This article has been cited by:
1. Dhananjay Bapat, Deepa Mazumdar. 2015. Assessment of business strategy: implication for Indian banks.
Journal of Strategy and Management 8:4, 306-325. [Abstract] [Full Text] [PDF]
2. Mohammad Alipour. 2013. Has privatization of state-owned enterprises in Iran led to improved
performance?. International Journal of Commerce and Management 23:4, 281-305. [Abstract] [Full Text]
[PDF]
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
3
9
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
doc_274023951.pdf