An empirical analysis of cost efficiencies in the Indian banking industry.
Malhotra, D.K. ; Poteau, Raymond ; Malhotra, Ashok 等
I. INTRODUCTION
The banking industry in India has come a long way from the
nationalization of its banks in 1969 to the liberalization of the
financial system since 1991. During the reform process that started in
1991, the banking sector was opened up with the objective of improving
the efficiency of the banking system in India through increased
competition from private and foreign banks. With this view, the
government initiated the process of removing interest rate controls. The
government also introduced capital adequacy requirements and other
safety norms to ensure a sound banking system. The objective is to
strengthen banking supervision and increase competition through
licensing of private banks and foreign banks. The ultimate goal is to
integrate Indian banks into the global financial system.
Although the amount of assets and deposits managed by the Indian
banking industry has increased several folds, empirical research on
economies of scale and cost efficiencies in the Indian banking industry
is still limited. The issue of economies of scale and cost efficiencies
in the banking industry is important for several reasons.
Firstly, the Indian economy is the second fastest growing economy
in the world after China. Since these nations represent an engine of
growth for the world economy, a large amount of capital is flowing to
the stock markets of these nations. Banks, as financial intermediaries,
are playing a crucial role by bringing enhanced liquidity and promoting
market efficiency by facilitating smooth transfer of funds between
borrowers and lenders that will promote capital mobility among nations.
A sound and efficient banking system is essential for a smooth
integration of Indian financial markets with the rest of the world,
because banks play a crucial role in facilitating transfer of funds
between borrowers and lenders. Therefore, the size of the banking system
is bound to grow further.
Secondly, previous studies show that a country's financial
sector influences future economic growth. The banking sector is the most
important part of the financial markets. If the Indian banking sector is
sound and efficient, it will have a positive impact on India's
growth.
Thirdly, we examine the cost efficiencies of Indian commercial
banks during the period 2007 to 2013. This time period covers
"before-crisis" and "after-crisis" time. Findings
from this study will highlight the cost behavior of the Indian banking
sector during and after the global financial crisis.
This study will also help the banking industry as well as
regulatory agencies such as the Reserve Bank of India (RBI) get a better
understanding of the impact of growth of a bank on a bank's
expenses and its benefits to bank shareholders in the form of higher
returns and increased shareholder wealth.
We distinguish our study from previous studies in two ways.
Firstly, this study provides a more comprehensive view of the cost
efficiencies in the Indian banking sector. Cost efficiency studies
require specifications of input and output variables. This study
evaluates cost efficiencies by studying economies of scale not only in
total cost, but also in each component of the total cost. Specifically,
we evaluate economies of scale in operating cost, non-operating cost,
interest expenses, and employee cost. By studying each component of the
total cost, we will be able to identify the source of cost efficiencies
in total cost. Furthermore, we estimate cost efficiencies with respect
to output and output is defined in three different ways--total assets,
total deposits, and total loans. Secondly, this study covers the period
of the global financial meltdown and we evaluate the cost efficiencies
of the Indian banks during and after this meltdown.
This paper has six sections. Section II provides a discussion of
previous research related to this topic. Section III briefly describes
our data. Section IV describes our methodology and gives information on
banks used in this study. Section V presents our empirical results.
Section VI gives our conclusions.
II. PREVIOUS RESEARCH
Several studies have examined economies of scale in the banking
industry. Edirisuriya and O'Brien (2001) studied economies of scale
for Australian banks after financial deregulation. They found evidence
of economies of scale and scope in four major Australian banks. Toby
(2006) reviewed previous studies on economies of scale in the banking
industry and concludes that smaller banks are more efficient in
comparison to larger banks in most countries. Stimpert and Laux (2011)
reported that while costs decline and profitability increases as bank
size increases, these relationships do not hold indefinitely and
diseconomies of scale are experienced by larger banks. When size is
measured by total assets, larger banks begin to encounter lower levels
of net income, but the very largest banks are able to enjoy net income
that increases at an increasing rate as size increases. When size is
measured by total deposits, net income increases at an increasing rate
for a wide range of bank sizes and only begins to decrease for the
largest banks. McNulty (2000) measured economies of scale for six large
Canadian banks. He reported economies of scale in Canadian banking
industry due to technological and regulatory changes. Margono and Sharma
(2010) estimated cost efficiency, economies of scale, technological
progress, and productivity growth among Indonesian banks from 1993 to
2000. They found that average cost efficiency for the banking sector
over this period was 70%. They also reported a marked difference in cost
efficiency before and after the Asian economic crisis. The banking
sector cost efficiency was 80% prior to the crisis and 53% after the
crisis. Moreover, results indicated that private-owned banks and joint
venture/foreign banks were more efficient than public-owned banks. They
attributed cost reductions attributed to technological progress and
economies of scale. Kasman (2005) examined the cost efficiency and scale
economies of banks operating in Poland and the Czech Republic during the
period from 1995 to 2000. They found that Polish banks are, on average,
more efficient than Czech banks. The study also suggested that foreign
banks operating in the Czech banking sector had significantly higher
efficiency levels than those of domestic banks. They also reported
evidence of significant economies of scale for small and medium-sized
banks, but diseconomies of scale for large-sized banks. Das and Das
(2007) used a multi-product Fourier flexible cost function specification
to investigate scale economies, cost complementarities and technical
progress of Indian banks during the post reform period 1992 to 2003. The
empirical results indicate that there exist significant economies of
scale for all size classes of banks and there is no evidence of
diseconomies of scale, even for larger banks. Ray (2007) evaluated the
size efficiency, as distinct from scale efficiency, of Indian banks. He
found that often a bank is operating in the region of diminishing
returns to scale but is not a candidate for break up.
III. DATA
Data covers the fiscal year ending March 31st 2007 to March 31st
2013. The data sample consists of 20 state owned banks and 15 private
sector banks for each year in the sample except for 2012 and 2013. In
2012 and 2013, we have 14 private sector banks. Table 1 provides a
summary statistics of the variables used in this study. (1)
During the period 2007 to 2013, on an average:
* Total expenses have gone up by more than 230 percent for the
banks as a whole (229 percent for public sector banks and 221 percent
for private sector banks);
* Operating expenses have increased by 120 percent (108 percent for
public sector banks and 144 percent for private sector banks);
* Non-operating expenses have increased by 279 percent (279 percent
for public sector banks and 259 percent for private sector banks);
* Interest cost that represents of cost of funds for banks has gone
up by 280 percent (280 percent for public sector banks and 261 percent
for private sector banks);
* Employee cost has gone up by 165 percent (140 for public sector
banks and 265 percent for private sector banks);
* Total assets have increased by 196 percent (192 percent for
public sector banks and 191 percent for private sector banks);
* Total deposits have gone up by 195 percent (196 percent for
public sector banks and 174 percent for private sector banks), and
* Loans have gone up by 215 percent (218 percent for public sector
banks and 200 percent for private sector banks).
Thus, there is more than proportionate increase in total expenses
relative to assets, deposits, and loans. Most of the increase in total
expenses is due to increase in non-operating expenses that have gone up
by 279 percent during the period 2007 to 2013. Operating expenses, on an
average, show a lower percentage increase relative to increase in
assets, deposits, and loans.
As shown in Table 1, during the period 2007-2013, percentage
increase in total expenses, non-operating expenses, and interest cost is
higher for public sector banks, but operating expenses have gone up more
at private sector banks relative to public sector banks. Public sector
banks also show a relatively higher increase in total assets, total
deposits, and loans in comparison to private sector banks. Employee cost
has gone up significantly more for private sector banks in comparison to
public sector banks during the seven-year period of 2007 to 2013.
IV. METHODOLOGY
Our methodology involves estimation of the coefficients of a
translog cost function to determine which factors contribute to
economies of scale and their degree of contribution. We then estimate
cost elasticity with respect to the amount of assets using the first
derivative of the translog cost function. Cost elasticity is estimated
for the total sample for each year and for subsets of the annual
samples. The subsets are created according to ownership of the bank.
In order to investigate economies of scale in banks, we use a
two-part methodology. The first part is an estimation of coefficients
for a translog cost function to determine which factors contribute to
economies of scale and the extent to which they contribute for each of
the even years in the period 2007 to 2013. We estimate economies of
scale for total expenses of a bank and also with respect to each
component of the total expenses, namely operating expenses,
non-operating expenses, interest expense (cost of funds), and employee
cost.
The second part is an estimation of coefficients for a translog
cost function using the panel data approach. The panel data approach
allows for pooling of observations on a cross-section of banks over
seven years. When observations possess the double dimension (cross
section and time series), the crucial aspect of the problem is to have a
clear understanding of how differences in behavior across individuals
and/or through time could and should be modeled. A panel data set offers
several econometric benefits over traditional pure cross section or pure
time series data sets. The most obvious advantage is that the number of
observations is typically much larger in panel data, which will produce
more reliable parameter estimates and, thus, enable us to test the
robustness of our linear regression results. Panel data also alleviates
the problem of multicollinearity, because when the explanatory variables
vary in two dimensions (cross-section and time series), they are less
likely to be highly correlated. Panel data sets make it possible to
identify and measure effects that cannot be detected in pure cross
section or time series data. For instance, sometimes it is argued that
cross section data reflect short-run behavior, while time series data
emphasize long-run effects. By combining the cross-section and time
series features of a data set, a more general and comprehensive dynamic
structure can be formulated and estimated. The use of panel data
suggests that individuals, firms, states, or countries are heterogeneous
(Balestra 1995). Time series and cross-section studies not controlling
for this heterogeneity run the risk of obtaining biased results (Baltagi
2000). Panel data controls for individual heterogeneity.
The most intuitive way to account for individual and/or time
differences in the context of panel data regression is to use the fixed
effects model. The fixed effect model assumes that difference across
banks can be captured in differences in the constant term. The
regression coefficients (the slope parameters) across groups in this
model are unknown, but fixed parameters. It is also known as the least
square dummy variable (LSDV) model and we use the LSDV fixed-effect
model to estimate cost efficiencies in the Indian banking industry.
A. Translog Cost Function (2)
In financial economics, the translog model is the most pervasive
approach for investigating economies of scale. (3) The translog cost
model implicitly assumes a U-shaped average cost function. It is used
here because it allows economies of scale to vary with level of bank
assets.
The estimation of scale economies with a translog cost function
requires cost and output measures. For the banking industry, the output
in this paper has been defined in three different ways:
* Total assets
* Total deposits
* Loans
Total cost of each bank is defined as the total expenses of a bank.
A bank's total expense is modeled as a function of total assets and
control variables that affect level of expenses.
We use translog cost function to estimate economies of scale in the
Indian banking industry. Ordinary least squares (OLS) regression is used
to find coefficients of the independent variables. Equations 1a to 1c
show the translog cost functions to estimate economies of scale for the
Indian banks (See Latzko, 1999).
Ln COST = [[beta].sub.0] + [[beta].sub.1] Ln ASSETS + 1/2
[[beta].sub.2] [(Ln ASSETS).sup.2] + [[SIGMA].sub.j] [[beta].sub.j]
[X.sub.j] + e (1a)
Ln COST = [[beta].sub.0] + [[beta].sub.1] Ln DEPOSITS + 1/2
[[beta].sub.2] [(Ln DEPOSITS).sup.2] + [[SIGMA].sub.j] [[beta].sub.j]
[X.sub.j] + e (1b)
Ln COST = [[beta].sub.0] + [[beta].sub.1] Ln LOANS + 1/2
[[beta].sub.2] [(Ln LOANS).sup.2] + [[SIGMA].sub.j] [[beta].sub.j]
[X.sub.j] + e (1c)
In the translog function, definition of COST depends on the input
variable with respect to which we are computing economies of scale.
Therefore, cost can be the dollar amount of a bank's total
expenses, operating expenses, non-operating expenses, total interest
expenses, and employee cost. In Equation 1a, ASSETS represent the total
assets under management at a bank. Equation 1b shows the translog cost
function to estimate economies of scale with reference to total deposits
of a bank. Equation 1c shows the translog cost function to estimate
economies of scale with reference to loans made by banks. [X.sub.j]
includes control factors that affect the costs of management and
administration of a bank. In equation 1a, we do not use any control
variables. In Equations 1b and 1c, we use size of the bank as measured
by total assets as control variables.
B. Cost Elasticity
The most common measure of operating efficiency in economies of
scale studies is the elasticity of cost with respect to the output. When
the rate of increase in output exceeds the rate of increase in cost in
an industry, economies of scale characterize that industry. For the
banking industry, cost elasticity with respect to assets can be used to
evaluate the existence and extent of economies of scale. It is measured
by percentage change in cost associated with a percentage change in bank
assets. We calculate this elasticity by taking the first derivative of
the translog cost function (Equation 1) with respect to assets. The
result is Equation 2.
[partial derivative](Ln COST)/[partial derivative](Ln ASSETS) =
[[beta].sub.1] + [[beta].sub.2] (Ln ASSETS) (2a)
[partial derivative] (Ln COST)/[partial derivative](Ln DEPOSITS) =
[[beta].sub.1] + [[beta].sub.2](Ln DEPOSIT S) (2b)
[partial derivative] (Ln COST)/[partial derivative] (Ln LOANS) =
[[beta].sub.1] + [[beta].sub.2] (Ln LOANS) (2c)
where COST can represent total expenses, total operating expenses,
total non-operating expenses, interest expenses, or employee cost of a
bank in Equations 2a to 2c. ASSETS represent total assets of a bank in
Equation 2a, DEPOSITS are total deposits of a bank in Equation 2b, and
LOANS are total loans made by a bank in Equation 2c.
If cost elasticity is less than one, bank's expenses increase
less than proportionately with changes in bank assets. This implies that
economies of scale exist. If the elasticity is greater than one, we can
infer that diseconomies of scale exist.
To investigate the existence of economies of scale, we estimate the
scale economy measure for each observation and then average across
observations to derive the group scale economy measure. The cost
elasticity is found for each observation (bank). Then an average across
observations is computed to obtain the group average elasticity.
We estimate cost elasticities for the total group of banks in each
annual sample. We also estimate elasticities for groups within each
annual sample where the groupings are according to ownership--private
sector or public sector banks.
V. EMPIRICAL RESULTS
A. Cost Function
Regression results for total annual samples of banks are shown in
Table 2. Some of the results are as expected, while others are not.
Model 1 in Table 2 shows that our model in equation 1 explains 98%
to 99% of the total expenses of a bank. Table 2 shows that size of the
bank as measured by assets is positively related to total expenses. As
bank size grows, total expenses also increase and the coefficient on
natural logarithm of assets is statistically significant in explaining
the total expenses. Ownership structure does not play a statistically
significant role in explaining total expenses of a bank. Cost elasticity
ranges between 0.92 in 2010 and 1.05 in 2007 and it is statistically
significant for each year in our sample. Cost elasticity in 2007 is
1.05, which means that for every rupee increase in assets, total
expenses increased by 1.05 rupees, which points to diseconomies of
scale. In six out of seven years, Indian banks have statistically
significant cost elasticity below 1, which points to economies of scale
for Indian banks. Panel data also shows that there are cost efficiencies
in terms of lower expenses for Indian banks, because cost elasticity for
the entire sample is below 1 and it is statistically significant.
The panel data model in Table 2 also shows that operating expenses
are impacted by ownership structure in a statistically significant
manner. Public sector banks have lower operating expenses in comparison
to private sector banks. There are economies of scale with respect to
operating expenses in 2011 and 2013 only. However, panel data shows that
there is cost efficiency associated with total assets of a bank, because
the cost elasticity is 0.96 for the panel data and it is statistically
significant. On an average, for every rupee increase in total assets,
total cost increased less than proportionately for Indian banks during
the period 2007 to 2013.
As the size of the bank as measured by total assets increases,
non-operating expenses are rising less than proportionately as is
evidenced by below 1 cost elasticity throughout the sample period. Panel
data also confirms that there is cost efficiency associated with
non-operating expenses, interest rates, and employee costs, because the
cost elasticity is below 1 and is statistically significant throughout
the sample period. Panel data regression results in Table 2 show that
public sector banks have a statistically significantly lower operating
cost in comparison to private sector banks. On the other hand, public
sector banks have a higher non-operating cost and interest expenses
relative to private sector banks. Ownership structure does not impact
employee cost in a statistically significant manner.
Table 3 shows the regression results for the translog cost function
for cost efficiencies for Indian banks with respect to total deposits of
a bank with size of the bank as measured by total assets as a control
variable.
On an average, our model explains 97% to 99% of the total expenses
of a bank with respect to total deposits of a bank. Natural logarithm of
deposits is positively related to the total expenses of a bank for each
year in the sample and the relationship is statistically significant in
all years except for the year 2009. Ownership structure plays a role in
determining the total expenses of a bank, with a negative coefficient on
the public sector banks reporting lower total expenses relative to
private sector banks.
Cost elasticity is less than one for every year from 2007 to 2013
except for the year 2009, which points to economies of scale in total
expenses for Indian commercial banks with respect to deposits of the
banks. Highest economies of scale are experienced in 2007 with a cost
elasticity of 0.79, which means for every rupee increase in deposits,
total expenses, on an average, increased by 0.79 rupees only. In 2009,
the cost elasticity is 1.01 and it points to diseconomies of scale for
that year with respect to deposits. However, the panel data results show
overall there are economies of scale in total expenses with respect to
deposits for the pooled sample of 2007 to 2013 with a highly
statistically significant cost elasticity of 0.95.
Table 3 also shows that public sector banks have statistically
significant lower operating cost relative to private sector banks.
Furthermore, there are cost efficiencies in operating expenses,
non-operating expenses, interest expenses, and employee costs with
respect to total deposits of a bank. Panel data shows that the cost
elasticity is below 1 and it is statistically significant for operating
expenses, non-operating expenses, interest expenses, and employee costs.
Table 4 evaluates cost efficiencies for Indian commercial banks
with respect to loans with total assets of the bank as a control
variable. Our model explains, on an average, 98 percent to 99 of total
expenses of a bank with respect to loans of a bank. Total expenses are
positively related to total loans for each year in the sample from 2007
to 2013. Panel data also shows that the relation between total expenses
and total loans is positive and is statistically significant. The
coefficient on natural logarithm of loans is below 1 for the year 2007
to 2010, which means that for every rupee increase in loans, total
expenses increase by less than one, but in 2011, 2012, and 2013 the
coefficient on natural logarithm of loans is more than one, which
implies that for every one rupee increase in loans, total expenses
increase by more than a rupee. Ownership structure plays a role in
influencing total expenses of a bank. Public sector banks have lower
total expenses relative to private sector banks.
In 2007, cost elasticity equals one, but is not statistically
significant and in 2008, cost elasticity of total expenses to total
loans is 1.03 and is statistically significant. In all other years in
the sample, cost elasticity is below one and statistically significant.
Panel data results show that during the sample period of 2007 to 2013,
the cost elasticity is below one at 0.92 and there are cost efficiencies
in total expenses with respect total loans for Indian commercial banks.
Table 4 also shows that public sector banks have lower operating
expenses relative to private sector banks. Ownership structure does not
play a statistically significant role in influencing the non-operating
expenses, interest expenses, and employee cost with respect to total
loans of a bank.
Panel data results shows cost efficiencies for Indian banks in
operating expenses, non-operating expenses, interest expenses, and
employee cost, because the cost elasticity is below one and is
statistically significant.
B. Economies of Scale by Ownership
Table 5 shows cost elasticity of total expenses, operating
expenses, non-operating costs, interest expenses, and employee cost with
respect to total assets, total deposits, and total loans when we analyze
economies of scale by bank ownership.
On an average, cost elasticity of total expenses with respect to
total assets is less than one for public and private sector banks and is
statistically significant for each year in the sample since 2009. Total
expenses of public and private sector banks do not increase in the same
proportion as the increase in assets, which points to economies of scale
throughout the sample period. Panel data shows that both public and
private sector banks have same cost elasticity of total expenses with
respect to total assets at 0.96.
For each year in the sample, private sector banks report higher
cost efficiencies over public sector banks. Panel data results show that
cost elasticity of operating expenses with respect to total assets for
public sector banks is 0.99 and for private sector banks is 0.94.
Private sector banks show more cost efficiencies relative to public
sector banks for every rupee increase in total assets.
As per panel data, interest expenses of public sector banks do not
increase at the same rate as the interest expenses of private sector
banks. The cost elasticity for public sector banks is 0.92 and the cost
elasticity for interest expenses is 0.94 for private sector banks.
Therefore, for every one rupee increase in total assets, public sector
banks' cost of funds, on an average, is 2 basis points lower than
private sector banks. With regard to employee cost, private sector banks
enjoy higher cost efficiency than public sector banks, which points to
higher employee productivity for private sector banks over public sector
workers.
Both public and private sector banks enjoy cost efficiencies with
regard to total deposits with cost elasticity at less than one. With
increase in deposits, total expenses, operating expenses, non-operating
expenses, interest expenses, and employee cost rise less than
proportionately. With regard to deposits, panel data results show that
public sector banks enjoy higher cost efficiencies in total expenses,
non-operating expenses, interest expenses, and employee cost relative to
private sector banks. Private sector banks show higher cost efficiencies
in operating expenses with regard to total deposits over public sector
banks.
The panel data results in Table 5 show that private sector banks
attain cost efficiencies in total expenses, operating expenses,
non-operating expenses, interest expenses, and employee cost with
respect to total loans for each year in sample. Panel data model shows
that cost efficiencies in total expenses, non-operating expenses,
interest expenses, and employee cost with respect to loans are higher
for public sector banks over private sector banks. In operating
expenses, the panel data model shows that private sector banks are more
efficient for every rupee increase in loans. In fact, for public sector
banks, every rupee increase in loans is accompanied by a 1.01 increase
in operating expenses.
VI. SUMMARY AND CONCLUSIONS
India started the process of economic reforms and opened up its
banking sector in 1991. The goal was to improve the efficiency of the
Indian banking sector with an aim to integrate into the global financial
sector. This study analyzed the cost efficiencies of Indian commercial
banks over the period 2007 to 2013. We used the translog cost function
to evaluate economies of scale in the Indian banking sector. The
translog cost function was estimated for total cost as well as for each
component of total cost, namely operating cost, non-operating cost,
interest expenses, and employee cost. We estimated cost efficiencies
with respect to output and output was defined in three different
manners--total assets, total deposits, and total loans. Estimates of
cost elasticity showed that Indian commercial banks are reaping
economies of scale when output is measured in terms of total assets of a
bank. This study showed that total cost increases less than
proportionately to increase in assets, which points to economies of
scale with reference to assets. This study also found evidence of cost
efficiencies in operating expenses, non-operating expenses, interest
expenses, and employee cost when the size of the bank as measured by
total assets rises.
When output is measured in terms of total deposits and total loans,
Indian banks continue to enjoy cost efficiencies with less than
proportionate increases in total expenses, operating expenses,
non-operating expenses, interest expense, and employee cost with every
rupee increase in total deposits.
Results also show that ownership structure of a bank plays a role
in determining cost efficiencies in the Indian banking industry. The
study found that private sector banks spend less on employee cost for
every rupee increase in assets, which points to higher efficiency or
productivity for private sector employees.
When output is measured in terms of deposits, public sector banks
enjoy higher cost efficiencies in total expenses, non-operating costs,
interest expenses, and employee costs. For every rupee increase in
deposits, public sector banks spend less in comparison to private sector
banks. Public sector banks have branches all over India including rural
India and it is easier for them get deposits in comparison to private
sector banks. When output is measured in terms of loans, public sector
banks continue to enjoy slightly higher cost efficiencies than their
private sector counterparts except in operating expenses.
REFERENCES
Allen, J., and Y. Liu, 2007, "Efficiency and Economies of
Scale of Large Canadian Banks." The Canadian Journal of Economics,
40, 225-244.
Arrow, K., H. Chenery, B. Minhas, and R. Solow, 1961,
"Capital-Labor Substitution and Economic Efficiency." Review
of Economics and Statistics, 45, 225-247.
Altunbas, Y., and P. Molyneuz, 1996, "Economies of Scale and
Scope in European Banking." Applied Financial Economics, 6,
367-375.
Balestra, P., 1995, "Introduction to Linear Models for Panel
Data." The Econometrics of Panel Data--A Handbook of the Theory
with Applications, edited by Laszlo Matyas and Patrick Sevestre, Kluwer
Academic Publishers.
Baltagi, B., 2000, Econometric Analysis of Panel Data, John Wiley
and Sons, England.
Bers, M., and T. Springer, 1997, "Economies of Scale for Real
Estate Investment Trusts." Journal of Real Estate Research, 14,
275-290.
Clark, J., and P. Speaker, 1994, "Economies of Scale and Scope
in Banking: Evidence from a Generalized Translog Cost Function."
Quarterly Journal of Business and Economics, 33, 3- 25.
Das, A., and S. Das, 2007. "Scale Economies, Cost
Complementarities and Technical Progress in Indian Banking: Evidence
from Fourier Flexible Functional Form." Applied Economics, 39, 565
Dermine, J., and L. Roller, 1992, "Economies of Scope and
Scale in French Mutual Funds." Journal of Financial Intermediation,
2, 83-93.
Drake, L., 1992, "Economies of Scale and Scope in UK Building
Societies: An Application of the Translog Multiproduct Cost."
Applied Financial Economics, 2, 211-219.
Edirisuriya, P., and G. O'Brien, 2001, "Financial
Deregulation and Economies of Scale and Scope: Evidence from the Major
Australian Banks." Asia--Pacific Financial Markets, 8, 197-197.
Goldberg, L., G. Hanweck, M. Keenan, and A. Young, 1991,
"Economies of Scale and Scope in the Securities Industry."
Journal of Banking and Finance, 15, 91-107.
Kasman, A., 2005, "Efficiency and Scale Economies in
Transition Economies: Evidence from Poland and the Czech Republic."
Emerging Markets, Finance & Trade, 41, 60-81
Kmenta, J., 1967, "On estimation of the CES production
function." International Economic Review, 8, 180-189.
Lang, G., and P. Welzel, 1996, "Efficiency and Technical
Progress in Banking: Empirical Results for a Panel of German Cooperative
Banks." Journal of Banking and Finance, 20, 1003-1023.
Latzko, D., 1999, "Economies of Scale in Mutual Fund
Administration." Journal of Financial Research, 22, 331-339
Margono, H., S. Sharma, and P. Melvin, 2010, "Cost Efficiency,
Economies of Scale, Technological Progress and Productivity in
Indonesian Banks." Journal of Asian Economics, 21, 53
McNulty, J., J. Verbrugge, and D. Blackwell, 1995, "Thrift
Scale Economies: An Alternative Approach." Quarterly Journal of
Business and Economics, 34, 47-59.
McNulty, J. 2000, "Another Look at Scale Economies at Large
Commercial Banks." American Business Review, 18, 96-104.
Noulas, A., S. Miller, and S. Ray, 1993, "Regularity
Conditions and Scope Estimates: The Case of Large U.S. Banks."
Journal of Financial Services Research, 7, 235-248.
Noulas, A., S. Ray, and S. Miller, 1990, "Returns to Scale and
Input Substitution for Large U.S. Banks." Journal of Money, Credit,
and Banking, 22, 94-108.
Ray, S., 2007, "Are Some Indian Banks Too Large? An
Examination of Size Efficiency in Indian Banking." Journal of
Productivity Analysis, 27, 41-56
Stimpert, J., and J. Laux, 2011, "Does Size Matter? Economies
of Scale in the Banking Industry." Journal of Business and
Economics Research, 9, 47-55
Toby, A., 2006, "Methodological Approach to the Study of
X-Efficiencies and Scale Economies in Banking: Are Smaller Banks More
Efficient Than Larger Banks?" Journal of Financial Management &
Analysis, 19, 85-96.
Zumpano, L., and H. Elder, 1994, "Economies of Scope and
Density in the Market for Real Estate Brokerage Services." Journal
of American Real Estate and Urban Economics Association, 22, 497-513.
ENDNOTES
(1.) Bank of Rajasthan, a private-sector bank, merged with ICICI
bank. Therefore, we have only 14 private sector banks in 2012 and 2013.
(2.) A translog cost function is a Taylor series expansion for
estimating the dual of a Cobb-Douglas production function. In the area
of models of producer behavior, the paper by Arrow, Chenery, Minhas, and
Solow (1961) calls into question the inherent restriction of the
Cobb-Douglas model that all elasticities of factor substitution are
equal to 1. Researchers have since developed numerous flexible functions
that allow substitution to be unrestricted. The transcendental
logarithmic, or translog, function is the most frequently used flexible
function in empirical work. The function was developed by Kmenta (1967)
as a means of approximating the production function. According to
Guilkey, Lovell, and Sickles (1983), a translog function is the most
reliable of the several available alternatives. Typically, translog cost
function includes input prices.
(3.) Many studies have used translog cost functions to study
economies of scale in the financial services industry. These include
studies by Bers, Springer, and Thomas (1990) (real estate investment
trusts), Goldberg, Hanweck, Keenan, and Young (1991) (securities
industry), Drake (1992) (U.K. Building societies), Noulas, Miller, and
Ray (1993) (large sized U.S. banks), Zumpano and Elder (1994) (real
estate brokerage services), Clark and Speaker (1994) (banking industry),
McNulty, Verbrugge, and Blackwell (1995) (thrifts), Altunbas and
Molyneuz (1996)(French, German, Italian, and Spanish banking markets),
Lang and Welzel (1996) (German cooperative banks), and Latzko (1999).
D.K. Malhotra [a], Raymond Poteau [b], Ashok Malhotra [c]
[a] Professor of Finance, Philadelphia University, Philadelphia, PA
19144 MalhotraD@philau.edu
[b] Professor of Accounting, Philadelphia University, Philadelphia,
PA 19144 PoteauR@philau.edu
[c] Associate Professor, Birla Institute of Management Technology,
India ashok.malhotra@bimtech.ac.in
Table 1
Descriptive statistics for the variables used in this study
Overall Sample 2007 2008 2009 2010
Number of Banks 35 35 35 35
Total Expenses 5,840.5 7,634.5 9,695.5 10,494.8
8,065.0 10,045.0 12,364.6 13,466.3
Operating Expenses 1,751.5 2,024.2 2,465.7 3,049.7
2,569.1 2,935.2 3,491.9 4,441.2
Non-Operating 4,089.0 5,610.4 7,393.7 7,445.2
Expenses 5,520.9 7,156.3 9,043.3 9,148.3
Interest Cost 3,477.9 5,002.3 6,584.9 6,755.8
4,608.9 6,375.4 7,968.6 8,349.9
Employee Cost 830.5 904.0 1,134.2 1,316.1
1,359.9 1,346.2 1,690.1 2,139.3
Assets 81,455 101,877 124,683 144,224
107,470 133,386 169,673 185,819
Deposits 64,710 79,690 99,499 116,486
81,307 97,294 128,919 141,389
Loans 47,419 59,220 75,353 86,400
63,445 77,115 97,698 110,858
Public Sector Banks
Number of Banks 20 20 20 20
Total Expenses 7,558.1 9,658.7 12,443.9 14,014.4
8719.7 10,584.1 13,790.6 15,741.1
Operating Expenses 2,195.8 2,408.2 2,880.6 3,762.1
2771.8 3,056.9 3,790.0 5,208.3
Non-Operating 5,362.3 7,250.5 9,563.3 10,252.3
Expenses 5,977.6 7,560.8 6,354.5 10,611.1
Interest Cost 4,535.0 6,472.9 8,501.2 9,350.9
4,807.2 6,515.1 5,810.4 9,655.9
Employee Cost 1,209.0 1,250.3 1,524.3 1,849.8
1,683.9 1,649.0 679.4 2,673.5
Assets 107,027 133,315 167,592 195,799
116686 147,937 198,895 218,387
Deposits 87,095 107,416 137,978 163,490
90,354 110,232 152,512 165,605
Loans 63,212 78,847 100,309 120,185
69,641 85,730 57,234 130,943
Private Sector Banks
Number of Banks 15 15 15 15
Total Expenses 3,550.3 4,935.6 6,030.8 5,802.1
6,704.0 8,922.0 9,381.2 7,926.8
Operating Expenses 1,159.0 1,512.1 1,912.4 2,099.8
2,223.5 2,783.7 3,089.5 3,065.2
Non-Operating 2,391.3 3,423.5 4,118.5 3,702.3
Expenses 4,486.3 6,150.3 6,354.5 4,917.0
Interest Cost 2,068.4 3,041.5 3,690.4 3,295.7
4,062.1 5,822.1 5,810.4 4,510.1
Employee Cost 325.8 442.3 552.9 604.5
406.7 557.9 679.4 682.1
Assets 47,358 59,960 67,471 75,457
85,971 101,056 100,454 101,307
Deposits 34,862 42,722 48,194 53,814
57,488 62,737 62,135 62,967
Loans 26,362 33,051 37,881 41,354
48,602 56,420 57,234 52,646
Overall Sample 2011 2012 2013
Number of Banks 35 34 34
Total Expenses 12,284.4 16,647.2 19,336.0
15,451.4 19310.4 21,664.6
Operating Expenses 3,767.2 3,856.3 3,852.2
5,375.9 4,577.9 5,207.3
Non-Operating 8,517.1 12,790.9 15,483.8
Expenses 10,154.5 14,809.5 16,616.5
Interest Cost 7,488.2 11,075.1 13,214.1
8,684.7 11,541.5 13,540.9
Employee Cost 1,742.5 1,942.5 2,200.2
2,478.0 2,894.6 3,152.2
Assets 173,948 208,723 240,795
218,184 242,417 281,651
Deposits 140,450 165,835 191,036
166,452 188,559 216,668
Loans 106,107 130,449 149,220
134,369 155,309 186,965
Public Sector Banks
Number of Banks 20 20 20
Total Expenses 1,6533.3 21,764.4 24,884.8
1,8264.7 10,728.1 24,904.1
Operating Expenses 4,942.7 4,856.4 4,567.7
6,514.8 2,845.2 6,106.6
Non-Operating 11,590.6 16,908.0 20,317.1
Expenses 11,823.5 7,962.2 18,879.7
Interest Cost 10,303.3 14,681.5 17,233.2
10,019.2 6,548.7 15,362.7
Employee Cost 2,420.2 2,578.6 2,907.1
3,043.1 1,142.3 3,852.0
Assets 235,360 271,804 312,978
256,139 144,762 325,709
Deposits 196,360 224,683 257,869
194,193 88,420 250,667
Loans 146,388 174,460 200,905
158,759 78,301 222,213
Private Sector Banks
Number of Banks 15 14 14
Total Expenses 6,619.1 9,337.1 11,409.3
8,178.7 10,728.1 13,036.3
Operating Expenses 2,199.9 2,427.6 2,830.2
2,825.0 2,845.2 3,524.1
Non-Operating 4,419.1 6,909.4 8,579.1
Expenses 5,404.7 7,962.2 9,625.5
Interest Cost 3,734.6 5,923.0 7,472.5
4,530.0 6,548.7 7,755.4
Employee Cost 838.9 1,033.8 1,190.3
902.0 1,142.3 1,292.1
Assets 92,064 118,607 137,677
118,322 144,762 163,867
Deposits 65,904 81,765 95,561
75,419 88,420 103,176
Loans 52,399 67,575 79,078
65,063 78,301 92,044
For each variable, first line represents the mean value and
second line shows the standard deviation.
Table 2
Regression results for the translog cost function for total
expenses of a bank to measure economies of scale with respect
to size of the bank as measured by total assets
Variables 2007 2008 2009
# of Banks 35 35 35
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.99 0.99
Ln of 0.73 0.79 0.76
Assets (3.26 *) (3.02 *) (2.57 **)
1/2 (Ln of 0.03 0.02 0.02
Assets^2) (1.22) (0.79) (0.68)
Public -0.01 -0.05 -0.07
Sector (-0.26) (-1.03) (-1.33)
Cost 1.05 1.01 0.96
Elasticity (8.79 *) (2.30 **) (-11.13 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.95 0.94 0.94
Ln of 0.29 0.41 0.60
Assets (0.55) (0.67) (0.96)
1/2 (Ln of 0.07 0.06 0.04
Assets^2) (1.34) (1.03) (0.71)
Public -0.13 -0.25 -0.39
Sector (-1.27) (-2.25 **) (-3.33 *)
Cost 1.04 1.07 1.05
Elasticity (3.03 *) (5.73 *) (5.69 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.98 0.98 0.99
Ln of 0.88 0.87 0.75
Assets (2.78 *) (2.75 *) (2.57 **)
1/2 (Ln of 0.01 0.01 0.02
Assets^2) (0.38) (0.35) (0.65)
Public 0.04 0.03 0.05
Sector (0.68) (0.45) (0.86)
Cost 0.998 0.98 0.94
Elasticity (-0.82) (-10.59 *) (-18.06 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.98 0.99
Ln of 0.88 0.82 0.95
Assets (2.83 *) (2.27 **) (3.56 *)
1/2 (Ln of 0.01 0.01 -0.001
Assets^2) (0.35) (0.41) (-0.03)
Public 0.05 0.08 0.04
Sector (0.84) (1.22) (0.85)
Cost 0.99 0.93 0.94
Elasticity (-6.32 *) (-36.37 *) (-463.29 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adjusted [R.sup.2] 0.91 0.90 0.92
Ln of 0.06 0.45 0.29
Assets (0.08) (0.57) (0.40)
1/2 (Ln of 0.08 0.04 0.06
Assets^2) (1.12) (0.61) (0.89)
Public 0.21 0.06 0.01
Sector (1.44) (0.44) (0.10)
Cost 0.92 0.93 0.92
Elasticity (-5.06 *) (-8.01 *) (-6.71 *)
Variables 2010 2011 2012
# of Banks 35 35 34
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.98 0.99
Ln of 0.70 0.85 0.75
Assets (2.80 *) (2.18 **) (3.62*)
1/2 (Ln of 0.02 0.01 0.02
Assets^2) (1.01) (0.20) (0.97)
Public 0.01 0.06 0.03
Sector (0.19) (0.91) (1.02)
Cost 0.92 0.93 0.96
Elasticity (-18.91 *) (-51.30 *) (-11.13 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.93 0.94 0.94
Ln of -0.01 0.29 0.23
Assets (-0.01) (0.41) (0.38)
1/2 (Ln of 0.09 0.06 0.06
Assets^2) (1.49) (0.95) (113)
Public -0.28 -0.04 -0.06
Sector (-2.32 **) (-0.34) (-0.64)
Cost 1.01 0.98 1.05
Elasticity (0.54) (-1.76 **) (5.69 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.98 0.99
Ln of 1.06 1.13 0.94
Assets (4.03 *) (2.81 *) (4.35 *)
1/2 (Ln of -0.01 -0.02 0.001
Assets^2) (-0.50) (-0.54) (0.08)
Public 0.14 0.11 0.07
Sector (2.92 *) (1.63) (1.93 ***)
Cost 0.95 0.90 0.94
Elasticity (-27.01 *) (-25.77 *) (-18.06 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.98 0.99
Ln of 0.83 1.01 0.95
Assets (2.83 *) (2.56 **) (3.56 *)
1/2 (Ln of 0.01 -0.01 -0.001
Assets^2) (0.28) (-0.32) (-0.03)
Public 0.19 0.18 0.04
Sector (3.60 *) (2.81 *) (0.85)
Cost 0.91 0.90 0.94
Elasticity (-59.32 *) (-54.17 *) (-463.29 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adjusted [R.sup.2] 0.92 0.90 0.92
Ln of 0.07 0.10 0.29
Assets (0.09) (0.11) (0.40)
1/2 (Ln of 0.07 0.07 0.06
Assets^2) (116) (0.89) (0.89)
Public 0.07 0.12 0.01
Sector (0.53) (0.86) (0.10)
Cost 0.86 0.90 0.92
Elasticity (-10.16 *) (-7.05 *) (-6.71 *)
Panel
Variables 2013 Data
Model
# of Banks 34 243
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.98 0.99
Ln of 0.97 0.89
Assets (2.73 *) (9.23 *)
1/2 (Ln of -0.002 0.01
Assets^2) (-0.05) (0.74)
Public 0.01 -0.01
Sector (0.16) (-0.37
Cost 0.95 0.97
Elasticity (-165.87 * (-9.05 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.94
Ln of 1.40 0.52
Assets (5.37 *) (2.47 *)
1/2 (Ln of -0.04 0.04
Assets^2) (-1.90 **) (2.25 **)
Public 0.04 -0.22
Sector (1.15) (-5.41 *)
Cost 0.94 0.96
Elasticity (-3.59 *) (-79.34 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.95 0.98
Ln of -0.13 1.03
Assets (-0.23) (9.74 *)
1/2 (Ln of 0.09 -0.01
Assets^2) (1.97 **) (-0.76)
Public -0.34 0.07
Sector (-3.84 *) (3.53 **)
Cost 0.91 0.95
Elasticity (-15.36 *) (-92.49 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.98 0.99
Ln of 1.27 1.13
Assets (3.42 *) (10.61 *)
1/2 (Ln of -0.03 -0.02
Assets^2) (-0.89) (-1.86 **)
Public 0.10 0.10
Sector (1.67 ***) (4.66*)
Cost 0.92 0.93
Elasticity (-10.03 *) (-50.76 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adjusted [R.sup.2] 0.93 0.93
Ln of 0.11 0.34
Assets (0.15) (1.33)
1/2 (Ln of 0.07 0.05
Assets^2) (114) (2.31 **)
Public -0.03 0.06
Sector (-0.23) (119)
Cost 0.94 0.93
Elasticity (-4.44 *) (-18.10 *)
This table reports the regression results of the
translog cost function for the years 2007-2013.
To estimate cost elasticity for each year, we
estimate scale economy for individual bank and
then average across observations to find the
scale economy measure for the entire sample.
A two tailed t-test tests for whether the
average cost elasticity is significantly
different from 1.0. t-statistics have been
reported in parentheses. * Statistically
significant at the 1% significance level,
** Statistically significant at the 5%
significance level, and ***Statistically
significant at the 10% significance level
Table 3
Regression results for the translog cost function for economies
of scale with respect to deposits
Variables 2007 2008 2009
# of Banks 35 35 35
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adjusted [R.sup.2] 0.98 0.98 0.97
Ln of 2.27 1.64 0.79
Deposits (3.03 *) (2.07 **) (0.88)
(Ln of -0.14 -0.07 0.02
Deposits^2) (-1.77 **) (-0.83) (0.19)
Public -0.02 -0.11 -0.18
Sector (-0.31) (-146) (-1.94 **)
Assets 0.00 0.00 0.00
(2.34 **) (1.32) (0.25)
Cost 90.79 0.89 1.01
Elasticity (-7.55 *) (-8.64 *) (2.18 **)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.95 0.94 0.91
Ln of 0.91 0.59 0.08
Deposits (0.84) (0.45) (0.05)
1/2 (Ln of 0.002 0.04 0.09
Deposits^2) (0.01) (0.31) (0.63)
Public -0.17 -0.34 -0.50
Sector (-1.51) (-2.62 *) (-3.37 *)
Assets 0.00 0.00 0.00
(0.81) (0.36) (-0.12)
Cost 0.93 1.02 1.06
Elasticity (-176.9 *) (2.57 *) (3.60 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.97 0.97 0.97
Ln of 2.66 1.87 0.94
Deposits (3.01 *) (2.18 **) (1.15)
1/2 (Ln of -0.18 -0.09 0.000
Deposits^2) (-1.92 **) (-1.04) (0.01)
Public 0.03 -0.03 -0.06
Sector (0.35) (-0.41) (-0.67)
Assets 0.00 0.00 0.00
(2.20 **) (1.35) (0.38)
Cost 0.76 0.90 0.95
Elasticity (-6.78 *) (-5.65 *) (-555.6 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.97 0.97 0.97
Ln of 2.88 1.97 1.41
Deposits (3.13 *) (2.11 **) (1.73 **)
1/2 (Ln of -0.20 -0.10 -0.05
Deposits^2) (-2.10 **) (-1.07) (-0.56)
Public 0.05 0.02 -0.05
Sector (0.52) (0.27) (-0.61)
Assets 0.00 0.00 0.00
(2.35 **) (139) (0.76)
Cost 0.77 0.90 0.86
Elasticity (-5.86 *) (-5.48 *) (-13.90 *)
Dependent Variable: Natural Logarithm of Employee Cost in
Indian Rupees
Adjusted [R.sup.2] 0.92 0.91 0.90
Ln of -0.09 0.18 -0.35
Deposits (-0.06) (0.12) (-0.23)
1/2 (Ln of 0.10 0.07 0.12
Deposits^2) (0.66) (0.47) (0.82)
Public 0.16 -0.02 -0.09
Sector (1.09) (-0.12) (-0.59)
Assets 0.00 0.00 -0.00
(0.14) (0.12) (-0.09)
Cost 0.96 0.93 0.96
Elasticity (-1.84 **) (-5.15 *) (-1.64 ***)
Variables 2010 2011 2012
# of Banks 35 35 34
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adjusted [R.sup.2] 0.98 0.99 0.98
Ln of 1.13 1.52 1.24
Deposits (1.85 **) (2.59 *) (2.02 **)
(Ln of -0.02 -0.06 -0.03
Deposits^2) (-0.30) (-0.98) (-0.48)
Public -0.14 -0.12 -0.10
Sector (-2.28 **) (-2.05 **) (-1.69 ***)
Assets 0.00 0.00 0.00
(110) (1.67) (110)
Cost 0.93 0.90 0.89
Elasticity (-19.27 *) (-9.76 *) (-18.71 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.92 0.94 0.93
Ln of -0.36 0.67 0.11
Deposits (-0.26) (0.53) (0.09)
1/2 (Ln of 0.13 0.02 0.07
Deposits^2) (0.95) (0.20) (0.64)
Public -0.47 -0.22 -0.21
Sector (-3.28 *) (-1.81 ***) (-1.82 ***)
Assets -0.00 0.00 0.00
(-0.04) (0.62) (0.03)
Cost 1.08 0.89 0.92
Elasticity (3.37 *) (-27.25 *) (-6.38 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.99 0.99
Ln of 1.97 1.95 1.68
Deposits (3.72 *) (3.45 *) (2.79 *)
1/2 (Ln of -0.10 -0.10 -0.07
Deposits^2) (-1.91 **) (-1.75 ***) (-1.19)
Public 0.001 -0.06 -0.06
Sector (0.02) (-1.15) (-1.02)
Assets 0.00 0.00 0.00
(2.16 **) (1.91 ***) (1.56)
Cost 0.86 0.82 0.87
Elasticity (-7.31 *) (-9.52 *) (-9.59 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.99 0.98
Ln of 1.72 1.85 1.51
Deposits (2.95 *) (3.11 *) (2.35 **)
1/2 (Ln of -0.08 -0.09 -0.06
Deposits^2) (-1.36) (-1.55) (-0.90)
Public 0.05 0.02 -0.01
Sector (0.86) (0.32) (-0.10)
Assets 0.00 0.00 0.00
(1.87 **) (1.81 ***) (0.96)
Cost 0.83 0.83 0.82
Elasticity (-10.92 *) (-9.82 *) (-16.05 *)
Dependent Variable: Natural Logarithm of Employee Cost in
Indian Rupees
Adjusted [R.sup.2] 0.93 0.91 0.92
Ln of 0.45 0.57 0.14
Deposits (0.39) (0.38) (0.10)
1/2 (Ln of 0.04 0.03 0.07
Deposits^2) (0.30) (0.18) (0.50)
Public -0.08 -0.05 -0.13
Sector (-0.60) (-0.35) (-0.99)
Assets 0.00 0.00 0.00
(0.70) (0.62) (0.68)
Cost 0.89 0.80 0.95
Elasticity (-13.63 *) (-53.51 *) (-4.10 *)
Variables 2013 Panel Data
with Fixed
Effects
Model
# of Banks 34 243
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adjusted [R.sup.2] 0.97 0.99
Ln of 1.59 1.06
Deposits (1.84 **) (6.57 *)
(Ln of -0.06 -0.01
Deposits^2) (-0.73) (-0.67)
Public -0.12 -0.08
Sector (-1.56) (-3.86 *)
Assets 0.00 0.00
(0.93) (1.31)
Cost 0.90 0.95
Elasticity (-9.42 *) (-62.57 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.94 0.94
Ln of 0.61 0.78
Deposits (0.50) (2.27 **)
1/2 (Ln of 0.03 0.02
Deposits^2) (0.24) (0.46)
Public -0.48 -0.29
Sector -4.32 * (-6.84 *)
Assets 0.00 0.00
(0.84) (0.90)
Cost 0.95 0.996
Elasticity (-8.94 *) (-2.71 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.97 0.99
Ln of 1.95 1.21
Deposits (2.22 **) (7.07 *)
1/2 (Ln of -0.09 -0.03
Deposits^2) (-111) (-1.51)
Public -0.03 0.004
Sector (-0.38) (0.19)
Assets 0.00 0.00
(0.96) (1.33)
Cost 0.90 0.89
Elasticity (-5.92 *) (-48.49 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adjusted [R.sup.2] 0.99 0.99
Ln of 2.22 1.30
Deposits (4.01 *) (7.34 *)
1/2 (Ln of -0.12 -0.04
Deposits^2) (-2.29 **) (-2.03 **)
Public -0.08 0.03
Sector (-1.49) (141)
Assets 0.00 0.00
(1.81 ***) (1.30)
Cost 0.82 0.86
Elasticity (-8.00 *) (-42.09 *)
Dependent Variable: Natural Logarithm of Employee Cost in
Indian Rupees
Adjusted [R.sup.2] 0.92 0.93
Ln of 1.06 1.06
Deposits (0.75) (2.58 *)
1/2 (Ln of -0.02 -0.02
Deposits^2) (-0.13) (-0.54)
Public -0.15 0.01
Sector (-1.18) (0.14)
Assets 0.00 0.00
(0.93) (2.25 **)
Cost 0.94 0.82
Elasticity (-30.28 *) (-103.19 *)
t-statistics have been reported in parentheses.
* Statistically significant at the 1% significance level,
** statistically significant at the 5% significance level,
and *** Statistically significant at the
10% significance level
Table 4
Regression results for the translog cost function for
economies of scale regarding loans
Variables 2007 2008 2009
# of Banks 35 35 35
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adj. [R.sup.2] 0.99 0.99 0.98
Ln of 0.80 0.82 0.81
Loans (1.78 **) (1.73 ***) (1.54)
1/2 (Ln of 0.2 0.02 0.01
Loans^2) (0.36) (0.32) (0.26)
Public -0.06 -0.11 -0.14
Sector (-114) (-2.11 **) (-2.34 **)
Assets 0.00 0.00 0.00
(0.15) (0.12) (0.15)
Cost 1.00 1.03 0.96
Elasticity (0.95) (7.08 *) (-16.17 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.94 0.93 0.94
Ln of 0.67 0.82 0.68
Loans (0.62) (0.69) (0.62)
1/2 (Ln of 0.03 0.01 0.03
Loans^2) (0.21) (0.11) (0.28)
Public -0.16 -0.29 -0.46
Sector (-1.31) (-2.27 **) (-3.73 *)
Assets 0.00 0.00 0.00
(0.40) (0.43) (0.12)
Cost 0.98 0.92 0.997
Elasticity (-4.02 *) (-38.63 *) (-0.39)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.99 0.99 0.99
Ln of 0.85 0.80 0.77
Loans (1.56) (1.62) (1.51)
1/2 (Ln of 0.02 0.02 0.01
Loans^2) (0.26) (0.34) (0.29)
Public -0.01 -0.04 -0.01
Sector (-0.20) (-0.71) (-0.23)
Assets -0.00 -0.00 0.00
(-0.14) (-0.13) (0.10)
Cost 1.05 1.01 0.61
Elasticity (13.37 *) (2.01 **) (-128.30 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adj. [R.sup.2] 0.99 0.98 0.99
Ln of 0.70 0.69 1.10
Deposits (1.29) (1.23) (2.30 **)
1/2 (Ln of 0.03 0.03 -0.02
Deposits^2) (0.54) (0.47) (-0.34)
Public -0.01 0.01 -0.01
Sector (-0.09) (0.23) (-0.28)
Assets -0.00 -0.00 0.00
(-0.42) (-0.24) (0.44)
Cost 1.01 1.00 0.94
Elasticity (0.95) (031) (-20.95 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adj. [R.sup.2] 0.90 0.89 0.91
Ln of 0.72 1.43 0.91
Deposits (0.48) (0.97) (0.71)
1/2 (Ln of 0.01 -0.06 -0.01
Deposits^2) (0.05) (-0.40) (-0.05)
Public 0.21 0.05 -0.03
Sector (1.26) (0.32) (-0.20)
Assets 0.00 0.00 0.00
(0.54) (0.85) (0.68)
Cost 0.8 0.81 0.83
Elasticity (-123.27 *) (-16.39 *) (-114.43 *)
Variables 2010 2011 2012
# of Banks 35 35 34
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adj. [R.sup.2] 0.99 0.98 0.99
Ln of 0.82 2.05 1.08
Loans (1.74 ***) (3.12 *) (2.36 **)
1/2 (Ln of 0.01 -0.12 -0.01
Loans^2) (0.21) (-1.77 **) (-0.31)
Public -0.09 -0.002 -0.04
Sector (-1.78 ***) (-0.03) (-0.99)
Assets 0.00 0.00 0.00
(0.56) (2.20 **) (0.61)
Cost 0.93 0.84 0.92
Elasticity (-36.3 *) (-7.39 *) (-29.18 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.93 0.93 0.95
Ln of -0.28 1.49 -0.04
Loans (-0.23) (1.23) (-0.03)
1/2 (Ln of 0.12 -0.06 0.09
Loans^2) (1.00) (-0.51) (0.84)
Public -0.40 -0.10 -0.16
Sector (-3.23 *) (-0.83) (-1.59)
Assets -0.00 0.00 -0.00
(-0.22) (1.18) (-0.41)
Cost 1.01 0.83 0.97
Elasticity (0.55) (-14.44 *) (-1.58)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.99 0.98 0.99
Ln of 1.52 2.37 1.53
Loans (2.95 *) (3.51 *) (2.92 *)
1/2 (Ln of -0.06 -0.15 -0.06
Loans^2) (-1.16) (-2.18 **) (-109)
Public 0.06 0.05 0.001
Sector (1.05) (0.74) (0.02)
Assets 0.00 0.00 0.00
(1.33) (2.21 **) (1.12)
Cost 0.87 0.72 0.85
Elasticity (-10.60 *) (9.50 *) (-12.75 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adj. [R.sup.2] 0.98 0.98 0.99
Ln of 1.26 2.14 1.33
Deposits (2.08 **) (3.07 *) (2.34 **)
1/2 (Ln of -0.03 -0.13 -0.04
Deposits^2) (-0.61) (-1.83 ***) (-0.70)
Public 0.11 0.13 0.05
Sector (1.75 ***) (1.84 ***) (1.05)
Assets 0.00 0.00 0.00
(1.04) (1.97 ***) (0.42)
Cost 0.61 0.71 0.88
Elasticity (-32.38 *) (-11.36 *) (-15.82 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adj. [R.sup.2] 0.93 0.89 0.93
Ln of 0.88 1.60 0.32
Deposits (0.70) (1.06) (0.23)
1/2 (Ln of -0.01 -0.08 0.05
Deposits^2) (-0.06) (-0.55) (0.36)
Public -0.01 0.08 -0.07
Sector (-0.08) (0.53) (-0.56)
Assets 0.00 0.00 0.00
(0.91) (1.26) (0.56)
Cost 0.80 0.72 0.88
Elasticity (-137.09 *) (-17.85 *) (-12.35 *)
Panel Data
Variables 2013 with Fixed
Effects
# of Banks 34 243
Dependent Variable: Natural Logarithm of Total
Expenses in Indian Rupees
Economies of Scale with respect to Deposits
Adj. [R.sup.2] 0.98 0.98
Ln of 1.04 1.36
Loans (1.54) (5.92 *)
1/2 (Ln of -0.01 -0.04
Loans^2) (-0.12) (-1.70 ***)
Public -0.08 -0.13
Sector (-1.34) (-4.69 *)
Assets 0.00 0.00
(0.04) (2.65 *)
Cost 0.99 0.92
Elasticity (-7.31 *) (-27.84 *)
Dependent Variable: Natural Logarithm of Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.96 0.94
Ln of 0.002 0.76
Loans (0.01) (1.89 **)
1/2 (Ln of 0.09 0.02
Loans^2) (0.86) (0.51)
Public -0.43 -0.35
Sector (-4.84 *) (-7.45 *)
Assets 0.00 0.00
(0.04) (116)
Cost 1.03 0.98
Elasticity (1.60) (-11.82 *)
Dependent Variable: Natural Logarithm of Non-Operating
Expenses in Indian Rupees
Adj. [R.sup.2] 0.98 0.98
Ln of 1.41 1.62
Loans (1.97 **) (6.98 *)
1/2 (Ln of -0.04 -0.06
Loans^2) (-0.60) (-2.79 *)
Public 0.02 -0.04
Sector (0.25) (-161)
Assets 0.00 0.00
(0.16) (3.00 *)
Cost 0.95 0.91
Elasticity (-6.00 *) (-18.21 *)
Dependent Variable: Natural Logarithm of Interest
Expenses in Indian Rupees
Adj. [R.sup.2] 0.99 0.98
Ln of 1.94 1.75
Deposits (3.24 *) (7.43 *)
1/2 (Ln of -0.10 -0.08
Deposits^2) (-1.68 ***) (-3.32 *)
Public -0.02 -0.01
Sector (-0.37) (-0.55)
Assets 0.00 0.00
(1.06) (3.03 *)
Cost 0.80 0.90
Elasticity (-10.46 *) (-17.40 *)
Dependent Variable: Natural Logarithm of Employee
Cost in Indian Rupees
Adj. [R.sup.2] 0.93 0.93
Ln of 0.58 0.74
Deposits (0.43) (1.67 ***)
1/2 (Ln of 0.03 0.01
Deposits^2) (0.22) (0.31)
Public -0.11 -0.06
Sector (-0.92) (-114)
Assets 0.00 0.00
(0.40) (1.71 ***)
Cost 0.92 0.89
Elasticity (-13.66 *) (-105.92 *)
t-statistics have been reported in parentheses. * Statistically
significant at the 1% significance level, ** statistically
significant at the 5% significance level, and *** Statistically
significant at the 10% significance level
Table 5
Economies of scale by bank ownership for Indian banks
for the period 2007 to 2013
2007 2008 2009
Cost elasticity with respect to Total Assets
Cost Elasticity of Total Expenses with respect
to Total Assets of a Bank
Public Sector 1.07 1.02 0.97
Banks (13.13 *) (5.6 *) (-9.26 *)
Private Sector 1.03 0.99 0.95
Banks (3.08 *) (-.87) (-9.49 *)
Cost Elasticity of Operating Expenses with respect to
Total Assets of a Bank
Public Sector 1.08 1.10 1.07
Banks (6.50 *) (9.54 *) (9.44 *)
Private Sector 0.99 1.02 1.02
Banks (-0.59) (1.29) (1.25)
Cost Elasticity of Non-Operating Costs with respect
to Total Assets of a Bank
Public Sector 1.003 0.98 0.95
Banks (2.06 **) (-8.78 *) (-16.96 *)
Private Sector 0.99 0.97 0.93
Banks (-3.06 *) (-8.97 *) (-13.91 *)
Cost Elasticity of Interest Expenses with respect
to Total Assets of a Bank
Public Sector 0.993 0.93 0.943
Banks (-4.27 *) (-37.7 *) (-517.89 *)
Private Sector 0.98 0.92 0.944
Banks (-6.58 *) (-25.18 *) (-293.18 *)
Cost Elasticity of Employee Cost with respect
to Total Assets of a Bank
Public Sector 0.96 0.96 0.96
Banks (-2.82 *) (-5.89 *) (-4.38 *)
Private Sector 0.86 0.90 0.88
Banks (-5.78 *) (-7.35 *) (-6.66 *)
Cost elasticity with respect to Total Deposits
Cost Elasticity of Total Expenses with respect
to Total Deposits of a Bank
Public Sector 0.72 0.85 1.02
Banks (-11.75 *) (-12.9 *) (5.88 *)
Private Sector 0.90 0.94 0.99
Banks (-2.24 **) (-2.9 **) (-119)
Cost Elasticity of Operating Expenses with respect
to Total Deposits of a Bank
Public Sector 0.932 1.04 1.12
Banks (-199.44 *) (6.24 *) (7.48 *)
Private Sector 0.93 0.99 0.99
Banks (-118.39 *) (-0.86) (-0.26)
Cost Elasticity of Non-operating expenses with respect
to Total Deposits of a Bank
Public Sector 0.67 0.85 0.946
Banks (-10.86 *) (-9.73 *) (-627.6 *)
Private Sector 0.90 0.97 0.945
Banks (-1.73) (-114) (-371 *)
Cost Elasticity of Interest Expenses with respect
to Total Deposits of a Bank
Public Sector 0.67 0.84 0.83
Banks (-9.81 *) (-9.53 *) (-19.2 *)
Private Sector 0.92 0.97 0.90
Banks (-113) (-1.03) (-6.57 *)
Cost Elasticity of Employee Cost with respect
to Total Deposits of a Bank
Public Sector 1.02 0.97 1.03
Banks (1.00) (-2.53 **) (1.54)
Private Sector 0.89 0.88 0.87
Banks (-3.90 *) (-5.88 *) (-3.73 *)
Cost elasticity with respect to Total Loans
Cost Elasticity of Total Expenses with respect
to Total Loans of a Bank
Public Sector 1.01 1.04 0.96
Banks (4.20 *) (11.24 *) (-14.8 *)
Private Sector 0.99 1.01 0.94
Banks (-2.02 **) (2.10 **) (-13.1 *)
Cost Elasticity of Operating Expenses with respect
to Total Loans of a Bank
Public Sector 0.99 0.93 1.02
Banks (-1.55) (-40.4 *) (2.80 **)
Private Sector 0.95 0.92 0.97
Banks (-5.24 *) (-24.2 *) (-2.77 *)
Cost Elasticity of Non-operating expenses with respect
to Total Loans of a Bank
Public Sector 1.06 1.02 0.60
Banks (18.58 *) (5.50 *) (-146.6 *)
Private Sector 1.04 0.99 0.62
Banks (6.04 *) (-116) (-81.17 *)
Cost Elasticity of Interest Expenses with respect
to Total Loans of a Bank
Public Sector 1.02 1.02 0.93
Banks (4.20 *) (3.58 *) (-26.64 *)
Private Sector 0.98 0.98 0.95
Banks (-2.02 **) (-2.24 **) (-11.14 *)
Cost Elasticity of Employee Cost with respect
to Total Loans of a Bank
Public Sector 0.81 0.78 0.83
Banks (-139.55 *) (-21.8 *) (-131.1 *)
Private Sector 0.80 0.85 0.84
Banks (-82.61 *) (-8.06 *) (-72.12 *)
2010 2011 2012
Cost elasticity with respect to Total Assets
Cost Elasticity of Total Expenses with respect
to Total Assets of a Bank
Public Sector 0.94 0.93 0.99
Banks (-17.32 *) (-49.61 *) (-1.71)
Private Sector 0.91 0.92 0.97
Banks (-14.68*) (-36.01 *) (-4.61 *)
Cost Elasticity of Operating Expenses with respect to
Total Assets of a Bank
Public Sector 1.06 1.01 0.96
Banks (3.57 *) (0.94) (-3.59 *)
Private Sector 0.94 0.94 0.89
Banks (-2.06 **) (-3.52 *) (-5.68 *)
Cost Elasticity of Non-Operating Costs with respect
to Total Assets of a Bank
Public Sector 0.94 0.89 0.957
Banks (-32.01 *) (-29.03 *) (-172.6 *)
Private Sector 0.95 0.91 0.956
Banks (-15.12 *) (-14.56 *) (-102.8 *)
Cost Elasticity of Interest Expenses with respect
to Total Assets of a Bank
Public Sector 0.92 0.89 0.905
Banks (-63.62 *) (-58.01 *) (-48.12 *)
Private Sector 0.91 0.90 0.918
Banks (-42.66 *) (-33.19 *) (-24.07 *)
Cost Elasticity of Employee Cost with respect
to Total Assets of a Bank
Public Sector 0.90 0.94 1.02
Banks (-7.92 *) (-4.45 *) (1.10)
Private Sector 0.81 0.86 0.89
Banks (-9.00 *) (-6.98 *) (-2.98 *)
Cost elasticity with respect to Total Deposits
Cost Elasticity of Total Expenses with respect
to Total Deposits of a Bank
Public Sector 0.920 0.87 0.88
Banks (-25.1 *) (-13.92 *) (-23.20 *)
Private Sector 0.95 0.94 0.92
Banks (-10.3 *) (-3.94 *) (-9.53 *)
Cost Elasticity of Operating Expenses with respect
to Total Deposits of a Bank
Public Sector 1.16 0.91 0.95
Banks (7.22 *) (-26.43 *) (-3.97 **)
Private Sector 0.98 0.88 0.87
Banks (-0.48) (-21.37 *) (-6.58 **)
Cost Elasticity of Non-operating expenses with respect
to Total Deposits of a Bank
Public Sector 0.80 0.76 0.84
Banks (-11.6 *) (-13.66 *) (-13.32 *)
Private Sector 0.94 0.89 0.92
Banks (-2.20 **) (-3.77 *) (-3.67 *)
Cost Elasticity of Interest Expenses with respect
to Total Deposits of a Bank
Public Sector 0.78 0.78 0.79
Banks (-15.7 *) (-13.98 *) (-20.32 *)
Private Sector 0.89 0.90 0.86
Banks (-4.66 *) (-3.97 *) (-7.82 *)
Cost Elasticity of Employee Cost with respect
to Total Deposits of a Bank
Public Sector 0.92 0.81 0.98
Banks (-11.9 *) (-55.06 *) (-1.50)
Private Sector 0.86 0.78 0.90
Banks (-12.04 *) (-39.33 *) (-5.12 *)
Cost elasticity with respect to Total Loans
Cost Elasticity of Total Expenses with respect
to Total Loans of a Bank
Public Sector 0.93 0.78 0.92
Banks (-36.7 *) (-10.63 *) (-33.33 *)
Private Sector 0.92 0.92 0.93
Banks (-26.9 *) (-2.43 **) (-16.15 *)
Cost Elasticity of Operating Expenses with respect
to Total Loans of a Bank
Public Sector 1.08 0.80 1.02
Banks (3.85 *) (-17.98 *) (1.05 *)
Private Sector 0.92 0.87 0.91
Banks (-2.25 *) (-7.15 *) (-3.34 *)
Cost Elasticity of Non-operating expenses with respect
to Total Loans of a Bank
Public Sector 0.84 0.64 0.83
Banks (-14.9 *) (-12.83 *) (-16.09 *)
Private Sector 0.92 0.83 0.90
Banks (-4.46 *) (-3.84 *) (-5.74 *)
Cost Elasticity of Interest Expenses with respect
to Total Loans of a Bank
Public Sector 0.58 0.64 0.86
Banks (-38.9 *) (-14.77 *) (-19.32 *)
Private Sector 0.66 0.81 0.91
Banks (-19.0 *) (-5.08 *) (-7.69 *)
Cost Elasticity of Employee Cost with respect
to Total Loans of a Bank
Public Sector 0.80 0.68 0.91
Banks (-154 *) (-21.53 *) (-10.25 *)
Private Sector 0.81 0.78 0.85
Banks (-88.9 *) (-9.43 *) (-10.16 *)
2013 Panel Data
Cost elasticity with respect to Total Assets
Cost Elasticity of Total Expenses with respect
to Total Assets of a Bank
Public Sector 0.951 0.96
Banks (-178.5 *) (-76.35 *)
Private Sector 0.952 0.96
Banks (-98.2 *) (-56.56 *)
Cost Elasticity of Operating Expenses with respect to
Total Assets of a Bank
Public Sector 0.98 0.99
Banks (-1.24) (-2.33 **)
Private Sector 0.88 0.94
Banks (-4.27 *) (-11.71 *)
Cost Elasticity of Non-Operating Costs with respect
to Total Assets of a Bank
Public Sector 0.90 0.95
Banks (-18.9 *) (-104.60 *)
Private Sector 0.93 0.95
Banks (-7.19 *) (-53.08 *)
Cost Elasticity of Interest Expenses with respect
to Total Assets of a Bank
Public Sector 0.91 0.92
Banks (-13.2 *) (-60.65 *)
Private Sector 0.95 0.94
Banks (-3.97 *) (-26.45 *)
Cost Elasticity of Employee Cost with respect
to Total Assets of a Bank
Public Sector 0.97 0.96
Banks (-2.13 **) (-11.86 *)
Private Sector 0.90 0.89
Banks (-4.79 *) (-17.48 *)
Cost elasticity with respect to Total Deposits
Cost Elasticity of Total Expenses with respect
to Total Deposits of a Bank
Public Sector 0.87 0.89
Banks (-13.2 *) (-37.67 *)
Private Sector 0.94 0.95
Banks (-3.55 *) (-11.84 *)
Cost Elasticity of Operating Expenses with respect
to Total Deposits of a Bank
Public Sector 0.96 0.99
Banks (-6.79 *) (-4.73 *)
Private Sector 0.93 0.97
Banks (-8.16 *) (-14.56 *)
Cost Elasticity of Non-operating expenses with respect
to Total Deposits of a Bank
Public Sector 0.86 0.88
Banks (-9.37 *) (-27.38 *)
Private Sector 0.97 0.96
Banks (-131) (-5.43 *)
Cost Elasticity of Interest Expenses with respect
to Total Deposits of a Bank
Public Sector 0.76 0.86
Banks (-11.63 *) (-26.51 *)
Private Sector 0.91 0.96
Banks (-2.64 **) (-5.43 *)
Cost Elasticity of Employee Cost with respect
to Total Deposits of a Bank
Public Sector 0.94 0.90
Banks (-35.9 *) (-105.33 *)
Private Sector 0.95 0.96
Banks (-16.85 *) (-4.89 *)
Cost elasticity with respect to Total Loans
Cost Elasticity of Total Expenses with respect
to Total Loans of a Bank
Public Sector 0.98 0.95
Banks (-10.57 *) (-73.46 *)
Private Sector 0.99 0.96
Banks (-2.27 **) (-34.54 *)
Cost Elasticity of Operating Expenses with respect
to Total Loans of a Bank
Public Sector 1.07 1.01
Banks (4.47 *) (4.63 *)
Private Sector 0.96 0.98
Banks (-1.29) (-8.06 *)
Cost Elasticity of Non-operating expenses with respect
to Total Loans of a Bank
Public Sector 0.93 0.87
Banks (-9.17 *) (-58.62 *)
Private Sector 0.98 0.91
Banks (-1.45) (-25.35 *)
Cost Elasticity of Interest Expenses with respect
to Total Loans of a Bank
Public Sector 0.75 0.85
Banks (-13.94 *) (-51.87 *)
Private Sector 0.87 0.90
Banks (-4.23 *) (-21.17 *)
Cost Elasticity of Employee Cost with respect
to Total Loans of a Bank
Public Sector 0.94 0.81
Banks (-11.87 *) (-116.29 *)
Private Sector 0.90 0.84
Banks (-10.80 *) (-61.03)