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Setup
in 1957, the Tamilnadu Electricity Board (TNEB)
has been making rapid strides in various dimensions.
Its role in rural electrification is commendable.
From 1,67,297 huts in 1978-80 power reached to 1,05,24,024
huts in 1993. Now more than 14 Lakh huts are lit with
lights. Its contribution to modernization of agriculture
is significant. Energization of pump sets zoomed up
from 33,440 in 1955-56 to 14,45,951 in 1992-93. Now
it has crossed 20 lakh1. It has been the dynamo of
the socio-economic transformation of the rural sector.
TNEB has carved a niche in the generation of energy
from non-conventional sources. Despite these colorful
performances, TNEB has been working under several
severe constraints.
There
is a significant drop in the generational hydel power.
It declined from 70% in 1950-51 to 32% in 1991-92
as against the all India average of 43% in 1970-71
and 28% in 1991-922. Though generation of thermal
power has shown substantial progress, its production
cost has been uneconomical due to the high percentage
of the ash content of lignite and the increase in
the cost of transportation of coal from far away states
such as Bihar to the thermal power stations. Besides,
it also poses a serious threat to the environment.
The non-conventional sources of energy are still in
the nascent stage. Power generation here is not stable.
Under these circumstances nuclear power is the only
option open to Tamilnadu. To develop this power on
commercial basis TNEB has to strengthen its capital
structure in the years to come.
Capital
structure: Theoretical Formulations
Capital
structure refers to a mixture of a variety of long
term sources of funds and equity shares including
reserves and surpluses of an enterprise. It hardly
takes in its structure, all the complex quantitative
factors as well as qualitative attributes affecting
investment decisions. The Net Income Approach under
certain assumptions, postulates an inverse relationship
between the weighted average cost of capital and the
total value of the firm. The Net Operating Income
Approach does not visualize such a definite relationship
between the two, even in the event of changing leverages.
The Traditional View holds that a judicious blend
of debt and equity results in the emergence of an
optimal capital structure. Rejecting this intermediate
position, MODIGLIANI and MILLER argue that in the
absence of taxes, the market value of the firm and
its cost of capital, remain invariant to the changes
in the capital structure. Yet practicing managers
do believe in optimal capital structure owing to tax
advantages associated with corporate borrowings. A
sound capital structure, they feel, besides conservatism,
must ensure profitability, solvency, flexibility and
effective control.
Empirical
Determinants - Capital Structure
Most
of the empirical works on capital structure, both
abroad and in India using multiple regressions with
proxies for the unobservable theoretical attributes,
are marked by many limitations. Though unique representations
are not ruled out for many attributes, often more
than one proxy explains a particular attribute. It
is also plausible that a proxy may radiate information
relating to many attributes. In the absence of well-defined
guidelines, financial economists are constrained to
include in their econometric models only those proxies
that work well in terms of Goodness of fit criterion.
Besides the selectivity bias in the collection of
data, the presence of dubious correlations among the
chosen variables, often renders the estimated coefficients
spurious. Not withstanding these limitations, regression
analyses on capital structure do shed light on the
influence of certain variables, and their inter-relationships
in arriving at a near-optimal capital structure.
BALAI
and MASULIS, JENSEN and MACKLING and MYERS postulate
a direct kinship between the debt equity ratio of
a firm and the collateralization of its debt. Since
all projects are seldom collateralized, firms often
go in for equity finance rather than borrowed capital.
MYERS and MAJLUF observed that the issue of debt buttressed
by assets with known values, do away with the costs
associated with the issue of new shares3. SCOTT believes
that a firm can maximize the value of its equity by
disposing secured debts to unsecured creditors. GROSMEN
and HART believe that at a higher debt level a firm
that is exposed to the threat of bankruptcy is burdened
with rising agency costs. This cripples its ability
to garner additional funds. The collateral value attribute
is captured by the ratio of intangible assets to total
assets, and the ratio of inventory (plus gross plant
and equipment in money terms) to total assets. The
first ratio is negatively related to the collateral
value of assets while the second is positively related
to it4.
DE
ANGELO and MASULIS argue that enterprises with
large tax benefits relative to their expected cash
inflows, prefer less debt in their capital structure5.
When a levered firm prospers, owing to its increasing
agency costs, its growth will have a negative relationship
with the long term debt. To mitigate the effect of
bulging agency costs, when enterprises mobilize short
term debts, growth will cultivate a positive relationship
with it. Convertible debentures can also cut agency
costs to size. Hence growth will assume a direct relationship
with convertible debt ratios. Capital expenditure
to total assets, and the increase in total assets
measured by its percentage change, can also be indicators
of growth. Since progressive enterprises earmark more
funds for R&D to innovate and generate new investment
opportunities, the ratio of the above to sales too
can be a proxy for growth6.
TITMAN
concludes that firms manufacturing specialized products
to meet the specific needs of the customers normally
go for equity financing. In such cases a negative
relationship between equity and debt is plausible.
In certain empirical studies the ratios of selling
expenses to sales and R&D to sales are treated
as proxies for uniqueness of a firm. WARNER, AUG,
CHUA and MCCONNELL observe that larger firms with
greater degree of diversification are less prone to
bankruptcy and liquidation. Such firms are hence highly-levered.
The size of a firm is often gauged by the natural
log of sales. Some financial analysts believe that
the optimum debt level is a decreasing function of
the volatility of earnings. Such firms prefer more
equity and less debt. The Standard Deviation of the
percentage of change in operating income can capture
this attribute7.
MYERS
and BREALE give more prominence to retained earning
as a source of capital structure. When debt level
is low at higher profitability, promising firms rely
more on equity and less on debt for their expansion
and diversification, since they can easily mobilize
equity funds on attractive terms. Even debt on a massive
scale with soft terms can knock at their doors. The
relationship between profitability and debt hence
can be both direct as well as indirect. Profitability
is measured by the ratio of operating income to sales,
and operating income to assets8. Thus determinants
of capital structure of a firm are governed by a myriad
of factors which make the identification of optimal
capital structure an uphill task.
Capital
structure: Indian industries
Studies
on capital structure of Indian Industries are inconclusive
and often conflicting. A study by Sharma and Rao (1968)
on 30 Engineering firms for 3 years conclude that
debt due to its tax-deductibility is a prominent determinant
of the cost of capital. A study by I. M. Pandey (1981)
on cotton textiles, chemicals, engineering and electricity
generations lends support to the traditional approach.
Bhatt (1980) in his paper concludes that the leverage
ratio is very much influenced by business risks measured
in term of variability in earnings, profitability,
debt service capacity, and dividend-payout ratio.
I. M. Pandey (1984) in another study found that during
1973-81 about 80% of the assets of the companies sampled
was financed by external debt and current liabilities.
Large sized companies were more levered though a large
number of small firms also courted more debt capital.
Leverage did not exhibit a definite relationship with
growth and profitability, although all the three variables
moved in the same direction. He also found that a
majority of the profitability and growth oriented
companies were within the narrow bands of leverage.
S. K. Chakraborty (1977) in his study found that age,
retained earnings, and profitability were negatively
correlated with the debit equity ratio, while total
assets and capital intensity were directly related
to it. He felt that a high cost of capital for all
the consumer industries was due to their low debt
component. His indirect attempt to test the MM hypothesis
for 22 firms showed that cost of capital was almost
invariant to the debt equity ratios.
Before
1980s Indian financial managers courted debt due to
its low cost, tax advantages and the complicated procedures
to be observed in garnering equity capital. The substitutability
of short term debt for long term loan was another
attraction. However, with the waves of liberalization,
privatization and globalization sweeping the capital
market in recent years, the corporate world has started
wooing equity capital in a big way. The arrival of
a matrix of new financial instruments such as commercial
papers, asset securitisation, factoring and forfeiting
services, and the market related interest rate structure
and their stringent conditions for lending, force
modern enterprises to court equity finance.
To
examine the capital structure of the TNEB, 8 financial
ratios for a period of 18 years (1981-1998) are selected
on the basis of the empirical findings of many previous
studies. The relevant basic data are collected from
various reports of the TNEB statistics at a glance.
They include 1) debt equity ratio, 2) ratios of capital
assets to total assets, 3) depreciation to total assets,
4) capital expenditure to total assets, 5) gross surplus
to sales, 6) gross surplus to total assets, 7) growth
in total assets and 8) natural log of sales. The debt
equity ratio is designated as Criterion Variable while
the remaining ratios are called Tests or Control variables.
Using Wherry Doolittle Selection Model the crucial
determinants of the debt equity ratio of the TNEB
are identified.
Algorithm
- Wherry Doolittle Selection Model
To
start with, 5 tables are opened simultaneously. The
first row of Table-1 displays the correlations between
the criterion and each of the 7 control variables.
The other columns and rows indicate the correlations
among the 7 tests. 11 correlations are significant
at 5% level in terms of t-test, while the levels of
significance of 17 correlations go beyond 10%. The
correlations between each of the 7 tests and the criterion
are entered with signs reversed in V1 row of Table-2.
It is simply a mechanical reproduction of all the
correlations found in the 1st row of Table-1 with
signs reversed. The numbers heading the columns always
represent tests. The Z1 row of Table 3 has 7 unitary
values. Each column begins with 1.0000 as the first
value. The first test selected to explain the variations
in the criterion is one having the highest (V21 ¸
Z1) quotient. It is obvious from Table-1 that the
ratio of capital assets to total assets has the highest
correlation of 0.9171 with the debt equity ratio.
It is identified as the first determinant of the capital
structure of TNEB.
The
WHERRY Shrinkage formula is used to find out the various
values displayed in Table-4. R2 = 1- K2 [(N-1) ¸
(N-m)] where R is the shrunken multiple correlation
coefficient which is free from chance error. This
Table contains 7 columns. The first value under the
last column has R = 0.9171. This explains the amount
of variations in the debt equity ratio contributed
by the ratio of total capital assets to total assets
of the TNEB. A sequence of preceding calculations
derives this value. They are explained subsequently.
Additional
calculations that are needed to select the second
control variable, are shown in Table-5. The first
7 columns represent the correlation among the 7 control
variables. The 8th column has the correlation between
the selected test and the criterion with the sign
reversed. The 9th column gives the row total. The
last column has a list of selected tests. The first
row a1 is left blank. In row b1 are entered the correlations
between the selected test and each of the other tests
found in Table-1. These are 1.0000, 0.9292,etc. They
are entered in the columns correspond to the tests.
In the column meant for the first selected test is
entered 1.000.In the 8th column (-c) the correlation
between the first selected tests and the criterion
is recorded with sign reversed. Here it is -0.9171.
The last column has the algebraic sum of all the values
of b1 row. It is 1.9370. Each b1 entry is now multiplied
by the negative reciprocal of the b1 entry for the
first selected test. The products are entered in the
c1 row. The negative reciprocal of the first selected
test found in b1 entry is -1.000. Hence all the entries
found in b row are repeated in the c1 row with signs
reversed.
Before
computing v2 and z2 in order to select the second
test, a vertical line is drawn under test 1 in Tables
2 and 3 since it has already been selected as a determinant
of the capital structure of the board. V2 is the sum
of two values. The first one being v1 and the second
is the product of the b1 entry in the criterion (-C)
of Table 5 and the C1 entry for each of the other
tests. Thus V2 = V1 + [b1 (criterion) x C1 (each test).
Eg: V22 = [V12 + b1 (c) x (C12)]. i.e. . [-0.8037
+ (-0.9171 X -0.9292) = 0.0485]. Z2 is also the sum
of two values. The first one is Z1 and the second
one is the product of b1 and c1 entries for each test
found in Table 5. Thus z2+ z1 [b1 (a given test )
x c1 the same test)]. Eg: Z22 = [Z12 + (b12 x C12)].
i.e; Z22 = [1.0000 + (0.9292) x (-0.9292)]= 0.1366.
Now (V22¸Z2) is calculated for all V2 and Z2
values. The highest quotient 0.0782 is identified
as the second test to be included in the battery of
the control variables. This quotient 0.0782 measures
the contribution of the second test (viz. log of sale
of power) to the squared multiple correlation coefficient,
R2. This quotient is subtracted from the first value
(0.1589) found under column 3 and the result 0.8007
is entered in the second row of the same column. Now
the quotient of [(N-1) ¸ (N-m)] is computed.
Since N=18 and m is the number of tests chosen, the
quotient here is (17 ¸ 15) = 1.0625.
The
product of the values found under columns in the second
row is recorded in the same row under col.5. Here
it is 0.0857. This value is subtracted from 1.0000
to obtain 0.9143 which is entered in the second row
under the column 6. The square root of this value
0.9562 is recorded again in the same row under column
7. This value represents the total contribution of
the of first two selected tests towards the criterion.
Here the ratio of capital assets to total assets and
the natural log of sales collectively explain 95.9%
of variation in the dept equity ratio of the electricity
board. In Tables 2 and 3 vertical lines are drawn
under the second chosen test to indicate that they
are already selected.
Cross
checks:
There
are four cross checks for b2 and C2 entries.
i) The b2 entry for the second test must be equal
to the Z2 entry of the same test. Both entries here
are 0.9266.
ii) The entry in the criterion column must be equal
to b2 entry of the second selected test. Here the
entry is -0.2691.
iii) The entry in the checksum column must tally with
the sum of all the entries of c2 row. Here it is -0.6013.
iv) In the criterion column the product of b2 and
c2 entries must tally with (V2 ¸ Z2) under column
b second row of Table 4 in absolute value disregarding
the sign. Here it is 0.0782. These checks are also
applicable to other tests.
In
order to select the third test, V3 and Z3 are computed
following the procedure already explained in respect
of V2 and Z2. The formula for V3, is V3 = V2 + b2
(criterion) x C2 (each test and Z3, is Z3 = Z2 + b2
(a given test) x C2 (same test). The third selected
test, like the second one must have the highest (V23
¸ Z3) quotient. Here the largest quotient 0.0101
belongs to the ratio of gross surplus to sale of power
by the board. The other relevant calculations are
made, following the procedures already explained in
connection with the selection of the second test.
They are recorded in the appropriate tables.
In
order to select the 4th test a3, b3, c3, b4, and z4
are calculated. The highest quotient of (V24 ¸
Z4) of the 4th test and other relevant tests are calculated.
Here the contribution of the 4th test viz. gross surplus
to sales is highly negligible. Hence the selection
of the relevant control variables is restricted to
(1) Capital assts to total assets, (2) Natural log
of sales and (3) Gross surplus to sales of power.
They collectively contribute 96.4% variation in the
capital structure of Tamilnadu Electricity Board.
In
Table 6 the three selected tests and the criterion
are recorded in the order in which they have been
selected for the battery of control variables. Each
row in Table-6 when equated to zero, is an equation
defining the b weights. Solving them b1 = 0.8452.
b4 = 0.2679 and b6 = -0.0756 are obtained.
Interpretation:
The
foregoing empirical exercise makes it clear that the
ratios of capital assets to total assets, gross surplus
to sales ,and the natural log of sales characterize
the capital structure of the TNEB. The influence of
the first ratio is quite significant (0.8452) while
that of the second one is not significant (-0.0756).
Sales has modest influence (0.2679) on the debt-equity
ratio. These suggest that the Board has to concentrate
more on augmenting its income. The low gross surplus
suggests the growing manufacturing expenses and the
poor inflow of revenue income in spite of several
upward revisions of tariff structures. During the
period of study tariffs have been revised six times.
Lack of income from the supply of power to the farm
sector more due to political consideration, loss of
power due to technical and non-technical reasons,
theft of power, misuse of concessions given to certain
categories of consumers etc. are the underlining factors
afflicting the board. To turn the corner and brave
foreign competition, the board has to make it clear
to the political powers that electricity is no longer
a free good, since the Electricity Supply Act insists
on a minimum of 3% return on capital employed.
Restructuring
Managerial Strategy:
The
ultimate success of an enterprise in competition hinges
on its managerial excellence. It is in this area enterprises
can develop & sustains their uniqueness. This
calls for investment in R&D which could generate
innovative processes, employee reskilling and multi-skill
development with emphasis on customer satisfaction
in a global perspective10. To wage a war against productivity
illness wherever possible TNEB should revamp processes,
reduce overheads and redundant activities, and enhance
quality of the products and services, ridding the
organization of mistakes and miscommunications. Besides
streamlining rationally the internal processes in
all areas of operation with special emphasis on procurements
and replacements, the Board in the present liberalized
atmosphere has to strive for strategic partnership
with new entrants. This is indeed a super challenge
the Board has to cope with.
To
achieve super efficiency, a genuine strategic partner
who will offer substantial opportunities, to enhance
overall performance should be identified. Secondly
an executive steering committee of leaders from both
should be constituted to reshape investments, roles,
and share benefits. It can also evolve procedures
for resolving disputes. A technical team of experts
from both should suggest ways and means for process
redesigning and changes in management, keeping in
mind
a)
the interest of the final customers, b) the restructuring
of the entire process as a single unit with none repeated
more than once and, c) the operation of the entire
process with single data base10. Finally the implementation
of this strategy should aim at an early benefits.
The communication chain at each level should be intact
so that all concerned will be knowing the ongoing
changes around them. Technology audit must supply
information to the management in the relevance of
current technology, its capability in fulfilling the
needs of the customers in a dynamic environment, the
technology of the rivals and the threat from the emerging
technologies11.
Innovate
or Perish:
In
any organization, there are white space and black
space. The former is large but mostly unoccupied territory
where rules are vague, authority is fuzzy, budgets
are non-existent and strategy is imprecise. The latter
encompasses all opportunities, an organization has
formally targeted and organized itself to capture12.
Survey results suggest that technical personnel are
more innovative than top management is. Hence the
biggest challenge is to identify creative people and
give them specialized attention so that the organization
will reap rich dividends. Creative employees have
to be managed in a specialized way to maximize their
potentials13. The Berlin Wall that lies between various
hierarchies must be smashed. "Each for all and
all for each" should be the maxim of the organization.
Level 5 leaders are best suited to this formidable
task. Such a leader is modest, calm, creative and
determined. He exhibits an unwavering resolve to do
whatever must be done. He is humane, willful, shy
and fearless. He will never blame others, external
factors or bad luck14. He is holistic in his approach
to all issues confronting him. He performs his duties
with pointed devotion. Bhagavadgita calls him a Karma
Yogi.
Such
leaders are necessary for huge organizations such
as TNEB to turn the corner. The positive qualities
described above can be nurtured by the Transcendental
Meditation and the TM-Sidhi programmes of His Holiness
Maharishi Mahesh Yogi. Scientific research on these
programmes and their impact on practitioners have
proved beyond doubts that these Vedic techniques can
activate the creative stimuli lying dormant in human
beings. People practicing these techniques exhibit
high degree of mental alertness and psychophysiological
integration as indicated by faster reaction to external
stimuli. They also promote auditory acuity, and enhance
sensitivity, indicating the growth of flexibility
in the functioning of nervous system15. The following
diagram describes significant positive Inter-correlations
among EEG coherence (coh), creativity (CR), Paired
Hoffman Reflex (PHR) which measures responsiveness
of central nervous system, and clarity of experience
of Transcendental Consciousness (TC) suggesting that
these Vedic Technologies if practiced regularly, are
bound to promote integrated personality in employees
through coherent thinking, clarity, creativity and
neuropsychological efficiency16.
Integrated personality in employees will go a long
way towards improving interpersonal relation and thereby
providing a congenial atmosphere wherein everyone
will contribute his / her best for the organization.
These
will provide the much needed impact on higher productivity
and growing profitability. In the current rapidly
changing socio-economic scenario, it is imperative
that the creative spirit does not wane but is further
manured and strengthened through these Vedic technologies
even more effectively, since they unlock the secrets
of future growth and prosperity. These may sound a
far cry from reality, but we have no other option
if we want to give our teeming millions a decent standard
of living in the near future.
***
Endnotes:
1.
Tamilnadu Electricity Board, Statistics at a glance
- various reports.
2. Ibid
3. Sheridan, Titman and Roberto Wessels, 1988 "The
Determinants of Capital Structure Choice". The
Journal of Finance Vol. XIII No.1 March P 3.
4. Ibid
5. Ibid
6. Ibid
7. Ibid
8. Ibid
9. Managing Global Competition, Achieving World Class
Program, Arunkumar J. P- 165.
10. Harvard Business Review Sep. 2001 The Superefficient
Company Michael Hammer P88-9.
11. Managing Global Competition.
12. Harvard Business Review Feb. 2001 Managing in
the White Space Mark C Halety and Nitin Nohria P165.
13. Effective Creativity - Harold R McAlindon - How
Effectively are we Managing Innovation, P 335-356.
14. Harvard Business Review Jan. 2001 Level 5 Leadership:
The Triumph of Humility and Fierce Resolve, Jim Collins
P 73.
15. Scientific Research on Maharishi's Transcendental
Meditation and TM-Sidhi Program collected papers Vol.
3 MERU Publication No N 312221 Ed. by Roger Chambers,
Geoffrey Clements, Hartmunt Schenkluhn, Michael Weirless
P1926.
16. Scientific Research on The Transcendental Meditation
collected papers Vol. 1 Ed.
by
David W Orome - Johnson and John T Farrow MERU Press
Pub No. G K 81 P 680.
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