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Capital Structure and Managerial Performance:
A Study of Tamilnadu Electricity Board


Introduction

Dr T.S Mohanchandralal,
Director, Maharishi Institute of Management, Bangalore

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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