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CHAPTER VIII

SUMMARY AND CONCLUSIONS

There has been increased level of globalization, liberalization and rapid

economic expansion after early nineties. Despite the continued to economic

slowdown, the business environment is still frenetic as companies struggle to shift to

business strategies, lower costs and improve quality and service. It is no secret that

today’s business managers have to consider the effects of global economic uncertainty,

geopolitical unrest, and increased shareholder alertness, strict watch by regulatory

bodies, limited resources and the increasing complexity of business. Investment and

financing decisions are in the midst of this transformation journey. The aim of the

present chapter is to briefly summarize the major findings of the work. This apart, the

chapter also presents the limitations and some suggestions for future researches. The

present study has tried to study the relationship between capital expenditure

(corporate investment) and financing pattern of Indian corporate sector.

Investment decisions are an important aspect of managerial decisions.

Traditional finance theories have considered investment decisions as unrelated to

financing decisions. However, this conclusion is reached on the pre-condition of a

perfect market with no frictions, i.e. there is no tax, no cost to bankruptcy, nor any

other transaction costs, no information asymmetry, and managers always maximize

shareholders’ wealth. In such a perfect market, investment decisions are completely

separated from financing decisions, and managers only need to identify the positive

NPV projects for the firm (MM, 1958)263. However, finance literature in recent years

recognizes that the market is imperfect. In an imperfect market, various factors

influence firms’ investment decisions.

As this study aims at understanding capital expenditure behavior of major

Indian companies, these expenditures have been referred to as business fixed

investment or corporate investment in a broader paradigm. Corporate investment is in

turn a significant barometer of growth and development in an economy and involves

huge stakes. Five basic models of investment have been highlighted to bring forward

263 Modigliani, F. and M. Miller, "The Cost of Capital, Corporation Finance and the Theory of

Investment", American Economic Review 48, 1958, 261-297

274

the relative importance of the various factors (output, cashflows, cost of capital, and

so on) in shaping up the investment decision. The present study has used accelerator-

cashflow model as the basic model of analysis as change in output and internal funds

seem to be the most significant factors in explaining investment. Most of the studies

of Indian origin have used accelerator, accelerator cashflow models due to data

availability constraints attached to user cost of capital concept of neoclassical mode.

Moreover, markets in India are not efficient enough to reflect the true value of firms

and thereby restrict the usage of Tobin’s Q. Further, the different sources available

with firms’ for raising funds have also been provided. The propositions laid by

Modigliani and Miller (hereafter referred as MM) in their seminal article of 1958264

have proved to be a landmark in the literature of corporate finance. They showed that

a firm’s financial policy is irrelevant for taking investment and dividend decisions by

proving that the market value of the firm depends only on its profits and is

independent of its capital structure. They argued that internal and external funds are

perfect substitutes. However, this separation of investment and financing decisions

was presented with the underlying assumptions of perfect and symmetric information.

A vast empirical literature supports the hierarchy of financing which expects

that the investment expenditure of some firms may be constrained by lack of

internally generated funds. Various factors like access to markets, availability of

information and transaction costs make internal sources of finance preferred over

external sources for a number of firms. For such firms, the cost of external capital

does indeed seem to exceed the cost of internal funds. Myers and Majluf (1984)265

have tagged the hierarchy of financing driven by asymmetric information and/or the

real direct and indirect costs of different sources of financing as the pecking order

theory. The firms utilize internal finances for positive net present value projects in the

first instance, subsequently debt (as the least risky form of external financing)

followed by all kinds of hybrid debt with equity components and finally with external

equity as a last resort.

264 Modigliani and Miller, op. cit. 265 Myers, Stewart. C. and Majluf, Nicholas S., “Corporate Financing and Investment Decisions When

Firms have Information that Investors do not”, Journal of Financial Economics, 13, 1984, pp. 187-221.

275

Accordingly, a positive relation between investment and internal funds may

result from asymmetric information because the lack of internal capital and the ‘high

cost’ of external capital create an underinvestment problem (Goergen and Renneboog,

2000)266. To put it in another way, the positive relation may also be the outcome of

an abundance of retained earnings which makes internal funds too inexpensive (from

the management’s point of view). In certain firms agency costs also impact the

relation between investment and internal funds. In such cases, managers’ interests are

not perfectly aligned with those of the shareholders, (Bernanke and Gertler, 1989267):

managerial decision-making may be motivated by ‘empire building’ and lead to

overinvestment. In this setting, managers may place a discount on internal funds and

may overspend by undertaking even negative NPV projects as long as there is

excessive liquidity in the firm because managers may derive more private benefits by

increasing their firm’s size (Hart and Moore, 1995)268.

The question whether or not the level of investment depends on sources of

finance, has drawn substantial attention over the recent decades since the seminal

paper by Fazzari, Hubbard and Petersen (1988)269 rekindled the interest in the

determinants of investments. However, relatively few studies tested the investment-

financing relation in Indian context. Notable Indian contributions include,

Krishnamurty and Sastry (1975)270, Athey and Laumas (1994)271, Purohit, Lall and

266 Goergen M. and L. Renneboog, "Investment Policy, Internal Financing and Ownership

Concentration in the UK", Centre for Economic Research, November 2000 267 Bernanke, B. and Gertler, M., "Agency Costs, Net Worth and Business Fluctuations," American

Economic Review, 73, 1989, pp 257 - 276. 268 Hart, Oliver, and John Moore, “Debt and Seniority: An Analysis of the Role of Hard Claims in

Constraining Management”, American Economic Review, 85, Issue 3, June, 1995, pp. 567-586 269 Fazzari, Steven and Hubbard, R. Glenn and Petersen, Bruce C., “Financing Constraints and

Corporate Investment," NBER Working Papers 2387, National Bureau of Economic Research, Inc., September 1988

270 Krishnamurthy, K. and Sastry, D.U., Investment and Financing in the Corporate Sector in India, Tata McGraw-Hill Publishing Company Ltd, New Delhi, 1975

271 Athey, M. J. and Laumas, P. S., "Internal Funds and Corporate Investment in India", Journal of Development Economics, Vol. 45, 1994, pp. 287-303

276

Panda (1994)272, Gangopadhyay, Lensink and Molen (2001)273, Athukorala and Sen

(2002)274, Nair (2004)275, Bhaduri (2005)276 and Bhattacharyya (2007)277.

Hence, the role of corporate investment in the process of development has

been well recognized. A robust status of corporate investment is considered as a

crucial instrument for economic growth as it indicates growth in aggregate demand

followed by growth of aggregate supply resulting in a closer move towards full

employment level. Moreover, the economic reforms post Industrial Policy 1991 has

led to a paradigm shift in the corporate sector by enhancing the productivity and

performance of the same. This prompted to study the significance of financing

patterns on corporate investment decisions which is a broad area of research. This

work is motivated by the fast development in this field and attempts to extend the

status quo and contribute to current literature.

8.1 OBJECTIVES AND RESEARCH METHODOLOGY REVISITED

The present study primarily aims to study the financing of capital expenditures in

Indian corporate sector. Within this primary objective, the specific objectives of study

are:

i) To identify the trends about the frequency and size of capital expenditures.

o To study the significance of various sources of funds for financing

long-term investment decisions.

j) To analyze the importance of cashflows in firm’s investment decisions and

the nature of its relationship with corporate investment.

272 Purohit, Bad ri Narayan; Lall, Gouri Shankar and Panda, Jagannath, Capital Budgeting in India,

Kanishka Publishers Distributors, 1994 273 Gangopadhyay, S., Lensink, R. and Van Der Molen, R., "Business Groups, Financing Constraints

and Investment", CCSO Quarterly Journal, Vol. 3, No. 4, 2001 274 Athukorala, P.C. and K. Sen, ''Liberalization and Business Investment in India'', Australian and

East Anglian Universities: Research School of Pacific and Asian Studies Press, 2002 275 Nair, V.R. Prabhakaran, "Financial Liberalization and Determinants of Investment: An Enquiry

into Indian Private Corporate Manufacturing Sector", 8th Capital Markets Conference, Indian Institute of Capital Markets Paper, December 20, 2004, Available at SSRN: http://ssrn.com/abstract=872268 or http://dx.doi.org/10.2139/ssrn.872268

276 Bhaduri, Saumitra N., "Investment, Financial Constraints and Financial Liberalization: Some Stylized Facts from a Developing Economy", India, Journal of Asian Economics, Volume 16, Issue 4, August 2005, pp 704-718

277 Bhattacharyya, Surajit, “Determinants of Private Corporate Investment: Evidence from Indian Manufacturing Firms”, Economic Society of South Africa, Conference, 2007

277

k) To examine the relationship between financing and capital expenditure

decisions.

Hypotheses

As regards the first objective, the hypothesis is that routine investments are

more frequent than growth related investments. The sub- hypotheses are as follows:

c) Change in net fixed assets (capital expenditure) has taken place in every

year of the study period.

d) Rate of increase in capital expenditures incurred by sample companies

has increased over the study period.

As regards the second objective of the study, it is hypothesized that borrowed

funds are most frequently used for financing capital expenditures. Following sub-

hypothesis has been developed in this regard:

g) Flow of new equity has a significant relationship with change in net

fixed assets.

h) Flow of borrowings has a significant relationship with change in net

fixed assets.

i) The coefficient for flow of borrowings is larger than coefficient of flow

of new equity in investment equation.

j) The coefficient for flow of borrowings is larger than coefficient of

operating cashflows (proxy used for internal funds) in investment

equation.

k) Change in inventory has a negative and significant relationship with

change in net fixed assets.

l) Trade credit has a positive and significant relationship with change in net

fixed assets.

As regards the third objective of the study, it is hypothesized that investment

decisions of firms are sensitive to cash-flows and there is a U-shaped relationship

between investment and cashflows. This has been elaborated as follows:

278

d) Accelerator -cashflow theory of investment is applicable in Indian

corporate sector.

e) Internal funds (operating cashflows) have a significant relationship with

change in net fixed assets.

f) There is a U-shaped relationship between change in net fixed assets

(investment) and operating cashflows.

As regards the fourth objective, the hypothesis is that sources of finance

have a positive relationship with change in net fixed assets. Within this major

hypothesis, the following hypotheses have been tested:

d. Flow of new equity has a positive relationship with change in net fixed

assets.

e. Flow of borrowings has a positive relationship with change in net fixed

assets.

f. Operating cashflows have a positive relationship with change in net

fixed assets.

The data for the study is obtained from secondary sources from database

maintained by Centre for Monitoring Indian Economy (Prowess). A sample of 176

companies from ET500 (Top 500 companies of India on turnover basis) list published

by Economic Times Group in 2008 is considered. The study is based on the initial

sample of 500 largest companies of India on the premise that large companies are

actively involved in capital (investment) expenditures thereby rendering authenticity

to the results. Government companies run as commercial enterprises by the

government have also been included in the sample subject to sample selection criteria.

The following criterion has been applied to select companies in the study:

• Continuity of Operations over the study period from 1994-95 to 2008-09.

• Consistent Data Availability for the fourteen year study period.

• Common and Consistent Accounting Year throughout the fourteen years.

279

The trends have been captured by tabulating the major variables used in the study

for aggregate as well as industry-wise samples. The same have been graphically

depicted by using line charts.

Since this is a study of investment behavior of Indian corporate sector requiring a

cross-section study comprising of companies over fourteen years (1994-95 to 2008-

09), panel data models are used for regression and estimation. In this study, panel data

model has been used with balanced dataset. The classical regression (Ordinary Least

Squares) results have been estimated using LIMDEP Software, Version 7.0. Further,

fixed effects model has been examined wherever, LM test statistic favors fixed

effects/ random effects model over classical regression. A choice between fixed and

random effects model has been made as suggested by Hausman Test statistic.

Additionally, fixed effects results have been presented for both ‘group dummy’ and

‘group dummy and period effects’. In the present study, the issue of heteroskedasticity

has been addressed by scaling down the dependent and independent variables by

beginning of the year value of net fixed assets. Hence, no specific tests had to be

carried out. Correlation matrix for various independent variables has been estimated

for aggregate as well as industry group-wise sample. The analysis of these matrices

has been carried out to study the existence and extent of multicollinearity. Moreover,

auto-correlation has been addressed by analyzing Durbin-Watson statistic. The model

has been specified and estimated for the cumulative sample and industry-wise sub-

samples.

8.2 MAJOR FINDINGS

This section has been sub-divided into three sub-sections to discuss the

findings of the study. Section 8.2.1 deals with findings related to trend analysis and

Section 8.2.2 presents Empirical findings related to aggregate sample. Empirical

findings related to industry wise sub-samples have been provided in Section 8.2.3.

8.2.1 Findings Related to Trend Analysis

280

The major findings trend analysis pertaining to major variables of the study

have been captured below.

a. The rate of change in net fixed assets over the study period shows that routine

investments are more frequent than growth related investments. This trend has

been in line with the hypothesis for the study.

b. There has been a consistent rise in the change in output figures of the sample

companies over the study period. Change in output and change in net fixed

assets have significant and positive correlation. This variable has been used as

a proxy for accelerator for both current and previous year values.

c. A significantly positive correlation amongst flow of borrowings and change in

net fixed assets lend support to the hypothesis of importance of borrowings in

explaining capital expenditure decisions of the firms. It seems that external

funds are heavily employed for sponsoring the capital expenditures of Indian

corporate sector.

d. Trend analysis pattern of sales and change in output have been largely similar

and the degree of their correlation with net fixed assets has been found to be

significant and positive.

e. A rhythmic trend has been observed between change in net fixed assets and

trade credit. The movements of both the variables strongly favor a highly

positive correlation coefficient amongst the two variables.

f. Trends illustrate a significantly positive relationship between operating

cashflows and change in net fixed assets indicating the importance of internal

funds for Indian corporate sector.

g. A positive but statistically insignificant relationship has been found amongst

change in net fixed assets and change in inventory. A deeper understanding

has been gathered through panel data analysis.

h. It is interesting to note that flow of equity has been positive for maximum part

of the study but 1998-99 has witnessed a negative growth which coincides

with the introduction of buy-back norms in India. However, the quantum of

funds raised through equity has been much less than other sources of finance.

8.2.2 Empirical Findings Related to Aggregate Sample

281

The panel regression results for the aggregate sample of 176 large sized Indian

companies have been presented below.

a. The results for the aggregate sample have been robust and majorly in line with

the pre-established hypothesis that all explanatory variables except change in

inventory have a positive relationship with change in net fixed assets

(corporate investment) and are significant at different significance levels.

b. Accelerator (change in output) theory of investment plays a determining role

in firm’s fixed investment behavior. Change in output (Y) representing

accelerator has found empirical support as an important factor in influencing

the investment decision. Both changes in output (Y) and change in output in

the previous year (LAGY) are found to be statistically significant at 1 percent

and 10 percent level of significance in fixed effects results with group dummy

variables. It is pertinent to note here that fixed effects results have been

favored over classical regression and random effects model as per Lagrange

Multiplier Test Statistic and Hausman Test Statistic.

c. The coefficient of change in net fixed assets in the previous year (LAGF) has

not been found to be significant which in turn indicates that investments in

fixed assets are not dynamically related to the level of investment in the

previous period.

d. Change in inventory has been found as negatively significant. This suggests

the substitution relationship between fixed and inventory investment due to

significant negative coefficient of change in inventory. Hence, this finding

confirms the theoretical belief that in order to commit a greater share of funds

towards long-term investment, inventory investment of a company has to be

streamlined.

e. The results confirm a highly significant and positive relation of trade credit

with change in net fixed assets as postulated thereby paving way for

acceptance of null hypothesis. Therefore, the sample from Indian corporate

sector confirms the theoretical justification that increase in short-term funds

through better bargains with creditors and acceptances effects the change in

net fixed assets in a positive and significant manner.

282

f. Cashflow from operating activities (CFO) which has been used as a proxy for

internal funds in the study has been found to be highly significant with a

positive coefficient at 1 percent level of significance. This lends support to the

theoretical belief that internally generated surplus funds play a noteworthy role

in influencing the level of investment in net fixed assets.

g. A notable contribution of equity financing in total funds raised has been

observed during the analysis of panel data results. The significant impact of

this variable can be attributed to a robust and growing economy. This finding

of the study goes against the famous pecking order hypothesis and this may be

attributed to the fact that during the study period Indian capital markets have

developed rapidly, not only in terms of turnover and market capitalization but

also in terms of availability of diverse fund-raising instruments.

h. The analysis reveals that flow of borrowings is highly significant variable.

Hence, despite rapid economic growth and significance of flow of equity in

explaining investment behavior of firms, this variable has been found to have

a positive and highly significant relation with change in net fixed assets.

i. The study has postulated a non-monotonic relationship between investment

and cashflows. In order to further dwell on this postulate, a square and a cubic

term in the regression to capture the higher order relationship between cash

flow and investment to empirically check for existence of U-shaped

relationship between investment and cashflow. As postulated, CFO has a

positive coefficient which turns to be negative with CFO square and finally

returns to be positive with CFO cube. Hence, the U-shaped relationship

between investment and cashflow has been reinstated by empirical findings.

8.2.3 Empirical Findings Related to Industry-Wise Sample

283

This section presents the regression results of financing of capital expenditures

for twelve of fourteen industry groups. Panel regression has not been carried out for

coal mining and paper industry as there is only one company each from these industry

groups in the aggregate sample.

a. Basic Metal Alloys and Metal Products Industry

i. Lagrange Multiplier Test Statistic has favored ordinary least squares

over fixed and/or random effects model.

ii. The significance of change in output (Y) along with the positive sign

indicates presence of accelerator model in this industry group.

However, a negative and significant change in output in the previous

year (LAGY) is contrary to the hypothesis.

iii. Amongst the internal and external sources of finance used in the

investment equation, Flow of borrowings (FB) and cashflow from

operating activities (CFO) appears to be the most significant

determining variables of investment. Apparently, industries in this

group rely more heavily on borrowing than equity as preferred source

of financing their investment requirements. It is pertinent to note here

that Flow of equity (FEQ) has been observed to have a negatively

significant coefficient, opposing the hypothesis.

iv. Trade credit and change in inventory have been insignificant in the

panel data results.

v. The U-shaped relationship hypothesized between investment and

cashflow is not supported by the results of this industry group. Rather a

positive coefficient for operating cashflow square (CFSQ) and a

negative coefficient for operating cashflow cube (CFCUBE) indicate

towards the obverse, i.e., traces of an inverse U-shaped relationship in

this group.

b. Beverages, Tobacco and Tobacco Products Industry

284

i. Classical regression results have been preferred over fixed and/or

random effects model.

ii. Accelerator theory has not been found operational due to insignificant

coefficient assigned to both change in output in the current and

previous year.

iii. Flow of borrowings (FB) has statistically significant and positive

coefficient as hypothesized. It implies that external funds raised in the

form of borrowings are predominantly used for financing investment in

this industry group. The other three variables representing sources of

finance, viz. cashflows from operating activities and flow of equity and

trade credit have insignificant coefficient.

iv. In regressions with higher powers of cashflow, it has been found that

only flow of borrowings (FB) have a significant coefficient. The U-

shaped relationship between investment and cashflows lacks empirical

support in this industry group.

c. Chemical and Chemical Products Industry

i. A significant and positive coefficient for change in output in the

previous year (LAGY) while insignificant coefficient for change in

output (Y) implies that the accelerator operates with a lag in case of

chemicals industry.

ii. Contrary to the hypothesis, change in inventory (CHG_I) has a positive

and significant coefficient. This implies that the firms in this group

have increased their capital investment even when their inventories

have gone up.

iii. Though operating cashflows (CFO) and flow of borrowings (FB) have

a positive and statistically significant coefficient, flow of equity (FEQ)

is insignificant. Positive and significant coefficient for operating

cashflows (CFO) along with borrowings (FB) indicates that both

internal as well as external sources of finance are crucial in shaping

capital expenditures of this industry group.

285

iv. In regressions with higher powers of cashflow, operating cashflows

(CFO)’s coefficient turns negative. Operating cashflow square (CFSQ)

has a positive coefficient and operating cashflow cube (CFCUBE) has

a negative coefficient (significant only in ordinary least squares (OLS)).

Thus there is some empirical evidence against U-shaped relationship in

this group of industry.

d. Food Articles Industry

i. The insignificant coefficient of change in output in the current (Y) and

previous year (LAGY) indicates absence of accelerator theory in this

industry.

ii. Flow of borrowings (FB) and trade credit (TC) has positive and

significant coefficient as hypothesized. However, cashflow from

operating activities (CFO) and flow of equity (FEQ) have been

insignificant.

iii. In regressions with higher powers of cashflow the coefficient for

operating cashflow square (CFSQ) is statistically significant positive

and there is negative coefficient for operating cashflow cube

(CFCUBE). Thus, empirical results do not support U-shaped

relationship between cashflow and investment.

e. Food Products Industry

i. The presence of accelerator theory has been confirmed in this industry

by a positive and significant coefficient of Change in output (Y)

ii. Operating cashflows (CFO), flow of equity (FEQ) and flow of

borrowings (FB) have a positive and significant coefficient. These

results are pretty much in line with the hypothesis. Hence, both internal

and external funds are employed for financing the capital expenditure

needs of the firms.

iii. In regressions with higher powers of cashflow, some empirical support

for a U-shaped relationship between cashflow and investment has been

observed. Although, (positive) coefficient for operating cashflows

286

(CFO) is not statistically significant, the negative coefficient for

cashflow square and positive coefficient for cashflow cube is

significant. Therefore, there is some empirical evidence of U-shaped

relationship between investment and cashflow in this group.

f. Machinery and Machine Tools Industry

i. Empirical results are not in line with hypothesis in case of change in

output (Y) implying that the accelerator is not in operation in this

group.

ii. Except flow of equity (FEQ) all other sources of finance including

operating cashflows (CFO), Flow of borrowings (FB) and trade credit

(TC) have positive and significant coefficients as hypothesized.

iii. Change in inventory (CHG_I) is an important variable for this group

with a negative and significant coefficient as hypothesized. This

signals a substitution relationship between short-term (inventory) and

long-term (capital expenditures) investment.

iv. There is strong empirical support for U-shaped relationship between

cashflow and investment. The coefficients of cashflows, cashflow

square and cashflow cube are significant and have positive, negative

and positive sign respectively.

g. Minerals Industry

i. Accelerator operates in this industry but with a year’s lag. This has

been deduced by an insignificant coefficient of change in output of

current year (Y) but significant and positive coefficient of change in

output in the previous year (LAGY). However, this result has been

provided in fixed effects model (FEM) (group dummy) and both the

indicators of accelerator theory have insignificant coefficients in

classical regression.

ii. The results are robust and broadly in line with the hypothesis for all the

variables representing sources of finance. Flow of equity (FEQ) and

trade credit (TC) have positive and significant coefficient in ordinary

287

least squares (OLS). Additionally, operating cashflows (CFO) and flow

of borrowings (FB) have significant and positive coefficients in fixed

effects model with group dummy and period effects.

iii. There is empirical evidence for a U-shaped relationship between

investment and cashflow. Both internal and external sources of finance

have significant coefficients in the investment equation.

h. Non Metallic Mineral Products Industry

i. Contrary to the hypothesis change in inventory (CHG_I) has a positive

and significant coefficient along with change in output in the previous

year (LAGY) (in ordinary least squares (OLS) and fixed effects model

(FEM) group dummy).

ii. Operating cashflows (CFO), flow of borrowings (FB) and trade credit

(TC) have positive and significant coefficients. However, no major

role of equity has been highlighted by the results as the respective

coefficient is insignificant.

iii. There is no support for U-shaped relationship as operating cashflows

(CFO)’s coefficient becomes insignificant in regressions run with

higher powers for cashflows.

i. Rubber and Plastic Products Industry

i. There is some evidence in support of accelerator theory as change in

output (Y) has a significant and positive coefficient.

ii. Flow of borrowings (FB) and operating cashflows (CFO) have positive

and significant coefficients signaling their dominance in explaining the

investment equation in this industry group. However, flow of equity

(FEQ) and trade credit (TC) do not seem to play a major role due to

insignificant coefficients in panel regression results.

iii. Operating cashflows (CFO) has a positive but insignificant coefficient,

operating cashflow square (CFSQ) has a negative but insignificant

coefficient. Interestingly there is significant and positive coefficient for

288

operating cashflow cube (CFCUBE). Thus, the U-shaped relationship

is not fully established by empirical results in this case.

j. Textiles Industry

i. Change in output (Y) has a positive and significant coefficient

supporting the existence of accelerator theory.

ii. Flow of borrowings (FB) has a positive and significant coefficient as

hypothesized.

iii. The negatively significant coefficient of change in inventory (CHG_I)

indicates a substitution relationship between long-term and short-term

investment.

iv. This industry group has been unable to gather support for U-shaped

relationship between cashflow and investment.

k. Transport Equipment and Parts Industry

i. Accelerator theory has strong empirical support in this group. Change

in output (Y) has a significant positive coefficient.

ii. However, contrary to the hypothesis, change in inventory (CHG_I) has

a significant positive coefficient in ordinary least squares (OLS) results.

iii. In regressions with higher powers of cashflow the signs of coefficients

are not in line with the theory of U-shaped relationship.

l. Electricity Industry

i. Accelerator theory has strong empirical support in this group. Change

in output (Y) has a significant positive coefficient.

ii. However, contrary to the hypothesis, change in inventory (CHG_I) has

a significant positive coefficient in ordinary least squares (OLS) results.

iii. In regressions with higher powers of cashflow the signs of coefficients are

not in line with the theory of U-shaped relationship.

Observing the above findings, it can be concluded that flow of borrowings (FB)

appears to be more important variable as compared to flow of equity (FEQ). This has

289

been observed despite the fact that Indian capital markets have developed

tremendously during the period of study. Apparently, either the firms consider it

easier to borrow rather than raising capital through stock exchanges because of

procedural issues, and/or the firms find borrowing a cheaper source of funds as

compared to equity capital. The industry group specific results have wide divergence

from the hypotheses, whereas composite results are broadly in line with the

hypotheses. Thus it is plausible to argue that the composite panel is more

representative than the industry specific panels.

8.3 CONTRIBUTION OF THE STUDY

The Indian economy is one of the fastest growing economies of the world.

Despite the recent economic recession faced by some of the biggest economies of the

world, Indian economy has fared remarkably well at the financial front. The

frequency, quantum and diversity of investment opportunities faced by present day

Indian corporate sector is the primary reason for understanding the preferred

financing pattern in depth. Additionally post industrial policy 1991, the structural and

macroeconomic reforms followed due to liberalization, privatization and globalization

regime makes it even more interesting to study the financing patterns in an era

accompanied by plethora of investment opportunities.

The findings of this study will be of great use by policy makers, the Indian

corporate sector and investors in general. The present study, besides enhancing the

existing empirical literature, has provided the results with a sample comprising of

private and public sector enterprises from Indian corporate sector. The study will be

found useful from various dimensions and its justification is derived from wider

considerations, both academic and practical in terms of its relevance to the Indian

corporate sector.

The study will be especially serving both public and private sector enterprises

as very few studies take a combined sample for analysis. It will also be of

considerable usage to the companies in identifying and understanding the deviations

in financing pattern of a particular industry group from the aggregate sample results.

As the study covers the period after liberalization, it will provide a reference ground

290

for financial heads and top management executives in making choices between

various sources of finance for various investment proposals. Moreover, the results

pertaining to U-shaped relationship of investment and cashflows have enriched the

available literature on this topic by providing results from a developing economy

sample.

Additionally, the sensitivity of investment to cashflows has strengthened the

signaling effect of cashflows. The status of cashflows may be used by investors not

only as an indicator of future prospects but also a firm’s plan to indulge in fresh

capital expenditures. The role of trade credit in defining investment behavior of the

companies has been a highlight of the study. Finance managers, students and

researchers can explore this relationship at a larger scale and work towards better

management of this variable keeping in mind its relative importance.

In the wake of a globalised markets, liberalized trade regimes, economic

recessions and challenges presented by atrocious natural calamities, Indian corporate

sector has been undergoing a dramatic transformation. Investment opportunities have

expanded beyond the geographical borders and so has been the widening of financing

options and above all the dependence on capital markets has increased. In this

scenario, the empirical finding of this study will be interesting to financial institutions

like IDBI, IFCI, ICICI, along with Commercial Banks. As these institutions play a

pivotal role in answering the financing needs of corporate sector. The findings will be

relevant to the private corporate sector in general for their investment portfolio

decisions.

An exhaustive list of contribution of the study has not been provided keeping

in consideration that a study revolving around investment and financing decisions and

covering multiple variables may shed light on various aspects of financial

management and may help the researchers in answering various queries.

8.4 SUGGESTIONS FOR FUTURE RESEARCH

The study has primarily revolved around the relationship between capital

expenditures and preferred financing pattern of Indian corporate sector. A few

suggestions and related areas where further investigations can be done are as follows:

291

1. Re-specification of existing variables and inclusion of new variables is

always a possibility.

2. The study has concentrated on large scale companies only. An

extensive study can be conducted covering medium and small scale

companies.

3. International comparison of the financing pattern and its relationship

with capital expenditures could be made and their findings can be

generalized.

To finish off with, this is certainly not an exhaustive list but just an effort to

procure areas whose study might reap juicy fruits. The present chapter summarizes

the research work carried out and discussed in previous chapters.

292

APPENDIX I LIST OF SAMPLE COMPANIES

1 Aarti Industries Ltd. 36 Chettinad Cement Corpn. Ltd. 2 Aditya Birla Nuvo Ltd. 37 Cipla Ltd. 3 Agro Tech Foods Ltd. 38 Colgate-Palmolive (India) Ltd. 4 Akzo Nobel India Ltd. (ICI India) 39 Coromandel International Ltd. 5 Alok Industries Ltd. 40 Crompton Greaves Ltd. 6 Amara Raja Batteries Ltd. 41 Cummins India Ltd.

7 Anik Industries Ltd. 42 D C M Shriram Consolidated Ltd.

8 Apar Industries Ltd. 43 D C W Ltd. 9 Apollo Tyres Ltd. 44 Dabur India Ltd. 10 Asahi India Glass Ltd. 45 Dalmia Cement (Bharat) Ltd.

11 Ashapura Minechem Ltd. 46 Deepak Fertilisers & Petrochemicals Corpn. Ltd.

12 Ashok Leyland Ltd. 47 Dr. Reddy'S Laboratories Ltd. 13 Asian Paints Ltd. 48 E I D-Parry (India) Ltd. 14 Atul Ltd. 49 Eicher Motors Ltd. 15 B A S F India Ltd. 50 Electrosteel Castings Ltd. 16 Bajaj Electricals Ltd. 51 Electrotherm (India) Ltd. 17 Balkrishna Industries Ltd. 52 Emco Ltd. 18 Balmer Lawrie & Co. Ltd. 53 Eveready Industries (India) Ltd. 19 Berger Paints India Ltd. 54 Exide Industries Ltd.

20 Bharat Electronics Ltd. 55 Fertilisers & Chemicals, Travancore Ltd.

21 Bharat Forge Ltd. 56 Finolex Cables Ltd. 22 Bharat Heavy Electricals Ltd. 57 Forbes & Co. Ltd. 23 Bharat Petroleum Corpn. Ltd. 58 Force Motors Ltd. 24 Bhushan Steel Ltd. 59 Godfrey Phillips India Ltd. 25 Birla Corporation Ltd. 60 Godrej Industries Ltd. 26 Blue Star Ltd. 61 Graphite India Ltd. 27 Bombay Dyeing & Mfg. Co. Ltd. 62 Grasim Industries Ltd.

28 Britannia Industries Ltd. 63 Gujarat Alkalies & Chemicals Ltd.

29 C E S C Ltd. 64 Gujarat Ambuja Exports Ltd. 30 C M C Ltd. 65 Gujarat Fluorochemicals Ltd.

31 Carborundum Universal Ltd. 66 Gujarat Industries Power Co. Ltd.

32 Century Enka Ltd. 67 Gujarat Mineral Development Corporation Ltd.

33 Century Textiles & Inds. Ltd. 68 Gulf Oil Corporation Ltd.

34 Chambal Fertilisers & Chemicals Ltd.

69 H B L Power Systems Ltd.

35 Chennai Petroleum Corpn. Ltd. 70 H E G Ltd. 71 Hatsun Agro Products Ltd. 111 Motherson Sumi Systems Ltd. 72 Havells India Ltd. 112 Mukand Ltd.

293

73 Hero Honda Motors Ltd. 113 N M D C Ltd. 74 Himatsingka Seide Ltd. 114 N T P C Ltd.

75 Hindalco Industries Ltd. 115 Nagarjuna Fertilizers & Chemicals Ltd.

76 Hindustan Petroleum Corpn. Ltd. 116 Nahar Industrial Enterprises Ltd. 77 Hindustan Zinc Ltd. 117 Nahar Spinning Mills Ltd.

78 Hindusthan National Glass & Inds. Ltd.

118 National Aluminium Co. Ltd.

79 I T C Ltd. 119 National Fertilizers Ltd. 80 I T I Ltd. 120 National Steel & Agro Inds. Ltd. 81 India Cements Ltd. 121 Nava Bharat Ventures Ltd. 82 India Glycols Ltd. 122 Neyveli Lignite Corpn. Ltd. 83 Ipca Laboratories Ltd. 123 Nilkamal Ltd. 84 Jindal Poly Films Ltd. 124 Nirma Ltd. 85 Jubilant Organosys Ltd. 125 O C L India Ltd. 86 Jyoti Structures Ltd. 126 Omax Autos Ltd.

87 K R B L Ltd. 127 Orchid Chemicals & Pharmaceuticals Ltd.

88 K S Oils Ltd. 128 Orient Paper & Inds. Ltd.

89 Kalpataru Power Transmission Ltd.

129 Panacea Biotec Ltd.

90 Kalyani Steels Ltd. 130 Pidilite Industries Ltd. 91 Kansai Nerolac Paints Ltd. 131 Piramal Healthcare Ltd. 92 Kei Industries Ltd. 132 Polyplex Corporation Ltd. 93 Kesoram Industries Ltd. 133 Power Grid Corpn. Of India Ltd. 94 Kirloskar Brothers Ltd. 134 Praj Industries Ltd. 95 Kirloskar Ferrous Inds. Ltd. 135 R S W M Ltd. 96 Kohinoor Foods Ltd. 136 Rallis India Ltd.

97 Lakshmi Machine Works Ltd. 137 Rashtriya Chemicals & Fertilizers Ltd.

98 Lloyds Steel Inds. Ltd. 138 Ratnamani Metals & Tubes Ltd. 99 Madras Cements Ltd. 139 Raymond Ltd. 100 Maharashtra Seamless Ltd. 140 Reliance Industries Ltd. 101 Mahindra & Mahindra Ltd. 141 Reliance Infrastructure Ltd. 102 Mahindra Ugine Steel Co. Ltd. 142 Rico Auto Inds. Ltd. 103 Man Industries (India) Ltd. 143 Ruchi Infrastructure Ltd.

104 Mangalore Chemicals & Fertilizers Ltd.

144 Ruchi Soya Inds. Ltd.

105 Marico Ltd. 145 S R F Ltd. 106 Maruti Suzuki India Ltd. 146 Salora International Ltd. 107 Matrix Laboratories Ltd. 147 Savita Oil Technologies Ltd. 108 Mirc Electronics Ltd. 148 Sesa Goa Ltd. 109 Monnet Ispat & Energy Ltd. 149 Shah Alloys Ltd. 110 Moser Baer India Ltd. 150 Shasun Chemicals & Drugs Ltd. 151 Sintex Industries Ltd. 164 Tata Global Beverages Ltd. 152 Spentex Industries Ltd. 165 Tata Metaliks Ltd.

294

153 Steel Authority Of India Ltd. 166 Tata Motors Ltd. 154 Sun Pharmaceutical Inds. Ltd. 167 Tata Power Co. Ltd. 155 Sundram Fasteners Ltd. 168 Tata Steel Ltd. 156 Surana Industries Ltd. 169 Thermax Ltd. 157 Surya Roshni Ltd. 170 Torrent Pharmaceuticals Ltd. 158 T I L Ltd. 171 Tube Investments Of India Ltd. 159 T V S Motor Co. Ltd. 172 Uttam Galva Steels Ltd.

160 Tamil Nadu Newsprint & Papers Ltd.

173 Vardhman Textiles Ltd.

161 Tamilnadu Petroproducts Ltd. 174 Voltas Ltd. 162 Tata Chemicals Ltd. 175 Wipro Ltd. 163 Tata Coffee Ltd. 176 Zuari Industries Ltd.

295

APPENDIX II WHOLSALE PRICE INDEX (BASE YEAR 1993-94 = 100)

ARTICLE 1994 -95

1995 -96

1996 -97

1997 -98

1998 -99

1999 -00

2000 -01

2001 -02

2002 -03

2003 -04

2004 -05

2005 -06

2006 -07

2007 -08

2008 -09

Food Articles 112.8 122.2 137.3 141.4 159.4 165.5 170.5 176.1 179.2 181.5 186.3 195.3 210.5 222.0 239.8

Non-Food Articles 124.2 135.4 134.2 137.5 151.8 143.0 146.5 152.9 165.4 186.3 187.6 179.1 188.2 211.9 235.8

Minerals 104.9 94.7 107.2 99.8 110.9 110.4 113.5 119.3 118.8 121.6 255.1 322.8 413.6 460.4 631.6

Coal Mining 105.1 106.4 117.7 139.8 143.6 149.1 161.1 181.7 181.1 193.6 223.3 231.6 231.6 237.7 253.5

Minerals Oils 106.1 106.2 122.9 138.7 142.9 159.9 226.2 239.5 254.7 274.3 315.8 359.8 388.1 391.6 435.2

Electricity 113.6 127.8 133.5 151.8 157.2 168.9 200.0 224.8 238.0 248.8 253.0 263.4 271.7 273.0 275.9

Food Products 114.1 117.8 124.9 134.6 149.7 151.3 145.7 145.4 153.0 166.7 174.9 176.8 182.5 190.2 209.3 Beverages, Tobacco & Tobacco Products

118.3 128.1 134.9 150.5 166.7 174.1 179.8 193.8 204.3 205.6 216.2 226.8 243.5 268.3 294.0

Textiles 118.2 129.4 118.7 115.5 114.4 115.0 119.9 119.3 122.2 131.6 135.7 129.5 132.3 130.9 138.8

Paper & Paper Products 106.1 131.2 131.0 126.7 130.8 149.3 165.4 172.8 174.0 173.3 174.6 178.5 190.7 194.2 202.7 Leather & Leather Products

109.7 119.2 121.2 128.8 133.2 154.6 149.6 141.0 130.1 146.9 155.7 166.8 159.5 166.1 167.9

Rubber & Plastic Products 106.4 123.0 124.2 124.5 123.7 123.6 125.5 126.0 132.6 135.0 134.5 139.1 148.2 158.9 166.3 Chemicals & Chemical Products

116.6 126.8 131.1 137.1 145.8 155.2 164.4 169.0 173.9 177.2 181.7 188.2 193.9 204.6 219.5

Non-Metallic Mineral Products

110.9 126.4 129.4 127.0 130.2 127.4 133.9 144.0 143.4 148.3 157.7 170.0 191.7 208.7 216.6

Basic Metals Alloys & Metals Products

108.4 120.3 125.9 130.7 132.8 135.0 140.3 140.7 145.1 167.8 203.3 218.4 233.3 248.6 285.3

Machinery & Machine Tools

106.0 111.8 115.7 115.3 116.0 116.1 123.0 129.1 130.3 132.7 140.2 147.4 155.6 166.6 174.5

Transport Equipment & Parts 107.4 115.9 123.1 127.8 131.4 135.4 143.4 146.8 147.5 147.4 154.3 159.9 162.4 166.8 175.5