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Comparison of capital structure determinants of public sector and private sector companies in India.

INTRODUCTION

Companies have been struggling with the wrong capital structures for over four decades. During credit expansions, companies have time and again failed to build enough liquidity to survive the contractions, especially those enterprises which have an unpredictable cash flow stream end up with excess debt during business slowdowns. Achieving the right capital structure by defining the composition of debt and equity for an organization to finance its operations and investments has challenged academics and practitioners alike. While many companies are holding substantial amounts of cash and discussing on what to do with it, the choice of capital structure for firms is, by and large, the most fundamental issue of the financial framework of a business entity.

We have examined 870 listed Indian companies of which 809 are Private Companies and 61 Government Companies and tested a range of hypotheses to determine which factors affect the capital structure decisions. Due to the uniqueness of India as a country, it is essential to understand the behaviour of firms in the Indian economy individually. The maturity of the Indian markets provides the motivation to study the determinants of capital structure for Indian firms.

LITERATURE REVIEW

The elusive search for optimal capital structure under the static model motivated more recent studies to focus on the long-term behaviour of debt ratio; Baker and Wurgler (2002), Welch (2004) and Kayhan and Titman (2007). Frank and Goyal (2009) reported that lagged profits become less important in determining the current leverage after 1980.

Consistent support for trade-off theory draws from the positive effect of size and value of assets on leverage ratio; Chang and Dasgupta (2009). Corroborative support is derived from the evidence that a firm's debt-equity choice is influenced by deviations from long-term target leverage; Opler and Titman (2001)

Rao and Lukose (2001), in their study, revealed that size and risk measures were additional factors which influenced capital structure decisions. Gurucharan's (2010) finding showed that higher profitable firms use less debt to finance their investment.

Ba-Abbad and Ahmad Zaluki (2012) discovered that company size and profitability had dominant roles in explaining the variation in the total debt ratios. Kouki and Said (2012) stated that firms adjust their debt levels based on a target ratio explained by several variables: firm size, profitability, growth opportunities and non-debt tax shield. Ramjee and Gwatidzo (2012) found that asset tangibility, growth, size and risk were positively related to leverage, while profitability and tax were negatively related to leverage. Owolabi and Inyang (2012) revealed that for non-financial firms, there is a significant positive relationship between asset structure (tangibility) and long-term debt ratios.

Baker and Wurgler's paper (2002) established the impact of equity market valuation on firms' debt-equity choice. Several authors including, Welch (2004), and Kayhan and Titman (2007), have used the partial adjustment model to find that fluctuations in market-to-book ratios, cash flows, investment opportunities, and stock returns lead to significant deviations from the target leverage ratio, and capital structures move back to the target level albeit at a slow rate. Kayhan and Titman (2007) showed that in market leverage regressions, the effect of profitability is positive, contrary to the notion that profitable firms use less debt.

Hovakimian and Li (2012) discovered that during the passive periods, changes in capital structure are induced only by changes in profitability with no adjustment, whereas during active financing periods, speed of adjustment is as high as one. Lemmon, Roberts and Zender (2008) report that variations in capital structure are primarily driven by factors that remains stable for long periods of time, although a transitory component makes some secondary contributions to the evolution of capital structure.

RESEARCH METHODOLOGY

Objectives

Model 1: To understand the impact of each independent variable while raising short term debt for public sector companies

Model 2: To understand the impact of each independent variable while raising long term debt for public sector companies

Model 3: To understand the impact of each independent variable while raising total debt for public sector companies

Model 4: To understand the impact of each independent variable while raising short term debt for private sector companies

Model 5: To understand the impact of each independent variable while raising long term debt for private sector companies

Model 6: To understand the impact of each independent variable while raising total debt for private sector companies

DATA SOURCE

The sample contains names of public and private sector companies listed on the National Stock Exchange. The source for entire data is Prowess. The data covers the period from 2001 to 2010. It comprises of 870 listed companies of which 809 are Private Companies and 61 Government Companies, selected on the basis of availability of complete record.

RESEARCH METHOD

Multiple regression analysis has been used by satisfying all its five assumptions, i.e. The Normality Assumption Test, The Homoscedasticity Assumption Test, The Linearity Assumption Test of each of the Independent Variables with the Dependent Variable, The Durbin-Watson d Statistic Test for Detecting Serial Correlation and The Multicollinearity Test, in trying to understand the significant and the insignificant variables.

Explanatory Variables

1. Dependent Variables

Total Debt Ratio (TDR): It is the ratio of total debt and total assets calculated by dividing total debt to total assets.

Long Term Debt Ratio (LTDR): Long term debt ratio is computed as Long Term Debt/Total Assets.

Short Term Debt Ratio (STDR): It is computed as short-term debt to total assets.

2. Independent Variables

Profitability (PROF): Operating profit rate of return (EBIT/ Total Assets) is used as a measure of profitability.

Growth (GROW): The growth factor is measured by the percentage change of assets.

Assets Tangibility (TAN): The formula used is the ratio of net fixed assets to total assets.

Size (SIZE): The measure used in this study is the natural logarithm of its total assets.

Cost of Debt (COD): The measure of Cost of Debt in the study is using interest before tax/ long term debt.

Liquidity (LIQ): It is calculated by dividing the total current assets over the total current liabilities.

Financial Distress (FINDIST): Volatility (standard deviation) of firm's cash flow is used as proxy for the observable firm's risk and the probability of financial distress.

Tax Rate (TAXR): Tax rate has been measured for each company by dividing its tax provision by profit before tax.

Debt Serving Capacity (DSC): The study proxies for debt with the ratio between profit before depreciation, interest and taxes to total interest.

Age (AGE): The dummy variable takes the value one if the firm is below the age of 20 years and zero otherwise.

RESULTS

Model 1:

Summary of Null Hypotheses of Model 1

[H.sub.011] There is no significant impact of Profitability of public sector companies on Short Term Debt

[H.sub.012] There is no significant impact of Growth of public sector companies on Short Term Debt

[H.sub.013] There is no significant impact of Asset Tangibility of public sector companies on Short Term Debt

[H.sub.014] There is no significant impact of Size of public sector companies on Short Term Debt

[H.sub.015] There is no significant impact of Cost of Debt of public sector companies on Short Term Debt

[H.sub.016] There is no significant impact of Liquidity of public sector companies on Short Term Debt

[H.sub.017] There is no significant impact of Financial Distress of public sector companies on Short Term Debt

[H.sub.018] There is no significant impact of Tax Rate of public sector companies on Short Term Debt

[H.sub.019] There is no significant impact of Debt Serving Capacity of public sector companies on Short Term Debt

[H.sub.0110] There is no significant impact of Age of public sector companies on Short Term Debt

The results of the ten independent variables of model 1 are given in the table 2 below.

Null hypothesis [H.sub.011], [H.sub.012], [H.sub.013], [H.sub.014], [H.sub.016], [H.sub.017], [H.sub.018], [H.sub.019], [H.sub.0110] were not rejected, hence it was concluded that profitability, growth, asset tangibility, size, liquidity, financial distress, tax rate, debt serving capacity and age did not produce significant impact on Short Term Debt.

Whereas, null hypothesis [H.sub.015] was rejected and it was concluded that Cost of Debt produced significant impact on Short Term Debt.

Model 2:

Summary of Null Hypotheses of Model 2

[H.sub.021] There is no significant impact of Profitability of public sector companies on Long Term Debt

[H.sub.022] There is no significant impact of Growth of public sector companies on Long Term Debt

[H.sub.023] There is no significant impact of Asset Tangibility of public sector companies on Long Term Debt

[H.sub.024] There is no significant impact of Size of public sector companies on Long Term Debt

[H.sub.025] There is no significant impact of Cost of Debt of public sector companies on Long Term Debt

[H.sub.026] There is no significant impact of Liquidity of public sector companies on Long Term Debt

[H.sub.027] There is no significant impact of Financial Distress of public sector companies on Long Term Debt

[H.sub.028] There is no significant impact of Tax Rate of public sector companies on Long Term Debt

[H.sub.029] There is no significant impact of Debt Serving Capacity of public sector companies on Long Term Debt

[H.sub.0210] There is no significant impact of Age of public sector companies on Long Term Debt

The results of the ten independent variables of model 2 are given in the table 3 below.

Null hypothesis [H.sub.021], [H.sub.022], [H.sub.023], [H.sub.026], [H.sub.027], [H.sub.028] were not rejected and hence it can be concluded that profitability, growth, asset tangibility, liquidity, financial distress and tax rate did not produce significant impact on Long Term Debt.

Whereas, null hypothesis [H.sub.024], [H.sub.025], [H.sub.029], [H.sub.0210], were rejected and hence it can be concluded that size, cost of debt, debt serving capacity and age produced significant impact on Long Term Debt.

Model 3:

Summary of Null Hypotheses of Model 3

[H.sub.031] There is no significant impact of Profitability of public sector companies on Total Debt

[H.sub.032] There is no significant impact of Growth of public sector companies on Total Debt

[H.sub.033] There is no significant impact of Asset Tangibility of public sector companies on Total Debt

[H.sub.034] There is no significant impact of Size of public sector companies on Total Debt

[H.sub.035] There is no significant impact of Cost of Debt of public sector companies on Total Debt

[H.sub.036] There is no significant impact of Liquidity of public sector companies on Total Debt

[H.sub.037] There is no significant impact of Financial Distress of public sector companies on Total Debt

[H.sub.038] There is no significant impact of Tax Rate of public sector companies on Total Debt

[H.sub.039] There is no significant impact of Debt Serving Capacity of public sector companies on Total Debt

[H.sub.0310] There is no significant impact of Age of public sector companies on Total Debt

The results of the ten independent variables of model 3 are given in the table 4 below.

Null hypothesis [H.sub.031], [H.sub.032], [H.sub.033], [H.sub.036], [H.sub.037], [H.sub.038] were not rejected and hence it can be concluded that profitability, growth, asset tangibility, liquidity, financial distress and tax rate did not produce significant impact on Total Debt.

Whereas, null hypothesis [H.sub.034], [H.sub.035], [H.sub.039], [H.sub.0310], were rejected and hence it can be concluded that size, cost of debt, debt serving capacity and age produced significant impact on Long Term Debt.

Model 4:

Summary of Null Hypotheses of Model 4

[H.sub.041] There is no significant impact of Profitability of Private sector companies on Short Term Debt

[H.sub.042] There is no significant impact of Growth of Private sector companies on Short Term Debt

[H.sub.043] There is no significant impact of Asset Tangibility of Private sector companies on Short Term Debt

[H.sub.044] There is no significant impact of Size of Private sector companies on Short Term Debt

[H.sub.045] There is no significant impact of Cost of Debt of Private sector companies on Short Term Debt

[H.sub.046] There is no significant impact of Liquidity of Private sector companies on Short Term Debt

[H.sub.047] There is no significant impact of Financial Distress of Private sector companies on Short Term Debt

[H.sub.048] There is no significant impact of Tax Rate of Private sector companies on Short Term Debt

[H.sub.049] There is no significant impact of Debt Serving Capacity of Private sector companies on Short Term Debt

[H.sub.0410] There is no significant impact of Age of Private sector companies on Short Term Debt

The results of the ten independent variables of model 4 are given in the table 5 below.

Null hypothesis [H.sub.042], [H.sub.043], [H.sub.045], [H.sub.046], [H.sub.047], [H.sub.0410] are not rejected and hence it can be concluded that growth, asset tangibility, cost of debt, liquidity, financial distress and age did not produce significant impact on Short Term Debt.

Null hypothesis [H.sub.041], [H.sub.044], [H.sub.048], [H.sub.049], are rejected and hence it can be concluded that profitability, size, tax rate and debt serving capacity produced significant impact on Short Term Debt.

Model 5:

Summary of Null Hypotheses of Model 5

[H.sub.051] There is no significant impact of Profitability of Private sector companies on Long Term Debt

[H.sub.052] There is no significant impact of Growth of Private sector companies on Long Term Debt

[H.sub.053] There is no significant impact of Asset Tangibility of Private sector companies on Long Term Debt

[H.sub.054] There is no significant impact of Size of Private sector companies on Long Term Debt

[H.sub.055] There is no significant impact of Cost of Debt of Private sector companies on Long Term Debt

[H.sub.056] There is no significant impact of Liquidity of Private sector companies on Long Term Debt

[H.sub.057] There is no significant impact of Financial Distress of Private sector companies on Long Term Debt

[H.sub.058] There is no significant impact of Tax Rate of Private sector companies on Long Term Debt

[H.sub.059] There is no significant impact of Debt Serving Capacity of Private sector companies on Long Term Debt

[H.sub.0510] There is no significant impact of Age of Private sector companies on Long Term Debt

The results of the ten independent variables of model 5 are given in the table 6 below.

Null hypothesis [H.sub.056], [H.sub.057], [H.sub.0510] were not rejected and hence it can be concluded that liquidity, financial distress and age did not produce significant impact on Long Term Debt

Null hypothesis [H.sub.051], [H.sub.052], [H.sub.053], [H.sub.054], [H.sub.055], [H.sub.058], [H.sub.059] were rejected and hence it can be concluded that profitability, growth, asset tangibility, size, cost of debt, tax rate and debt serving capacity produced significant impact on Long Term Debt

Model 6:

Summary of Null Hypotheses of Model 6

[H.sub.061] There is no significant impact of Profitability of Private sector companies on Total Debt

[H.sub.062] There is no significant impact of Growth of Private sector companies on Total Debt

[H.sub.063] There is no significant impact of Asset Tangibility of Private sector companies on Total Debt

[H.sub.064] There is no significant impact of Size of Private sector companies on Total Debt

[H.sub.065] There is no significant impact of Cost of Debt of Private sector companies on Total Debt

[H.sub.066] There is no significant impact of Liquidity of Private sector companies on Total Debt

[H.sub.067] There is no significant impact of Financial Distress of Private sector companies on Total Debt

[H.sub.068] There is no significant impact of Tax Rate of Private sector companies on Total Debt

[H.sub.069] There is no significant impact of Debt Serving Capacity of Private sector companies on Total Debt

[H.sub.0610] There is no significant impact of Age of Private sector companies on Total Debt

The results of the ten independent variables of model 6 are given in the table 7 below.

Null hypothesis [H.sub.065], [H.sub.066], [H.sub.0610] were not rejected and hence it can be concluded that cost of debt, liquidity and age did not produce significant impact on Total Debt

Null hypothesis [H.sub.061], [H.sub.062], [H.sub.063], [H.sub.064], [H.sub.067], [H.sub.068], [H.sub.069] were rejected and hence it can be concluded that profitability, growth, asset tangibility, size, financial distress, tax rate and debt serving capacity produced significant impact on Total Debt

CONCLUSION

Major observations from the study have been such that while determining capital structure, public sector companies lay much emphasis on factors like their size in terms of their asset, age, interest rates at which debt is availed and their capacity to service that debt. This finding indicates that although public sector companies have access to both equity and debt markets, yet while raising debt by issuing bonds such as Government Guaranteed Bonds, Debentures, PSU Bonds, Commercial papers etc., size, age, cost of capital and debt serving capacity have a significant impact. Such debt can only be catered to by companies which have existed for decades and only such companies can bear the interest burden that follows with it. Thus, determinants such as size, age, debt servicing capacity and interest rates play a crucial role in determining capital structure of public sector companies.

The results for private sector companies show that these companies make capital structure decisions depending on factors such as their profitability. When these companies have high profitability, their growth and asset size increases. With higher profits, tax liabilities also show an upward movement. In order to control increasing taxes, they seek support of debt instruments, therefore factors like cost of debt and the company's debt servicing capacity also play a major role in making profitability, growth, asset tangibility, size, cost of debt, tax rate and debt servicing capacity as the major determinants of the capital structure. Also with a higher asset tangibility position, these companies are easily in a position to raise debt. Therefore, these factors are considered favourable while making capital structure decisions.

The results are mostly consistent with much of the previous studies done on the issue. With the introduction of key variables such as cost of debt, liquidity, age, tax rate debt serving capacity that have not been studied previously, this study distinguishes itself from previous works.

REFERENCES

(1.) Ba-Abbad, K. and Ahmad Zaluki, N. (2012). The determinants of Capital Structure of Qatari Listed Companies. International Journal of Academic Research in Accounting, Finance and Management Sciences, 2(2), 93-108.

(2.) Baker, M., and Wurgler, J. (2002). Market Timing and Capital Structure. Journal of Finance, 57(1), 1-32.

(3.) Bhaduri, S. (2002). Determinants of capital structure choice: a study of the Indian corporate sector. Applied Financial Economics, 12(9), 655-665.

(4.) Chang, X. and Dasgupta, S. (2009). Target Behavior and Financing: How Conclusive Is the Evidence? Journal of Finance, 64(4), 1767-1796.

(5.) Frank, M.Z. and Goyal, V.K. (2009). Capital Structure Decisions: Which Factors are Reliably Important? Financial Management, 38(1), 137.

(6.) Gurcharan, S. (2010). A Review of Optimal Capital Structure Determinant of Selected ASEAN Countries. International Research Journal of Finance and Economics, 47, 30-41.

(7.) Hovakimian, A. and Li, G. (2012). Is the Partial Adjustment Model a Useful Tool for Capital Structure Research? Review of Finance, 16(3), 733-754.

(8.) Hovakimian, A., Opler, T. and Titman, S. (2001). The Debt-Equity Choice. Journal of Financial and Quantitative Analysis, 36(1), 124.

(9.) Kayhan, A. and Titman, S. (2007). Firms' Histories and Their Capital Structure. Journal of Financial Economics, 83(1), 132.

(10.) Kouki, M. and Said, H.B. (2012). Capital Structure Determinants: New Evidence from French Panel Data. International Journal of Business Management, 7(1), 214-229.

(11.) Lemmon, M.L., Roberts, M.R. and Zender, J.F. (2008). Back to the Beginning: Persistence and the Cross-Section of Corporate Capital Structure. The Journal of Finance, 63(4), 1575-1607.

(12.) Owolabi, S. A., & Inyang, U.E. (2012). Determinants of Capital Structure in Nigerian Firms: A Theoretical Review, eCanadian Journal of Accounting and Finance, 1 (1), 7-15.

(13.) Ramjee, A. & Gwatidzo, T. (2012). "Dynamics in capital structure determinants in South Africa", Meditari Accountancy Research, 20(1), 52-67.

(14.) Rao, S.N. & Lukose P.J. (2001). Determinants of Capital Structure in India: A Comparative Study of Pre-and-Post Liberalization Regime. The Journal of Management and Accounting Research, 5(1), 73-92.

(15.) Welch, I. (2004). Capital Structure and Stock Returns. Journal of Political Economy, 112(1), 106-131.

Prof. Anshu Handoo, Assistant Professor, Acropolis Faculty of Management and Research, Devi Ahilya University, Indore, M. P.; e-mail: anshujaisinghani@gmail.com

Dr. Kapil Sharma, Reader, Institute of Management Studies, Devi Ahilya University, Indore, M. P.; e-mail:kapil.mhow@ gmail.com
Table 1: Results of Regression Analysis for comparison between
public sector and private sector companies in India

 Public Sector Companies

 Short Term Long Term Total Debt Ratio
 Debt Ratio Debt Ratio

(Constant) 0.774 (0.290) 0.111 (1.623) 0.059 (1.933)
PROF 0.307 (-1.038) 0.916 (-0.106) 0.712 (-0.372)
GROW 0.936 (0.081) 0.278 (-1.097) 0.147 (-1.472)
TAN 0.217 (1.259) 0.618 (0.502) 0.239 (1.191)
SIZE 0.055 (-1.994) 0.002 * (-3.347) 0.001 * (-3.638)
COD 0.012 * (-2.663) 0.001 * (-3.642) 0.000 * (4.172)
LIQ 0.633 (0.482) 0.170 (-1.393) 0.305 (-1.035)
FINDIST 0.873 (-0.161) 0.318 (1.008) 0.34 (0.963)
TAXR 0.556 (0.595) 0.661 (-0.441) 0.925 (-0.095)
DSC 0.492 (-0.695) 0.002 * (-3.327) 0.001 * (-3.597)
AGE 0.702 (0.386) 0.006 * (2.862) 0.011 * (2.639)
[R.sup.2] 0.592 0.649 0.709

 Private Sector Companies

 Short Term Long Term Total Debt Ratio
 Debt Ratio Debt Ratio

(Constant) 0.000 (-4.341) 0.000 (-17.83) 0.000 (-10.806)
PROF 0.000 * (-4.335) 0.000 * (-9.477) 0.000 * (-12.903)
GROW 0.932 (0.086) 0.000 * (4.327) 0.000 * (3.841)
TAN 0.595 (0.531) 0.000 * (14.256) 0.000 * (11.401)
SIZE 0.000 * (-7.620) 0.020 * (2.336) 0.031 * (-2.157)
COD 0.745 (0.325) 0.004 * (-2.908) 0.302 (-1.034)
LIQ 0.865 (-0.171) 0.834 (0.209) 0.134 (1.498)
FINDIST 0.104 (-1.628) 0.065 (-1.849) 0.043 * (-2.024)
TAXR 0.040 * (-2.059) 0.004 * (-2.904) 0.005 * (-2.811)
DSC 0.000 * (4.688) 0.000 * (-4.848) 0.000 * (-7.736)
AGE 0.271 (-1.101) 0.802 (-0.251) 0.640 (-0.468)
[R.sup.2] 0.169 0.336 0.385

Values in the parentheses represent t-statistics adjusted using the
procedures of White (1980).

Significance at 5% level is indicated by one asterisk.

Table 2: Coefficients (a) and 't' value of the ten
independent variables of Model 1

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) .636 2.192
PROF -8.537 8.222 -.232
GROW .447 5.535 .014
TAN 2.206 1.752 .206
SIZE -.494 .248 -.370
COD -1.028 .386 -.432
LIQ .023 .048 .075
FINDIST -.008 .048 -.020
TAXR 2.140 3.596 .104
DSC -.007 .010 -.118
AGE .557 1.442 .063

Independent t Sig Null Hypothesis
Variables Results

(Constant) .290 .774
PROF -1.038 .307 Not Rejected
GROW .081 .936 Not Rejected
TAN 1.259 .217 Not Rejected
SIZE -1.994 .055 Not Rejected
COD -2.663 .012 Rejected
LIQ .482 .633 Not Rejected
FINDIST -.161 .873 Not Rejected
TAXR .595 .556 Not Rejected
DSC -.695 .492 Not Rejected
AGE .386 .702 Not Rejected

(a.) Dependent Variable: logSTDR

Table 3: Coefficients (a) and 't' value of the ten
independent variables of Model 2

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) 1.434 .883
PROF -.295 2.788 -.014
GROW -1.934 1.763 -.119
TAN .362 .720 .059
SIZE -.289 .086 -.399
COD -.374 .103 -.370
LIQ -.029 .021 -.142
FINDIST .023 .023 .097
TAXR -.620 1.406 -.053
DSC -.003 .001 -.346
AGE 1.300 .454 .283

Independent t Sig Null Hypothesis
Variables Results

(Constant) 1.623 .111
PROF -.106 .916 Not Rejected
GROW -1.097 .278 Not Rejected
TAN .502 .618 Not Rejected
SIZE -3.347 .002 Rejected
COD -3.642 .001 Rejected
LIQ -1.393 .170 Not Rejected
FINDIST 1.008 .318 Not Rejected
TAXR -.441 .661 Not Rejected
DSC -3.327 .002 Rejected
AGE 2.862 .006 Rejected

(a.) Dependent Variable: LTDR

Table 4: Coefficients (a) and 't' value of the ten
independent variables of Model 3

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) 1.617 .836
PROF -.981 2.639 -.046
GROW -2.457 1.669 -.145
TAN .812 .682 .127
SIZE -.297 .082 -.394
COD -.405 .097 -.385
LIQ -.020 .020 -.096
FINDIST .021 .022 .084
TAXR -.127 1.331 -.010
DSC -.003 .001 -.340
AGE 1.135 .430 .238

Independent t Sig Null Hypothesis
Variables Results

(Constant) 1.933 .059
PROF -.372 .712 Not Rejected
GROW -1.472 .147 Not Rejected
TAN 1.191 .239 Not Rejected
SIZE -3.638 .001 Rejected
COD -4.172 .000 Rejected
LIQ -1.035 .305 Not Rejected
FINDIST .963 .340 Not Rejected
TAXR -.095 .925 Not Rejected
DSC -3.597 .001 Rejected
AGE 2.639 .011 Rejected

(a.) Dependent Variable: logTDR

Table 5: Coefficients (a) and 't' value of the ten
independent variables of Model 4

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) -.866 .199
PROF 2.416 .557 -.166
GROW .016 .191 .003
TAN .114 .214 .019
SIZE -.192 .025 -.265
COD .001 .002 .011
LIQ -.002 .012 -.006
FINDIST -.002 .001 -.055
TAXR -.413 .201 -.072
DSC .006 .001 -.167
AGE -.102 .093 -.040

Independent t Sig Null Hypothesis
Variables Results

(Constant) -4.341 .000
PROF -4.335 .000 Rejected
GROW .086 .932 Not Rejected
TAN .531 .595 Not Rejected
SIZE -7.620 .000 Rejected
COD .325 .745 Not Rejected
LIQ -.171 .865 Not Rejected
FINDIST -1.628 .104 Not Rejected
TAXR -2.059 .040 Rejected
DSC -4.688 .000 Rejected
AGE -1.101 .271 Not Rejected

(a.) Dependent Variable: logSTDR

Table 6: Coefficients (a) and 't' value of the ten
independent variables of Model 5

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) -2.428 .136
PROF -3.411 .360 -.299
GROW .567 .131 .140
TAN 2.094 .147 .430
SIZE .041 .018 .069
COD -.005 .002 -.084
LIQ .002 .008 .006
FINDIST -.002 .001 -.054
TAXR -.409 .141 -.087
DSC .000 .000 -.143
AGE -.016 .065 -.008

Independent t Sig Null Hypothesis
Variables Results

(Constant) -17.830 .000
PROF -9.477 .000 Rejected
GROW 4.327 .000 Rejected
TAN 14.256 .000 Rejected
SIZE 2.336 .020 Rejected
COD -2.908 .004 Rejected
LIQ .209 .834 Not Rejected
FINDIST -1.849 .065 Not Rejected
TAXR -2.904 .004 Rejected
DSC -4.848 .000 Rejected
AGE -.251 .802 Not Rejected

(a.) Dependent Variable: logLTDR

Table 7: Coefficients (a) and 't' value of the ten
independent variables of Model 6

Independent Unstandardised Standardised
Variables Coefficients Coefficients

 B Std. Error Beta

(Constant) -1.247 .115
PROF -3.934 .305 -.392
GROW .427 .111 .119
TAN 1.419 .124 .330
SIZE -.032 .015 -.061
COD -.002 .002 -.029
LIQ .011 .007 .043
FINDIST -.001 .001 -.056
TAXR -.335 .119 -.081
DSC -.001 .000 -.220
AGE -.026 .055 -.014

Independent t Sig Null Hypothesis
Variables Results

(Constant) -10.806 .000
PROF .12.903 .000 Rejected
GROW 3.841 .000 Rejected
TAN 11.401 .000 Rejected
SIZE -2.157 .031 Rejected
COD -1.034 .302 Not Rejected
LIQ 1.498 .134 Not Rejected
FINDIST -2.024 .043 Rejected
TAXR -2.811 .005 Rejected
DSC -7.736 .000 Rejected
AGE -.468 .640 Not Rejected

(a.) Dependent Variable: logTDR
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Author:Handoo, Anshu; Sharma, Kapil
Publication:Paradigm
Article Type:Author abstract
Geographic Code:9INDI
Date:Jul 1, 2012
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