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

INTRODUCTIONCompanies 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 |
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Publication: | Paradigm |

Article Type: | Author abstract |

Geographic Code: | 9INDI |

Date: | Jul 1, 2012 |

Words: | 4786 |

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