- Akash, R. S., Shah, S. Z., Hasan, A., Hamid, K., & Suleman, M. T. (2011). The Impact of Sensitivity and Validity of Debt Signaling Hypothesis in Transitional and Emerging Market: Perspectives from Pakistan. International Research Journal of Finance and Economics. 71(1), 7-18.
- Azhagaiah, R., & Gavoury, C. (2011). The Impact of Capital Structure on Profitability with Special Reference to IT Industry in India. Managing Global Transitions: International Research Journal, 9(4).
- Baker, M., & Wurgler, J. (2002). Market timing and capital structure. The journal of finance, 57(1), 1-32.
- Booth, L., Aivazian, V., Demirgucâ€ÂKunt, A., & Maksimovic, V. (2001). Capital structures in developing countries. The journal of finance, 56(1), 87-130.
- Cheng, S. R., & Shiu, C. Y. (2007). Investor protection and capital structure: International evidence. Journal of Multinational Financial Management, 17(1), 30-44.
- Danso, A., & Adomako, S. (2014). The financing behaviour of firms and financial crisis. Managerial finance.
- De Jong, A., Kabir, R., & Nguyen, T. T. (2008). Capital structure around the world: The roles of firm-and country- specific determinants. Journal of banking & Finance, 32(9), 1954-1969.
- Deesomsak, R., Paudyal, K., & Pescetto, G. (2004). The determinants of capital structure: evidence from the Asia Pacific region. Journal of multinational financial management, 14(4-5), 387-405.
- Deitiana, T., & Robin, M. (2016). The Effect of Firm Size, Profitability, Tangibility, Non-Debt Tax Shield and Growth to Capital Structure on Banking Firms Listed in Indonesia Stock Exchange From 2007- 2012. Economics and Law, 10(1).
- Delcoure, N. (2007). The determinants of capital structure in transitional economies. International Review of Economics & Finance, 16(3), 400-415.
- Demirgüç-Kunt, A., & Maksimovic, V. (1999). Institutions, financial markets, and firm debt maturity. Journal of financial economics, 54(3), 295-336.
- Hamid, K., Hussain, Z., & Ghafoor, M. M. (2020). Abnormal Returns, Corporate Financial Policies and the Dynamics of Leverage: Empirical Evidence from Non-Financial Sector of Pakistan. Review of Economics and Development Studies, 6(1), 153-166
- Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3(4), 305-360.
- Kahya, E. H., Ersen, H. Y., Ekinci, C., Taş, O., & Simsek, K. D. (2020). Determinants of capital structure for firms in an Islamic equity index: comparing developed and developing countries. Journal of Capital Markets Studies, 4(2), 167-191.
- Myers, S. C. (1984). Capital structure puzzle. NBER Working Paper, (w1393).
- Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of financial economics, 13(2), 187-221.
- Panda, A. K., & Nanda, S. (2020). Determinants of capital structure; a sector-level analysis for Indian manufacturing firms. International Journal of Productivity and Performance Management, 69(5), 1033-1060.
- Pouraghajan, A., Malekian, E., Emamgholipour, M., Lotfollahpour, V., & Bagheri, M. M. (2012). The relationship between capital structure and firm performance evaluation measures: Evidence from the Tehran Stock Exchange. International journal of Business and Commerce, 1(9), 166- 181.
- Qiu, M., & La, B. (2010). Firm characteristics as determinants of capital structures in Australia. International journal of the Economics of Business, 17(3), 277- 287.
- Sadiq, M. N., & Sher, F. (2016). Impact of capital structure on the profitability of firms' evidence from automobile sector of Pakistan. Global Journal of Management and Business Research
- Saif-Alyousfi, A. Y., Md-Rus, R., Taufil- Mohd, K. N., Taib, H. M., & Shahar, H. K. (2020). Determinants of capital structure: evidence from Malaysian firms. Asia-Pacific Journal of Business Administration.
- Serghiescu, L., & Văidean, V. L. (2014). Determinant factors of the capital structure of a firm-an empirical analysis. Procedia Economics and Finance, 15, 1447-1457.
- Sheikh, N. A., & Wang, Z. (2011). Determinants of capital structure: An empirical study of firms in manufacturing industry of Pakistan. Managerial finance.
- Vătavu, S. (2015). The impact of capital structure on financial performance in Romanian listed companies. Procedia Economics and Finance, 32, 1314- 1322.
Abstract:
Capital structure is expressed as the mixture of long-term debt and equity that a company uses in its financing composition. The importance of long-term financing in any business cannot be misjudged because it identifies the choice of optimal financing mix for the long-run survival of the business. The basic purpose of this study is to identify the behavior of financing composition through main corporate financial decisions in the non-financial sector of Pakistan. Data has been taken for 52 non-financial companies for 2015-2020. Outcomes of the study have been retrieved through OLS, Fixed Effect, Random Effect Model and Hausman Test by using Eviews software. The main corporate financial policies regarding leverage decisions include a firm’s profitability, earning volatility, firm size, non-debt tax shield, and liquidity. Results identified that earning volatility, liquidity and profitability of the firm have a negative but significantly related to leverage; on the other hand, the study denotes that assets tangibility, not debt tax shield, firm size positively related to leverage. However as per fixed effect model earning volatility, liquidity and profitability has negative significant impact on leverage whereas, assets tangibility and firm size has positive significant impact on leverage. It is concluded that earning validity, liquidity and profitability are negative determinants of the firm’s leverage. Whereas, assets tangibility and firm size are the positive determinants of the leverage. The corporate policy regarding these determinants should be well recognized while designing the capital structure of the organization.
Key Words:
Corporate Policy, Capital Structure, Leverage, Earning Volatility
Introduction
The capital structure is composition of long term debt, preferred stock and common stock which is utilized to finance the long run projects of the business. Generally the composition of strategic capital structure is to design the optimal mix of long term debt and shareholder’s equity in a manner that may enhance the value of the firm in a long run perspective. Stockholders are the owners of the firm who invest in the company for long time period and are committed but debt holders play the role of lender to the business and these lenders have no long term commitment. Lenders are only concerned to the repayment of their principal amount back as well as interest amount. Leveraged firm is that firm which have both equity and long term debt but the unlevered firm is that firm which have only equity segment. However tax deductible benefits are available in debt financing because cost of debt is tax adjustable. It is decided on the grounds that how much debt should be included in the composition of capital structure of the firm in comparison to the equity. As the cost of equity is great than the cost of debt due to tax adjustability of interest payment therefore the long term debt decisions are more important in designing the optimal combination of debt and equity mix which may lead to enhance the value of the firm. Hence, the price of the equity is more than the price of debt therefore a balanced mix of financing decisions are made which deemed to be suitable and more valuable for a corporate unit.
Corporate policy generally considered as a wider concept. However, evaluation of capital structure dependency is one of the key motive of these policies. Firm performance and size of the business play a dynamic role in the strategic financing decisions. Therefore, the tax effect and earning volatility has to analyze to see the changing impact of these corporate policies on leverage decisions. The main goal of a business is to increase the value of share for the shareholders, therefore, financial decision makers perform their duty in best way for optimizing the capital structure for a business. To select the best optimal capital structure, a company must have to increase the output and also have to minimize the cost to meet the challenge. (Pouraghajan and Maklekian, 2012). Firm may go either for equity or long term debt to invest in its assets. The best alternative is the mixture of debt and equity. However, in a situation where debt is taxable, mangers or decision makers may prefer to debt on equity because they are in a position to maximize the overall value of the firm (Azhagaiah and Gavoury, 2011). Agency cost issues may be seen while using the debt in capital structure of a firm. Agency cost conflicts may start between the shareholders and mangers of a firm and also between shareholders and debt holders (Jensen and Meckling, 1976).
Some companies prefers equity financing because stock valuation is advantageous, where debt finance uses during low valuation of stock. Financial decision makers weigh the financial market while financing for new project if the financial market condition favorable then firm take long term loan even if they do not need (Baker and Wurgler, 2002).
This study is significant because it is focusing on the changing corporate policies that may affect the capital structure decisions in Pakistan for non-financial sector. Moreover, this study contributes practically for decision makers that how corporate financial policy may be designed by considering the empirical evidences. The basic purpose is to see the impact of corporate policies on the capital structure decisions of the companies. Study has taken into consideration 52 non-financial companies listed on Pakistan Stock Exchange for the period of 2015 to 2020. Eviews software has been used to analyze the data.
Further this study is exploring to identify the factors that may affected the capital structure decision of non-financial companies in Pakistan in recent past. It is important because Pakistan is going launch its economy to robust the business and banking industry has enough financing to facilitate the business sector. Problem statement indicates that presently this issue is now more focusing upon the recent scenario of new business financing models in a post COVID scenario in Pakistan and restructuring of the businesses. Therefore the capital structure decisions are the key decisions that may apply in the sense that may enhance the value of the firm in a long run perspective and to attain the basic goal of wealth maximization of shareholder of the company. The rest of article is organized as Follow: Section 2 described Literature Review. Section 3 consists on theories ad hypotheses. Section 4 data and methodology of the study. Section 5 provides results and discussion and section 6 provide conclusion.
Literature Review
Mei Qiu and Bo La (2010) used unbalanced data of 367 companies for the period 1992 to 2006 for Australian firms. The panel data findings showed that long term debt positively correlated with assets tangibility and have inverse relationship with growth. It was also found that levered firms generated more profit as compared to unlevered firms. However, profitability is found negatively associated with leverage. The impact of firm size was not found in this study.
Sheikh and Zong (2011) explored capital structure determinants for 160 non-financial for the period 2003-2007. The results specified that profitability, liquidity, earning volatility and assets tangibility were negatively associated with firm size.
Serghisescu and Vaidean (2014) tested 20 non-financial companies for the period 2009-2011by using OLS model and fixed effects model for Romanian Firms. They identified that profitability and liquidity were found adversely associated to leverage. However, tangibility was negatively associated with debt ratio. Furthermore, size of the firm was positively related with assets turnover.
Vatavu (2015) conducted a research on 196 Romanian firms listed for period of 2003 to 2010. The outcomes of study indicated that efficiency in Romanian firms has been improved while using equity and avoid debt finance. However, leverage has negative association with ROA and ROE.
Sadiq and Sher (2016) tested capital structure determinants for 19 firms from automobile sector for the period 2006-2012. Results identified that there was negative association between profitability and leverage.
Panda and Nanda (2020) examined a research, the purpose of this research was to observe the elements of capital structure and their relationship with the firm and macroeconomics factors for Indian manufacturing firms. Panel semi-parametric and non-parametric regression was used to find the key elements of capital structure. To find the continuing connection of financial leverage with its determinants, panel co-integration models were used. Data was reviewed of 1592 firms from 8 sectors over the period of 2007 to 2017. The study found that the level of debt expressively by assets tangibility, tax rate, growth opportunity, cash flow, not debt tax shield, profitability, size of firm, economic growth, foreign direct investment, interest rate and government borrowing.
Saif-Alyousfi et al.,(2020) examined the factors effecting capital structure for 827 companies for the period 2008 to 2017 listed on KLSE Malaysia. Results were testified through 2SLS and GMM approach and identified that ROA, liquidity, tax shield, growth and cash flow volatility is negatively associated with leverage. Earning volatility, the effect of collateral and non-debt tax shield has positive association with leverage. Furthermore, age of the firm, size of the firm, interest rate and inflation rate are also significant parameters of leverage.
Data and Methodology.
To analyze the impact of corporate financing decisions on optimization of capital Structure determinants in Pakistan. Data has been collected for 52 non-financial Pakistani Companies from 8 different sectors, namely, Textile, chemical, Cement sector, Power sector, fertilizer automobile industry, metal and metal products, construction and real estate. Financial data of these firms have been collected for a period of six years from 2015-2020. Research is grounded on secondary data only. Data has been taken from State Bank of Pakistan record and yearly fiscal individual results have been measured to do the observed estimation.
The panel data is strongly balance and have 300 observations. To evaluate the panel data E-Views Statistical software has been used for descriptive, correlation, OLS, Fixed Effects Model, Random Effect Model and Housman Test.
LEV?_it=?_0+?_1(PROF)_it+?_2 (EVOL)_it+?_3(ATAN)_it+?_4(FISZ)_it+?_5(NDTS)_it+?_6(LIQ)_it+?_it (1)
Whereas
LEV?_it=Leverage as dependent variable
(PROF)_it=Profitiblity
(EVOL)_it=Earning volailtiy
(ATAN)_it=Assets Tangiblity
(FISZ)_it=Size of the firm
(NDTS)_it=Non-debt tax shield
(LIQ)_it=Liquidity
?_it=Error term .
Table 1. Proxies Table for Variable Computations
| Variables width="61" valign="top">Symbol width="156" valign="top">Description width="225" valign="top">Proxy Used by | > Leverage width="61" valign="top">LEV width="156" valign="top">Total debt divided by total assets width="225" valign="top">Delcoure (2007),Danso & Adomako (2014), Cheng and Shiu (2007) | > Profitability width="61" valign="top">PROF width="156" valign="top">Ratio of operating income to total assets width="225" valign="top">Kahya & Ersen (2020). De Jhong et al,(2008), Danso & Adomako (2014) | > Earning Volatility width="61" valign="top">EVOL width="156" valign="top">Ratio of the standard deviation of operating income to total assets width="225" valign="top"> | > Assets Tangibility width="61" valign="top">ATAN width="156" valign="top">Ratio of fixes assets to total assets width="225" valign="top">Deesomsak et at. (2004) Kahya & Ersen (2020). Deitiana & Robin (2016) | > Firm size width="61" valign="top">FSIZ width="156" valign="top">Log of total asset width="225" valign="top">Deitiana & Robin (2016) Danso & Adomako (2014), Kahya & Ersen (2020). Panda & Nand (2020). | > Non-debt tax shield width="61" valign="top">NDTS width="156" valign="top">Ratio of depreciation expenses to total assets width="225" valign="top">Sheikh Wang (2011), Deitiana & Robin (2016), Panda & Nand (2020). | > Liquidity width="61" valign="top">LIQ width="156" valign="top">Ratio of current assets to current liabilities width="225" valign="top">Danso & Adomako (2014) Kahya & Ersen (2020). Sheikh and Wang (2011). |
Results and Discussion
The below table 2 display the mean, median, slandered deviation as a measure of central tendency and Kurtosis, Skewness and Jarque- Bera Tests indicate the normality level of the data.
Table 2. Descriptive Statistics
| width="66" nowrap="" valign="top"> LEV width="60" nowrap="" valign="top">EVOL width="54" nowrap="" valign="top">ATAN width="58" nowrap="" valign="top">FSIZ width="53" nowrap="" valign="top">LIQ width="56" nowrap="" valign="top">NDTS width="54" nowrap="" valign="top">PROF | > Mean width="66" nowrap="" valign="top">0.180 width="60" nowrap="" valign="top">0.018 width="54" nowrap="" valign="top">0.66 width="58" nowrap="" valign="top">17.07 width="53" nowrap="" valign="top">1.50 width="56" nowrap="" valign="top">0.031 width="54" nowrap="" valign="top">0.048 | > Median width="66" nowrap="" valign="top">0.160 width="60" nowrap="" valign="top">0.010 width="54" nowrap="" valign="top">0.657 width="58" nowrap="" valign="top">17.10 width="53" nowrap="" valign="top">1.20 width="56" nowrap="" valign="top">0.027 width="54" nowrap="" valign="top">0.046 | > Maximum width="66" nowrap="" valign="top">1.005 width="60" nowrap="" valign="top">0.213 width="54" nowrap="" valign="top">2.262 width="58" nowrap="" valign="top">20.37 width="53" nowrap="" valign="top">7.57 width="56" nowrap="" valign="top">0.145 width="54" nowrap="" valign="top">0.288 | > Minimum width="66" nowrap="" valign="top">0 width="60" nowrap="" valign="top">-0.224 width="54" nowrap="" valign="top">0.056 width="58" nowrap="" valign="top">13.70 width="53" nowrap="" valign="top">0.09 width="56" nowrap="" valign="top">-0.008 width="54" nowrap="" valign="top">-0.26 | > Std. Dev. width="66" nowrap="" valign="top">0.15 width="60" nowrap="" valign="top">0.06 width="54" nowrap="" valign="top">0.37 width="58" nowrap="" valign="top">1.55 width="53" nowrap="" valign="top">1.11 width="56" nowrap="" valign="top">0.02 width="54" nowrap="" valign="top">0.09 | > Skewness width="66" nowrap="" valign="top">1.80 width="60" nowrap="" valign="top">0.292 width="54" nowrap="" valign="top">0.720 width="58" nowrap="" valign="top">0.10 width="53" nowrap="" valign="top">2.29 width="56" nowrap="" valign="top">1.8194 width="54" nowrap="" valign="top">-0.29 | > Kurtosis width="66" nowrap="" valign="top">8.7 width="60" nowrap="" valign="top">4.6 width="54" nowrap="" valign="top">4.0 width="58" nowrap="" valign="top">2.2 width="53" nowrap="" valign="top">9.9 width="56" nowrap="" valign="top">8.7 width="54" nowrap="" valign="top">3.8 | > Jarque-Bera width="66" nowrap="" valign="top">577.8 width="60" nowrap="" valign="top">37.27 width="54" nowrap="" valign="top">38.66 width="58" nowrap="" valign="top">8.20 width="53" nowrap="" valign="top">872.59 width="56" nowrap="" valign="top">573.58 width="54" nowrap="" valign="top">13.78 | > Probability width="66" nowrap="" valign="top">0 width="60" nowrap="" valign="top">0 width="54" nowrap="" valign="top">0 width="58" nowrap="" valign="top">0.016 width="53" nowrap="" valign="top">0 width="56" nowrap="" valign="top">0 width="54" nowrap="" valign="top">0.001 | > Sum width="66" nowrap="" valign="top">54.12 width="60" nowrap="" valign="top">5.53 width="54" nowrap="" valign="top">200.16 width="58" nowrap="" valign="top">5121.26 width="53" nowrap="" valign="top">451.71 width="56" nowrap="" valign="top">9.57 width="54" nowrap="" valign="top">14.51 | > SumSq. Dev. width="66" nowrap="" valign="top">7.33 width="60" nowrap="" valign="top">1.1317 width="54" nowrap="" valign="top">42.11 width="58" nowrap="" valign="top">720.72 width="53" nowrap="" valign="top">374.15 width="56" nowrap="" valign="top">0.128 width="54" nowrap="" valign="top">2.530 | > bservations width="66" nowrap="" valign="top">300 width="60" nowrap="" valign="top">300 width="54" nowrap="" valign="top">300 width="58" nowrap="" valign="top">300 width="53" nowrap="" valign="top">300 width="56" nowrap="" valign="top">300 width="54" nowrap="" valign="top">300 |
Descriptive statistics for leverage shows 0.18 ± 0.15 mean and standard deviation respectively and the leverage is positively skewed. Standard deviation indicates lower value that indicates low volatility. The average of earning volatility (EVOL) is 0.018 and Standard Deviation is 0.06 while skewness is positively related. Mean of assets tangibility is 0.66 and standard deviation is 0.37 and positively skewed. Mean of size of firm is 17.07 and Standard deviation of 1.55 and firm size is positively skewed. The average of liquidity is 1.505 and standard deviation is 1.11 while liquidity is positively skewed. Mean of liquidity is observed 1.50 it means that firms can get easy debt from lenders. Average of non-Debt Tax Shield is 0.031 and standard deviation is 0.02 while non-debt tax shield is negatively skewed. The result shown that firms get more leverage to entertain the tax benefits. Average of profitability is 0.048 and standard deviation is 0.09 and profitability is negatively skewed. The result shows that average profit is almost 5% which means that higher amount of debts lends to larger amount of interest paid which result as negative for profit.
Table 3. Correlation Matrix The below Table Indicate the Correlations between the Variables
| width="78" nowrap="" valign="top"> LEV width="66" nowrap="" valign="top">ATAN width="75" nowrap="" valign="top">EVOL width="67" nowrap="" valign="top">FSIZ width="61" nowrap="" valign="top">LIQ width="67" nowrap="" valign="top">NDTS width="58" nowrap="" valign="top">PROF | > LEV width="78" nowrap="" valign="top">1 width="66" nowrap="" valign="top">width="75" nowrap="" valign="top"> width="67" nowrap="" valign="top"> width="61" nowrap="" valign="top"> width="67" nowrap="" valign="top"> width="58" nowrap="" valign="top">
| > ATAN width="78" nowrap="" valign="top">0.39* width="66" nowrap="" valign="top">1 width="75" nowrap="" valign="top">width="67" nowrap="" valign="top"> width="61" nowrap="" valign="top"> width="67" nowrap="" valign="top"> width="58" nowrap="" valign="top">
| > EVOL width="78" nowrap="" valign="top">-0.33* width="66" nowrap="" valign="top">-0.30* width="75" nowrap="" valign="top">1 width="67" nowrap="" valign="top">width="61" nowrap="" valign="top"> width="67" nowrap="" valign="top"> width="58" nowrap="" valign="top">
| > FSIZ width="78" nowrap="" valign="top">0.18** width="66" nowrap="" valign="top">-0.04 width="75" nowrap="" valign="top">-0.29* width="67" nowrap="" valign="top">1 width="61" nowrap="" valign="top">width="67" nowrap="" valign="top"> width="58" nowrap="" valign="top">
| > LIQ width="78" nowrap="" valign="top">-0.27* width="66" nowrap="" valign="top">-0.25* width="75" nowrap="" valign="top">0.14*** width="67" nowrap="" valign="top">-0.15*** width="61" nowrap="" valign="top">1 width="67" nowrap="" valign="top">width="58" nowrap="" valign="top">
| > NTDS width="78" nowrap="" valign="top">0.20** width="66" nowrap="" valign="top">0.65* width="75" nowrap="" valign="top">-0.13*** width="67" nowrap="" valign="top">-0.12*** width="61" nowrap="" valign="top">-0.07 width="67" nowrap="" valign="top">1 width="58" nowrap="" valign="top"> | > PROF width="78" nowrap="" valign="top">-0.10*** width="66" nowrap="" valign="top">-0.01 width="75" nowrap="" valign="top">0.03 width="67" nowrap="" valign="top">0.10*** width="61" nowrap="" valign="top">0.19** width="67" nowrap="" valign="top">0.05 width="58" nowrap="" valign="top">1 |
| DV= Leverage width="138" nowrap="" colspan="2" valign="top">OLS width="126" nowrap="" colspan="2" valign="top">Fixed Effects width="130" nowrap="" colspan="2" valign="top">Random Effects | > Variable width="72" nowrap="" valign="top">Constant width="66" nowrap="" valign="top">Prob. width="72" nowrap="" valign="top">Constant width="54" nowrap="" valign="top">Prob. width="72" nowrap="" valign="top">Constant width="58" nowrap="" valign="top">Prob. | > C width="72" nowrap="" valign="top">-0.0974 width="66" nowrap="" valign="top">0.342 width="72" nowrap="" valign="top">-0.1161 width="54" nowrap="" valign="top">0.258 width="72" nowrap="" valign="top">0.05521 width="58" nowrap="" valign="top">0.740 | > Earning Volatility width="72" nowrap="" valign="top">-0.4282 width="66" nowrap="" valign="top">0.003* width="72" nowrap="" valign="top">-0.4332 width="54" nowrap="" valign="top">0.002* width="72" nowrap="" valign="top">-0.3539 width="58" nowrap="" valign="top">0.0002* | > Asset Tangibility width="72" nowrap="" valign="top">0.13539 width="66" nowrap="" valign="top">00000* width="72" nowrap="" valign="top">0.13468 width="54" nowrap="" valign="top">0.000* width="72" nowrap="" valign="top">-0.0352 width="58" nowrap="" valign="top">0.265 | > Firm Size width="72" nowrap="" valign="top">0.01382 width="66" nowrap="" valign="top">0.0133** width="72" nowrap="" valign="top">0.0150 width="54" nowrap="" valign="top">0.007* width="72" nowrap="" valign="top">0.01018 width="58" nowrap="" valign="top">0.265 | > Liquidity width="72" nowrap="" valign="top">0.01916 width="66" nowrap="" valign="top">0.013** width="72" nowrap="" valign="top">-0.0186 width="54" nowrap="" valign="top">0.015* width="72" nowrap="" valign="top">-0.0143 width="58" nowrap="" valign="top">0.019* | > Non-debt tax shield width="72" nowrap="" valign="top">-0.1654 width="66" nowrap="" valign="top">0.7471 width="72" nowrap="" valign="top">-0.146 width="54" nowrap="" valign="top">0.774 width="72" nowrap="" valign="top">0.1435 width="58" nowrap="" valign="top">0.769 | > Profitability width="72" nowrap="" valign="top">-0.1324 width="66" nowrap="" valign="top">0.1395 width="72" nowrap="" valign="top">-0.1874 width="54" nowrap="" valign="top">0.0426 width="72" nowrap="" valign="top">0.0498 width="58" nowrap="" valign="top">0.4769 | > R-squared width="138" nowrap="" colspan="2" valign="top">0.24 width="126" nowrap="" colspan="2" valign="top">0.26 width="130" nowrap="" colspan="2" valign="top">0.07 | > Adjusted R-squared width="138" nowrap="" colspan="2" valign="top">0.23 width="126" nowrap="" colspan="2" valign="top">0.23 width="130" nowrap="" colspan="2" valign="top">0.05 | > Sum squared resid width="138" nowrap="" colspan="2" valign="top">5.5110 width="126" nowrap="" colspan="2" valign="top">9.5504 width="130" nowrap="" colspan="2" valign="top">3.8679 |
| Variable width="89" nowrap="" valign="top">Fixed width="89" nowrap="" valign="top">Random width="89" nowrap="" valign="top">Var(Diff.) width="67" nowrap="" valign="top">Prob. | > Earning Volatility width="89" nowrap="" valign="top">-0.31857 width="89" nowrap="" valign="top">-0.35393 width="89" nowrap="" valign="top">0.001082 width="67" nowrap="" valign="top">0.2824 | > Asset Tangibility width="89" nowrap="" valign="top">-0.12467 width="89" nowrap="" valign="top">-0.03523 width="89" nowrap="" valign="top">0.000412 width="67" nowrap="" valign="top">0.000 | > Firm Size width="89" nowrap="" valign="top">-0.01459 width="89" nowrap="" valign="top">0.01018 width="89" nowrap="" valign="top">0.000145 width="67" nowrap="" valign="top">0.0399 | > Non Debt Tax Shield width="89" nowrap="" valign="top">0.085662 width="89" nowrap="" valign="top">0.143579 width="89" nowrap="" valign="top">0.048704 width="67" nowrap="" valign="top">0.793 | > Liquidity width="89" nowrap="" valign="top">-0.01571 width="89" nowrap="" valign="top">-0.01433 width="89" nowrap="" valign="top">0.000005 width="67" nowrap="" valign="top">0.543 | > Profitability width="89" nowrap="" valign="top">0.014472 width="89" nowrap="" valign="top">0.04985 width="89" nowrap="" valign="top">0.001094 width="67" nowrap="" valign="top">0.2848 |