The Comprehensive Study of the Capital Structure of Textile Composite in Pakistan … · of the WTO regime and its effects on the textile industry. He added that escalation of the

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JANUARY 2012 VOL 3, NO 9

The Comprehensive Study of the Capital Structure of Textile Composite in Pakistan over the Decade

1Yasir Hassan 1Lecturer: Lahore Business School, the University of Lahore, Pakistan

2Kashif-ud-din 2Dean: Lahore Business School, the University of Lahore, Pakistan

3Usman Ahmed Khan, Khalil Ahmed, Farrukh Eijaz, Mujadad Younis, Adeel Yaseen, Ahmed Bilal Naseer, Hammd Buttar and Abdual Mateen

3Lahore Business School, the University of Lahore, Pakistan

Abstract In this research paper, the determinants of capital structure in the textile sector of Pakistan are shown. The purpose of this study is to check the effect of overall capital structure in the progress of textile composite in Pakistan. This study also reveals the overall effect of capital structure on textile composite growth in the past decade. The study explains how profit before tax, no. of shares and sales changes capital structure behavior of textile composite. It also explains that how Paid up Capital, Total Assets and Equity have acted as for as the growth of textile composite is concerned. With the help of multiple linear regression analysis the results shows that whether profit after tax is increasing or decreasing. The backward method explains how the capital structure fit the regression model to explain the variables which can effect on profit after tax (dependent variable).The results shows the rate of growth of this sector is in positive direction but very slow that have negligible effect on the development of overall economy. Through all this study firms can make valuable decisions to launch their projects in a better direction. Key words: Leverage, debt, composite

Introduction The combination of debt, equity and other sources of finance that uses to fund long term asset is called as capital structure of a company. The amount of debt financing is measured by gearing or leverage as the debt and equity is key barrier in capital structure. In developing countries such as Pakistan, financing is a major concern due to unpredictable information (external financing) and having low internal financing. So the options of capital structure are few and far between as compared to developed countries. The policies of government affect the interest changed on debt and other modes of external financing. The study of Singh and Hamid (1992) and Singh (1995) show contrasting results. They argue that developing country rely heavily on external financing in capital structure. The textile sector has been considered due to the fact that it is the largest sector in the country. According to the Pakistan textile mills association (APTMA), the leading national trade association of textile spinning, weaving, and composite mills exemplified the organized sector in Pakistan. “APTMA” appears as the leading association of the country as it indicates 396 textile mills of which, 44 weaving, 315 are spinning, and 37 composite units. The weaving mills have enormous number of air-jet looms, spinning mills have large production facilities for the dyeing of yarns and texturing mercerizing and the composite mills have production facilities from spinning to finished textile products all under one roof. The total capacity of APTMA member mills accounts for 1897 conventional looms, 10,452shutteless/air jet looms, 61,608 rotors, and 9,661,366 spindles. Pakistan has captured first position in export of woven fabrics of synthetic staple to Malaysia with 30.53% share amongst the five top exporters approximately around RM12.91 million. In bed linen sector,



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Pakistan has occupied forth position having 14.96% total shares, valuing around RM17.01 million. Textile Company has always been a huge strength for the economy of Pakistan and it contribute many time in the development of Pakistan in terms of creating job opportunities and earning from foreign trade. But recent increase in petroleum prices is expected to unfavorably affect the textile industry of Pakistan, as the dramatic increase in the cost of manufacturing of exportable goods would be intolerable to foreign buyers. Country 70% electricity produced through thermal power plants where oil has a major role and hike in petroleum prices will lead to increase in electricity prices. The chairman Pakistan textile exporter association (PTEA) khurram mukhtar said that recent trade policy had targeted 6% growth in export while the last six months trading trend has shown 3% fall in export. The slowdown in the US economy has affected the overall textile export to a greater extent because it has been the biggest market for Pakistani exports during last few years. Pakistan also faces threatening competition from China, India, Bangladesh and Turkey in the EU market in textile apparel. Pakistan's exports are highly concentrated in a few items namely, cotton alone contributing 54.7% and synthetic textiles (2.9%). According to the data, Textile exports for the first eight months of current financial year registered negative growth of 5.6 percent as against the exports recorded consistent period of the last financial year by Federal Bureau of Statistics. The total Exports recorded $6.85 billion during July-February (2007-08) while Exports during July-February (2008-09) totaled $ 6.47 billion. During this era of time the exports of silk, art and synthetic textile were severely decreased by 23.45% and the highest negative growth of 51.24% has also been verified in the export of yarn. Similarly, exports of cotton (carded or combed) declined by 13.81%, readymade garments by 12.43%, cotton yarn by 15.28%, bed wear by 10.44%, made-up articles by 0.3%, knitwear by 2.66%, canvas, tents and tarpaulin by 21.18% in the same period. On the other hand the export of cotton clothes, towels and raw cotton increased by 5.57%, 10.02% and 154.5% respectively. The government is trying to talk with the European Union to get generalized system of preferences plus status of Pakistan while will help exporters to compete in European market. APTMA Chairman Anwar Ahmed Tata said that during last three-four months production of yarn rose up to 245,000 tons per month, out of which requirement for downstream industry is 110,000 tons per month as weaving sector consumes 60,000 tons per month, hence there is an extra quantity of 25,000 tons per month available after imposition of quota. According to the economic survey of WTO 2009 Pakistan export in 2008 $17.9 billion and clothing trade was $3.9 billion In recent year’s composite industry developed very fast. Especially there is an increasing interest in structural textile composite due to their remarkable features and mechanical properties.Textile sector of the country has portrayed strong earnings growth of 23 percent in first half of fiscal 2009. Analysts said that composite sector, which account for almost 67 percent of the entire textile sector market capitalization, posted an extraordinary earning growth of 61 percent. Moreover, weaving sector came back into profit whereas the spinning sector rushed into losses when compared to the corresponding period last year. In the report of textile composite sector which is published in April 09,2009 a sample of 24 companies from the composite sector , 6 weaving companies and 31 spinning units representing 92 percent,95 percent and 80 percent market capitalization of their particular sector, was used for analysis.



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Analyst, Ali zafar perceived amid rise in export based revenue due to depreciating rupee (21percent in 1hfy09), net sale of the textile sector shot up by 22 percent to Rs127 billion. This resulted in improve margins, which rose by 377bps despite high cotton prices (up 21 percent) during the period. However, a 100percent increase in financial cost to Rs12.4bn brought down earning to Rs3.4bn, still up by 23 percent. Financial cost rose on the back of higher borrowing rates as 6-month KIBOR during the period average 14.59 percent, 458bps. Composite sector remarkable earning growth of 61 percent was largely driven by improving growth margin which increased by 451bps. Due to its export orientation, depreciating rupee boosted rupee based revenue of the sector which increased by 26 percent to Rs84bn. Its impact on the bottom line was however impaired by 105percent increase in finance cost to Rs8.5bn. LITERATURE REVIEW The Textile Composite is very large industry and plays very important part in the growing economy of a country. Capital structure has been the subject under consideration on numerous occasions over the last 50 years. The capital structures of a company shows company present and compare it to the past position of firms Khan & Mahmood (1996) [1] studied and estimated that the Pakistan textile would ends up in benefit after elimination of the MFA regime, they added that Pakistan market access would improve by approximately sixty two percent and for clothing and textile is would go to about sixty seven percent. The end of MFA provides Pakistan better opportunity. Asim (2003) [2] indicated the concerns of the Pakistani exporters about the misinterpretation of the WTO regime and its effects on the textile industry. He added that escalation of the MFA on one side would ease the exporters in terms of dealing with the international competitors. On the other side Pakistan is uneasy with the competition provided by the major countries like china, India and Bangladesh. On the whole he examined that on the elimination of the quota restriction Pakistan will maintain the positive trend and yarn and cotton demand would enhanced. (Rohail, 2008)[3] “ In US textile market China tops market with 36 per cent of share, Bangladesh at second with 21 per cent, Morocco with 19 per cent, India at 18 per cent and Pakistan dropping with13 per cent. South Korea has also lost a share 20 per cent of the US market. In the EU textile market China again tops with 29 per cent of share, Vietnam with 28 per cent of share, India 19 per cent and Pakistan with 1.5 per cent while the Philippines had lost 11 per cent share.. Currently the biggest threat the Pakistan textile industry is facing is to maintain its competitive position against its competitors and increase its share in world exports (Naqvi, Nasir, Yousaf and Ahmad 2011) [4]. Opler (1997) [5] and Levy (1998) [6] have tried to evaluate a formula for defining the ideal capital structure. Both techniques form a type of consideration analysis, whereby the value effects of different factors of debt and equity funding are measured. Damadoran (2001) [7] argue that firms should conclude the ideal structure by trading off the expenses and benefits of debt. But, in actuality, businesses may possibly use one of the following methods; a) Benchmarking against other firms in their industry. b) Strong preference for a type of financing (pecking order theory c) selecting debt and equity with respect to their life cycle. Jasir (2011) [8] The study finds that determining the exact optimal or best capital structure is not a science, so after studying a number of issues, a firm forms a target capital structure it believes is optimal, which is then used as a guide for raising funds in the future. A research in contradiction to this statement (Myers and Majluf, 1984) [9] stated that firms go for internal financing due to information asymmetry. This research shows negative impact of leverage on profitability. (Stuitz)[10] stated that firms are unwilling to issue equity because of



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the cost that interrelated with being structuralized. However, Tong and Green run experimental proofs for the care of packing order theory. Along with static trade-off theory and pecking order theory, further view about capital structure was established by (Ross)[11], who suggested that the debt is measured a way highlights the hope of investors on the company. This view is named as signaling theory. The theory suggested that if a company issues debt it’s giving the signals to the market that the firm is hoping positive results in the future cash flows. (Sajid,Raza and Musarrat)[12] Proposed results from their study on the capital structure of Pakistan textile and they are on the following conclusion: Firms of Pakistan followed the financing pattern giving by the trade-off theory and pecking order theory like developed economy. The ownership didn’t affect leverage structure. Working capital is known as life giving force for any economic unit and its management is considered among the most important function of corporate management. Every organization whether, profit oriented or not, irrespective of size and nature of business, requires necessary amount of working capital. Working capital is the most crucial factor for maintaining liquidity, survival, solvency and profitability of business (Mukhopadhyay, 2004) [13]. Padachi (2006) [14] has observed the developments in operational capital management and its effect on firm’s performance for 58 Mauritian small manufacturing firms during 1998 to 2003. He explained that a well-planned and effected working capital management is anticipated to promote positively to the making of firm’s value. The results showed that high investment in accounts and receivables is linked with low profitability and also showed an increasing trend in the short term element of working capital financing. Shah and Sana (2006) [15] used a very small sample of 7 oil and gas sector firms to study this association for period 2001-2005. The results proposed that managers can create positive return for the shareholders by efficiently managing working capital. Deloof (2003) [16] investigated a sample of Belgian firms, and Wang (2002) studied a sample of Japanese and Taiwanese firms, stressed that the way the operational capital is achieved has a major impact on the profitability of firms and increase in profitability by dropping number of day’s accounts receivable and dropping inventories. A shorter Cash Conversion Cycle and net trade cycle is related to better performance of the firms. Moreover, effective working capital management is very important to form cost for the shareholders. Lazaridis and Tryfonidis(2006) [17] explored the relationship of corporate profitability and working capital management for firms listed at Athens Stock Exchange. They reported that there is statistically major relationship between profitability measured by the Cash Conversion Cycle and gross operating profit. Moreover, Managers can create profit by correctly handling the individual components of working capital to a peak level. Raheman,Talat, Mahmood and Abdul (2010) [19] ,The results shows that for overall industrial sector, Working Capital Management has a substantial influence on profitability of the firms and plays a main role in value creation for shareholders as longer Cash Conversion Cycle and Net Trade Cycle have negative impact on Net Operating Profitability of a firm. Rajan and Zingales (1995)[19] related leverage and its determinates across G-7 countries that are united states, Germany, Canada, Italy, France, Japan and united kingdom. They investigated there was a positive relationship of leverage and profitability only in Germany. Tangibility is positively correlated in all countries. Size is positively correlated with leverage except Germany. Antonoiu, Guney and Paudyal (2002) [21] studied factors of capital structure and leverage ratio of French, German and British firms with the help of strict data. Their results proposed that size of the firm positively affect the leverage ratio. They analyze relation of productivity, size of firms, fixed assets. This study identifies a positive impact on firm’s size on leverage.



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While the relationship between fixed asset ratio and level of leverage was mixed means positive in Germany but negative in France and UK. This indicates that tangibility of assets is more important in bank borrowing in Germany. The effect of all these factors on leverage depends on financial environment and tradition of the country in which firm operates. Frank and Vidhan (2005) [22] studied that there are a large number of variables that appear to be related to debt ratio of the firm but only few factors have significant effect on debt ratio. They found that relation between leverage and size of firm is positive. For tangibility of assets Empirical results showed a positive relation among leverage and tangibility of assets of firm. Harris and Reviv (1990)[22] gave one more reason of using debt in capital structure. They say that management will hide information from shareholders about the liquidation of the firm even if the liquidation will be in the best interest of shareholders because managers want the perpetuation of their service. Altman (1984)[24] was the first to identify direct and indirect costs of bankruptcy. By studying 12 retail and 7 industrial firms, he found that firms in the sample faced 12.2% of indirect bankruptcy costs at time t-1 and 16.7% at time t. He concluded that capital structure should be such that the present value of marginal tax benefits is equal to marginal present value of bankruptcy costs. Amihud and Lev (1981)[25] suggest that mangers have incentives to pursue strategies that reduce their employment risk. This conflict can be solved by increasing the use of debt financing since bondholders will take control of the firm in case of default as they are powered to do so by the debt indentures. Research regarding the size of the firm and the capital structure (Titman and Wessels, 1988)[26] stated that debt financing might be large for small firms and small for large firms. This case can be true only if small firms take debts for short periods thus decreasing the overall cost of borrowing. The existence of highly levered small firms can only be true if borrowing is in short term. If the creditors see the value of the firm decline, they will lose their confidence in the firm and avoid investment, which would lead to loss of a major portion of the capital structure and thus lead to a decline in the growth and operations of the firm. In developing countries, creditors prefer low risk rather than higher returns. Due to this reason, investors in developing countries almost always invest in firms with higher stability than in the firms with higher return. The reason for this is that once a firm defaults on its debt, then it might take a long time for the compensation of the creditors or they might never get compensated as the legal proceedings are quite slow in such countries. From the above research study of passed literatures we can say that there many reasons for the growth of their capital structure. Textile composite is very mature industry but in some past few years there is a decline to this industry and their debts need long term maturity and so much leverage to complete all the operations. After searching all the literatures on capital structures we found some gaps. (1) Determinants of capital structure can be changed day by day so, researches should latest data to study. (2) Diversification of Debt rate on capital structure. Methodology In order to make an in depth analysis in textile composite in Pakistan we collected the data from year (2001-2009) to observe the capital structure. Then we calculated coefficient of variation to check the consistency of different determinants of capital structure over some specified years. In the end with the help of software “SPSS 17.0” we applied different tests and analyze the results. There are some limitations regarding to that research paper that some unknown reasons data for the year 2010 is not available to find the results.



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Empirical Results Histogram is a graphical representation showing a visual impression of the distribution of data.

The graph is showing an interesting picture because sales star declining from year 2001.the minimum value of sales is in year 2008 and it star increasing in year 2009 but it is still lower than the values of previous years.

The graph shows that profit after tax has maximum value in 2001 and there is no significant difference till year 2007 but in year 2008 and 2009 it is showing a great decline.



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In this graph mean values of total assest are gradually increasing . the equityy is also showing same increasing trend but from year 2008-2009 it star decreasing. While on the other hand profit before tax and profit after tax have same trend. Coefficient of variation Years Means S.D CV

2001 169.7437 200.1586 117.9 2002 176.2003 223.6964 127.0 2003 189.6104 236.9043 124.9 2004 197.2124 239.4232 121.4 2005 217.5203 286.2172 131.6 2006 335.8668 607.2039 180.8 2007 322.9673 572.4483 177.2 2008 332.5141 501.7190 150.9 2009 442.1021 806.9438 182.5

paid up capital(in mil.Rs.

TOTAL 264.8597 408.3016 146.0222 2001 16.9744 20.0159 117.9 2002 17.6200 22.3696 127.0 2003 18.9610 23.6904 124.9 2004 19.7212 23.9423 121.4 2005 21.7520 28.6217 131.6 2006 26.7555 55.7680 208.4 2007 32.2967 57.2448 177.2 2008 23.6705 44.8342 189.4 2009 34.6313 73.5811 212.5

No. of Shares

TOTAL 23.5980 38.89644 156.7



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2001 318.0425 811.4986 255.2 2002 390.7177 838.0370 214.5 2003 567.9462 1099.8460 193.7 2004 708.9855 1378.3185 194.4 2005 1,002.5019 1961.1826 195.6 2006 1,533.4083 3410.8933 222.4 2007 1,970.2350 4644.6245 235.7 2008 2,109.7168 5384.6569 255.2 2009 1,657.9390 3567.0732 215.2

EQUITY (MILL.)

TOTAL 1139.944 2566.237 220.2111 2001 1,542.3716 2273.7462 147.4 2002 1,634.8322 2259.8263 138.2 2003 2,024.6219 2700.0357 133.4 2004 2,632.5385 3256.0761 123.7 2005 3,436.1625 4009.4491 116.7 2006 4,421.8711 6029.2585 136.4 2007 5,032.4438 7067.8892 140.4 2008 5,787.0442 8580.7176 148.3 2009 5,713.9790 7840.3362 137.2

TOTAL ASSETS (MIL.)

TOTAL 3580.652 4890.815 135.7444 The coefficient of variation is used for checking the consistency of some particular item over a particular year. The minimum value indicates the consistency. According to the table the PAID-UP CAPITAL and NO. OF SHARES are most consistent in 2001 whereas EQUITY is showing consistency in 2003 and TOTAL ASSETS are consistent in year 2005.

Years mean S.D C V 2001 1,447.7928 2005.6923 138.5 2002 1,595.0590 2164.7541 135.7 2003 1,829.8931 2454.0311 134.1 2004 2,350.4225 2843.4189 121.0 2005 2,048.2409 2295.0279 112.0 2006 2,783.1628 3101.8388 111.5 2007 3,254.7580 3456.6564 106.2 2008 3,887.4362 4414.1262 113.5 2009 4,333.1025 4933.1442 113.8

SALES (MILL.)

TOTAL 2614.43 3074.299 120.7 2001 55.8530 144.7711 259.2 2002 62.7286 131.4299 209.5 2003 74.4544 135.4815 182.0 2004 95.3055 194.1694 203.7 2005 138.2961 300.2342 217.1 2006 136.0371 323.7003 237.9 2007 138.3875 325.6973 235.4 2008 227.7582 1012.1371 444.4 2009 35.5493 314.0031 883.3

PROFIT BEFORE TAX

TOTAL 107.1522 320.1804 319.1667



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2001 42.5454 129.7011 304.9 2002 46.1822 113.8203 246.5 2003 61.6428 116.6612 189.3 2004 75.8056 169.9230 224.2 2005 118.1500 275.6595 233.3 2006 112.6007 295.3667 262.3 2007 109.7299 302.8664 276.0 2008 193.7736 973.9394 502.6 2009 7.7991 270.9042 3473.5

PROFIT AFTER TAX

TOTAL 85.3588 294.3158 634.7333 Sales are showing consistency in year 2007 because it has the minimum value in the specified year as compared to others. PROFIT BEFORE TAX and PROFIT AFTER TAX both are showing consistency in year 2003. ONE WAY ANOVA TEST ANOVA

Sum of Squares df

Mean Square F Sig.

Between Groups

3555043.059 8 444380.38 2.143 .031

Within Groups

90394083.394 436 207325.88

Paid-up Capital

Total 93949126.453 444 Between Groups

18129.985 8 2266.2482 1.143 .333

Within Groups

948016.916 478 1983.299

No of Share


157095718.039 8 19636965 2.501 .012

Within Groups

3086250911.398 393 7853055.8

Equity


987655149.369 8 123456894 4.704 .000

Within Groups

10314386598.653 393 26245259

Total Assets


354354263.592 8 44294283 4.583 .000

Within Groups

3798185126.522 393 9664593.2

Sales


1272714.762 8 159089.35 1.020 .420 Profit Before Tax Within

Groups 65193307.662 418 155964.85



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1091342.937 8 136417.87 .988 .445

Within Groups

57718646.817 418 138082.89

Profit After Tax

Total 58809989.754 426

HYPOTHESIS In this H0 is our null hypothesis where as H1 is our Alternative hypothesis. Sales H0: µ2001= µ2002= µ2003= µ2004= µ2005= µ2006= µ2007= µ2008= µ2009 H1: At least two variables are different since the P value is less than 0.05 which is highly significant so we reject our null hypothesis and accept our alternative hypothesis. LSD

Year year Mean Difference (I-J) Sig.

2006 2001 1335.370659* .034

2001 1806.966213* .004

2002 1659.699979* .009

2007

2003 1424.864703* .026

2001 2439.643922* .003

2002 2292.377687* .005

2003 2057.542411* .012

2004 1537.013406 .061

2008

2005 1839.195177* .025

2001 2885.309864* .000

2002 2738.043629* .000

2003 2503.208353* .000

2004 1982.679348* .002

2005 2284.861119* .000

2009

2006 1549.939204* .017

According to the LSD Test it can be observed that mean value of 2001-2009 is significantly different. The mean value of year 2006 is also showing significant difference with the average values of year 2007 and 2008.It also seen that µ2009 ≠ µ2001, µ2002, µ2003 and µ2004. H0: µ2001= µ2002= µ2003= µ2004= µ2005= µ2006= µ2007= µ2008= µ2009 H1: At least two variables are different Since the calculated P- values of sales as shown in the above table is less than 0.05 for sales, its mean that we will accept alternative hypothesis (H1) and reject null hypothesis (H0). Similarly, Paid up Capital, Equity and Total Assets also have the values less than 5% .where other variables Profit after Tax, Profit before Tax and No. of shares have no difference in their means from year 2001-2009.so we accept our null hypothesis (H0) and reject alternative hypothesis (H1).



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Multiple linear regression analysis has applied on the data. We took Y=profit after Tax as dependent variable and X2=Paid UP Capital, X3=No. of Shares, X4= Equity, X5=Total Assets, X6=Sales, X7=Profit before Tax. So, Our Model will be like as: Y=β0+ β1X1+ β2X2+ β3X3+β4X4+β5X5+ β6X6

Model R R Square Adjusted R

Square Std. Error of the

Estimate

1 .998a .997 .997 21.524141 2 .998b .997 .997 21.497352 3 .998c .997 .997 21.519601

The above value of table shows the value of R Square the goodness fit of the model by. Its value is 0.997 so we can say that our model is 99.7% accurate and it means that our independent variables are explaining the dependent variable up to 99.7%. ANOVAd

Model Sum of Squares df

Mean Square F Sig.

Regression 56248399.0 5 11249679.8 24282.227 .000a

Residual 183462.3 396 463.3

1

Total 56431861.3 401 Regression 56248393.2 4 14062098.3 30428.476 .000b

Residual 183468.0 397 462.1

2

Total 56431861.3 401 Regression 56247550.2 3 18749183.4 40486.844 .000c

Residual 184311.1 398 463.1

3

Total 56431861.3 401 a. Predictors: (Constant), Profit Before Tax, No of Share, Sales, Equity, Total Assets

b. Predictors: (Constant), Profit Before Tax, No of Share, Sales, Total Assets

c. Predictors: (Constant), Profit Before Tax, No of Share, Sales

d. Dependent Variable: Profit After Tax

Unstandardized Coefficients Standardized Coefficients

Model B Std. Error Beta t Sig.

(Constant) .847 1.458 .581 .561

No of Share .111 .044 .014 2.509 .013 Equity .000 .001 .001 .111 .911 Total Assets -.001 .001 -.015 -1.115 .265 Sales -.008 .001 -.067 -9.368 .000

1

Profit Before Tax .977 .004 1.039 219.515 .000



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(Constant) .808 1.413 .572 .568

No of Share .110 .043 .014 2.537 .012 Total Assets .000 .001 -.014 -1.351 .178 Sales -.008 .001 -.067 -9.667 .000

2

Profit Before Tax .977 .004 1.039 266.964 .000 (Constant) 1.138 1.394 .816 .415

No of Share .067 .029 .008 2.293 .022 Sales -.009 .000 -.074 -18.265 .000

3

Profit Before Tax .975 .003 1.037 293.367 .000 a. Dependent Variable: Profit After Tax Profit after Tax (PAT) is a (dependent) and Paid up capital, No. of Shares, Equity, Total Assets, Sales, Profit before Tax are independent variables. After applying backward method No. of shares, Sales, and Profit before Tax has described the dependent variable better. PAT= β0+ β1 (No. of Shares) + β2 (Sales) + β3 (Profit before Tax) PAT=1.138+0.067(No. of Shares) + (-0.009) (Sales) +0.975 (Profit before Tax) Above Model concluded that No. of Shares and Profit after Tax has positive effect on PAT while sales have negative effect on PAT but overall effect is positive. Conclusion The study that we have conducted provides overall effect of different variables of capital structure on industrial progress from 2001-2009. The result shows that the value of profit after tax is positive which means that this industry is making profit but the growth rate of profit is very low. The strange thing that has been concluded from the results is that sales have a negative impact on profit after tax. According to this if we increase our sales by one unit it will decrease PAT by (-0.009). It means that their final product is not even paying them the total cost incurred on it. On the other hand profit before tax and no. of shares have a positive impact on PAT thus they overcome the negative effect of sales on PAT. From the data collected, it has been concluded that most of the textiles companies are shifting to personal goods. This can also be a reason for the downfall of textile in Pakistan. As textile industry is the back bone of Pakistan economy so in order to enhance the performance of this sector government should fulfill their basic requirements (gas and electricity).



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