بررسي رابطه ساختار سرمايه و كارايي شركت هاي پذيرفته‌شده در بورس اوراق بهادار تهران با استفاده از تكنيك تحليل پوششي داده ها

Investigating the Relationship between Capital Structure and companies’ Efficiency in Tehran Stock Exchange, Using DEA Method

اين پژوهش كاربردي ـ تجربي بوده و رابطه ساختار سرمايه و كارايي شركت ها را بررسي مي نمايد. هدف اين است كه چه سطحي از بدهي مي تواند به‌عنوان ابزاري نظام بخش منجر به كارايي بيشتر گردد و آيا ساختار سرمايه در شركت هاي كاراتر دربرگيرنده‌ي نسبت بدهي به سرمايه بالاتر و يا پايين تري مي باشد؟ روش ارزيابي كارايي شركت ها، تحليل پوششي داده ها (DEA) است كه ده نسبت مالي، به‌عنوان ورودي و خروجي هاي اين تكنيك، از صورت هاي مالي شركت هاي پذيرفته شده در بورس اوراق بهادار تهران (1384-1388) در چهار صنعت استخراج شده اند؛ سپس با متوسط ارزش بازار سهام هر شركت، ارزش دفتري حقوق صاحبان سهام و جمع دارايي ها را تعديل نموده ايم. پس از تعيين كارايي، فرضيات تحقيق با استفاده از دو مدل رگرسيوني با متغيرهاي كنترلي آزمون شده اند. نتايج حاصل از تحقيق وجود رابطه معنادار ميان كارايي و نسبت بدهي را نشان مي دهد؛ همچنين رابطه اين دو متغير با تعدادي از متغيرهاي كنترلي مورد استفاده معنادار مي باشد.

This paper investigates the relationship between capital structure and companies’ efficiency. We employ non-parametric data envelopment analysis (DEA) method to empirically construct the industry’s ‘best practice’ frontier and measure companies’ efficiency in each industry. This is a practical & empirical research, which uses the financial statements to collect required data. The statistic population is the listed companies in Tehran Stock Exchange from 2005 to 2009, and sample selection is done based on the systematic omission. The selected sample includes 870 companyʹs year in 4 different industries. Financial ratios are calculated for each companyʹs year and are used as inputs and outputs in DEA technique. To make the historical information, appeared on the financial statements more relevant, the average of market value per share for each company is used as an adjusting factor for book value of owner’s equity and assets. After determining the efficient companies in each industry, we examine the relationship between the leverage ratio of the previous year and efficiency of the current year and the effects of current year’s efficiency on the leverage ratio of the next year in terms of two hypotheses using two regression equations. In these two equations we use efficiency and leverage ratios (our main variables) and also five more control variables, including profitability, tangibility, intangibility, company size (the natural log of the company’s sales), sales growth and the type of industry as our dummy variable. The results of our research show a meaningful relationship between efficiency and leverage ratios. Also, there are some meaningful relations between some of our control variables and the two main variables.