Investment Analysis in Fixed Assets

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. Investment Analysis in Fixed Assets Dr. S. L.Tulasi Devi, Prof. V. V. L. N. Rao Abstract This paper focuses attention on specific aspects of entrepreneurial decisions relating to investment, both in the total fixed investments and plant & machinery (separately). Demand and financial factors, internal and external, are considered in the investment analysis. Finally the influence of determinants of fixed investment and investment plans are examined in Metals, Alloys, Metal Products and Structurals Industry in India. Keywords Determinants, Fixed Assets, Investment, Multiple Regression, Best equation. T I. INTRODUCTION he fixed investment decision is an important decision in the valuation of the firm, attempts were made previously to understand the factors that influence the fixed investment decision of the firm. Such studies have identified different factors which play an important role in the determination of the fixed investment of the companies and the studies made by some of the researchers like John.R.Meyer and Edwin Kuh, K.Krishnamurthy and D.U.Sastry, K.L.Krishna, G.D.Misra, Dr.Premkumar, Prasant Kumar Sahoo 7, Ranganadhan, M, and Madhumathi R Ashim Lal Chakraborthy 9, and Mrs. Sadhna Srivastava, Bonton E. Gup 0, Gompers, Paul A., Jorgenson, D.W have added significant contributions to this important area of Business Finance. Though some attempts were made earlier to find out the validity of such contributions in the Indian context, there are very few studies, which tested their applicability at the micro level units on a more comprehensive basis. Hence an attempt is made in this study to understand the different economic variables which influenced the fixed investment of some sample companies in selected industries in India. II. OBJECTIVES, METHODOLOGY AND LITATIONS Being exploratory in character, the present study aims at understanding the fixed investment behavior of some sample companies in Metals, Alloys, Metal Products and Structurals Industry. This study is undertaken: To analyze the investment pattern in Gross Fixed Assets of S.L.Tulasi Devi is with the National Institute of Technology, Warangal, (NITW) - A.P.-000 INDIA. She is now with the School of Management (corresponding author: +9 90; fax: +9 7097; (e-mail: sltdevi.nitw@gmail.com). V.V.L.N.Rao is with the Department of Commerce and Business Administration, Aacharya Nagarjuna University, Gunturu, A.P., INDIA. (email:vvlnrv@yahoo.co.in). some selected companies in the Metals, Alloys, Metal Products and Structurals Industry in India. To analyze the investment pattern in Plant & Machinery separately in the above companies of Metals, Alloys, Metal Products and Structurals Industry. To analyze the determinants of investment in Gross Fixed assets i.e., Gross Block and Plant & Machinery in Metals, Alloys, Metal Products and Structurals Industry. To analyze the best models, which determine the investment behavior in fixed assets through Stepwise Multiple Regression Analysis. To analyze the best equation from the RegressionAnalysis. Source of data The data relating to the different economic variables of companies have been collected from various issues of the Bombay Stock Exchange Official Directory. The source of data for the fixed investment policy of Metals, Alloys, Metal Products and Structurals Industry is the data relating to the individual sample companies in Metals, Alloys, Metal Products and Structurals Industry. The industry, for the purpose of the study, means the aggregate of sample units in the industry. Thus the cross section data of micro level economic variables is added to make up the industry data. Period of study The present study covers a period of 0 years from 000 to 009. Since the fixed investment policy is a long-term policy, a period of 0 years is considered to be long enough to study the Fixed Investment policy of companies/industries. The sample selection The selection criteria of the companies for inclusion in the sample of the study have been that a) Companies must have been incorporated on or before 97, i.e., years before the period for which analysis has been started here so that a minimum period of at least years must have been elapsed for them to establish themselves and invest in fixed assets; b) Companies must have had a paid-up capital of more than Rs 0 lakhs in 97 so that only medium and large companies as per the classification of the Reserve Bank of India are included in the sample; and c) Companies must be continuously profit making companies in all 0 years (which is the study period here) so as to

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. ensure that only which made profits on consistent basis are included. Based upon the above selection criteria a total of the following six firms constitute the size of the sample for the purpose of this study.. Electro Steel Castings Ltd.. Sundaram Fasteners Ltd.. Ispat Alloys Ltd.. Surya Roshini Ltd..Jindal Iron & Steel Company Ltd.. Tatagarh Industries Ltd. Variables A list of the variables both dependent and independent that are used in this study is presented. Dependent Variables. GB t- (t-) = Change in Gross Block. Pm t- (t-) = Change in Plant & Machinery Independent variables. S t- (t-) = Change in sales. GIF t = Gross Internal Funds. NL t = Stock of Net Liquidity. D t =Dividends. EC t- (t-) =Growth of equity capital. DETOUT t =Debt outstanding 7. T t = Provision for taxes. I t =Interest on borrowed funds Step wise Regression The present study is mainly based on stepwise multiple regression analysis. This technique begins with the simple correlation matrix and enters into regression of the independent variables most highly correlated with the dependent variable. Using the partial coefficients generated with respect to the other variables, the computer programme then selects the next variable to enter the model. Stepwise regression permits the analyst to start with a large number of variables that might have predictive values and then use the model to select the particular variables that appear to provide the prediction. Statistical analysis The data used in this study was processed by using computer packages, they are Statistica and Limdep. The multiple linear stepwise regression was run in order of importance in terms of explanatory powers of different variables influencing the dependent variable in the study. In other words, which independent variable has the greatest effect in determination of the dependent variable? How sensitive is dependent variable to fluctuations in independent variables? This technique is adopted in order to obtain a realistic picture of the importance of the various independent variables, which influence financing investment in the Metals, Alloys, Metal Products and Structurals Industry in India. Models built This study is conducted on the basis of three models. These three models have been tested in the case of each company. They are. Adding Model. Constant Model. Elimination Model. The above three models have been tested in each case with the intercept term. Thus altogether + equations are estimated in each case.. Adding Model It may be noted that in this model, an independent variable has been entered into the model at an earlier step, and then another independent variable is added to the first one and then another variable etc. So ultimately all the independent variables are added and tested under this model. The following are the equations, which are estimated under this model.. GB t- (t-) or PM t- (t-) = b 0 + b S t-(t-). GB t- (t-) or PM t- (t-) = b 0 + b S t-(t-) + b GIF t. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b NL t. GB t- (t-) or PM t- (t-) = b 0 + b S t-(t-) + b GIF t+ b NL t+ b D t. GB t- (t-) or PM t- (t-) = b 0 + b S t-(t-) + b GIF t+ b NL t+b D t+ b EC t-(t-). GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b NL t+b D t+ b EC t-( t-)+b DBTOUT t 7. GB t- (t-) or PM t- (t-) = b 0 +b S t-( t-)+b GIF t+b NL t+b D t+ b EC t-( t-)+b DBTOUT t+ b 7 T t. GBt - (t-) or PM t- (t-) =b 0 + b S t-( t-)+b GIF t +b NL t+b D t+ b EC t-( t-)+b DBTOUT t+b 7 T t + b I t.. Constant Model In this model the first two independent variables (change in sales and gross internal funds) are kept as constant variables because these two are very closely related to the dependent variables, and the third variable is changed in each model. The following are the equations, which are estimated under this model.. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b NL t. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b D t. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b EC t-( t-). GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b DBTOUT t. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b T t. GB t- (t-) or PM t- (t-) = b 0 + b S t-( t-)+ b GIF t+ b I t. Elimination Model In elimination model, the estimated equations are not constant but the number of equations depends on the significance of the variables which proved to be significant. The following procedure is adopted while estimating the equations. Initially, all the independent variables are included in the model. Based upon the significance of t values, the variable with the least t value is dropped and then again the equation is estimated with the remaining independent variables. Again the variable with the least t value is dropped and the equation is again estimated. This process is continued

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. till all the independent variables in the equation have proved to be significant either at or at 0% level. So the number of equations varies depending upon the significance of variables in each case of companies. The above + equations are estimated for all the companies and industry aggregate. The total numbers of estimated equations are as follows: For companies and industry aggregate in two cases (both gross block and plant and machinery): In Adding Model. 7 = In Constant Model... 7 = In Elimination Model... = Total 9 - Thus altogether 9 equations have been estimated with all the necessary tests, using the data for 0 years in each case. To find out the effect of different independent economic variables on the fixed investment of the companies during the period of this study, the Multiple Linear Regression Analysis is used with all its limitations. Selection of the best model The following procedure is adopted to select the best model in each case from out of the + estimated equations. Step - I Out of the + estimated equations in each case, all those equations, whose Multiple Correlation Coefficients are found to be significant at level based on their calculated F values are picked up for further analysis. Step II The equations thus picked up according to step-i above are further screened in the following way: a) The values of intercept term (b 0 ) and other regression coefficients (b, b, b ) are tested at level of significance based on their calculated t values. If only one equation is found in which all the explanatory variables are significant at level, then that equation is taken as the best model to explain the fixed investment behavior of the company. If, on the other hand, there are two or more equations in which all the explanatory variables are found significant at level, the procedure explained in step III is followed. b) But if, in a company, there is not even a single equation in which all the independent variables show significant effect at level, the significance level is relaxed and the impact of the variable is tested at 0% level wherever necessary. That is, the variables, which are not significant at level, are tested at 0% level of significance. However, this has happened in a very few cases in this study. If only one equation is found in which the explanatory variables are significant at level or 0% level, then that model is selected as the best model to describe the fixed investment behavior of the company. On the other hand, if there are two or more than two equations in which the independent variables are significant at or 0% level, the procedure explained that in step III is followed to decide the best model. Step III As stated in step II, if there are two or more equations in which all the explanatory variables are significant that particular equation whose R is the highest is chosen as the best equation to explain the fixed investment behavior of the company. Limitations of the study This study has the following limitations. ) The accounting years of the sample companies are not common and the closing of the accounting years is spread over all the months of the year. So for the industry aggregate data the accounting year is not uniform. ) The Industry data, for the purpose of the study, comprise the aggregate of the data of the micro level sample units that are selected for this study. As there is difference in the classification of industries between Reserve Bank of India and the Bombay Stock Exchange, the RBI data could not be relied upon for the industry aggregate data and the Bombay Stock Exchange Directory does not provide the Industry aggregate data. Since it is highly difficult to collect the data of all the firms which appear on the Bombay Stock Exchange Directory the aggregate data of the sample micro level units is taken to represent the industry data for this study. ) The data for the study are taken in absolute values as given in the Bombay Stock Exchange Directory and no price deflator is used to adjust for the inflationary trends. ) This study is only exploratory in its objectives and does not aim at recommending any policy measures either for the companies or for the government. III. ANALYSIS OF THE REGRESSION RESULTS OF FIRMS IN METALS, ALLOYS, METAL PRODUCTS AND STRUCTURALS INDUSTRY This section deals with the study of investment behavior of sample firms taking into consideration two dependent variables namely Gross Block (Y ) and Plant and Machinery (Y ) in Metals, Alloys, Metal Products and Structurals Industry of India. This study deals with eight explanatory variables, which influence the investment behavior in fixed assets (Y and Y ). This study is conducted on the basis of three models. They are Adding model, Constant model and Elimination model. In Adding model there are eight estimated equations. In 7

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. Constant model there are six estimated equations and in Elimination model the estimated equations are not Constant but the number of equations depend on the significance of independent variables. The following abbreviations are used in the tables: -The number of firms, where the explanatory variable has shown an impact. -The number of equations in which the explanatory variable is significant at level. 0% - The number of equations in which the explanatory variable is significant at 0% level. M - Metals, Alloys, Metal Products and Structurals Industry (The numbers indicate the number of equations that TABLE No. Of firms: ) Explanatory variable : CHANGE IN SALES (b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% TABLE No. Of firms: ) Explanatory variable : GROSS INTERNAL FUNDS (b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 7 9 0% 0% 0% 0% 0 0 0 0 E M - Elimination model TABLE No. Of firms: ) Explanatory variable DIVIDENDS(b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 0% 0% TABLE Metals, Alloys, Metal Products and Structurals Industry (Total No. Of firms: ) Explanatory variable GROWTH OF EQUITY CAPITAL(b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 7 0% 0% TABLE Metals, Alloys, Metal Products and Structurals Industry (Total No. Of firms: ) Explanatory variable GROWTH OF EQUITY CAPITAL(b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 0% 0% 7 TABLE No. Of firms: ) Explanatory variable : STOCK OF NET LIQUIDITY(b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% are estimated) 0% 0% 0 AM - Adding model CM - Constant model

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. TABLE No. Of firms: ) Explanatory variable INTEREST ON BORROWED FUNDS(b ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 7 0% 0% IV. ANALYSIS OF THE BEST EQUATION FROM THE REGRESSION RESULTS OF FIRMS IN METALS, ALLOYS, METAL PRODUCTS& STRUCTURALS INDUSTRY This section deals with the determination of the best equation from the estimated equations of three models namely, Elimination model, Adding model, and Constant model. In Adding model, there are eight estimated equations. In Constant model there are six estimated equations. But in Elimination model the estimated equations are not constant but the number of equations depend on the significance of explanatory variables. The best equation is to be determined, from the equations, which consists of all the explanatory variables, which are significant at either level or at 0% level. If there are two or more than two equations from the three models the best equation is to be determined on the basis of highest value of R. In the following pages a detailed analysis of the determinants of investment in fixed assets of a total of six firms in the Metals, Alloys, Metal Products & Structurals Industry is taken up to determine the best equation.. Electro Steel Castings Ltd.: - Y Gross Block: When the investment in Gross Block as a dependent variable is analysed, Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Dividends, Growth of Equity Capital, Debt Outstanding, Provision for Taxes and Interest on Borrowed Funds are used as the independent variables in the present study. In Adding model there is only one equation which consists of only one independent variable, that is, Change in Sales, which is significant at 0% level out of eight estimated equations in Electro Steel Castings Ltd. In this company, in Constant model also there is only one equation out of six estimated equations which includes three independent variables namely, Change in Sales, Gross Internal Funds and Provision for Taxes, which are found to be significant at level. Similarly in Elimination model there is only one equation which involves five independent variables namely, Stock of Net Liquidity, Dividends, Growth of Equity Capital, Provision for Taxes and Interest on Borrowed Funds, which appear to be significant either at level or at 0% level out of four estimated equations. The best equation is selected from the Elimination model on the basis of value of R. In this equation, the value of R is more than the value of R of the equations under Adding and Constant models. It is concluded that, in Electro Steel Castings Ltd., Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Dividends, Growth of Equity Capital, Provision for Taxes and Interest on Borrowed Funds, appear to influence the investment in Gross Block. Y Plant and Machinery: In Electro Steel Castings Ltd., all the explanatory variables are found to be not significant in any of the equations under Constant and Adding models. Where as in Elimination model there are seven estimated equations. The best equation contains two independent variables namely, Stock of Net Liquidity and Growth of Equity Capital. These variables have proved to be significant at level. Hence it can be said that, in Electro Steel Castings Ltd., Stock of Net Liquidity and Growth of Equity Capital influence the investment in Plant and Machinery.. Ispat Alloys Ltd.: - Y Gross Block: In this company, there is only one equation which includes only one independent variable, that is, Change in Sales, which is found to be significant at level out of eight estimated equations under Adding model. Similarly in Constant model there is only one equation out of six estimated equations which involves three independent variables namely, Change in Sales, Gross Internal Funds and Provision for Taxes, which are found to be significant some at level and some at 0% level. In Elimination model there are two equations. The best equation contains seven explanatory variables namely, Change TABLE 7 No. Of firms: ) Explanatory variable PROVISION FOR TAXES(b 7 ) Gross Block ( Y ) Plant & Machinery (Y ) 0% 0% 0% 0% in Sales, Gross Internal Funds, Dividends, Growth of Equity Capital, Debt Outstanding, Provision for Taxes and Interest on 0 9

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. Borrowed Funds. These variables appear to be significant either at level or at 0% level. From the above three equations, the best equation is selected from the Elimination model on the basis of value of R. In this equation, the value of R is greater than the value of R of the equations under Adding and Constant models. Finally in Ispat Alloys Ltd., the above seven independent variables appear to influence the investment in Gross Block. Y Plant and Machinery: In Ispat Alloys Ltd., all the independent variables are found to be not significant in all the estimated equations under Adding and Constant models. Where as in Elimination model, there are five estimated equations. The best equation contains four independent variables, which are significant at level. These variables are Gross Internal Funds, Debt Outstanding, Provision for Taxes and Interest on Borrowed Funds. Ultimately, in Ispat Alloys Ltd., the investment in Plant and Machinery is influenced by the above four independent variables.. Jindal Iron & Steel Company Ltd.: - Y Gross Block: In Jindal Iron & Steel Company Ltd., when the investment in Gross Block as a dependent variable is studied, all the independent variables in the present study are found to be not significant in any of the equations under Constant model. In Adding model there is only one equation which includes only one independent variable that is, Change in Sales, which is found to be significant at 0% level out of eight estimated equations. Similarly in Elimination model there is only one equation out of four estimated equations, Change in Sales, Gross Internal Funds, Growth of Equity Capital, Provision for Taxes and Interest on Borrowed Funds are used as the independent variables and they have proved to be significant at level. The equation from the Elimination model is selected as the best equation from the above two equations on the basis of value of R. In this equation, the value of R is more than the value of R of the equation under Adding model. Thus in Jindal Iron & Steel Company Ltd., the above five independent variables appear to influence the investment in Gross Block. Y Plant and Machinery: When the investment in Plant and Machinery as a dependent variable is analysed, all the independent variables appear to be not significant in any of the equations under Adding and Constant models in Jindal Iron & Steel Company Ltd. In Elimination model, there are four estimated equations. The best equation consists of five independent variables, which are found to be significant at level. These variables are Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Debt Outstanding and Interest on Borrowed Funds. So the above five independent variables are influencing the investment in Plant and Machinery in Jindal Iron & Steel Company Ltd.. Sundaram Fasteners Ltd.: - Y Gross Block: Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Dividends, Growth of Equity Capital, Debt Outstanding, Provision for Taxes and Interest on Borrowed Funds are the independent variables which are tested for their influence on Gross Block. These variables appear to be not significant in any of the equations under Constant model. Where as in Adding model there are two equations which include two independent variables namely, Change in Sales and Gross Internal Funds which are found to be significant at level out of eight estimated equations in Sundaram Fasteners Ltd. In this company, there are two equations under Elimination model. The best equation contains seven independent variables namely, Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Growth of Equity Capital, Debt Outstanding, Provision for Taxes and Interest on Borrowed Funds. These variables have proved to be significant at level. The best equation is selected from the Elimination model on the basis of value of R. In this equation, the value of R is greater than the value of R of the equations under Adding model. It is concluded that, in Sundaram Fasteners Ltd., the above seven independent variables appear to influence the investment in Gross Block. Y Plant and Machinery: In Sundaram Fasteners Ltd., all the explanatory variables are found to be significant in any of the equations under Constant model. There is only one equation out of three estimated equations which involves six independent variables namely, Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Debt Outstanding, Provision for Taxes and Interest on Borrowed Funds and they are found to be significant at level. In Adding model there are two equations which consist of two independent variables namely, Change in Sales and Gross Internal Funds which appear to be significant at level and 0% level out of eight estimated equations. From the above three equations, only one equation from Elimination model is selected as the best equation on the basis of value of R. In this equation, the value of R is more than the value of R of the equations under Adding model. Hence it can be said that in Sundaram Fasteners Ltd., the above six explanatory variables influence the investment in Plant and Machinery.. Surya Roshini Ltd.: - Y Gross Block: When the investment in Gross Block as a dependent variable is analysed, all the independent variables appear to be not significant in all the six estimated equations under Constant model. In Adding model there is only one equation which consists of only one independent variable, that is, Change in Sales, which is found to be significant at level out of eight estimated equations. 0

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. In Surya Roshini Ltd., in Elimination model there are five estimated equations. The best equation consists of four explanatory variables namely, Gross Internal Funds, Dividends, Debt Outstanding, and Interest on Borrowed Funds. These variables have proved to be significant at level and 0% level. Only one equation from Elimination model is selected as the best equation on the basis of value of R. In this equation, the value of R is more than the value of R of the equation under Adding model. Finally in Surya Roshini Ltd., the above four independent variables appear to influence the investment on Gross Block. Y Plant and Machinery: In this company, out of eight estimated equations there is only one equation under Adding model, where Change in Sales, Gross Internal Funds, are used as the independent variables and they have proved to be significant at level. But in Constant model there are two equations out of six estimated equations, which involve four independent variables namely, Change in Sales, Gross Internal Funds, Growth of Equity Capital and Provision for Taxes, which are found to be significant at level. In Elimination model there are six estimated equations. The best equation contains three independent variables, which are found to be significant at level. These are Change in Sales, Gross Internal Funds and Provision for Taxes. From the above four equations, only one equation from Elimination model is selected as the best equation on the basis of value of R. In this equation, the value of R is Greater than the value of R of the equations under Adding model and Constant model. Ultimately in Surya Roshini Ltd., Change in Sales, Gross Internal Funds, Growth of Equity Capital, Provision for Taxes appear to influence the investment in Plant and Machinery..Tatagarh Industries Ltd.: - Y Gross Block: In Tatagarh Industries Ltd., in Adding model there is only one equation, which consists of all the eight explanatory variables, which are found to be significant at 0% level out of eight estimated equations. Similarly in Constant model there is only one equation out of six estimated equations which includes three independent variables namely, Change in Sales, Gross Internal Funds Debt Outstanding which are significant at level. In this company in Elimination model, there is only one equation, which consists of all the independent variables and they have proved to be significant at 0% level. The best equation is selected from the Adding and Elimination models. In this equation, the value of R is more than the value of R of the equation under Constant model. Thus in Tatagarh Industries Ltd., all the eight independent variables influence the investment in Gross Block. Y Plant and Machinery: When the investment in Plant and Machinery as a dependent variable is analysed, all the explanatory variables in the present study are found to be not significant in any of the equations under Constant model. In Adding model in only one equation, where Change in Sales and Gross Internal Funds are used as the independent variables that have proved to be significant either at level or at 0% level out of eight estimated equations. Similarly in Elimination model there are three estimated equations. The best equation contains Six explanatory variables, which are found to be significant, some at level and some at 0% level. These variables are Change in Sales, Gross Internal Funds, Stock of Net Liquidity, Growth of Equity Capital, Provision for Taxes and Debt Outstanding. From the above two equations, the equation from Elimination model is selected as the best equation on the basis of value of R. In this equation, the value of R is greater than the value of R of the equation under Adding model. Hence it can be said that in Tatagarh Industries Ltd., the above six variables appear to influence the investment in Plant and Machinery. METALS, ALLOYS, METAL PRODUCTS & STRUCTURALS INDUSTRY: - Y Gross Block: When the aggregate of sample firms in Metals, Alloys, Metal Products & Structurals Industry is taken as a whole, in Adding model there are two equations which involve two independent variables namely, Change in Sales, Gross Internal Funds which are found to be significant at level out of eight estimated equations. Similarly in Constant model there are two equations out of six estimated equations which include four independent variables namely, Change in Sales, Gross Internal Funds, Debt Outstanding and Provision for Taxes which appear to be significant some at level and some at 0% level. In case of Elimination model there are six estimated equations. In one equation, three independent variables namely, Dividends, Debt Outstanding, Provision for Taxes and their significance level is. The equation from the Elimination model is selected as the best equation out of the above five equations on the basis of value of R. In this equation, the value of R is greater than the value of R of the equations under Adding and Constant models. It is concluded that, in the aggregate of sample firms, Change in Sales, Gross Internal Funds, Dividends, Debt Outstanding, and Provision for Taxes influence the investment in Gross Block. Y Plant and Machinery: When the investment in Plant and Machinery as a dependent variable is studied, in the aggregate of sample firms under Adding model there is only one equation which consists of only one independent variable, that is, Change in Sales, which is found to be significant at level out of eight estimated equations. In case of Constant model all the

International Journal of Humanities and Applied Sciences (IJHAS) Vol. No. independent variables are found to be not significant in any of the equations. In Elimination model there are four equations. In one equation which consists of five independent variables namely, Change in Sales, Gross Internal Funds, Dividends, Debt Outstanding, Interest on Borrowed Funds. The variables have proved to be significant some at level and some at 0% level. From the above two equations, only one equation from the Elimination model is selected as the best equation on the basis of value of R. In this equation, the value of R is more than the value of R of the equation under Adding model. Ultimately, in the aggregate of sample firms in Metals, Alloys Metal Products & Structurals Industry, the above five explanatory variables appear to influence the investment in Plant and Machinery. V CONCLUSIONS The Summary of the analysis is presented in the tables the following conclusions are drawn.. The major finding of the study is that, the elimination model is the most appropriate model in determining the behavior of investment in total fixed assets & plant and machinery separately.. The results of this analysis suggest that gross internal funds (retained earnings + depreciation) are more important for the fixed investment in almost all the companies in the present study.. Change in sales (growth rate in sales), stock of net liquidity, debt outstanding dividends are also significant determinants of fixed investment.. Provision for taxes and Interest on borrowed funds are also significant factors in Metals, Alloys, Metal Products and Structurals.. The study reveals that demand considerations in the longrun are of some importance in the entrepreneurial fixed investment decisions. Financial considerations seem to dominate over demand factors in fixed investment decisions.. The implication of the results of the present study is that profitability is an important consideration in entrepreneurial investment decisions. Profits influence dividend policies and hence retained earnings. Retained earnings in turn influence investment. Profits influence dividends and dividends influence the flow of external finance. External finance in turn exerts its influence on investment. Thus profits both directly and indirectly influence investment, directly through retained earnings and indirectly through external finance. 7. As retained earnings is an important factor in the determination of investment, it is important to see that higher profitability is not dissipated through dividend disbursals. As self financing is non-inflationary, it may be desirable to encourage asset expansion through internal savings rather than through borrowings. REFERENCES [] Meyer, J., and Kuh, E., The Investment Decision, Harvard, 97. [] Kuh, E., Capital Stock Growth: A Micro Econometric Approach, North Holland Publishing Company, 9. [] Krishna, K.L., and Krishnamurthy, K., Investment Functions for the Corporate Sector, Towards An Econometric Model of Indian Economy Part III, Report submitted to ICSSR, 97 (Mimeo). [] Krishnamurthy, K.,Investment and Financing in the Corporate Sector in and Sastry, D.U., India, Tata McGraw Hill, Bombay, 97. [] C. J. Misra G.D., Investment, Financing and Earnings in the Corporate Sector in India, Allahabad, Kitabmahal, 9. [] Prem Kumar., Growth of Industrial Corporations in India Structure, Strategy, Determinants, Chandigarh: Deep& Deep Publications, 9. [7] Prasant Kumar Sahoo., Sources of Finance for Indian Corporate Sector, Berhampur; Deep & Deep Publications, 9. [] Ranganadhan, M, & Madhumathi R., Market Price as an Influence of Investment Decisions, Finance India, March 99. [9] R. Ashim Lal Chakraborthy, Fixed Assets Acquisition & Their Management A Mrs. Sadhna Srivastava., Case Study, Journal of Accounting & Finance, [0] Bonton E. Gup., The financial Consequences of Corporate Growth; The Journal of Finance, Dec., 90. [] Gompers, Paul A., Optimal Investment, Monitoring & the Stagging of Venture Capital, Journal of Finance, December 99. [] Jorgenson, D.W., The Theory of Investment Behaviour in determinants of Investement Behaviour, NBER, 97. S.L.Tulasi Devi has received Bachelor s Degree in Commerce in 9 and Masters in Commerce in 99, M.Phil in Commerce in 99 and Doctorate in Commerce in 00. She was received Bachelor s Degree in Law in 997, and Masters in Business Administration in 009 in Finance. She is presently associated with the School of Management, National Institute of Technology, Warangal, India. Earlier she was associated with GITAM University, Visakhapatnam, India and GMR Institute of Technology, Rajam, A.P., India as Associate Professor. Her interesting areas are Finance and Econometrics. Dr. S.L.Tulasi Devi is the member of American Finance Association and Eastern Finance Association. Prof. V.V.L.Narasimha Rao has received his Bachelor s Degree in Commerce in 97. Subsequently he received Masters in Commerce in 97, and Doctorate in Commerce in 9. He was associated as Lecturer from 979, as Reader from 9 and as Professor from 99 with the Aacharya Nagarjuna University, Guntur,A.P., India. Dr.V.V.L.Narasimha Rao was the Chairman, Board of Studies and Acadsemic Adviser, MBA Distance Learning Programme, Aacharya Nagarjuna University, Guntur, A.P.,India. He is the founder Head and Coordinator for the Department of Tourism and Hospitality Management.