Factors Influencing Investment Behaviour of Indian Firms in a Contemporray Risky Scenario

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1 Factors Influencing Investment Behaviour of Indian Firms in a Contemporray Risky Scenario Pankaj Kumar Gupta, Jasj Bhatia 1 Abstract Formulating optimal investment strategies of the firm comprises of one of the most important decisions in corporate finance especially in the contemporary risky scenario after the global turmoil. The impact of these decisions is long-term and therefore, firms have to ensure the optimal allocation of capal to the right investment projects. This motivates us to explore the factors that influence the investment behaviour of firms. In view of the current uncertain environment, the tradional models that explain the firm s propensy to invest have lost importance. Our paper proposes to explore the linkage between firm specific financial parameters and investment decisions for top companies in India for the period of The specific aspects of the investment behaviour are analysed wh respect to the cash flows, cash holdings, dividend payout ratio, age, size and leverage characteristics of the firms to empirically examine the factors the study uses a Panel Regression methodology considering both fixed and random effects models. Key words Panel Regression, Granger Causaly, Firm specific financial variables, Investment Behaviour JEL Classification: C22,G14,G32 1. Introduction In the current uncertain scenario, investment decisions by business firms are becoming extremely difficult and complex exerting a strong negative influence on future investments. Firm specific financial parameters incorporate these impacts in one or other form. The decision to acquire fixed capal is crucially influenced by expectations about events that impact the future cash flows. Various investment theories and models developed in the lerature consent to the view that a business firm is portfolio of projects striving to maximize the value around three major financial decisions namely investment, financing and prof disbursement. Modigliani and Miller (1958) show that under the perfect and complete market assumptions, a firm s investment decisions are independent from the financing sources. However, firm s rate of investments is constrained by the supply of funds (Meyer and Glauber, 1964). Firms' investment decision-making in relation to risk propensy is largely affected by future performance and liquidy constraints (Lin et al 2012). Capal market frictions like agency costs, information asymmetry, and transaction costs favors funding of future investment from internal sources in an attempt to reduce the financing costs (Jenson and Meckling, 1976; Stiglz and Weiss, 1981; Myers and Majluf, 1984). Liquidy theory also suggests that financing through external funds could become a strain on the firm s investment, thus implying large dependence on internal funds for making investments. 1 Dr. Pankaj Kumar Gupta, Associate Professor, Centre for Management Studies, Jamia Millia Islamia, New Delhi (India); pkg123@eth.net. Jasj Bhatia Assistant Professor, Symbiosis Centre for Management Studies, Noida, (India); jasj.bhatia@yahoo.com 357

2 Chen and Kensinger (1988) argue that managers holding substantial stakes in their firms may face severe consequences if the firm fails that accentuate managers to avoid risky ventures, which might be desirable for outside shareholders implying agency conflicts. Monsen et al. (1968) establish that owner controlled firms outperform the manager controlled firms by a considerable margin. Pawlina and Renneboog (2005) establish that outside block holders influence firms investment policies and the types of outside block holders determine the diversified abilies and motivations to monor management and influence firms investments. Fazzari et.al. (1988) classify into three groups based on the severy of their financial constraints using the dividend paying capacy as a classifier. Kaplan and Zingales (1997) show that an increase in the investment/cash flow sensivy is not necessarily an increase in the degree of financial constraints. Cleary (1999) suggest that investments of large firms and firms wh high payout ratios have higher sensivy to internal funds than small firms and firms wh lower payout ratios. Liquidy constraints in investment decision making arising out of asymmetric information and agency costs have been investigated by Vogt (1994) who use the payout ratio and firm size as proxies for both asymmetric information and agency costs problems and deploy the equilibrium level of Tobin s Q approach. Tobin s Q ratio (Tobin and Brainard (1977) is measured as the ratio of the firm s market value to the book value of s asset. The accelerator theory of investment says that firms have a preferred level of assets to be acquired and they undertake investments to reach to that preferred level. Tobin s q theory of investment says that the excess of market valuation over replacement cost encourages investment, that is, investment will be undertaken if market value is greater than book value on the assumption of perfect capal market. Aggarwal and Zong (2006) study of largest industrialized countries provide evidence of the existence of financial constraints in an international environment and establish that investment levels are related to cash flow in varying degrees. Studies in India have contributions from Rajakumar (2005) who analyzed the relationship between investment behavior and the financing patterns of Indian firms for the period to The firms in the study were segregated according to the mode of financing and the results for the relationship between debt equy ratio and investment at the aggregate level reported a posive correlation coefficient, thus suggesting higher the debt, greater the investment. A recent study by Reserve Bank of India (2010) looks at the determinants of private corporate investment in India from to and report that firm specific factors like firm size, debt to asset ratio, cash flow ratio and growth in value of production are posively associated whereas, dividend payout ratio and effective cost of borrowing are negatively associated wh investment of the firm. It can, therefore, be seen that the firm s investment behaviour is determined by a large number of factors that include the availabily of capal, market valuations, future cash flow generation capabilies and Liquidy assurance. On the behavioural side, the management stake, promoter s profile and risk capabilies, public posture of firm etc. exert influence on investment behaviour of firms. In the current uncertain business environment a period before and after the global financial turmoil motivates us to examine the investment behaviour of firms and determine the factors that need careful consideration the investment decisionmaking. 2. Methodology In order to determine the factors influencing the behaviour of Indian firms, we use a panel regression model assuming a linear relationship between the investment and the various firm financial parameters based on reported financial statements. The panel regression model based 358

3 specification proposed by Gujarati (2006) uses a dependent variable, which in our case is Y representing the firm s investment wh a constant β β 1 and as regressors. Y = β + β X β X + µ k k Where firm ( i) = 1,2,3,..., k and time period( t) = 1,2,3,..., n µ i is a random error term denoting firm specific effects. i = 1, 2,..., k and t = 1, 2, 3,..., n, µi -firm specific effects, The explanatory variables are firm size (Total Assets; TA), Years of Incorporation (Age), Dividend Payout Ratio (DP), Leverage (Debt to Total Assets; DA), and Cash Flows (CASHFLOW) during the year. We conducted un root test to examine the stationary of the series based on Augmented Dickey-Fuller and PP specifications. We also conduct a Granger causaly test to examine the relationship between the Cash flow and Investment and another simple set of regression between the Investment and Dividend payouts. We first use a generic estimator first to find the co-efficient of the regressors and then proceed to find the impact of fixed effects (FE) and random effects (RE) in the cross sections. We can test whether a fixed or random effects model is appropriate using a Hausman test X where Z and as instruments yields a consistent estimate. H 0 : α i X, Z H ; a : α i X, Z H Λ, If o is true, both β and Λ RE β FE are consistent, but Λ only β H RE is efficient. If a is true, β RE is consistent and β FE is not. Λ We have used the Capaline database on listed firms that are part of the BSE 100 Index that consists of the top companies in India as per market capalization. From the inial sample we have excluded all those firms for whom observations are not available for any variable included in the model during the sample period. The period under consideration is 3 years before the global financial crisis that is from April 2004 to March 2007 and five years after the crisis period that is from April 2007 to March The description of dependent and independent variables is as follows: - Investments-Investment is an endogenous variable representing the changes in the level of gross fixed assets normalised to account for the difference between firms. Total Debt to Total assets Ratio represent the debt posion of the company. It determines the percentage of a company s assets wh respect to the total assets of the firm. Impact of financial leverage on investment decisions of the firm is measures by this ratio. Age- Presence of the firm in market place impacts the borrowing capabily and also the risk taking capabily. The age of the firm for respective years is calculated from the date of incorporation. Cash flows and Cash Holdings - Cash flow and cash holdings are an important determinant influencing investment decisions. If firms have enough cash inflows can be utilized in investment activies. A relation between cash and investment will also provide evidence that investment is related to the availabily of internal funds, which has been an area of research. We use two measures of cash holdings: - 1. Cash flows of the current year- measured by the ratio of Cash Flow to Assets Cash Flow are the sum of earnings before interest, tax and depreciation. 2. Cash holdings- measured as Cash to total assets, which corresponds to the ratio of cash and equivalents to total assets. Dividend payout ratio - Dividend payout ratio is a good indicator of whether a firm has internal funds. Fazzari et. al (1988) have classified firms paying low dividends as classified as 359 Λ

4 financially constrained and those paying high dividends classified as financially unconstrained. Hence this ratio can be used as the proxy for the severy of external financing constraints. Firm Size-The size of the firm will be considered to see whether there are any significant differences in investment behavior of large firms vis-à-vis small and medium size firms. As large firms have better access to the capal markets we expect greater responsiveness towards investment opportunies for these firms. We take natural log of the reported Total Assets. 3. Results Te Leverage and payout ratios have declined after the global financial crisis (Table 1). It can be seen that dividend payout in 2010 and 2012 have improved a b in tandem wh the economy but slipped in 2012 following the Euro zone crisis and declining profs due to poor exports. It is seen that the companies shave been trying to reduce the debt levels after the period of crisis because of galloping debt costs and service related problems raising doubts on liquidy. Since the sample set represents the top companies on the bourses, the impact of the risky scenario is visible on the future investments. Table 1: Financial ratios of Sample Companies during Ratio Debt to Mean Total S.D. Assets Ratio Dividend Payout Ratio Mean S.D We have conducted the panel un root analysis of the dependent and independent variables at 5% significance level (Table 4). Results indicate that the null hypothesis is rejected of all the measures for all processed variables. This allows us to proceed for direct regression estimates whout modifications. Granger casualty results in Table 5 indicate a strong causation between the Investment and cash flow, which support the earlier studies (Christopher, 2010). We first run the panel regression wh None Effects and estimate the coefficients (Table 1). It is observed that all the co-efficient are significant at 5% level wh relatively higher standard error for DARATIO (Table 2). We further estimate the coefficients wh fixed effects and random effects. Table 2: Panel Regression Coefficients-None and Fixed Independent Variables None Effect Coefficient Fixed Effects Coefficient AGE CASHFLOW DARATIO DP TA In order to proceed for selection between the fixed and random effects we use the Hausman (1968) test specifications. The computed Hausman statistic in our regression model is indicated that null hypothesis cannot be rejected at 5% level of significance (Table 7). We 360

5 therefore use random effects model in our analysis. Table 3 shows the observed coefficients. P-value of CASHFLOW, DARATIO and TA indicate that these variables are important in determining the investment behaviour of Indian firms especially in the risk environment postulated by the crisis. Dividend payout is negatively associated wh investment, which is obvious, but is not statistically significant. Table 3: Panel Regression Coefficients-Random Effects Random Effects Standard Error P-value Independent Variables Coefficient AGE CASHFLOW DARATIO DP TA Contrary to the earlier researches worldwide dividend do play an important role in deciding the investment to be made by the firm and conventional theories stating that dividend payments reduces the cash flow, the dividend payment are losing importance. Another aspect of DP ratio is that role of internal funds in financing of future investment is loosely defined. Interestingly the debt to assets ratio is negatively associated wh investment though statistically significant. This may be indicated the importance of debt in the capal structure though the debt costs are serially increasing over time periods. The size of the firm emerged as an important variable in investment by firms. Logically this indicates that firms have grown over a period of time and the propensy to invest depends upon the investment makes in total assets. We also find that age of the organisation is not important in investment decisionmaking oppose to the notion that older firms are more prone to newer investments. In fact the older organisation has extensively used the real options to defer their projects because of sliding demand worldwide. 4. Summary In this paper we explore the factors affecting the investment patters of Indian firms using a panel regression model run on 67 firms representing top market capalisation on Indian stock exchanges. The issue of investment hinges around the considerations of leverage, cash flow generation power and liquidy constraints affecting the value maximisation process. It is observed that Indian firms that expanded in size developed the propensy to invest vis-à-vis the risky environmental forces. In developing countries like India investments are imperative to development in terms of contribution to GDP and employment. Results on cash flow clearly indicate that once the business model Indian firm is perceived to be robust primarily because of assured and alternative domestic demand, the financing appears to be unimportant constraint. Our paper also supports the irrelevance of dividends in investment decision making for the selected period. 361

6 Table 4: Un Root Tests Panel un root test: Summary Series: CASHFLOW Date: 08/19/12 Time: 13:15 Exogenous variables: Individual effects Automatic selection of maximum lags Automatic lag length selection based on SIC: 0 to 1 Newey-West automatic bandwidth selection and Bartlett kernel Cross- Method Statistic Prob.** sections Obs Null: Un root (assumes common un root process) Levin, Lin & Chu t* Null: Un root (assumes individual un root process) Im, Pesaran and Shin W-stat ADF - Fisher Chi-square PP - Fisher Chi-square ** Probabilies for Fisher tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normaly. Panel un root test: Summary Series: INVESTMENT Date: 08/19/12 Time: 13:16 Exogenous variables: Individual effects Automatic selection of maximum lags Automatic lag length selection based on SIC: 0 to 1 Newey-West automatic bandwidth selection and Bartlett kernel Cross- Method Statistic Prob.** sections Obs Null: Un root (assumes common un root process) Levin, Lin & Chu t* Null: Un root (assumes individual un root process) Im, Pesaran and Shin W-stat ADF - Fisher Chi-square PP - Fisher Chi-square ** Probabilies for Fisher tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normaly. Panel un root test: Summary Series: DP Date: 08/19/12 Time: 13:16 Exogenous variables: Individual effects Automatic selection of maximum lags Automatic lag length selection based on SIC: 0 to 1 Newey-West automatic bandwidth selection and Bartlett kernel Cross- Method Statistic Prob.** sections Obs Null: Un root (assumes common un root process) Levin, Lin & Chu t*

7 Null: Un root (assumes individual un root process) Im, Pesaran and Shin W-stat ADF - Fisher Chi-square PP - Fisher Chi-square ** Probabilies for Fisher tests are computed using an asymptotic Chi -square distribution. All other tests assume asymptotic normaly. Panel un root test: Summary Series: DARATIO Date: 08/19/12 Time: 13:17 Exogenous variables: Individual effects Automatic selection of maximum lags Automatic lag length selection based on SIC: 0 to 1 Newey-West automatic bandwidth selection and Bartlett kernel Cross- Method Statistic Prob.** sections Obs Null: Un root (assumes common un root process) Levin, Lin & Chu t* Null: Un root (assumes individual un root process) Im, Pesaran and Shin W-stat ADF - Fisher Chi-square PP - Fisher Chi-square ** Probabilies for Fisher tests are computed using an asymptotic Chi -square distribution. All other tests assume asymptotic normaly. Table 5: Granger Causaly Tests Pairwise Granger Causaly Tests Date: 08/19/12 Time: 13:19 Lags: 2 Null Hypothesis: Obs F-Statistic Prob. CASHFLOW does not Granger Cause INVESTMENT E-09 INVESTMENT does not Granger Cause CASHFLOW E-05 Dependent Variable: INVESTMENT Method: Panel Least Squares Date: 08/19/12 Time: 13:20 Periods included: 9 Cross-sections included: 67 Total panel (balanced) observations: 603 Variable Coefficient Std. Error t-statistic Prob. DP R-squared Mean dependent var Adjusted R-squared S.D. dependent var

8 S.E. of regression Akaike info crerion Sum squared resid Schwarz crerion Log likelihood Hannan-Quinn crer Durbin-Watson stat Table 6: Panel Regression Results None Effects Dependent Variable: INVESTMENT Method: Panel Least Squares Date: 08/19/12 Time: 13:11 Periods included: 9 Cross-sections included: 67 Total panel (balanced) observations: 603 Variable Coefficient Std. Error t-statistic Prob. AGE CASHFLOW DARATIO DP TA R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info crerion Sum squared resid Schwarz crerion Log likelihood Hannan-Quinn crer Durbin-Watson stat Fixed Effects Dependent Variable: INVESTMENT Method: Panel Least Squares Date: 08/19/12 Time: 13:10 Periods included: 9 Cross-sections included: 67 Total panel (balanced) observations: 603 Variable Coefficient Std. Error t-statistic Prob. C AGE CASHFLOW DARATIO DP TA Cross-section fixed (dummy variables) Effects Specification R-squared Mean dependent var Adjusted R-squared S.D. dependent var

9 S.E. of regression Akaike info crerion Sum squared resid Schwarz crerion Log likelihood Hannan-Quinn crer F-statistic Durbin-Watson stat Prob(F-statistic) Random Effects Dependent Variable: INVESTMENT Method: Panel EGLS (Cross-section random effects) Date: 08/19/12 Time: 13:12 Periods included: 9 Cross-sections included: 67 Total panel (balanced) observations: 603 Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-statistic Prob. C AGE CASHFLOW DARATIO DP TA Effects Specification S.D. Rho Cross-section random Idiosyncratic random Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Unweighted Statistics R-squared Mean dependent var Sum squared resid Durbin-Watson stat References [1] Aggarwal, R., Zong, S., The cash flow investment relationship: international evidence of limed access to external finance. Journal of Multinational Financial Management 16, p [2] Cleary, S. 1999, The Relationship between Firm Investment and Financial Status, The Journal of Finance, Vol. 54(2), p [3] Fazzari, S., Hubbard, R.G. and Petersen, B. 1988, Financing Constraints and Corporate Investment, Brookings Papers on Economic Activy, p

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