Panel data Procedure

Panel character of data allows for the use of panel data methodology. The process of estimation of equation will be the Panel Two Stage Least squares. Panel data sets possess several major advantages over conventional cross-sectional or time-series data sets (e.g., Hsiao (1985a, 1995, 2000). Panel data usually give the researcher a larger number of data points which increase the degree of freedom and reduce the collinearity among the explanatory variables thus improve the efficiency of econometric estimate. This approach is more useful than either cross section or time series alone89.

The coefficient on the independent intercept (α0) can vary across companies and over time. The simplest model is to pool the data in which case there is one fixed intercept. It is unlikely that the profitability models are fully specified. For example there are no available proxies for factors like the magnitude of distress costs or industry effects that are important to the profitability. Moreover the data is unbalanced, as the number of observations for each

89 _{As this study collect data from SMEs the availability of data for the whole period of study is not fulfilled. So it}

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company is different. Thus, a simple pooling might not result in either efficient or unbiased estimates. The fixed effect model allows us to use the data, while the intercept is allowed to vary across firms and time. The effects of omitted explanatory variables can be captured in the changing company intercept. In addition to that by including a fixed time effect the model automatically assess the impact of the macro environment on profitability.

Model estimation using panel data requires first to determine whether there is a correlation between the unobservable heterogeneity of each firm and other control variables of the model. We would obtain the consistent estimation by means of the within–group estimator, if there is a correlation (fixed effects). If not,(random effect) the more efficient estimator can be achieved by estimating the equation through Generalized Least Squares(GLS).

Using the Hausman(1978) test it can be determined whether the effects are fixed or random under the null hypothesis90 E(ηi/Xit). Here Xit is all other regressors.

90

If the null hypothesis is rejected the effects are considered to be fixed. The model can be estimated by OLS. Accepting null hypothesis would mean to have random effects and the model have to be estimated by GLS. More efficient estimator of β we achieve in this way.

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The basic model can be written as,

Yit = αi+ Σ βk Xk,it +λt +ηi+ ε i,t (5.1)

Fixed effect model allows different intercepts for each individual firm and firm specific effects are assumed constant over time (αi is firm specific constant term).

It is assumed here that the slope and intercept coefficients are the same across the firm and time (See Baltagi,2001; Gujarati, 2004). So OLS provides consistent and efficient estimates of α and βk where the above equation (5.1) be converted into;

Yit = α + Σ βk Xk,it +λt +ηi+ ε i,t (5.2)

α is the overall constant for all firms.

By performing the F- test we could test the joint significant of dummies. i.e. H0: µ1 = µ2 =…

=µN-1 =0 by performing an F- test91.

We measure the effect of capital structure on profitability. The model for the empirical investigation can be stated as follows.

ROAi,t = α0 + α1 LIQUIDITYRATIOi,t + α2 LOGSIZE i,t + α3 GEARINGRATIO i,t +

α4 STDTD i,t + α5SALESGR i,t +λt +ηi +ε i,t (5.3)

Where the subscript i denotes the cross section, i= 1,2…n and t denotes the time t=1,2…n. ROAi,t is return on assets of firm i in time t, LIQUIDITYRATIO i,t is liquidity of firm i in

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time t, LOGSIZE i,t is sales or total assets of firm i in time t, GEARINGRATIO i,t is the financial leverage of firm i in time t, STDTD i,t is the short term debt as a ratio of total debt of firm i in time t and SALESGR i,t is the sales growth of firm i in time t. The parameter λt is a time dummy variable to pick up aggregate factors which influence profitability, although does not allow variation across firms, ηi the unobservable heterogeneity of each firm and εi,t measures the random disturbance. Like Krishnan and Moyer (1997) we also use two proxies to measure profitability92.

An alternative model for equation 5.3 can be written as follows with the proxy of the dependent variable.

ROCEi,t = α0 + α1 LIQUIDITYRATIOi,t + α2 LOGSIZEi,t + α3 GEARINGRATIOi,t +

α4 STDTDi,t + α5SALESGRi,t +λt +ηi +ε i,t (5.4)

Where all variables are defined as above excluding the dependent variable, ROCEi,t. ROCEi,t

is the return on capital employed of firm i in time t.

5.5 Theoretical predictions

The following predictions have summarized based on the trade off theory, pecking order theory, agency theory and the previous empirical studies to capture the impact of other variables on profitability.

92 _{See appendix 5A for detailed variable definition and descriptive statistics are included in Table 4.2. ROA}

shows how well the management is employing the company’s total assets to make a profit and ROCE provide more comprehensive evaluation of how well management is using the debt and equity it has at its disposal.

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5.5.1 Profitability.

The pecking order theory of Myers (1984) Myers and Majluf(1984), and Shyam-Sunder and Myers(1999) suggest firms prefer to finance investment first from retained earnings, second from debt and third from equity. More profitable firms should have lower leverage ratio than less profitable firms as they are able to finance their investment opportunities with the retained earnings according to the theory. Moreover the theory says that leverage has a negative effect on the firm profitability. This idea is strengthen by Gleason et al (2000), Arbor (2005) and Arbor (2007) more profitable firms tend to use earnings to pay debt and therefore they would have a lower leverage than less profitable firms.

In this study two profitability measures are used in which one indicate the firm management use total assets to make profit and other indicates how well management use the debt and equity capital to enhance the firm profitability. The profitability is measured using the Return On Assets (ROA) (Abor,2007;Arcas and Bachiller, 2008;Goddard et al,2005) and return on capital employed (ROCE)(Krishnan and Moyer,1997).