Fixed and random effect models have been used to analyze the impact of firm-specific determinants on a firm’s leverage
Analyze the effect of firm-specific determinants on the capital structure of the firm panel data analysis is employed.
Panel data analysis is used to analyse of impact of determinants that are firm specific. It is always preferable to choose panel data analysis over the cross section and time series analysis. Unlike cross sectional and the time series analysis, better results with the use of small data size are offered by panel data analysis. This is the reason why all the cross sectional observations that are collected over a period of time are combined leading to increase in number of observations. Employment of this technique is considered more efficient as it reduces the co-linearity of the predictor variables and also it offers gain in terms of freedom. It provides more reliable parameters by reducing the interaction among all the variables. It uses the data that is both time dimensional and cross section dimensional. The research study uses both the panel data methods i.e. fixed effect method and the random effect method. The better method is then selected applying the Hausman test. Both the models have been represented through the following equations respectively:
DRjt = β0j + β1TANGjt + β2PROFjt + β3SIZEjt + β4GROjt + β5LIQjt + β6NDTSjt + μjt
DRjt = β0 + β1TANGjt + β2PROFjt + β3SIZEjt?+ β4GROjt + β5LIQjt + β6NDTSjt + ?jt + μjt
Where,
DRjt= measure of firm’s leverage in year t
β0= common y intercept
TANG, PROF, SIZE, GRO, LIQ and NDTS= represents the determinants of leverage that are firm specific.
?jt = stochastic error term for firm j at time t
β0j= firm j’s y intercept
μjt= error term for firm j at time t.
β1 to β6= coefficients of explanatory variables
Various empirical findings and other estimation results have been covered in this section. The fixed effect model is run for 61 companies on data panel and then random effect model is run using the reviews of former model. The outcome of both methods is shown in Table 2.
As per fixed effect method, among all the variables that have been considered for this study, the rate of growth of total assets, PROF and LIQ, company’s size and TANG of assets are key determinants of the firm’s capital structure at 5%. Whereas only 4 among the said 5 variables are considered as significant by the random effect model.
To select one from both the models, Hausman test is conducted. This test helps by selecting a model that is more efficient by making proper comparisons of fixed and random effects. All the outcomes of this test are shown in Table 3. For the null hypothesis of the test, the method that is preferred is random effects, whereas for the alternative hypothesis, the model that is preferred is fixed effects.
The above results shows that fixed effect model must be used as the probability 0.0153 is less than 0.05. As Hausman test has resulted in selection of fixed effect model, the further analysis will be undertaken on the basis of this model. In the current study, the most dominant capital structure’s determinant is PROF with the value of -0.621 as its coefficient. This implies that PROF and Leverage are negatively related to each other. This relationship, therefore, supports the pecking order theory. The results of the test are also consistent with various other studies such as: Titman & Wessels (1988), Harris & Raviv (1991), Rajan & Zingales (1995), Booth et al., (2001), Qiu and La (2010), Genimakis & Noulas (2011), Bayrakdarog?lu et al. (2013).
Comparison of fixed and random effect models using the Hausman test
The second most dominant capital structure’s determinant of the study is found as TANG in Oman. TANG of assets of the firm holds negative relationship with the capital structure of firms of Oman. On a theoretical basis, results of the test are in consistence with agency theory. The negative relationship of tangible asset’s proportion and the firm’s leverage is predicted by agency model. However, the results of the test are in contradiction with the theory of pecking order and trade-off. The logic behind the negative relationship between the two can be explained as: the firms with more fixed assets has greater potential of earning profit and hence they rely more on the internal financing. The overall results are in consistence with Cornelli et al. (1996), Booth et al (2001), Huang & Song (2002), Nivorozhkin (2002), Sbeiti (2010), Smith (2012), Bayrakdarog?lu et al. (2013). Since, all these cases holds the fact that leverage and TANG are negatively related.
Size is also one among the key determinant of the capital structure of companies of Oman. The relationship between the size of the firm and its capital structure is in consistence with the pecking order theory as well as theory of trade-offs that proves the positive relationship between the size and leverage of the firm. These results are consistent with the results of many such as Jin Xu (2012), Gaud et al., (2005) and Graham et al., (1998). As per Graham et al., (1998), the large size of firm enables them to negotiate in smoother way and due to this they have access to cheap debt market.
The relationship between the company’s growth rate and its leverage is also positive and it is significant enough for the companies. The findings of the present study supports the theory of pecking order and the idea pursued by it i.e. the firms with high growth potential prefers debt financing over equity financing in the situations where internal funds are insufficient. The outcome of current study also supports the results of Jensen (1986) for the agency costs theory. This theory suggests that firm’s with higher growth potential generally have high leverage in order to minimise the agency costs between the company’s managers and its shareholders since debt capital is normally used to control the managers. The results are in consistence with Bevan and Danbolt (2001), Sayilgan et al. (2006), Ameer (2013) who observed positive relationship between the firm’s growth and leverage.
Yet another key independent variable of the present study is LIQ, which holds negative relationship with the leverage. The current study in this relation is in support of pecking order theory which predicts negative relationship between the LIQ and leverage. The negative relation of the two confirms the fact that the firms with higher LIQ in Oman prefers the use of internal funding rather than relying on the external financing in the form of debt. However, the trade-off theory argues that the companies with higher LIQ can easily opt for debt financing since it is easy for those companies to pay off the interest expenses on timely basis (Abdul Jamal et al., 2013). In the current literature authors like Deesomsak et al. (2004), Mat Kila and Wan Mansor (2008), Sbeiti (2010), and Hossain and Ali (2012) have experienced the same results for LIQ.
Conclusion:
The above study was attempted to determine and evaluate the key determinants of firm’s capital structure. The data of 61 non-financing companies that are listed on Muscat Securities Exchange from the year 2011 to 2015 has been analysed. The analysis is undertaken using various panel data techniques such as fixed effects approach and random effects approach. The entire study has assumed the debt ratio to be a dependent variable. As a result of empirical analysis it is found that PROF, TANG and LIQ holds negative relationship with the leverage of the company. The results are in line with the results of studies carried by Hossain and Ali (2012) in Bangladesh, Sbeiti (2010) for the study carried on GCC firms and Qiu and La (2010) for the study carried on Australian companies. The results in relation to PROF and LIQ are in line with the theory of pecking order. Whereas, the variable TANG has offered contrary results from the theory of trade off and order pecking. However, it is consistent with results of agency model.
It can be concluded that the size of the firm and its growth potential are positively related to the firm’s leverage in Oman. This finding of the research is consistent with the study conducted on Brazilian firm. The relationship between the two depicted by the study is in line with the theory of trade-off. Whereas, the findings of the study in context of growth rate is in support of order pecking theory and its idea that firms with higher growth rate prefers debt financing instead of equity financing. Further, the negative impact of LIQ on firm’s debt ratio implies that if a firm has high LIQ ratio, it will tend to opt for low leverage since they are able to generate sufficient cash inflows that can be deployed in further investment. This connection of LIQ and leverage confirms the theory of order pecking. The research findings are in line with the studies conducted by Viviani (2008), Wang & Sheikh (2011), and Abdullah (2005).
As against the expectations, NDTS has proved to be an insignificant variable for the firms that have been selected in this study for the analysis. However, NDTS is an important determinant of capital structure of the firms in Arab economies with the non-tax structure. But, for the companies operating in the countries which have adequate tax system NDTS is irrelevant determinant (Barakat and Rao, 2003).
From the above study it can be concluded that theory of pecking order is fair enough to explain the significance of determinants of capital structure for Oman firms. Therefore, implementation of the said theory would be more appropriate in Oman. However, at the same time, the theories of trade-offs and agency cost must not be ignored completely as these theories also indicates positive relation for size variable and negative for TANG. The finance managers are therefore recommended to consider all the benchmarks in their decision making process in the area of capital structure.
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