Financial Sector Across the Eurozone - Research Paper Example

Financial ratios and Firm Profitability in the Eurozone The work contributes to the literature seeking to determine the relation between financial ratios and firm profitability. The work created a regression model using the knowledge contributed by earlier studies. Based on the regression model and its empirical implementation in a multiple regression, there is a good basis to argue that debt/common equity, total common equity to total assets, and average equity to average assets significantly affect firm profitability. Financial ratios and Firm Profitability in the Eurozone I. Introduction The relationship between financial accounting ratios and firm profitability has been studied in the literature but past and current studies on them are far from satisfactory. This is because the direction of relationship between the financial ratios and firm profitability has not been adequately established. Some of the studies indicate that certain financial ratios are positively correlated with firm profitability; other studies, however, show the contrary and contradict earlier studies. This mean s that studies on the subject must be sustained until a more satisfactory set of results are obtained or consistent results are obtained from a large number of studies on the subject. The failure to get consistent results from the relationship between financial ratios and firm profitability can also indicate that regression strategies on how to conduct the regression must be refined. Meanwhile, in 2007 or 2008, a financial crisis in the United States erupted and affected Europe. It is interesting to take a look at the latest data and find out how the crisis may have affected Europe even as we remain focused on studying the relationship between the financial ratios and firm profitability. II. Review of Literature As pointed out earlier, the direction of relationship between financial ratios and firm profitability are reported inconsistently in the latest studies although the studies have been indicating what variables are most important in affecting firm profitability. Martani et al. (2009) investigated the effect of financial ratios, firm size, and cash flow on the stock return. The authors used a sample of listed companies in the Indonesian Stock Market covering 780 observations. They found net profit margin, return on equity, and several other financial rations have a positive effects on market adjusted returns. At the same time, ratios such as credit ratio, total assets turnover ratio, and other financial ratios are negatively correlated with the market adjusted returns from firms. In general, what Martani et al. (2009) have found is that the correlation between financial ratios and their correlation with market adjusted returns are inconsistent with expectations and their hypothesis. Nevertheless, their results did not prevent Martani et al. from concluding that a higher return on equity can earn higher return on stockholder’s equity. Martani et al. (2009) also found that their regression suggests that that total assets turnover has negative correlation with return, contradicting expectations and their hypothesis. The authors reasoned that the “result of negative correlation of TATO on return might be caused by big firm’s domination on high stock return, whereas big firms usually cannot increase their TATO” or their total assets turnover easily (Martani et al. 2009, pp. 50-51). They added that “another factor that caused negative relation is that stock return is also affected by non operating profit which is not gained from sales” (Martani et al. 2009, p. 51). Singapurwoko and El-Wahid (2011) investigated the impact of financial leveraging to the profitability of non-financial companies listed in the Indonesia Stock Exchange and found that debt, total assets turnover, firm size, and type of industry positively affect profitability. However, contrary to their expectations and hypothesis, the regression results they obtained indicated that the Bank of Indonesia interest rate positively affected firm profitability. The Singapurwoko and El-Wahid (2011) view that that the Bank of Indonesia interest rate would negatively affect company profitability was not empirically supported by their own regressions. Singapurwoko and El-Wahid used a sample of 228 companies in the Indonesian Stock Exchange and their data fro 2003 to 2009. Comparing their results with the work of Harjanti and Tandelilin in 2007, Singapurpwoko and El-Wahid pointed out that their finding that leveraging positively affect profitability contradicted the finding of Harjanti and Tandalilin study of 2007 that obtained evidence that leverage is negatively correlated with profitability. In an attempt to reconcile that showed inconsistent correlations between firm debt and profitability, Singapurwoko and El-Wahid offered the view that the conflicting results can be interpreted to mean that debt significantly affect firm profitability, whether or not the correlation between the two is positive or negative. The authors interpreted the view to extend also to leveraging: leverage significantly affect firm profitability, whether the correlation is positive or negative. Turkmen and Demiral (2012) studied the economic factors affecting financial ratios and chose 13 real estate companies in the Istanbul Stock Exchange during the period 2007 to 20120. They interpreted their regression results to indicate that the consumer price index, benchmark interest rates and the exchange rate do not have significant effects on firm profits after tax/equity ratio. However, they concluded that total debt/net asset value, total debt/equity, acid-test ratio, net profit after tax/net asset value, net asset value per share/common stock price and the exchange rate have significant effects on net profit/equity ratios. It is very clear that although their regression results have the positive or negative signs, the authors chose to interpret their results in terms of the significance of the ratio in affecting the profitability of a firm. For them, it appears adequate to find out whether a financial ratio significantly affect firm profitability and the question of whether the effect is positive or negative is merely a secondary question. Taani and Banykhaled (2011) investigated the effect of financial ratios, firm size and cash flows on the Jordanian industrial sector. For their study, they obtain a sample of 50 companies in the Amman Stock Market and used multiple regressions using profitability, liquidity, debt to equity, market ratio, asset size and cash flow as independent variables and earning per share as the dependent variable. From their regressions, the Taani and Banykhaled (2011) concluded that market ratio, cash flow and leverage significantly affect earnings per share. According to Taani and Banykhaled (2011), “the variables which are consistently significant on earning per share are profitability ratio (ROE), market value ratio (PBV), cash flow from operating activities, and leverage ratio (DER).” The authors interpreted their results to indicate the importance of looking into and monitoring financial ratios for decision-making on investments (Taani and Banykhaled 2011). The authors also reported that the highest adjusted R2 they obtained from all of their regressions is only 42%, indicating that studies need not reflect a very high adjusted R2 in their regression results to make valid interpretations of statistical or regression results. Again, like the other studies, Taani and Banykhaled did not mind the signs of the coefficients of the independent variables in interpreting their results. It seems that for Taani and Banykahled, it suffices that a variable has been identified as significant variable affecting another variable or, at least, a variable or variables are identified as important variables to control. III. The Model Based on the foregoing, this work constructed a regression model based with firm profitability as the dependent variable and crisis, firm debt, ownership type, financial leverage, firm size, and number of employees as the independent variable. The basis for the regression model are the earlier studies which have identified the factors which affect firm profitability as well as standard knowledge on the relationship between the select variables and profitability. This work implemented a multiple regression on cross-sectional data as there are fewer problems in handling such data. For instance, in cross-sectional data, the problems of autocorrelation and other error errors associated with time series regression are avoided. Of course, it is possible that each observation is located in a particular environment that can either distort or affect fundamental relationships but the problem is also present in time series data and, if the sample is sufficiently large, the distortions presented by the specific location of each observation can be cancelled out by the sheer magnitude of the data set: for example, one environment of an observation may be exaggerating positively a relationship while another observation may be balancing the distortion out. IV. Methods and Data In implementing the regression model discussed in the earlier section, the multiple regression model will use the variables enumerated in Table 1. The variables enumerated in Table 1 were identified as among the financial variables that can affect the firm profitability. It is highly possible that multicollinearity among the independent variables is present. However, according to Woolridge (2003, p. 134), “there is not much we can do about this” as multicollinearity are usually present in all data. Gujarati (2004, p. 369-370) also pointed out that multicollinearity “is not a serious problem” so long as the objective of regressions are predictions and not precise estimation of parameters. However, as pointed out by Koop (2005, p. 100), “a multicollinearity problem reveals itself through low t-statistics” and so if the t-statistics of the more relevant variables are relatively high, then multicollinearity need not be considered a very big problem. Table 1. Definition of variables Variable Calculation Symbol Return on Common Equity ((Net Income – preferred dividends) / Average Total Common Equity) x 100 ROE Financial Leverage Average Total Assets / Average Total Common Equity) * FinLeverage Inflation Rate Inflation rate for country of domicile for 2010, calculated using HICP indices from Eurostat Inflation Debt/Common Equity Short Term Borrowings + Long Term Borrowings / Total Common Equity) x 100 Debt_Eq Ownership Type percentage of shares owned by central government AS OF NOVEMBER 2012 OwnType Debt/Total Assets (Short Term Borrowings + Long Term Borrowings / Total Assets) x 100 Debt_Ast Total Common Equity to Total Assets (Total Common Equity / Total Assets) x 100 CE_TotAst Total Capital Short term borrowings + Securities sold with Repo agreements + Long Term Borrowings +Preferred Equity + Minority Interest + Total Common Equity TotCap Market Capitalisation Total value of shares (No. of Shares x Share Price MktCap Number of employees Number of employees in firm Employees Average Equity / Average Asset Average Total Common Equity / Average Total Assets AvgEqty_AvgAst V. Results and Interpretation Implementation of the regression model discussed in the earlier section yielded the regression statistics in Table 2. Table 2 was computed using the latest version of Gretl, an econometric software. Table 2. Empirical Results with Return on Common Equity as Dependent Variable Variable Coefficient Std. Error t-ratio p-value Constant 8.22303 5.12304 1.605 0.1098 Financial Leverage 0.134373 0.125704 1.069 0.2862 Inflation Rate -211.060 158.373 -1.333 0.1839 Debt/Common Equity 0.0167065 0.00407975 -4.095 5.78e-05 *** Ownership Type -0.126311 0.0988177 -1.278 0.2024 Debt/Total Assets 0.159809 0.102212 1.564 0.1193 Total Common Equity to Total Assets 3.13246 0.309335 10.13 2.76e-020 *** Total Capital 3.71146e-011 2.34583e-011 1.582 0.1149 Market Capitalisation 2.75483e-010 6.13114e-010 0.4493 0.6536 Number of employees -0.000102893 0.000181036 -0.5684 0.5703 Average Equity / Average Asset -3.19085 0.305183 -10.46 2.59e-021 *** Adjusted R2 0.378597 F (10, 239) 14.56133 P-value (F) 4.07e-20 Some of the independent variables in Table 2 indicated a high correlation with the other independent variables. The correlations and their significance were computed but are not reported in this work. The correlation among some of our independent variables confirms that our regression equation has a multicollinearity problem. Nevertheless, so long as the aim is prediction rather than precise estimation of parameters, we can invoke Woolridge (2003) and Gujarati (2004) to argue that the regression is useful. VI. Conclusion This work affirms the findings of earlier studies that debt can negatively affect firm profitability. However, it fails to sustain earlier findings by other researchers that leverage positively affect firm profitability. This is because, based on the p-value associated with the variable financial leverage, we cannot reject the null hypothesis that the coefficient for the variable is zero. Independent variables debt/common equity, total common equity to total assets, and average equity to average assets significantly determines firm profitability. It is possible that a negative coefficient is associated with average equity to average assets because the variable may be indicating the changes in the percentage of equity to average assets: when the variable is low, the regression may be interpreting the phenomenon as detrimental to profitability. References Cottrell, A. and Lucchetti, R., 2012. Gnu regression, econometrics and time-series library. Wale Forest University and Universita Politecnica delle Marche. Demirel, E., Atakisi, A. and Atmaca, M., 2011. Financial and economic factors affecting debt ratio and ROE. European Journal of Scientific Research, 61 (3), 458-466. Gujarati, D., 2004. Basic econometrics. 4th ed. McGraw-Hill. Koop, G., 2005. Analysis of economic data. 2nd ed. John Wiley & Sons, Ltd. Martani, D., Mulyono and Khairurizka, R., 2009. The effect of financial ratios, firm size, and cash flow from operating activities in the interim report to the stock return. Chinese Business Review, 8 (6), 44-55. Singapurwoko, A. and El-Wahid, M., 2011. The impact of financial leverage to profitability study of non-financial companies listed in Indonesia Stock Exchange. European Journal of Economics, Finance and Administrative Sciences, 32, 136-148. Taani, K. and Banykhaled, H., 2011. The effect of financial ratios, firm size and cash flows. International Journal of Social Sciences and Humanity Studies, 3 (1), 197-205. Turkmen, S. and Demirel, D., 2012. Economic factors affecting financial ratios. European Journal of Scientific Research, 69 (1), 42-51. Woolridge, J., 2003. Introductory econometrics. 2nd ed. South-Western Publication. Read More