The relationship between liquidity and profitability has been investigated by many researchers (Eljelly, 2004; Zainudin, 2006; Rehman and Nasr, 2007; Bhunia, Khan and Mukhuti, 2011). Some of these researchers claimed the inverse relationship between liquidity and profitability of a firm (Eljelly, 2004 and Rehman and Nasr, 2007) and some researchers argued that positive relationship exist between them (Zainudin, 2006; Bhunia, Khan and Mukhuti, 2011 and Bhunia, 2012). The positive relationship shows that firms which have higher liquidity have a propensity to make better profits (Zainudin, 2006).

There are two basic measures of liquidity; current ratio and quick (acid test) ratio. I have used current ratio to calculate liquidity as it is a wide measure of liquidity that gives confidence to short-term creditors that current liabilities will pay off by liquidating current assets (Zainudin, 2006) and mostly used by researchers as a proxy of liquidity (Rehman and Nasr, 2007, Bhunia, Khan and Mukhuti, 2011 and Bhunia, 2012). So the liquidity of a firm would be calculated as under:

Liquidity= Current Ratio

= Current assets/Current liabilities

Contents

- 1 3.3.2.2 Inventory turnover ratio
- 2 3.3.2.3 Debt-to-equity ratio
- 3 3.3.2.4 Size ownership
- 4 3.4 Population
- 5 3.5 Sample and Sampling technique
- 6 3.6 Data sources
- 7 3.7 Hypothesis
- 8 Table 3.1 Explanatory variables with their proxy and expected relationship with the profitability (ROA)
- 9 Variable Name
- 10 Proxy for the variable
- 11 Expected relationship
- 12 Chapter 4
- 13 Analysis and Discussion
- 14 4.1 Analysis
- 15 4.1.1 Descriptive Statistics
- 16 Table 4.1 Descriptive Statistics
- 17 ROA
- 18 LQ
- 19 INVT
- 20 DER
- 21 SZ
- 22 Â
- 23 Mean
- 24 Â
- 25 Â
- 26 Â
- 27 Â
- 28 Median
- 29 Â
- 30 Â
- 31 Â
- 32 Maximum
- 33 Â
- 34 Â
- 35 Minimum
- 36 Â
- 37 Std. Dev.
- 38 Â
- 39 Â
- 40 Skewness
- 41 Â
- 42 Â
- 43 Â
- 44 Kurtosis
- 45 Â
- 46 Â
- 47 Â
- 48 Â
- 49 Jarque-Bera
- 50 Â
- 51 Â
- 52 Â Probability
- 53 Â
- 54 Â
- 55 Â
- 56 Sum
- 57 Â
- 58 Â
- 59 Â
- 60 Â
- 61 Sum Sq. Dev.
- 62 Â
- 63 Â
- 64 Â
- 65 Â
- 66 Â
- 67 Observations
- 68 Â
- 69 4.1.2 Correlation Analysis
- 70 Table 4.2 Correlation Matrix
- 71 ROA
- 72 LQ
- 73 INVT
- 74 DER
- 75 SZ
- 76 ROA
- 77 Â
- 78 Â
- 79 LQ
- 80 Â
- 81 INVT
- 82 Â
- 83 Â
- 84 DER
- 85 Â
- 86 Â
- 87 SZ
- 88 Â
- 89 Â
- 90 Â
- 91 Â
- 92 Â
- 93 4.1.3 Regression Analysis (The Fixed Effects Model)
- 94 Table 4.3 Regression Analysis: The fixed effects model (ROAit= ÃŽÂ²0+ÃŽÂ²1 LQit+ÃŽÂ²2 INVTit+ÃŽÂ²3 DERit+ÃŽÂ²4 SZit+eit)
- 95 Variable
- 96 Coefficient
- 97 Std. Error
- 98 t-Statistic
- 99 Prob.Â Â
- 100 C
- 101 LQ
- 102 INVT
- 103 DER
- 104 SZ
- 105 Effects Specification
- 106 Cross-section fixed (dummy variables)
- 107 R-squared
- 108 Â Â Â Â Mean dependent var
- 109 Adjusted R-squared
- 110 Â Â Â Â S.D. dependent var
- 111 S.E. of regression
- 112 Â Â Â Â Akaike info criterion
- 113 Sum squared resid
- 114 Â Â Â Â Schwarz criterion
- 115 Log likelihood
- 116 Â Â Â Â Hannan-Quinn criter.
- 117 F-statistic
- 118 Â Â Â Â Durbin-Watson stat
- 119 Prob(F-statistic)
- 120 4.1.4 Remarks
- 121 4.1.5 Regression Analysis (The Random Effects Model)
- 122 Table 4.4 Regression Analysis: The random effects model (ROAit= ÃŽÂ²0+ÃŽÂ²1 LQit+ÃŽÂ²2 INVTit+ÃŽÂ²3 DERit+ÃŽÂ²4 SZit+eit)
- 123 Variable
- 124 Coefficient
- 125 Std. Error
- 126 t-Statistic
- 127 Prob.Â Â
- 128 C
- 129 LQ
- 130 INVT
- 131 DER
- 132 SZ
- 133 Effects Specification
- 134 S.D.Â Â
- 135 RhoÂ Â
- 136 Cross-section random
- 137 Idiosyncratic random
- 138 Weighted Statistics
- 139 R-squared
- 140 Â Â Â Â Mean dependent var
- 141 Adjusted R-squared
- 142 Â Â Â Â S.D. dependent var
- 143 S.E. of regression
- 144 Â Â Â Â Sum squared resid
- 145 F-statistic
- 146 Â Â Â Â Durbin-Watson stat
- 147 Prob(F-statistic)
- 148 Unweighted Statistics
- 149 R-squared
- 150 Â Â Â Â Mean dependent var
- 151 Sum squared resid
- 152 Â Â Â Â Durbin-Watson stat
- 153 4.1.6 Remarks
- 154 4.2 Discussion
- 155 Chapter 5
- 156 Conclusion and Implications
- 157 5.1 Conclusion
- 158 5.2 Limitations of the research
- 159 5.3 Directions for the future research

Inventory turnover ratio pointed out how quickly firm sells its inventory, measured as rate of goods movement into the firm from raw material to finished goods and out of the firm in the form of sales (Stickney & Weil, 2002). Variability in inventory turnover ratio is caused by segment-wise-effect and when firms work in sales decline state then bigger changes are due to changes in sales (Kolias, Dimelis & Filios, 2010). Usama (2012) argued that minimum inventory turnover in days and cash conversion cycle can create higher profit. Capkun, Hameri & Weiss (2009) examined the inventory performance by total inventory and the distinct components of inventory such as raw material, work in process and finished goods. They found that inventory performance is positively correlated with financial performance of the firm and association between the performance of distinct components of inventory and financial performance differ across inventory components.

Previous researches show various results regarding inventory turnover ratio as Gaur, Fisher & Raman (2004), Boute et al. (2007) and Kolias, Dimelis & Filios (2010) claimed that inventory turnover and profitability are negatively correlated while Capkun, Hameri & Weiss (2009) and Sahari, Tinggi & Kadri (2012) argued that inventory turnover ratio and firm performance are positively correlated. The formula to measure inventory turnover ratio is as under:

Inventory turnover ratio= Total sales/inventory

Debt-to-equity ratio is used to evaluate the risk associated with firm’s financing structure (Wild, Larson & Chiappetta, 2007, p. 689). It shows the proportion of equity and debt which the firm is using to finance its assets. A firm adopts suitable mix of sources of finance such as retained earnings, issuance of ordinary and preference shares and debt to maximize shareholders wealth (Afza & Hussain, 2011). Debt financing gives a tax shield to a firm therefore they took high level of debt to gain maximum tax benefits and eventually increase profitability. However, the increase of debt financing increases the possibility of bankruptcy (Myers, 2001). A high leverage or a low equity capital ratio causes to reduce the agency cost related to outside equity and raises firm value (Berger & Bonaccorsi di Patti, 2003). The level of investment can be increased through the use of borrowed capital and it increased the return of invested capital but it also increased the risk for the firm and for the owners due to fixed expenses of interest (Eriotis, Frangouli &Neokosmides, 2011).

Elsas, Flannery & Garfinkel (2006) argued that debt financing produces negative long run performance more than equity financing whereas financing with internal funds never produce important share underperformance. Amjed (2011) claimed that debt financing is considered to be cheaper than equity financing due to tax benefit and concluded that long term debt has a negative impact on firm’s performance and short term debt has a positive impact on firm’s performance. Eriotis, Frangouli & Neokosmides (2011) claimed that debt-to-equity ratio has a negative impact on firm’s performance. The formula of debt-to equity ratio is provided below:

Debt-to-equity ratio= Total debt/Total equity

Size shows the level of firm’s operations. Larger firms are stronger to face risky situations and have better means to go through these types of situations. Size also brings stronger bargaining power to the firm over its competitors and suppliers and bigger firms have superior technology (Bhattacharyya &Sexena, 2009). ). Gibrat(1931) presented a law that growth rate and size of a firm are independent. His law advocated that during a specific period, the probability of change in size is same for all the firms in the given industry.

Small firms are more productive but lower survival probability due to two to four times more level of risk as compare to large firms (Dhawan, 2001). Small firms have high profit rate increase as compare to medium or large firms and when these firms become bigger, their profits rate become higher (Ammar et al., 2003). Past studies have different views regarding size and profitability relationship. Some researchers found that profitability of a firm increases as firm size decreases (Dean, Brown & Bamford, 1998; Ammar et al., 2003; Ramasamy, Ong, & yeung, 2005; Abu-Tapanjeh 2006 and Punnose, 2008) while other claimed that firm size and level of profitability are positively correlated (Treasy1980, Amirkhalkhali & Mukhopadhyay, 1993 and Bhattacharyya & Sexena, 2009 ).

Many proxies are used for size by many researchers according to the requirements of their study. Mostly total sales, total assets or market capitalization is used as proxy of size. In this study, total sales is used as proxy of firm size. Majumdar (1997) and Bhattacharyya and Sexena (2009) also used total sales to measure firm size. For data symmetry, I used natural log of total sales. So the firm size would be:

Size= Log (Total Sales)

Population is the concerned group of individuals, data or items from which sample is taken. The concerned population in this study is the Chemical firms listed on the Karachi stock exchange for the period of 2005-2010. The total number of chemical firms listed on Karachi stock exchange is 36.

To find out the determinants of firm’s profitability, this study took the sample of 20 firms from Textile industry of Pakistan which are listed on Karachi Stock Exchange (KSE) during 2005 to 2010 as it is the oldest and largest stock exchange in Pakistan. The firms were selected for the sample by using simple random sampling technique as this technique assures that each component in the population has an equal probability of being selected in the sample ( Zikmund, 2002, p.384).

This study took only firm specific factors which affect firm’s profitability. So, the data for firm’s specific factors was calculated from the financial statements of the respective firms and report provided by State Bank of Pakistan namely ‘Financial Statement Analysis of Companies (Non-Financial), listed at Karachi Stock Exchange’ issue 2005-2010. This research is a longitudinal research because same variables were observed repeatedly for the period of six years from 2005 to 2010.

This study contains one dependent variable i.e. returns on assets (ROA) and four independent variables such as liquidity, inventory turnover ratio, debt-to-equity ratio and size. So, the testable hypotheses (the alternate hypothesis) are hereafter:

H11: There may exist a negative relationship between liquidity and profitability of a firm. Firms with higher level of liquidity may possess lower level of profitability and vice versa.

H12: There may exist a positive relationship between inventory turnover ratio and profitability of a firm. Firms with higher inventory turnover ratio may possess higher level of profitability and vice versa.

H13: There may exist a negative relationship between debt-to-equity ratio and profitability of a firm. Firms with higher level of debt-to-equity ratio may possess lower level of profitability and vice versa.

H14: There may exist a negative relationship between size and profitability of a firm. Firms with larger size may possess lower level of profitability and vice versa.

Liquidity

Current Ratio (CR)

Negative

Inventory turnover

Inventory turnover ratio (INVT)

Positive

Debt-to-equity ratio

Debt-to-equity ratio (DER)

Negative

Size

Log (Total Sales) (SZ)

Negative

This chapter includes the statistical analysis of the sample data and gives details regarding empirical findings of the study.

This part would indicate the empirical findings of the study. The first table provides the descriptive statistics which quantitatively describe the main characteristics of the data. The second table contains correlation matrix which shows the association between all the variables. The third table entails the OLS regression estimates with fixed effects and fourth table contains the random effects to establish the relationship between dependent and independent variables.

Descriptive statistics portrays summary of the data which is used in the study to clearly understand the range and characteristics of the data. Table 4.1 represents descriptive statistics for 20 Pakistani Chemical firms for a period of 6 years from 2005 to 2010 and for a 120 firms-year observations. Mean shows the average value of the data and median indicates the middle value of the data. In the table 4.1, mean for the dependent variable i.e. return on assets is 15.927 and median is 13.66. Standard deviation

Â 15.92700

1.736000

12.59517

1.037250

Â 6.539098

13.66000

Â 1.455000

Â 6.560000

0.945000

Â 6.563317

Â 45.13000

Â 5.130000

Â 222.5300

3.490000

Â 7.945245

-10.98000

Â 0.230000

Â 0.000000

Â 0.190000

Â 5.361393

Â 11.32618

0.972208

Â 22.98619

Â 0.671968

Â 0.618107

Â 0.566959

1.599074

6.861938

Â 1.111136

Â 0.069343

2.577047

5.240897

Â 60.02378

4.483081

Â 2.357129

Â 7.323292

76.24882

Â 17200.28

35.69009

Â 2.162585

Â 0.025690

0.000000

Â 0.000000

0.000000

Â 0.339157

1911.240

208.3200

1511.420

Â 124.4700

Â 784.6917

Â 15265.60

112.4775

62875.43

53.73339

45.46468

Â 120

Â 120

Â 120

120

Â 120

signifies the distinctive deviation from the mean. The standard deviation of return on assets is 11.32618.

The first main independent variable i.e. liquidity (current ratio) has mean value 1.736; median is 1.455 and standard deviation is 0.972208. The second independent variable which is inventory turnover ratio has mean 12.59517; median is 6.56 and standard deviation is 22.98619. The mean, median and standard deviation of third independent variable i.e. debt to equity ratio are 1.03725, 0.945 and 0.671968 respectively. In the case of firm size (natural logarithm of total sales), which is the last independent variable has mean 6.539098; median is 6.563317 and standard deviation is 0.618107.

The data of dependent variable which is return on assets and all the independent variables is positively skewed. The kurtosis is also positive among all the variables. The Jarqua-Bera test is used to check the normality of the data rejects the null hypothesis that all the dependent and independent variables are normally distributed because Jarqua-Bera statistic is very high in most of the variable’s results and the p value is zero in almost all of the cases. Therefore, the data relating to the variables used in the estimation is not normally distributed because the skewness and kurtosis coefficients are not equal to 0 and 3 respectively.

The degree of association between the variables is judged by Pearson’s correlation coefficient (r). Table 4.2 presents the correlation analysis of all the variables which are used in the analysis. The basic purpose of correlation analysis is to detect the presence of multicollinearity. Gujrati (2008, p.337) recommends that the problem of multicollinearity exist if the correlation coefficient exceeded 0.80. In correlation matrix, no value is greater than or equal to 0.80. So, there is no high correlation among the variables which are used in the analysis. Returns on assets has significant and positively correlation of 42.57% with liquidity, 39.11% with inventory turnover ratio, 42.48% with firm’s size and negatively correlated with 27.79% with debt to equity ratio.

1.000000

Â 0.425709

0.391140

-0.277932

Â 0.424855

Â 1.000000

-0.175564

-0.648455

Â 0.002791

1.000000

Â 0.233890

Â 0.388966

1.000000

Â 0.227785

1.000000

Inventory turnover is positively associated with debt to equity ratio and firm’s size with 23.39% and 38.90% respectively. Debt to equity ratio is positively associated with 22.78% with firm’s size.

Table 4.3 provides the regression analysis to examine the influence of liquidity (LQ), inventory turnover ratio (INVT), debt to equity ratio (DER) and size of a firm (SZ) on its profitability (ROA). In this model, determinants of firm’s profitability are estimated with fixed effects. The results of regression analysis shows that this model is good fitted having F-statistic 17.5899 and p- value is 0.000. The adjusted R2 value is 0.762270 which predicts that almost 76% variation in the profitability (ROA) uniquely or jointly due to independent variables. Durbin-Watson stat value is 1.641899, points out that no serial correlation is present in the data as the test value is nearly equal to 2 which is the standard value and it is less than the table value dU= 1.663 under 1% level of significance.

5.868965

21.19104

0.276955

0.7824

4.596135

0.977998

4.699533

0.0000

0.063956

0.036370

1.758493

0.0819

-3.315956

1.584092

-2.093285

0.0390

0.720754

3.245100

0.222105

0.8247

0.808218

15.92700

0.762270

11.32618

5.522370

6.432348

2927.671

6.989846

-361.9409

6.658750

17.58990

1.641899

0.000000

The relative importance of all independent variables liquidity (LQ), inventory turnover ratio (INVT) debt to equity ratio (DER) and size of a firm (SZ) in the determination of firm’s profitability (ROA) depends upon the higher coefficient value and t-statistic. Results revealed that liquidity has more influence on the profitability of a firm than other variables. Liquidity, inventory turnover and firm’s size have positive coefficients of 4.596135, 0.063956 and 0.720754 with t-statistics of 4.649953, 1.758493and 0.222105 respectively while debt to equity ratio has negative coefficient of -3.315956 with t-statistics of -2.093285. Moreover, the variables liquidity, debt to equity ratio and inventory turnover are significant at 1%, 5% and 10% level of significance.

The aim of this study is to identify the determinants of firm’s profitability while using the data of Chemical firms in Pakistan which are listed on Karachi Stock Exchange. While analyzing the firm specific factors, liquidity is found to have positive impact on profitability. So, H11 is rejected. Inventory turnover ratio shows the positive impact on profitability according to study findings. So, H12 is accepted in this regard. Moreover, the impact of debt-to-equity ratio is found negative on firm’s profitability. So, we accept H13. Size of the firm indicated positive impact on firm’s profitability. So, H14 is rejected with respect to study results. All the variables are found significant determinant of firm’s profitability except size of the firm which has insignificant result according to the study findings.

Table 4.4 entails the regression analysis to examine the influence of liquidity (LQ), inventory turnover ratio (INVT), debt to equity ratio (DER) and size of a firm (SZ) on its profitability (ROA). In this model, determinants of firm’s profitability are estimated with random effects. In random effects model the intercept shows the mean value or average value of all the intercepts and error term shows the random deviation of single intercept from the mean value.

The findings of regression analysis indicates that this model is good fitted having F-statistic 14.92818 and p- value is 0.000. The adjusted R2 value is 0.318882 which predicts that almost 32% variation in the profitability (ROA) randomly due to

-22.16595

13.27979

-1.669149

0.0978

4.447065

0.922300

4.821712

0.0000

0.097785

0.033657

2.905343

0.0044

-3.070943

1.450723

-2.116837

0.0364

4.943581

2.047117

2.414900

0.0173

6.345424

0.5690

5.522370

0.4310

0.341777

5.332229

0.318882

6.785963

5.600447

3606.976

14.92818

1.382481

0.000000

0.453175

15.92700

8347.605

0.597366

independent variables. On the other hand, Durbin-Watson stat value is 1.382481, points out that no serial correlation is present in the data as the test value is less than the table value dU= 1.663 under 1% level of significance.

Coefficient value and t-statistic indicates the relative importance of all independent variables liquidity (LQ), inventory turnover ratio (INVT) debt to equity ratio (DER) and size of a firm (SZ) in the determination of firm’s profitability (ROA). Results revealed that liquidity has more influence on the profitability of a firm than other variables. Liquidity, inventory turnover and firm’s size have positive coefficients of 4.447065, 0.097785 and 4.943581 with t-statistics of 4.821712, 2.905343 and 2.414900 respectively while debt to equity ratio has negative coefficient of -3.070943with t-statistics of -2.116837. Moreover, the variables liquidity and inventory turnover ratio are significant at 1% and debt-to-equity ratio and size are significant at 5% level of significance.

The basic purpose of this study is to find out those factors which affect firm’s profitability. The above model is used to find out the relationship between the dependent and independent variable with the random effects model. The model exhibits that liquidity is significantly positively correlated with profitability. So, H11 is rejected. Inventory turnover ratio shows the significantly positive impact on profitability. So, H12 is accepted in this regard. On the other hand, the impact of debt-to-equity ratio is found to be significantly negatively associated with the firm’s profitability. So, we accept H13. Size of the firm indicated significantly positive impact on firm’s profitability. So, H14 is rejected with respect to study results. All the variables are found significant determinant of firm’s profitability in random effects model.

The basic purpose of this study is to identify the determinants of firm’s profitability while using the data of Chemical firms in Pakistan which are listed on Karachi Stock Exchange. The research findings show that liquidity is significantly positively correlated with profitability which satisfies the findings of (Zainudin, 2006, Bhunia, Khan & Mukhuti, 2011 and Bhunia, 2012) but it opposes the results of (Eljelly, 2004 and Rehman and Nasr, 2007). Inventory turnover ratio shows the significantly positive impact on profitability according to study findings which is consistent with the finding of (Sahari, Tinggi & Kadri, 2012). On the other hand, the impact of debt-to-equity ratio is found to be significantly negatively associated with the firm’s profitability which supported the conclusion of (Eriotis, Frangouli & Neokosmides, 2011). Size of the firm indicated significantly positive impact on firm’s profitability according to the findings of (Treacy, 1980; Bhattacharyya & Sexena, 2009 and Amirkhalkhali & Mukhopadhyay, 1993) and the findings rejected the arguments of (Ramasamy, Ong & yeung, 2005, Ammar et al., 2003 and Dean, Brown & Bamford, 1998).

On the whole, the selected variables are strongly associated with the profitability of the firm. Liquidity is the most important factor to affect profitability. Although size and debt-to equity ratio reveal strong power to affect profitability, but their explanatory power is less than liquidity. On the other hand, inventory turnover ratio has a significant positive relationship with profitability but its explanatory power is less than other independent variables.

This chapter provides conclusion, limitations and of the study further directions for future research.

The primary objective of this study was to find out the factors which determine the profitability of the firm while analyzing the financial data of Chemical industry of Pakistan which are listed on Karachi Stock Exchange for the period of 2005 to 2010. The findings revealed that the selected variables have significant relationship with the profitability and they strongly affect the profitability of the firm. The findings suggested that liquidity has a strong positive impact on profitability. Firms should maintain optimal level of liquidity to meet short term obligations. The results also show that inventory turnover ratio is positively associated with firm’s profitability. It means that firm gets higher profit by quickly converting its inventory into cash. The findings reject the pecking order theory as debt-to-equity ratio has inverse relationship with profitability as debt-to-equity ratio increases, the firm’s profitability decreases. It shows that firm should not rely on heavy debt financing. The findings confirm the trade-off theory that firms should focus on trade-off of costs and benefits while selecting how much equity and debt to use as financing sources. Lastly, the findings reject the Gibrat’s law and claimed that firm size and profitability are positively related. The results indicated that profitability goes up as firm’s size become larger.

This study is carried out in Pakistan which has developing economy so there are many problems with respect to availability of data as many manipulations and misrepresentations are existed in publically available data. Many sources were used for data collection. So, the quality of results of this study depends upon the available data of selected companies. Due to limitations of time and scope of the research required to focus only on limited number of firms. Due to available resources, only internal factors which affect profitability are included in the study.

This research was first time conducted in Pakistan to explore the determinants of firm’s profitability in Karachi Stock Exchange. Further studies should be carried out in Pakistan to explore this phenomenon on different sectors or in other developing economies to evaluate whether the factors have same effect in different economies. Comparative research on this topic could be employed while taking different sectors of the economy. Moreover, external factors could be used to analyze their affect on profitability in developing economy. Different models could be employed for further in-depth analysis.

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