Effects of Working Capital Management on Zimbabwean and Turkish Banks

Abstract

Management of working capital entails the management of the components of current assets and current liabilities. Prior evidence has also endeavored to established the relationship that exists between working capital and the efficiency of companies. Therefore, this research study examined the effects of working capital management on commercial banks’ efficiency for two different countries. For this study, Zimbabwean and Turkish commercial banks were selected. The research study was carried out by utilizing audited financial statements of a sample of 10 Zimbabwean and 10 Turkish commercial banks for the period of 2009 to 2017. The efficiency was measured by looking at performance in terms of return on equity (ROE), and return on asset as another dependent variable in terms of profitability. The working capital was determined by looking at the components Current ratio, Liquidity Coverage ratio and Total Cash ratio, which were all used as independent working capital variables. Furthermore, bank size as measured by logarithm of sales and financial leverage were used as control variables. The data was studied using SPSS (version 20.0), estimation equation by both correlation analysis and pooled panel data regression models of cross-sectional and time series data were also employed for the analysis. The study further notes that Turkish banks performed better than the Zimbabwean ones with regards to liquidity coverage as they try to adhere to the Basel III reforms implemented by the Basel Committee on Banking Supervision (BCBS).

Keywords: working capital management, efficiency

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1. Introduction

It is quite fundamental to be able to have an effective working capital policy for the sustainability and success of any type of business firm. It’s significant to create an optimal balance between the assets which comprise working capital with regards to risk, liquidity and profitability of the firms. Time spent by the finance managers managing the working capital components is much more than the time spent on other financial issues. The significance of working capital ascends out of the formation of the optimal balance between the assets that enable the sustainability of the business operations, in place of time which is spent by financial managers.

The optimal balance on working capital entails reducing the needs of working capital and growing the potential sales. An effective working capital management policy is aided by the increment in the free cash flow which achieves a growth potential of the business firm as much as possible. This would surge the firm value of the company and also have a positive effect on the income of the shareholders. Conventionally, the recent trend has been to increase efficiency in working capital management even though finance managers get focused on long-term capital budgets and capital structure decisions (Ganesan, 2007; Lamberson, 1995).

There isn’t a precise application of the efficiency of working capital. It could differ from sector to sector dependent upon the year. It is thus nearly impossible to establish the ratio of working capital components within the assets correspondingly for each company. It could be an indication for the working capital to be different between the firms when it is considered that the sector has its own exclusive features and economy changes from year to year. Some research studies have also been able to prove this (Filbeck & Krueger, 2005; Lamberson, 1995; Maxwell et al. 1998).

Preceding research studies have examined the working capital elements of firms in different sectors in the same country. Nevertheless; the aim of this study was to contrast whether these components, that differ depending upon sectors and years, also have the same differences in the same sector but in different countries, or not. Hence, working capital elements of commercial banks operating in two different countries were assessed. Zimbabwean and Turkish commercial banks were chosen for the study.

The following section presents literature summary and method will be mentioned afterwards. Fourth section will present the findings and the last section will be the conclusion.

2. Literature Review

Academic studies which have been carried out on working capital management can be categorized

into four different groups. First category is the cross-sectoral examination of working capital components. Second category is the investigation of the effects of working capital policies on the risks and income levels of business firms. Third category is on the analysis of the effects of working capital management on profitability. And finally, the fourth group is the determination of the indicators of working capital. While all these studies seem indistinguishable, they hold different characteristics of working capital.

The first studies on working capital indirectly examined working capital (Gupta, 1969; Gupta & Huefner, 1972; Gombola & Ketz, 1983). The common features of these studies were that they put forth the averages of cross-sectoral financial ratios. Accordingly, activity ratios, liquidity and profitability of the companies differ depending upon the sectors. Reserch studies that have directly investigated the efficiency of working capital management through financial ratios depending on the sector, have also put forward alike results (Filbeck & Krueger, 2005; Maxwell et al. 1998; Weinraub & Visscher, 1998; Hawawini et al., 1986). As a result, ratios that put forth the efficiency of working capital management also differ depending upon the sectors, just as the other ratios.

The second category of studies have evaluated the effects of working capital policies on the risks and income of the business firms. In these studies (Gardner et al. 1986; Weinraub & Visscher, 1998), it was seen that companies which favor aggressive working capital policies are more profitable but at the same time risky. Whereas companies which favor conservative policies experience a favor aggressive working capital incur losses money, contrary to these research studies. lower level of income but are less risky. Nevertheless; Nazir & Afza (2009) state that companies which

Third category of studies tried to establish how working capital components increase the performance and profitability of the business firms when they are well managed. Shin and Soenen (1998), Deloof (2003), Lazaridis & Tryfonidis (2006), Ugurlu et al. (2014), Mathuva (2009) and Dursun & Ayrıçay (2012) suggested that there is a statistically significant association between working capital management and these factors. According to these research studies, managers must sell off their inventories and collect their receivables as soon as possible should they want to increase their performance and profitability.

Fourth category of the studies investigated the indicators of the requirements of efficient working capital management. Factors that affect the requirements of working capital were determined as financial leverage (Öztürk & Demirgüneş, 2008; Chiou et al., 2006; Akinlo, 2012; Vijayalakshmi & Bansal, 2013), company size (Nazir & Afza, 2009; Mansoori & Muhammad, 2012; Akinlo, 2012) as well as return on assets (Öztürk & Demirgüneş, 2008; Ugurlu et al., 2014; Abbadi & Abbadi, 2013; Archavli, et al., 2012; Doğan & Elitaş, 2014).

3. Methodology

3.1 Research Design

This study intended to both discover and explain the effects that shifting management attention has on the efficiency of working capital and how companies continually work with WCM. There was a starting point from theoretical sources in order to understand what kind of empirical findings that were needed to answer the aim of the study. Hence, the research was both deductive and inductive. Collins et al (2007), identified three types so research designs; exploratory, descriptive and explanatory (Casual). Exploratory research is a research which is conducted to get a better comprehension of issues under studied. Collins et al specified that exploratory research is a significant tool for establishing what is going on, seek new concepts, and to evaluate and question phenomenon. An exploratory research may contain the use of many methods- interviews, observations, documentations etc, (ibid). Descriptive research attempts to describe the characteristic of population or phenomenon. Its objectives are to give out precise information of a person, event or situation (Yin, 2003). Explanatory research is utilized to identify cause-effect relationship amongst variables. A research work that seeks to bring out the relationship between two or more variables is also known as explanatory research (Yin et al, 2003). Such studies accentuate on explaining relationship. As the research objective of the study was to determine the relationship between working capital management and efficiency of commercial banks, the research assumed the explanatory research method.

3.2 Research Hypotheses

For a better appreciation of the impact of the components of working capital on Return on Equity (ROE)and on the Return on Assets (ROA), the following hypotheses were designed.

• There is a significant relationship between the CUR and the banks’ ROE.
• There is a significant relationship between LCR and the banks’ ROE.
• There is a significant relationship between TCR and the banks’ ROE.
• There is a significant relationship between CUR and the banks’ ROA.
• There is a significant relationship between LCR and the banks’ ROA.
• There is a significant relationship between TCR and the banks’ ROA.

3.3 Model Specifications

As mentioned earlier, the effects of working capital management on banks’ efficiency was estimated by using comparable quantitative models of Raheman and Nasr, (2007), Panigrahi, Anita Sharma (2013). The general formula used for the model was:

= + +

= + +

Source: Panigrahi, Anita Sharma (2013)

Where;

ROEit and ROAit = Return on Equity, and Return on Asset of the banks i at time t; i = 1, 2, 3…, 20 banks respectively.

β0 = the intercept of equation

βi = Coefficient of Xit variables

Xit = the different independent variables for working capital management of firm i at time t.

t = Time from 1, 2…, 9 years

є = error term

4. Findings

In order to establish the significant differences between Zimbabwean and Turkish commercial banks, the independent t-test was conducted. Prior to the t-test, descriptive statistics-mean, minimum, maximum and std. dev. Values were calculated. Table 1 and Table 2 show the descriptive statistics of 10 Turkish commercial banks and 10 Zimbabwean commercial banks, respectively for nine years from the period of 2009-2017.

Table 1: Descriptive Analysis – Turkish Banks

Variable

Obs.

Minimum

Maximum

Mean

Std. Deviation

ROE

90

-0.4

30.4

12.904

6.06849

ROA

90

1.02

2.9

1.7543

0.37488

CUR

90

0.1

1.3

1.0347

0.12572

LCR

90

0.21

0.67

0.4022

0.10634

TCR

90

0.85

1.25

1.1007

0.10679

LEV

90

0.1023

0.3552

0.213898

0.0560818

SIZE

90

5.0461

11.9511

8.340537

1.3548919

Valid N (listwise)

90

Source: Research Findings

Table 2: Descriptive Analysis – Zimbabwean Banks

Variable

Obs.

Minimum

Maximum

Mean

Std. Deviation

ROE

90

-7.2

28

12.9601

5.99733

ROA

90

-2.68

2.98

1.2779

1.03085

CUR

90

0.87

1.71

1.0474

0.10535

LCR

90

0.32

42

1.001

4.61322

TCR

90

1.25

1.0931

0.15965

LEV

90

0.1132

0.2971

0.201707

0.0411494

SIZE

90

5.6245

9.23

7.62818

0.8077211

Valid N (listwise)

90

Source: Research Findings

4.1 Regression Results

Firstly, a test was carried out to determine which model was more appropriate to estimate the regressions, as mentioned before. The researcher started by using the Pooled OLS model to run the regressions and analyze the F Statistic test. The Hausman test was thereafter performed to examine if those effects are regarded to be random or fixed. Lastly, the null hypothesis of the test was rejected, demonstrating that the unobservable individual effects are regarded to be fixed and, therefore, the best model was the FE. After all these tests it was then possible to carry out the multiple regression analysis with a robust sample and the adequate model.

4.2 Multiple Regression Analysis: Linear Relationship

There exists wide empirical evidence about a linear relationship between working capital management and efficiency, indicating that a decrease on the components of the working capital will have a positive effect on firms’ efficiency (Deloof, 2003; Lazaridis & Tryfonidis, 2006; García-Teruel & Martínez-Solano, 2007).

Table 3.7: Model Testing Results on Dependent Variable ROE

Parameter

Model 1

Model 2

Model 3

Model 4

R2

0.647

0.139

0.056

0.06

Adjusted R2

0.64

0.12

0.035

0.039

Regression F

83.23

7.316

2.687

2.873

Significance

0.000**

0.000**

0.049**

0.039*

Constant

21.972(0.000)**

3.287(0.001)**

7.063 (0.000)**

7.040 (0.000)**

CUR

4.346(0.000)**

-14.973 (0.000)**

LCR

-9.124(0.000)**

2.836 (0.005)**

TCR

-0.379 (0.705)

2.199 (0.030)*

LEV

2.465(0.015)

0.556 (0.579)

-0.092 (0.927)

0.109 (0.913)

SIZE

-4.776(0.000)***

-1.285 (0.201)

-2.539 (0.012)

-2.701 (0.008)**

Source: Research Findings

Results of Model 1. This model included CUR as independent variable along with two control variables and tested the hypothesis that there is no significant relationship between CUR and ROE. The regression F-value at 83.23 evidence that it is highly significant, and thus we cannot reject hypothesis H1. It can be concluded that CUR is a significant factor in predicting the banks' ROE. The adjusted coefficient of determination in this model indicates that 64% of the variation in the ROE is explained by variations in CUR. Furthermore, the model identifies appositive relationship between CUR and banks’ performance (ROE).

Results of Model 2. There is a significant relationship between LCR and ROE. Similar to Model 1, the same variables are used, except CUR which has been replaced with LR. The estimated result for adjusted R2 at 0.120 and regression F at 7.316 shows the Model 2 is statistically significant, the hypothesis H2 is thus accepted. The regression results depict that there is a significant negative relationship between LCR and ROE.

Results of Model 3 In order to test the effect of TCR on the banks’ ROE, model 3 was constructed. The structured hypothesis that there is a significant relationship between TCR and ROE was tested through this model. The estimates of the model showed that the coefficient of TCR is negative with -0.379, but it was not statistically significant from zero. Hence, the hypothesis H3 was rejected and can be concluded that TCR is not a significant factor that should be considered in increasing banks' ROE.

Table 3.8: Model Testing Results on Dependent Variable ROA

Parameter

Model 5

Model 6

Model 7

Model 8

R2

0.527

0.139

0.056

0.18

Adjusted R2

0.032

0.12

0.035

0.09

Regression F

59.13

7.316

2.687

3.875

Significance

0.048**

0.207**

0.649**

0.039*

Constant

18.562(0.000)**

6.385(0.001)**

9.983 (0.000)**

8.240 (0.000)**

CUR

-15.116(0.000)**

-14.973 (0.000)**

LCR

14.273(0.207)**

-3.421698

2.836 (0.005)

TCR

-10.512 (0.197)**

2.199 (0.030)

LEV

2.465(0.015)

0.556 (0.579)

-0.092 (0.927)

0.109 (0.913)*

SIZE

-4.776(0.000)***

-1.285 (0.201)

-2.539 (0.012)

-2.701 (0.008)**

Source: Research Findings

In Table 3.8 the dependent variable tested was ROA. Model 5 tested CUR as an independent variable along with the other two other control variables. This model revealed that there is a negative relationship between CUR and ROA; it means that a decrease in CUR will also lead to an increase in the ROA. At the significance level of 0.048< 0.05, it is statistically significant. The weight of evidence, therefore suggested acceptance of the hypothesis H4 and confirming that there was a significant relation between CUR and ROA of commercial banks under study.

As shown in the table, Model 6 tested the relationship between LCR, as an independent variable with the other two control variables, and ROA. It revealed a positive relation between LCR and ROA, which means that an increase in LCR will also lead to an increase in the ROA. At the significance level of 0.207< 0.05, it was statistically insignificant. The weight of evidence, therefore suggested rejecting the H5 hypothesis. This implies that change in LR does not have an impact on the ROA of the commercial banks under study.

Model 7 was constructed in order to test the impact of a change in TCR on ROA. As shown in the table, the coefficient of TCR stood at -10.512. This indicated that TCR has negative relationship with ROA implying that a decrease in TCR will also lead to an increase in the ROA. At the significance level of 0.649< 0.05, it is statistically insignificant. The weight of evidence, therefore recommended rejecting the hypothesis H6. The R2, the coefficient of multiple determinations shows the extent to which the independent variables impact the dependent variable. The (model snapshot) revealed that coefficient of multiple determinations (R2) is 0.056. Thus 5.6 % of the variations in the dependent variable are clarified by the independent variables of the model. It also showed that the selected independent variables were not the major determinants factor of return on assets (ROA) of the commercial banks.

5. Conclusion

Working capital management has a key role in the decisions of financial management of any company. The objective of working capital management is to establish an optimal balance between the elements which constitute working capital. The financial success of a business firm will be enabled through the increase in the firm value. One of the most crucial issues which increases firm value is an efficient and profitable working capital management. Firm success is closely associated with the efficient management of all the components of working capital.

In emerging countries like Turkey, the development of the banking sector plays a key role in the development of the country’s economy. Banks need to solve the financing problem, which is one of the most fundamental problems to survive in markets based on competition. Also, banks need to become greater in their efficiency by effectively managing their working capital in order to reduce the need for external financing due to scarce resources. In this context, this research’s aim was to reveal the tradeoff between WCM and the commercial banks efficiency by using the data of the banks listed on BIST Industry Index in Turkey as well as the ZSE in Harare, Zimbabwe.

In this research study, working capital elements of 10 Zimbabwean commercial banks and 10 Turkish commercial banks listed in İstanbul Stock Exchange all of which have operated 2009 and 2017 have been compared. In accordance with the results, Turkish companies seem to have enjoyed increasing and better ROA better than the Zimbabwean banks. It can be said that Turkish banks have a more efficient management mentality with regards to profitability. However; in terms of CUR, Zimbabwean banks have a slightly much more efficient management mentality than Turkish banks. This implies that Zimbabwean banks have a slight advantage in terms of being able to meet their short-term obligations as they fall due than Turkish companies.

Furthermore; Turkish banks have been able to maintain the LR on satisfactory levels much better than the Zimbabwean banks. After the 2008 global financial crisis, Turkish banks have religiously adhered to Base III reforms finalized by the Basel Committee on Banking Supervision in January 2013. So, they follow a more efficient policy than Zimbabwean banks in terms of liquidity coverage.

When we consider that Turkish companies have much more cash and equivalent assets within their total assets on average than Zimbabwean banks, it shows that Turkish companies attribute much more importance to liquidity, nonetheless. It enables flexibility to Turkish banks in case of any negative cases to make their short-term debt payments.

Return on Assets, as mentioned earlier, of Turkish banks are much more than Zimbabwean banks on average. Return on equity of the banks in both countries didn’t seem to differ notably on average. However; this study did not analyze whether the profitability of the banks arises out of working capital or not. A different analysis is necessary for this. In this study, the average differences between the profitability of the companies from only two countries were analyzed.

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