Determinants of Working Capital Requirements In

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Determinants of Working Capital Requirements in

Selected Quoted Companies in NigeriaOlayinka Olufisayo Akinlo

a

aDepartment of Management and Accounting, Obafemi Awolowo University, Ile-Ife, Niger

Version of record first published: 04 Apr 2012.

To cite this article: Olayinka Olufisayo Akinlo (2012): Determinants of Working Capital Requirements in Selected QuotedCompanies in Nigeria, Journal of African Business, 13:1, 40-50

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Determinants of Working Capital Requirements in SelectedQuoted Companies in Nigeria

Olayinka Olufisayo Akinlo

Department of Management and Accounting, Obafemi Awolowo University, Ile-Ife, Nigeria

In this article, the author investigates the determinants of working capital requirementsof 66 firms in Nigeria using panel data for the period 19972007. The results suggest thatsales growth, firms operating cycle, economic activity, size, and permanent workingcapital are firm specific characteristics that positively drive working capital policy.

Leverage, however, is inversely related to working capital requirements. Essentially,the results imply that traditional valuation methods used to quantify the efficiency ofcorporate working capital policy may be suspect as increased investments in operatingworking capital may be necessitated by increased business uncertainties. In general, thefindings suggest that some of the insights from modern finance theory are potable toNigeria.

Key words: determinants, Nigeria, panel, working capital

INTRODUCTION

The importance of working capital among firms cannotbe overemphasized. It constitutes a major externalsource of capital for small and medium-sized and high-growth firms. Working capital position of firms is notonly an internal firmspecific matter but also an impor-tant indicator of risk of creditors (Moyer, McGuigan, &Kretlow, 1995). Working capital is important because ofits effects on the firms profitability and risk and, conse-quently, its value (Smith, 1980). Excessive levels ofcurrent assets can easily result in a firm realizing a sub-stantial return on investment. However, inadequateworking capital not only impairs the firms profitabilitybut also results in production interruptions and ineffi-ciencies and sales disruptions.1

Indeed, the significant decline of corporate perfor-mance during the late 1990s financial crisis has brought

to fore the need for firms, especially in developing indus-trialized countries, to pay more attention to workingcapital management. The financial crisis has shownclearly that improving working capital managementis very important for firms to withstand the impactsof economic turbulence (Reason, 2008). Moreover,efficient working capital management is essential forfirms during the booming economic periods (Lo,2005), for the reason that working capital managementis related to all aspect of managing current assets andcurrent liabilities. Working capital management is notonly to immunize firms from financial crisis but can bemanaged strategically to enhance competitive positionand profitability. In short, investigating the determi-nants of working capital management in general pro-vides valuable information that can be utilized informulating an effective working capital strategy toimprove profitability. However, to date, a large numberof studies on working capital management have beenfocused on firms in developed and industrialized econ-omies. Only few studies have been devoted to firmsin developing countries. Indeed, to the best of our

This study was financed by the Council for the Development of

Social Science Research in Africa (CODESRIA). The author wouldlike to thank two anonymous referees and the editor of the journal

for valuable comments and suggestions. All remaining errors are theauthors responsibility.

Address correspondence to Olayinka Olufisayo Akinlo, Depart-ment of Management and Accounting, Obafemi Awolowo University,Ile-Ife, Nigeria. E-mail: [email protected]

Journal of African Business, 13(1), 4050, 2012

Copyright # Taylor & Francis Group, LLCISSN: 1522-8916 print=1522-9076 online

DOI: 10.1080/15228916.2012.657951


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knowledge, no known study has been focused on work-ing capital management in the case of Nigeria. Thedearth of research on determinants of working capitalrequirement might not be unconnected with the lackof firm-level data in most developing countries. How-ever, there is need to fill this gap. Hence, the main objec-tive of the study is to examine the determinants of

working capital management of some selected firms inNigeria. It is expected that the outcome of this study willbe of great use for corporate managers and other stake-holders to understand the impact of forces that influenceworking capital requirements.

The rest of the study is organized as follows: the nextsection presents the literature review. The third sectionprovides the sample and data description. The fourthsection discusses the methodology and the fifth sectionreports the empirical findings of the study. The lastsection concludes the article.

LITERATURE REVIEW

Theoretical Issues

A large number of theoretical and empirical studieshave been conducted on small and medium-sized firmsin Sub-Saharan Africa. Some of these include Owusu-Frimpong and Martins (2010), Acquaah and Appiah-Nkrumah (2011), Babatunde and Laoye (2011), andAnderson (2011). However, most of these studies havenot focused on determinants of working capital.2 In gen-eral, a large number of factors, each having differentimportance, influence working capital needs of firms.

However, the importance of factors tends to changefor a firm over time. This explains why an analysis ofrelevant factors should be made in order to determinetotal investment in working capital. Theoretically, sev-eral factors have been identified in the corporate financeliterature (Ramamoorthy, 1976). These include the nat-ure of the business, market and demand conditions,technology and management policy, credit policy, avail-ability of credit from suppliers, operating efficiency, andprice level changes.

The nature of the business is a major determinant ofworking capital need of a firm. Retail stores will need tocarry large stocks of a variety of goods to satisfy variedand continuous demands of their customers; likewise,trading and financial firms will require a large sum ofmoney to be invested in working capital. In the sameway, some manufacturing businesses and constructionfirms will need to invest substantially on working capitaland a nominal amount in fixed assets. In contrast, publicutilities will have limited need for working capital buthave to invest substantially in fixed assets. As pointedby Pandey (2006), the working capital requirements of

public utilities in general, will be low because they mayhave only cash sales and supply services, not products.Hence, no funds will be tied up in debtors and stocks(inventories). As has been pointed out in the literature,the working capital requirements of most manufacturingcompanies will likely fall between the two extremerequirements of trading firms and public utilities. There-

fore, manufacturing firms will need to make adequateinvestment in current assets depending upon the totalassets structure and other variables.

Another important factor is sales. Theoretically, it isdifficult to ascertain precisely the nature of the relation-ship between sales volume and working capital needs.A firm that is growing might need to invest in fixedassets to be able to sustain growing production andsales. This will, no doubt, result in increase investmentin current assets to support enlarged scale of operations.However, sales are function of demand conditions.More often than not, large numbers of firms do experi-ence seasonal and cyclical fluctuations in the demand for

their services and products. These business variationshave been argued to affect the working capital require-ment, especially the temporary working capital require-ment of the firm.

In the period of economic boom, a firms investmentin inventories and debtors will increase because sales willincrease. Moreover, in the period of boom, firms mightneed to make additional investment in fixed assets so asto increase their productive capacity. This action of thefirm will entail increasing their level of working capital.The reverse is the case when there is a decline in theeconomy. In the period of slump, sales will fall and thusthe levels of inventories and debtors. Consequently,

firms will curtail short-term borrowings and hence theirrequirements of funds for working capital. As noted inPandey (2006), apart from the fact that seasonal fluc-tuations affect working capital requirement, they alsocreate production problems for the firm. In the periodsof peak demand, increasing production may be expens-ive for the firm. In the same way, firms may face moreexpensive production during the slack period as theymay have to maintain a large workforce and physicalfacilities without adequate production and sales(Pandey, 2006). In order to utilize its resources to thefullest, a firm might adopt the policy of level production,irrespective of seasonal changes. However, adoption ofsuch a policy will entail accumulation of inventories dur-ing the off season and their quick disposal during thepeak season. The increasing level of inventories duringthe slack season will require increasing funds tied upin the working capital for some months.

One other factor is the technology and manufacturingpolicy of firms. Each firm has a manufacturing cycle,which is also known as the inventory conversion cycle.The cycle starts when the firm purchases raw materials,

WORKING CAPITAL REQUIREMENTS IN SELECTED QUOTED NIGERIAN COMPANIES 41


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uses the raw materials, and turns them into finishedgoods. The manufacturing cycle can be long or short.If it is long, the firms working capital requirement willbe large, whereas the opposite is the case if it is short.For example, a firm that produces soaps, sweets, cakes,etc. may have a cycle that last for few hours, but for afirm producing cars, the cycle could last weeks or

months. By implication, a long manufacturing cycle willbring about a larger tie-up of funds in inventories. Inorder to reduce the working capital requirement andshorten the manufacturing cycle, the firm must searchfor improved technology that will ensure prompt com-pletion of the finished product. However, for this to beachieved there is need for proper planning and coordi-nation at all levels of activity. This will ensure that thereare no delays that can result in accumulation of work-in-progress and a waste of time. Manufacturing firms thatneed a lot of investment in working capital usually havea policy of asking for advance payments from their cus-tomers in order to minimize the amount they will invest

in working capital, whereas nonmanufacturing firms,especially service and financial enterprises, do not havea manufacturing cycle.

Moreover, to resolve the working capital problemsdue to seasonal changes in demand for the firms pro-duct, there is a need to maintain a steady productionpolicy. This type of policy causes inventories to accumu-late during off-season periods and this will expose thefirm to greater inventory costs and risks,3 although thereare firms that operate a variable production policy dueto the high costs and risks of maintaining a constantproduction schedule. This implies varying productionschedules with changes in demand. Firms whose manu-

facturing capability can accommodate more than oneproduct usually solve their working capital problemsby manufacturing the original product during itsincreasing demand, and during the off-season they pro-duce other products in order to utilize physical resourcesand working force. This shows that production policyvaries from firm to firm depending on the peculiaritiesof each firm.

Another factor is the issue of credit policy. Each firm,depending on the industry in which it is located, usuallyhas credit policies that should be followed. A firm canshape its own credit policy within the constraint of theindustry norms and practices and it is advisable that afirm should use its discretion in granting credit termsto customers. Hence, a firm should not maintain a lib-eral credit policy without a prior knowledge of the cred-itworthiness of customers because there may be problemof collecting the money later. Another issue tied withcredit policy is the issue of collection periods. Where afirm has slack collection procedures there is a chanceof increasing the firms bad debt. Therefore, firmsshould evaluate the creditworthiness of their customers

before granting them credit and endeavor to avoid highcollection periods because a lot of funds will be tied upin debtors.

One thing that reduces the working capital need of afirm is the availability of credit from its suppliers. Thisfinances the firms inventories and also reduces the cashconversion cycle. Where a firm is unable to have credit

from the suppliers but has favorable bank credit (i.e.,the interest rate is at a reasonable cost), the difficultyof financing its inventories and debtors is removedbecause the working capital policy of the firm will begreatly influenced. Moreover, there is need for everyfirm to utilize its resources efficiently and effectively inorder to increase profitability and reduce the pressureon working capital requirement. The resources arematerials, labor, and overhead.

Last, every firm is expected to think past its presentstate, especially anticipating changes that could occurin the nearest future. In a nation like Nigeria whereprices of commodities are always skyrocketing, a firm

depending on the industry in which it operates shouldknow that as price level increases, the working capitalrequirement will increase except where the firm is ableto change the prices of its products immediately. Somefirms may not be affected by this price level changebecause of their industry.

Empirical Evidence on the Determinants of WorkingCapital

Some empirical studies have been conducted to identifythe determinants of working capital management in thedeveloped countries. However, in developing countries,

Nigeria inclusive, not very many studies have beenconducted on the subject matter. In this subsection, weprovide a summary of the findings of the few existingempirical studies on the determinants of working capitalmanagement. Nunn (1981) used the PIMS databaseto examine why some product lines have low workingcapital requirements, while other product lines havehigh working capital requirements. The results basedon factor analysis, identified factors associated with pro-duction, sales, competitive position, and industry.Hawawini, Viallet, and Vora (1986) examined the influ-ence of a firms industry on its working capital manage-ment. The study was based on 1181 U.S. firms overthe period 1960 to 1979. The results showed that therewas a substantial industry effect on firm workingcapital management practices that is stable over time.The main conclusion from Nunn (1981) and Hawawiniet al. (1986) was that sales growth and industry practiceswere important factors influencing a firms investment inworking capital.

Prior research on business indicator and financialratios revealed that business exerted an influence on

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the financial ratios of a company (Horrigan, 1965; Liu,1985; Luo, 1984; Su, 2001; Zhou, 1995). Apart frombusiness indicator, another important factor that hasbeen found to affect the working capital policies of acompany is uncertainty of the wider economic environ-ment (Merville & Tavis, 1973). Different industriesrespond differently to the impact of economic environ-

ment due to the different natures of their operations.Shulman and Cox (1985) indicated that current ratioand quick ratio are used to evaluate a firms capabilityto pay debts from the perspective of liquidity with noconsideration of the going concern of the company,while net working capital integrating operational andfinancial strategy is not a suitable indicator of liquidity.In predicting the financial crisis of a company, Shulmanand Cox (1985) classify net working capital into workingcapital requirement (WCR) and net liquid balance(NLB) to evaluate the management of working capitaland capability of raising and allocating capital, respect-ively. They found NLB better than traditional indicators

in terms of predicting financial crisis and the liquidity ofa company. Hawawini et al. (1986) believed that evalua-tions based on NLB and WCR were better than anybased on traditional indicators.

Looking at the work of Kieschnick, LaPlante, andMoussawa (2006) on the determinants and conse-quences of corporate working capital, they looked atthe factors that influence a firms working capital usingthe cash conversion cycle (CCC) against the NTC usedby Shin and Soenen (1998). Like Hawawini et al.(1986), they believe that industry practices are signifi-cant determinants of a firms working capital practices.

Chiou and Cheng (2006), in their article on the

determinants of working capital, investigated therelation of business indicator and management of short-term capital from the perspective of a firms workingcapital, which traditionally is rated by current ratio,quick ratio, and net working capital. They used theNLB and WCR as measures of a companys workingcapital in analyzing the influence of firm characteristics,outside business factors, and industry effect. Theirresults showed that debt ratio and operating cash flowevaluated by both WCR and NLB exert influence onworking capital.

Specifically, Kim, Mauer, and Sherman (1998)analyzed the determinants of liquidity holdings for asample of U.S. companies. They developed a model ofoptimal corporate investment in liquid assets based ona cost-benefit trade-off between the holdings of liquidassets and the benefits of minimizing the need to fundprofitable future investment opportunities with costlyexternal financing. They found those firms facing highercosts of external financing, having more volatile earn-ings, and with relatively lower returns on assets holdsignificantly larger liquid assets.

In the same way, Opler, Pinkowitz, Stulz, and Wil-liamson (1999), in their study based on U.S. firms, foundthat small firms and firms with strong growth opportu-nities and riskier cash flows hold larger amounts ofcash. The study by Pinkowitz and Williamson (2001)examined the cash holdings of firms from United States,Germany, and Japan. The results obtained by Pinkowitz

and Williamson were similar to the Opler et al. (1999)findings. However, in addition to Opler et al. (1999),they found that the monopoly power of banks had asignificant impact on cash balance.

Ozkan and Ozkan (2004) examined the empiricaldeterminants of cash holdings for a sample of U.K.firms. The results revealed that managerial ownershipplayed an important role in determining corporate cashholdings in the United Kingdom. The results showedthat board composition and the presence of ultimatecontrollers do not have a significant impact on cashholdings.

Nazir and Afza (2008) examined the various factors

that determine working capital requirements for 204manufacturing firms for the period 1999 to 2006 inPakistan. The results based on panel OLS estimationfound that operating cycle, leverage, return on assets(ROA), and Tobins q are the internal factors that sig-nificantly influence working capital. The results alsoshowed that working capital management practices arealso related to industry and that different industriesare following different working capital requirements.

Kim et al. (1998) and Opler et al. (1999) estimate thedeterminants of cash holdings. The summaries of thetwo studies are consistentcash varies inversely withsize and leverage but varies directly with the degree of

asymmetric information and cash flow volatility. Thesefindings support the transactions, precautionary, andspeculative motives for holding cash developed byKeynes. The only difference in their works is thatKim et al. (1998) report a significant negative relationbetween cash and cash flow, while Opler et al. (1999) esti-mate a direct relation between the cash and cash flow.

Sample Characteristics and Sources of Data

The study utilized data obtained from 66 purposivelyselected firms from the 100 listed nonfinancial firms onthe Nigerian Stock Exchange (NSE). The quoted com-panies covered in this study are dispersed over manystates in the country However, many of them have theirheadquarters located in Lagos State; this is as a result ofthe fact that Lagos is the commercial nerve center ofthe country. Most of the data used in this study weresourced from the annual reports and statement ofaccounts of the selected firms, obtained from the head-quarters of the companies and from the NSE office inIbadan, Oyo state. Only firms listed before 1999 and still



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in operation through the end of the 2007 financial yearwere chosen.

The study only involved firms that were listed in thestock market as information on the unlisted companiesare not readily available. Indeed, the management ofmost unlisted firms was not always ready to divulge infor-mation on their companies.4 The sample of firms cut

across 15 sectors of the NSE classification: automobileand tire, breweries, building materials, chemical andpaints, computer and office equipment, conglomerates,construction, food beverages and tobacco, healthcare,industrial=domestic products, machinery, packaging,petroleum, printing and publishing, and real estate.5

METHODOLOGY

In examining the determinants of working capitalrequirements of firms in Nigeria, the study employspanel data procedures as the sample contains dataacross firms and over time. In the estimation, three esti-mation models were adopted, namely, pooled OLS,fixed effects, and random effects. The use of pooledOLS is anchored on the assumption that there are nogroup or individual effects among the firms. However,as panel contains observation on the same cross-sectional units over several time periods, there are mostlikely to be cross-sectional effects on each firm or on aset of group of firms. To take care of this problem, weuse other estimation techniques: fixed effects and ran-dom effects. Fixed effect approach takes into consider-ation the individuality of each firm or cross-sectional

unit included in the sample by allowing the interceptto vary for each firm while assuming that the slope coef-ficients are constant across firms. Random effects, onthe other hand, assume that the individual or groupeffects are uncorrelated with other explanatory variablesand can be formulated.

Model Specification

The general model specification is represented by thefollowing equation:

WCRit a0 a0Xit biZit eit i 1; . . . ;n t 1; . . . ;T

i

1

where X is a vector of time-varying independent vari-ables and Z is the vector of the control variables. a0 isa firm-specific intercept representing unobservable indi-vidual characteristics,6 and eit is a white noise error termfor firm iat time t. In this equation, it is considered thatthe error term is distributed independently and identi-cally in a manner that the variance is equal to zero.

The dependent variable is the working capital. For thisstudy, working capital was measured in two ways. Thefirst measure is WCR defined as the difference betweencurrent assets less current liabilities. The second measureis called the CCC. The variable CCC is measured as thesum of number of days accounts receivable and thenumber of days inventories minus the number of days

accounts payable.7

However, to reduce the influence offirm size, both measures of working capital were deflatedby total assets.

The time-varying independent variables that wereincluded in the model are sales growth, operating cycle,firm size, and leverage. Thus, specifying the modelexplicitly, we have:

WCRit a0 a1SGRit a2OPC a3SIZit a4RATAit

a5LEVit a6it GDP a8CONVj; t eit . . .

2

Equation 2 states that working capital requirementsmeasured as difference between working current assetsless current liabilities (WCR) and CCC is a function ofsales growth, operating cycle, firm size, proportion ofa firms assets accounted for by fixed assets (RATA),leverage (LEV), and business indicator measured asthe growth rate of the level of economic activity(GDP) and control for permanent working capitalrequirements (CONV) measured as minimum workingcapital ratio (MWC) or average working capital ratio(AWC).8

Sales growth (SGR) is calculated as annual per-centage change in growth given as [Salest salest 1]=

salest 1. Operating cycle (OPC) is the sum of days ininventory and days in accounts receivable. Firm size(SIZ) is the natural logarithms of sales deflated by totalassets. RATA is the ratio of fixed financial assets tototal assets. Fixed financial assets are shares in otherfirms (mainly affiliated) firms, intended to contributeto the activities of the firms that holds them and loansthat are granted with the same purpose. LEV is mea-sured as the ratio of total debt to net assets. Net assetsare net fixed assets plus net current assets, where netcurrent assets are current assets minus current liabilitiesexcluding interest-bearing short-term debt for workingcapital. Net assets equal capital employed because capi-tal employed includes total debt and net worth. Grossdomestic product growth rate (GDP) is defined as theannual growth rate of GDP. CONV is control for per-manent working capital requirements and is measuredin two ways: MWC and AWC. The MWC is eachfirms minimum working capital requirements dividedby the firms average total assets. The AWC is eachfirms working capital requirements divided by averagetotal assets.9

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EMPIRICAL RESULTS

Descriptive Statistics

Table 1 provides further information on the series emp-loyed in our study. The working capital requirementsvariable has a mean of 1,913,137 naira, which is highestin 2007 and at its minimum in 2001. The positive andhigh values of working capital requirement indicate thatcompanies are maintaining a relatively loose policyregarding their working capital management. In the pro-sperous period of high economic growth rate and highsales growth rate, the working capital ratio is quite highcompared to other years.

The cash conversion cycle used as a proxy to checkthe efficiency in managing working capital is on average95 days and standard deviation is 127 days. Firmsreceive payment against sales after an average of 53 daysand standard deviation is 62 days. Firms wait an aver-age of 46 days to pay their purchases with standard devi-

ation of 187 days. It takes an average of 93 days to sellinventory with standard deviation of 74 days.The statistics in Table 1 show that profit was highest

between 2001 and 2003 but dropped below sampleaverage between 2004 and 2006. It, however, increasedabove sample average in 2007. Firm size is increasingwith the passage of time. Leverage tends to be relativelystable over the years. However, it recorded extraordi-nary increase in 2002. Sales growth falls below the sam-ple mean over the period 1999 to 2003. However, thereverse was the case between 2004 and 2007; salesgrowth far exceeded the sample mean during this per-iod. This might possibly reflect the increase in the price

of oil that led to increase revenue in the latter period of1999 to 2007. Increased oil revenue might have posi-tively affected consumers demand and, thus, firmsproduction.

REGRESSION RESULTS

The results for the determinants of working capitalrequirement (WCR and CCC) using pooled OLS andfixed-effects panel methods respectively are presentedhere.10 Each econometric methodology is used to esti-mate three variations of Equation 2. Model 1 is the base

model of estimated Equation 2. Model 2 controls forpermanent working capital via the minimum WCRratio, and model 3 controls for permanent componentof WCR using the AWC requirements ratio. In the sameway, Equation 4 is the base model and estimated Equa-tion 2 using panel fixed-effects methodology. Also,adopting panel fixed-effects approach, models 5 and 6control for permanent WCR via minimum and AWCratios, respectively.

Pooled OLS Results

The results of the pooled OLS as shown in Table 2

are quite satisfactory. The adjusted R2 for the modelsranges from .917 to .959. This simply suggests that theindependent variable explain 92% of the variation inthe dependent variable. The high adjusted R2 showsthe independent variables explain most of the cross-sectional variation in working capital management. Inother words, there is no problem of omitted variable.Moreover, many of the coefficients are significant andconformed to a priori expectation. The F-statistic issignificant for all the models. The information criteriaused (Schwarz and Akaike) are as reported in Table 1.The Durbin-Watson statistic reported is obtained bycomputing the first-order residual correlation on the

stacked set of residuals.11,12 The reported intercept forthe fixed-effects models is the average value of the fixedeffects.13

TABLE 1

Descriptive Statistics Results (means by year)

WCR PROF LEV SGR RATA SIZ PAY CCC ARE INVT MWC AWC N

Means 1,913,147 8.188 4.237 2,119,588 0.403 6.393 45.549 94.596 52.770 93.058 5.015 0.310 594S.D. means

by year

4,756,876 16.177 26.925 5,994,663 0.534 0.873 187.463 127.283 61.781 74.615 5.728 0.213

1999 1,055,266 7.473 2.844 1,011,445 0.347 6.134 54.267 114.046 58.917 109.396 2.789 0.310

2000 980,399.3 6.571 3.185 889,749.3 0.471 6.201 70.766 88.928 54.828 104.866 2.871 0.3102001 887,944.5 11.081 3.234 1,863,673 0.366 6.288 60.271 86.580 48.718 98.132 3.047 0.310

2002 1,316,234 10.955 12.433 1,752,251 0.393 6.326 60.525 109.187 56.815 112.897 3.967 0.3102003 1,791,749 11.017 3.579 1,890,106 0.385 6.404 22.392 121.403 56.286 87.509 4.644 0.3102004 1,739,611 5.573 3.890 3,085,239 0.516 6.465 3.360 78.114 52.608 80.265 4.871 0.310

2005 2,603,620 6.088 3.740 3,280,462 0.383 6.508 49.776 78.723 47.948 80.551 5.989 0.3102006 2,856,524 6.397 2.504 2,721,408 0.384 6.572 40.887 88.564 48.136 81.315 7.378 0.308

2007 3,986,972 8.533 2.723 2,581,963 0.383 6.641 47.693 85.567 50.665 82.595 9.580 0.310

Note. The definition and measurements of all the variables in Table 1 is as given in Appendix 2. The SGR reported is the means of the differencebetween current and last years sales. The nonratio variables are expressed in millions of naira except WCR.



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The results show a positive relationship between sales

growth and working capital in models 1 and 3. How-ever, the coefficient of sales growth is negative in model2 but not significant. Using model 3 as a lead, the resultshows that increased sales growth leads to increasedworking capital requirements. A 1% increase in salesgrowth will lead to .035 increases in working capitalrequirements.

The coefficient of operating cycle (OPC) used to mea-sure working capital management efficiency of firms ispositive and statistically significant at 1% level of signifi-cance in the three models. This means the higher thedays of operating cycle, the higher the working capitalthat would be required by firm as operative necessity.

The implication of this is that if firms want to reduceits investment in working capital in order to capitalizesome profitable projects, the operating cycle needs tobe optimized. For each model, working capital require-ment varies directly with size and the estimated coeffi-cients have statistical significance at the 1% level. Thiscorroborates the view that larger firms have more finan-cing alternatives available; hence, these firms more easilyafford investments in working capital requirements. The

result supports finding by Almeida, Campello, and

Weishbach (2004), who found that larger firms are lessfinancially constrained firms and hold less cash thansmaller firms.

The results show that leverage is strongly and nega-tively related to the working capital requirement of thefirm. The estimated coefficients have statistical signifi-cance at the 1% level. This indicates that with a risingdebttototal assets ratio, the firms are supposed topay more attention to efficient management of workingcapital to avoid much capital being tied up in accountreceivables and inventories. Hence, firms with anincreasing debttototal assets ratio (high leverage)show lower working capital requirements. This indeedsupports the pecking order theory.

As expected, the controls (minimum and averageworking capital) both have significant positive effecton working capital requirements. Their coefficients aresignificant at 1% level in each equation. This result sup-ports the view that firms must maintain a minimum levelof net operating working capital.

The measure of business indicator (growth rate ofeconomic activity) has significant negative effect on

TABLE 2

Empirical Results of the Determinants of Working Capital

WCR

Pooled OLS Fixed Effect

Without

Control 1

Without

Control 2

Without

Control 3

Without

Control 4

Without

Control 5

Without

Control 6

C 18.501

(23.784)

13.595

(24.485)

18.581

(25.442)

22.377

(9.539)

11.998

(169.700)

20.323

(8.816)SGR 0.019

(1.373)

0.017(1.021)

0.035

(2.032)0.004

(0.194)

9.55E05(1.040)

2.43E05(0.001)

OPC 1.140

(19.622)

0.881

(19.795)

1.060

(20.416)

1.012

(12.985)

0.001

(1.071)

1.015

(12.917)SIZ 13.383

(48.859)

13.655

55.400

13.262

(42.513)

16.770

(11.451)

0.047

(1.170)

17.267

(11.705)RATA 0.003

(0.096)0.104

(4.958)0.054

(2.202) 0.063

(1.782) 0.0004(0.830)

0.061

(1.667)

LEV 0.090

(3.149) 0.099

(5.366) 0.113

(4.722) 0.066

(1.906) 0.0001(0.802)

0.061

(1.760)

GDP 0.088

(3.434)

0.180

(7.842)0.100

(3.104)

0.020(0.503)

0.0003(0.787)

0.041(1.014)

MWC 0.474

(15.473) 0.999

(1373.874)

AWC 1.057

(8.878)

7.557

(2.503)Adjusted R2 0.917 0.959 0.929 0.963 0.965 0.956Schwarz criterion 1.520 0.826 1.384 1.646 6.152 1.655

F-statistic 761.681 1380.94 766.782 129.761 327601.4 128.369

Akaike 1.452 0.748 1.305 0.963 6.847 0.962Durbin-Watson statistic 0.724 0.529 0.867 1.550 1.653 1.556No. of observations 410 410 410 410 410 410

Note. The figures in parentheses indicate t-statistics.Significance at 10%.Significance at 5%.Significance at 1%.

46 O. O. AKINLO


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working capital requirement in almost all the modelsexcept in pooled OLS without control. However, thevariable is majorly significant when CCC is used as mea-sure of working capital. This seems to conform to apriori expectation. As earlier pointed out, fluctuationof general economic activity in the long run is expectedto be negatively related to working capital. It is not easy

for a firm to raise money during the period of economicfluctuations, when cash supply is relatively tight. Hence,to retain capital for daily operations, working capitalrequirement must be kept at a higher level, and businessindicator is expected to be negatively proportional toworking capital. Moreover, in the period of economicfluctuations, the expansion of a company may not beas smooth as expected, with possibly longer time periodsfor collecting accounts receivable or possibly expendedinventories due to decline in sales. Hence, a relativelyhigh net volume of working capital requirements mayoccur. Over, the study period, the Nigerian economydid not witness significant progress in terms of economic

growth. The only sector that experienced boom duringthe study period was the financial sector. Unfortunately,the boom in the financial sector did not filter into theproductive sector, especially the manufacturing sector.Banks were not ready to extend credit to the manufac-turing sector. The result was the collapse of manufactur-ing firms during the study period.

Fixed Effects Results

The results of the fixed effects are presented in Table 2(models 4, 5, and 6). Overall, the results from thefixed-effects models are to a reasonable extent consist-

ent with the pooled results. However, there were minordifferences in the two results.14 These minor differenceswere not unexpected as the OLS estimation does nottake into consideration firm specific differences inworking capital requirements.

Examining the results from the fixed-effects models,this study found that the significance levels of most ofthe coefficients dropped as compared to the pooledOLS. It was discovered from the results of fixed effectsthat operating cost, size, leverage, and minimum work-ing capital are statistically significant and retain the samesign as for the pooled results. This is particularly truewith models 4 and 5. Hence, one can safely conclude thatthe results of both pooled OLS and fixed effects are to areasonable extent similar. All the significant variableshave the same sign and their magnitudes very close.

ROBUSTNESS CHECK

As a way of checking the robustness of this analysis onthe determinants of working capital requirement, the

study estimated Equation 2 using cash conversion cycle(CCC) as a measure of working capital management.The results are as shown in Table 3. The pooled OLSresults without and with controls are as shown in Equa-tions 13 of Table 2 while the results from fixed-effectsmethod without and with controls are as shown inEquations 46, respectively, in Table 2.

Just as in the case of the first measure of workingcapital (WCR), the models performed well. The adjustedR2 for the equation are very high ranging from 74% to99.2%. The F-statistics for all the models are highlysignificant. The coefficients of many of the independentvariables are also significant.

Overall, the results from the two measures of workingcapital are quite consistent. However, few minor areasof differences are discernible. The coefficient units ofoperating costs, leverage, GDP, and MWC are statisti-cally significant and retain the same sign as for pooledresults when we use actual working capital of the firms.The coefficient of sales growth obtained using CCC as

measure of working capital management tallies withthat obtained using actual working capital except inmodel 1 (the base model) as against positive sign.

The result from the fixed-effects models using CCC asproxy for working capital are in every respect consistentwith that obtained using the difference between currentassets and liabilities as a measure of working capital.The signs are the same for all the variables and theirmagnitudes are quite close. The only area of differenceis the coefficient of size, which comes out negative whenCCC is used as a proxy for working capital. However,this result is unexpected because CCC actually measuresthe efficiency of working capital management by firms.

This simply means that the larger the firm size, theshorter the CCC, or the smaller the firm size, the longerthe CCC. This suggests that the smaller firms shouldlook for ways to shorten their CCC. This result indeedcorroborates the finding from the correlation analysis.

The coefficient for RATA with CCC as dependent vari-able has a negative sign in both models 1 and 3 comparedto a positive sign obtained when the difference betweencurrent assets and current liabilities (WCR) is used. How-ever, the coefficient of RATA when CCC is adopted asworking capital is not significant (in both models 1 and3). Thus, conclusive inference cannot be drawn from it.However, in the two measures of working capital, thecoefficient of RATA is positive and significant in model2. This simply suggests that as fixed to total assets for afirms increases, the working capital also increases.

CONCLUDING REMARKS

In general, working capital management is very impor-tant because of its effects on the firms profitability and



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risk, and thus its value (Smith, 1980). However, it hasattracted less attention of researchers and practitioners

in developing countries like Nigeria. Therefore, thiscurrent study uses both internal and external factors toexplore the determinants of working capital requirementsof firms in Nigeria. We use operating cycle, leverage, pro-portion of firms assets accounted for by fixed assets, salesgrowth, and permanent and minimum working capital asinternal firmrelated factors and level of economicactivity as external macroeconomic variable.

We have found that sales growth, size, permanentworking capital requirements, and firms operating cycleare primary drivers of working capital requirement.Leverage is significantly negatively related to workingcapital requirement, while the level of economic activityis significantly and positively related to working capitalrequirement, indicating that a firm will raise its debtratio when its short-term capital is depleted.

These results are quite consistent with earlier studiesby Alfa and Nazir (2008), Chiou and Cheng (2006),and Wu (2001), among others. Although a few of thefindings seem to conflict with some earlier studies onthe issue, the development may be attributed to theevolving market of Nigeria. The reasons for this

contradiction should therefore constitute an area offuture research. Finally, disaggregating the sectors into

distinct common group should equally be explored insubsequent research to ascertain if the same sets of fac-tors determine their working capital requirements.

NOTES

1. Several studies have articulated theoretically the various dan-gers that are associated with excessive and inadequate working capitalin any firm (for details, see Ramamorthy [1976], Pandey [2006], Blinder

& Maccini [1991], and others).2. Some other studies that have examined thecharacteristics, deter-

minants, and performance of firms in Sub-Saharan African countries

include Damoense-Azevedo and Jordaan (2011), Kyeroboah-Coleman

and Amidu (2008), Dane (2008), and Wirston and Dadzie (2007).3. However, it needs be pointed out that several ingenious inven-

tory management approaches have been devised in modern times by

firms to attenuate the problem of inventory accumulation. Theseinclude just-in-time approach, outsourcing approach, and computer-ized inventory control systems.

4. Financial institutions such as banks, insurance companies, etc.were purposively excluded from the sample due to the format used in rep-

orting their balance sheets and the different components of working capitalsuchas stock thatare missing fromthe balance sheet. Thismakes their capi-tal structure significantly different from those of nonfinancial firms.

TABLE 3

Empirical Results of the Determinants of Working Capital

CCC

Pooled OLS

Without Control 1

Pooled OLS

With Control 2

Pooled OLS

With Control 3

Fixed Effects

Without Control 4

Fixed Effects

With Control 5

Fixed Effects

With Control 6

C 2.011

(3.597)

2.833

(5.075)

2.047

(3.557)

5.618

(2.185)

26.055

(36.850)

3.531

(1.484)SGR 0.004

(0.317)

0.038

(2.466)

0.012

(0.697)

0.005

(0.313)

0.001

(0.100)

0.001

(0.077)OPC 1.282

(31.014)

0.999

(35.153)

1.194

(29.190)

1.217

(23.738)

0.160

(4.733)

1.221

(22.983)SIZ 0.324

(1.302)0.138

(0.612)0.446

(1.771)2.714

(1.614)0.009

(0.820)3.218

(1.864)

RATA 0.055(1.485)

0.049

(3.025)0.003

(0.116)0.049

(1.791)0.002

(0.363)0.047

(1.646)LEV 0.098

(3.414)

0.107

(6.519)

0.122

(4.743)

0.068

(2.091)

0.002

(0.363)

0.064

(1.960)GDP 0.057

(3.282)

0.187

(7.256)

0.069

(3.071)

0.060

(1.244)

0.027

(1.946)

0.081

(1.678)MWC 0.445

(12.999)

0.881

(40.698)

AWC 1.106

(8.547) 7.642

(2.677)

Adjusted R2

0.744 0.877 0.795 0.884 0.992 0.885Schwarz criterion 1.243 0.525 1.034 1.202 1.473 1.207F-statistic 199.229 416.684 227.575 46.405 738.483 46.121

Akaike 1.175 0.447 0.956 0.516 2.169 0.511Durbin-Watson

statistic

0.557 0.486 0.723 1.405 1.577 1.416

No. of observations 410 410 410 410 410 410

Note. The figure in parentheses indicates t-statistics.Significance at 10%.Significance at 5%.Significance at 1%.

48 O. O. AKINLO


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5. The number of firms in each of the 15 sectors selected for thestudy is shown in Appendix 1.

6. The intercept ao is for the general specification for the pooleddata. It needs be pointed out that one can choose between alternativespecification for ao. In the case of no intercept (i.e., identical intercept

for all pool members): ao a. However, for fixed effect where differentintercepts are estimated for each pool member, ao ai. Finally, for ran-

dom sheets where intercepts are treated as random variables acrosspool members: a0 ai, a(ai ait) 0.

7. The definition and measurement of number of days accountreceivable, account payable, the number of days inventories, and othervariables in the regression are given in Appendix 2.

8. Firms generally maintain a minimum or permanent level ofworking capital to support operations since it is not likely that saleswill drop to zero. Hence, the current level of working capital should

be an increasing function of minimum or permanent working capital.Subsequently, we control for permanent working capital requirements

by adding proxies for the variables in Equation 1.9. All the variables in this study and their measurements are lar-

gely adopted from existing literature.10. Both fixed effects and random effects specifications of the

models were estimated but the Hausman (1978) test conducted showedfixed effects as the preferred model. This explains why we havereported the results for random effect estimation. The Hausman

(1978) test is used to determine which estimation model fixed effectsor random effects best explain ones estimations.

11. In general, thevalues of Durbin-Watson statistic forpooled OLSandfixed effects show that theproblem of autocorrelationtendsto reduce

with the use of fixed-effects approach. However, we may not be able tomake conclusive inference on this as the data point is rather short.

12. We tried to reestimate the equation by incorporating an

autoregressive root or lagged value of the dependent variable each;however, we only observed marginal increase in the value of theDurbin-Watson statistics for pooled OLS and fixed effects estimation.

13. Generally, the intercept aai, is computed as aai

Ptyyixx

0ibFE

N

where yyi represents mean of the dependent variable, xxi is the mean

of the nonconstant regressors, bFE is the fixed effect parameters, andN is the cross-sectional units.

14. Essentially, the minor differences in the results from pooled

OLS and fixed effects could be seen in the sign of sales growth, busi-ness indicator measured as GDP growth rate, and ratio of fixed assets

to total firms assets that changed from positive to negative. However,

except for RATA, the coefficients were not significant in most casesand thus a firm conclusion could not be based on them.

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Appendix 1

Selected Firms by Sectors

No. Industrial Sector No. of Firms

1 Automobile and Tyre 32 Breweries 33 Building 3

4 Chemical and paints 65 Conglomerates 86 Construction 4

7 Computer and office equipment 38 Food and beverages 7

9 Health 6

10 Industrial=domestic 711 Machinery=marketing 112 Petroleum 713 Packaging 3

14 Printing and publishing 315 Real estate 1

Total 66

Appendix 2

Definition and Measurement of Variables

Sales growth (SGR): Sales growth is calculated as annual percentage change in growth. This is calculated as [Sales t salest 1]=salest 1.

Ratio of fixed financial assets to total assets (RATA): This is the ratio of fixed financial assets to total assets. Fixed financial assets are shares inother firms (mainly affiliated) firms, intended to contribute to the activities of the firms that holds them and loans that are granted with thesame purpose.

Firm size (SIZ): This is defined as the natural logarithms of sales.

Leverage (LEV): This is measured as the ratio of total debt to net assets. Net assets are net fixed assets plus net current assets. Where net currentassets are current assets minus current liabilities excluding interest-bearing short-term debt for working capital. Net assets equals capital employedbecause capital employed includes total debt and net worth.

Gross domestic product growth tate (GDP): Growth rate of gross domestic product measures as the annual growth rate.Minimum working capital (MWC) ratio: This variable is defined as each firms minimum working capital requirements divided by the firms average

total assets.

Average working capital (AWC) ratio: This variable is calculated by taking the average of each firms working capital requirements and scaling it bythe firms average total assets.

Account receivables (ARE): The number of days account receivables (ARE) is calculated as (accounts receivables=sales) 365. This variable repre-sents the average number of days that the firm takes to collect payments from its customers. The higher the value, the higher its investment in

account receivable.Account payable (PAY): The number of days accounts payable (PAY) reflect the average time it takes firms to pay their suppliers. This is calculated

as (account payable=purchases) 365. The higher the value, the longer firms take to settle their payment commitments to their supplier.Inventory turnover days (INVT): the number of days of inventory (INVT) is calculated as (inventories=purchases) 365. This variable reflects

the average number of days of stock held by the firm. Longer storage times represent a greater investment in inventory for a particular level

of operations.Operating cycle (OPC): This is the sum of days in inventory and days in accounts receivable.Working capital requirement (WCR): this is defined as working liquid assets less working liquid liabilities. This WCR (account receivables

inventories) (accounts payablesother payable).

Cash conversion cycle (CCC): this variable is calculated as the number of days account receivable plus the number of days of inventory minus thenumber of days accounts payable. The longer the CCC, the greater the net investment in current assets, and hence the greater the need for finan-cing of current assets.

50 O. O. AKINLO

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