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The Islamic Liquidity Ratio:

Towards a Sharia-compliant Corporate Liquidity Measure

Abstract.

We develop ―Islamic Sharia Compliant‖ measure of corporate liquidity. The Islamic

liquidity ratio ―IR‖ overcomes the ―bakhs‖, ―gharar‖, and ―Implicit riba‖ components of the

conventional liquidity measures. The IR provides a fair valuation of corporate liquidity

according to Islamic Sharia law. Our IR has two desirable properties. First, it minimizes the

undervaluation problem inherent in the Quick-ratio and cash-based liquidity measures. Second, it

also reduces the uncertainty problem inherent in the Current ratio. Our results show that firms‘

liquid inventory holdings affect corporate dividend policy.

Keywords: Islamic finance, sharia law, corporate liquidity, ratio analysis.

JEL classification: G31; G33; M41

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The Islamic Liquidity Ratio:

Towards a Sharia-compliant Corporate Liquidity Measure

I. BACKGROUND: CORPORATE LIQUIDITY.

Determining the value of corporate liquidity is one of the ten most important unresolved

problems in finance according to Brealey and Myers (2003).

Managing liquid assets is of special importance to all firm stakeholders due to multiple

agency concerns associated with these assets (Jensen and Meckling, 1976 and Smith and Warner,

1979). In their investigation of how financing decisions affect investment and the role played by

debt covenants, Chava and Roberts (2008) document that covenants restricting the CR are

included in 2,098 dollar-denominated private loans (with a combined face value of over a trillion

dollars) made to U.S. corporations during the period 1994 to 2005, and 779 loans have covenants

that specify a minimum QR. DeAngelo et al. (2002) investigate the credit agreements between

the Bank of America and L.A. Gear from December 1990 through February 1997. The initial

agreement contained a covenant specifying a minimum acceptable QR and several follow up

agreements modified the QR covenant over the years 1991, 1992 and 1993.

Corporate liquidity is shown to affect corporate capital structure, dividend policy and

investment policy. Teresa (1993) argues that the optimal amount of corporate liquid assets is

positively associated with the cost of financial distress. Gryglewicz (2011) argues that corporate

liquidity can shed light on capital structure choice, valuation and credit spread. Horne (1983) and

Weston and Brigham (1981) document that firm liquidity is an important managerial

consideration when making dividend decisions. Moreover, in their survey of managerial views

about dividends policy, Baker, Farrelly, and Edelman (1985) show that availability of cash is one

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of the major determinants of corporate payout policy. In his recent study Gryglewicz (2011)

argues that the interaction between liquidity and solvency can explain the empirical patterns in

cash holding and dividends policies. Chava and Roberts (2008) show that debt covenant

violations related to corporate liquidity (measured by the CR) affect firms‘ investment policies

through creditors‘ threat of transferring control.

Corporate liquidity determinants and implications have received considerable attention in

the finance literature. Kim et.al. (1998) model the corporate decision to invest in liquid assets

(measured as the sum of cash and marketable securities); their model predicts that the optimal

investment in liquidity is positively related to the cost of external finance and the importance of

corporate liquidity increases during periods of financial distress. On the other hand, Riddick and

Whited (2009) show that income uncertainty increases the need for liquidity even more than the

cost of external finance. Wang (2002) shows that aggressive liquidity management enhances

operating performance and is associated with higher firm value both in Japan and Taiwan. Myers

and Majluf (1984), Almeida et. al. (2004), and Archarya. et al. (2007) argue that information

asymmetry between managers and external investors increases the value of corporate liquidity as

firms are not required to frequently tap external capital markets to fund their capital

expenditures.

Gryglewicz (2011) defines corporate liquidity as ―a short term characteristic that

measures the ability of a firm to pay its obligations on time‖. But, do cash holdings, the QR, or

the CR really measure this ability? DeAngelo et al. (2002) posits that they do not. On the one

hand, QR can potentially understate the ability of some firms to meet their obligations, especially

those with unique abilities to liquidate their non-cash current assets. On the other hand, the CR

can potentially overstate the liquidity of a firm, particularly for firms with poor ability to

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liquidate their non-cash current assets. More importantly, the biases stated above are not solely

systematic, but depend on the nature of inventory held by each firm and its operational

efficiency.

Furthermore, Gitman (1974) addresses the drawbacks of using static liquidity ratios and

suggests a working capital management approach or the Cash Conversion Cycle (CCC) as a

better ―dynamic‖ measure of corporate liquidity. Richards and Laughlin (1980) also recommend

that decision makers and corporate stakeholders focus on emphasizing firms‘ abilities to cover

their obligations with cash flows extracted from liquidating inventory and receivables within the

normal course of corporate operations. Knight (1972) argues that it is inappropriate to examine

the optimal level of the several current assets independently. Gaur, Fisher, and Raman (2005)

show that inventory turnover varies widely across retailers and over time. They also find an association

between inventory turnover and gross margin, as well as capital intensity and sales surprise.

This paper contributes to the corporate liquidity literature as well as the Islamic finance literature.

First, we show that incorporating liquid inventory in measuring corporate liquidity affects important

corporate decisions like payout policy. Second, our liquidity measure partially solved the problems of

more static liquidity ratios like Current ratio and Acid test ratio. Third, we introduce Sharia Compliant

liquidity measure that can be used by Islamic Banks and Sharia compliant funds.

The remainder of this paper is organized as follows; Section II introduces the issue of corporate

liquidity under the principles of the Islamic Sharia law. We also develop the Sharia compliant liquidity

ratio. Section III summarizes study data and methodology. Section IV presents the effect of using Sharia

compliant liquidity ratio on benchmarking and ratio analysis. Section V investigates the relationship

between corporate inventory characteristics and corporate payout policy. And Section VI concludes

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II. SHARIA LAW AND CORPORATE LIQUIDITY

Standard financial ratios can violate Sharia law. Sharia law consisted of the rules that are

set forth by the holy Quran and by Prophet Mohamed that were recorded and verified in the

Sunna. Since standard financial ratios violate basic rules in Sharia, such standard ratios cannot

be employed by devout Muslims to value a firm or to determine the financial strength of a firm.

This presents a serious problem for analysts and investors who adhere to the teachings of Islam.

In this paper, we explore the relationship between a basic financial concept, i.e., liquidity,

the standard ratios used to categorize liquidity (the current and quick ratios), and the fundamental

teachings of Sharia law that prohibits bakhs, gharar, and riba. We demonstrate that both standard

liquidity ratios, i.e., the current ratio (CR) and the quick ratio (QR), violate the teachings of

Islam. Thus, devout Muslims cannot use or apply these liquidity ratios. The main contribution

of this paper is to develop an Islamic-liquidity ratio (IR) that is in full compliance with Sharia

law. Thus, our IR can be used by devout Muslims who are interested in valuing a firm or

measuring the financial health of a firm.

Developing Sharia-compliant financial and accounting measures is of critical importance.

Muslims account for 22.74% of the world‘s population in 2013.1 The percent is to grow as

currently Islam is the fastest growing world religion. Another way to see the importance for the

need of Sharia-compliant financial ratios is to consider the growth in Islamic business enterprise

and in Islamic-compliant funds. Islamic financial assets around the world hit $1.3 trillion in

2011, a 150 percent increase over five years.2 Given the growing importance of Islamic business

activity, it is surprising that no academic papers have addressed the fact that standard financial

1 http://www.indexmundi.com/world/demographics_profile.html

2 http://www.reuters.com/article/2012/03/29/islamic-finance-growth-idUSL6E8ET3KE20120329

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ratios violate Sharia law and thus cannot be used by devout Muslims. This paper attempts to fill

this gap by developing a Sharia-compliant liquidity ratio.

In this section, we first define and discuss the topics in Sharia Law that are relevant to

developing a corporate liquidity measure. Next we develop a Sharia-compliant ratio, which we

label the Islamic-liquidity ratio (IR).

a. Sharia Law - Explanation

We argue that the conventional static liquidity measures do not comply with Sharia law in

multiple ways. First, the QR undervalues corporate liquidity. This is true as the QR considers

inventory as a non-liquid asset. However, 30 days is standard business practice to make payment.

At least some inventory can be liquidated over this time. Thus, the practice of not fairly valuing

the inherent liquidity of a firm‘s inventory over the standard 30 day grace period violates the

principle of ―bakhs‖. Bakhs is the Arabic word for undervaluation. Bakhs or undervaluation is

strictly prohibited in three different verses of the holy Quran. To be Sharia-compliant, Islamic or

Sharia financial analysis should strive to use financial ratios that do not undervalue firm assets.

That is, Sharia-compliant financial ratios should not violate the concept of bakhs.

A second commonly used liquidity measure is the CR. However, the CR includes multiple

sources of ―gharar‖. In Arabic, gharar is most equivalent to uncertainty. Islam prohibits business

transactions and practices with ―avoidable‖ uncertainty with regard to: price, timing, quality,

occurrence of the transaction, etc... The CR classifies the full amount of inventory as a liquid

asset. However, classifying the full amount of inventory as liquid includes gharar component.

For example, a firm is not certain when it will be able to liquidate its inventory; in fact, there is

uncertainty as to whether the entire inventory can be liquidated. Since liquidation is a future

transaction, there is also uncertainty on the price of the inventory. Thus, the CR violates Sharia

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law. Sharia-compliant financial ratios should minimize exposure to gharar to that gharar that is

unavoidable.

Riba, or interest, is strictly prohibited in 4 different verses of the holy Quran. Thus,

payment or receipt of riba is a strict violation of Sharia law. Any Sharia-compliant financial

ratio should be calculated such that there no riba is involved.

A Sharia-compliant measure of corporate liquidity should lie between the two extreme

standard liquidity ratios, i.e., between QR and CR. In Sharia, bakhs is a command than gharar, as

gharar is allowed as long as it is unavoidable, while bakhs is a strict order. We now develop a

Sharia-compliant liquidity ratio that complies with bakhs and riba avoidance, and also attempts

to reduce gharar to that which is unavoidable.

b. Sharia-compliant Liquidity Ratio - Development

We argue that inventory that could be liquidated within 30 days -within normal firm‘s

operations- can be regarded as cash. Inventory turnover reports how many times a firm turns its

inventory during specified period of time, usually one year. We use the firm-specific turnover

ratio to fairly price the value of inventory that can be liquidated over a 30 day grace period.

Using turnover is also consistent with the concept of reducing the degree of price uncertainty

(i.e., price gharar). According to bakhs prohibition, a Sharia-compliant liquidity ratio must

attempt to fairly price the value of liquidity available to pay debt due. Since this is a strict order

and a 30 days grace is standard in business practice, using less than 30 days to value the liquid

value of inventory would under valuate firm‘s liquidity (bakhs). Using more than 30 days would

violate the principle of interest prohibition (riba). i.e, when a firm uses less liquid inventory as

collateral to get immediate cash, this creates a burden to pay interests as payment will be made

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after 30 days. The price uncertainty associated is unavoidable in this case, but it is minimized

due to the short duration involved.

Using annual data from the financial statements, inventory turnover is calculated as:

ITOit = Cost of Goods Sold it

Inventory it (1)

Hence the number of days required to turn the inventory stock once (days of sales in inventory)

is:

DSIit = 365

ITO it (2)

DSI informs us how long, on average, it takes to convert inventory to cash. However, DSI

may or may not be consistent with Sharia. To determine the maximum number of days to

convert inventory, one must consider standard business practice and riba. The target Islamic

liquidity measure should specify the number of days, N, that satisfies three requirements. First,

an IR should not explicitly or implicitly include or promote any interest bearing business

practice, i.e., riba should be avoided.3 Second, N should be long enough to avoid undervaluing a

firm‘s liquid inventory, i.e., bakhs should be avoided. Finally, N should be short enough to

reduce the remaining sources of gharar, the uncertainty regarding how long the firm will

continue to have the same rate of ITO and the inventory liquidation price, i.e., gharar should be

reduced to that which is unavoidable. Our definition of liquid assets will then take the general

form:

𝑙𝑖𝑞𝑢𝑖𝑑 𝑖𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦 = 𝑁

𝐷𝑆𝐼 × 𝑡𝑜𝑡𝑎𝑙 𝑖𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦 (3)

Liquidity ratios measure a firm‘s ability to meet its financial obligations once they become

due. The QR, as well as more restrictive cash-based measures, consider the entire inventory as a

3 Riba (interest) is strictly prohibited in the Holy Quran in four different verses. See for example, Appendix A,

number 7-10.

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non-liquid asset. However, during standard business conditions, 30 days grace period from

invoice is standard. Most loans and credit lines will not charge interests if the balance is paid

back within a maximum of 30 days. A firm can get credit up to the amount of inventory that it

can liquidate within 30 days, i.e., a firm can use a proportion of its inventory (that which can be

liquidated within 30 days) as immediate cash, and most importantly according to Islamic Sharia,

without being charged interest.

Restricting N to less than or equal to 30 days has two benefits. It eliminates the riba

component to a liquidity ratio. Compared to the CR, an N of 30 days significantly reduces

uncertainty (gharar). By reducing the time horizon for selling inventory from one year to one

month, it is more likely that recent firm performance, like ITO, will remain valid and price

uncertainty is reduced. Within the set {1, 30} of ―riba-free‖ days, 30 days minimizes the

undervaluation of firm‘s inventory (i.e., the bakhs problem is minimized). If an N less than 30

days is utilized, the remaining gharar is reduced, but at the expense of undervaluing a firm‘s

liquid inventory. Since bakhs is mandatory, and gharar is allowed if it is unavoidable, using less

than 30 days increases bakhs at the expense of reducing gharar. Thus, 30 days is optimal

according to Sharia and standard business practice. Since Islamic Sharia allows a certain degree

of gharar which is unavoidable, we use the 30 days cut off point as the target N, and so:

Liquid inventoryit = Total inventoryit ×30

DSI it (4)

And hence:

Illiquid inventory = total inventory – liquid inventory (5)

The IR then will be calculated as in Equation (6) as the ratio of total current assets minus the

approximated amount of illiquid inventory to the total current liabilities

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IR = Curent Assets −illiquid inventory

current liabilities (6)

IR is compliant with Islamic Sharia in multiple ways. First, the IR measures liquidity

without assuming any implicit interest bearing practice inherently assumed in corporate liquidity

measures like the CR. Second, within the riba-free range, IR minimizes the undervaluation or

bakhs of a firm‘s inventory. Finally, IR reduces the gharar or uncertainty inherent in the

calculation when compared with the CR in two different ways: (i) IR uses a firm‘s ability to

turnover inventory in measuring liquidity, and (ii) by restricting N to 30 days, IR restricts the

strong assumption that the firm will retain its ITO, i.e., the IR assumes the firm will do so for 30

days.

Not only is our IR Sharia compliant with bakhs, gharar, and riba, but it provides a fair

approximation of corporate liquidity. The following example illustrates this fairness property of

IR as a measure of corporate liquidity. Table I presents hypothetical data for five firms with

similar CRs, but with varying inventory holdings and varying abilities to liquidate inventory.

[Please insert Table I here]

Table I shows how ignoring a firm‘s ability to liquidate inventory will result in unfair

measures of corporate liquidity. When the CR is used to measure corporate liquidity, all five

firms appear to possess equal short-term liquidity. This happens since the CR ignores the fact

that these five firms hold completely different amounts of inventory and have different abilities

to liquidate these inventories. When using QR, firm (A) – despite having the most liquid

inventory, i.e., the lowest DSI – has the worst liquidity ratio. On the other extreme firm (E) –

which has the least liquid inventory figure – has the best ranking by the QR merely because it‘s

relatively small inventory holdings. When IR is used, firm (A), which previously ranked 5th

,

now is ranked as the firm with the best liquidity position.

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III. Data and methodology

Our sample consists of all Compustat firms for the period 1980-2011. In addition to our

proposed liquidity measure we use different measures of corporate liquidity. Cash to current

assets ratio is measured as the total end of year cash balance (Compustat data item 162) divided

by total current assets (Compustat data item 4). CR is measured as the total current assets

(Compustat data item 4) divided by total current liabilities (Compustat data item 5). QR is

measured as the total current assets minus total inventories (Compustat data item 3) divided by

total current liabilities. We proxy corporate dividend policy with two variables: dividend yield

and cash dividends. Dividend yield is the dividends per share (Compustat data item 26) divided

by the closing stock price at the end of fiscal year (Compustat data item 199) multiplied by 100.

Cash dividend is the total amount of cash dividends paid to both common and preferred stocks

(Compustat data item 127).

We prove our conjecture regarding the cash-equivalence of liquid inventory through

summary statistics and then formally by logit and OLS regressions. First, we summarize the

relative size of cash, inventory and liquid inventory holdings of different Fama and French

industries. Then we show the possible impact of ignoring liquid inventory consideration on ratio

analysis and benchmarking. Finally, we show the relationship between liquid inventory and cash-

related corporate policies like corporate payout policy.

[Please insert Table II here]

Table II reports descriptive statistics for study variables. These statistics lends further

support to our conjectures regarding the relative size of inventory holdings versus cash holdings.

For the entire sample, the mean inventory holding is $245 million which is around 40% more

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than the average cash holdings of $178 million. On average liquid inventory represents around

40% of the entire holdings of inventories. US firms on average hold in liquid inventories around

60% of what they hold in cash.

Table III reports Pearson correlation coefficients between study variables. Correlation

coefficient provides several primary insights that support our conjectures. Cash dividend is

highly correlated with the liquid inventory holding with a correlation coefficient of 0.57. The

correlation between cash dividends and the total inventory or illiquid inventory is less strong (.2

and .15, respectively). This gives preliminary evidence that managers don‘t look at their total

inventories when making dividend decision, they rather consider the liquid part only. The

correlations between cash dividends and dividend yield on one hand and dividend determinant

firm specific variables is consistent with prior literature. Dividend is positively related with firm

size and profitability, and is negatively related to firm growth. It is worth noting that correlation

between liquid inventory holdings and size is high at 0.34. it is then important to show that

holding liquid inventory is not a mere property of large firms that has no separate impact on

corporate dividend policy.

[Please insert table III here]

IV Liquidity ratios, Benchmarking and ratio analysis.

DeAngelo, DeAngelo and Wruck (2002) study the collapse of L.A. Gear, a very

successful athletic shoe manufacturer during the late 1980s. They argue that the liquidity nature

of ―non-cash current assets‖ provides managerial discretion during distressed periods. They

assert that ―asset liquidity provides a source of marketable assets that can be monetized to fund

operating losses and buy time for management of firms that experience a decline in growth

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opportunities‖. Particularly, L.A. Gear started its decline in 1991 with a very small cash balance

of $3.3 million. DeAngelo, DeAngelo and Wruck (2002) argue that the liquid nature of L.A

Gear‘s asset structure provided management with six years of strategic and operating discretion

and provided a cushion against raising external funds until they filed for chapter 11 in January

1998. L.A. Gear started the decline phase with a balance of $160 million in inventories with

accounts for 47% of firm‘s current assets. In the section, we show that having such liquid assets

structure is not uncommon in many industries. The fact that liquid ―non-cash‖ current assets can

affect corporate strategic, operational and financing decisions is not uniquely associated with

L.A Gear.

Table IV reports the size of cash and inventories as proportions of current assets as well

as the difference between cash and inventory balances for the Fama and French 48 industries.

Inventories include total inventories held by the firm. Table IV demonstrates that nventories

represent a significant proportion of current assets. For the entire sample, firms hold on average

28% more inventories than cash (i.e., inventories are 27% of current assets versus 21% in cash).

On average, firms in 30 out of the 48 Fama and French industries hold more inventories than

cash. Inventories versus cash holdings vary greatly among different industries. For example, in

the financial sector (Fin) inventories are only 21.1%, (i.e., 8%/38%) the level of cash, while, in

industries like retail (Rtail) inventories are 407.1%, (i.e., 57%/14%) the level of cash.

[Please insert Table IV here]

The assets structure of L.A. Gear that DeAngelo, DeAngelo and Wruck (2002) argue as a

key to the firm‘s resistance to quick failure is very common among USA public firms. However,

total inventories may not be the most appropriate measure of liquid assets as situations exist for

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which a portion of assets are illiquid. For example, a significant part of L.A Gear‘s inventories

had been accumulated because of holding outdated models. Several other scenarios could result

in large illiquid inventory holdings, such as sales inefficiencies, inaccurate marketing forecasts

and production planning inefficiencies. Our definition of liquid inventory partially solves these

problems by defining liquid inventories as those that could be turned into cash within short

period of time, by which we mean 30 days.

Cash is a standard measure of liquidity in the finance literature. However, what we learn

from Table IV is that some industries have very high inventory compared to cash, while others

have the exact opposite relationship. Also, by the antidotal evidence of L.A. Gear, we also learn

that inventory is an important contributor to liquidity and the ability to delay bankruptcy. Given

the importance role of inventory in meeting financial obligations and the large differences in

levels of inventory and cash across industries, it seems prudent to incorporate the differences in

liquidity across industries by including inventory in the liquidity measure. Industries that have a

lot of inventory compared to cash are better able to meet their financial obligations as inventory

does affect a firm‘s ability to raise short term funds. However, not all inventories are liquid.

Table V reports the size of cash and liquid inventories as proportions of current assets as

well as the difference between cash and liquid inventory balances for the Fama and French 48

industries. Again there is significant variation of the proportion of liquidity held in liquid assets

compared to cash. For example, utilities have 277.8% more liquid assets than cash, while drugs

have only 19.5%. Liquid inventories represent a significant proportion of current assets in all

industries. Industries like food, wholesale, utilities, textiles, meals, and boxes have inventories

amounts that are 200% or more of the cash holdings. Thus, liquid inventories represent a

significant component of liquidity across several industries. For such industries, focusing on cash

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as a sole measure of corporate liquidity provides an entirely inaccurate perspective of the options

available to firms have to meet their current obligations. For the entire sample, firms hold on

average 18% of their current assets in the form of liquid inventories, a figure which is very

comparable to the 21% holdings of cash as a proportion of current assets. On average, firms in

20 out of the 48 Fama and French industries hold more liquid inventories than cash. This group

includes industries with higher inventory turnover ratios as well as those with inherently large

stocks of inventories.

[Please insert Table V here]

Liquidity ratios and benchmarking

Benchmarking is a cornerstone in financial statement and ratios analysis. Information like

―firm XYZ has current ratio equal to 2‖ is meaningless, unless this figure is compared with the

correct benchmark. Using the industry average or peers as a benchmark is a common practice

used by both academics and practitioners to conduct financial statements analysis. We argue that

ignoring firm specific abilities in liquidating inventory will result in distorted liquidity measures.

The magnitude of the inaccuracies in measuring liquidity will depend on the magnitude of

inventory holdings as well as how variant are firms with regard to their inventory turnover ratios.

Traditional liquidity ratios will be more inaccurate in industries with high average inventory

holdings as well as high variation in inventory turnover.

This section shows how different is the liquidity information provided by IR compared

with traditional liquidity measures. For each firm/year we calculate the firm‘s liquidity ranking

using both CR and IR. The difference in ranking between CR and IR reflects how different (we

argue also inaccurate and unfair) are liquidity ratios when ignoring inventory liquidation

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capabilities. Table VI reports differences in liquidity rankings for all Fama and French 48

industries for the period 1980-2011. Positive differences mean CR ranks the firm in a lower

position than IR. For example a difference of 10 might reflect a situation where CR ranks the

firm in the 18th

position while IR ranks the firm in the 8th

position. Positive differences means

that CR ranks the firm as relatively less liquid compared to its raking under IR. This positive

differential will be associated with firms with better inventory turnover capabilities than industry

peers. On the other hand, Negative differences mean CR ranks the firm in a higher position than

IR. For example, a difference of -10 means CR ranks the firm 10 places higher than the IR (one

situation is that the firm is ranked in the 18th

position by CR, while IR ranks the firm in the 28th

position). This negative differential could result if the firm has weaker inventory turnover

capabilities than its industry peers. Table VI shows that the average ranking error is higher than

5% in certain industries, for example drugs, oil and telecommunications. This means on average

firms are mistakenly classified as less liquid than 5% of their industry peers. For the entire

sample, the maximum (minimum) difference in ranking is 37% (-43%). This means some firms

are mistakenly classified as less (more) liquid than 37% (43%) of their industry peers. Along this

continuum, most firms will be miss-ranked by CR when compared to industry peers with regard

to liquidity.

[Please insert Table VI here]

Tables V and VI demonstrates that different liquidity measures lead to quite different

orderings of which firms are liquid and illiquid. Table V and VI also shows that firms in some

industries maintain large inventory compared to cash. We argue that highly liquid inventories

should be treated similarly to cash in corporate liquidity measurements. To formally prove our

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conjecture regarding cash-equivalence of liquid inventory, we show how liquid inventory might

affect cash-related corporate decisions like corporate dividends policy.

V. Corporate liquidity and dividends policy

Baker, Farrelly, and Edelman (1985) validate the theoretical models of dividend policy

against managers‘ views. They survey hundreds of NYSE firms‘ CFOs about the determinants of

corporate dividend policy. Corporate liquidity (as measured by availability of cash) is shown to

be one of the major determinants of dividend policy. Twenty years later, Brav et al (2005) in a

similar study survey and interview CFOs from US public and private firms. They explore the

determinants of corporate payout policy. Their results provide weak support for agency,

signaling, and clientele hypotheses of payout policy. Brav et al (2005) assert that dividend

increases are considered only after investment and liquidity needs are met. We argue that if cash

availability plays a significant role in corporate payout policy, then cash-like current assets

should also have a significant impact on such vital corporate decision. We argue that managers,

when making dividends decisions, look not only at cash available but also at cash equivalents.

i.e., they look at how much they have and how much they can have shortly.

Table VII show the relationship between dividend policy and firms‘ holdings of liquid

inventory. Panel A reports the mean dividend yield and cash dividends for two groups of firms.

Liquid-intense firms are firms for which liquid inventory exceeds illiquid inventory. Illiquid-

intense firms are firms for which illiquid inventory exceeds liquid inventory holdings.

Descriptive statistics show that the mean dividend yield of liquid-intense firms is 1.5% which is

30% higher than the 1% figure reported for illiquid-intense firms. Liquid-intense firms‘ average

cash dividends is $65 million which is almost double the cash dividend paid by illiquid-intense

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firms with an average of $35 million. The differences between mean dividend yield and cash

dividend among liquid-intense and illiquid-intense firms are significant at 1% significance level.

[Please insert Table VII here]

Table VII (panel B) reports mean dividend yield and cash dividends for Compustat firms

divided into four quartiles based on liquid-inventory/total inventory ratio. These statistics show

the gradual nature of the relationship between dividends and liquid inventory holdings. The

higher the percentage of liquid inventories to total inventory the higher the dividend yield and

the cash dividends. The upper quartile have dividend yield (cash dividends) of 1.54% ($66.8

million). On the other extreme, the bottom quartile have dividend yield (cash dividends) of 0.8%

($30.9 million). With the upper quartile firms pay on average double as the bottom quartile

firms, we provide preliminary evidence that corporate dividend policy could be related not only

to how much cash a firm has but also to how much cash could be generated from the highly

liquid current assets.

We formally test the relationship between liquid inventory and corporate payout policy.

We test two related conjectures. First, if liquid inventory is thought of as cash by corporate

managers, then it should affect cash-related decisions such as payout policy. Second, the

relationship between liquid inventory and dividends should be stronger for firms which liquid

inventory represents greater proportion of their current assets. We use dividend policy model in

Fama and French (2001). They model dividend policy using the following logit regression;

𝐷𝐼𝑉_𝑌𝐿𝐷𝑖𝑡 = 𝛼 + 𝛽1𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽2𝑃𝑟𝑜𝑓𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦𝑖𝑡 + 𝛽3𝑔𝑟𝑜𝑤𝑡𝑕𝑖𝑡 + 𝑋𝑖𝑡 + 𝜀 (7)

Where DIV is dummy variables equals ―1‖ if the firm is a dividend payer and ―0‖ if not. We

proxy Size using firm‘s total assets. We proxy profitability using the ratio of Earnings before

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interest and taxes to firm‘s total assets. And we proxy growth using the growth rate of firm‘s

total assets. Xs are added variables to capture the liquidity nature of firm‘s inventory holdings.

[Please insert Table VIII here]

Table VIII reports results for our dividends policy determinants logit regression.

Consistent with literature dividend yield dummy is positively correlated with size and

profitability and negatively related with growth. I.e. dividends payers are larger and more

profitable firms with less investment opportunities. Consistent with our conjectures, dividends

yield dummy is positively correlated with firm‘s holdings of liquid inventory. On the other hand,

dividend dummy is negatively related with illiquid inventory holdings. Having large stack of

highly liquid inventory increase the possibility of dividends payment. Conversely, having a large

stack of inventory that is hard to get rid of, reduce the possibility to pay dividends. Different

components of inventory –calculated based on how quick they could be turned over- then have

opposing associations with corporate decisions.

If managers consider the efficiency of their cash machines when making dividend

decisions, then the amount –not only the decision- of dividends paid to shareholders should be

affected by how much liquid inventory the firm has. To test this conjecture, we use OLS

regression for the determinants of dividends policy;

𝐶𝐴𝑆𝐻_𝐷𝐼𝑉𝑖𝑡 = 𝛼 + 𝛽1𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽2𝑃𝑟𝑜𝑓𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦𝑖𝑡 + 𝛽3𝑔𝑟𝑜𝑤𝑡𝑕𝑖𝑡 + 𝑋𝑖𝑡 + 𝜀 (8)

Where 𝐶𝐴𝑆𝐻_𝐷𝐼𝑉𝑖𝑡 is the total cash dividends paid to both common and preferred shareholders.

We proxy Size, profitability and growth similarly to the logit regression (equation 7). Table IX

reports results of the OLS regression. OLS results provides further support to our first conjecture.

Liquid inventory is positively related to cash dividends at 1% significance level. On the other

20

hand illiquid inventory is negatively correlated with cash dividends. Hence, Total inventory

should not treated as liquid asset as implied by CR. Managers not only consider how much cash

they have but also how much they can get within short period of time.

To test our second conjecture, we run the OLS regression for subgroups of firms based on

their ratio of liquid inventory to current assets. Our hypothesis assume that the higher the liquid

inventory holdings the higher their effect on different corporate decisions. I.e. dividends decision

makers will consider liquid inventory more when it represents a higher proportion from their

current assets. Testing the second conjecture is reported in Table X. adjusted R2 is an increasing

function in the liquid inventory to current assets ratio. The more the liquid inventory as a

proportion to current assets the firms have, the larger the explanatory power of the dividends

model to the cash dividends.

Robustness tests

As a robustness check we run the OLS regression for three different ten years time periods.

1980-1990, 1991-2000, and 2001-2011. We report results for this test in Table XI. Results in

Table XI lend further support to our conjectures regarding the relationship between dividend

policy and liquid inventory holding. The magnitude and sign of coefficients of illiquid inventory

and illiquid inventory does not change during the last three decades. Over the entire period,

firm‘s with more liquid inventory tend to pay higher cash dividends. Also firms with high stacks

of illiquid inventory tend to pay fewer amounts of cash dividends.

VI. Conclusion

We develop ―Islamic Sharia Compliant‖ measure of corporate liquidity. The Islamic

liquidity ratio ―IR‖ overcomes the ―bakhs‖, ―gharar‖, and ―Implicit riba‖ components of the

21

conventional liquidity measures. We argue that the IR provides a fair valuation of corporate

liquidity according to Islamic Sharia law. Our IR has two desirable properties. First, it

minimizes the undervaluation problem inherent in the Quick-ratio and cash-based liquidity

measures. Second, it also reduces the uncertainty problem inherent in the Current ratio. By

incorporating firms unique ability to liquidate inventory, IR provides less-static measure of

corporate liquidity than the traditional Current and quick ratios. We investigate the effect of

corporate inventory characteristics on dividends payout policy. Our results show that firms with

high stacks of liquid inventory are more likely to be dividend payers. Our results also show that

firms that have higher stacks of liquid inventory pay higher amounts of cash dividends.

22

References

Acharya, V., Almeida, H., Campello, M., 2007. Is cash negative debt? A hedging perspective on

corporate financial policies. Journal of Financial Intermediation 16, 515–554.

Almeida, H., Campello, M., Weisbach, M., 2004. The cash flow sensitivity of cash. Journal of

Finance, 59, 1777–1804.

Baker H. Kent, Gail E. Farrelly, and Richard B. Edelman,(1985) ― a survey of management

views on dividend policy,‖ Financial Management 14, 78-84.

Bates, T., Kahle, K., Stulz, R., 2009. Why do U.S. firms hold so much more cash than they used

to? Journal of Finance 64, 1985–2021

Benartzi, Shlomo, Roni Michaely and Richard Thaler, 1997, .Do changes in dividends signal the

future or the past?, Journal of Finance 52 (3), 1007-1043.

Bhattacharya, Sudipto, 1979, .Imperfect Information, Dividend Policy, and ‗The Bird In The

Hand. Fallacy, Bell Journal of Economics, 10 (1), 259-270.

Brealey A., and S. Myers, 1996, Principles of corporate finance, fifth edition. New York, NY:

McGraw Hill Book Co.

Brealey A., and S. Myers, 2003, Principles of corporate finance, seventh edition. New York, NY:

McGraw Hill Book Co.

Brickley, James, 1983, Shareholders wealth, information signaling, and the specially designated

dividend: An empirical Study, Journal of Financial Economics 12, 187-209.

Chava Sudheer, and Roberts R. Michael, 2008, How Does Financing Impact Investment? The

Role Of Debt Covenants, Journal of Finance LXIII 5, 2085-2121.

DeAngelo H., DeAngelo L., and K.Wruck, 2002. Asset Liquidity, debt covenants, and

managerial discretion in financial distress: the collapse of L.A. Gear, Journal of Financial

Economics 64, 3-34.

Deloof Marc, 2003, Does Working Capital Management Affect Profitability OF Belgian Firms?,

Journal of Business Finance and Accounting, 30(3) & (4), 0306-686X

Gamba, A., Triantis, A., 2008. The value of financial flexibility. Journal of Finance 63, 2263–

2296.

Gitman, L.J., 1974 estimating corporate liquidity requirements: a simplified approach. The

Financial Review 9, 79-88.

23

Gryglewicz S., 2011, A theory of corporate financial decisions with liquidity and solvency

concerns, Journal of Financial Economics 99, 365-384.

Healy, Paul M. and Krishna G. Palepu, 1988, .Earnings Information Conveyed by Dividend

Initiations and Omissions,. Journal of Financial Economics, 21 (2), 149-176.

Jensen, Michael C., and William H. Meckling, 1976, Theory of the firm: Managerial behavior,

agency costs, and capital structure, Journal of Financial Economics 3, 305–360.

J. C. Van Horne, Financial Management and Policy, 6th

ed., Englewood Cliffs, NJ, Prentice-

Hall, 1983.

J. F. Weston and E. F. Brigham, Managerial Finance, 7th

ed., Hinsdale, IL, Dryden Press, 1981.

John, Kose and Joseph Williams, 1985, .Dividends, Dilution, and Taxes: A Signaling

Equilibrium,. Journal of Finance, 40 (4), 1053-1070.

Kallberg J., and K. Parkinson, 1992, Corporate Liquidity. Management and Measurement,

Homewood, IL, Irwin,

W.D. Knight, "Working Capital Management-Satis-ficing Versus Optimization," Financial

Management, (Spring 1972), p. 33.

Miller, Merton and Kevin Rock, 1985, .Dividend Policy Under Asymmetric Information,.

Journal of Finance, 40 (4), 1031-1051.

Myers, S., Majluf, N., 1984. Corporate financing and investment decisions when firms have

information the investors do not have. Journal of Financial Economics 13, 187–221.

Richards, V.D., Laughlin, E.J., (1980) A cash conversion cycle approach to liquidity analysis,

Financial Management 9, 32-38

Riddick, L., Whited, T., 2009. The corporate propensity to save. Journal of Finance 64, 1729–

1766.

Smith, Clifford W., and Jerome B. Warner, 1979, on financial contracting: An analysis of bond

covenants, Journal of Financial Economics 7, 117–161.

Teresa A. John, 1993, accounting measures of corporate liquidity, leverage, and costs of

financial distress, Financial Management 22, 91-100.

Tirole, Jean, 2006, the Theory of Corporate Finance (Princeton University Press, Princeton).

Vishal Gaur, Marshall L. Fisher and Ananth Raman (2005), an Econometric Analysis of

Inventory Turnover Performance in Retail Services. Management Science 51,2., 181-194

24

Table I

Comparison of Traditional Liquidity Measures with IR

We present hypothetical data for five firms (A to E). Current assets (CA) are 1,000 and

current liabilities (CL) are also 1,000 for all five firms, but inventory varies from 900 for Firm

A to 100 for Firm E and days of sales in inventory (DSI = 365/ Inventory turnover) varies

from 30 to 150. Traditional measures of liquidity—the current ratio (CR= CA/CL) and the

quick ratio (QR = (CA – Inventory)/CL)—are reported in columns four and five, respectively.

In column 6, we present our new Sharia-compliant measure of liquidity, the Islamic Liquidity

Ratio (IR = (CA – Illiquid Inventory)/CL). The last three columns report the rank of each

firm‘s liquidity using CR, QR and IR, respectively.

Ratio Value Rank by Ratio

Firm Inventory DSI CR QR IR CR QR IR

A 900 30 1 0.10 1 1 5 1

B 700 60 1 0.30 0.65 1 4 5

C 500 90 1 0.50 0.66 1 3 4

D 300 120 1 0.70 0.775 1 2 3

E 100 150 1 0.90 0.920 1 1 2

25

Table II

Descriptive statistics

This table reports descriptive statistics of variables used in this study. Cash is total amount of

cash balance measured in millions of dollars (Compustat data item 162). Inventory is the total

amount of inventory holdings measured in millions of dollars (Compustat data item 3). Liquid

inventory is the proportion of total inventory that could be turned over within 30 days. Illiquid

inventory is the difference between total inventory and liquid inventory. Dividend yield is the

dividends per share (Compustat data item 26) divided by the closing stock price at the end of

fiscal year (Compustat data item 199) multiplied by 100. Cash dividend is the total amount of

cash dividends paid to both common and preferred stocks (Compustat data item 127). Size is the

firm‘s total assets (Compustat data item 6). Profitability is the ratio of earnings before interest

and taxes (Compustat data item to firm‘s total assets. Growth is the percentage change in firms‘

total assets. IR is the Islamic liquidity ratio (measured as shown in equation 6). Current ratio

(CR) is the ratio of total current assets (Compustat data item 4) to total current liabilities

(Compustat data item 5). Quick ratio (QR) is the ratio of total current assets minus inventories to

total current liabilities.

Obs. Mean Std. Dev Minimum Maximum

Cash 248499 178.05 1700.31 0 168896.50

Inventory 264537 245.26 4808.86 0 472266.20

Liquid inventory 194316 107.09 593.57 0 32591.75

Illiquid-inventory 141002 335.97 6464.33 0 469273.1

Dividend yield 198906 11.17 2264.83 0 921000

Cash dividends 257853 41.31 301.02 0 36112

Size 270353 4570.35 50783.3 0 3771200

Profitability 267565 -.66 55.32 -23957.5 1625

Growth 243169 2.99 324.94 -1 103908

IR 172839 2.11 5.53 0 1543.86

CR 225928 3.56 55.80 0 24108

QR 227114 3.33 66.38 0 24100

26

Table III

Correlation coefficients

cash

total

inventory

liquid

inventory

illiquid

inventory

dividend

yield

cash

dividend

total

assets profitability Growth

cash 1

Total inventory 0.3751 1

Liquid inventory 0.4484 0.2102 1

Illiquid inventory 0.3335 0.9945 0.1068 1

dividend yield 0.022 0.0061 0.0234 0.0037 1

cash dividend 0.4699 0.2078 0.5709 0.1502 0.0521 1

total assets 0.7185 0.4815 0.3494 0.4523 0.0193 0.4768 1

profitability 0.014 0.0064 0.022 0.0041 0.011 0.021 0.0093 1

growth -0.0011 -0.0005 -0.0015 -0.0004 -0.0009 -0.0012 -0.0008 -0.0005 1

27

Table IV

Relative holdings of cash and total inventories 1980-2011.

We report average holdings of cash and total inventories as a proportion of current assets for each of

the Fama and French 48 industries. Average holdings are measured for all Compustat firms within

each industry over the period 1980-2011. Inventory/CA is the ratio of end of period total inventory to

the end of period total current assets. Cash/CA is the ratio of end of period cash balance to end of

period total current assets. Difference is the difference between Inventory/CA and Cash/CA ratios. We

also report the average inventories and cash holding for two larger pools, namely the entire sample

(All) and the entire sample excluding financial firms (All ex fin).

Industry

Inventory

/CA Cash/CA Difference

Industry

Inventory

/CA Cash/CA Difference

Agric 35% 17% 19% Ships 38% 13% 24%

Food 40% 13% 28% Guns 24% 21% 3%

Soda 28% 19% 9% Gold 15% 48% -33%

Beer 39% 15% 24% Mines 17% 41% -24%

Smoke 50% 16% 34% Coal 19% 26% -7%

Toys 35% 17% 18% Oil 10% 27% -18%

Fun 11% 37% -26% Util 23% 9% 14%

Books 20% 16% 5% Telcm 7% 27% -19%

Hshld 39% 13% 26% PerSv 14% 30% -16%

Clths 45% 12% 33% BusSv 7% 32% -25%

Hlth 6% 23% -17% Comps 22% 25% -3%

MedEq 29% 26% 3% Chips 30% 23% 6%

Drugs 14% 41% -28% LabEq 33% 20% 13%

Chems 32% 18% 14% Paper 37% 11% 25%

Rubbr 35% 14% 21% Boxes 41% 10% 31%

Txtls 47% 7% 40% Trans 9% 23% -14%

BldMt 38% 13% 26% Whlsl 38% 12% 26%

Cnstr 20% 17% 4% Rtail 57% 14% 43%

Steel 42% 11% 31% Meals 19% 32% -14%

FabPr 37% 10% 27% Banks 13% 30% -17%

Mach 38% 15% 22% Insur 4% 30% -26%

ElcEq 36% 17% 20% RlEst 15% 30% -15%

Autos 38% 13% 25% Fin 8% 38% -30%

Aero 46% 12% 35% Other 16% 29% -13%

All 27% 21% 6%

All ex fin 29% 20% 9%

28

Table V

Relative holdings of cash and liquid inventories 1980-2011.

We report average holdings of cash and liquid inventories as a proportion of current assets for each

of the Fama and French 48 industries. Average holdings are measured for all Compustat firms

within each industry over the period 1980-2011. Liquid inventory is the proportion of inventories

that could be liquidated within 1 month period according to firm‘s end of year inventory turnover

ratio. Liquid Inventory/CA is the ratio of end of period liquid Inventory holdings to the end of period

total current assets. Cash/CA is the ratio of end of period cash balance to end of period total current

assets. Difference is the difference between liquid Inventory/CA and Cash/CA ratios. We also report

the average liquid inventories and cash holding for two larger pools, namely the entire sample and

the entire sample excluding financial firms (Banks, Insurance companies, Real Estates, and financial

institutions).

Industry

Liquid

Inv/CA Cash/CA Difference

Industry

Liquid

Inv/CA Cash/CA Difference

Agric 16% 17% -1% Ships 18% 13% 4%

Food 26% 13% 13% Guns 14% 21% -7%

Soda 20% 19% 2% Gold 18% 48% -30%

Beer 14% 15% -1% Mines 16% 41% -25%

Smoke 10% 16% -6% Coal 24% 26% -1%

Toys 12% 17% -5% Oil 17% 27% -10%

Fun 27% 37% -10% Util 25% 9% 16%

Books 14% 16% -1% Telcm 15% 27% -12%

Hshld 13% 13% 1% PerSv 20% 30% -10%

Clths 14% 12% 2% BusSv 13% 32% -19%

Hlth 20% 23% -3% Comps 10% 25% -15%

MedEq 7% 26% -18% Chips 10% 23% -13%

Drugs 8% 41% -33% LabEq 8% 20% -12%

Chems 15% 18% -3% Paper 19% 11% 8%

Rubbr 17% 14% 4% Boxes 22% 10% 12%

Txtls 18% 7% 12% Trans 29% 23% 6%

BldMt 17% 13% 5% Whlsl 25% 12% 13%

Cnstr 19% 17% 2% Rtail 27% 14% 13%

Steel 19% 11% 8% Meals 65% 32% 33%

FabPr 17% 10% 7% Banks 15% 30% -14%

Mach 12% 15% -4% Insur 23% 30% -7%

ElcEq 12% 17% -5% RlEst 18% 30% -12%

Autos 19% 13% 5% Fin 17% 38% -21%

Aero 14% 12% 2% Other 16% 29% -13%

all industries 18% 21% -3%

all excluding financial 18% 20% -2%

29

Table VI

CR versus IR ranking, Benchmarking and How inaccurate are traditional liquidity measures?

We report the difference in ranking firms using current ratio (CR) and Islamic liquidity ratio (IR) for all FF 48 industries for the period 1980-2011. Unfair_CR

is the firm‘s ranking position within industry for certain year using CR minus its ranking position using IR. For example, an unfair_CR equals 10 means the

firm is ranked 18th

among industry/year firms using CR and ranked 8th

using IR. Unfair_CR adjusted is the unfair_CR adjusted by the industry size defined

as the number of firms belonging to a certain industry in any specific year.

industry unfair_CR minimum maximum

unfair_cr

adjusted minimum maximum industry unfair_CR minimum maximum

unfair_cr

adjusted minimum maximum

Agric 2 -20 18 2% -19% 17% Ships 0 -9 10 0% -21% 23%

Food 1 -94 77 0% -25% 20% Guns 1 -6 6 3% -19% 19%

Soda 0 -10 10 0% -16% 16% Gold 21 -16 51 8% -6% 19%

Beer 1 -26 11 1% -34% 14% Mines 14 -12 63 6% -5% 29%

Smoke 0 -7 6 0% -26% 23% Coal 1 -6 7 2% -10% 12%

Toys 2 -41 27 1% -18% 12% Oil 77 -135 248 6% -10% 24%

Fun 22 -64 79 4% -12% 15% Util 7 -258 221 1% -43% 36%

Books 4 -51 25 2% -27% 13% Telcm 56 -85 245 6% -8% 24%

Hshld 2 -92 78 1% -23% 13% PerSv 12 -38 55 4% -13% 20%

Clths 1 -44 51 0% -15% 17% BusSv 187 -269 1001 6% -9% 33%

Hlth 24 -23 103 5% -5% 23% Comps 16 -287 174 1% -29% 17%

MedEq 12 -122 108 2% -17% 15% Chips 11 -319 200 0% -28% 17%

Drugs 118 -65 283 11% -6% 26% LabEq 2 -125 61 1% -31% 15%

Chems 4 -87 80 1% -23% 21% Paper 1 -65 62 0% -26% 25%

Rubbr 2 -49 54 0% -20% 22% Boxes 0 -19 15 0% -30% 23%

Txtls 0 -50 34 0% -30% 20% Trans 34 -104 111 5% -15% 17%

BldMt 3 -122 97 0% -26% 21% Whlsl 9 -249 263 1% -25% 27%

Cnstr 4 -44 35 1% -14% 11% Rtail 7 -339 402 1% -28% 34%

Steel 2 -84 91 1% -28% 30% Meals 7 -96 116 1% -19% 23%

FabPr 1 -26 20 1% -27% 21% Banks 9 -9 24 0% 0% 1%

Mach 5 -204 109 1% -30% 16% Insur 13 -5 64 2% -1% 10%

ElcEq 3 -80 52 1% -26% 17% RlEst 14 -13 51 3% -3% 13%

Autos 2 -80 58 1% -25% 18% Fin 41 -12 88 1% 0% 2%

Aero 1 -28 25 1% -33% 30% Other 38 -74 135 5% -10% 19% all industries 11 -339 1001 2% -43% 37%

30

Table VII

Dividends policy and liquid inventories holdings We present the average (mean) dividend yield and cash dividends for different groups based on

liquid inventory holdings. Dividend yield is the dividend per share divided by the end of year

stock price. Cash dividends is the total cash dividends paid to both common and preferred stocks.

Panel A reports average dividend yield and cash dividends for two groups of firms, namely

liquid-intense and illiquid-intense firms. Liquid-intense firms refer to firms for which liquid

inventory is larger than illiquid inventory (i.e. liquid inventory is more than half of the total

inventory holding). Conversely, illiquid-intense firms refer to firms for which illiquid inventory

is larger than liquid inventory (i.e. illiquid inventory is more than half of the total inventory

holding).Panel B reports average dividend yield and cash dividends for four distinct quartiles of

firms based on the percentage of liquid inventory out of firm‘s total inventory holdings. P-values

are provided in parentheses. *, **, and *** denote significance at the 0.10, 0.05 and 0.01 levels,

respectively.

Panel A. Liquid-inventory intensive versus illiquid-inventory intensive firms

group Dividend yield Cash dividends

Liquid_intense 1.50

(0.000)***

65.60

(0.000)***

Illiquid_intense 0.99

(0.000)***

35.16

(0.000)***

difference 0.51

(0.000)***

30.44

(0.000)***

Panel B. quartiles based on liquid_inventory/total inventory ratio.

Lowest(quartile 1) 0.80

(0.000)***

30.97

(0.000)***

Quartile 2 1.13

(0.000)***

35.73

(0.000)***

Quartile 3 1.42

(0.000)***

63.22

(0.000)***

highest(quartile 4) 1.54

(0.000)***

66.84

(0.000)***

Difference (2-1) 0.33

(0.004)***

4.76

(0.000)***

Difference (3-1) .62

(0.000)***

32.24

(0.000)***

Difference (4-1) .74

(0.000)***

35.86

(0.000)***

31

Table VIII

Logit regression for the determinants of dividends policy

We report result for the Logit regression of the determinants of dividends payout ratio.

Following Fama and French (2001) the dependent variable is dividends yield dummy variable

which equals ―1‖ if the firm is a dividends payer and equals ―0‖ if it is not. Size is the total firm‘s

assets. Profitability is the ratio of earnings before interest and taxes (EBIT) to firm‘s total assets.

Growth is the percentage change in firm‘s total assets. Liquid inventory is the amount of

inventory that a firm could liquidate within 30 days according to its inventory turnover over the

designated year. Illiquid inventory is difference between total inventory and liquid inventory

holdings. Liquid_vs_illiquid is a dummy variable that equals ―1‖ if the firm holds more liquid

inventory than illiquid and equals‖0‖ otherwise. . P-values are provided in parentheses. *, **,

and *** denote significance at the 0.10, 0.05 and 0.01 levels, respectively.

Model (1) Model (2) Model (3) Model (4) Model (5)

Constant -.867

(0.000)***

-.881

(0.000)***

-.918

(0.000)***

-.919

(0.000)***

-1.067

(0.000)***

Size .004

(0.000)***

.006

(0.000)***

.002

(0.000)***

.002

(0.000)***

.005

(0.000)***

Profitability 4.22

(0.000)***

4.3947

(0.000)***

4.212

(0.000)***

4.21

(0.000)***

4.449

(0.000)***

Growth -.0002

(0.869)

-1.404

(0.000)***

-1.168

(0.000)***

-1.166

(0.000)***

-1.377

(0.000)***

Illiquid inventory -.008

(0.000)***

-.004

(0.000)***

Liquid inventory .159

(0.000)***

.157

(0.000)***

Liquid_vs_illiquid .390

(0.000)***

No. 147200 104033 104033 104033 104033

- Log likelihood 79910.434 58532.847 58726.428 -58696.249 -58193.61

32

Table IX

OLS regression for determinants of dividends policy

We report result for the OLS regression of the determinants of dividends payout ratio. The

dependent variable is Cash dividends which is measured as the total amount of cash dividends

paid to both common and preferred stocks. Size is the total firm‘s assets. Profitability is the ratio

of earnings before interest and taxes (EBIT) to firm‘s total assets. Growth is the percentage

change in firm‘s total assets. Liquid inventory is the amount of inventory that a firm could

liquidate within 30 days according to its inventory turnover over the designated year. Illiquid

inventory is difference between total inventory and liquid inventory holdings. Liquid_vs_illiquid

is a dummy variable that equals ―1‖ if the firm holds more liquid inventory than illiquid and

equals‖0‖ otherwise. . P-values are provided in parentheses. *, **, and *** denote significance at

the 0.10, 0.05 and 0.01 levels, respectively.

Model (1) Model (2) Model (3) Model (4) Model (5)

Constant 28.09

(0.000)***

25.61

(0.000)***

1.75

(0.000)***

2.031

(0.574)

23.24

(0.000)***

Size .246

(0.000)***

.3774

(0.000)***

.234

(0.000)***

0.252

(0.000)***

.350

(0.000)***

Profitability .004

(0.680)

3.96

(0.000)***

2.509

(0.000)***

2.518

(0.000)***

4.017

(0.000)***

Growth -.0570

(0.734)

-.083

(0.767)

-.030

(0.903)

-.0313

(0.901)

-.080

(0.777)

Illiquid inventory -.5

(0.000)***

-.343

(0.000)***

Liquid inventory .257

(0.000)***

0.255

(0.000)***

Liquid_vs_illiquid 4.919

(0.000)

Industry FE Yes Yes Yes Yes Yes

No. 232868 171012 171012 171012 171011

Adjusted R2 0.18 0.22 0.40 0.40 0.22

33

Table X

OLS regression for determinants of dividends policy

We report result for the OLS regression of the determinants of dividends payout ratio. We test our

model for three groups of firms. Liquid_inv/CA>25 perc are firms which liquid inventory to

current assets ratio is higher than the 25 percentile which equals 7%. Liquid_inv/CA>50 perc are

firms which liquid inventory to current assets ratio is higher than the 50 percentile which equals

13%. Liquid_inv/CA>75 perc are firms which liquid inventory to current assets ratio is higher than

the 75 percentile which equals 21%. The dependent variable is Cash dividends which is measured

as the total amount of cash dividends paid to both common and preferred stocks. Size is the total

firm‘s assets. Profitability is the ratio of earnings before interest and taxes (EBIT) to firm‘s total

assets. Growth is the percentage change in firm‘s total assets. Liquid inventory is the amount of

inventory that a firm could liquidate within 30 days according to its inventory turnover over the

designated year. Illiquid inventory is difference between total inventory and liquid inventory

holdings. Liquid_vs_illiquid is a dummy variable that equals ―1‖ if the firm holds more liquid

inventory than illiquid and equals‖0‖ otherwise. . P-values are provided in parentheses. *, **, and

*** denote significance at the 0.10, 0.05 and 0.01 levels, respectively.

Model (1)

Liquid_inv/CA>25 perc

Model (2)

Liquid_inv/CA>50 perc

Model (3)

Liquid_inv/CA>75 perc

Constant .782

(0.835)

.295

(0.951)

-5.934

(0.09)*

Size .2242

(0.000)***

.216

(0.000)***

.2103

(0.000)

Profitability 1.435

(0.062)*

.994

(0.255)

.442

(0.615)

Growth -.013

(0.957)

-.053

(0.957)

-.068

(0.946)

Liquid inventory .252

(0.000)***

.248

(0.000)***

.2171338

(0.000)***

Illiquid inventory -.340

(0.000)***

-.301

(0.000)***

-.250

(0.000)***

Industry FE Yes Yes Yes

No. 134343 94138 55091

Adjusted R2 0.46 0.49 0.56

34

Table XI

OLS regression for determinants of dividends policy

We report result for the OLS regression of the determinants of dividends payout ratio. We test our

model for three time periods. Models (1), (2) and (3) test periods 1980-1990, 1991-2000, and

2001-2011 respectively. The dependent variable is Cash dividends which is measured as the total

amount of cash dividends paid to both common and preferred stocks. Size is the total firm‘s assets.

Profitability is the ratio of earnings before interest and taxes (EBIT) to firm‘s total assets. Growth

is the percentage change in firm‘s total assets. Liquid inventory is the amount of inventory that a

firm could liquidate within 30 days according to its inventory turnover over the designated year.

Illiquid inventory is difference between total inventory and liquid inventory holdings.

Liquid_vs_illiquid is a dummy variable that equals ―1‖ if the firm holds more liquid inventory than

illiquid and equals‖0‖ otherwise. . P-values are provided in parentheses. *, **, and *** denote

significance at the 0.10, 0.05 and 0.01 levels, respectively.

Model (1)

1980-1990

Model (2)

1991-2000

Model (3)

2001-2011

Constant .1189

(0.924)

.33171

(0.921)

4.981

(0.444)

Size 0.666

(0.000)***

.395

(0.000)***

.2625

(0.000)***

Profitability 6.125

(0.000)***

2.829

(0.000)***

2.2754

(0.051)*

Growth -.0373

(0.932)

-.018

(0.895)

-.402

(0.813)

Liquid inventory 19.107

(0.000)***

19.558

(0.000)***

26.636

(0.000)***

Illiquid inventory -.924

(0.000)***

-.7514

(0.000)***

-.353

(0.000)***

Industry FE Yes Yes Yes

No. 54871 59909 52265

Adjusted R2 0.49 0.43 0.39