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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 + 𝛽3𝑔𝑟𝑜𝑤𝑡𝑖𝑡 + 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 + 𝛽3𝑔𝑟𝑜𝑤𝑡𝑖𝑡 + 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