Cash holdings and Multinationality: a European perspective

Abstract

Using data from twelve countries in the European Union over a 13-year period (2002-2015) with

9,707 observations, the effect of multinationality and the crisis on cash holdings is examined in a

European setting. Both firm and country characteristics of firms are taken into account. This research

contributes to the fields of risk management in the area of cash holdings and multinationality. Findings

suggest that the cash ratio of companies is not significantly related to multinationality or the financial

crisis. Moreover, findings show that, when taking determinants of cash holdings into account, Dutch

firms have significantly higher cash holdings than eight out of eleven countries in the sample.

Name: Ruben Hanson

Student number: s2359022

Supervisor: dr. R. M. van Dalen

Second Supervisor: prof. dr. B.W. Lensink

Faculty of Business and Economics, University of Groningen

Study Programme: MSc International Financial Management

Field Key Words: JEL: G30 (General Corporate Finance and Governance), G32 (Financial

Risk and Risk Management)

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Table of Content

Introduction p. 3

Literature Review p. 5

Motives for cash holdings p. 5

Firm characteristics p. 6

Country characteristics p. 9

Cash holdings and the crisis p. 10

Cash holding motives and determinants p.11

Data and methodology p. 12

Model p. 12

Data p. 12

Variables p. 16

Method p. 19

Empirical results p. 20

Conclusion p. 23

References p. 25

Appendix p. 28

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Introduction

In the first fiscal quarter of 2017, the cash holdings of Apple were 246.1 billion US dollar.

That is the highest cash holding for a non-financial company ever recorded (CNN, 2017). To

put that in perspective, the cash holdings of Apple are higher than the GDP of developed

countries such as New Zealand and Finland (World Bank, 2017).

The high cash holdings of Apple are striking, but Apple is certainly not the only company that

has increased its cash holdings substantially over the last years. According to Moody’s (2016)

corporate cash holdings in the United States have more than doubled from 2006 to 2016. This

could implicate on the one hand that firms have healthy balance sheets that can cope with

adverse shocks. On the other hand it can also be problematic, because these increases in cash

holdings can implicate that firms are reluctant to invest their money. This reluctance to invest

does not benefit countries that are trying to increase their growth rates and employment. As

suggested by Pinkowitz et al. (2016), firms have increased their cash holdings because they

are hesitant to invest for the future.

In earlier research, Pinkowitz et al. (2012) focus on the role that multinational corporations

have in the increase of cash holdings in the United States. They find that multinational

corporations increased their cash holdings from 157 billion dollar in 1998, to 835 billion

dollar in 2010. In this period, multinationals increased their cash holdings by 433 percent

while they increased their assets by 205 percent. On the other hand, domestic firms increased

their cash holdings by 66 percent, while their assets increased by 40 percent. This indicates a

strong positive relationship between multinationality and cash holdings. Nonetheless, this

cannot be said about all countries, as Fernandes and Gonenç (2016) find that this positive

relationship between multinationality and cash holdings only holds in developing countries. In

their sample of companies in 58 different countries they even find a negative relationship

between multinationality and cash holdings.

In the EU non-financial companies in the core-EU (Belgium, Germany, France and Italy)

increased their cash holdings over the period 1995-2010. However, the increase in cash

holdings in the Netherlands is larger than in the core-EU. Cash holdings of non-financial

companies in the Netherlands exceeded those of the core-EU in the period 1995-2012. The

difference between the Netherlands and the core-EU ranged from 7.1 percent of GDP in 1995

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to 21.6 percent of GDP in 2007. The latest measurement in 2012 shows a difference of 20

percent of GDP (CPB, 2014).

This data presents a clear difference in cash holdings between the Netherlands and the core-

EU. One of the factors that could play a role here is multinationality, which provides mixed

results in the available literature. On the one hand Pinkowitz et al. (2012) found that in the

United States multinationals were responsible for a large part of the increase in cash holdings.

On the other hand Fernandes and Gonenç (2016) find a negative relationship between

multinationality and cash holding. These mixed results will be looked into in more detail for

the EU sample. This will be done using the following research question:

What is the effect of multinationality on cash holdings in the European Union?

After researching this question in the paper, the findings show no significant relationship

between multinationality and cash holdings at any significance level. With regard to the crisis,

it is striking that cash holdings decreased sharply when the crisis began, but cash holdings

increased to levels even higher than pre-crisis levels in recent years. However, in the

regression analysis there was no significant relationship found between cash holdings and the

crisis. When looking at the difference between The Netherlands and other countries in the EU,

it is striking to see that Dutch firms have significantly more cash holdings than eight out of

eleven countries in the sample.

In the remainder of this thesis the following sections are distinguished. The second section

will consist of the literature review. In the literature review there will be a distinction between

the motives for holding cash and the determinants of cash holdings. Section three describes

the data and methodology. This section is composed of the research design and a description

of the variables. The fourth section discusses the results and the final section consists of the

conclusion, which includes limitations and directions for further research.

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Literature review

The literature review will discuss motives for corporate cash holdings. In the subsequent

sections, these four motives will be linked to firm determinants, country determinants of cash

holdings and the financial crisis. The final section of the literature review provides a summary

of the link between these determinants and the motives for holding cash.

Motives for cash holding

Firms can have different motives to hold cash. According to Bates, Kahle and Stulz (2009)

there are four main motives for holding cash: the transaction motive, the precautionary

motive, the tax motive and the agency motive. These will be discussed in more detail in this

section.

First of all, the precautionary motive argues that firms hold more cash when access to capital

markets is costly, for example due to adverse shocks. Firms with riskier cash flows and poor

access to external capital hold more cash according to this motive. According to Keynes

(1936) the precautionary motive consists of three reasons to hold cash, these are: the ability to

pay unforeseen expenses, the ability to take advantage of opportunities related to

advantageous investments and the ability to pay foreseen expenses. In other words, businesses

hold cash today to be able to utilize investment opportunities in the future and to be able to

pay expenses.

The second motive provided by Bates et al. (2009) is the transaction motive. This motive

takes into account the costs that are related to changing a financial asset into cash and using

cash for payments. As there are economies of scale with this motive, it is expected that larger

firms will hold less cash.

The tax motive implicates that firms that are subject to repatriation of taxes because of foreign

earnings have higher cash holdings. They have higher cash holdings as they hold their cash in

order to pay less taxes. Because of this, multinationals are expected to have higher cash

holdings compared to local companies as they are more likely to be subject to repatriation of

taxes as they have more business abroad. According to Foley et al. (2006, p24) “affiliates in

countries with low tax rates, which imply high tax costs of repatriating earnings, hold more

cash than other affiliates of the same firm”.

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Finally, the agency motive is concerned with shareholder and creditor protection by the legal

system (Ferreira & Vilela, 2004). In countries with little shareholder and creditor protection

entrenched managers are more likely to retain cash than to increase pay-outs to shareholders

when the firm has poor investment opportunities. They accumulate cash to be able to

influence the investment decisions of the firm more. In this case bad corporate governance

would lead to higher cash holdings.

Firm characteristics and cash holdings

In terms of determinants of cash holdings, a distinction can be made between country

characteristics and firm characteristics. The firm characteristics that can affect cash holdings

will be discussed first.

Multinationality

Multinationality can affect cash holdings in two ways. First, based on the transaction motive,

large multinationals can have economies of scale with regard to cash management and thus

they are expected to hold relatively less cash. This is supported by the findings of Fernandes

and Gonenç (2016) who find a negative relationship between cash holdings and

multinationality. However, their results indicate a difference between emerging and

developed countries. Cash holdings tend to decrease when foreign sales of multinationals

increase in developed markets, while the contrary is the case in emerging markets. Opposed to

this reasoning there is the tax motive, which implicates that multinationals hold more cash

compared to domestic firms. Bates et al. (2009, p1989) argue that “corporations that would

incur tax consequences associated with repatriating foreign earnings hold higher levels of

cash”. As multinationals experience the consequences of this repatriation the most, they are

expected to hold more cash. This is supported by the findings of Pinkowitz et al. (2012), who

find that a large part of the increase in cash holdings in the United States is due to the increase

of cash holdings by multinational firms.

Following the transaction motive and the research of Gonenç and Fernandes (2016) would

lead to predicting a negative relationship between cash holdings and multinationality,

especially because the sample used in this paper consists of developed markets. On the other

hand, following the tax motive and the research of Pinkowitz et al. (2012) one could argue

that there is a positive relationship between cash holdings and multinationality. Because there

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seems to be no stronger evidence for one of both relationship, the following hypothesis is set

up:

Hypothesis 1: Cash holdings in Europe are affected by multinationality of firms.

Substitutes

There are different substitutes of cash holdings that affect the level of cash holdings in a firm.

It is expected that these substitutes are negatively related to cash holdings, as there is less

need to hold cash when a company is in possession of a substitute (Ferreira & Vilela, 2004).

This is in line with the precautionary motive, as substitutes decrease the necessity to hold cash

to be able to pay future investments and expenses. Substitutes for which a negative

relationship is expected are net working capital and dividends. Net working capital consists of

substitutes for cash, thus assets that can easily be turned into cash. With regard to dividends

Opler et al. (1999) mention that firms that pay dividend can raise capital by stopping to pay

dividend. Thus for firms that pay dividends to their shareholders, there is less need to hold

cash as they are in possession of a substitute.

Another determinant that can be seen as a substitute for holding cash is leverage. When

borrowing is seen as a substitute for cash, a negative relationship with cash holdings is

expected. However, when leverage of a firm increases, then the firm is increasingly likely to

experience financial distress. For this reason these firms increase their cash holdings to

decrease the risk of bankruptcy, thus for higher levels of leverage this argument suggests that

there is a positive relationship between leverage and cash holdings (Guney, Ozkan & Ozkan,

2007). This can be linked to financially constrained firms, which are discussed next.

Financially constrained firms

Financially constrained firms are more likely to hold higher levels of cash, as they have

greater difficulties to attract external capital compared to non-constrained firms. Highly

leveraged firms are expected to face greater costs of financial distress and thus they are likely

to hold more cash. Moreover, in line with this argument, industries with greater industry cash

flow volatility are expected to hold more cash, as they face greater difficulties to attract

external capital. (Denis & Sibilkov, 2009). This is because attracting external capital is more

difficult for businesses in high risk industries. Consequently, as financially constrained firms

need to hold more cash to pay for future investments and expenses, this can be linked to the

precautionary motive.

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Firm size

The negative relation between firm size and cash holdings found by Opler et al. (1999) can be

due to the fact that smaller firms are often younger and not as well-known as larger firms.

Therefore they will need to hold more cash in order to be able to utilize their investment

opportunities as they will have less access to capital markets compared to larger firms in the

case of market imperfections (Denis & Sibilkov, 2009). This is in line with the precautionary

motive. Moreover, it can be argued that there are economies of scale and thus larger firms will

hold less cash, which is in line with the transaction motive. (Bates, Kahle and Stulz, 2009).

Investment

According to Haushalter, Klasa and Maxwell (2006) firms with higher cash holdings are more

likely to increase their investment compared to other firms in their industry. Based on these

results one would expect a positive relationship between cash holdings and investment. Three

different types of investment are examined: R&D spending, capital expenditure and

acquisitions. First of all, in industries with high research and development (R&D) spending,

having more cash turns out to be more important for business performance compared to

industries with low R&D spending (Fresard, 2010). This leads to the expectation of a positive

relationship between cash holdings and R&D spending. Secondly, the findings of Opler et al.

(1999) show a positive relationship between capital expenditure and cash holdings. Firms

with high cash holdings invest in capital expenditure even when investing opportunities are

poor. Finally, firms with higher levels of cash holdings are more likely to make acquisitions

according to research by Harford (1998). In line with the agency motive of holding cash, he

finds that when there is bad governance in the firm, these acquisitions are often value

decreasing. This leads to the expectation of a positive relationship between acquisitions and

cash holdings. Besides the agency motive, the precautionary motive is relevant here as well,

as firms that invest more need to hold more cash to be able to finance future investments.

Another relevant factor here is the market-to-book value, as this is a measure of investment

opportunities or growth opportunities (Chen and Zao, 2006). Bates et al. (2009) argue that

firms with better investment opportunities will have higher cash holdings as it is costly for

these firms not to be able to use these investment opportunities. This argument is in line with

the precautionary theory.

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Cash flow

The effect of the cash flow on cash holdings can be explained in two ways. On the one hand it

can be argued that firms with higher cash flows accumulate more cash and thus have higher

cash holdings (Bates et al., 2009). This positive relationship is also found by Opler et al.

(1999). On the other hand, firms that have higher cash flows do not need to hold as much cash

as firms with lower cash flows as they can replenish their cash holdings more quickly

(Pinkowitz et al, 2016), which is in line with the precautionary motive.

Raising capital

Bates et al. (2009) argue that firms that raise capital have higher cash holdings just after they

raised this capital. After this their levels of cash will decrease as they spend the money they

raised. This effect of raising capital can be caused both by issuing debt and issuing equity.

Using the precautionary motive, it can be argued that firms that raised more capital will have

higher levels of cash holdings, as businesses will save this capital for when they need it.

Country characteristics and cash holdings

Next to the firm characteristics that influence cash holdings, the external environment of a

firm has an impact on this as well. Therefore the next section will deal with the country

characteristics. There are different country characteristics that can be distinguished which can

affect corporate cash holdings, such as the quality of institutions and the economic and

financial development of countries. Pinkowitz et al. (2016) distinguish these characteristics as

well and argue that institutions have an impact on the type of investment decisions that

companies make in a certain country. As the risk of expropriation increases, it become more

likely that a company will invest in assets that are harder to expropriate. As this affects the

firm characteristics of the companies operating in a country, cash holdings also differ as

institutions differ.

Moreover, firms in countries that have a poor investor protection are expected to hold more

cash, as they are subject to more agency problems (Dittmar, Mahrt-Smith, 2003). This is

confirmed by Pinkowitz et al. (2006), who find that cash that is held by companies in

countries with poor investor protection is valued less compared to countries with high investor

protection.

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With regard to financial and economic development, Love (2001) finds that companies in

countries with more developed financial markets have lower corporate cash holdings.

Developed financial markets make it easier for companies to attract money when they need

funds, therefore decreasing their need to hold cash in the firm, which is in line with agency

theory.

The crisis and cash holdings

The precautionary and transaction motives can explain why the 2007 financial crisis can

affect corporate cash holdings. First of all, the precautionary motive states that firms hold

more cash when access to capital markets is costly, which can be the case due to adverse

shocks such as a financial crisis. Thus, when firms were hit by the crisis, the precautionary

motive leads to the expectation that firms decreased their cash holdings, as they were holding

cash as a buffer that could be used in case of an adverse shock.

The second motive that affects cash holdings in times of crisis is the transaction motive,

which deals with the costs related to converting a noncash financial asset into cash. In a crisis

banks do not supply as much loans as usually. This makes borrowing for companies more

expensive or even impossible in a crisis. Therefore it is expected that cash holdings decrease

for companies during a crisis as they have to use internal funds instead of external funds to

finance their operations.

These two motives both expect cash holdings to decrease in times of crisis and these

arguments are supported by the research of Campello, Graham and Harvey (2010), who find

that firms that were financially constrained during the crisis were forced to decrease their cash

holdings in order to deal with the financial crisis. Moreover, Almeida et al. (2009) state that

firms used cash holdings and other relatively cheap sources of funding to mitigate the effect

of maturing debt when the crisis hit them in 2008. Kahle and Stulz (2013) have somewhat

different results. They find that firms that were not dependent on credit before the crisis

decreased their cash holdings during the crisis. However, firms that were dependent on credit

before the crisis did not reduce their cash holdings during the crisis. Pinkowitz et al. (2012,

2016) provide mixed results regarding the effect of the crisis on cash holdings. On the one

hand they find countries that clearly increased their cash holdings after the crisis compared to

before the crisis such as Japan. On the other hand they find that in the United Kingdom cash

holdings are clearly lower after the crisis compared to before the crisis. Overall, prior research

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provides either mixed results or a negative relationship between the crisis and cash holdings.

As only the negative relationship is supported by the motives, it is expected that there will be

a negative relationship between the crisis and cash holdings.

Cash holding motives and determinants

The expected relationships between the motives and the determinants of cash holdings is

summarized in table 1. It stands out that only multinationality is expected to have a negative

effect on cash holdings based on the transaction motive, while it has a positive effect on cash

holdings based on the tax motive. Moreover, the country related determinants (quality of

institutions and economic and financial development) and the crisis are expected to have a

negative relationship with cash holdings.

Table 1. Expected relationships between motives and determinants

Table 1 describes the expected relationship between the motives and the determinants of cash holdings discussed

in the literature review.

Precautionary Transaction Tax Agency

Firm determinants

Multinationality Negative Positive

Substitutes Negative

Financially constrained firms Positive

Firm size Negative Negative

Investment Positive Positive

Cashflow Negative

Raising Capital Positive

Country determinants

Quality of institutions Negative

Economic and financial development Negative Negative

Crisis

Crisis Negative Negative

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Data & methodology

Based on the literature above, the effect of multinationality on cash holdings will be

investigated. The following set up will be used to test the hypothesis and to find out what the

effect is of multinationality on cash holdings in the European Union.

Model

The following equation is used to answer the research question:

Cash holdingsi,c,t = α + β1*Multinationalityi,c,t + β2*Firm Controli,c,t + β3*Country Control,c,t

+ β4*Crisisi,c,t + 𝜀i,c,t

In which i is a subscript of firms, c is a subscript of countries and t is a subscript of time.

Using this model, the goal is to find the effect of multinationality on cash holdings. This

model controls for different firm and country characteristics discussed in the literature review.

The following section elaborates on the data composition and the different variables used.

Data

The sample period examined in this research will cover the years 2002 to 2015, this period is

chosen to have a large sample of both the pre-crisis and the crisis period. In order to create the

sample, countries from the European Union were selected. Next, countries that did not have

enough characteristics available were dropped. This resulted in a sample consisting of firms

from the Netherlands, Germany, France, Italy, Slovakia, Spain, Portugal, Luxembourg,

Ireland, Austria, Belgium and Greece. Firms from these countries were found using the Orbis

database, firm codes were then used to download firm data from the Datastream database.

Selected firms needed to be headquarters of publicly listed firms. This was done to make sure

that every company was present only once in the sample and to make sure that there was

enough information. Furthermore, firms that had no data on cash holdings and total assets

were omitted from the sample as these variables form the dependent variable. Financial and

utility companies are excluded from the sample in line with Opler et al. (1999). They argue

that this is necessary because the business of financial firms includes inventories of

marketable securities that are part of cash holdings, moreover they are subject to regulations

regarding capital requirements. Utility firms are excluded because they can be subject to

regulatory supervision of the government, which can lead to restrictions with regard to cash

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holdings. Initially, the sample consisted of 1082 firms. After omitting firms from the sample

that did not have sufficient data or were not available in the Datastream database, 1040 firms

were left in the sample.

The descriptive statistics in table 2 show that there are 9,707 observations of companies over

the sample period for the dependent variable cash ratio. The cash ratio has a minimum value

of 0 and a maximum value of 0.99 and the reported mean is 0.14.

Table 2. Descriptive statistics

Variable Observations Mean Std. Dev. Min Max

Cash ratio 9.707 0.1362 0.1410 0.0000 0.9889

Multinational 9.707 0.7436 0.4367 0.0000 1.0000

Crisis 9.707 0.6414 0.4796 0.0000 1.0000

Size 9.707 12.8192 2.2260 6.6631 19.7395

Cash flow 9.707 0.0608 0.1304 -2.6627 2.5121

R&D 9.707 10.1461 146.2722 0.0000 7735.2900

Capex 9.707 5.0798 7.2234 0.0000 190.0000

Equity

Issuance

9.707 0.0225 0.0964 -0.1116 2.1857

NWC 9.707 0.0164 0.1835 -1.4646 0.7884

Leverage 9.707 0.2392 0.1809 0.0000 0.9960

Industry

Volatility

9.707 128489.7000 194352.5000 489.0531 4760697.0000

MTB 9.707 1.6135 3.7509 0.0551 89.7045

Dividend 9.707 0.6384 0.4805 0.0000 1.0000

WGI 9.707 0.0351 1.0148 -2.6873 1.6945

ASDI 9.707 0.3449 0.1069 0.2028 0.7889

RADI 9.707 3.3029 0.8231 2.0000 5.0000

Bank Credit 9.707 96.2092 24.4605 29.8046 172.4112

Turnover 9.707 0.8890 0.5773 0.0015 3.7725

GDP 9.707 39377.0900 9926.5490 11144.4300 110001.1000

Figure 1 illustrates the development of cash holdings in the sample. Striking about this graph

is that the cash ratio decreases in from to 2007 to 2008, when the financial crisis affected the

world economy heavily. However, after this decrease, the cash ratio is almost at pre-crisis

level again in 2009 and after a somewhat constant period from 2009 to 2012, the cash ratio

increases to a level that is even higher than before the crisis.

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0

0,02

0,04

0,06

0,08

0,1

0,12

0,14

0,16

0,18

Figure 1. Average cash ratio of firms in the sample

To look into this in more detail, table 3 provides the cash ratio means per country over the

sample period of the countries that have ten or more companies in the sample, which leads to

the exclusion of Slovakia in the table. The table shows that for every country, the cash ratio

falls from 2007 to 2008. Moreover, in every country, apart from Luxembourg, the cash ratio

increases again in 2009.

Table 3. Country means of cash holdings for every year in the sample

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Austria .098 .087 .094 .135 .140 .137 .130 .141 .114 .107 .107 .105 .099 .109

Belgium .106 .134 .147 .137 .153 .152 .137 .151 .145 .138 .149 .156 .155 .180

France .142 .142 .147 .157 .153 .146 .143 .156 .158 .156 .153 .165 .180 .186

Germany .158 .166 .167 .181 .180 .174 .161 .170 .169 .162 .168 .173 .176 .169

Greece .076 .075 .070 .059 .062 .070 .066 .078 .077 .069 .070 .071 .074 .081

Ireland .085 .071 .121 .088 .085 .068 .064 .071 .096 .076 .075 .088 .096 .086

Italy .126 .114 .111 .118 .114 .114 .110 .119 .114 .106 .122 .116 .151 .143

Luxembourg .066 .095 .153 .160 .126 .172 .146 .124 .132 .144 .129 .131 .122 .141

Netherlands .135 .122 .164 .134 .119 .197 .123 .137 .163 .146 .127 .165 .152 .152

Portugal .050 .054 .043 .066 .052 .062 .042 .090 .120 .126 .117 .137 .116 .113

Spain .099 .101 .131 .133 .141 .132 .094 .096 .117 .125 .117 .121 .119 .132

To compare the pre-crisis period cash holdings with the crisis period cash holdings, a test for

equality of means is used. A variance ratio test rejected the null hypothesis that the standard

deviations are equal and thus a test for equality of means with unequal variances is used. The

results are shown in table 4. The means indicate that the cash holdings in the crisis sample are

higher compared to the pre-crisis sample. This is however not confirmed by the alternative

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hypothesis of the equality of means test which states that crisis cash holdings are larger than

pre-crisis cash holdings. It is striking that the mean increased instead of decreased as was

expected. However, this notion should be treated with caution as the result is not significant at

any level.

Table 4. Equality of means test for the crisis

This table compares the means of cash ratios in the pre-crisis period and the crisis period, without

taking into account any other variables.

Group Observations Mean Cash ratio

Pre-crisis 3,485 0.1350

Crisis 7,789 0.1370

Difference = mean(Pre-crisis) – mean(Crisis)

Ha: diff < 0 Pr(T<t) = 0.2507

To look into the effect of multinationality, a test for equality of means is used again. The

variance ratio test rejects the null hypothesis that the standard deviations are equal and thus a

test for equality of means with unequal variances is used again. The results show that the

mean for multinational firms is clearly lower in comparison to domestic firms. This is

confirmed by the acceptance of the alternative hypothesis that the mean cash ratio of domestic

companies is larger compared to multinational firms, which is significant at a 0.01

significance level. This t- test thus provides preliminary evidence that the cashratios of

multinational companies are smaller than the cash ratios of domestic companies.

Table 5. Equality of means for multinational firms

This table compares the means of cash ratios of domestic firms and multinational firms, without taking

into account any other variables.

Group Observations Mean Cash ratio

Domestic firms 2,500 0.1466

Multinational firms 7,224 0.1327

Diff = mean(Domestic firms) – mean (Multinational firms)

Ha: diff > 0 Pr(T>t) = 0.0001

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As the report of the CPB (2014) in the introduction mentions higher cash holdings in the

Netherlands compared to the core-EUR, this will now be looked into in more detail. The

difference will be examined by performing equality of means tests between the countries of

the Core-EU (Germany, France, Belgium, Italy) and the Netherlands. These tests are

performed to determine whether cash ratios in the Netherlands differ statistically significant

from the other countries. First of all a variance ratio test rejected the null hypothesis that the

standard deviations are equal for all countries, thus a test for equality of means with unequal

variances is used. The outcome of these tests (see appendix, table 13-16) show that the cash

holdings in the Netherlands are significantly smaller than cash holdings in Germany and

significantly larger than cash holdings in Italy. There are no significant differences found

between the cash holdings in Belgium, France and the Netherlands. It has to be noted here

that no other variables are taken into account, so these tests only provide preliminary

evidence.

Variables

In this section the different variables will be described, exact definitions and sources can be

found in the appendix, table 17. All variables are denoted in Euro’s, except for GDP per

capita. Moreover, all variables were examined for possible non normality and outliers. This

resulted in the exclusion of several outliers and the usage of the logarithm of size.

The cash ratio will be the dependent variable, which is defined as cash divided by total assets,

this is in line with Pinkowitz et al. (2016) and Bates et al. (2009) and is sourced from

Datastream.

The degree of multinationality consists of the amount of foreign sales divided by the total

sales of a company. A multinational company is a company with more than 25 percent foreign

sales. This definition is sourced from Worldscope by Pinkowitz et al. (2016) and is in line

with Ferrnandes and Gonenç (2016) and Pinkowitz et al. (2012). When a company is a

multinational company in one year, it will be a multinational for all years in the sample,

which is in line with Pinkowitz et al., 2016.

With regard to firm characteristics, there will be proxies for the firm determinants of cash

holdings, which will be discussed next. All firm characteristics are taken from the Datastream

database. The substitutes of cash holdings that will be taken into account are non-cash net

working capital to assets, dividends and leverage. With regard to dividend, an indicator

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variable is used that becomes 1 if a firm pays dividend if a firm does not the variable is 0.

Leverage is measured by total debt to assets. It is expected that the substitutes are negatively

related to cash holdings, as higher substitutes reduce the incentive to hold cash.

To measure firm size, the logarithm of total assets is used. The relationship between firm size

and cash holdings is expected to be negative, as there are economies of scale with cash

management and thus larger firms need relatively less cash. A logarithm is used as the

distribution of firm size was non-normal.

To measure investments, R&D expenses to sales and capital expenditure to assets are used.

When firms have no value for R&D expenses, then tis variable is set to 0, in line with Bates et

al. (2009). The variable acquisition was not available in various databases. A positive

relationship is expected, as firms that invest much need money to do these investments. Firm

characteristics that cover the extent to which firms are financially constrained are leverage

and the industry’s cash flow volatility. A positive relationship is expected here, as more

financially constrained firms face more difficulties when attracting external capital, therefore

they need more cash to stay in business.

The market to book value of the assets serve as a proxy for the investment opportunities of a

company. The better the investment opportunities, the more cash a firm is expected to hold, as

adverse shocks and financial distress are more costly (Bates et al., 2009)

The controls for firms that raise capital are next. There are controls for equity and debt issues

because capital raising firms tend to have more cash after they raised capital and their cash

decreases again when they spend the capital they raised (Bates et al., 2009). Net debt

issuance is measured by the long term debt due in one year plus total long term debt minus a

lagged long term debt due in one year and a lagged total long term debt. Net equity issuance is

measured by net proceeds from sale divided by the issue of common and preferred stock,

which is available on Datastream.

To measure country characteristics that affect cash holdings, the same variables as Pinkowitz

et al. (2016) are used. First of all, as a proxy for the quality of institutions, indicators from the

Worldwide Governance Indicators (WGI) are used: Voice and Accountability; Political

Stability and absence of Violence/Terrorism; Government Effectiveness; Regulatory Quality;

Rule of Law and Control of Corruption. It is noted that Oman and Arndt (2006, 2010)

18

criticize the WGI index, because the indicators are based on an average of zero. This means

that if a value changes in one country, then values of other countries change as well.

Consequently, values of countries can change, while there is no actual change in the country.

However, the WGI consist of much information and they give a general view of the

institutional quality of a country, which does make them useful in research.

In appendix, table 11 a correlation matrix for the WGI variables is provided, as the six

indicators are summarized in one variable. The correlation values between the different WGI

variables is varying from 0,55 to 0,96, which indicates that the WGI are subject to

multicollinearity. This is not surprising, as the different variables are highly correlated

because they all measure a component of the quality of the institutions and governance in a

country. Although Pinkowitz et al. (2016) do not take this into account, other research does.

For example Globerman and Shapiro (2002) and Buchanan et al. (2011) do address this

problem by using a principal component factor analysis. This approach is followed here as

well and the results of this approach can be found in the appendix, table 12. This table shows

that only the first factor can be retained, as its eigenvalue is 4.84, while the other factors have

eigenvalues below 0.55. In table 12 the factor loadings are shown, from this table it can be

concluded that political stability reports a high uniqueness value compared to the other

variables with a value of 43.78 percent. This means that more than 43 percent of the variance

in the variable is not explained by the factor.

The next country characteristics that are taken into account is the anti-self-dealing index

(ASDI) from Djankov et al. (2008) which measures the extent to which minority shareholders

are legally protected against expropriation by employees of the firm where they are

shareholders. A similar variable is the revised anti-director index (RADI), which was

originally created by La Porta (1998) and revised by Djankov et al. (2008). This index is a

measure of investor protection and the data can be found on the website of Andrei Shleifer1.

Data is different for all countries, but does not change over time.

The measures of financial and economic development are discussed now. The development of

the corporate bond market can be measured by bond market capitalization to GDP. It is

expected that a more effective bond market will lead to easier access to external capital and

thus the need for cash holdings will be smaller when bond market capitalization to GDP is

1 See: http://scholar.harvard.edu/shleifer/publications/law-and-economics-self-dealing

19

high. This data is sourced indirectly from the World bank and is available for all countries in

the sample until 20112.

The second ratio is stock market trading divided by the stock market capitalization. This is a

measure for the activity of the stock market and a proxy for stock market development. A

better developed stock market is expected to lead to lower cash holdings, as this increases the

availability of external capital. Bank credit is used as a proxy for development of the banking

sector. A better developed banking sector is expected to lead to easier access to external

capital and thus lower cash holdings. The last measure is GDP per capita in 2010 US dollars,

this measure is included to make sure that no other variable corrects for changes in GDP per

capita (Pinkowitz et al., 2016). These measures are sourced from the World Bank.

Method

First of all, both firm and country determinants will be taken into account to look into the

effect of multinationality and to see whether the crisis has an influence on cash holdings. Net

debt issuance and bond market had a large number of missing values, which reduced the

available sample heavily. In order to increase the available data, these two variables were

excluded from the final sample. A Hausman test was conducted to see if a fixed or random

model was appropriate. The results (see appendix, table 9) implicated that a fixed model was

appropriate to use. As there was a focus on the differences between countries, a country fixed

effects regression with clustered standard errors is used. These standard errors are clustered

by firm and take into account possible heteroscedasticity. To check for multicollinearity, a

correlation matrix (see appendix, table 8) was made. There was one correlation above 0.5, this

was the case between GDP and the WGI. However, as this correlation is not with the

independent variable and leaving them out would harm the model, it is chosen to

acknowledge that there may be multicollinearity in the model. Standard errors may increase

because of this.

2 See: https://knoema.com/WBFDSD2013Apr/financyial-development-and-structure-dataset-april-

2013?tsId=1022600 data available from 1990

20

Empirical Results

The outcome of the regression analysis is shown in table 7. The regression has an R-squared

of 0.33, which means that 33 percent of the variance in the cash ratio is explained by the firm

characteristics in the sample.

The results indicate that there is a positive relationship between being multinational and the

cash ratio, as the positive coefficient of 0.0067 shows. This is contrary to the preliminary

evidence provided by the equality of means test in table 5. However, as the probability value

is 0.438, the result is not significant at any significance level. Therefore this results fails to

confirm the first hypothesis, which stated that multinationality affects cash holdings.

Table 7. Country fixed effects regression with clustered robust standard errors

This table shows the output of the country fixed effects regression with clustered robust standard

errors. Coefficients are shown next to the variables, standard errors are displayed in parentheses.

Countries are compared to The Netherlands due to the dummy trap.

Variables Regression Output Countries (continued)

Multinational 0.0068 Austria -0.1163

(0.0087) (0.0224)

Crisis 0.0011 Belgium -0.5201*

(0.0037) (0.0788)

Size -0.0068*** France -.1873

(0.0016) (0.040)*

Cash flow 0.0310 Germany 0.0085

(0.0280) (0.0228)

R&D 0.0001** Greece -0.1162*

(0.0000) (0.0354)

Capex -0.0011*** Ireland -0.7494*

(0.0003) (0.1008)

Equity Issuance 0.3360*** Italy -0.4421*

(0.0389) (0.720)

NWC -0.1720*** Luxembourg -0.2333*

(0.0185) (0.0487)

Leverage -0.3300*** Portugal -0.4241*

(0.0192) (0.0716)

Industry Volatility 0.0000* Slovakia -0.1388*

(0.0000) (0.0579)

MTB 0.0010 Spain -0.0028

(0.0009) (0.0335)

Dividend 0.0015 Constant 0.2143*

(0.0055) (0.0405)

WGI -0.0097

21

(0.0061) Total Observations 9,707

ASDI 1.7150*** R-squared 0.329

(0.2090)

RADI -0.1180***

(0.0106)

Bank Credit 0.0001

(0.0001)

Turnover -0.0020

(0.0026)

GDP 0.0000

(0.0000)

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

When looking at the other probability values, it stands out that the dummy variable to take

into account the crisis is insignificant. This is in line with the preliminary evidence found in

the equality of means test is table 4, where it was found that pre-crisis cash ratios were not

statistically significantly different from crisis cash ratios. The other variables are statistically

significant, except for cash flow, MTB, Dividend, WGI, turnover, bank credit and GDP.

The results show that size has a negative and significant coefficient. This indicates that there

are economies of scale with cash holdings and the results are in line with both the transaction

motive and the precautionary motive.

The coefficient for the investment characteristic R&D is positively related to the cash ratio.

For R&D the coefficient is relatively small considering this variable consist of R&D

expenditures divided by sales, however the coefficient is significant. Capex, a variable

measuring capital expenditure, is the other investment characteristic taken into account.

Contrary to R&D, capex is negatively related to the cash ratio, which is contrary to what

Opler et al. (1999) find. Both the precautionary motive and the agency motive led to the

expectation of a positive relationship between investment and the cash ratio, which is only

supported by the coefficient of R&D.

With regard to substitutes, the NWC has a negative coefficient. When looking at the leverage,

there is a relatively large negative significant coefficient of -0.3300. It has to be noted here

that the leverage of the companies in the sample is between 0 and 1, which implicates that if a

company would increase its leverage with 0.01 unit, then this would result in the cash ratio

decreasing by 0.0033 unit. The results indicate that the substitutes NWC to assets and

leverage are negatively related to the cash ratio, as expected. When firms hold more

22

substitutes of cash holdings, there is less need to hold cash, which is in line with the

precautionary motive.

Equity issuance is positively related to the cash ratio. This suggests that when firms have

raised capital, they hold more cash, which is in line with the precautionary motive. The

industry volatility is negatively related to the cash ratio. However, the corresponding

coefficient is very low. The negative relationship is contrary to the expectation that firms with

higher industry cash flow risk were expected to have higher cash ratios to compensate for the

fact that they face greater difficulties in attracting external capital.

The ASDI coefficient is positive and significant. Better minority shareholder protection was

expected to lead to a lower cash ratio, however the results indicate that this is the other way

around. The coefficient of RADI is negatively related to the cash ratio and significant. This

result implies that more investor protection leads to lower degrees of the cash ratio, which is

in line with the agency motive.

The coefficients on the country fixed effects show the intercepts of firms in the countries in

our sample relative to firms in the Netherlands, as fixed effects for the Netherlands are not

included due to the dummy trap. It stands out that all countries except Germany have smaller

coefficients than The Netherlands. The coefficients are significant for all countries except for

Germany, Spain and Austria. These results correspond to the equality to the equality of means

tests for Germany and Italy that were executed earlier (see appendix, table 13-16). For

Belgium and France, the equality of means tests didn’t show a significant difference in means

between the Netherlands and France and Belgium, but the regression results which control for

time-varying firm characteristics and time-varying country characteristics show that Dutch

firms have significantly higher average cash ratios than firms from these countries, as well as

compared to firms from Greece, Ireland, Portugal, Luxembourg and Slovakia. This suggests

that non-time varying factors in the Netherlands result in significantly higher cash ratios

compared to eight of the other countries in the sample. Potential non-time varying factors that

could affect cash holdings of Dutch firms could be features of the tax system or the

investment climate. In addition, other time-varying firm and country characteristics that were

not considered in the analysis could drive the cross-country differences. This question is left

for further research.

23

Conclusion and limitations

This research looked into corporate cash holdings in the European Union. Preliminary

evidence seemed to point at a negative relationship between multinationality and cash

holdings. However, in the regression analysis the effect of multinationality on cash holdings

in the European Union was not found to be significant. This is not striking as mixed results

were provided in earlier research. With regard to the effect of the crisis on cash holdings, the

overall development of the cash ratio over the sample, as shown in figure 1, shows that the

cash ratio was quite stable in the years prior to the crisis. When taking into account the effect

of the crisis, it stands out that the start of the crisis in 2007 decreased cash holdings of firms

all over Europe. This was true for every country in the sample. However, this effect was only

visible for one year, in 2009 all countries except for Luxembourg reported growing cash

holdings compared to the prior year. Even more striking, in recent years (from 2012 to 2015)

the cash holdings even started to grow to levels that were even higher than before the crisis.

When looking at the differences between European countries, it stands out that there are

significant differences among countries with regard to cash holdings. The regression

compared all countries in the sample to the Netherlands, findings include that Portugal, Italy,

France, Greece, Slovakia, Ireland, Luxembourg and Belgium all have negative significant

coefficients. When looking into the difference that between the core-EU and The Netherlands

mentioned in the introduction, preliminary evidence provided no statistical proof that The

Netherlands has higher cash holdings compared to countries in the core-EU, which included

Germany, Belgium, France and Italy. The Netherlands only reports statistically significant

higher cash holdings compared to Italy. When comparing to Germany, the Netherlands

reports significantly smaller cash holdings, while the differences with Belgium and France are

insignificant. However, when taking into account the determinants of cash holdings, it is

striking to see that the Netherlands has significantly higher cash ratios than eight out of eleven

countries in the sample. This means that being just the fact that a firm is Dutch increases the

cash holdings of a company.

This paper extends the mixed existing research regarding multinationality and cash holdings.

Moreover, it shows that the crisis did not have a large impact on cash holdings over the

sample period. Besides that, the paper has a European perspective, whereas other papers

concerned with cash holdings often focus on the United States. In this sense it is striking to

24

see that within Europe there are differences between countries, that cannot be explained by

current literature on cash holdings.

One of the limitations of this research is that the variable acquisition to assets was not

available. This variable is seen as one of the determinants of cash holdings and was used by

many papers such as Pinkowitz et al. (2016), Fernandes and Gonenç (2016) and Bates et al.

(2009). Moreover, the variables net debt issuance and bond market were not used although

they were available. The usage of these variables would decrease the sample substantially,

which is why they were dropped.

Directions for future research could include a focus on what characteristics of certain firms or

countries determine cash holdings. As shown in this paper, many factors are already known,

but the regression results presented show significant cross-country differences when

controlling for time-varying firm and country characteristics. Exploring the factors driving

these differences, such as other firm characteristics or other (non-time varying) country

characteristics, is a question for future research.

Moreover, the results regarding the crisis are striking. The cash ratio went down in the first

year of the crisis, but recovered to pre-crisis levels in two years, this was true for all but one

country in the sample. Thus to look into what happened to the cash holdings in other countries

during the crisis years might be another direction for future research.

25

References

Almeida, H., Campello, M., Laranjeira, B., & Weisbenner, S. (2009). Corporate debt maturity

and the real effects of the 2007 credit crisis (No. w14990). National Bureau of Economic

Research.

Bates, T. W., Kahle, K. M., & Stulz, R. M. (2009). Why do US firms hold so much more cash

than they used to?. The journal of finance, 64(5), 1985-2021.

Campello, M., Graham, J. R., & Harvey, C. R. (2010). The real effects of financial

constraints: Evidence from a financial crisis. Journal of financial Economics, 97(3), 470-487.

Chen, L., & Zhao, X. (2006). On the relation between the market-to-book ratio, growth

opportunity, and leverage ratio. Finance Research Letters, 3(4), 253-266.

Denis, D. J., & Sibilkov, V. (2009). Financial constraints, investment, and the value of cash

holdings. Review of financial studies, hhp031.

Dittmar, A., Mahrt-Smith, J., & Servaes, H. (2003). International corporate governance and

corporate cash holdings. Journal of Financial and Quantitative analysis, 38(01), 111-133.

Fernandes, N., & Gonenc, H. (2016). Multinationals and cash holdings. Journal of Corporate

Finance, 39, 139-154.

Ferreira, M. A., & Vilela, A. S. (2004). Why do firms hold cash? Evidence from EMU

countries. European Financial Management, 10(2), 295-319.

Foley, C. F., Hartzell, J. C., Titman, S., & Twite, G. (2007). Why do firms hold so much

cash? A tax-based explanation. Journal of Financial Economics, 86(3), 579-607.

Fresard, L. (2010). Financial strength and product market behavior: The real effects of

corporate cash holdings. The Journal of finance, 65(3), 1097-1122.

Guney, Y., Ozkan, A., & Ozkan, N. (2007). International evidence on the non-linear impact of

leverage on corporate cash holdings. Journal of Multinational financial management, 17(1),

45-60.

26

Harford, J. (1999). Corporate cash reserves and acquisitions. The Journal of Finance, 54(6),

1969-1997.

Haushalter, D., Klasa, S., & Maxwell, W. F. (2007). The influence of product market

dynamics on a firm's cash holdings and hedging behavior. Journal of Financial Economics,

84(3), 797-825.

Jansen, C., & Ligthart, M. (2014). Spaaroverschot niet-financiële bedrijven: ontwikkeling,

oorzaken en gevolgen. Retrieved February 17, 2017, from

https://www.cpb.nl/publicatie/spaaroverschot-niet-financi%C3%ABle-bedrijven-

ontwikkeling-oorzaken-en-gevolgen

Keynes, J.M. (1936). The General Theory of Employment. Interest and Money. Hartcourt

Brace, London.

Porta, R. L., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. (1998). Law and finance.

Journal of political economy, 106(6), 1113-1155.

Love, I. (2001). Financial development and financing constraints: international evidence from

the structural investment model (Vol. 2694). World Bank, Development Research Group,

Finance.

Moodys: US corporate cash pile, led by tech sector, to grow to $1.77 trillion by end of 2016.

(2016, November 03). Retrieved April 12, 2017, from

https://www.moodys.com/research/Moodys-US-corporate-cash-pile-led-by-tech-sector-to--

PR_357576

Opler, T., Pinkowitz, L., Stulz, R., & Williamson, R. (1999). The determinants and

implications of corporate cash holdings. Journal of financial economics, 52(1), 3-46.

Oman, C., & Arndt, C. (2006). Governance Indicators for Development (No. 33). OECD

Publishing.

Oman, C. P., & Arndt, C. (2010). Measuring governance. OECD Development Centre Policy

Briefs, (39), 1.

27

Pinkowitz, L., Stulz, R., & Williamson, R. (2006). Does the contribution of corporate cash

holdings and dividends to firm value depend on governance? A cross‐country analysis. The

Journal of Finance, 61(6), 2725-2751.

Pinkowitz, L., Stulz, R. M., & Williamson, R. (2016). Do US firms hold more cash than

foreign firms do?. Review of Financial Studies, 29(2), 309-348.

Pinkowitz, L., Stulz, R. M., & Williamson, R. (2012). Multinationals and the high cash

holdings puzzle (No. w18120). National Bureau of Economic Research.

Still slipping the net. (2015, October 08). Retrieved April 06, 2017, from

http://www.economist.com/news/business/21672232-europes-corporate-tax-havens-say-they-

are-reforming-up-point-still-slipping-net

Appendix

Table 8. Correlation matrix of cash holding determinants

This table consists of the correlations between all variables used in the regression in table 7. Correlations above 0.5 could implicate multicollinearity. This is

only the case with GDP and the WGI however, to make sure the model is not harmed both variables are included in the model.

Cash

ratio

Multinational Crisis Size Cash

flow

R&D Capex Equity

Issuance

NWC Leverage

Cash ratio 1

Multinational 0 1

Crisis 0,0067 -0,0618 1

Size -0,203 0,3255 -0,0194 1

Cash flow -0,0944 0,0846 -0,0871 0,2418 1

R&D 0,1591 -0,0392 0,0036 -0,0599 -0,1868 1

Capex -0,0543 -0,0279 -0,1015 0,0383 0,1205 -0,0025 1

Equity Issuance 0,2953 -0,0624 -0,0306 -0,1822 -0,3546 0,1512 0,0995 1

NWC -0,0964 0,1369 -0,079 -0,115 0,1547 -0,0139 -0,0581 -0,0653 1

Leverage -0,4289 -0,0125 0,0489 0,1884 -0,1005 -0,0247 0,0728 -0,0678 -0,2682 1

Industry Volatility -0,0653 0,0846 -0,0313 0,3526 0,0597 -0,0009 0,0448 -0,0295 -0,0391 0,0101

MTB 0,0484 0,0083 -0,011 0,015 -0,0012 0,045 -0,0058 0,0415 -0,0046 -0,0487

Dividend -0,0917 0,1331 -0,0526 0,4302 0,3127 -0,0784 0,0561 -0,1991 0,1153 -0,0577

WGI 0,1548 0,203 -0,1648 0,0923 0,0622 0,0346 0,0677 0,0568 0,0992 -0,2846

ASDI 0,0105 0,0756 -0,0637 0,107 0,0336 0,0044 0,0111 0,0338 -0,0692 -0,0206

RADI 0,0758 0,1309 -0,0219 0,0945 0,0355 -0,0134 0,007 0,039 -0,0248 -0,0808

Bank Credit -0,0639 0,0079 0,1472 0,0681 -0,025 -0,0115 -0,0417 -0,0205 -0,0976 0,1838

Turnover 0,0471 0,0797 0,0208 0,0436 0,034 -0,0014 0,0153 -0,0155 0,0547 -0,0641

GDP 0,1049 0,1522 0,0018 0,0866 0,0528 0,031 0,0519 0,0414 0,031 -0,2128

29

Table 8. Correlation matrix firm characteristics (continued)

(Continued) Industry Volatility MTB Dividend WGI ASDI RADI Bank Credit Turnover GDP

Industry Volatility 1

MTB -0,022 1

Dividend 0,1033 0,0242 1

WGI 0,0314 0,0852 0,0466 1

ASDI 0,0422 0,237 0,025 0,1286 1

RADI 0,0459 0,1236 -0,0094 0,3259 0,3897 1

Bank Credit 0,0335 0,0572 -0,0537 -0,2802 -0,1259 0,4071 1

Turnover 0,0388 -0,0529 0,0255 0,0793 -0,1477 0,1542 0,144 1

GDP 0,0229 0,1316 0,0562 0,7054 0,1654 0,0297 -0,3192 -0,0638 1

Table 9. Hausman test

The outcome of the Hausman test shows that it is appropriate to use a fixed model for the

regression. The null hypothesis of random effects is rejected at a 0.01 significance level.

chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)

= 231,84

Prob>chi2 = 0.0000

Table 10 Correlation Matrix WGI

This table shows the correlations between the different variables that form the WGI.

Voice and

Accountability

Rule of

Law

Regulatory

Quality

Political

Stability

Government

Effectiveness

Control of

Corruption

Voice and

Accountability

1

Rule of Law 0.7287 1

Regulatory

Quality

0.7460 0.9054 1

Political

Stability

0.5541 0.6422 0.6977 1

Government

Effectiveness

0.7166 0.8868 0.8056 0.5654 1

Control of

Corruption

0.7471 0.9598 0.9188 0.6465 0.897 1

Table 11. Principal component factor analysis results

Factor Eigenvalue Difference Proportion Cumulative

Factor1 4.84001 4.32368 0.8067 0.8067

Factor2 0.51633 0.16029 0.0861 0.8927

Factor3 0.35604 0.18038 0.0593 0.9521

Factor4 0.17566 0.10179 0.0293 0.9813

Factor5 0.07387 0.03578 0.0123 0.9937

Factor6 0.03809 . 0.0063 1

31

Table 12. Factor loadings (pattern matrix) and unique variances

Variable Factor1 Uniqueness

Voice and Accountability 0.8326 0.3068

Rule of Law 0.9591 0.0801

Regulatory Quality 0.9470 0.1032

Political Stability 0.7498 0.4378

Government Effectiveness 0.9120 0.1683

Control of Corruption 0.9676 0.0638

Table 13. Equality of means test Germany-Netherlands

This table compares the means of cash ratios in The Netherlands and Germany, without taking into

account any other variables.

Group Observations Mean

Germany 2,612 0.1646

The Netherlands 239 0.1427

Diff = mean(German firms) – mean (Dutch firms)

Ha: diff > 0 Pr(T>t) = 0.0112

Table 14.Equality of means test Belgium-Netherlands

This table compares the means of cash ratios in The Netherlands and Belgium, without taking into

account any other variables.

Group Observations Mean

Belgium 740 0.1452

The Netherlands 239 0.1427

Diff = mean(Belgian firms) – mean (Dutch firms)

Ha: diff != 0 Pr(|T| > |t|) = 0.8246

32

Table 15. Equality of means test France-Netherlands

This table compares the means of cash ratios in The Netherlands and France, without taking into

account any other variables.

Group Observations Mean

France 2995 0.1459

The Netherlands 239 0.1427

Diff = mean(French firms) – mean (Dutch firms)

Ha: diff != 0 Pr(|T| > |t|) = 0.7343

Table 16. Equality of means test Italy Netherlands

This table compares the means of cash ratios in The Netherlands and Italy, without taking into

account any other variables.

Group Observations Mean

Italy 383 0.1175

The Netherlands 239 0.1427

Diff = mean(Italy firms) – mean (Dutch firms)

Ha: diff < 0 Pr(T < t) = 0.0074

Table 17. List of variables

ADRI Revised anti-director rights index, from:

https://scholar.harvard.edu/shleifer/publications?page=3

ASDI Anti-self-dealing index, from:

https://scholar.harvard.edu/shleifer/publications?page=3

Bank Credit Bank credit to GDP, sourced from the World bank

Bond Market Private Bond Market Capitalization to GDP, from:

https://knoema.com/WBFDSD2013Apr/financial-development-and-

structure-dataset-april-2013?tsId=1022600

33

Capex Capital expenditures divided by assets, from: Datastream

Cash Cash divided by assets, from: Datastream

Cash flow Cash flow divided by assets, from: Datastream

Debt Issuance Net debt issuance divided by assets. Net debt issuance is computed by:

(long term debt due in one year + total long term debt) – (lagged long

term debt due in one year + lagged total long term debt). From:

Datastream

Dividend Dummy variable, turns into 1if a firm pays dividend, from: Datastream

Equity Issuance Net equity issuance divided by assets. Net equity issuance consists of

net proceeds from sale and issue of common & preferred equity stock.

From: Datastream

GDP GDP per capita in 2010 US dollars, from: World bank

Industry volatility Industry mean of firm standard deviation of the cash flow of the prior

ten years, with a minimum of three years data availability to compute

firm volatility, from: Datastream

Leverage Total debt to assets. Total debt is computed by short term debt + long

term debt, from: Datastream

MTB Market to book value of total assets. Computed by: ((total assets -

total equity) + (common shares outstanding * share price)) / total

assets. From: Datastream.

MNC Dummy variable which turns into one if a firm is a multinational,

firms are multinational when 25% or more of their sales are from

abroad, from: Datastream.

NWC Net working capital to total assets, computed by: (working capital –

cash and short term investments) / total assets. From: Datastream.

R&D Research and Development to total sales, from Datastream

Size Logarithm of total assets, from: Datastream

Turnover Stock market turnover, from: World bank

WGI World Governance Indicators. A principal component factor analysis

is used to create this variable out of six indicators. From: World bank