International Tax Planning and the Determinants of Cash Holdings:
A Tax Motive for Holding Cash.
David S. Möllers
University of Groningen, Faculty of Economics and Business, dsmoellers@gmail.com. Combined Master Thesis for the Master of Science International Financial Management and Master of Science International Business and Management. Supervised by Wim Westerman and Henk Ritsema due on the 13.01.2017.
Abstract: This study investigates a tax based motive for holding cash. The empirical analysis deploys multiple OLS regression to compare accounting data of US Fortune500 firms cross-sectional in the year 2014 using long term GAAP and Current effective tax rates (ETRs) from the period 2004-2014. Effective tax rates have been used to distinguish between above industry average tax planners (TPs) and below industry average tax planners (NTPs). The sample consist of 266 US firm level observations separated in independent samples with 82 TPs and 184 NTPs. The findings show significant differences between the two samples. Firms that accumulate cash motivated by tax planning do not always follow the traditional relationships predicted by the literature based on precautionary, speculative and transactional motives. Noticeably, the relationship between leverage and cash holdings is highly significant in the NTP samples but no correlation is found in the TP samples. A significant positive relationship between foreign sales and cash holdings in the TP sample manifests the evidence for a tax based motive as well a stark positive relationship between R&D and cash holdings. Finally, firms categorized as TP on median hold 3% more cash than NTPs.
2
1. Introduction
On 30th August 2016 the European Commission released a statement concluding that the member state
of Ireland gave illegal tax benefits to Apple worth up to 13 billion Euro’s. The technology multinational was granted selective treatment by Ireland that enabled it to pay substantially less tax than competitors. An important element of this agreement involves profits being internally allocated to a “head office” which due to a legal mismatch of Irish and US tax code is not based in any country and thus not being taxed at all. Only a small percentage of profits were taxed in Ireland and allowed Apple to minimize its effective tax rate down to 0.005 per cent in 2014. The corporation seems more than capable of paying the fine considering its current cash holdings of more than 230 billion Euro’s (European Comission, 2016).
The Apple case raises questions about the capital structure of corporations applying tax planning strategies. Researchers find that US corporations with comparable tax planning schemes prefer to not repatriate their profits to the USA but keep their cash abroad (Foley et al., 2007). This results in no corporate taxation of foreign profits in the USA and reduced overall effective corporate tax rate internationally. Profits are not directly paid-out to home country shareholders and remain available within the corporation as liquidity or investment funds (Killian, 2006; McIntyre, 2015; Duchin et al., 2015).
This study investigates the effect of having cash trapped abroad as measured by lower effective tax rates on the determinants of cash holdings. Opler et al. (1999, pp. 4) investigated the determinants for holding cash, and defined the optimum as,” a level that the marginal benefit of cash holdings equals the marginal cost of those holdings”. Furthermore, he explains that the cost of holding those liquid assets include a liquidity premium as well as possible tax disadvantages. Benefits of holdings liquid assets are described as the savings on transaction costs in the process of raising funds for investments when other funds are expensive and the liquidity can be used to finance operations without using its line of credit.
3 This research adopts the hypothesis of US tax treatment of profit repatriation partially responsible for increasing cash holdings of US multinationals. I seek to find firm level differences in managing liquid assets between above average tax-planners (TPs) and below average tax-planners (NTPs). The following research question is applied:
What are the effects of tax planning strategies on the main financial determinants of corporate cash holdings from US corporations?
A number of studies discuss the subject of repatriation cost and cash holdings (e.g. Killian, 2006; Pinkowitz et al., 2016; Foley et al., 2007; Bates et al., 2009, Faulkender et al., 2016). However, the existing research on the topic suffers from confusion in its findings and the tax based motive for cash holdings is yet to be researched in its totality. To the best of my knowledge, former research has not yet looked explicitly at the tax planning hypothesis and investigated the implications for the determinants of cash holdings.
The empirical analysis of the study deploys multiple OLS regression to compare accounting data of U.S. Fortune 500 firms cross-sectional in the year 2014 and applies 10 year accumulated effective tax rates (ETRs) from the period 2004-2014. Effective tax rates are a less biased indicator for the global tax paid and serve as a proxy to distinguish between above and below average tax planners in each Industry. The accumulated 10-year effective tax rates were used to classify 266 firms into 184 below average tax planners and 82 above average tax planners. In order to account for industry differences in tax rates, the analysis was categorized by the first digit SIC code. DataStream served as the main source to extract accounting data for the years 2004 - 2014. This data was substituted with help from a NGO, Citizen for Tax Justice (CTJ). In order to deliver robust results, the samples were constructed with the help of two different proxies for effective tax rates, GAAP ETR and the Current ETR. Furthermore, regression analysis was once performed on the dependent variable cash holdings as defined by Al-Najjar’s (2013) and again by as defined Foley et al. (2007). The data collection focused on a sample of U.S firms because the costs of repatriation tax and therefore the tax based motive for holding cash is bound to the national tax code of the United States of America.
I find robust results providing evidence for the existence of a tax based motive for above average tax planners in the TP sample. In general, the traditional determinants of cash holdings do not seem to hold their significance when tax planning is involved. In particular, leverage, research and development spending (R&D) and foreign sales (internationalisation) were found to differ substantially from the NTP sample and statistically behave as predicted by the tax based motive.
4 the two samples and ends with a discussion of the results. Finally, conclusions are presented before outlining the implications and recommendations for further research.
2. Literature Review
2.1 Cash Holdings: Definition
Cash is an essential part of a firm’s (daily-) operations, since without cash a firm is unable to operate and to finance its activities. Financial liquidity in turn, refers to the measurement of the ease with which an individual or company can meet their financial obligations with the liquid assets available to them. In this definition, and also in financial literature in general, the term cash covers real cash and short-term marketable securities or cash equivalents (Opler et al, 1999; Bates, et al, 2009). Cash equivalents can be defined as assets that can easily be changed into cash. Examples of cash equivalents include saving accounts, bonds (especially near their maturities) and money markets.
2.2 The meaning of Cash Holdings: What do corporations need the cash for?
In the absence of significant market frictions, the firm should optimally maintain zero excess liquidity (Kim, Mauer, & Sherman, 1998). In the face of capital market imperfections, firms can benefit from holding cash for different interconnected purposes which explain different optimal levels of cash holdings.
The transaction motive refers to the amount of cash holdings that is actually needed to feed the company’s operations. The amount of cash in need consists of the payment-obligations on the one hand (Opler et al., 1999; Damodaran, 2008; Bates et al., 2009, Lyandres & Palazzo, 2012) and the amount of cash-holdings required to be able to raise funds on the other hand (Custodio et al.,2005). Keynes (1936) described the transaction motive behind cash holdings as the cost of converting substitutes for cash into actual cash. This implies that not holding cash yields costs to the firm. Firms can raise cash and liquid assets via decreasing dividends or investment and accessing funds externally via selling its assets or accessing the capital market. However, the process of raising cash has fixed and variable transaction costs depending on the type of transaction and firm characteristic (Lyandres & Palazzo, 2012). Thus, the optimal level of cash holdings in this scenario is reached when the holdings suffice to support operations and minimize flotation costs to finance projects.
5 unexpected circumstance occurs, the firm has to employ extremely costly financing resources or, in the worst case, bankruptcy due to non-availability of financial resources (Custodio et al., 2005; Kim et al., 2011). The amount of cash needed in this motive depends on different business-environmental circumstances which determine the likelihood of shocks in that environment (Damodaran, 2008). In a situation where cash is held in excess of transactional purposes, opportunity costs arise from a misallocation of the funds which earns lower returns. Keynes (1936) finds a major advantage of liquidity is that it allows firms to make investment instantly to increase its value. The speculative motive firms hold cash because they could miss good investment opportunities otherwise. (Jensen & Meckling, 1976; Myers & Majluf, 1984). Almeida et al. (2002) explain that cash holdings can be valuable, because they can be used to increase the probability of a firm to be able to perform investments in the future when access to capital markets is constrained. On the other hand, increasing the amount of cash holdings for the same firm is costly because it decreases the amount of cash that is to be invested into positive NPV projects.
These three classical motives come to acknowledge the value of cash holdings, but seek to explain the motivation that drives firms to differ in the amount of cash that is accumulated.
2.3 Cash Holdings Theories
There are several theoretical frameworks applicable to the study of corporate cash holdings and this research. This section outlines the trade-off theory and the pecking-order theory to demonstrate how they complemented the cash holdings literature.
6 accounting for trade-off between future financing needs and costs of external finance. Here, the cash holdings of firms increase for precautionary purposes when uncertainty for future income is high and/or funds from external financing partners are pricey. Controversially, Anderson and Carverhill (2012) demonstrate in a benchmark of U.S. industrial firms that there is a negative relationship leverage and levels of cash holdings. Palazzo (2012) examines the optimal corporate cash policy because of a trade-off between cash flows and the systematic risk for cash holdings. He finds that non-risk neutral investors prefer a trade-off between the present dividend distribution policy and precautionary levels of cash holdings to avoid costs in the future. Findings by Ferreira and Vilela (2004) and Opler et al. (1999) demonstrate that there is a positive relationship between cash holdings and cash flows of European and American firms, but the size, number and leverage of substitutes to liquid assets have a negative relationship to levels of cash holdings and investment opportunity.
Pecking-Order theory assumes that such a concept as the optimal cash level does not exist. The level of cash holdings is considered an outcome of decisions concerning investments and financing these investments. Depending on these decisions, firms prefer (1) internal funds as taken from retained earnings, (2) safe and risky debt from external financing partners and (3) debt with equity. The order of these financing options is important. Firstly, firms shall depend on internal funds before considering debt or finally equity (Myers & Majluf, 1984). Hence, when positive NPV investment opportunities uncover and the firm’s level of cash holding is not sufficient only then debt or equity should be used as a source of finance. In this logic, there is a negative relationship between cash holdings and leverage if there is a sufficient supply of good investment opportunities (Ferreira & Villella, 2004). Managers need to inform shareholders about the real state of the corporation if it is publicly traded. However, a certain degree of information asymmetry will persist. This creates asymmetric information costs which can influence the choice between internal and external funds (Myers & Majluf, 1984). When confronted with high information asymmetry, assets on the balance sheet and opportunities for future growth can be undervalued and will consequently increase the costs of obtaining external financing and lead corporation to build up cash holdings internally (Dittmar et al., 2003). Firms that face increased cost for raising funds with high asymmetric information differences tend to hold more cash (Opler et al. 1999). Also, Fereira and Vilela (2004) find their result in line with this theory. Their research reveals that firms with higher levels of cash holdings have lower leverage. Dittmar et al. (2003) found that the Pecking-Order theory reinforces the effects assumed to originate from other theories such as the trade-off theory, especially for the cash holdings, future investment opportunities and leverage.
2.4 Traditional Determinants of Cash Holdings
7 Large firms tend to hold less cash than small firms in most of the academic findings to date. Opler et al. (1999) in their investigation on cash holdings factors about U.S. publicly traded firms find that smaller sized firms hold more cash than their counterparts. These findings are confirmed by the research of other scholars investigating firms globally (Haushalter et al, 2007; Kim et al, 1998., 2006; Dittmar et al., 2003). More recently the work of Gao et al. (2013) considers the determinants of cash holdings policies in private and public U.S. firms and finds that smaller firms have higher cash holdings. Al-Najjar (2013) deploys a sample of firms in developing markets while comparing the results with firms of U.S and U.K origin. A robust negative relationship between size and cash holdings is found for developed and developing markets. Furthermore, Bates et al. (2009) confirms this relationship for a sample of U.S. firms with a large sample between 1980 and 2006. Smaller firms seem to be more constrained in their access to external financing and hold more cash for precautionary purposes (Han & Qiu, 2007). On the other hand, Song and Lee (2012) investigate how the corporate liquidity management in the long term is affected by a financial crisis in eight East Asian markets. In this special context, the relationship between size and levels of cash holdings is positive because firms reduce investments and increase their cash holdings. This could imply that larger firms can accumulate more money by reducing investments. Another exception to the established relationship is the research of Itzkowitz (2013) who examines how buyer-supplier interaction influences the management of corporate cash holdings. Once again the risk of distress included in relationship with higher sales concentrations could account for the positive relationship between size and cash holdings.
There is a scientific consensus for the relationship between leverage and levels of cash holdings. Throughout existing literature, leverage is argued to be a major determinant of corporate cash holdings. The relationship between leverage and cash holdings can also be based on the trade-off theory, which implies that firms characterized by a high degree of financial leverage hold more cash because of a higher probability of financial distress. Opler et. al (1999) argue that firms with more debt, i.e. higher leverage, have less cash available as a direct result of the obligation to repay outstanding debt. Based on this assumption, the relationship between leverage and cash holdings is negative. This finding is further supported by for example Al-Najjar (2013), Foley et al. (2007) and Bates et al. (2009). Ferreira and Vilela (2004) confirm the negative relationship between debt and cash holdings. Firms with a high level of debt are less able to stockpile cash. This is a result of the fact that these firms are better monitored when compared to firms with a relatively low level of debt.
8 robustness of the relationship between leverage and cash holdings to firm size. The sample includes small and medium-sized firms in the United Kingdom and found a negative relationship between liquidity and levels of cash holdings.
A firm that regularly pays dividends can trade-off the cost of holding cash by decreasing dividend payments in the future. This was confirmed by Al-Najjar and Belghitar (2011). They argue that dividend paying firms have access to cheaper forms of financial resources when needed by reducing their dividend payments. Additionally, Ozkan and Ozkan (2004) state that for firms with limited internal financing resources, costly forms of funding can be avoided by reducing the amount of dividend expenditures. Thus, dividend paying firms can hold less cash as they have better abilities to raise funds when needed by reducing future dividends. Opler et al. (1999) also defines firms that must cut back on dividends as being short on cash and thus less liquid. Bates et al. (2009) investigate the development of levels Cash holdings of U.S. firms over time and find that the levels of cash holdings increase gradually while the level of debt decreases especially for firms that pay no dividends. This argument is grounded in the disappearing dividends phenomenon as documented by Fama and French (2001). Firms which do not pay dividends have a positive time trend for increasing levels of cash holdings and decreasing levels of debt. In other words, firms that are more established and normally pay dividends exhibit stable levels of cash holdings. Foley et al. (2007) find coefficients like the former findings. Firms that pay no dividends hold more cash. The interpretation of these results is also in line with the former line of argumentation. However, Song and Lee (2012) find inconsistent results with previous literature. In their sample of firms from East-Asia the coefficient of the dividends to asset ratio is positive. Therefore, cash dividends do not seem to consume cash in their context. Inconsistencies are also found by Kuan et al. (2011) during research on control rights and cash holdings.
9 Table 1 Academic Findings: Determinants of Cash Holdings
Dependend Variable: Cash Holdings
Scientific Source / Variable Prof. Size Lev. Divi. Liq. R&D
Al-Najjar (2015) -
Al-Najjar (2013) - - - - +
Gao et al. (2013) + - - +
Itzkowitz (2013) + + +
Song and Lee (2012) + - +
Al-Najjar and Belghelar (2011) + -
Kuan et al. (2011) - + +
Bates et al. (2009) + - - - +
Harford et al. (2008) + - +
Foley et al. (2007) - - +
Han and Qiu (2007) -
Haushalter et al. (2007) - - +
Ferreira and Vilela (2004) + -
Ozkan and Ozkan (2004) - - - -
Dittmar et al. (2003) + -
Opler et al. (1999) - - - - +
Kim et al. (1998) -
Note: Prof. refers to Profitability; Lev to Leverage; Divi to Dividends; Liq to Liquidity; R&D to Research and Development Costs. The definition of variable which measures the proxy can vary per study.
Table 1 summarizes the direction of the relationships for the determinants of cash holdings used in this section. The first column contains the research paper that used cash as dependent variable. The following six columns contain the independent variables (determinants) and the direction of the coefficient for the respective study. The relationship between cash holdings and size, leverage, dividends and liquidity is negative for the greater part. Coefficients for research and development (R&D) and profitability are positive.
2.5 Corporate Tax Planning: Legal or illegal?
10 techniques. Tax evasion is illegal and tax returns are not disclosed to investors. Thus, it can only be labelled ‘tax evasion’ until after the firm is penalized by authorities (Armstrong, Blouin, & Larcker, 2012). On the other extreme, tax planning is the natural attempt of a firm to minimize its tax bills as permitted by the laws. Jacob (2010) argues that we should be using the terminology legitimate or non-artificial tax avoidance and illegitimate and non-artificial tax avoidance. In the end, it does not matter whether we call it planning, avoidance or evasion. Most importantly is to understand that legality is the presumption and illegality has to be proven. However, academic literature seems to label less aggressive tax management practice as tax planning and talks about avoidance or evasion when discussing aggressive strategies. This study will follow the same logic for its terminology.
2.6 Explaining Tax Planning with ETRs
11 problem with ETRs which are based on annual data. They describe year-to-year variation and negative pre-tax income as problems. Measures streching over several years are used consequently. The total income tax expense is composed of the current tax expense plus (deferred) taxes that will be cleared in the future. Thus, the GAAP ETR includes both current and deferred tax expenses. Therefore, the total income tax expense measured annually might not be able to account for a great deal of activities that accelerate or defer income for tax planning purposes. Only using the current tax expense on annual basis can provoke difficulties with expense recognition under US general accepted accounting principles. Dyreng et al. (2008) measures tax rates over a long time period of 10 years in order to assemble effective tax rates that track the firms tax rates more precisely over the long term. I adopt this approach to construct less biased effective tax rates.
2.7 Tax Planning and Cash Holdings
Explanations for the increase in firm’s cash holdings are plentiful. Many studies focus on the trade-off perspective and the agency perspective. The tax based explanation has been discussed in academic research (Bigelli & Sánchez Vidal, 2012; Foley et al., 2007; Pinkowitz et al, 2012) but is yet to be researched more deeply. Bigelli and Sánchez-Vidal (2012) performed one of the few investigations of the relationship between cash holdings and effective tax rates on a sample of Italian private firms. They find that firms with lower effective tax rates, smaller size and higher risk are significantly related to Table 2 Academic Findings Effective Tax Rates
Author Title Year ETR Proxy Findings and Concepts
Stickney and McGee
Effective Corporate Tax Rates: The effect of size, capital intensity, leverage, and other
factors. 1982 GAAP ETR, Foreign ETR, Current ETR
(1) Firms with highest Capital Intensity and Leverage have lowest ETRs (2) Foreign Involvement and Size play less important role for ETRs
Rego
Tax-avoidance activities of US multinational corporations. Contemporary Accounting
Research 2003 GAAP ETR
(1) ETRs capture the use of foreign operation to avoid taxes (e.g. income shifting) and (2) Tax motivated transactions (e.g. tax credits and deferral of income recognition, foreign sales)
Dyreng et al.
Long Run Corporate Tax
Avoidance 2008
10-year Cash ETR
(1) 10 year ETRs are a more precise measure of tax avoidance (2) Some evidence of industry effects on ETRs (3) Low Annual ETRs are persistent over the years
Lanis and Richardson
Corporate Social
Responsibility and Tax Aggressiveness. An empirical analysis 2012 Current ETR, Current ETR/ OCF
(1) Corporations that avoid corporate taxes by reducing their taxable income while maintaining their financial accounting income have lower ETRs, making an appropriate measure of tax aggressiveness.
Donohoe
The economics of financial derivatives on corporate tax
avoidance 2015
Current ETR, Cash ETR
(1) Lower ETRs imply higher levels of tax avoidance
Powers, Robinson and Stromberg
How do CEO incentives affect corporate tax planning and financial reporting of income
taxes.? 2016
GAAP ETR, Cash ETR
(1) Firms that engage in tax planning have lower ETR
12 levels of cash holdings. Foley et al. (2007) investigate the relationship between cash holdings and tax costs for a large sample of multinational corporations from the United States in the period 1982-2004. Their investigation shows that the tax costs which are bound to the repatriation process of foreign earnings cause a 7.9% increase in cash holdings per one standard deviation. Firms that face higher tax cost for repatriating their earnings do hold more cash in this sample. On the other hand, Pinkowitz et al. (2012) investigate a sample of US firms in the period of 1990–2010 and find a strong increase of cash holdings for US firms relative to foreign firms especially after the millennium. Thus, US firms hold more cash in the present relative to similar foreign firms. Firm with more than 25% foreign sales categorized as multinationals experience growth of 433% in cash holdings while their assets only increase 205%. Firms do not seem to increase their assets holdings. This provides reasonable doubt that the increase in cash holdings might not be explained by improved firm performance alone. Pinkowitz et al. (2012) suggest that the reason for this increase needs further explanation. However, they noticed that the Homeland Act of 2004 which eliminated the cost of repatriation tax temporarily for the very same year, firms did not decrease cash holdings significantly. Nevertheless, Faulkender et al. (2016) most recent study acknowledges the dramatic increase in precautionary cash holdings within US firms. While precautionary motives explain the variation in cash holding for domestic firms, they carry limited explanatory power when it comes to foreign cash holdings. Because of the costs imposed by repatriation tax firms cannot use the foreign and domestic cash holdings as perfect substitutes. Their findings show that firms with higher average tax rates hold less total cash when foreign and domestic cash holdings are aggregated in one position. However, looking at the positions separately reveals that domestic cash holdings cannot be explained by ETRs for multinationals, but there is a strong significant negative relationship between ETRs and foreign cash holdings. Firms with lower ETRs hold higher levels of foreign cash. These findings are consistent with the research of Foley et al. (2007) which provides reasons to believe that the cost of US repatriation tax incentivizes firms to hold their cash abroad.
2.8 The Tax Hypothesis of Trapped Cash
13 and to not repatriate cash in order to pay-out, invest at home or in case they do not have attractive investment opportunities abroad, to stockpile the cash (Foley et al., 2007). Killian (2006) provides a consistent argument about the impact of tax competition on the international stakeholders for U.S. tax planning in Ireland. The research describes US tax planners in Ireland as having a higher rate of retained earnings due to a lower overall tax liability as well as experiencing a delay during the repatriation process of profits which leads to a distorted pay-out policy. Stewart (2008) supports this argument. In his research it is described that under the US tax system zero foreign tax rates result in zero US tax credits. Therefore, when dividends are repatriated back to the US which have been subject to low tax rates, US corporate tax must be paid up until the 35% mark has been reached. Moreover, Duchin et al. (2015) explains when income tax rates for corporations are lower than income tax rates of investors, there is a benefit from firms that defer payments of operating cash flow out to investors. Whether the low foreign income tax is achieved via low statutory income tax rates or tax planning schemes such as the double Irish agreement does not matter for the tax burden when repatriating cash holdings. One tax planning scheme that has received some attention from the media recently is the so called Double Irish Arrangement (DIA) in which multinational corporation from the United States relocate headquarters to Ireland and use the legal environments to channel profits through the Netherlands to a secrecy jurisdiction offshore. Tax planning schemes are not illegal and within the boundaries of the text of the national laws, yet they still have received many high level criticisms in the past (Needham, 2013; Barford & Holt, 2013). It is not important for the tax hypothesis of trapped cash how corporate income tax is minimized, whether through shifting income to low tax jurisdiction or using tax planning schemes involving several tax jurisdictions. Finally, what matters is not how the low tax rate was achieved, but the differential between foreign income taxes paid and the US corporate income tax rate in order to balance the pros and cons of repatriating foreign earnings.
3. Hypothesis formation
This section describes the formulation of the hypotheses for the determinants of cash holdings for US firms that are considered above average tax planners with lower industry effective tax rates as compared to firms considered below average tax planner with higher industry effective tax rates. The determinants of cash holdings have been researched extensively and section 2.3 outlined the findings and directions of the coefficients for the most important studies with cash holdings as a dependent variable. In addition to size, leverage, liquidity, dividends, profitability and research & development, internationalisation is added to the list and hypothesized.
3.1 Leverage
14 determinants of cash holdings in developing and developed markets confirms the negative relationship. Bates et al. (2009) investigates a dataset of U.S. industrial firms throughout the period of 1980 to 2004 and finds that the average cash holdings increase by 129% while this upward trend is causing a sharp secular decrease of net debt. Ferreira and Vileila (2004) investigate a sample of firms within the European Monetary Union which are in line with the former findings. The relationship also holds for a large sample of East Asian firms in which financially unconstrained firms with low leverage tend to hold higher levels of cash (Song & Lee, 2012). In the presence of repatriation cost, due to tax planning, firms show distinctive behaviour. Financially constrained firms with high domestic debt are less likely to defer repatriation taxes by holding cash abroad because of the domestic payment obligation. Firms that are less domestically financially constrained and more technology intense are more sensitive to repatriation tax. However, firms with higher leverage accumulate less cash (Foley et al. 2007). Alternative repatriation strategies might cause disturbance in the consistency of this relationship. Altshuler and Grubert (2000) explain how multinationals strategically borrow from a low-tax subsidiary to bypass repatriation tax indefinitely. Overesch and Wamser (2014) provide further evidence for bilateral intra-firm borrowing and other debt related tax planning mechanisms. Therefore, I expect the relationship between leverage and cash holding to remain negative for below average tax planners (NTPs) but to lose its explanatory power for the sample of above-average tax planners (TPs).
H1a: There is a negative relationship between leverage and cash holdings for NTPs H1b: There is no significant relationship between leverage and cash holdings for TPs.
3.2 Dividend Payments
15 because of provision F. Dividends are subject to passive income tax treatment abroad and do not minimize taxes.
H2a: There is a negative relationship between dividend payment and cash holdings for NTPs.
H2b: There is a stronger negative relationship between dividend payments and cash holdings for TPS than NTPs.
3.3 Profitability
The pecking order theory predicts a positive effect of profitability on cash holdings (Ferreira & Vilela, 2004, Ditttmar et al., 2003). Firms tend to rely on retained earnings before debt and equity in order to finance projects and obtain cash. Therefore, more profitable firms have higher cash holdings (Al-Najjar and Belghelar, 2011). Profitability is directly related to the amount of taxes to be paid. Rego, (2003) finds that firms with greater pre-tax income have lower effective tax rates. The goal of minimizing taxes to be paid is to reduce the taxable income while remaining successful in the eyes of investors. Following the pecking order theory that prioritizes retained earnings as the main source of obtaining cash and the secondary findings I hypothesize a positive relationship between profitability and cash holdings in the NTP sample. However, I expect above average tax planners (TPs) to report lower profitability but hold higher levels of cash as both lower profitability and higher cash holdings are an indicator of tax planning efforts in this sample.
H3a: There is a positive relationship between profitability and cash holdings for NTPs. H3b: There is a negative relationship between profitability and cash holdings for TPs.
3.4 Liquidity
Liquid assets are less costly to convert to cash than other assets. Firms holding more liquid assets are likely to hold less cash (Ozkan and Ozkan, 2004; Al-Najjar, 2013). In accordance with the trade-off theory, liquid assets are substitutes for cash, which is why firms with more liquid assets will hold less cash. More recently, Al-Najjar (2015) indicates a robustness of the relationship between liquidity and cash holdings to firm size. Based on the empirical findings I predict the relationship between liquidity and cash holdings to be negative in the NTP sample. The discussion about liquidity and the impact of repatriation tax is focused on the investor perspective. Stakeholders external to the firm might have difficulties with assessing true liquidity when cash is trapped abroad and might not provide liquidity for domestic purposes (Chen, 2015). However, this discussion is obsessed with the reporting standards rather than levels of liquidity reported actually. Therefore, the relationship between liquidity and cash holdings remains negative in the TP sample.
H4a: There is a negative relationship between liquidity and cash holdings for NTPs H4b: There is a negative relationship between liquidity and cash holdings for TPs.
3.5 Firm Size
Al-16 Najjar, 2013) The smaller the firms, the bigger is the challenge to obtain external capital and therefore have a greater incentive to accumulate more cash for precautionary and speculative motives. Smaller firms are more financially constrained in their access to external financing. There is a negative relationship between firm size and cash holdings in the NTPs sample. In the context of tax planning, this relationship is expected to change. The possibility to minimize tax cost increase linearly with the size of a firm and cash holdings are higher for TPs as compared to NTPs. Economies of scale to tax planning exist (Rego, 2003). Larger firms have more incentives and resources to engage in tax planning. Therefore, the relationship between firm’s size and cash holdings is positive in the TP sample.
H5a: There is a negative relationship between firm size and cash holdings for NTPs. H5b: There is a positive relationship between firm size and cash holdings for TPs.
3.6 R&D
Research and development (R&D) is consistently found to have a positive relationship with cash holdings. The common proxy for this determinant is the ratio of research and development expenditures to total sales (Kuan et al., 2012; Harford et al. 2008). Bates et al. (2009) finds a positive correlation of R&D spending to cash holdings. At the first glimpse, it appears that R&D spending decreases cash holdings but in their research, it is utilized as a proxy for investment opportunities (growth) in line with the precautionary motive, because financial distress could be costlier for firms with better investment opportunities. R&D investment is often uncertain and hard to finance for firms that face financial difficulties so that firms increase their cash holdings. Foley et al. (2007) looks at R&D spending from a tax based perspective. Firms shift profits in between high and low tax jurisdiction especially when intangible property is produced via research and development efforts, because the value of intangible property is harder to assess. As a result of the tax minimization, the firm retains more earnings and increases cash holdings. Opler et al. (1999) also expects firms with high R&D expenses to face a higher cost of financial distress because of higher information asymmetries and thus hold more liquid assets. Thus, the relationship is expected to be positive for TPs and NTPs. However, due to the relationship between R&D and international tax planning the levels and coefficients of R&D maybe expected to be stronger for TPs.
H6a: There is a positive relationship between R&D and cash holdings for NTPs.
H6b: There is a stronger positive relationship between R&D and cash holdings for TPs than for NTPs.
3.7 Internationalisation
17 et al., 2007) Hence, there should be a strong positive relationship between the degree of internationalisation of a firm in the TP sample and its levels of cash holdings. On the other hand, the degree of internationalisation in the NTP sample does not necessarily correlate with the amount of cash holdings under the same assumptions. Empirical evidence on the relationship between internationalisation and cash holdings is rare. However, Bates et al (2009) examining the time trend of cash holdings find a larger increase of cash holdings for firms with no or little foreign activities, thus indicating a negative relationship. Contrary to the former findings, Pinkowitz et al. (2012) find an abnormal increase of cash holdings for U.S. multinationals over time but not for domestic firms. Therefore, the relationship between cash holdings and internationalisation for the NTP sample remains ambiguous.
H7a: There is no relationship between internationalisation and cash holdings for NTPs. H7b: There is a positive relationship between internationalisation and cash holdings for TPs.
4. Data Collection and Methodology
4.1 Data Collection
In order to construct a sample of above average and below average industry tax planners from the U.S, I created a dataset which is based on a list provided by the non-governmental agency Citizen for Tax Justice (CTJ). Their original list is drawn from the Fortune500 list 2015 and contains 387 US corporations with references to cash held offshore and the location of tax haven subsidiaries. This data on foreign subsidiaries can be found in the Exhibit 21 of 2014’s 10-k filings published in the EDGAR data base of the Securities and Exchange Commission (SEC). In order to classify tax havens and financial privacy jurisdictions the data from the 10-K filings was compared to a ‘John Doe’ summons list from the IRS. The list contains 387 firms that report permanently re-invested earnings (earnings offshore) and tax haven subsidiaries
I started with the aggregated list of CTJ and extracted firm level accounting data from Thomson Reuter DataStream using the corresponding ticker symbol for each firm and the data-stream item code for each book data item (see appendix). Then I reduced the sample by the following exclusions:
1. Firms that did not report foreign subsidiaries in the 10-K filings despite reporting permanently re-invested earnings (earnings offshore). These firms were judged to be inconsistent in their reporting and not to be trusted in other disclosures. (28 Firms).
2. Firms with missing data in the period 2004-2014 specially to calculate the long-term effective tax rates and accounting data necessary to construct the variables (52 Firms).
3. Financial firms with a Standard Industry Code (SIC) starting with 6 because government policy is likely to affect their effective tax rates differently (Lanis &Richardson, 2012) (25 Firms). 4. Firms with a negative sum of the 10 years (2004-2014) pre-tax accounting income as this results
18 This resulted in a sample of 266 non-financial firms with headquarters registered in the United States, but reported earnings offshore and subsidiaries in tax havens. These firms have complete data to calculate current and GAAP effective tax rates over the period 2004-2014 with non-negative pre-tax accounting income.
Subsequently, the 266 firms were classified in below average tax planners (NTPs) and above average tax planners (TPs) along their effective tax rates. I categorized firms in industry groups by the first digit of the SIC code as 1-9 because different industries provide completely different opportunities for tax planning and thus have different effective tax rates1. Then, the upper seventy percent of an industry
group with the highest GAAP effective tax rates were classified as NTPs and the lowest thirty percent as TPs. This distribution is meant to resemble the standard tax rates in the USA which range from 15% at the lowest and 35% as standard rate. This process was repeated for current effective rates and eventually resulted in four samples each consisting of 82 TPs and 184 NTPs across the 8 industry groups.
4.2 Methodology
The data selection method and separation of the datasets creates a binary classification of tax aggressiveness. Tax planning is never obvious and not definite, but the use of effective tax rates as proxy for tax planning result in a robust 16% tax rate for below average tax planners (NTPs) and 36% for above average tax planners (TPS) throughout the samples. This corresponds perfectly with the institutional range of tax obligation in the USA. Given the disaggregation of TPs and NTPs, the resulting cross-sectional samples are analysed using robust ordinary least square (OLS) regression analysis in EViews 9 to test both samples on the importance of the determinants of cash holdings. The outcome of this analysis is compared to the findings of former research on the determinants of cash holdings (as summarized in table 1) which did not account for tax planning. Two models are constructed to investigate the tax-based motivation of cash holdings as compared to traditional motivations:
(1) The first model distinguishes between TPs and NTPs on grounds of the 10 Year GAAP ETR:
CASHi = β0 + β1LEVi + β2DPOi + β3ROAi + β4LIQi +β5SIZEi + β6INTi + β7R&Di + β8G_ETRi + β9SUBi + β10D_IRi
+ β11D_Manui + β12D_TECHi +εi
The abbreviations of the variables are explained in section 4.2.1. Betas one to seven are proxies for the seven hypothesized determinants of cash holdings, where beta eight to twelve are controls and dummies. Notably, model one and model two differences are the proxies for effective tax rates. Model one used the GAAP ETR (G_ETR) two classify tax planning and model two used Current ETR (C_ETR).
19 (2) The second model test uses the 10 Year Current ETR to classify TPS and NTPS with the same variables:
CASHi = β0 + β1LEVi + β2DPOi + β3ROAi + β4LIQi +β5SIZEi + β6INTi + β7R&Di + β8C_ETRi + β9SUBi + β10D_IRi
+ β11D_Manui + β12D_TECHi +εi
In both models the traditional determinants of corporate cash holdings are tested on significant correlation with the dependent variable. Effective tax rates, the number of subsidiaries in tax havens and a series of dummies control for tax specific effects. Also, both models use 10-year long term accumulated effective tax rates to eliminate earnings management techniques as specified by Dyreng et al. (2008). Section 4.2.1 and 4.2.2 explain the definition of the variables and their academic proxies.
4.2.1 Dependent and Independent Variables
The statistical analysis is performed on two independent variables which both measure corporate cash holdings. Firstly, CASH (1) refers to corporate cash holdings of firms as measured by Al-Najjar (2013). It is measured as the ratio of cash and equivalents (DataStream item WC02001) to total assets (WC02999). Secondly, CASH (2) refers to corporate cash holdings of firms as measured by Foley et al. (2007) and Opler et al. (1999). It is measured as the natural logarithm of cash and equivalents (WC02001) divided by total assets (WC02999) net of cash and equivalents (WC02001).
C𝐚𝐬𝐡 (𝟏) =𝐂𝐚𝐬𝐡 & 𝐄𝐪𝐮𝐢𝐯𝐚𝐥𝐞𝐧𝐭𝐬
𝐓𝐨𝐭𝐚𝐥 𝐀𝐬𝐬𝐞𝐭𝐬 𝐂𝐚𝐬𝐡 (𝟐) = 𝐋𝐍 (
𝐂𝐚𝐬𝐡 & 𝐄𝐪𝐮𝐢𝐯𝐚𝐥𝐞𝐧𝐭𝐬
𝐓𝐨𝐭𝐚𝐥 𝐀𝐬𝐬𝐞𝐭𝐬 − 𝐂𝐚𝐬𝐡 & 𝐄𝐪𝐮𝐢𝐯𝐚𝐥𝐞𝐧𝐭𝐬)
The first independent variable LEV is the abbreviation for leverage and measured by the ratio of total debt (WC03255) to total assets (WC02999). This ratio represents the relationship between a firm’s debt and assets. DPO is the abbreviation for the dividend pay-out ratio measured by dividend per share (W05101) divided by earnings per share (W05201). ROA is a measure for profitability of the firm seen as return assets. It is measured by Net Income GAAP (WC06895) divided through total assets (WC02999). LIQ is the liquidity ratio and is obtained by measuring cash and equivalents (WC02001) to current liabilities (WC03101). SIZE represents firm size and is measured as the natural logarithm of total assets (WC02999). INT represents the degree of foreign sales (WC07101) relative to total sales (WC01001) and measures the internationalisation of the individual firms in terms of sales revenue. R&D accounts for the research and development expenses incurred measured as the ratio of global R&D expenses (WC01201) to total sales (WC01001). Consistent with Opler et al. (1999) I assume that firms which do not report research and development cost are firms with no R&D expenses.
20 deployed by Opler et al. (1999). Internationalisation in terms of foreign sales was introduced by Foley et al (2007) as important determinant to the tax based motive for cash holdings.
4.2.3 Control Variables
Effective tax rates (GAAP and Current) have been of importance for the classification of the individual firms into above industry average tax planners (TPs) and below industry average tax planners (NTPs). However, it is not hypothesized and deployed as independent variables because the explanatory power is to be found in the comparison of the regression coefficients of both samples. Effective tax rates vary per industry and thus not necessarily correlate with cash holdings in an aggregated sample. In particular, scholars have found a negative significant relationship between cash holdings and ETRs (Bigelli & Sánchez-Vidal, 2012). This correlation is not necessarily expected in my samples because of the industry categories created in the data selection. Dyreng et al. (2008) gives reasons to measure the tax rate not annually, but in order to improve the explanatory power and eliminate earnings management, divide the sum of 10-year current income tax paid (WC18186 + WC18187) or total global income tax (WC01451) by the sum of 1year pre-tax income (WC01401). The variables were truncated to the 0-1 range to be consistent with previous research (Gupta and Newberry, 0-1997; Chen et al., 200-10). The variable G_ETR represents the GAAP effective tax rates and C_ETR the Current effective tax rates. The following equation should clarify the variables:
𝑮𝑨𝑨𝑷 𝑬𝑻𝑹 𝒊 = ∑𝟏𝟎𝒌=𝟏𝑻𝒐𝒕𝒂𝒍 𝑰𝒏𝒄𝒐𝒎𝒆 𝑻𝒂𝒙 𝑷𝒂𝒊𝒅 𝒊𝒕
∑𝟏𝟎𝒌=𝟏𝑷𝒓𝒆𝒕𝒂𝒙 𝑰𝒏𝒄𝒐𝒎𝒆 𝒊𝒕 𝑪𝒖𝒓𝒓𝒆𝒏𝒕 𝑬𝑻𝑹 𝒊 =
∑𝟏𝟎 𝑪𝒖𝒓𝒓𝒆𝒏𝒕 𝑰𝒏𝒄𝒐𝒎𝒆 𝑻𝒂𝒙 𝑷𝒂𝒊𝒅 𝒊𝒕
𝒌=𝟏
∑𝟏𝟎𝒌=𝟏 𝑷𝒓𝒆𝒕𝒂𝒙 𝑰𝒏𝒄𝒐𝒎𝒆 𝒊𝒕
21
5. Empirical Results
5.1 Descriptive Statistics
Table 3 contains the descriptive statistics for TPs from the GAAP effective tax rate sample. Table 4 shows the NTPs sample of the same proxy. The median value of corporate cash holdings for TPs is 11%. The median for NTPs as reported in table 4 is 8%. The descriptive statistics reveal that TPs hold higher levels of cash than NTPs.
Table 3 Descriptive Statistics TPS GAAP ETR
Variables N Mean Median Max Min SD
Dependent Variable Cash 82 0.14 0.11 0.56 0 0.12 Independent Variables Profitability 82 0.06 0.05 0.35 -0.11 0.06 Leverage 82 0.33 0.31 0.81 0 0.17 Firm Size 82 16.71 16.59 20.29 14.39 11.00 Dividends 82 0.31 0.26 2.35 0 0.37 Liquidity 82 1.15 1.03 7.71 0.15 0.87 Internationalisation 82 0.45 0.44 1 0 0.29 R&D 82 0.04 0.01 0.32 0 0.07 Control Variables GAAP ETR 82 0.16 0.19 0.35 0 0.11 Subsidiaries 82 23.7 13.5 155 1 3.02 Dummy Tech 82 0.02 0 1 0 0.16 Dummy Manu 82 0.54 1 1 0 0.50 Dummy Ireland 82 0.46 0 1 0 0.50
22 GAAP effective tax rate for NTPs is 36%. This fits the institutional expectation of tax to be paid from a U.S. corporation whereas the median value in the TP sample is only 19%. The median number of reported foreign subsidiaries in tax havens is slightly higher for TPS (13.5) than for NTPs (12). Notably, the amount of subsidiaries in tax haven jurisdiction doesn’t necessarily predict the degree of tax aggressiveness and tax planning.
Table 4 Descriptive Statistics NTPS GAAP ETR
Variables N Mean Median Max Min SD
Dependent Variable Cash 184 0.11 0.08 0.51 0 0.10 Independent Variables Profitability 184 0.07 0.06 0.24 -0.19 0.06 Leverage 184 0.29 0.26 0.84 0 0.16 Firm Size 184 16.59 16.42 19.67 14.45 10.30 Dividends 184 0.33 0.28 2.31 0 0.37 Liquidity 184 1.21 1.11 4.55 0.24 0.60 Internationalisation 184 0.37 0.34 2 0 0.29 R&D 184 0.02 0.00 0.21 0 0.04 Control Variables GAAP ETR 184 0.38 0.36 1 0.21 0.14 Subsidiaries 184 22 12 258 1 3.20 Dummy Tech 184 0.03 0 1 0 0.18 Dummy Manu 184 0.53 1 1 0 0.50 Dummy Ireland 184 0.39 1 0 0.49
23
Table 5 Descriptive Statistics TPS Current ETR
Variables N Mean Median Max Min SD
Dependent Variable Cash 82 0.11 0.09 0.39 0 0.10 Independent Variables Profitability 82 0.06 0.06 0.35 -0.11 0.06 Leverage 82 0.33 0.31 0.81 0 0.16 Firm Size 82 16.76 16.70 20.29 15.01 1.07 Dividends 82 0.31 0.25 2.35 0 0.37 Liquidity 82 1.10 1.07 2.58 0.25 0.46 Internationalisation 82 0.40 0.34 1 0 0.28 R&D 82 0.03 0 0.24 0 0.05 Control Variables Current ETR 82 0.15 0.18 0.32 0 0.10 Subsidiaries 82 22 15 132 1 25 Dummy Tech 82 0.02 0 1 0 0.16 Dummy Manu 82 0.54 1 1 0 0.50 Dummy Ireland 82 0.50 0.50 1 0 0.50
The compared values for TPs and NTPs in the second model are consistent with the first model except the mean value of the dependent variable. The median amount of cash holdings in the TP sample is 9% and so it is in the NTP sample. Moreover, the independent variable internationalisation shows the opposite value in the Current ETR model. Below average tax planners have a median value of 39% of foreign sales whereas the value for above average tax planners is 34%. Nevertheless, if the regression analyses are consistently supporting the predicted hypothesis for internationalisation throughout both models the inconsistency in the descriptive statistics could be interpreted as robustness check.
Table 6 Descriptive NTPs Current ETR
Variables N Mean Median Max Min SD
24 Table 7 in the appendix contains the correlation matrix for dependent and independent variables of all samples for the GAAP and Current effective tax rate methods. This matrix is used to investigate the dependence between multiple variables simultaneously. A higher Pearson correlation than 0.6 causes problems in the model estimation. However, table 5 shows no critical correlation between independent variables. The correlation between cash (1) and cash (2) can be ignored since they are not deployed in the same models.
5.2 Regression Results
Table 8 presents the results for both models of OLS regression. In this regression the dependent variable is cash holdings as measured by Al-Najjar (2013). The independent variables are the variables that have been shown to determine the amount of corporate cash holdings in former studies as outlined in the first table. Both models confirm that traditional determinants of cash holdings do not consistently correlate with cash holdings in the TP sample. Leverage and liquidity do not show significance in either of the two models for the TP sample. Also, the dividend pay-out ratio has no significance in neither of the models. Research and development spending is highly significant in both models and all samples without any sign chance. There is a consistent positive relationship between R&D and cash holdings for TPs and NTPs. However, the economic significance is much stronger for the samples of above average tax planners with coefficients almost double the size. This implies that spending on research and development leads to much higher cash holdings when combined with tax planning.
Table 8 OLS Regression Cash (1)
Depend Variable: Cash holdings (1) Al-Najjar 2013
Model 1: GAAP ETR Model 2: Current ETR
TPs NTPs TPs NTPs LEV -0.055 (0.074) -0.101*** (0.033) 0.008 (0.057) -0.081** (0.037) DPO 0.005 (0.031) -0.004 (0.014) 0.011 (0.025) -0.007 (0.016) ROA 0.272 (0.178) 0.475*** (0.108) 0.422*** (0.159) 0.411*** (0.114) LIQ -0.003 (0.013) -0.021** (0.01) -0.016 (0.020) -0.011* (0.008) SIZE 0.010 (0.011) -0.011** (0.006) -0.005 (0.009) -0.005 (0.007) INT 0.079* (0.042) 0.030 (0.021) 0.119*** (0.034) 0.011 (0.024) R&D 1.023*** (0.179) 0.516*** (0.157) 0.923 *** (0.140) 0. 655*** (0.184) Control Variables SUB -0.001* (0.000) 0.000 (0.000) -0.001** (0.000) 0.000 (0.000) D_IR 0.022 (0.026) -0.001 (0.013) 0.027 (0.019) 0.006 (0.015) D_TECH -0.127* (0.073) 0.207*** (0.033) -0.073 (0.058) 0.165*** (0.037) D_MANU -0.031876 (0.029) -0.011 (0.012) -0.007 (0.021) -0.012 (0.013) G_ETR -0.192 (0.122) -0.033 (0.045) C_ETR -0.125 (0.102) 0.001 (0.040) Adjusted R² 0.48 0.43 0.42 0.45
25 The regression yields significant coefficients for internationalisation with a positive sign in both models only for TPS. This result adds to the evidence already collected to support the tax based motive for cash holdings. There is a positive relationship between foreign sales and cash holdings in the TP sample. The control variables only yield one result which is statistically significant. The technology dummy for firms that are considered to be part of the technology industry with more mobile assets is highly significant for the NTP sample. The last result implies that firms belonging to this industry sub-group hold higher levels of cash with lower tax planning activity. In both models the membership of the technology industry relates to lower levels of cash holding. Statistically significant is the relationship between number of subsidiaries and cash holdings. Despite the significance, the value of the coefficient is below 0. The Ireland dummy has no significance. Firms in these four samples do not show altered levels of cash holdings when at least one of the subsidiaries is located in Ireland.
Table 9 OLS Regression Cash (2)
Depend Variable: Cash holdings (2) Foley et al. (2007)
Model 1: GAAP ETR Model 2: Current ETR
TPs NTPs TPs NTPs LEV -0.892 (0.803) -1.645*** (0.449) -0.907 (0.809) -1.035** (0.442) DPO 0.420 (0.340) -0.113 (0.196) 0.280 (0.353) -0.119 (0.199) ROA 1.791 (1.923) 5.417*** (1.475) 2.716 (2.254) 5.180*** (1.349) LIQ 0.100 (0.141) -0.181 (0.129) -0.367 (0.295) -0.053 (0.097) SIZE 0.137 (0.119) -0.131* (0.076) -0.025 (0.125) -0.039 (0.077) INT 1.268*** (0.458) 0.528* (1.826) 1.816*** (0.494) 0.293 (0.284) R&D 8.619*** (1.937) 4.201** (2.139) 7.559* (1.663) 4.346*** (2.615) Control Variables SUB -0.007 (0.004) -0.001 (0.003) -0.009 (0.006) -0.001 (0.003) D_IR 0.260 (0.276) -0.026 (0.177) 0.316 (0.281) 0.043 (0.440) D_TECH -1.475* (0.791) 1.455*** (0.443) -0.731 (0.833) 1.106** (0.440) D_MANU -0.484 (0.312) 0.101 (0.163) 0.011 (0.302) 0.054 (0.163) G_ETR -3.046** (1.322) -0.593 (0.614) C_ETR -0.775 (1.458) 0.472 (0.483) Adjusted R² 0.37 0.33 0.31 0.32
Standard errors that correct for clustering of errors by firm are presented in parentheses. *, ** and *** indicate statistical significance at the 10%, 5% and 1% level, respectively.
26 Moreover, the values of the coefficient remain almost double the size in the TP sample. Thus, spending on research and development consistently leads to higher cash holdings in the TP sample. The relationship between internationalisation and cash holdings is also robust in this regression. Despite the inconsistency in the descriptive statistics of the Current ETR model, the coefficient remains significant throughout all models. This means that even with lower levels of foreign sales the relationship between cash holdings and internationalisation is only significant in the TP sample. The weak significance of internationalisation in the NTP sample of GAAP effective tax rates could provide reasons to suspect a positive relationship between internationalisation and cash holdings in general. However, the value of the coefficient of internationalisation in the TP samples remains significantly higher than in the NTP samples. In this regression the control variables yield two significant results. Firstly, the finding for the technology dummy in the former model remain significant. Secondly, GAAP effective tax rates have a strong negative relationship with cash holdings.
5.3 Discussion
This section will now discuss the findings from the descriptive statistics and the empirical results from the regression analysis with regards to the original expectations from section 2. Table 11 displays the findings for each of the different models and hypotheses, whereas table 10 summarizes the relevant findings of the descriptive statistics. In Section 2.7 I described the mechanics of the tax hypothesis of trapped cash as a requisite for the tax based motive of cash holdings. Foley et al. (2007) depict that foreign sales in tax jurisdiction with lower corporate income tax than the US remain permanently reinvested abroad because of the costs of repatriation tax to US registered firms. This increases worldwide cash holdings, which affects dividend policy and other balance sheet items (Faulkender et al., 2016; Stewart, 2008). The descriptive statistics of the sample reveal evidence to support the tax based motive for cash holdings. Table 10 shows a comparative overview of the descriptive statistics of the two samples of below and above average tax planners.
Table 10 Descriptive Statistics Summary
Variables TPS NTPs Cash 14% 11% Internationalisation 45% 37% R&D 4% 2% GAAP ETR 16% 38% Dividends 31% 33% Leverage 33% 29%
Note: The table contains the average values of the GAAP ETR model
27 holdings. Spending on research and development (R&D) was described to enable tax planning and income shifting because of increased levels of intangible assets that are involved (Foley et al., 2007). Effective tax rates are slightly higher than the standard institutional rate in the United States (35%) for NTPs and they touch the bottom of the institutional range (15%) for the TP sample. Dividends payments also show slightly lower levels for TPs than for NTPs. Above average tax planners were expected to pay less dividend because of tax disadvantages. Finally, the leverage for TPs is 4% percentage points higher and gives reasons to look closer at cross-financing and internal borrowing to defer repatriation tax indefinitely as described by Overesch and Wamser (2014).
My expectations for the first hypothesis (H1), relationship between leverage and cash holdings, can be confirmed for both samples. There is a significant negative relationship between leverage and corporate cash holdings in the NTP sample. This is highly consistent with the research of other studies in the area of cash holdings and its determinants (Bates et al., 2006; Opler et al., 1999; Al-Najjar, 2013). Furthermore, my expectation for the relationship between leverage and cash holdings under the influence of tax planning was also confirmed. Based on Overesch and Wamser (2014) I expected the traditional negative correlation to be disturbed because firms might deploy strategies of cross-financing and internal borrowing to bypass repatriation tax. Both results are consistent throughout all models as can be observed in table 11.
Table 11 Overview Hypothesis and Results
Model / Hypothesis H1a H1b H2a H2b H3a H3b H4a H4b H5a H5b H6a H6b H7a H7b
GAAP ETR - Cash
(Al-Najjar) *** C x x *** x ** x ** x *** *** C *
Current ETR - Cash
(Al-Najjar) ** C x x *** x * x x x *** *** C ***
GAAP ETR - Cash
(Foley et al.) *** C x x *** x x x * x ** *** x ***
Current ETR - Cash
(Foley et al.) ** C x x *** x x x x x *** *** C ***
Note: *, ** and *** indicate statistical significance at the 10%, 5% and 1% level. C indicates confirmed hypothesis when no relationship was hypothesized. X indicates that he hypothesis is rejected.
The second hypothesis (H2) thematising the dividend pay-out policy of firms did not meet expectations. No statistical evidence was found that confirms the relationship between dividend payments and cash holdings in neither of the samples. Dividends were expected to have a negative relationship to cash holdings when considering tax planning efforts, because repatriation tax was preventing the distribution to home country shareholders (Foley et al., 2007) and subpart F provision of the US tax code specifies that dividends distributed are immediately taxable even if not repatriated.
28 The traditional negative relationship between Liquidity (H4) and cash holdings was confirmed by the statistical analysis of both samples in the Al-Najjar models. It seems to hold that liquid assets remain substitutes for cash in the NTP sample. There is no evidence that this relationship holds in the TP sample.
I hypothesized that firm size (H5) and cash holdings have a negative relationship in the TP sample. The basis for this assumption was the research of Rego (2003) who found economies of scale to tax planning where larger firms have more incentive to deploy resources for tax planning. The analysis does not confirm the latter hypothesis.
The findings for research and development costs of hypothesis 6 were the most consistent findings within the entire analysis. The positive relationship between R&D and cash holdings was confirmed at a 1% significance level throughout all models, but one which shows significance at the 5% level. Hypothesis 6b expects a stronger relationship between R&D and cash holdings for above average tax planners. This argument is based on the finding of Foley et al. (2007) that firms more engaged in research and development utilize their intangible property to manage taxes since the value of the intangibles is harder to assess from external stakeholder’s position. The analysis shows that the coefficient of R&D in the TP sample has almost twice the magnitude than in the NTP sample. Each dollar spent on research and development in the TP sample leads to double the cash holdings. This finding further supports the tax based motive for holding cash.
Finally, internationalisation (H7) was identified as key determinant of the tax based motive (Foley et al. 2007). The tax based motive of cash holdings rests on the declaration of permanently reinvested earnings abroad which in turn depend on foreign sales. Hence, the inflation of cash holdings sparked by tax planning strategies goes hand in hand with the amount of foreign earnings. On the other side, this relationship does not need to hold for firms that engage little or not at all in tax planning. The analysis shows that the relationship for TPs between foreign sales and corporate cash holdings is consistently significant throughout all four models.
All things considered, it is noticeable that the traditional relationships for the determinants of cash holdings as predicted in section 2.3 and summarized in table 1 tend to hold for the NTP sample. This can be seen as for example the relationships between cash holdings and leverage, profitability, liquidity or firm size. Apart from hypothesis 6 (R&D), the traditional relationships as predicted by former research do not seem to remain statistical significant in the TP sample.
