Financial and Institutional Determinants of Cash Holdings in
the Oil and Gas Industry
University of Groningen Faculty of Economics and Business MSc International Financial Management
Supervisor: Dr. Wim Westerman Date: 5/06/2017
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Abstract
The paper analyses the determinants of cash holdings within the oil and gas industry in various geographical markets of the European continent over the period of 2010-2014, using the tradeoff theory and the pecking order theory. The empirical results suggest that cash holdings are negatively affected by net working capital, leverage, collateral and size, while cash flows and capital expenditures have positive influence on cash reserves. Our findings offer evidence that firms in countries with strong governance as measured by the World Governance Index hold more liquidity. Furthermore, the state of financial market development as measured by the Global Financial Centers Index is also positively related to cash holdings with the effect of financial market dominating the effect of governance.
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Table of Contents
1. INTRODUCTION ... 4
2. THEORETICAL FRAMEWORK AND INDUSTRY OVERVIEW ... 7
2.1 OIL AND GAS SECTOR ... 7
2.2 IRRELEVANCE OF CASH HOLDINGS ... 9
2.3 THEORY AND EMPIRICAL HYPOTHESES ... 9
2.3.1 TRADEOFF THEORY ... 9
2.3.2 PECKING ORDER THEORY ... 10
2.3.3 INSTITUTIONS AND MACROECONOMIC EXPOSURE ... 11
2.4 FINANCIAL AND INSTITUTIONAL DETERMINANTS OF CASH HOLDINGS ... 12
2.4.1 COLLATERALIZABLE ASSETS ... 12
2.4.2 CASH FLOW ... 13
2.4.3 FIRM SIZE ... 13
2.4.4 LEVERAGE ... 14
2.4.5 NET WORKING CAPITAL ... 14
2.4.6 CAPITAL EXPENDITURES ... 14
2.4.7 COUNTRY GOVERNANCE ... 15
2.4.8 FINANCIAL MARKET DEVELOPMENT ... 15
2.5 HYPOTHESIS DEVELOPMENT ... 17
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3.1 SAMPLE AND DATA ... 18
3.2 VARIABLES CONSTRUCTION ... 19
3.3 REGRESSION MODEL SPECIFICATION ... 20
4. EMPIRICAL FINDINGS ... 23
4.1 DESCRIPTIVE STATISTICS ... 23
4.2. REGRESSION MODELS ... 25
4.2.1. THE EFFECTS OF FINANCIAL FACTORS ON CASH HOLDINGS ... 25
4.2.2. THE EFFECTS OF FINANCIAL AND INSTITUTIONAL FACTORS ON CASH HOLDINGS ... 25
4.2.3. THE EFFECTS OF FIRM CHARACTERISTICS AND FINANCIAL MARKET DEVELOPMENT ON CASH HOLDINGS ... 26
4.3. REGRESSION RESULTS ... 27
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1. Introduction
During the Global Financial Crisis of 2007–2008 Warren Buffett made an emphatic public declaration from the widely read opinion pages of The New York Times. He warned public that by holding cash it “opted for a terrible long-term asset, one that pays virtually nothing and is certain to depreciate in value” (New York Times, 2008). Interestingly enough, at the end of 2015 non-financial S&P 500 companies held on their books $1.44 trillion in cash (MarketWatch, 2015), and ever since the financial crisis, record high cash holdings of American firms have been attracting significant media attention (Pinkowitz et al., 2013). In Continental Europe energy, car, telecom and utility industries were the greatest liquidity hoarders, holding €490bn (FT, 2015).
In a world of perfect capital markets, a firm does not have the necessity to hold any cash at all, since it is capable to obtain funding for its profitable investment project at negligible transaction costs (Mogdigliani and Miller, 1958). Thus, cash is merely viewed as negative debt, and hence there is no optimal cash holdings level. However, many international studies demonstrate that companies maintain sizeable portions of their assets in cash. Guney et al. (2003) observe firms holding an average cash ratio of 14%, Ferreira and Vilela (2004) find an average cash ratio of 15% and Kalcheva and Lins (2003) observe firms holding on average 16% of their total assets in cash or cash equivalents.
For the oil and gas sector, Antill and Arnott (2000) have spotted the trend of increasing cash holdings couple of decades earlier. They noted that inability of the industry to reinvest all of its free cash at a required profit forced it to develop net cash on balance sheets. Even though a recent dramatic plunge in energy commodities pressured companies in the sector to initiate the down-cycle drill by cutting capital expenditures, selling non-core assets and laying off personnel, world’s top producers still have over half-trillion dollars in their liquid assets (Bloomberg, 2015). Exxon Mobil Corp. amassed $320bn, Chevron had $65 bn in cash and its own shares tucked away, followed by BP ($53bn), Royal Dutch Shell ($32bn), ConocoPhillips ($31.5bn) and Total SA ($30.5bn). The situation is not unique to western majors, as in the same year Russian SurgutNefteGaz, rather than investing in new plants or hiring new staff, reserved about $34bn of cash and Gazprom held at least $22bn at the end of 2014. (Bloomberg, 2015, Moody’s, 2014).
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influence it. In pursuit of a "normal" pattern of financial structure that reflects the kind of industry the firm operates, Chudson (1945) found that within industries inequalities in the level of vertical integration, production process cycle as well as profitability contributed to cash-to-assets variations. U.S. studies of Opler et al. (1999) and Kim et al. (1998), lend credence to the tradeoff theory, suggesting there is an optimal liquidity level, which results from equalizing the marginal benefits of cash holdings to their marginal costs (Von Eije, 2012). Firms increase their cash balances with the business risk, capital expenditures and financial market access constraints, while size, leverage and dividend payments reduce cash holdings. The pecking order theory (Myers and Majluf, 1984) puts forward a contentious conclusion of no target cash levels, viewing liquidity as a cushion between retained earnings and investment necessities. To decrease financing costs, companies fund new projects primarily with retained earnings, then with safe debt and risky debt, and lastly with equity. Having at its disposal ample operational cash flows to finance its investments, a firm repays debt and accumulates cash.
Recent studies on international samples explored the relations between cash holdings and the countries’ institutional differences as well as levels of financial markets’ development. The vast majority of these studies (Love, 2000; Dittmar et al., 2003; Ferreira and Vilela, 2004) confirmed the tradeoff theory and presented evidence that in countries with superior investor protection and high quality of law enforcement companies tend to carry less liquid assets. However, there are some contradicting results concerning the extent of financial market development, as Ferreira and Vilela (2004), Love (2000) find a higher level having a negative impact on cash holdings, while Dittmar et al. (2003) observes a positive impact.
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holdings and whether the trend of money pileup in energy companies can be explained by existing theories.
We reevaluate the relation between cash holdings, country’s institutional settings, and state of financial market development using a sample of 800 both listed and unlisted energy firms from various geographical markets of the European continent, considered over the period 2010-2014. The underlying research question is: What are the determinants, both financial and institutional, that drive oil and gas companies to hold a certain amount of cash on their balances?
Opposed to many of previous studies that support the tradeoff theory, our findings confirm that both tradeoff and pecking order theories are essential in explaining the determinants of corporate cash holdings.
We provide evidence that companies from the oil and gas sector in countries with a stronger institutional framework as well as developed financial markets hold more liquidity compared to firms operating in countries with weaker governance regimes, which contradicts our initial expectations and previous empirical evidence of Dittmar et al. (2003) and Seifert and Gonenc (2016). However, the results are in line with Caprio et al. (2013), who also observe the positive relation between government quality and corporate cash holdings. We also find the level of capital markets development being positively related with cash holdings, which is contrary to Ferreira and Vilela (2004), but consistent with Dittmar et al. (2003), indicating that oil and gas companies choose to hold more cash when they have opportunities to do so.
The paper contributes to the limited research on cash-holdings in the oil and gas sector and adds to the literature by outlining the significance of country-level institutional variations and state of financial market development in explaining corporate cash holdings alongside to the firm-specific variables. The empirical evaluation of the matter is of concern to managers in the energy sector, since they should take into consideration the settings in which their companies are set to operate when making corporate cash policy choices.
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2. Theoretical framework and industry overview
In this part, we give a short description of the oil and gas sector and present the prevailing theories on corporate cash holdings. As there are several, sometimes contradictious, financial theories on the matter, we would contract the scope of literature review to include relevant to our subject underlying assumptions. We begin by featuring some financial theories, then proceed to elaborating on the possible reasons for holding cash, and lastly present some outlines of the recent research.
2.1 Oil and gas sector
The cyclical and mature oil and gas sector is an integral element of the proper functioning global economy. The industry supplies the needed transportation and heating fuels as well as crucial feedstock for construction and chemicals manufacturing. Oil and natural gas fulfil a fundamental role in the current global energy system constituting 52% of primary energy used across the globe (World Economic Forum, 2016). The sector consists out of three major segments—upstream, midstream, and downstream companies.
Upstream companies are in the business of discovering, developing, and producing oil and natural gas. The business model is analogous to raw materials extraction. Upstream companies administer development and production costs, while emphasizing production on volume in order to obtain high profit margins, which are susceptible to commodity market price fluctuations. This price risk can disrupt stability in firm’s cash flows and cause downgrading of its reserves. To get possession of deposits and start development, upstream companies have to commit large preliminarily investments. Capital outlays are intensive, and the largest investments originate several years prior to production start (Tordo et al., 2011). Firms are faced with ascending complexity in geological works, which as a result transmits pressure on production costs, subsequent recovery volumes and leads to sizable project downtime (Hvozdyk and Mercer-Blackman, 2010). Once companies start production activity, the existing reserves begin to deplete and require large amounts of ongoing capital expenditures to maintain.
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that charges duties and fees as volume is moved, stored or processed. Midstream operators are outstanding generators of consistent cash flow, which proved to be resilient even during a very challenging macro backdrop, however, longstanding infrastructure of the midstream demands heavy preliminarily investments (Watson, 2016)
Petroleum refinement, manufacturing, marketing, as well as distribution of gasoline, jet fuel, heating oil and lubricants is done by downstream companies. Afterwards, the processed products are sent to wholesale, retail, or direct industrial customers. The business model is akin to value-added manufacturing that gains low to medium profitability from refining raw materials, which in turn is highly susceptible to marginal changes in product supply and demand. Risks due to instability and uncertainty of raw materials supply, new environmental regulations, investments in infrastructure require high allocation of capital up front (Speight, 2011).
Since 2006, the liabilities borne by the oil and gas sector have surged from roughly $1 trillion to around $2.5 trillion in 2014. Propelled by high prices on energy products and large profit margins, the sector experienced record levels of expansion as energy companies have actively borrowed both from banks and in bond markets. For the period of 2006 to 2014, borrowings of European companies have been mounting by 17% per annum (Domanski et al., 2015).
In 2013, dramatic drop in crude oil and natural gas prices coupled with a great uncertainty challenged financial stability of companies. In December 2015, crude oil prices declined to US$37 per barrel, the lowest level since May 2004, with natural gas prices experiencing resembling downward trend. Nowadays, the sector is amidst a landmark structural shift. Brogan (2015) describes it as a transition from a “resource scarcity” mind-set driving investment decisions to a “plethora of global energy supply”. Because the oil and gas price is a proxy for the value of the underlying assets carrying that debt, recent epic oil rout and subsequent value loss of the energy commodities inflicted fundamental financial strains on the industry. Burdened with high fixed costs and seeing the price of their products erode many companies find it hard to meet their debt services as lenders await millions of dollars in losses on credits extended to the companies and look to scale down their overall exposure to the industry (WSJ, 2015; Reuters, 2016).
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(Bloomberg, 2017). Overall, the oil and gas sector is constantly adjusting to strenuous conditions as uncertain energy policies, geopolitical complexities, and climate change all present severe challenges.
2.2 Irrelevance of cash holdings
In a world of efficient capital markets, there is no incentive to hold any liquidity as, once needed, it can be drawn from markets without hindrance and at a reasonable price. (Opler et. al 1999, Garcia-Teruel and Martinez-Solano, 2008). Consequently, in the absence of a liquidity premium cash holdings have no opportunity cost and do not maximize shareholder wealth. According to the classic Modigliani-Miller theorem, the market value of the company has no dependence on its financing structure. In a world of perfect and frictionless capital markets, firms are always able to secure funding for positive net present value projects and cash reserves are irrelevant. In practice, firms operate in imperfect markets and as a result, there are valid reasons for why a company may opt to carry liquidity on its balance sheet and not consider external financing as a perfect substitute for an internal one. The literature on corporate cash holdings defines several primary motives for holding liquidity, which would be discussed further in detail.
2.3 Theory and empirical hypotheses 2.3.1 Tradeoff theory
According to the tradeoff theory companies establish their optimal level of liquidity by weighting the marginal costs and benefits of holding cash (Ferreira and Vilela, 2004). Primary cost associated with cash holdings is frequently called as cost-of-carry and results from inferior return relative to other investments of the same risk. The benefits of having ample liquidity balances arise from two motives: transaction and precautionary (Dittmar et al., 2003).
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cash balances are dependent on the transaction costs a company is exposed to while converting non-cash financial assets into cash. Thus, due to the economies of scale with the transaction motive, large firms carry less liquidity. Later, Mulligan (1997) also confirmed that big business tends to hold less cash as a percentage of sales compared to small ones.
The transaction cost motive also considers charges of obtaining external financing. As there are costs to purchasing and disposing real assets, in a similar vein there are fixed and variable expenses to external financial acquisition. In the presence of liquid assets shortage, a firm will have to choose between various options: dividends and investments reduction, assets sale or borrowing funds in capital markets, with the letter being a more preferred choice (Opler et al., 1999). The expenses attached to the financial market access prompt the company to resort to external financing less often and hold optimal amount of cash as a buffer (Kim et al., 1998). Therefore, companies with better investment prospects are assumed to be in possession of larger liquid reserves to pursue optimal investment policy; therefore, level of capital spending should be positively related with cash balances (Dittmar et al., 2003). Koller et al. (2005), similarly to Bates et al. (2009), pointed to a substitution effect of working capital due to its relatively simple and quick transformation features; that is firms with large working capital number tend to have less cash. The precautionary motive is regarded as a preventive measure against unforeseen circumstances. Mitigation of financial distress costs compels firms to hold ample funds as in terms of liquidity and in readily available lines of credit. Opler et al. (1999) also highlights advantage of keeping a portion of capital in the form of liquid assets stating that it helps to avoid passing on profitable projects due to liquidity shortage.
2.3.2. Pecking order theory
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entity. Thus, to minimize asymmetric information and other financing costs while choosing its options management will give preference to retained earnings first, then to the debt, and lastly to the equity. Such hierarchy of financial policies, rooted in the information asymmetry problem, gained widespread recognition as a pecking order theory. Presented with sharp adverse selection costs a company might pass on value creating projects, because it will not prove able to raise the needed funds. As a viable response to this scenario, aiming to circumvent adverse selection costs and not to pass on positive NPV projects, a firm may choose to bulk up its financial slack (Myers, 1984).
For oil and companies, Chen (2016) provides evidence of a “pecking order” existence in relation to cash flows. Constrained firms primarily deploy their cash flows for cash reserves accruement, while unconstrained firms direct their cash flows to discharge liabilities and arrange a share repurchase program once positive cash flow shocks occur.
However, findings by Seifert and Gonenc (2008) attest to the fact that the pecking order hypothesis is not relevant in some national environments, as companies from the US, UK, and Germany finance a substantial amount of their shortfalls with new equity issuance. In this regard, it is assumed that investor rights, quality and transparency of information flows in those countries presumably counter informational asymmetry between corporate insiders and the public.
2.3.3. Institutions and macroeconomic exposure
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of small elite, clips off economic activity and discourages capital spending. According to Bushman and Piotroski (2006), political and legal systems substantially contribute to the company's activity.
Westerman and von Eije (2005) emphasize that legislative developments in Eurozone enhanced performance of cross border financial markets. They found liberalization and deregulation of capital markets in the Eurozone lowered firms' costs associated with transactions and bankruptcy. Disintermediation was followed by cutbacks of working capital and funding expenditures. North (1990) attributed regulatory effectiveness to confidence and security building within a country, which helps to create a stable and transparent business networks. Bae and Goyal (2006) present evidence of creditor and property rights protection largely decreasing costs of raising funds from banks. Extending credit in economies with underdeveloped governance constitutes a significant expropriation threat, contracting the local credit distribution (Seifert and Gonenc, 2016). Thus, strong country governance, widely recognized rule of law along with vigorously pursued rights of creditors promote lower liquidity holdings within firms, while in riskier economies companies would opt to hold more cash as a safeguard against adverse shocks (Pinkowitz et al., 2006).
Further, we proceed to examine the principal firm characteristics as well as relevant external factors, which determine cash holdings decisions.
2.4. Financial and Institutional determinants of cash holdings 2.4.1. Collateralizable assets
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promote the firm’s risks profile make the collateral requisitions for external finance more prominent. Covered loans to oil and gas industry are deemed to be less risky compared to unsecured bonds, which could bring near-complete losses. (Bloomberg, 2016). Bottom line, firms in possession of low collateral value assets are up against significant challenges in sourcing external finance supply, forcing companies to reserve liquidity. Thus, we expect to find a negative link between cash holdings and collateralizable assets.
2.4.2 Cash flow
Company’s cash holdings could be regarded as retained historical cash flows. Given moderate cash flow volatility, high present cash flow should translate to relatively high cash holdings, yielding a positive relation between the two. Additionally, according to pecking order theory, companies will resort to internal generated funding, before going to external capital market. Therefore, large cash flows would be consistent with higher cash holdings, as confirmed by Opler et al. (1999). However, Kim et al. (1998) argue that cash flow provides an additional source of liquidity, viewing it as a cash substitute. In such a manner, increasing cash flow would alleviate the necessity of hanging on to cash overstock and for this reason, the relation in fact should be negative. Consequently, the estimated relationship between cash holdings and cash flow is ambiguous.
2.4.3. Firm size
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2.4.4. Leverage
The fundamental advantage of corporate liquidity is its function as internal funding for value creating projects. In a pecking order environment, debt is expected to increase within company when investment surpasses retained earnings and decrease when investment is less than retained earnings. Ferreira and Vilela (2004) suggest that correspondingly cash holdings should adhere to an inverse dynamics. Cash balances are reduced when investment exceeds retained earnings and rise once investment is less than retained earnings. In this manner, such a notion justifies the assumption that there is an inverse relation between cash and leverage. In much the same way, Kim et al. (1998), Opler et al. (1999) and Ozkan and Ozkan (2004) also lend credence to an inverse relation between leverage and cash holdings considering that firms can issue debt to generate cash when internal funds are little in amount. However, indebtedness also increases the probability of financial distress, forcing the firm to accumulate liquid resources, which in this sense could be viewed as a hedging tool (Acharya et al., 2007), leading to a positive impact. Hence, the estimated relationship between cash holdings and leverage is ambiguous.
2.4.5. Net Working Capital
In an environment of volatile oil prices, tighter regulations and intense pressure from shareholders, oil and gas companies have been focusing meticulously on cash and working capital management aiming to increase returns and deliver satisfactory cash flow to support investments and dividends (EY, 2014). Working capital aids the industry in tapping into valuable liquidity resources and its optimization is able to unlock cash to support itself and invest for the future (PwC, 2015). Opler et al. (1999), Anderson and Hamadi (2007), Garcia-Teruel and Martinez-Solano (2008) find that net working capital may serve as substitutes for cash and could be readily and relatively efficiently converted into liquidity once the need arises. Therefore, we expect to observe negative relations between liquid asset holdings and net working capital.
2.4.6 Capital expenditures
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development of oil and gas resources are forecasted to be reduced by 22% or US$740 billion (Wood Mackenzie, 2016), the sector still requires massive capital, as it devotes it to continuous proliferation of new property, plant and equipment in its upstream and downstream operations.
Previous studies on cash holdings have shown mixed results regarding capital outlays. For instance, Mikkelson and Partch (2002) find that high cash reserves are accompanied by greater investments, while Kalcheva and Lins (2007) observe companies with larger capital expenditure holding less liquidity. In general, tradeoff theory predicts a positive relationship between capital expenditures and cash holdings, since firms increase their cash balances to finance capital expenditures, while the pecking order suggests a negative sign as companies primarily finance their investment projects with accumulated cash (Dittmar et al., 2003). Therefore, the relation between capital expenditures and liquidity reserves is equivocal.
2.4.7. Country governance
According to La Porta et al. (2004), the democratic institute lays special emphasis on the separation and creation of laws and the administration of justice. In such context, achieving high level of business activity requires sustainable legal and economic environment coupled with quality regulations. Strong governance ensures better property rights protection by enforcing business contracts and improves lenders’ confidence, since the probability of loan repayment and collateral repossessing increases (Ayyagari et al., 2010). Sound governance regimes contribute to lower liquidity holdings within firms by reducing uncertainty (Seifert and Gonenc, 2016), while in riskier economies firms tend to reserve liquidity as a precautionary measure (Pinkowitz et al., 2006). Consequently, we expect to find a negative relation between a country’s quality of institutional framework and cash holdings of companies.
2.4.8. Financial market development
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1999). Even at times when oil price was above $100 a barrel for the recent years, major oil firms routinely needed to raise capital to cover their outlays (WSJ, 2015). Besides internal actions to raise liquidity, whether through capital expenditure cuts, reductions in dividends distributions and headcount contraction, energy firms regularly turn to external sources via debt or equity offerings. According to Brogan (2015) small cap explorers usually resort to equity issuance, whereas mid-to large-cap independent oil and gas producers are the largest users of reserve-based lending facilities from banks. Big international oil companies heavily rely on the support from banks, infrastructure funds, pension funds and other institutional investors.
Less developed financial markets provide limited credit supply and higher transaction costs of obtaining additional financial resources, which ultimately results in firms hoarding more cash (Ferreira and Vilela, 2004). A better access to finance decreases the marginal value of cash, reducing the necessity to hold large amount of precautionary liquidity (Faulkender and Wang, 2006). Hereby, we expect to observe an inverse relation between a cash holdings and country’s state of capital market.
However, as noted by La Porta et al. (1997), countries with strong governance mechanisms, as indicated by legal framework and the quality of law enforcement, have better developed financial markets. Thus, we will employ model assessing the impact of both factors on cash holdings and allowing comparison of their role in explaining cash reserves.
Table 1 shows summary of the relation between cash holdings and the established variables.
Table 1. Determinants of Cash Holdings
Variable Relation with cash holdings Explanation
Firm size Negative Economies of scale,
financial constraints Collateralizable value of assets Negative Ease of securing a
credit
Cash flow Negative/Positive Ready source of
liquidity/ Preference for financing with internal sources
Leverage Negative/Positive Increased funding costs/
Avoidance of financial distress
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2.5 Hypothesis development
In view of the theories explained above, we have constructed hypotheses related to corporate cash holdings that subsequently will be tested and analyzed. Cash holdings in oil and gas industry are estimated by applying factors found to influence the cash policies of non-energy companies: collateralizable value of assets, cash flow, firm size, leverage, country governance, capital market development, net working capital. We will use those explanatory attributes as proxies for the determinants of cash holdings to construct the regression models. In instances when predicted relationship between liquidity and some variable is ambiguous, we will resort to the prevailing view in the literature in formulating our hypothesis.
H1: Corporate cash holdings are inversely related to firm size
H2: Corporate cash holdings are inversely related to firm collateralizable assets H3: Corporate cash holdings are inversely related to firm cash flow
H4: Corporate cash holdings are inversely related to firm leverage
H5: Corporate cash holdings are inversely related to firm net working capital H6: Corporate cash holdings are positively related to firm capital expenditures H7: Corporate cash holdings are lower in countries with a strong governance H8: Corporate cash holdings are lower in developed financial markets
Country governance Negative Uncertainty reduction
Capital Expenditures Negative/Positive Decrease of internal funds/ Investment support
Net working capital Negative Source of additional
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3. Methodology and data collection
In this section, we describe the used dataset as well as our variables and methodology. We bring into focus objective and quantifiable observations that can be examined statistically and produce solid generalizations.
3.1 Sample and Data
In order to carry out the practical part of the research, we collected secondary data from the ORBIS database, compiled by Bureau Van Dijk. The database includes accounting and financial information on firms around the world, derived from the annual financial statements. In a few particular occurrences, we used primary data obtained directly from annual reports of companies. The sample includes listed and non-listed oil and gas companies (NACE codes 061, 0610, 06, 0620, 091, 0910, 495, 4950, 3523) from 33 European countries between the years 2010-2014. Only firms that have their domicile constant were counted, while companies that chose to relocate its nominal registration to other jurisdiction or subsidiaries of foreign firms were excluded. The countries presented vary in their institutional and economical aspects. Some countries were left out of the sample as completely lacking companies from the sector. After the corresponding criteria are applied, we proceed to a panel construction consisting of 800 firms representing total of 4000 firm-year observations. The specified sample is considered sufficient, since previous studies have generally analyzed a smaller amount of companies from energy industry (Haushalter, 2000, Jin and Jorion, 2004). The sample firms meet the following criteria: (a) possess more than $20 million in total assets; (b) have turnover more than $1 million; and (c) hold more than €0.5 million worth of cash reserves. Predominantly, we needed variables such as total assets, tangible assets, working capital and cash holdings to be positive, as well as any other variable defined as positive. The data covering the governance issues was acquired from World Bank World Governance Index website and the information on capital market from Z/Yen Group and their Global Financial Centers Index.
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various sectors on the quality of different properties of governance such as law enforcement, juridical system in protecting state's citizens against crime, freedom of expression, quality of public services, and property rights (Kaufmann et al., 2009, 2010). The WGI data sources reflect the perceptions of a very diverse group of respondents including surveys, country analysts at the major multilateral development agencies, non-governmental organizations, and commercial business information providers. For instance, in 2009, commercial business data accounted for 34 percent of the country-year information, while surveys and NGOs contribute 20 percent each, and public sector providers delivered the remaining 26 percent (Kaufman et al., 2009). Kauffmann et al. (2010) attributes particular value to perceptions data in the determination of governance as active participants from business or public sectors reference their actions according to perceptions and views.
The Global Financial Centers Index (GFCI) was obtained from a publishing agency website. The index encompasses two blocks: Instrumental factors and Financial center assessments. Instrumental factors consist of five broad areas constituting competitiveness of a capital market: Business Environment, Financial Sector Development, Infrastructure, Human Capital, Reputational and General Factors. The World Bank, The Economist Intelligence Unit, the OECD and the United Nations provide these quantitative measures. Financial center assessments is comprised of over 3000 financial professionals responses to questions related to their perceptions of financial market development. To exclude home bias, assessments from respondents’ home centers are removed from the factor assessment model (GFCI, 2014).
3.2.Variables construction
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logarithm of total assets. The capital market development (GFCI) has been approximated by considering the underlying data from The Global Financial Centers Index. For leverage (LEV), we use total debt to total assets. We measure capital expenditures (CAPEX) as capital expenditures to total assets. Net working capital (NWC) is estimated as net current assets minus cash. The cash flow has been measured by pre-tax profits plus depreciation over sales (CF1) or total assets (CF2). Collateralizable assets (COLL) would be a proxy for collateral firms need to secure the loan and is calculated as tangible assets over total assets. Measures of country institutional framework’s characteristics (WGI) are governance scores obtained from the World Governance Index. For more on the definitions of the variables mentioned consult Table 2.
Table 2. The description of Variables
3.3 Regression model specification
Since the data in our research encloses both time series and cross-sectional elements, the particular set of data would be known as a panel of data. There are a several benefits to a panel data analysis utilization, which is able to capture and quantify effects undetected in cross-sections and time series analysis (Baltagi, 1995).
The usage of panel data can demonstrate a causal link between governance indicators, financial markets development and cash holdings levels in firms. Compared to trend analysis,
Name Definition
Cash holdings (CASH1) Cash + Marketable securities/Total
assets
Cash holdings (CASH2) Cash + Marketable securities/Total
assets − (Cash + Marketable securities)
Size (SIZE1) ln (Sales)
Size (SIZE2) ln (Assets)
Leverage (LEV) Total debt/Shareholders equity
Cash flow (CF1) Pre-tax profits + Depreciation/Sales
Cash flow (CF2) Pre-tax profits + Depreciation/Total
assets
Net Working Capital (NWC) (Working capital − (Cash +
Marketable securities))/Total assets
Capital expenditures (CAPEX) Capital expenditures/Total assets
Capital market development (GFCI)
GFCI
Collateralizable assets (COLL) Tangible assets/Total assets
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where each time a new group is selected, the differences in personal preferences have less impact. In panel data analysis, a much larger set of data can be explored compared to time- and cross section analysis. Panel data has also a larger capacity to capture the complexity of human behaviour compared to time series data or a single cross-section. Such larger capacity has several advantages. The first advantage is the control of the impact of the variables that could have been omitted and unobserved. Second, the panel data has the possibility of releasing relationships that are dynamic (Hsiao, 2007). This is a big advantage since the behaviour in the economy is inherently dynamic, so that most econometrically interesting relationship are implicitly or explicitly dynamic (Nerlove, 2003). The third advantage is that testing and constructing of hypotheses with more complex behaviour will be possible.
Based on the variables and approaches discussed above, the following regression equations were constructed:
Regression with country-fixed effects to assess the impact of unobserved country-specific characteristics and the extent of cross-country heterogeneity.
_ ijt ijt j ijt Cash balance =X β+ +v u
The set of firm characteristics (X) used in our analysis is rather comprehensive, which relaxes a possible omitted variable bias. However, due to the fact that we have relatively many missing values, the number of observations per firm is often very limited for us to account for individual firm effects. That is why cross-country heterogeneity was accounted for by using country-fixed effects (vj). Computationally the approach is identical to including a set of dummy variables for countries. These fixed effects account for such unobserved factors as attitudes and laws towards cash holdings in different countries, which are mostly time-invariant, but country-specific.
a) Regression with institutional framework’s characteristics as possible explanatory factors of cross-country heterogeneity
_ ijt ijt jt ijt Cash balance =X β+Z δ +u
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b) Regression with the rating of the largest nearest financial center (F) as a possible explanatory factor of cross-country heterogeneity
La Porta et al. (1997) suggest that countries with deficient investor protection frameworks have less-developed financial markets confining firms in their access to external financing due to higher transaction costs of raising additional funds and promoting companies to accumulate more liquid balances. Djankov et al. (2007) as well as Bae and Goyal, (2009) point to similar positive relation between high creditor protection and large private credit markets. Thus, it could be that companies in countries with strong institutional framework hold less cash due to well-developed capital markets and not because of the precautionary motive. To test this hypothesis, we utilize the third model adding the variable from the Global Financial Centers Index that estimates the capital market development of the firm’s country of origin. This model assumes that the development of financial market explains the unobserved heterogeneity not accounted for by firm-level characteristics.
_ ijt ijt jt ijt
Cash balance = X β+F γ +u
c) Regression with the rating of the largest nearest financial center characteristics (F) and institutional framework’s characteristics (Z) as a possible explanatory factor of cross-country heterogeneity
_ ijt ijt jt jt ijt Cash balance = X β+Z δ+F γ +u
This model assumes that both macro-level factors influence cash holdings and allows comparing their role in explaining cash balances.
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4. Empirical findings 4.1 Descriptive statistics
Summary statistics of our dependent variables (CASH1 and CASH2), as well as of the average WGI indicator and financial centers’ ratings by country are presented in Tables 3 and Tables 4.
For the whole sample our average values of cash-to-assets ratio of 12% are almost the same as reported by Damodaran (2005) for U.S. oil and gas companies (12,6%), which suggests that companies in our sample hold comparable cash balances to their U.S. peers. Mean leverage results of our sample (48%) also corresponds with U.S. companies (46,9%).
It is worth noting that in Table 4 the variability of governance (WGI) within countries over time is extremely small with standard deviation not being higher than 3% of the mean for all countries except Ukraine, which means that governance quality is very stable, at least, in the short term. Financial market development ratings (GFCI) are somewhat more variable over time, but still rather homogeneous, with standard deviation being lower than 10% of the mean for all countries.
Table 5 presents cash holdings descriptive statistics by country with significant variations in some countries. These differences could be attributed to different institutional environment and the extent of financial markets development.
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Figure 1. Scatter plot of CASH1 vs. WGI
There is a moderately stronger positive relationship between cash holdings (CASH1) and the development level of the largest nearest financial center as presented in Figure 2. Multivariate analysis allows to verify whether this association remains significant after controlling for firm-level financial characteristics.
Figure 2. Scatter plot of CASH1 vs. financial market development
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4.2. Regression models
4.2.1. The effects of financial factors on cash holdings
The first set of models includes firm characteristics as regressors, as well as country-fixed effects to test the hypothesis that there is a significant heterogeneity of cash balances across countries controlling for firm features. We have checked that variance inflation factors (VIFs) do not exceed a commonly used threshold of five, indicating that standard errors are not seriously inflated by the collinearity among regressors.
Adding CAPEX has improved all of these models: the corresponding coefficient of CAPEX is systematically significantly different from zero. However, CAPEX is missing for some of the companies, which decreases the sample size. Nevertheless, we will include specifications 3 and 7 with CAPEX in our further analysis for robustness check.
Country fixed effects were included into all models 1-8, but were statistically significant (p<0.05) only for models explaining CASH1, while for models of CASH2 the presumption that individual country effects are zero cannot be rejected (p>0.05). Therefore, our conclusion is that some unobserved country-specific characteristics can influence CASH1, which points to the possibility of inclusion in the model institutional framework measures as they are relatively stable over time and can capture a significant portion of between- countries heterogeneity.
4.2.2. The effects of financial and institutional factors on cash holdings
Dittmar et al. (2003) find that a country’s institutional framework is related to the level of cash holdings. Consequently, the second set of models includes World governance indicators (WGI) as possible determinants of cross-country heterogeneity. These indicators are highly correlated with one another. The pairwise Pearson correlations vary from 0.77 to 0.99. Therefore, similarly to Seifert and Gonenc (2015) we averaged them out across all the 6 items after testing the reliability of the scale comprised of them. The reliability of scale is extremely high with Cronbach’s alpha equaling 0.98. That indicates a very high internal consistency of the set of governance quality measures. Therefore, these measures reflect the same construct and can be averaged out to obtain a single WGI score.
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is significantly positively associated with cash holdings (p<0.01). This set of models has a higher explanatory power than the set of models with country-fixed effects presented. The adjusted R-squares are higher, while information criteria are lower. A possible reason for this increase in explanatory power, yet small, could be that WGI ratings capture not only most of the cross-country heterogeneity, but also slightly vary in time, which is why WGI’s variance and thus explanatory power is somewhat higher than that of country-specific effects.
We can conclude that controlling for firm-level characteristics, companies operating in countries with higher governance have on average higher cash holdings. However, we cannot rule out the possibility that there is a presence of other country-specific factors such as certain laws and regulations that are difficult to account for in modeling, which could also be positively correlated with WGI and may promote higher cash holdings in such countries.
4.2.3. The effects of firm characteristics and financial market development on cash holdings
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4.3.Regression results Size
In line with Hypothesis 1 firm size (SIZE1 and SIZE2), denoted either as total sales or as total assets, has a negative coefficient with varying significance in all models, which is overall consistent with the argument that larger firms can access capital markets more easily and thus do not need to hold much cash. The negative relationship lends credence to the tradeoff argument, previously supported by Opler et al. (1999), Kim et al. (1998) as well as Seifert and Gonenc (2016). However, the results do not support previous empirical findings of Kalcheva and Lins (2003), Ozkan and Ozkan (2004), where the authors present evidence that cash holdings are positively related to the size of a company. Indeed, smaller oil and gas companies with less operational flexibility have limited access to liquidity via the public or private capital markets, while bigger energy companies are provided relatively easy access to cheap debt financing (Powell, 2015). Research, carried out by J.P.Morgan (2015) also attests to the fact that size and scale of oil and gas companies are the key determinants of their credit quality. A larger size helps companies to move into higher ratings categories, which consequently leads to better credit access.
Collateralizable assets
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Cash flow
Hypothesis 3 is rejected and we find a significant relationship opposite to what we hypothesised. Similarly to Ferreira and Vilela (2004) the sign of the cash flow to assets (CF2) coefficient is positive, which contradicts the tradeoff argument, but supports the pecking order theory. As is the case with Saddour’s research on French firms (2006) our evidence is significant in that cash balances increase with cash flow levels, since companies are able use their cash flow as liquidity substitution to finance investments. Therefore, as with other companies, oil and gas firms primarily fund themselves internally with cash flow and externally with debt (J.P. Morgan, 2015). Findings by Chen (2016) also suggest that oil companies build up their cash reserves from cash flows. As noted by Gavrilenkov et al. (2013), oil companies have great influence over their cash management policies design and can fine tune conditions in accordance to the given circumstances in order to have a ready source of liquidity. Overall, the results are consistent with the pecking order reasoning and are in conflict with the tradeoff argument.
Leverage
29
Net working capital
In the obtained results the negative sign and significance of the coefficients on NWC is similar to those documented in Opler et al. (1999) and Bates et al. (2009), supporting Hypothesis 5. It is consistent with the tradeoff model that regards working capital as the substitutes for cash holdings, since such readily obtainable assets other than cash can be liquidated in the event of a liquidity shortage. Therefore, firms with more liquid asset substitutes are better equipped to hold less cash. Indeed, as reported by EY (2014), of recent years firms from the oil and gas sector have been progressively focusing attention to cash and working capital management in an attempt to increase returns on capital and deliver sufficient cash flow to support investments. Today there is a rising awareness within the industry of how much value is left out because of previous little focus on working capital management as energy companies are having to operate in a lower surplus cash environment, coupled with increased competitive pressure and declining revenue streams.
Capital expenditures
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Country governance and financial market development
With regard to the variables of our main interest, we report evidence that companies from the oil and gas sector in countries with stronger institutional framework (WGI) hold more cash compared to firms operating in countries with weaker governance regimes. The relation is positive and significant and therefore, we reject Hypothesis 7 as the findings contradict our initial expectations and previous empirical evidence of Dittmar et al. (2003) as well as Seifert and Gonenc (2016). Even though the relative impact is small, it is still of interest because it contradicts the notion of higher cash holding ratios in countries with poor governance. The results, however, are in line with Caprio et al. (2013), who also find the positive relation between government quality and corporate cash holdings. With a sample of 30,000 firms across 109 countries, they find that a government with quality governance features tends to hold back from expropriation actions, and thus companies can hold more liquidity with less fear of government seizure. Conversely, consistent with precautionary motive, companies tend to shelter cash holdings from expropriation by carrying lower cash balances and channeling liquidity into less exposed tangible assets. Kusnadi and Yang (2010) as well as Iskandar-Datta and Jia (2014) also arrive to largely resembling findings.
Hypothesis 8 is also rejected as we find the level of capital markets development (GFCI) being significantly positively related with cash holdings, which is contrary to Ferreira and Vilela (2004), but consistent with Dittmar et al. (2003). It indicates that oil and gas companies hold more cash in developed capital markets and opposes the view that liquidity balances are determined by the failure of corporations to draw external financing. The motivation for such behavior could be explained by the precautionary reasons as reported by Opler et al. (1999). Companies from the sector hold excess cash to ensure that they will retain the ability to invest when cash flow is too low, compared to investment requirements. Results also suggest that the effect of financial market dominates the effect of governance, which means that cash holdings in oil and gas sector are clearly more sensitive to the level of financial market development than to governance factors.
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covers the period from 2010 to 2014. The obtained results in Table 15 are robust to this modification, match findings of Ferreira and Vilela (2004) as well as Seifert and Gonenc (2016) and support the notion that the extent of financial market development, measured by private credit to GDP, has a positive impact on cash holdings.
5. Conclusions
We explore the determinants of cash holdings for oil and gas firms in Europe, using panel data for the period 2010-2014. We model the cash-to-assets ratio as a function of company and country features. Similarly to previous observations (Opler et al., 1999; Ozkan and Ozkan, 2002, Bates et al, 2009) our findings suggest that the cash balances held by oil and gas firms are negatively affected by firm’s size, the amount of liquid asset substitutes, leverage and have positive relations with firm capital expenditures. These findings are largely in line with the tradeoff reasoning that optimal level of cash holdings is the result of firms stacking up the marginal costs against benefits of carrying liquid balances. This is foremost applicable in the oil and gas sector, where intrinsic forecasting challenges make holding a substantial buffer of immediately available funds paramount. Consistent with Ferreira and Vilela (2004) and Saddour (2006) we find positive relation between cash flow and cash holdings, which contradicts the tradeoff argument, but supports the pecking order theory. Therefore, we can safely assume that both tradeoff and pecking order theories provide a valid interpretation of the determinants of cash holdings in the oil and gas companies.
In conclusion, we provide evidence that firms in countries with strong governance, as measured by the World Governance Index, hold more cash. In this respect, the obtained evidence is consistent with the findings of Caprio et al. (2013), who suggest that in countries with poor governance firms appear to shelter assets from state expropriation by keeping fewer liquidity, as it is more vulnerable to expropriation than illiquid tangible assets (Myers and Rajan, 1998). The level of financial market development is positively related to cash reserves with the effect of financial market dominating the effect of governance, which is likely to be indicative of industry’s immense appetite for capital.
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39 APPENDIX
Table 3. Descriptive statistics for firm-level variables
Mean Standard
Deviation Percentile 25 Median Percentile 75 Valid N
CASH1 .12 .14 .03 .07 .15 4785 CASH2 .23 1.89 .03 .07 .18 4785 SIZE1 12.37 1.81 10.94 11.95 13.37 4785 SIZE2 12.36 2.17 11.18 12.35 13.51 4572 LEV .48 .26 .28 .49 .66 860 CF1 -5.22 175.01 .01 .07 .23 3788 CF2 -.26 22.18 .04 .08 .15 3907 CAPEX -.099 .133 -.151 -.085 -.039 672 NWC .00 .26 -.09 .00 .12 4785 COLL .32 .29 .03 .25 .55 4758
Table 4. Descriptive statistics for country-level variables
Mean Standard Deviation Percentile 25 Median Percentile 75 Valid N
voice_accountability 79.0 23.2 75.1 91.9 93.4 4785 polstab 63.0 22.1 57.3 63.5 76.8 4785 goveff 79.2 19.1 67.3 89.6 92.8 4785 regqual 80.5 19.0 74.9 86.7 94.8 4785 rulelaw 77.1 23.7 63.0 90.1 94.2 4785 corrupt 74.2 26.7 58.1 90.0 93.4 4785 WGI 75.5 21.5 67.2 86.4 89.3 4785 GFCI 634.4 87.8 581.0 629.0 677.0 4767
Table 5. Summary statistics by country: cash holdings
40 SE 0.064 0.044 0.027 0.062 0.091 0.071 0.053 0.028 0.066 0.101 SI 0.035 0.023 0.012 0.041 0.054 0.037 0.025 0.012 0.043 0.057 SK 0.095 0.074 0.042 0.058 0.13 0.112 0.101 0.044 0.062 0.15 TR 0.151 0.173 0.02 0.077 0.229 0.267 0.498 0.02 0.084 0.297 UA 0.08 0.087 0.015 0.053 0.124 0.099 0.131 0.015 0.055 0.141
Table 6. Summary statistics by country: average WGI and financial center rating
WGI GFCI
Mean SD Perc. 25 Median Perc. 75 Mean SD Perc. 25 Median Perc. 75
