Master Thesis Liquidity management before and during the recent financial crisis

Transcription

1 Master Thesis Liquidity management before and during the recent financial crisis An investigation of the trade-off between internal funds (cash, cash flow and working capital) and external funds (lines of credit) during normal and financially distressed times and an analysis of the usage of credit lines covenants Student: Sara Westling Student number: Supervisor: Dr. Erasmo Giambona July 2013

2 Abstract Liquidity management is essential to any firm at any time. However, efficient corporate liquidity management is particularly important during a financial crisis when there is uncertainty and scarcity of funds on the financial markets. The recent financial crisis has resulted in an opportunity to analyze how the shortage of external funds generally affects firms liquidity management. The aim of this research paper is to investigate the interaction between lines of credit, cash holdings, cash flow and working capital before and during the recent financial crisis. Two years are chosen for this research, namely, 2005 and 2008, which respectively represent a non-crisis and crisis period of time. The research is based on a unique hand-gathered dataset, which is collected by manually assessing annual reports and additional financial information is obtained from the Compustat database. When investigating firms liquidity management certain key firm characteristics as well as potential industry effects are also taken into account. Furthermore, attention is given to the usage of credit lines covenants in order to investigate whether credit line providers imposed more restrictions on their borrowers due to the financial crisis. Thus, it will be interesting to see whether the uncertainty and scarcity of funds on the financial markets during 2008, generally affected corporate liquidity management. The overall results of this study suggest that the lines of credit are negatively related with cash holdings, suggesting that credit lines and cash savings are substitutes. The findings also indicate that cash flow is essential to a firm s ability to obtain and sustain a line of credit. Thus, lines of credit and cash flow are found to be positively related however the positive effect of cash flow on lines of credit diminishes as cash holdings increases. Additionally, it seems that firms with a high level of internal funds tend to draw fewer funds from their revolving credit facilities. The relationships between lines of credit, drawdowns and the internal liquidity variables vary to some extent among different industries. Working capital is considered a substitute to cash savings and it seems to generally have a positive relation with credit lines. Furthermore, the financial crisis typically resulted in an increase in the usage of the credit lines covenants. 2

3 Table of content 1 Introduction Literature review Liquidity during the recent financial crisis Relationship between lines of credit, cash holdings and cash flow Firm characteristics effect on liquidity management Working capital; additional source of liquidity Covenants Data collection Methodology Descriptive statistics Firm characteristics Relationship between liquidity variables Subsample analysis Statistical covenant measures Results & Discussion Liquidity management at a glance Mean comparison analysis Lines of credit and drawdowns by firm characteristics Cash holdings and cash flow by firm characteristics Correlation analysis Regression analysis Regression analysis - Lines of credit, cash flow and cash holdings Regression analysis Credit line size, cash flow and cash holdings Regression analysis - Drawdowns, cash flow and cash holding Regression analysis Working capital as additional source of liquidity Regression analysis Subsample Covenants analysis Conclusion Bibliography Appendix

4 1 Introduction Liquidity management is the practice of ensuring that a company has enough cash or cash equivalents to meet its expected and unexpected financial obligations. Additionally, it should have sufficient resources of funds to be able to make long-term investments. The liquidity sources at a firm s disposal consist of for example its cash savings, which is the cheapest and most accessible source of credit. However, a firm can also have access to external funds, such as a line of credit. A revolving credit facility (line of credit) is an agreement from a financial institution to lend funds to a borrower until a certain limit is reached and the lender can impose certain restrictions on the borrower, which are known as covenants. A line of credit can be used to fill the liquidity shortage of a firm. A shortage of credit can be very costly for a company if it means forgoing profitable investment opportunities. Efficient liquidity management is therefore essential to any firm at any time. However, liquidity management is even more crucial during a financial crisis, when there is uncertainty and scarcity of funds on the financial market. The recent financial crisis has resulted in an interesting period of time to study, and the aim of this research paper is to analyze how a credit crunch affects corporate liquidity management. Namely, the trade-off between internal funds (cash holdings, cash flow and working capital) and lines of credit is investigated for 2005, a year of regular economic environment, and 2008, a year of financial turmoil. The research questions of this paper are therefore as follow: How did the relationship between internal and external sources of financing change during the recent financial crisis? & How did the usage of line of credit covenants evolve during this period of time? A line of credit is an important part of corporate liquidity management. However, extensive empirical research of this subject is lacking. A reason for this could be that financial information on lines of credit is generally not accessible from databases. This thesis will therefore contribute to existing literature by empirically investigating the interaction between lines of credit and internal funds, during normal and distressed times, using a unique handgathered dataset. The sample set consists of public non-financial companies from the US. The firms data concerning lines of credit and their related covenants is manually collected by assessing annual reports via the Securities and Exchange Commission website ( and additional financial information is obtained through Wharton Research Data Services and the database Compustat. This research builds on the investigation made by Sufi (2009), who for first time collected extensive data on lines of credit. He concluded, among other things, that lines of credit are an important part of corporate liquidity management and that firms with 4

5 a high level of cash flow consider credit lines as a viable substitute of liquidity. Campello, Giambona, Graham and Harvey (2011) have also contributed to this field of research. Namely, based on a survey, where international CEOs were asked about their liquidity management during the financial turmoil, they concluded that a positive relation between lines of credit and cash flow exists for companies with a low level of cash holdings, and they also found that financially unconstrained firms tend to hold a lower ratio of credit lines to total assets. Additionally, Campello et al. (2011) concluded that firms with lower levels of cash savings and cash flow tended to draw a higher proportion of funds from the available lines of credit. However, this investigation will differ from previous research since a new event window will be studied; a different sample set of firms will be used; liquidity management among various industries will be investigated; attention to an additional liquidity source (working capital) will be given and its effect on liquidity management will be studied; and whether the financial crisis affected the usage of lines of credit covenants will be researched for the first time. The results of this study will be relevant for firms and financial institutions. For example, it is important for firms to know how financial instability on the market can affect the external supplies of credit and what kind of restrictions financial institutions usually impose on a borrower, both during normal and financially distressed times. Additionally, the findings of this study can be relevant for economic policy-making as well as for academic purposes. In this research paper certain firm characteristics will be defined with the aim of investigating whether liquidity management differs among various types of firms. Namely, the sample will be divided controlling for size, investment grade, bank dependency and profitability. A mean comparison analysis will be performed for different liquidity sources while controlling for firm characteristics. The findings will give insight on how firm characteristics affected the liquidity management during the non-crisis and the crisis period. Previous research has, for example, concluded that access to lines of credit is greater among large, profitable, non-bank dependent companies with an investment grade, which are firms that can be considered as financially unconstrained (Campello, Graham and Harvey, 2010). The overall results of the mean difference test are in line with the findings of Campello et al. (2010), that the majority of firms with an available line of credit are unconstrained firms. Additionally, the outcome of the analysis reveal that unconstrained firms tend to hold a lower ratio of cash savings to total assets, which is consistent with the results of Almeida, Campello, and Weisbach (2004). 5

6 A correlation matrix and several ordinary least squares (OLS) regressions will be made with aim of analyzing the relationship between the different liquidity variables (lines of credit, drawdowns, cash holdings, cash flow and working capital) that are included in this study. The results indicate that cash flow has a positive effect on the access to a line of credit. However, this positive effect mitigates as cash holdings becomes larger and an increase in the cash flow ratio will not generally result in an increase in the size of the credit line. A revolving credit facility is concluded to be a valid substitute of cash savings, which is in line with the findings of Sufi (2009). Drawdowns from credit lines are highest among firms with a low level of internal liquidity, which also supports the findings of previous research. Working capital is throughout this paper defined as accounts receivable plus inventory minus accounts payable, while controlling for total assets. Working capital is negatively related with cash holdings during the financial crisis. Thus, working capital and cash savings can, during this period of time, be considered substitutes of liquid assets. Lines of credit and working capital seem to generally have a positive relationship, which indicates that providers of credit lines often require their borrowers to keep a certain level of accounts receivable and inventory as collateral. Small and bank dependent firms tend to have a higher level of working capital during the financial crisis compared to large and non-bank dependent companies. This outcome follows the line of existing research which argues that constrained firms, on average, have a higher demand for liquid assets, such as working capital (Almeida and Campello, 2010). This thesis paper will, additionally, contribute to previous research by analyzing whether the relationship between internal and external funds is diverse among different industries, before and during the recent credit crunch. This research s dataset consists to 99% of manufacturing firms from different divisions. Thus, this study will, by performing OLS regressions including an industry dummy variable, provide information on whether corporate liquidity management differs among various manufacturing segments. The findings of the industry analysis show that liquidity management differs, to some extent, among various manufacturing segments. For example, firms which produce chemical and allied products tend to have a slightly lower access to lines of credit during the crisis period compared to other manufacturing firms. 6

7 The usage of lines of credit covenants inside and outside the credit crisis will also be examined to further increase the contribution of this study. A mean difference test will be performed and the results indicate that the usage of credit line restrictions generally increased during the financial turmoil. However, the only increase that can be considered significant at a 10% test level, when comparing the non-crisis and the crisis period, is the usage of the M&A clause. Hence, providers of revolving credit facilities tended to significantly more often restrict their borrowers from engaging in consolidations or from making acquisitions during the financial crisis. An introduction to this paper s topic, liquidity management before and during the recent financial crisis, has now been provided. The remaining part of this thesis is organized as follows; the next section (2) will present the literature review where the findings of previous studies concerning the interaction between internal and external funds as well as firm characteristics effect on liquidity management and the usage of covenants will be discussed. In the subsequent sections (3) and (4), the data collection and the methodology of this study will be described, respectively. Section (5) will follow, where the empirical results will be presented and discussed. In the final section (6), a conclusion of the research will be provided to summarize the findings concerning the financial crisis s effect on corporate liquidity management. 2 Literature review In order to investigate the liquidity management, specifically the interaction between internal funds and lines of credit during normal and distressed financial times, it is important to know when lines of credit are typically provided and under which conditions they are generally drawn. In this section, the credit supply during the recent financial crisis will therefore be discussed. Further, the results of previous conducted studies concerning the relationship between lines of credit, cash holdings and cash flow will be analyzed. Firm characteristics also have an effect on the liquidity sources at their disposal. Therefore, the findings of existing research concerning firm characteristics and their liquidity management effects will also be discussed. Furthermore, a discussion of the effects of working capital on liquidity management will be provided. Finally, the usage of covenants will be discussed. 7

8 2.1 Liquidity during the recent financial crisis During the recent financial crisis, liquidity dried up which resulted in a decrease of credit supplies from banks (Cornett, McNutt, Strahan and Tehranian, 2011). Ivashina and Scharfstein (2009) noted that when the financial crisis hit the market, firms had difficulties to roll over their short term debt due to a run of short term bank creditors. However, the aggregate balance sheet of the US s banking sector actually showed an increase by $100 billion of loans from September to mid-october in the year of 2008 (Chari, Christiano, and Kehoe, 2008). This was due to an increase in drawdowns of already committed lines of credit (Ivashina et al., 2009). A paper by Gao and Yun (2009) discussed the effect of the financial crisis on the usage of commercial papers and credit lines for nonfinancial firms. They found similar results. Namely, they concluded that the aggregate use of commercial papers declined during the crisis, especially among firms with a high default risk and that these high-risk firms tended to substitute commercial paper borrowings with lines of credit. Thus, during financially distressed times, when liquidity is scarce, previous studies have found that firms tend to take advantage of their already established lines of credit and thus make more drawdowns. This paper will research whether similar result can be found when using this unique dataset. 2.2 Relationship between lines of credit, cash holdings and cash flow Lines of credit are an important part of corporate liquidity management. Nevertheless, there has been a limited amount of empirical research within the field of credit lines. However, in 2009, Sufi made an extensive contribution with his paper Bank Lines of Credit in Corporate Finance: An Empirical Analysis, which analyzed the management of liquidity. In particular, the choice between cash and lines of credit was investigated. He concluded that from 1996 to 2003, nearly 85% of the firms in his sample had obtained a line of credit. Thus, credit lines are undoubtedly an important factor of liquidity management. Sufi (2009) also concluded that lines of credit are a viable substitute of liquidity at least for firms with a high level of cash flow, whereas firms with a low level of cash flow tend to rely more heavily on cash. Sufi (2009) also pointed out that the usage of cash flow based covenants is very common and that this is an important factor of the positive relationship between cash flow and lines of credit. Thus, in order to meet the line of credit requirements, firms often have to maintain a high level of cash flow. This indicates that firms with a higher level of cash flow can more easily obtain and sustain credit lines. Additionally, this could explain why companies may or may 8

9 not choose to use lines of credit. Furthermore, Sufi (2009) found evidence of a negative relationship between cash holdings and lines of credit, which suggests that a substitution effect between cash holdings and lines of credit exists. However, a paper by Huang (2010), discussing the usage of credit lines during the recent financial crisis, concluded that lines of credits are not perfect substitute for cash holdings, at least not for smaller and more risky firms. This paper will research whether similar results can be found for this study. Campello et al. (2011) studied how different types of liquidity sources, namely how cash, cash flow and lines of credit, interacted during the recent financial crises. Their research, which was based on surveying international CEOs on their liquidity management during the financial turmoil, showed that when firms are facing a credit crunch they substitute between internal funding and lines of credit. However, firms without access to lines of credit tend to choose between saving and investing when liquidity is scarce. Similar to Sufi (2009), Campello et al. (2011) found that credit lines and cash flows are positively related. However, they only found this relationship for firms with low cash holdings. Additionally, they researched how the liquidity management affected firms decisions regarding capital investment, technology spending, and employment during the credit crisis. They concluded that lines of credit seem to have eased the effects on corporate investments during the financial crises. Moreover, Campello et al. (2011) showed that companies with a higher level of cash savings and cash flow tended to draw a smaller proportion of funds from the available lines of credits. Ivashina et al. (2009) and Campello et al. (2010) argued in their respective papers that the usage of credit lines increased during the financial crisis. 2.3 Firm characteristics effect on liquidity management Literature concerning the effects of firm characteristics on liquidity management found that financially constrained firms have a tendency of saving more cash than unconstrained firms (Almeid et al., 2004). The paper of Opler, Pilkowitz, Stulz, and Williamson (1999) revealed similar results, that unprofitable companies and firms without access to financial markets tend to have a higher level of cash holdings. Another study, argued that constrained firms hold more cash as a value-increasing response to expensive external funding (Denis and Sibilkov, 2010). Moreover, Campello et al. (2010) found evidence that small, unprofitable, and private firms without an investment grade, thus constrained firms, have a larger proportion of credit 9

10 lines to total assets. This study will also investigate how firm characteristics affect liquidity management. 2.4 Working capital; additional source of liquidity Most literature has focused on internal funds in terms of cash holdings and cash flow. However, working capital can also be seen as a part of internal liquidity. Fazzari and Petersen (1993) argued that working capital is a source of liquidity that is often neglected and that can, in addition to cash savings, be used to smooth fixed investments when firms face financial constraints. Working capital is defined as current assets, such as accounts receivable and inventory, minus current liabilities, as for example accounts payable (Fazzari et al., 1993). Enqvist et al. (2012) found, when researching a sample of Finnish listed firms from 1990 to 2008, that managing working capital is more important during financially distressed times than during better general economic circumstances. Additionally, Enqvist et al. (2012) argued that working capital is a key factor of firms liquidity and should therefore be included in firms financial planning. However, a survey performed by PwC (2009) on European companies showed that very little attention has been given to increase the efficiency of working capital between 2005 and A firm s characteristics might also affect whether a firm will choose to alter their level of working capital. Since, financially constrained firms tend to react differently to uncertainty on the market than unconstrained firms (Korajczyk and Levy, 2003). Constrained firms do not only worry about the financing of current expenses and investments, but also about future ones (Almeida et al., 2010). Therefore, constrained firms tend to have a higher demand for liquid assets than unconstrained firm and especially during a crisis when external liquidity is limited and very costly to obtain. As stated by Bates, Kahle, and Stulz (2009), net working capital consists of assets that are substitutes for cash holdings. Hence, both cash savings and working capital can be considered liquid assets. When a financial crisis hits the market, it is expected that firms will choose to increase their working capital in order to decrease their needs for external financing and to secure funds for future investment opportunities (Almeida et al., 2010). It is also expected that companies with a current line of credit agreement are less affected by a decrease of credit supplies during a financial crisis since they can draw funds from their credit lines. Therefore, it is likely that these firms will 10

11 not feel that a buffer of liquid assets is necessary to secure financing for future capital expenditures. Thus, lines of credit are from this aspect, expected to be negatively related to the level of working capital. However, it should be pointed out that lines of credit can, at times, be collateralized by accounts receivable and inventory. Additionally, the amount available to be borrowed under the line of credit does sometimes depend on the firm s level of inventory and accounts receivable. This could imply that lines of credit are actually positively related to the level of working capital. Since a firm with a current line of credit might, for example, be restricted to hold a certain level of inventory as collateral. This is in line with the findings of Agarwal, Chomsisengphet, and Driscoll (2004), who investigated private held firms with a line of credit and found that profitability and working capital have a positive effect on the size of the obtained credit line. This research paper will investigate this issue and conclude the relation between working capital, lines of credit and cash savings. 2.5 Covenants A covenant is a certain restriction imposed by a lender on the borrower. Covenants are commonly present in different types of financial contracts, such as private and public debt, and private equity (Chava and Roberts, 2008). Financial institutions usually also provide lines of credit restricted by some contractual covenants. These restrictions are developed in order to mitigate the risk for conflict of interest between the lender and the borrower. Hence, the covenants are intended to decrease the agency problem and consequently protect the lender (Smith and Warner, 1979). Chava et al., (2008) argued that covenants are set tightly and are regularly violated. Violations of covenants can result in increased fees and markups. Additionally, it can restrict a firm s access to credit facilities (Campello et al., 2010 and Sufi, 2009). Demiroglu and James (2010) found that line of credit agreements usually contain more restrictive and tight covenants for riskier and less transparent firms. Line of credit covenants often prohibit firms from taking on additional indebtedness and engaging in asset sales. Additionally, they usually restrict the firms payments of dividends to its shareholders unless certain conditions are met (Lins, Servaes, and Tufano, 2010). Thus, firms that regularly pay dividends might be less likely to consider lines of credit as a substitute for cash holdings. Smith and Warner (1979) argued that it is not surprising that dividend restrictions are often imposed on borrowers. Since, if dividend payments are financed by a reduction in the firm s investment expenditures, it will reduce the expected value of the company s assets and thus increase the likelihood of default. Other common covenants concern restrictions of 11

12 investments and M&A. These clauses can be expensive when firms must forgo profitable investment opportunities. In times of financial distress it can be expected that financial institutions that provide lines of credit will increase the usage of covenants and tighten these restrictions in an attempt to secure their interest. 3 Data collection A hand-gathered unique dataset is used to investigate how lines of credit affect corporate liquidity management. The dataset contains detailed information of credit lines and their associated covenants for nonfinancial US public firms. The years 2005 and 2008 are investigated. The sample contains data of 2212 US public companies for 2005 and of 1775 US public firms for The data concerning firms lines of credit, drawdowns and covenants are found by manually assessing annual 10-K or 10-KSB (small business) reports via the Securities and Exchange Commission website ( Following the methodology lines of Sufi (2009), certain key words, such as, credit lines, credit facility, revolving credit agreement and line(s) of credit, are used to search for the required information to justify whether a firm has a line of credit at the end of the fiscal year and under which conditions this credit lines is agreed upon. Hence, the paragraph surrounding the key word often reveals whether the line of credit is still valid at the end of the fiscal year, the total size of the credit line agreement and what the outstanding amount is. Additionally, the line of credit covenants which the firm needs to be in compliance with are usually stated. Information about the following covenants are collected; total leverage, dividends, investment, asset sale, M&A and share repurchase. If a firm is restricted by a certain line of credit covenant, a 1 is stated for that specific covenant, otherwise a 0 is notated. Moreover, additional financial information concerning cash holdings, cash flow (EBITDA), total assets, credit rating, accounts receivable, inventory and accounts payable is obtained through Wharton Research Data Services and the database Compustat. The dataset contains mostly manufacturing US public firms. Namely, 99% of the companies are classified as manufacturing firms, based on their four-digit Standard Industrial Classification (SIC) code. These companies have a SIC codes ranging from 2000 to 3999 and are therefore classified as manufacturing firms. The SIC codes were further used to identify and divide the sample into 20 different industries within the manufacturing sector. This was done with the purpose of the subsample analysis, which will investigate whether the relationship between internal funds and externals funds differ among different manufacturing 12

13 industries. Table 12 in the appendix provides additional information and presents the number of observations for each division. Following the lines of Campello et al. (2011), the liquidity variables are defined as below and these definitions are used throughout this paper. Table 1. Variable definitions Variable Line of credit: Cash flow: Cash holdings: Drawdowns: Working capital: Definition Total line of credit commitment to total assets EBITDA to total assets Cash and marketable securities to total assets Outstanding loan to total line of credit commitment Working capital to total assets 4 Methodology In this section the methodology of this study will be discussed. In order to answer the research questions concerning the relationship between internal funds and lines of credit, and the usage of lines of credit covenants, a number of statistical measures will be taken. A summary statistics will first be carried out, to give a glance on the liquidity management before and during the crisis. Then, a mean comparison analysis will be made in order to investigate whether the liquidity management significantly changed from 2005 to 2008 and how firm characteristics affect the management of liquidity. OLS regressions will follow, exploring the relationship between the key variables; cash holdings, cash flow, working capital, lines of credit and drawdowns. Regressions including the industry factor will also be carried out. Finally, a mean difference test will be taken to analyze the usage of covenants and to conclude whether the financial crisis made credit lines lenders impose more restrictions on the borrowers. 4.1 Descriptive statistics In order to get a first insight on when lines of credit are usually provided and drawn, and how credit lines are related to cash holdings, cash flow and working capital, a summary statistics will be carried out for the years 2005 and Thus, this will provide a picture on how the liquidity management changed when the recent financial crisis hit the market. The descriptive 13

14 statistics will include the percentage of firm having a line of credit, and the variables; line of credit, drawdowns, cash holdings, cash flow, working capital which follows the definitions described in the previous section. A number of firm characteristics will also be included, which are presented in more detail in the following part. In order to investigating the internal liquidity sources and the firm characteristics, the complete sample will be divided into two subsamples; firms with a current credit line and companies without a line of credit. This will give insight on the relation between the lines of credit and internal funds as well as which types of firms generally have access to lines of credit. The mean, the standard deviation, the 25 th, the 50 th, and the 75 th percentile will be reported for each variable in the summary statistics, as well as the sample size. 4.2 Firm characteristics In order to analyze the liquidity management for different types of firms, the sample will be divided controlling for certain firm characteristics. Namely, the size, the investment grade, the profitability of the firm, and whether the firm is bank dependent, will be taken into account. Campello et al. (2011) followed below qualifications when defining a borrower as regular/unconstrained or as non-regular/constrained. This research paper will follow the same definitions lines. Table 2. Constraint versus unconstraint borrower Constraint borrower Unconstraint borrower Small: Sales $1 billion Large: Sales > $1 billion Bank dependant: No S&P credit rating Non-bank dependent: S&P credit rating Non-investment grade: No credit rating, or credit rating < BBB- Investment grade: Credit rating BBB- Unprofitable : Negative net income Profitable: Positive net income Campello et al. (2011) found, as described in the literature review, that regular firms dominate the sample containing firms with a line of credit. Thus, according to previous research, large, profitable, non-dependent firms with an investment grade tend to more often have access to lines of credit. To test whether this statement also holds for this dataset a comparison of the means will be performed. Namely, with the aim of researching whether the liquidity management diverges among different types of firms and whether the management of funds significantly changed during the financial crisis, a two-tailed mean difference test will be carried out where the variables; lines of credit, drawdowns, cash holding, and cash 14

15 flow will be reported, conditional on above mentioned firm characteristics. Additionally, the percentage of firms with a line of credit and the percentage of companies with a drawdown, taking the firms characteristics into account, will also be included in the mean comparison analysis. 4.3 Relationship between liquidity variables The literature review showed that previous research has found a positive relationship between cash flow and lines of credit, which indicates that firms with a higher level of cash flow more easily can obtain and sustain credit lines. Existing literature has also found evidence of a negative relationship between cash savings and lines of credits, which suggests that a substitution effect between cash holdings and lines of credit exists. This also implies a negative relation between cash savings and drawdowns. Working capital is expected to have a negative relation with cash holdings since they can be considered substitutes of liquid assets. In order to investigate the correlation between these liquidity variables; credit lines, cash holdings, cash flow, drawdowns and working capital, a correlation analysis will be carried out, for 2005 and The results will show whether the outcomes of this study are in line with the findings of previous research. To further investigate the relation between the liquidity sources a number of OLS regressions will be performed. Following the lines of Campello et al. (2011), the effect of internal funding (cash and cash flow) on the level of availability of credit lines will first be estimated by an OLS regression while controlling for firm characteristics. To investigate whether the liquidity management differs over normal and financially distressed times, the regressions will be computed separately for 2005 and Furthermore, the regression will be computed for the whole sample, consisting of firms with and without lines of credit, as well as for the sample containing exclusively companies with a current credit line. The purpose of this is to provide additional insights of the relation between the liquidity sources. Hence, the additional regression based on the line of credit sample, will show the effect of cash flow and cash holdings on the size of the credit line. The regressions are based on following formula. LC i =c+ α 1 Cash flow i + α 2 Cash holdings i + α 3 (Cash flow*cash holdings) i + γx i + ε i 15

16 Where: Line of credit (LC), Cash flow, and Cash holdings are following the specified definitions. X is the control variable of firm characteristics, thus, controlling for size, bankdependency, grade of investment and profitability. ε is the error term. The aim of the next regression, also in line with the research of Campello et al. (2011), is to determine whether firms with a high level of cash flow and cash savings tend to draw less from their credit lines which is suggested by existing literature. This regression will also be computed for both years of interest with aim of researching whether the financial crisis affected the relation between these variables. DD i = c + α 1 Cash flow i + α 2 Cash holdings i + α 3 (Cash flow*cash holdings) i + γx i + ε i Where: Drawdowns (DD), Line of credit (LC), Cash flow, and Cash holdings are following the specified definitions. X is the control variable of firm characteristics, thus, controlling for size, bank-dependency, grade of investment and profitability. ε is the error term. As described in the literature review, working capital is an additional source of internal liquidity. Working capital is here defined as accounts receivable plus level of inventory minus accounts payable, controlled by total assets. Below regressions will be carried out with the aim of investigating the relationship between lines of credit, working capital and cash. It will be interesting to see whether firm characteristics, cash savings and access to a line of credit affect the level of working capital. The regressions will be carried out for both 2005 and 2008, in order to investigate whether the relationships diverge over the credit crisis. LC i =c+ α 1 Cash flow i + α 2 Cash holdings i + α 3 (Cash flow*cash holdings) i + α 4 Accounts receivable i + α 5 Inventory i + α 6 Accounts payable i + α 7( Current assets*current liabilities) i + γx i + ε i WC i =c + α 1 Cash flow i + α 2 Cash holdings i + α 3 (Cash flow*cash holdings) i + α 4 LC i + γx i + ε i Where: Line of credit (LC), Cash flow, Cash holdings and Working capital (WC) are following the specified definitions. X is the control variable of firm characteristics, thus, controlling for size, bank-dependency, grade of investment and profitability. Current assets 16

17 consist of accounts receivable and inventory and current liabilities represent accounts payable. ε is the error term. 4.4 Subsample analysis The dataset used for this research paper consists mostly of manufacturing firms and the sample is divided into 20 different manufacturing industries based on their SIC codes. The six out of these 20 divisions with the highest number of observation will be included in this analysis, as shown in table 12. This subsample research will enable a conclusion of whether liquidity management is diverse among different manufacturing industries and whether the financial crisis had a stronger affect on some particular division. Below regression will be carried out for both 2005 and 2008, and a dummy variable is included to control for industry. LC i =c+ α 1 Cash flow i + α 2 Cash holdings i + α 3 (Cash flow*cash holdings) i + βindustry i + γx i + ε i Where: Line of credit (LC), Cash flow, and Cash holdings are following the specified definitions. Industry is the dummy variable for manufacturing division, i.e. Food & Kindred Products, Chemicals & Allied Products, Industrial Machinery & Equipment, Electronic & Other Electric Equipment, Transportation Equipment, and Instruments & Related Products. X is the control variable of firm characteristics, thus, controlling for size, bank-dependency, grade of investment and profitability. ε is the error term. 4.5 Statistical covenant measures One of this paper s research questions is to analyze how the covenants have evolved from 2005 to As presented in the literature review, the usage of lines of credit covenants can be expected to have increased during the recent financial crisis. This will be researched by computing the percentage of firms with a specific covenant, hence determining the mean of the usage of each covenant for the non-crisis and the crisis period. Thus, only the firms with a current line of credit will be taken into account. The credit line covenants included in this study are, as already mentioned, total leverage, dividends, investments, asset sale, M&A and share repurchase. A two-tailed mean difference analysis will then be performed, in order to determine if the financial crises significantly affected the usage of covenants. Since the dataset used in this study only contains dummy variables equal to 1 when a firm is restricted by a certain line of credit covenant and otherwise the dummy variable is equal to 17

18 0, it will be impossible to conclude whether the restrictions are set tighter. Thus, this research will only be able to conclude whether more covenants are used during the financial crisis. 5 Results & Discussion In this section the results of the statistical measures, taken in order to answer this study s research questions, are presented and discussed. The tables which report the findings of the statistical measures can be found in the paper s appendix. The results of the summary statistics will first be analyzed, providing a broad picture of the liquidity management inside and outside a financial crisis. Then the outcome of the mean difference test will be analyzed, revealing whether liquidity management significantly differs among different types of borrowers and whether these relationships were affected by the financial crisis. The results of the correlation analysis and the outcome of the OLS-regressions will follow, where the relationship between cash, cash flow, working capital, lines of credit and drawdowns will be discussed. The OLS regressions will also take firm characteristics into account. Additionally, the results of the industry analysis will be evaluated, revealing whether liquidity management differs among different manufacturing divisions. Finally, the findings concerning the usage of covenants will be analyzed in order to conclude whether more restrictions were imposed on borrowers during the credit crisis. 5.1 Liquidity management at a glance The summary statistics presented in table 3 in the appendix show the liquidity management at a glance before and during the financial crisis. Specifically, the table reports the mean, the standard deviation, the 25 th, the 50 th and the 75 th percentile for the key variables included in this research as well as the sample sizes. As can be seen in the table, around 67% of the firms in this sample have a line of credit in 2005, this number increase to 69% in Thus, these results are consistent with the conclusion of Sufi (2009) that lines of credit are an important part of liquidity management. The variables; line of credit, drawdowns, cash holdings, cash flow and working capital are included in the statistical summary and they follow their specified definitions which are presented in table 1. The descriptive statistics results reveal that in 2005 an average firm tended to have a line of credit representing 18% of its assets. In 2008, this number had increased with 1%. Drawdowns increased from 18% in 2005 to 22% in 2008, which indicates that firms took more advantage of their lines of credit during the 18

19 financial crisis when liquidity was scarce. In order to investigate whether liquidity management is different among firms with and without a line of credit, the sample was divided into these two groups for the remaining part of the summary statistics. It can be seen that firms with access to a line of credit tend to hold less cash than companies without a line of credit. Specifically, in 2005 it was found that firms with a line of credit have a cash holding ratio of 16% whereas firms without a line of credit have a cash holding ratio of 48%. Thus, companies with no access to a line of credit tend to feel a stronger need to keep more cash on their balance sheet. Similar results were found for It should also be noted that the ratio of cash savings to total assets slightly decreased from 2005 to Hence, all types of firms tended to use their cash savings to a larger extent during the crisis. Furthermore, firms with a line of credit tend to have positive cash flow to total asset ratio whereas companies without a credit line on average have a negative cash flow ratio. This holds for both investigated years. This supports the argument of Sufi (2009), that to be able to receive and sustain a line of credit firms are often required to have positive cash flows. The summary statistics concerning working capital shows that for both 2005 and 2008 firms with a line of credit have approximately a 13% higher working capital ratio than firms without a line of credit. This indicates, as previously discussed, that firms with a line of credit are often required to keep a certain level of working capital. However, the working capital ratios are more or less constant for the investigated years, namely, around 25% for firms with a credit line and approximately 12% for companies without a line of credit, for both 2005 and This suggests that the financial crisis did not make firms alter their level of working capital. Lines of credit are provided to firms who the lender believes will be able to meet the required obligations. Thus, it can be expected that credit lines are generally given to unconstrained borrowers, that is, large, profitable firms with a satisfying S&P rating. In order to investigate this, the summary statistics were also here carried out for the two samples; firms with and without access to a line of credit, while controlling for firm characteristics. The results show that the sample of companies with a line of credit are to a larger extent firms that are financially unconstrained, thus profitable firms with sales over $1 billion and with an investment grade above BBB-. For example, 38% of the firms with a line of credit are considered large firms whereas only 6% of the firms without a credit line have sales over $1 billion. Notable is also that 71% of the firms with a line of credit were profitable in

20 while in 2008 only 60% of these firm had positive net income, which can be a result of the financial distress during this year. 5.2 Mean comparison analysis In this part the results of the mean difference test will be presented and discussed, which will reveal the liquidity management among different types of firms, before and during the crisis. Firstly, the findings concerning credit lines and drawdowns conditional on firm characteristics will be analyzed. Secondly, the results of cash holdings and cash flow with respect to firm characteristics will be reported Lines of credit and drawdowns by firm characteristics The results from the two-tailed mean difference test concerning lines of credit and drawdowns while controlling for firm characteristics are reported in table 4, which can be found in the appendix. The firm characteristics follow their pre-specified definitions and the years 2005 and 2008 are included in the comparison. Column 1 shows that approximately 60% of the small firms and around 91% of the large firms have access to a line of credit in Similar results are found for 2008, column 2. Thus, it can be concluded that for both investigated years, the majority of firms with a line of credit are large firms, i.e. firms with sales above $1 billion. Roughly, the same results are found when considering bank dependency and investment grade. There is a slight, but significant (10% test level) increase from 2005 to 2008 of the percentage of firms with a credit line that are non-bank dependent and that have an investment grade. It can also be noted that profitable firms dominate the sample of firms which have a line of credit, and that the difference between unprofitable and profitable firms ability to receive a line of credit is significant. Thus, these findings are in line with the results of Campello et al. (2011) that access to lines of credit is significantly greater among large, profitable, non-bank dependent companies with an investment grade. Column 3 and 4 show the percentage of firms with a drawdown at the end of the investigated fiscal year conditional on having access to a credit line. Thus, this sample only contains firms with an available line of credit. For the year of normal economic circumstances, 2005, it can be seen that constrained firms tend to more frequently draw funds from their lines of credit than regular borrowers. However, this difference is only significant at 1% test level when comparing small and large firms and when comparing unprofitable and profitable firms, 20

21 in For the crisis period, 2008, a significant difference concerning how often firms tend to draw funds from the credit lines can only be found when comparing unprofitable and profitable firms (1% test level). It is interesting to notice that the percentage of firms with an outstanding credit line at the end of the fiscal year increases for all types of companies from 2005 to However, only five out of these eight increases can be considered significant at a 5% test level. This indicates that, when the financial crisis hit the market, firms generally tended to more often take advantage of their available lines of credit. The average size of lines of credit, among different types of firms for the years 2005 and 2008, are presented in column 5 and 6, respectively. These columns reveal that small, unprofitable, bank dependent firms without an investment grade, thus firms which are more heavily constrained by credits, tend to have higher lines of credit to total asset ratios. The results are, for both years, significant at a 5% significance level when comparing the defined firm characteristics. These findings confirm the conclusion of Campello et al. (2010) that constrained firms have a larger proportion of credit lines to total assets. Moreover, the ratio of credit lines to total assets, tended to generally slightly increase from 2005 to However, only for small, bank dependent firms without an investment grade can this increase be considered significant at a 5% test level. The results of column 7 and 8 show that constrained firms on average drew considerably more funds from their lines of credit than unconstrained firms did. These results are significant at a 1% test level for all types of borrowers and for both investigated years. For example, in 2005, small firms with a line of credit drew on average down 21% of their available credit supplies while large firms on average drew down 11% of their revolving credit facility. Moreover, the drawdown ratio increased from 2005 to 2008 for all types of firms. The increases of these outstanding credit lines are significant at a 5% level, except when considering unprofitable firms Cash holdings and cash flow by firm characteristics Table 5, in the appendix, reports the result of the two-tailed mean comparison analysis for cash holdings and cash flow with respect to firm characteristics for the investigated time periods, 2005 and Column 1 and 2 report the level of cash holdings while controlling for different types of firms and by taking the entire sample into account, i.e. both firms with 21

22 and without a line of credit are included in the analysis. The results show that constrained firms (small, bank dependant, unprofitable companies without an S&P credit rating) hold significantly more cash on their hands than unconstrained firms (large, non-bank dependant, profitable companies with an S&P credit rating) during both the non-crisis and the crisis period. For example, bank dependent firms tend to have 21% and 19% higher cash holdings ratios than non-bank dependent companies during 2005 and 2008, respectively. These findings are consistent with the results of Almeida et al. (2004) and the conclusion of Opler et al. (1999) that unprofitable firms and companies without access to financial markets on average have a higher level of cash holdings. In column 3 and 4 is the level of cash holdings presented for the sample containing firms with access to line of credit for 2005 and 2008, respectively. Here it is also evident that small, bank dependent, unprofitable firms without an investment grade tend to have a higher cash holding ratio than larger, profitable firms with access to the financial markets. By comparing the complete sample with the sample of firms with a line of credit, it can be seen that companies with a credit line tend to have considerably lower cash holdings. For example, small firms from the complete sample, thus small firms with and without a line of credit, have an average cash holding ratio of 31% whereas when considering only small firms with access to a credit line, the average cash holding ratio is 18%. This indicates that there indeed is a substitution effect between cash holdings and lines of credit which is in line with the outcome of the study by Sufi (2009). It is also interesting to notice that in the crisis year, 2008, all types of firms decreased there level of cash holdings. However, only about half of these decreases can be considered significant at a 10% test level. Moreover, it can be seen that the difference between cash holdings of constrained and unconstrained firms generally decreased from 2005 to This suggests that constrained firms tended to use their cash saving to a larger extent than unconstrained firms did, when the financial crisis hit the markets and the liquidity dried up. The average cash flow conditional on company characteristics, for firms with and without lines of credit, is presented in column 5 and 6 for the years 2005 and 2008, respectively. As can be seen constrained firms tend to have negative EBITDA to total assets ratios whereas regular borrowers on average have positive cash flow ratios. The difference in cash flow of constrained and unconstrained firms is significant at a 1% test level, regardless 22

23 of which firm characteristics is taken into account. For example, small firms in 2005 are observed to have a negative cash flow ratio of 3% whereas large firms on average have a positive cash flow ratio of 15%. The cash flow ratios roughly stay the same from 2005 to 2008 when looking at different firm characteristics, only when analyzing unprofitable as well as profitable firms a slight but significant increase in cash flows can be noted. This is a bit surprising since it can be expected that revenues, hence cash flows would actually decrease in the crisis year. This suggests that firms still had enough cash savings and other liquid assets to support daily operations in The cash flow levels are likely to have decreased when the financial crisis continued to evolve. However, further research would be needed to investigate this matter. Column 7 and 8 report the cash flow results by firm characteristics of the sample, containing only firms with a line of credit, for the normal and the financially distressed period of time. These findings also show that constrained firms on average have significantly higher cash flows. In this sample positive cash flow ratios are found for all types of firms except for companies with a negative net income. Thus, by comparing the results for cash flow of the two samples it can be concluded that firms with a line of credit tend to, on average, have a higher level of cash flow. This is in line with the findings of existing literature and it suggests that a cash flow covenant is indeed often present in lines of credit agreements, as argued by Sufi (2009). 5.3 Correlation analysis The outcome of the correlation analysis for the key variables of this research is reported in table 6 which can be found in appendix. As can be seen the table the variables; lines of credit, cash holdings, cash flow, drawdowns, and working capital are included in the correlation matrix for the years 2005 and In both investigated years, lines of credit are significantly correlated with cash holdings, at a test level of 1%. Additionally, a negative correlation between cash holdings and drawdowns is found for the years 2005 and 2008, also significant at a 1% test level. The negative correlation between lines of credit and cash holdings and the negative relation between cash holdings and drawdowns are consistent with existing literature which suggests that firms substitute cash holdings with lines of credit and vise versa. Furthermore, credit lines are observed to be positively correlated with cash flows at 23

24 significance level of 1%, for both years of interest. Namely, in 2005 the relation between credit lines and cash flow is 0.26 while in 2008 the correlation in question is These positive relations confirm the conclusion of previous research that firms with a high level of cash flow can more easily obtain and sustain a line of credit. The decrease in correlation between lines of credit and cash flow from 2005 to 2008 could according to Sufi (2009) arise because firms with currently low cash flows or companies who expect a lower level of future cash flows might not consider lines of credit a viable substitute of liquidity. Working capital has positive and significant correlation with cash holdings, tested at a 1% significance level. This is in line with the statement of Bates et al. (2009) that cash savings and working capital are substitutes. Furthermore, lines of credit and working capital seems to be positively correlated. This positive relation is probably due to the fact that firms with a line of credit are at times required to keep a certain level of inventory and account receivable as collateral and that the total credit line commitment sometimes depends on the current level of the liquid assets. 5.4 Regression analysis In this part the results of the OLS regression analysis will be reported. The regressions were conducted to provide further insights of the liquidity management and the relation of the different liquidity variables, during normal and financially distressed times. First the relationship between lines of credit, cash holdings and cash flow will be discussed. The outcome of the relation between drawdowns, cash holdings and cash flow will follow. Then the results of the working capital analysis will be discussed. Finally, the findings of the subsample regressions, where the industry factor is taken into account, will be analyzed Regression analysis - Lines of credit, cash flow and cash holdings The outcome of the OLS regressions, which was carried out in order to investigate the relationship between lines of credit, cash flow and cash holdings, is presented in table 7 in the appendix. The dependent variable is line of credit and it follows its pre-specified definition, thus, credit lines are controlled by total assets and the regression is based on the complete sample (firms with and without lines of credit). The dependent variable is first regressed on cash flow, and then cash holdings are included in the regression. Finally, the interaction term between cash flow and cash holdings is added into the regression to check whether the two 24

25 internal liquidity sources have a joint effect on availability of credit lines. Firm characteristics are also taken into account in each regression. The sole effect of cash flow on the level of credit lines is displayed in column 1 and 4 for 2005 and 2008, respectively. The coefficient of cash flow is positive and significant at a test level of 1% for both investigated years, suggesting that cash flow has a positive effect on the level of credit lines. In column 2 and 5, cash savings are included in the regression, for 2005 and 2008, respectively. The results show that cash holdings have a negative effect on the level of credit lines. The coefficient is equal to for 2005, and for The coefficients can be considered significant at a 1% significance level. When the variable of cash holdings is included in the regression, the effect of cash flow on the availability of credit lines is still found to be positive, however, the cash flow coefficient has decreased and the effect can now only be considered significant in 2005, at a 5% test level. This change in magnitude of the cash flow coefficient indicates that there is indeed a joint effect between cash flow and cash savings and that there is a non-linear relationship between these liquidity variables. Thus, an interaction term is needed to isolate this effect, the results of such regression is discussed in following part. The results of the analysis where credit lines are regressed on cash flow, cash holdings and on the interaction term are reported in column 3 and 6 for the investigated years. This regression is expected to give the most accurate results since all these variables have an affect the availability of credit lines. Hence, the most emphasis should be paid to the results in column 3 and 6. Cash flow has a positive effect on the level of credit lines. The effect is a bit stronger during normal times. Namely, in 2005 the cash flow coefficient is equal to 0.19 compared to 0.14 in Cash holdings, on the other hand, have a negative effect on the level of credit line; in 2005 and in Thus, the strongest relation between cash savings and credit lines is found in the crisis period. The interaction term between cash flow and cash holdings also has a negative effect on the availability of lines of credit. Specifically, in 2005 the interaction term has a coefficient of while in 2008 the joint effect is a bit lower, i.e. 25

26 The coefficients of cash flow, cash holdings and of the interaction term can be considered significant at a 1% test level, for both 2005 and The positive relation between lines of credit and cash flow is consistent with existing literature that a positive and high level of cash flow helps secure a line of credit. Sufi (2009) also argued that this positive relationship could be a result of the frequent usage of cash flow covenants in lines of credit agreements. The negative effect of cash savings on revolving credit facilities supports the claim that firms with access to a credit line tend to hold less cash on their hands. This implies that cash holdings and lines of credit are indeed substitutes. That the interaction term is negative implies that when a firm lacks cash holdings, an increase in their cash flow will have a positive effect on their access to a line of credit. However, as cash savings increases, the positive effect of cash flow on the availability of credit lines is diminishing. These results confirm the findings of Campello et al. (2011) who concluded that lines of credit and cash flow are positively related when firms have low cash holdings Regression analysis Credit line size, cash flow and cash holdings The results of the analysis of the relation between lines of credit, cash flow and cash savings, conditional on having a credit line, is shown in table 8 (appendix). Thus, this analysis is based on the line of credit sample and therefore shows the effect of the liquidity variables on the size of the credit line. The OLS regression is made separately for 2005 and 2008, and firm characteristics are also taken into account. The findings of this investigation differ to some extent from the results of the previous regression where all firms were taken into account. Because, as can be seen in column 3 and 6, there is no significant relation between cash flow and lines of credit for both 2005 and Additionally, the interaction term can now be considered significant at 1% test level for 2005 and at a 10% significance level for The coefficient for cash holdings is however still positive and significant at a 1% test level for both investigated years, which again confirms the substitution effect between lines of credit and cash savings. Cash flow was in previous section concluded to have a positive effect on a firm s ability to secure a credit line. The results from this regression suggest, on the other hand, that cash flow does not have a significant effect on the size of credit lines. Thus, a certain level of cash flow can be essential when obtaining a line of credit agreement, however, an increase in cash flow does not generally result in a change of the credit line size. 26

27 The only firm characteristic which has a small but significant effect on the level of credit lines is large firms, i.e. firm with sales over $1 billion. Large firms are found to have a negative effect on the size of credit lines which can be explained by the fact that small firms with credit constraints tend to have a larger portion of credit lines to total assets (Campello et al., 2011) Regression analysis - Drawdowns, cash flow and cash holding Firms with high cash flows and large cash savings are expected to draw fewer funds from their lines of credits than firms with a low level of internal liquidity (Campello et al., 2011). The regression, presented in table 9, in the appendix, investigates this matter while controlling for firm characteristics. The dependent variable is drawdowns which is the outstanding loan to total line of credit commitment. Column 1 to 3 report the results for 2005 while column 4 to 6 show the findings of The table shows that cash flow and cash holdings have a negative effect on the level of drawdowns. Thus, companies with a high level of internal liquidity tend to draw less credit from their lines of credit. This conclusion is in the line with the findings of previously conducted research. In 2005, the coefficient of cash flow and cash holdings, can be consider significant at a 1% test level while the interaction term can only be classified as significant at a 5% significance level, as shown in column 3. For 2008, only the cash holdings coefficient and the interaction term can be classified as significant, at a 1% and 5% test level, respectively, as column 6 shows. By comparing column 3 and 6, thus, by looking at the relation of internal liquidity on drawdowns before and during the crisis, it can be seen that the negative effect of cash flow is larger and only significant before the crisis whereas the negative effect of cash holding is larger during the financially distressed times. The effect of the interaction term on drawdowns also slightly increases during This indicate that during the financial crisis, the level of cash flow did not affect the drawdown activity but the substitution effect, on the other hand, between lines of credit and cash holdings became even stronger. The increase of the substitution effect during the crisis makes sense from a cost saving perspective; firms will avoid drawing funds as long as they have cash savings in order to avoid interest payments on their borrowings. Regarding the effect of firm characteristics on the level of drawdowns, column 3 reports that large and profitable firms have a negative effect on the level of drawdowns in 2005 and that these results are significant at a 5% and 1% test level, respectively. In 2008, the 27

28 only firm characteristic which is considered significant at a 1% test level is profitability. Namely, both inside and outside the crisis profitable firms seem to draw fewer funds from their credit lines. A potential explanation of this negative profitability effect on drawdowns is that firms with a positive net income might have a lower need of external liquidity since they are likely to expect an increase in their level of cash flow and thus their level of cash holdings Regression analysis Working capital as additional source of liquidity Working capital is an additional source of liquidity which has often been neglected in previous studies. To shield some light on the relation between working capital and the other liquidity sources, two different OLS regressions were carried out. Table 10, in the appendix, shows the results of the OLS analysis where the ratio of credit lines to total assets is the dependent variable. The line of credit variable is regressed on the internal liquidity sources, including the working capital parameters. The included working capital factors are accounts receivable, inventory and accounts payable. An interaction term of the working capital parameters (current assets multiplied by current liabilities) is also taken into account, reported in column 2 and 4, for 2005 and 2008, respectively. However, the coefficient of the interaction term is considered non-significant at a 10% test level. Thus, there seems to be no significant joint effect of current assets and current liabilities on the level of credit lines. Furthermore, including the factors of working capital do not affect the conclusions previously drawn, namely, that cash flow are positively related to the availability of credit lines, at least when firms have low cash savings, and that cash savings and lines of credit tend to act as substitutes. As table 10 shows, accounts payable has a small negative effect on the level of credit lines. This effect can, however, only be classified as significant in 2005 (1% test level). The current assets; account receivable and level of inventory have a positive effect on the access of lines of credit. The positive effect can be considered significant at a 1% test level for both 2005 and Thus, these findings suggest that having a high level of working capital could facilitate the access of credit lines and the results also indicate that firms are often required to keep a certain level of liquid assets (accounts receivable and inventory) on their balance sheet. The effect of accounts receivable on the level of lines of credit is largest during the non-crisis period whereas the inventory level has a stronger effect on the availability of credit lines during the crisis. This finding could be explained by the fact that firms generally had more difficulties meeting their accounts payable obligations during the financial crisis. Hence, actually collecting an accounts receivable became more uncertain as the credit crisis 28

29 evolved. If credit line lenders realized this, it is likely that they adjusted the conditions of their credit facilities. For example, they could request a higher level of inventory as collateral, since this is a current asset on hand. Thus, the value is secure, unlike the value of accounts receivable. The results, shown in table 11 (appendix), report the effect of lines of credit and firm characteristics on the level of working capital. The dependent variable is working capital defined as; accounts receivable plus inventory minus accounts payable while controlling for total assets. Working capital is regressed on cash flow, cash holdings, their interaction, lines of credit and firm characteristics. Both 2005 and 2008 are investigated. When comparing the results of the non-crisis period with the crisis period, it can be seen that the findings are diverging. Specially, in 2005, none of the included variables have a significant effect on the level of working capital. However, in 2008, the line of credit coefficient is equal to 0.19 and is classified as significant at 1% test level. Yet again, a positive relation between working capital and lines of credit is found. Cash holdings have a coefficient equal to 0.22 in 2005 and in 2008, thus opposite effects before and during the crisis were found. However, only the effect of cash savings on the level of working capital in 2008 can be considered significant (1% test level). This indicates that during the credit crunch firms with higher cash holdings tended to hold lower levels of working capital. Thus, cash holdings and working capital can during the crisis be considered substitutes, which is in line with the argument of Bates (2009) that cash savings and working capital are both liquid assets and are therefore substitutes. Large and non-bank dependent firms seem to have a negative effect on the level of working capital during the crisis period. Their coefficients are in 2008, and -0.07, respectively, and the effect is considered significant at a 1% test level. The other firm characteristics, hence, investment grade and profitable indicate a positive effect on the level of working capital, however, this effect cannot be considered significant at 10% test level. Thus, small and bank dependent firms seem to have higher working capital levels than large and non-bank depend companies. These results can arise since small and bank dependent firms are credit constrained companies. Thus, they are likely to keep a higher level of working capital as a buffer for future capital expenditures when external liquidity is limited and very expensive. It seems that managing the level of working capital is more essential during 29

30 economic downturns than during normal time, this is consistent with the findings of Enqvist et al. (2012) Regression analysis Subsample In order to investigate whether the liquidity management diverge among various manufacturing industries the sample was divided, based on their SIC codes, into different manufacturing sectors, as can be seen in table 12 in the appendix. The six divisions with the most observations were included in the subsample analysis. The results of the regressions of credit lines on cash flow and cash savings while controlling for industry and firm characteristics are presented in table 13 and 14, for 2005 and 2008, respectively. The tables, which can be found in the appendix, confirm previous results of this research, namely that cash flow generally has a positive effect on the availability of credit lines and cash holdings have, on the contrary, a negative effect. The industry effect, on the level of credit lines, diverges among the sectors. However, the only division that has a significant effect in 2005 is the Industrial Machinery & Equipment industry, which has a positive effect equal to 0.02 (5% significance level), as shown in table 13. The firms included in this division are firms with high investment costs. Therefore, they might have a higher level of credit line commitments to total assets, since the credit lines can be used to finance their capital expenditures. In 2005, the dummy variable controlling for firm size has a negative and significant coefficient at a 5% test level for all included manufacturing sectors. Thus, during the non-crisis periods the large firms within these industries tend to hold smaller proportions of credit lines to total assets than small firms. In 2008, on the other hand, none of the firm characteristics have a significant effect. However, the manufacturing industry of Chemical and Allied Products has a significant negative effect on the level of credit lines (5% test level), as shown in table 14. Thus, firms that produce chemical and allied products such as drugs and other pharmaceuticals tend to have a lower level of credit lines to total assets than manufacturing firms from other sectors. The results of the subsample analysis where the relationship between drawdowns and internal liquidity is investigated conditional on industry and firm characteristics, is reported in table 15 and 16 for the non-crisis and crisis period, respectively. The tables can be found in the appendix. From the tables it can be concluded that the findings concerning the relation between drawdowns and cash flow and cash holdings confirm previous results, hence, that 30

31 firms with a higher level of internal liquidity tend to draw a smaller proportion of funds from their available lines of credit. In 2005, as table 15 shows, the industry effect cannot be considered significant at a 10% level for any of the included sectors. However, during the crisis period, it appears that firms which produce food and kindred products tend to draw fewer funds from their lines of credit. Namely, the coefficient of the dummy variable controlling for firms that produce food and kindred products is, in 2008, equal to and can be classified as significant at a 1% test level. The food market is not a very sensitive market to changes of the economic environment, since everyone priorities to purchase provisions. Therefore, it can be expected that these food producing companies are less heavily affected by a financial crisis compared to other manufacturing firms. Thus, this could explain why these firms tend to draw a smaller proportion of fund from their revolving credit facilities during the financial turmoil. For both 2005 and 2008, the coefficient controlling for profitability is considered significant at a 1% test level for all included manufacturing divisions. Thus, manufacturing firms which have a positive net income tend to draw fewer funds from their credit lines which might be because they can use their net income to meet financial obligations and to finance some investments. 5.5 Covenants analysis In this part the results for the investigation of the usage of covenants before and during the financial crisis will be presented and discussed. Table 17, which can be found in the appendix, reports the outcome of the two-tailed mean difference test for the different covenants included in this research. Column 1 shows the results of 2005 while column 2 displays the findings for As can be seen in the table, in 2005, 41.92% of the credit line agreements included a restriction on the level of leverage whereas in 2008 the percentage of revolving credit facilities with a leverage covenant had increased to 47.46%. Dividend covenants also appear to be commonly present in the credit line agreements. Namely, 43.43% and 39.55% of the firms with a line of credit are found to have a dividend restriction in 2005 and 2008, respectively. Here it is interesting to note that the percentage of dividend covenants in the line of credit agreements actually has decreased from 2005 to However, the decrease cannot be considered significant at a 10% test level. The restrictions on investments, hence the level of capital expenditures, are present in 31.31% of the line of credit contracts in 2005, while in 2008 this number is a bit higher, i.e %. Also the percentage of credit line agreements with a restriction on the disposal of a firm s asset is the highest during the financial crisis. 31

32 The percentage of firms with a line of credit which is restricted by an M&A clause, have the highest increase from 2005 to Namely, 8.23% more of agreements contains a restriction for engaging in mergers and to make acquisitions during the financial crisis. This increase, from the non-crisis to the crisis period, is the only one that can be considered significant at a 10% test level. The covenant concerning the redemption of the company s capital stock is not very common, namely, it appears in 15.66% of the investigated credit lines agreements in 2005 and slight more often in 2008, i.e %. When comparing the non-crisis period with the crisis period it can be concluded that the overall usage of covenants increased during the financial crisis, which was expected. Because during this uncertain time the lenders wanted to mitigate the risk of not retrieving the funds they lend out and this was achieved by including more covenants in the lines of credit agreement. It can also be concluded that the most common covenants in the lines of credit agreements are, during normal and during financially distressed times, restrictions on the total leverage ratio and on the distribution of dividends. Thus, the providers of the credit lines seem to consider the level of total leverage and dividends to be crucial to the retrieval of the credit that they have lent out. This is no surprise, since if the leverage ratio increases or additional loans are taken this will diminish the company s ability to meet all its financial obligations, thus the risk of default of the credit lines increases. Additionally, it was expected that dividend restrictions would often be imposed on the credit line borrowers. Because, as discussed in the literature review, if dividend distributions are financed by a decrease in a company s capital expenditures (investments), it will reduce the expected firm value and hence this would increase the likelihood of credit line default. Moreover, the most significant increase of the usage of a certain covenant in the revolving credit agreements, before and during the financial crisis, was the restriction on M&A. An explanation for this high increase of the M&A clause can be that credit lines providers wanted to ensure that the firms did not engage in mergers or that they did not make acquisition that were too risky, during the crisis. Thus, the credit lines providers wanted to make sure the borrowers did not take, from the lenders perspective, inefficient strategic decisions. Because during a credit crisis, when many firms experience severe financial distress, they tend to take higher risks, such as engaging in uncertain M&A and if the M&A were unsuccessful, this could have devastating results for the credit line providers, who might not be able to retrieve the funds that they lent. 32

33 This research will not be able to conclude whether the covenants are also set tighter during the financial crisis since, as previously mentioned, the covenant data of this study only indicates whether a firm is restricted by a certain line of credit covenant. Hence, the covenant data does not indicate the level of the restrictions. This is an interesting topic for future research, namely to investigate how the financial crisis affected the levels of the credit lines restrictions. 6 Conclusion The results of this study conclude that lines of credit are an important part of liquidity management, which confirms the findings of Sufi (2009). Liquidity management is the practice of ensuring that firms have enough cash or cash equivalents to support daily operations and to fund investment projects. During a financial crisis, when there is scarcity of funds and unstable conditions on the financial markets, efficient liquidity management is concluded to be even more crucial and that an available line of credit tend to ease the effects of a credit crunch. Large, profitable, non-bank dependent companies with an investment grade are defined as financially unconstrained firms whereas small, unprofitable, bank dependent firms without an investment grade are classified as constrained companies. The results show that unconstrained firm have a greater access to lines of credit compared to financially constrained firms, this is in line with the evidence of existing literature (Campello et al., 2011). Constrained firms are signified by having unstable cash flows and therefore have a higher demand for a buffer of cash holdings or other liquidity sources. The mean comparison analysis performed in this study confirms this, namely, that firms which are more heavily constrained by credits, tend to have lower cash flow ratios and higher cash holdings and lines of credit ratios. This research paper s findings also confirm the results of Campello et al. (2011) that lines of credit and cash flow are positively related for firms with low cash savings, and as cash holdings increases the positive effect between credit lines and cash flow diminishes. Additionally, this study finds that credit lines and cash holdings are negatively related, hence suggesting that they are substitutes, which is in line with study of Sufi (2009) who found that firms with a high level of cash flows consider credit lines a viable substitute of cash savings. Cash flows are in this research paper concluded to have no significant effect on the size of 33

34 credit lines. Thus, a certain level of cash flow can be essential when obtaining a line of credit agreement, however, an increase in cash flow level does not generally result in a change of the credit line size. The proportions of drawdowns are concluded to be larger among firms with a low level of internal funds, which is also consistent with the findings of previous studies. Additionally, more drawdowns occurred during 2008 compared to 2005, which indicates that firms took more advantage of their lines of credit during the financial crisis. Thus, the access to credit lines seems to have eased the effects of the credit crisis. Working capital, which is an additional liquidity source, is found to be positively related to lines of credit and firms with a current line of credit are found to have, on average, a considerably higher level of working capital compared to companies without an available line of credit. This positive relation between working capital and credit facilities is most likely due to the fact that credit line providers require borrowers to keep a certain level of accounts receivable and inventory on their balance sheet. Working capital and cash holdings are, on the other hand, found to be significantly negatively correlated at a 1% test level during the year of the financial crisis. This is in line with the conclusion of Bates (2009) which states that cash savings and working capital are both liquid assets and can therefore be considered substitutes. Small and bank dependent firm are found to have significantly higher working capital levels compared to large and non-bank depend companies, during the financial turmoil. Small and bank dependent firms are companies with financial constraints and are thus more likely to keep a higher level of working capital as a buffer for future capital expenditures, when external liquidity is scarce. The results of the subsample analysis, where the relationships between the liquidity variables are investigated while paying special attention to the manufacturing industry effect, show that the liquidity management are to some extent different among various manufacturing divisions. However, the coefficients of the dummy variable controlling for the industry effects can mostly not be considered significant at a 10% level. Although, for example, during the crisis year it is found that firms which produces food and related products tend to draw significantly fewer funds from their lines of credits. An explanation of this is that these firms are less affected by the financial crisis, since the demand for their products is relatively stable. 34

35 The usage of lines of credit covenants seems to be slightly higher during the crisis period compared to the time of normal economic circumstances. However, the covenant increase can only be considered significant at 10% test level for the M&A clause. Hence, during the financial crisis significantly more credit lines providers restrict their borrowers from engaging in mergers or making acquisitions. The two most commonly present covenants during both investigated time periods are a restriction on total leverage and on the distribution of dividends. Thus, the providers of revolving credit facilities seem to consider these covenants crucial to the retrieval of the funds that they have lent out. This research papers has provided new insights and evidence of how a financial crisis affects corporate liquidity management among different industries. However, further research is still recommended to broaden the scope of this interesting field of study. For example, future studies are recommended to increase the event window, since it would be interesting to see how the liquidity management changed for each year before the financial crisis and as the crisis continued to evolve. Moreover, increasing the diversity of the types of firms which are included in the industry analysis is recommended, because this would give further insight on how liquidity management differs among various industries. Furthermore, in order to investigate whether the lenders tightened the line of credit restrictions during the financial crisis, additional research concerning the usage of covenants is also recommended. 35

36 Bibliography Agarwal, S., Chomsisengphet, S., & Driscoll, J. (2004) Loan Commitments and Private Firms. Working Paper, FleetBoston Financial, Office of Federal Housing Enterprise Oversight and Federal Reserve Board. Almeida, H., & Campello, M. (2010) Financing Frictions and the Substitution Between Internal and External Funds. Journal of Financial and Quantitative Analysis, 45, pp Almeida, H., Campello, M., & Weisbach, M. S. (2004) The Cash Flow Sensitivity of Cash. The Journal of Finance, Vol. LIX, No. 4. Bates, T., Kahle, K., & Stulz, R. (2009) Why Do U.S. Firms Hold so Much More Cash Than They Used To? The Journal of Finance, Vol. LXIV, No. 5. Braun, M. & Larrain, B. (2005) Finance and the business cycle: International, inter-industry evidence. Journal of Finance, 60, pp Campello, M., Giambona, E., Graham, J. R., & Harvey, C. (2011) Liquidity Management and Corporate Investment During a Financial Crisis. Working paper, University of Illinois, University of Amsterdam and Duke University. Campello, M., Graham, J. R., & Harvey, C. (2010) The Real Effects of Financial Constraints: Evidence from a Financial Crisis. Journal of Financial Economics, 97, pp Chari, V. V., Christiano, L. J., & Kehoe, P. J. (2008) Facts and myths about the financial crisis of Working paper, Federal Reserve Bank of Minneapolis. Chava, S., & Roberts, M. R. (2008) How Does Financing Impact Investment? The Role of Debt Covenants. The Journal of Finance, Vol. LXIII, No. 5. Cornett, M. M., McNutt, J. J., Strahan, P. E., & Tehranian, H. (2011) Liquidity risk management and credit supply in the financial crisis. Journal of Financial Economics, 101, pp

37 Demiroglu, C., & James, C. (2011) The Use of Bank Lines of Credit in Corporate Liquidity Management: A review of empirical evidence. Journal of Banking and Finance, 35, pp Denis, D. J., Sibilkov, V. (2010) Financial Constraints, Investments, and the Value of Cash Holdings. Review of Financial Studies, Vol. 23, No. 1. Enqvist, J., Graham, M., & Nikkinen, J. (2012) The impact of working capital management on firm profit ability in different business cycles: evidence from Finland. Working paper, Nordea Bank, Royal Melbourne Institute of Technology University and University of Vaasa. Fazzari, S. M., & Petersen, B. C. (1993) Working Capital and Fixed Investment: New Evidence on Financing Constraints. The RAND Journal of Economics, Vol. 24, No. 3. Gao, P., & Yun, H. (2009) Commercial Paper, Lines of Credit, and the Real Effects of the Financial Crisis of 2008: Firm-Level Evidence from the Manufacturing Industry. Working paper, University of Notre Dame. Huang, R. (2010) How committed are bank lines of credit? Experiences in the subprime mortgage crisis. Working paper, Federal Reserve Bank of Philadelphia. Ivashina, V., & Scharfstein, D. (2010) Bank Lending During the Financial Crisis of Journal of Financial Economics, 97, pp Korajczyk, R. A., & Levy, A. (2003) Capital structure choice: macroeconomic conditions and financial constraints. Journal of Financial Economics, 68, pp Lins, K., Servaes, H., & Tufano, P. (2010) What drives corporate liquidity? An international survey of cash holdings and lines of credit, Journal of Financial Economics, 98, pp Opler, T., Pilkowitz, L., Stulz, R., & Williamson, R. (1999) The Determinants and Implications of Corporate Cash Holdings, Journal of Financial Economics, 52, pp

38 PricewaterhouseCoopers. (2009). European Working Capital Study Smith, C. W. Jr., & Warner, J. B. (1979) On Financial Contracting, An Analysis of Bond Covenants, Journal of Financial Economics, 7, pp Sufi, A. (2009) Bank Lines of Credit in Corporate Finance: An Empirical Analysis. Review of Financial Studies, 22, pp

39 Appendix Table 3. Descriptive Statistics Variable Sample Year Mean 25 pct. 50 pct. 75 pct. Std. Dev. N Percentage of firms with a LC Complete Percentage of firms with a LC Complete Line of credit Firms with a line of credit Line of credit Firms with a line of credit Drawdowns Firms with a line of credit Drawdowns Firms with a line of credit Cash holdings Firms with a line of credit Cash holdings Firms without a line of credit Cash holdings Firms with a line of credit Cash holdings Firms without a line of credit Cash flow Firms with a line of credit Cash flow Firms without a line of credit Cash flow Firms with a line of credit Cash flow Firms without a line of credit Working capital Firms with a line of credit Working capital Firms without a line of credit Working capital Firms with a line of credit Working capital Firms without a line of credit Large Firms with a line of credit Large Firms without a line of credit Large Firms with a line of credit Large Firms without a line of credit Non-bank dependent Firms with a line of credit Non-bank dependent Firms without a line of credit Non-bank dependent Firms with a line of credit Non-bank dependent Firms without a line of credit Investment grade Firms with a line of credit Investment grade Firms without a line of credit Investment grade Firms with a line of credit Investment grade Firms without a line of credit Profitable Firms with a line of credit Profitable Firms without a line of credit Profitable Firms with a line of credit Profitable Firms without a line of credit Table 3 reports the summary statistics of the main variables. This paper s dataset is collected by manually assessing SEC filings and additional financial information is obtained from the database Compustat. The data contains information of US non-financial public firms for the years 2005 and Line of credit refers to total line of credit commitment to total assets. Drawdowns represents outstanding loan to total line of credit commitment. Cash holdings measures cash and marketable securities to total assets. Cash flow is EBITDA to total assets. Working capital refers to accounts receivable plus inventory minus accounts payable, controlled by total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. 39

40 Table 4. Lines of credit and drawdowns by firm characteristics Firms with a line of credit (% of total firms) Firms with a drawdown (% of total LC firms) Complete sample Line of credit sample (1) (2) (3) (4) Diff Diff Small 59.76% 59.89% -0.13% 49.42% 52.15% -2.73% Large 91.34% 93.89% -2.55% 41.76% 53.36% %*** Diff small - large %*** %*** 7.66%*** -1.21% Bank dependent 58.77% 60.77% -2.00% 48.16% 52.93% -4.77%** Non-bank dependent 93.63% 96.04% -2.41%* 44.89% 51.94% -7.05%** Diff bank dep. - non-bank dep %*** %*** 3.27% 0.99% Non-investment grade 59.25% 61.15% -1.90% 48.68% 53.31% -4.63%** Investment grade 93.36% 95.91% -2.55%* 43.56% 51.13% -7.57%** Diff non-inv. - inv %*** %*** 5.12%* 2.18% Unprofitable 47.69% 58.63% %*** 58.76% 62.10% -3.34% Profitable 79.95% 79.01% 0.94% 42.27% 46.19% -3.92% Diff unprofit. - profit %*** %*** 16.49%*** 15.91%*** Line of credit (% of total assets) Drawdowns (% of total credit line) Line of credit sample Line of credit sample (5) (6) (7) (8) Diff Diff Small 19.85% 21.36% -1.51%** 21.10% 24.07% -2.97%** Large 15.14% 16.21% -1.07% 10.51% 17.79% -7.28%*** Diff small - large 4.71%*** 5.15%*** 10.59%*** 6.28%*** Bank dependent 19.49% 21.15% -1.66%** 21.03% 24.13% -3.10%** Non-bank dependent 16.17% 16.01% 0.16% 11.26% 16.92% -5.66%*** Diff bank dep. - non-bank dep. 3.32%*** 5.14%*** 9.77%*** 7.21%*** Non-investment grade 19.54% 21.09% -1.55%** 21.13% 24.25% -3.12%** Investment grade 15.92% 15.99% -0.07% 10.60% 16.45% -5.85%*** Diff non-inv. - inv. 3.62%*** 5.10%*** 10.53%*** 7.80%*** Unprofitable 19.62% 20.67% -1.05% 28.06% 30.21% -2.15% Profitable 17.94% 18.59% -0.65% 13.69% 15.98% -2.29%** Diff unprofit. - profit. 1.68%** 2.08%** 14.37%*** 14.23%*** Table 4 reports the results of a two-tailed mean difference analysis, where liquidity sources are taken into account while controlling for firm characteristics. Complete sample means that all firms are included in the test. Lines of credit sample indicates that only firms with a reported line of credit at the end of the fiscal year are taken into account. Firms with a line of credit refer to the percentage of companies will a valid line of credit reported at the end of the fiscal year. Firms with a drawdown represent the proportion of firms with an outstanding amount of credit at the end of the fiscal year. Line of credit is total line of credit commitment to total assets. Drawdowns measures outstanding loan to total line of credit commitment. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 40

41 Table 5. Cash holdings and cash flow by firm characteristics Cash holdings (% of total assets) Cash holdings (% of total assets) Complete sample Line of credit sample (1) (2) (3) (4) Diff Diff Small 30.74% 28.92% 1.82%* 18.10% 17.42% 0.68% Large 12.18% 10.86% 1.32%* 10.55% 9.71% 0.84% Diff small-large 18.56%*** 18.06%*** 7.55%*** 7.71%*** Bank dependent 31.49% 28.44% 3.05%*** 19.06% 17.37% 1.69%* Non-bank dependent 10.23% 9.73% 0.50% 8.93% 8.91% 0.02% Diff bank dep. - non-bank dep %*** 18.71%*** 10.13%*** 8.46%*** Non-investment grade 31.17% 28.29% 2.88%*** 18.76% 17.29% 1.47% Investment grade 10.50% 9.64% 0.86% 9.16% 8.79% 0.37% Diff non-inv. - inv %*** 18.65%*** 9.60%*** 8.50%*** Unprofitable 36.73% 29.90% 6.83%*** 18.82% 16.47% 2.35%* Profitable 19.64% 18.48% 1.16% 14.58% 13.22% 1.36%* Diff unprofit. - profit %*** 11.42%*** 4.24%*** 3.25%*** Cash flow (% of total assets) Cash flow (% of total assets) Complete sample Line of credit sample (5) (6) (7) (8) Diff Diff Small -3.39% -3.75% 0.36% 6.15% 4.07% 2.08%** Large 14.95% 14.81% 0.14% 14.77% 14.83% -0.06% Diff small - large %*** 18.56%*** -8.62%*** %*** Bank dependent -3.24% -2.71% -0.53% 6.30% 4.98% 1.32% Non-bank dependent 13.80% 14.21% -0.41% 13.94% 14.29% -0.35% Diff bank dep. - non-bank dep %*** %*** -7.64%*** -9.31%*** Non-investment grade -3.12% -2.64% -0.48% 6.32% 4.97% 1.35% Investment grade 14.07% 14.53% -0.46% 14.24% 14.63% -0.39% Diff non-inv. - inv %*** %*** -7.92%*** -9.66%*** Unprofitable % % -5.23%*** -6.82% -3.61% -3.21%** Profitable 14.72% 15.66% -0.94%** 15.22% 16.02% -0.80%* Diff unprofit. - profit %*** %*** %*** %*** Table 5 reports the results of a two-tailed mean difference analysis, where liquidity sources are taken into account while controlling for firm characteristics. Complete sample means that all firms are included in the test. Lines of credit sample indicates that only firms with a reported line of credit at the end of the fiscal year are taken into account. Cash holdings measures cash and marketable securities to total assets. Cash flow refers to EBITDA to total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Nonbank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 41

42 Table 6. Correlation analysis 2005 Line of credit Cash holdings Cash flow Drawdowns Working capital Line of credit 1 Cash holdings *** 1 Cash flow 0.257*** *** 1 Drawdowns 0.383*** *** Working capital 0.389*** *** 0.412*** 0.219*** Line of credit Cash holdings Cash flow Drawdowns Working capital Line of credit 1 Cash holdings *** 1 Cash flow 0.186*** *** 1 Drawdowns 0.403*** *** Working capital 0.314*** *** 0.333*** 0.156*** 1 Table 6 reports the correlation between the main variables of this study for 2005 and Line of credit refers to total line of credit commitment to total assets. Cash holdings measures cash and marketable securities to total assets. Cash flow is EBITDA to total assets. Drawdowns represents outstanding loan to total line of credit commitment. Working capital refers to accounts receivable plus inventory minus accounts payable, controlled by total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Nonbank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 42

43 Table 7. OLS regression analysis - Relationship between lines of credit, cash holdings and cash flow Dependent variable Line of credit (% of total assets) Line of credit (% of total assets) Complete sample Complete sample (1) (2) (3) (4) (5) (6) Cash Flow 0.136*** 0.035** 0.186*** 0.121*** *** (8.22) (2.05) (6.32) (6.72) (0.87) (4.15) Cash Holdings *** *** *** *** (-17.64) (-21.14) (-18.34) (-20.30) Cash Flow * Cash Holdings *** *** (-8.37) (-5.86) Firm characteristics Large *** *** *** ** (-2.61) (-3.46) (-3.88) (0.06) (-1.48) (-2.03) Non-bank dependent 0.093*** (2.97) (1.52) (1.08) (0.69) (0.03) (-0.15) Investment grade ** (-2.11) (-1.45) (-1.33) (-0.52) (-0.47) (-0.52) Profitable (0.70) (1.26) (0.38) (-1.28) (-0.42) (-1.38) Constant 0.118*** 0.180*** 0.185*** 0.137*** 0.208*** 0.215*** (18.97) (24.03) (25.08) (20.94) (25.08) (26.04) Sample size R² Table 7 reports the results of the OLS regression where the relation between lines of credit and internal liquidity sources are investigated while controlling for firm characteristics. Columns (1) to (3) show the findings for 2005 whereas columns (4) to (6) report the results for Complete sample means that all firms are included in the regression. Line of credit represents total line of credit commitment to total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (twotailed t-statistics). 43

44 Table 8. OLS regression analysis - Relationship between credit line size, cash holdings and cash flow Dependent variable Line of credit (% of total assets) Line of credit (% of total assets) Line of credit sample Line of credit sample (1) (2) (3) (4) (5) (6) Cash Flow *** (0.61) (-1.41) (1.58) (-0.93) (-3.00) (-0.66) Cash Holdings *** *** *** *** (-8.06) (-8.76) (-10.08) (-10.12) Cash Flow * Cash Holdings *** * (-3.92) (-1.92) Firm characteristics Large *** *** *** *** *** *** (-4.18) (-4.41) (-4.54) (-2.48) (-3.07) (-3.15) Non-bank dependent (0.58) (-0.21) (-0.36) (-0.88) (-1.13) (-1.21) Investment grade (-0.87) (-0.55) (-0.57) (0.19) (0.04) (0.03) Profitable (-1.03) (-0.18) (-0.58) (-0.54) (0.27) (-0.05) Constant 0.205*** 0.241*** 0.237*** 0.220*** 0.266*** 0.266*** (25.31) (26.54) (25.64) (28.14) (27.34) (27.27) Sample size R² Table 8 reports the results of the OLS regression where the relation between credit line size and internal liquidity sources are investigated while controlling for firm characteristics. Columns (1) to (3) show the findings for 2005 whereas columns (4) to (6) report the results for Lines of credit sample indicates that only firms with a reported line of credit at the end of the fiscal year are taken into account. Line of credit is the dependent variable and represents total line of credit commitment to total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t- statistics). 44

45 Table 9. OLS regression analysis - Relationship between drawdowns, cash holdings and cash flow Dependent variable Drawdowns (% of total credit line) Line of credit sample Drawdowns (% of total credit line) Line of credit sample (1) (2) (3) (4) (5) (6) Cash Flow *** *** ** *** *** (-3.84) (-5.82) (-2.41) (-2.85) (-4.21) (-1.34) Cash Holdings *** *** *** *** (-6.84) (-7.45) (-7.35) (-8.19) Cash Flow * Cash Holdings ** ** (-2.24) (-2.26) Firm characteristics Large * ** ** (-1.92) (-2.03) (-2.08) (0.57) (0.08) (-0.06) Non-bank dependent (0.18) (-0.46) (-0.53) (0.13) (-0.00) (-0.07) Investment grade (-0.98) (-0.72) (-0.73) (-0.74) (-0.89) (-0.90) Profitable *** *** *** *** *** *** (-3.83) (-3.23) (-3.43) (-5.03) (-4.39) (-4.72) Constant 0.280*** 0.338*** 0.335*** 0.305*** 0.379*** 0.379*** (17.46) (18.93) (18.41) (19.27) (20.17) (20.17) Sample size R² Table 9 reports the results of the OLS regression where the relation between drawdowns and internal liquidity sources are investigated while controlling for firm characteristics. Columns (1) to (3) show the findings for 2005 whereas columns (4) to (6) report the results for Lines of credit sample indicates that only firms with a reported line of credit at the end of the fiscal year are taken into account. Drawdowns is the dependent variable and represents outstanding loan to total line of credit commitment. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (twotailed t-statistics). 45

46 Table 10. OLS regression analysis - Relationship between lines of credit and working capital Dependent variable Line of credit (% of total assets) Line of credit (% of total assets) Complete sample Complete sample (1) (2) (3) (4) Cash Flow 0.166*** 0.166*** 0.120*** 0.120*** (5.64) (5.49) (3.43) (3.43) Cash Holdings *** *** *** *** (-12.46) (-12.42) (-11.21) (-11.13) Cash Flow * Cash Holdings *** *** *** *** (-8.19) (-8.12) (-5.41) (-5.41) Working capital Accounts receivable 0.187*** 0.192*** 0.149*** 0.137** (4.65) (5.06) (3.07) (2.31) Inventory 0.193*** 0.185*** 0.224*** 0.211*** (5.88) (3.88) (5.42) (4.30) Accounts payable *** *** (-9.45) (-9.45) (-0.33) (-0.65) Current assets*current liabilities Firm characteristics Large *** *** (-2.99) (-2.96) (-1.03) (-1.03) Non-bank dependent (0.76) (0.77) (0.17) (0.18) Investment grade (-0.42) (-0.43) (-0.41) (-0.43) Profitable (-0.32) (-0.31) (-1.54) (-1.49) Constant 0.107*** 0.107*** 0.137*** 0.140*** (9.91) (9.56) (9.31) (8.68) Sample size R² Table 10 reports the results of the OLS regression where the relation between credit lines and working capital is investigated. Columns (1) and (2) show the findings for 2005 whereas columns (3) and (4) report the results for Complete sample means that all firms are included in the regression. Line of credit is the dependent variable and represents total line of credit commitment to total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Current assets refer to accounts receivable and inventory. Current liabilities represent accounts payable. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 46

47 Table 11. OLS regression analysis - Relationship between working capital and liquidity sources Dependent variable Working capital Working capital (% of total assets) (% of total assets) Complete sample Complete sample (1) (2) Cash Flow *** (-0.59) (4.34) Cash Holdings *** (0.47) (-9.30) Cash Flow * Cash Holdings ** (0.92) (-2.56) Line of credit *** (1.35) (5.06) Firm characteristics Large *** (-0.01) (-5.85) Non-bank dependent ** (0.80) (-1.93) Investment grade (-1.15) (0.19) Profitable (1.11) (1.47) Constant *** (-0.36) (16.29) Sample size R² Table 11 reports the results of the OLS regression where the relation between working capital and other liquidity sources are investigated. Column (1) shows the findings for 2005 whereas column (2) reports the results for Complete sample means that all firms are included in the regression. Working capital is the dependent variable and is defines as; accounts receivable plus inventory minus accounts payable while controlling for total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Line of credit represents total line of credit commitment to total assets. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 47

48 Table 12. Manufacturing industries Manufacturing divisions Obs. Manufacturing divisions Obs. Food and Kindred Products 94 Food and Kindred Products 84 Tobacco Products 6 Tobacco Products 3 Textile Mill Products 17 Textile Mill Products 11 Apparel and Other Textile Products 44 Apparel and Other Textile Products 32 Lumber and Wood Products 20 Lumber and Wood Products 17 Furniture and Fixtures 24 Furniture and Fixtures 19 Paper and Allied Products 38 Paper and Allied Products 39 Printing and Publishing 61 Printing and Publishing 38 Chemicals and Allied Products 497 Chemicals and Allied Products 376 Petroleum and Coal Products 25 Petroleum and Coal Products 23 Rubber and Misc. Plastics Products 53 Rubber and Misc. Plastics Products 33 Leather and Leather Products 19 Leather and Leather Products 16 Stone, Clay, and Glass Products 21 Stone, Clay, and Glass Products 18 Primary Metal Industries 68 Primary Metal Industries 50 Fabricated Metal Products 56 Fabricated Metal Products 52 Industrial Machinery and Equipment 261 Industrial Machinery and Equipment 214 Electronic and Other Electric Equipment 406 Electronic and Other Electric Equipment 354 Transportation Equipment 100 Transportation Equipment 84 Instruments and Related Products 347 Instruments and Related Products 265 Miscellaneous Manufacturing Industries 44 Miscellaneous Manufacturing Industries 34 Table 12 reports the number of firms (with and without lines of credit) within in each manufacturing segment. The dataset of this study consists to 99% of manufacturing firms. The division into different sectors is based on the companies four-digit SIC code. The cursive manufacturing divisions are the segments with the most observations and those are the sectors that are included in the industry analysis. 48

49 Table 13. OLS regression analysis - Industry effect on lines of credit Dependent variable Line of credit (% of total assets) Complete sample (of included industries) 2005 (1) (2) (3) (4) (5) (6) Cash Flow 0.156*** 0.159*** 0.161*** 0.158*** 0.158*** 0.157*** (4.96) (5.02) (5.06) (5.01) (5.00) (4.98) Cash Holdings *** *** *** *** *** *** (-17.86) (-17.96) (-17.92) (-17.89) (-17.80) (-18.02) Cash Flow * Cash Holdings *** *** *** *** *** *** (-6.80) (-6.86) (-6.91) (-6.73) (-6.86) (-6.84) Industry Food & Kindred Products (0.84) Chemicals & Allied Products (-0.83) Industrial Machinery & Equipment 0.018** (2.01) Electronic & Other Electric Equipment (-0.45) Transportation Equipment (-0.02) Instruments & Related Products (-1.30) Firm characteristics Large ** ** *** ** ** ** (-2.18) (-2.14) (-2.19) (-2.17) (-2.17) (-2.25) Non-bank dependent (0.81) (0.75) (0.67) (0.79) (0.78) (0.79) Investment grade (-0.97) (-0.89) (-0.82) (-0.95) (-0.93) (-0.95) Profitable (0.51) (0.39) (0.35) (0.49) (0.50) (0.62) Constant 0.168*** 0.170*** 0.166*** 0.170*** 0.169*** 0.171*** (20.64) (20.55) (20.39) (20.56) (20.54) (20.48) Observations per industry R² Table 13 reports the results of the OLS regression where the industry effect on credit lines is investigated for Complete sample means that all firms of the included industries are taken into account. Line of credit is the dependent variable and represents total line of credit commitment to total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Industry is a dummy variable equal to 1 if a firm belongs to that industry, and otherwise 0. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 49

50 Table 14. OLS regression analysis - Industry effect on lines of credit 2008 Dependent variable Line of credit (% of total assets) Complete sample (of included industries) 2008 (1) (2) (3) (4) (5) (6) Cash Flow 0.117*** 0.120*** 0.119*** 0.118*** 0.118*** 0.120*** (3.34) (3.46) (3.41) (3.37) (3.38) (3.42) Cash Holdings *** *** *** *** *** *** (-17.08) (-16.78) (-17.60) (-17.54) (-17.38) (-17.40) Cash Flow * Cash Holdings *** *** *** *** *** *** (-5.23) (-5.55) (-5.36) (-5.28) (-5.30) (-5.34) Industry Food & Kindred Products (0.60) Chemicals & Allied Products ** (-2.21) Industrial Machinery & Equipment (0.66) Electronic & Other Electric Equipment (0.11) Transportation Equipment (-0.31) Instruments & Related Products (1.27) Firm characteristics Large (-0.50) (-0.40) (-0.46) (-0.47) (-0.47) (-0.42) Non-bank dependent (0.03) (-0.02) (0.00) (0.01) (0.03) (0.05) Investment grade (-0.58) (-0.50) (-0.56) (-0.56) (-0.58) (-0.58) Profitable (-0.42) (-0.47) (-0.46) (-0.41) (-0.41) (-0.46) Constant 0.189*** 0.193*** 0.189*** 0.190*** 0.191*** 0.188*** (20.75) (21.47) (20.95) (21.07) (21.08) (19.90) Observations per industry R² Table 14 reports the results of the OLS regression where the industry effect on credit lines is investigated for Complete sample means that all firms of the included industries are taken into account. Line of credit is the dependent variable and represents total line of credit commitment to total assets. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Industry is a dummy variable equal to 1 if a firm belongs to that industry, and otherwise 0. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Non-bank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 50

51 Table 15. OLS regression analysis - Industry effect on drawdowns Dependent variable Drawdowns (% of total credit line) Line of credit sample (of included industries) 2005 (1) (2) (3) (4) (5) (6) Cash Flow * * * * * * (-1.68) (-1.82) (-1.75) (-1.72) (-1.74) (-1.78) Cash Holdings *** *** *** *** *** *** (-5.41) (-5.42) (-5.33) (-5.32) (-5.35) (-5.35) Cash Flow * Cash Holdings ** * ** ** ** * (-2.03) (-1.78) (-1.99) (-2.02) (-1.99) (-1.95) Industry Food & Kindred Products (-0.97) Chemicals & Allied Products (1.00) Industrial Machinery & Equipment (-0.14) Electronic & Other Electric Equipment (0.53) Transportation Equipment (-0.21) Instruments & Related Products (-0.71) Firm characteristics Large (-0.94) (-1.00) (-0.94) (-0.93) (-0.93) (-1.01) Non-bank dependent (-0.92) (-0.82) (-0.87) (-0.91) (-0.89) (-0.89) Investment grade (0.03) (-0.09) (-0.03) (0.02) (-0.00) (-0.01) Profitable *** *** *** *** *** *** (-3.06) (-2.93) (-3.00) (-2.98) (-3.04) (-2.98) Constant 0.310*** 0.304*** 0.308*** 0.305*** 0.308*** 0.311*** (14.65) (14.11) (14.41) (13.74) (14.41) (14.24) Observations per industry R² Table 15 reports the results of the OLS regression where the industry effect on drawdowns is investigated for Lines of credit sample indicates that only firms of the included industries with a reported line of credit are taken into account. Drawdowns is the dependent variable and represents outstanding loan to total line of credit commitment. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Industry is a dummy variable equal to 1 if a firm belongs to that industry, and otherwise 0. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Nonbank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 51

52 Table 16. OLS regression analysis - Industry effect on drawdowns Dependent variable Drawdowns (% of total credit line) Line of credit sample (of included industries) 2008 (1) (2) (3) (4) (5) (6) Cash Flow (-1.16) (-1.31) (-1.20) (-1.19) (-1.19) (-1.20) Cash Holdings *** *** *** *** *** *** (-7.31) (-7.17) (-7.06) (-7.09) (-7.07) (-7.05) Cash Flow * Cash Holdings ** * *** ** ** ** (-2.18) (-1.82) (-2.05) (-2.07) (-2.07) (-2.05) Industry Food & Kindred Products *** (-2.89) Chemicals & Allied Products (1.54) Industrial Machinery & Equipment (-0.21) Electronic & Other Electric Equipment (0.29) Transportation Equipment (-0.40) Instruments & Related Products (-0.11) Firm characteristics Large (0.63) (0.41) (0.51) (0.52) (0.52) (0.51) Non-bank dependent (-0.31) (-0.24) (-0.26) (-0.26) (-0.24) (-0.26) Investment grade (-0.37) (-0.46) (-0.42) (-0.42) (-0.44) (-0.42) Profitable *** *** *** *** *** *** (-3.40) (-3.38) (-3.40) (-3.35) (-3.42) (-3.41) Constant 0.384*** 0.371*** 0.377*** 0.374*** 0.377*** 0.377*** (16.58) (16.54) (16.33) (15.09) (16.51) (15.97) Observations per industry R² Table 16 reports the results of the OLS regression where the industry effect on drawdowns is investigated for Lines of credit sample indicates that only firms of the included industries with a reported line of credit are taken into account. Drawdowns is the dependent variable and represents outstanding loan to total line of credit commitment. Cash flow is EBITDA to total assets. Cash holdings measures cash and marketable securities to total assets. Industry is a dummy variable equal to 1 if a firm belongs to that industry, and otherwise 0. Following variables are dummy variables controlling for firm characteristics; Large is equal to 1 when sales > $1 billion, and otherwise 0. Nonbank dependent is equal to 1 if the firm has an S&P credit rating, and otherwise 0. Investment grade is equal to 1 when credit rating BBB-, and otherwise 0. Profitable is equal to 1 if the firm has a positive net income, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t-statistics). 52

53 Table 17. Usage of covenants Dependent variable Firms with a specified line of credit covenant (% of total firms) Line of credit sample (1) (2) Diff Covenants Total leverage 41.92% 47.46% -5.53% Dividends 43.43% 39.55% 3.88% Investment 31.31% 36.16% -4.84% Asset sale 27.27% 32.20% -4.93% M&A 21.72% 29.94% -8.23%* Share repurchase 15.66% 18.64% -2.99% Table 17 reports the results of a two-tailed mean difference analysis of the usage of covenants before and during the crisis. Column (1) shows the findings for 2005 whereas column (2) reports the results for Lines of credit sample indicates that only firms with a reported line of credit at the end of the fiscal year are taken into account. Firms with a specified line of credit covenant refers to the percentage of firms that are restricted by a certain covenant. The covenants (total leverage, dividends, investment, asset sale, M&A, and share repurchase) are dummy variables which are equal to 1 if a firm s line of credit is restricted by that specific covenant, and otherwise 0. Please note, ***, **, and * indicate significance at a 10%, 5%, and 1% test level, respectively (two-tailed t- statistics). 53