CORPORATE CASH HOLDINGS AND CREDIT LINE USAGE

• Author: Nathalie Moyen,Martin Boileau
• Published date: 01 November 2016
• Date: 01 November 2016
• DOI: http://doi.org/10.1111/iere.12205

INTERNATIONAL ECONOMIC REVIEW

Vol. 57, No. 4, November 2016

CORPORATE CASH HOLDINGS AND CREDIT LINE USAGE∗

BYMARTIN BOILEAU AND NATHALIE MOYEN1

University of Colorado, U.S.A.

We investigate the factors driving the unprecedented rise in corporate liquidities since the 1970s. We find that an

economy-wide reduction in the cost of holding liquidities and an increase in risk best explain the rise in cash holdings

and the widespread use of credit lines. The structural estimation results shed light on two widely acknowledged motives

for holding cash. The precautionary motive and the liquidity motive translate risk exposure into cash holdings. Our

results, however, do not suggest that firms have become more prudent over time. It is higher liquidity needs that has

forced firms to hold more cash and use more credit lines.

1. INTRODUCTION

North American firms increasingly use liquidity instruments to manage the risk they face.

Bates et al. (2009) document a large and steady increase in cash holdings as a proportion of

total assets for U.S. listed firms. Alongside the unprecedented level of cash liquidities, Sufi

(2009) documents the widespread use of credit lines.2To gain some perspective, consider the

period starting in 1995 and ending in 2006 just before the crisis. For this period, long-term debt

represents 22% of total assets for the average firm in our sample of listed firms, whereas cash

holdings represents almost 21% of total assets. In fact, 45% of firms have on average more cash

than debt.

The literature highlights that, because of financial frictions, firms must rely on liquidity

instruments to manage risk. This suggests that the larger importance of liquidities is attributable

to three possible causes. Firms may rely more on liquidity instruments because they face more

risk, because the cost of using liquidities has decreased, or because financial frictions have

increased. Bates et al. (2009) conclude that the large cash increase is attributable to higher cash

flow risk for listed firms.

Building on Bates et al. (2009), we identify the mechanism by which the increase in risk

leads to an increase in liquidities for North American listed firms. Table 1 documents more

volatile sales and more volatile operating expenses, in accord with Dichev and Tang (2008).

Interestingly, the rise in the volatility of operating expenses is itself attributable to general,

selling, and administrative expenses, an item that is mostly unrelated to the scale of operations.

We use a structural approach to investigate the underlying mechanisms by which increases in

risk explain the large increase in corporate cash holdings amid prevalent credit lines and other

∗Manuscript received October 2013; revised July 2015.

1We thank Gian Luca Clementi, Adlai Fisher, Rick Green, Denis Gromb, Burton Hollifield, Lars-Alexander Kuehn,

Erwan Morellec, Norman Sch¨

urhoff, and Toni Whited for helpful comments and discussions. We would also like to

thank Jesus Fernandez-Villaverde, anonymous referees, and seminar participants at the American Finance Association

meetings, Carnegie-Mellon University, the Federal Reserve Bank of Dallas, French Finance Association meetings,

HEC Lausanne, INSEAD, KU Leuven, the Northern Finance Association meetings, the T2M annual conference, the

University of British Columbia Summer Finance Conference, the University of Colorado at Boulder, the University of

Wisconsin at Milwaukee, Victoria University Wellington, and Wilfrid-Laurier University for helpful comments. Please

address correspondence to: Nathalie Moyen, Leeds School of Business, University of Colorado, 995 Regent Drive -

419 UCB, Boulder, CO 80309, U.S.A. Phone: 303-735-4931. Fax: 303-492-5962. E-mail: moyen@colorado.edu.

2Using a random sample of 300 COMPUSTAT firms, Sufi (2009) documents that 85% of firms have access to a

credit line between 1996 and 2003, and their line usage amounts to about 6% of total assets on average. For firms with

a Standard and Poor’s credit rating, 94.5% of them have a credit line where usage represents 4.7% of total assets.

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(2016) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social

and Economic Research Association

1482 BOILEAU AND MOYEN

TABLE 1

STANDARD DEVIATIONS OF NET INCOME COMPONENTS

Panel A:Average Standard Deviations for Components of Net Income

Net Oper. Int. Spec. Non Minor. Disc.

Inc. Inc. Exp. Items oper. Taxes Int. Oper.

1971–82 0.046 0.073 0.012 0.011 0.009 0.028 0.000 0.014

1995–2006 0.180 0.134 0.016 0.048 0.012 0.021 0.001 0.013

Panel B: Average Standard Deviations for Components of Operating Income

Sales Operating Expenses Depreciation

1971–82 0.239 0.224 0.008

1995–2006 0.271 0.304 0.017

Panel C: Average Standard Deviations for Components of Operating Expenses

COGS XSGA

1971–82 0.184 0.055

1995–2006 0.193 0.114

NOTES: The data come from the North American COMPUSTAT file and covers the period from 1971 to 2006 excluding

the crisis period, where we focus on the first third of the sample period from 1971 to 1982 and the last third from 1995 to

2006. The COMPUSTAT sample includes firm-year observations with positive values for total assets (COMPUSTAT

Mnemonic AT), property, plant, and equipment (PPENT), and sales (SALE) from all industries except utilities and

financials, with at least five years of consecutive data. The data are winsorized to limit the influence of outliers at the 1%

and 99% tails. COGS refers to Cost of Goods Sold and XSGA refers to Selling, General and Administrative Expenses.

We compute the standard deviation of a firm’s time series (standardized by the firm’s total assets), then average over

all firms for each subsample.

liquidity management tools. As is standard, we model the sale revenue risk by a shock to total

factor productivity (TFP) observed by the firm at the beginning of the year. In line with the

data, we model another source of risk as a time-varying fixed cost unrelated to the production

scale of the firm. In addition, we recognize that shocks occur throughout the year, and we allow

this second shock to be realized during the year.

The structural model embeds two mechanisms by which more risk leads to more cash holdings.

First, the liquidity mechanism emphasizes the greater flexibility of cash and credit lines over the

firm’s other instruments. The model recognizes that it is more costly for firms to sell off assets,

take back distributed dividends, or raise new debt to cover an adverse midyear shock than to

use accumulated liquidities. Instead, firms transfer funds between those interest-earning assets

and cash at the beginning of each decision period in anticipation of their liquidity requirements

during that period. Thus, one possible mechanism explaining the rise in cash is the increase in

midyear risk that would escalate the need for liquidities. Such a liquidity mechanism is featured

in the seminal work of Miller and Orr (1966), where firms must manage cash inventories to face

immediate liquidity needs. The liquidity mechanism is also similar to that discussed in Telyukova

and Wright (2008), where liquidity needs yield a motive for consumers to accumulate liquidities.

Second, the precautionary mechanism emphasizes the role of taxes on distributions and costs

to issuing equity. Firms not only smooth payouts to avoid extreme taxes and issuing costs but

may also behave prudently and accumulate cash holdings to self-insure against future adverse

shocks. In this sense, the firm may accumulate precautionary holdings over and above those

required by immediate funding needs discussed above. In this second possible mechanism

explaining the cash increase, the increase in firms’ idiosyncratic risk underscores the need to

self-insure. This precautionary mechanism is similar to that discussed in Leland (1968) and

Carroll and Kimball (2008), where a convex marginal utility generates prudence and yields a

motive to accumulate precautionary cash holdings.

To summarize, both the Miller and Orr (1966) liquidity motive and the Leland (1968) pre-

cautionary motive operate through financial frictions. Our liquidity mechanism focuses on the