Is the investment-cash flow sensitivity still useful to gauge financing constraints?

Int. J. Economic Policy in Emerging Economies, Vol. 3, No. 1, 2010 71

Copyright © 2010 Inderscience Enterprises Ltd.

Is the investment-cash flow sensitivity still useful to gauge financing constraints?

Jamel E. Chichti Ecole Supérieure de Commerce de Tunis, Université de la Manouba, 2010, Tunisia, North Africa E-mail: [email protected]

Walid Mansour* Institut Supérieur de Finances et de Fiscalité de Sousse, Rue 18 Janvier 1952- Sousse 4000, Tunisia, North Africa E-mail: [email protected] *Corresponding author

Abstract: Most of the papers in corporate finance use the investment-cash flow sensitivity as a key metric to gauge financing constraints. However, it has been documented in the theoretical and empirical literature that this metric is not necessarily symptomatic of financing constraints. In this paper, we revisit the debate among authors regarding the usefulness of the so-called sensitivity in the context of the moral hazard literature. We theoretically show that the interpretation of this metric as an indicator of financing constraints is sceptical.

Keywords: investment-cash flow sensitivity; capital-market imperfections; moral hazard; costly state verification; monotonicity hypothesis.

Reference to this paper should be made as follows: Chichti, J.E. and Mansour, W. (2010) ‘Is the investment-cash flow sensitivity still useful to gauge financing constraints?’, Int. J. Economic Policy in Emerging Economies, Vol. 3, No. 1, pp.71–84.

Biographical notes: Jamel E. Chichti is a Professor of Finance and Insurance at the University of La Manouba (Tunisia). He earned his diplomas from the French Universities, especially the prestigious Paris Dauphine University. He is a former Tunisian Minister and was the Economic Adviser to Tunisia’s President in the beginning of the 1990s. His research interests cover mainly insurance studies and risk analysis.

Walid Mansour is an Assistant Professor of Finance. He previously published in international journals. His research interests include issues related to information-driven problems and corporate finance, investment theory, and Islamic Economics.

72 J.E. Chichti and W. Mansour

1 Introduction

In this paper, we revisit the debate among authors regarding the usefulness of the investment-cash flow sensitivity as a major indicator of financing constraints. Although it has been documented over the recent past that this sensitivity is one of the important key metrics that are used in financial economics (Almeida and Campello, 2007), its usefulness stands an open question in corporate finance. Fazzari et al. (1988, 1996, 2000) document that the cross-sectional differences of the investment-cash flow sensitivities may be considered as sheer evidence of the firms’ heterogeneity with respect to their access to external funding sources. A high investment-cash flow sensitivity is supposed to reflect the firm’s financing constraints. The uselessness of this sensitivity is not widely accepted among authors.

The critics lying behind the usefulness of the investment-cash flow sensitivity make it questionable and thus due to three main points. First, the grouping of the grand sample of firms is very sensitive to the classification scheme. Second, the observed excess of sensitivity may not just reflect the degree of financing constraints. D’Espallier et al. (2008, p.964) argue that it may “reflect another unobservable economic phenomenon inherent to the classification scheme”. Third, the error-laden proxy problem of marginal q brings forth a bias in the reduced-form investment equation’s estimates, as Erickson and Whited (2000, 2002) claim.

The objective of this paper is to revisit the hot debate among the parents of the literature by contriving a simple theoretical set-up.1 Indeed, we use the standard moral hazard set-up to derive an investment mapping under incentive restrictions and random shocks. Our theoretical findings show that a high investment-cash flow sensitivity – arguably – is not necessarily symptomatic of financing constraints.

The paper is organised as follows. Section 2 presents some prima facia beliefs. Section 3 describes the financial contractibility under incentive-driven problems in which financing constraints are encompassed parsimoniously. Section 4 revisits the debate regarding the usefulness of the investment-cash flow sensitivity. Section 5 concludes the paper.

2 Prima Facia beliefs

In Modigliani and Miller’s (1958) world, the firm’s financing instruments are perfect substitutes. That is, the firm can easily access to outside financing at the same cost of its net worth. Nonetheless, in the context of information asymmetries (à la Akerlof, 1970), its access is costly and the firm’s financing instruments are no longer substitutes. Indeed, the firm must pay an extra-cost2 to raise external funds.

The original paper by Akerlof (1970) was the first starting-point of the literature on Information Economics. Although this paper was rejected three times by three editors, its influence is far-reaching till our days. It analyses a market for a commodity where one part has more information than the other. The then strange term used by the author is ‘lemons’ (nowadays it is a colloquialism) to label the defective cars (or any other defective wares) and became a common term used by economists around the world. He pointed out that the logic underlying his analysis may be kindred to Thomas Gresham’s law. Gresham’s law claims that ‘bad’ money drives out ‘good’, which is not, according to Akerlof (1970, p.490) himself, a perfect analogous to the lemons principle

Is the investment-cash flow sensitivity still useful to gauge 73

since both sellers and buyers can presumably distinguish between ‘good’ and ‘bad’ money.3

The direct consequence of the situation of information asymmetries reining among claimants was deeply elucidated by Myers (1984) and Myers and Majluf (1984) through their pecking-order theory, which emphasises the role of the entrepreneurial net worth in driving the firm’s capital spending. Indeed, as it has been empirically and theoretically documented by several authors (e.g., Islam, 2002; Abel and Eberly, 2002; Hennessy and Whited, 2007), the internal and external funds do have not the same cost. The firm has consequently led to rely on its internally generated funds to attain its optimal, first-best capital stock at the conventional opportunity cost, or gets punished with an agency premium.

The line of empirical research involving the study of the magnitude of financing frictions embeds a long list of approaches. Tackling empirically the problem of financing frictions is related for instance to the estimation of underwriter fee schedules, the announcement effect (as a form of indirect costs of external equity), the indirect costs of financial distress, etc. The same line of empirical research adopts the approach based on split-samples and using the reduced-form investment regressions so as to test for the magnitude of financial frictions. This approach was pioneered for Finance by Fazzari et al. (1988) and adopted by many authors, e.g., Hoshi et al. (1991), Hubbard (1998), Bond et al. (2004), and Cleary et al. (2007).

The original empirical regularities documented by Fazzari et al. (1988) highlight the role of information-driven frictions and their worsening impact on the firm’s financing and investment decisions. Their approach is based on the common, prima facia belief that information-driven problems drive a wedge between the costs of internal and external funds (Greenwald et al., 1984; Jensen and Meckling, 1976).4 They argue that the investment-cash flow sensitivity is higher for small, young firms for which the profits are more volatile, relative to the one of the high-sized, mature ones. Their so-called monotonicity conjecture stresses the fact that the investment-cash flow sensitivity is supposedly monotonically and continuously increasing with the severity of information asymmetries’ severity.

Kaplan and Zingales (1997) argue that the investment-cash flow sensitivity is not a useful metric to detect the degree of financing constraints.5 They further question6 the monotonic behaviour of the investment-cash flow sensitivity, which casts doubt on the pertinence of the whole approach pioneered by Fazzari et al. (1988). Indeed, the support of Fazzari et al. (1988) view was detracted by many authors who inferred that the common interpretation of the positive cash flow effect on investment cannot be taken as sheer evidence of financing constraints facing firms. For instance, Gomes (2001) shows that investment is sensitive to cash flow in a frictionless context. Similarly, Cooper and Ejarque (2001) develop a model with quadratic adjustment costs and concave profit functions. After solving their model numerically, they prove that investment is sensitive to both Tobin’s q and cash flow in the absence of financing frictions. Hovakimian (2009) argues that recent studies (e.g., Allayannis and Mozumdar, 2004; Bhagat et al., 2005) explain that the ‘failure’ of the original work by the parents of the field (i.e., Fazzari et al., 1988) in gaining an unanimous attention is due to

“the inclusion of internal liquidity into the classification scheme and, particularly, grouping firms with negative earnings with financially constrained but otherwise healthy firms may affect the outcome of the cross-section analysis.”


Abel and Eberly’s (2002) model assumes perfect capital markets with no financing restrictions. They show that, after controlling for future growth opportunities, cash flow has a positive effect on investment. The failure in the interpretation of the cash flow effect has been identified in the empirical literature as artefact of measurement error, which leads to spurious cash flow effects.7 Hirth and Uhrig-Homburg argue that

“[...] these studies have come to ambiguous conclusions. While early empirical research starting with Fazzari et al. (1988) claimed that more constrained firms should have higher sensitivities of investment volume to cash flow, this was later questioned most prominently by Kaplan and Zingales (1997).” (Hirth and Uhrig-Homburg, 2007, p.2)

Hovakimian (2009) studies the excess of sensitivity of investment to cash flow from a different perspective. Indeed, he tackles the variables that drive this phenomenon. The approach of the author does not use the ex ante classification scheme8 that requires some criteria that reflect the firm’s easiness to access to external finance markets (e.g., size, credit worthiness, dividend policy, etc.) The approach of Hovakimian (2009) is based on two steps. The first step consists in estimating a new expression of the investment-cash flow sensitivity, which reflects the extent to which the capital expenditures are correlated with cash flows. The second step consists in partitioning the full sample into sub-groups on the basis of the value of the estimated firm-level investment-cash flow sensitivity. The author finds that

“firms with different levels of investment-cash flow sensitivity is non-monotonic with respect to all considered firm characteristics that proxy for financial constraints.”

The investment-cash flow sensitivity is not the only suggestion to capture the degree of financing constraints. Another measure – the cash flow sensitivity of cash – has been proposed by Almeida et al. (2004). Indeed, the proposition of this additional measure emerged as an alternative of the investment-cash flow sensitivity. D’Espallier et al. argue that

“Although these theoretical considerations cast serious doubt upon the ability of the Cash Flow Sensitivity of Investment (CFSI) metric to capture financial constraints, it is difficult to assess how strong this impact is when measuring financial constraints in a ‘real-world’ sample. One may thus conclude that the literature recognises that investments are driven by internal funds for a large number of firms, although it remains unclear to what extent these investment-cash flow sensitivities reflect limited access to external funds as a result of financial constraints.” (D’Espallier et al., 2008)

Almeida et al. (2004) claim that the cash flow sensitivity of cash is a better metric, since it measures the “change in cash or marketable securities as a response to the amount of cash flow generated by the firm”. The empirical studies that use this alternative measure is based on the fact that it must exhibit a positive relation with the degree of financing constraints. For instance, D’Espallier et al. claim that

“this parameter is predicted to be higher for financially constrained firms, since these firms tend to hoard cash (stock-piling) in order to cope with fluctuations in positive investment opportunities. Since constrained firms cannot rely on external funding sources at all times, they use cash and marketable securities as a cushion against fluctuations in positive future investment projects.” (D’Espallier et al., 2008, p.947)


The objective of this paper is not to study empirically the investment-cash flow sensitivity or its alternative metric, namely the cash flow sensitivity of cash. Our objective is rather of a theoretical nature. We aim at revisiting the debate among Fazzari et al. (1988, 2000) and their proponents and Kaplan and Zingales (1997, 2000) and their proponents. By borrowing the context of moral hazard and costly state verification and by encompassing financing constraints, our goal is to find out an investment mapping that depends on various parameters to derive its second-order partial derivatives that constitute the debate. As we will show, the interpretation of the investment-cash flow sensitivity as an indicator of financing constraints is ‘sceptical’ and its usefulness is – at least theoretically – fragile.

3 Encompassing financing constraints

We will borrow the approach of Mansour (2009). We consider a firm having a profitable investment opportunity, I, and its internally generated funds, W, are not sufficient to finance it all. It, therefore, must raise funds from external, non-residual claimants.9 The firm evolves in a stochastic environment. Indeed, the shock z reflects the economic conditions (e.g., marginal productivity of capital, technological endowment.) For simplicity purposes, we narrow down the set of z values to a two-element set, as in Hart (1995), i.e., { , }.hlz z z∈ The shock zh reflects good economic conditions, i.e., high marginal productivity of the capital. Similar to Hart (1995), the occurrence of the low-state shock is interpreted in terms of bankruptcy, after which the firm may exit the match. The firm generates a random revenue R that depends on both I and W.

We encompass information-driven problems through a combined moral hazard-CSV10 problem. The entrepreneur is supposed to gain (i.e., expropriate) a fraction

(0, 1)ϕ ∈ from the investment opportunity. That is, the expropriated funds are hypothetically equal to .Iϕ The entrepreneur may choose to use the fraction ϕ not to finance the investment opportunity as it is agreed upon in the financial contract. The parameter ϕ reflects hence the degree of information asymmetry between the financial contract’s parties. As Hart (1995) argues, if ϕ approaches the unity, without hitting it though, then the information asymmetries are expected to be the severest.11

The informational asymmetry does crop up neither ex ante (the adverse selection case) nor ex post (the hidden action problem), but arises once the pay-off is generated (Townsend, 1979). That is, the cumulative distribution function of the generated revenue is only observed by the entrepreneur. When the entrepreneur chooses to report the low-state shock, zl, in lieu of the high-state one, zh, by benefiting from the good states of nature, consequently the announced revenue reduces to ( , ).lz R I W 12

In this context, we invoke the revelation principle (Hillier, 1997)13 for which the financial contracts are restricted to those for which the entrepreneur’s reporting strategy is truthful. We additionally assume that the entrepreneur will truthfully report the revenue realisations, according to the epsilon-truthfulness hypothesis. Indeed, according to this hypothesis, the entrepreneur gains low benefits, say epsilon (0 < 1),ε ≺≺ when hiding the true revenue. Mathematically, Hart (1995) argues that the following condition should hold

( , ) ( , ).l hz R I W I z R I Wϕ+ ≤ (1)


The latter inequality means that the proceeds the entrepreneur may earn from hiding the true revenue (and which are the outcome of the combined moral hazard-CSV problem), i.e., ( , ) ,lz R I W Iϕ+ are always lower than those he earns when reporting the true one, i.e., ( , ).hz R I W

To encompass frictions, we suppose that the firm gets financially constrained when its pledge-raised funds are no longer feasible. That is, the firm becomes constrained when the mathematical condition ensuring its secured-lending form is violated. The external non-residual claimant requires the collateralisation of a fraction of the revenue (à la Tirole, 2006; Almeida and Campello, 2001) to finance the firm’s investment opportunity. That is, let us consider that the collateralised revenue amounts to ( , ),plg zR I Wψ where (0,1)plgψ ∈ is the parameter of the pledgeability. The aforementioned inequality becomes

(1 ) ( , ) (1 ) ( , ).plg plgl hz R I W I z R I Wψ ϕ ψ− + ≤ − (2)

The latter inequality means that the entrepreneur cannot earn more when hiding the true revenue and expropriating a fraction of the capital expenditures. That is, the left-hand side of the inequality is the entrepreneur’s entitlement when he simultaneously reports the ‘wrong’ shock and expropriates the fraction .ϕ In contrast, the right-hand side is the entitlement that he earns when he reports the true shock and he does not implement any misallocation. Notice that this inequality encompasses proxies for informational problems, the stochastic nature of the economy and the degree of pleadegability ensuring secured-lending form.

As long as inequality (2) is true, the firm can raise external funds as in the full information world. However, its violation leads to binding financing constraints and, accordingly, borrowing is no longer feasible at the predicted terms in the case of information symmetry. That is to say, there is an upper boundary of the pledgeability parameter (Kiyotaki and Moore, 1997)14 beyond which the firm gets financially constrained. Indeed, using condition (2), such an upper boundary can be defined as

1 , ( , ) > 0, ,( , )( )

plgmax l h

h l

I R I W z zR I W z z

ϕψ

≡ − ≠ − (3)

which is equivalent to the maximum pledgeability’s parameter beyond which financing investment becomes constrained.15 For all values of ψ that are equal or bigger than max ,plgψ the firm is not able to finance all its investment opportunities, even if they are positive-NPV, unless it gets punished with an agency premium charged on its loanable funds for the investment opportunities for which both net worth and the pledged revenue are not sufficient.

We know that, at equilibrium, the investment amounts to the level of internal and the borrowed funds. That is, the equilibrium is attained when the firm uses all its available (internal and external) funds. Indeed, the equilibrium condition could be given by16

max= ( , ).plghI W z R I Wψ+

The insertion of the expression of maxplgψ in the latter equation gives the expression of

investment arising from the pledged financial contract


= ( , ) 1 .( , )( )h

h l

II W z R I WR I W z z

ϕ + − −

(4)

A little modification of equation (4) gives the following expression of the investment at the equilibrium

[ ]( , )= ,h

h

z W z R I WI

z z ϕ∆ +

∆ + (5)

where = ( ).h lz z z∆ − As it is quite clear from equation (5), the investment mapping depends on five

variables ( ,ϕ W, zh, zl, )plgmaxψ and the function R. It turns out to be interesting

to understand the response of the investment to the fluctuation of each of these variables and function through the computation of their respective partial derivatives. More particularly, we are interested in the partial derivatives with respect to W and .ϕ The first partial derivative of equation (5) with respect to W is

( , )1= .

( , )1

h

h h

R I Wz zI W

R I WW z z zI

ϕ

∂ ∆ + ∂ ∂ ∂∂ ∆ − + ∂

(6)

In the financing constraints literature, equation (6) is the investment-cash flow sensitivity. In compliance with Fazzari et al. (1988), it should exhibit a positive sign and must be an increasing function of the severity of informational problems. In other terms, the investment-cash flow sensitivity is supposed to be monotonically increasing in the degree of financing constraints. Empirically, many authors showed that there are cross-sectional differences in the estimated sensitivities, which – arguably – proves that the financial variables in investment equations capture the firm’s financing conditions. That is, when capital-market imperfections bring forth acute financial frictions, the firm cannot have access to outside financing instruments at the same prices (of the break-even state of affairs in the conventional, neoclassical setting.). The capital expenditures increase monotonically with the fluctuations of the internally generated net worth, when the severeness of financial frictions tend to be higher. In the next sub-section, we will revisit the debate between Fazzari et al. (1988, 1996, 2000) and Kaplan and Zingales (1997, 2000) regarding this monotonic increase in investment with respect to internal funds.

The second partial derivative is given by

2

[ ( , )]= < 0, if > 0.

( )h h

h

z z W z R I WI zz zϕ ϕ

∆ +∂ − ∆∂ ∆ +

(7)

Clearly, this partial derivative displays a negative sign. This is consistent with the common, prima facia belief that acute information asymmetry worsens the firm’s level of investment, as a consequence of the lemons problem. Indeed, Akerlof (1970) and Stiglitz and Weiss’ (1981) standard results argue that, owing to the information asymmetries, the firm underinvests. Indeed, the situation of asymmetrically distributed information is


worsening to the firm’s investment decisions. In our case, this is quite clear since the increase in ϕ impacts negatively the firm’s investment.

4 The usefulness of the investment-cash flow sensitivity revisited

The central debate between Fazzari et al. (1988, 1996, 2000) and Kaplan and Zingales (1997, 2000) (and their respective proponents/opponents) is about the usefulness of the investment-cash flow sensitivity and its underlying monotonicity hypothesis. The problem we address is whether this sensitivity will bear a monotonic behavior or not. For firms facing a high degree of financing constraints (Cleary et al., 2007)17 (i.e., ϕ slopes up), the firm’s investment is expected to decrease. This is clear through the partial derivative given by equation (7).

The theoretical debate between Fazzari et al. (1988, 1996 2000) and Kaplan and Zingales (1997, 2000) centres at whether the investment-cash flow sensitivity bears a monotonic-upward scheme. In compliance with Kaplan and Zingales (2000), the investment-cash flow sensitivity is meaningful if and only if

2

2 < 0.IW∂

∂

Indeed, in contrast with Fazzari et al. (2000), Kaplan and Zingales (2000) argue that a high level of net worth does not mean that the firm is financially constrained18. That is, as long as the net worth level is high, the sensitivity is expected to be low. Hence, the monotonicity conjecture is true only under the latter condition, which is only weakly verified since Kaplan and Zingales assume that I W∂ ∂ does not certainly decrease when net worth increases.

Fazzari et al. (2000) claim that 2

2 > 0IW∂

∂

can hold true. In essence, they assume that, at a given, high level of net worth, the investment can be more sensitive to W for a firm having tighter financing constraints. That is, the monotonicity hypothesis can hold if, at a high level of net worth, the marginal cost of external funds is steeper for firm A relative to another firm B. That is to say, the monotonic-upward schedule is true if

2

> 0.IW ϕ∂

∂ ∂ In other terms, the argument of Fazzari et al. (2000) is true if the marginal cost of external funds (proxied for by ϕ in our case19) is higher for the firms having a high level of net worth.

To revisit the debate, we compute the two partial derivatives of the investment-cash flow sensitivity with respect to net worth and the proxy capturing information asymmetry. The partial derivatives of equation (6) with respect to W and ϕ are


2 2

22

2 2

2 22

2

2

=

1> 0,

h

h h

I R Rzz GW W I WI

W GR I R Rz z zW W I WI

G

∂ ∂ ∂∆ × + × ∂ ∂ ∂ ∂∂ ∂

∂ ∂ ∂ ∂ ∆ + × × + ∂ ∂ ∂ ∂∂ +

(8)

where ( ( ), )= 1 .h hR I W WG z z z

Iϕ∂ ∆ − + ∂

2

2

1= < 0.

1

h h

h h

Rz z zI W

W Rz z zI

ϕϕ

∂ ∆ + ∂ ∂ −∂ ∂ ∂ ∆ − + ∂

(9)

Similar to Fazzari et al. (2000), the second partial derivative (8) is positive, which means that at a high level of net worth (i.e., high Ws) the investment-cash flow sensitivity is high too. That is, when the firm constructs a buffer of cash stock its investment is more sensitive at high levels of net worth. Accordingly, if the partial derivative (8) is positive, then the claimed monotonicity conjecture is partially true. This result hence corroborates the definition of financing constraints by Fazzari et al. (2000).20 It is important to notice that the positivity of equation (8) depends on the positivity of its numerator, which depends on the convexity of the revenue function. In this case, the second partial derivative exhibits a positive sign. Alternatively, if its functional form is concave, the second partial derivative is no longer positive.21

From a different perspective, our theoretical result can be viewed as somewhat linked to liquidity management. Nonetheless, there is no unanimous understanding of how the firm should manage its liquidity. Indeed, Cummins and Nyman argue that

“Models with a premium on external finance produce counterfactual predictions about liquidity management. We address this shortcoming by introducing a fixed cost of increasing external finance into an otherwise standard investment/financing problem. This additional financial friction is well-motivated by case studies and our analysis shows that it generates more realistic predictions about liquidity management: firms hold external finance and idle cash simultaneously (in order to avoid paying the fixed cost in the future), and may invest an additional dollar of cash flow in liquidity rather than repaying external funds or investing in productive capital.” (Cummins and Nyman, 2004, p.226)

In compliance with Cummins and Nyman (2004), the existing models of external finance generate inconsistent interpretations of liquidity management. In effect, a firm that is plagued with debt cannot hold liquid resources (e.g., marketable securities, near-cash, unused lines of credit) or invest additional cash flow in liquidity. Seemingly, the prediction of Cummins and Nyman’s (2004) model about liquidity management is consistent with Kaplan and Zingales (2000). Indeed, the latter authors claim that a constrained firm does not hold a high level of liquidity similar to Cummins and Nyman (2004). Bhagat et al. (2005) show empirically that most constrained firms have larger free cash flows but less debt to finance their investment, which is consistent with


the theoretical result obtained through equation (8). Therefore, we can notice that the literature on this particular question is not unanimous.

In their response to Kaplan and Zingales (2000) and Fazzari et al. (2000) argue that the second partial derivative (9) should necessarily be positive. Using our own framework and notations, we do not confirm their condition and corroborate the critique by Kaplan and Zingales (2000) who provide theoretical examples for which equation (9) is not positive, as we did. Consequently, we clearly reached the same result as Kaplan and Zingales (2000) through a different theoretical framework. We, therefore, corroborate their scathing critique for which the investment-cash flow sensitivity does not necessarily respond to the increase in information asymmetries’ acuteness, as proxied for by .ϕ

From the latter discussion, it turns out that only one of the two conditions for the usefulness of the monotonicity hypothesis is theoretically met. That is, on the one side, we can confirm that

2

2 > 0,IW∂

∂

which is equivalent with the fact that, at high levels of net worth, investment can be more sensitive to cash flow fluctuations. This theoretical result stands for the judicious quantification of financing constraints on the basis of financial distress. That is to say, a high level of net worth is symptomatic of tightening financing conditions faced by the firm.

On the other side, the second theoretical result does not confirm Fazzari et al. (2000). In contrast, it confirms their opponents, namely Kaplan and Zingales (2000). Indeed, so as the investment-cash flow sensitivity increases monotonically with the severity of informational problems, I W∂ ∂ must increase when the borrowing conditions become worse. That is, the investment-cash flow sensitivity is expected to increase when the access to external financial sources is costly (i.e., higher ϕ s). Our result does not seem to be consistent with this ‘logical’ argument. So, we can say that something is going wrong with the usefulness of the investment-cash flow sensitivity and its underlying monotonicity hypothesis. Sheer discrepancies do exist among authors, which lets the ‘understanding’ of financing constraints very ambiguous.

5 Conclusion

The embedding of information-driven concerns in Modigliani and Miller’s (1958) standard, neoclassical framework renders the perfect substitution between internal and external funds not feasible. Owing to the asymmetrically distributed information, the agency problems drive a cost wedge between internal and external sources. Although the observed excess in the investment-cash flow sensitivity has been widely interpreted in terms of financing constraints, the usefulness of such a metric is questionable both empirically and theoretically.

The aim of this paper is to provide a theoretical framework to revisit the debate regarding the usefulness of the investment-cash flow sensitivity as an indicator of the firm's incapacity to access to external funding sources. We show that its usefulness as a key metric to gauge financing constraints is ‘sceptical’. A high investment-cash


flow sensitivity is not necessarily symptomatic of high financing constraints. We join, therefore, the disparaging critics by Kaplan and Zingales (1997, 2000) and Hennessy and Whited (2007), among others.

On the strength of our major implications, the upward-sloping monotonic schedule (the monotonicity hypothesis) is only partially verified, which is clear through the second-order partial derivatives of the investment mapping we derived. Recent studies also corroborate our findings. For instance, Hovakimian (2009) shows empirically that the investment-cash flow sensitivity is not monotonic with respect to various proxies of the degree of financing constraints. Accordingly, the firm’s investment does not always respond monotonically to increases in net worth. Care needs to be exercised here regarding the usefulness of such a sensitivity. Indeed, although most of the papers interpret it in terms of financing constraints, we do not stand for such an interpretation.

References Abel, A. and Eberly, J. (2002) Q Theory without Adjustment Costs and Cash Flow Effects without

Financing Constraints, Unpublished Working Paper, Wharton School. Akerlof, G.A. (1970) ‘The market for ‘Lemons’: quality uncertainty and the market mechanism’,

The Quarterly Journal of Economics, Vol. 90, No. 3, pp.475–498. Albuquerque, R. and Hopenhayn, H.A. (2004) ‘Optimal lending contracts and firm dynamics’,

The Review of Economic Studies, Vol. 71, No. 2, pp.285–315. Allayannis, G. and Mozumdar, A. (2004) ‘The impact of negative cash flow and influential

observations on investment-cash flow sensitivity estimates’, Journal of Banking and Finance, Vol. 28, pp.901–930.

Almeida, H. and Campello, M. (2001) Financial Constraints and Investment-Cash Flow Sensitivities: New Research Directions, Working Paper, New York University.

Almeida, H. and Campello, M. (2007) ‘Financial constraints, asset tangibility, and corporate investment’, Review of Financial Studies, Vol. 20, pp.1429–1460.

Almeida, H., Campello, M. and Weisbach, M.S. (2004) ‘The cash flow sensitivity of cash’, Journal Finance, Vol. 59, No. 4, pp.1777–17804.

Bhagat, S., Moyen, N. and Suh, I. (2005) ‘Investment and internal funds of distressed firms’, Journal of Corporate Finance, Vol. 11, pp.449–472.

Bond, S., Klemm, A., Newton-Smith, R., Syed, M. and Vlieghe, G. (2004) The Roles of Expected Profitability, Tobin’s Q and Cash Flow in Econometric Models of Company Investment, The Institute for Fiscal Studies, London WP04/12.

Cleary, S., Povel, P. and Raith, M. (2007) ‘The U-shaped investment curve: theory and evidence’, Journal of Financial and Quantitative Analysis, Vol. 42, pp.1–39.

Cooper, R. and Ejarque, J. (2001) Exhuming Q: Market Power vs. Capital Market Imperfections, NBER Working Paper No. 8182.

Cummins, J. and Nyman, I. (2004) ‘Optimal investment with fixed financing costs’, Finance Research Letters, Vol. 1, pp.226–235.

D’Espallier, B., Vandemaele, S. and Peeters, L. (2008) ‘Investment-cash flow sensitivities or cash-cash flow sensitivities? An evaluative framework for measures of financial constraints’, Journal of Business Finance and Accounting, No. 35, Nos. 7–8, pp.943–968.

Erickson, T. and Whited, T. (2000) ‘Measurement error and the relationship between investment and q’, Journal of Political Economy, Vol. 108, No. 5, pp.1027–1057.

Erickson, T. and Whited, T. (2002) ‘Two-step GMM estimation of the errors-in-variables model using high-order moments’, Econometric Theory, Vol. 18, pp.776–799.


Fazzari, S., Hubbard, G. and Petersen, B. (1988) ‘Financing constraints and corporate investment’, Brookings Paper on Economic Activity, Vol. 1, pp.141–195.

Fazzari, S., Hubbard, G. and Petersen, B. (1996) Financing Constraints and Corporate Investment: Response to Kaplan and Zingales, NBER Working Paper Series no. 5462.

Fazzari, S., Hubbard, G. and Petersen, B. (2000) ‘Investment-cash flow sensitivities are useful: a comment on Kaplan and Zingales’, Quarterly Journal of Economics, Vol. 115, pp.695–706.

Gomes, J.F. (2001) ‘Financing investment’, American Economic Review, Vol. 99, No. 5, pp.1263–1285.

Greenwald, B., Stiglitz, J. and Weiss, A. (1984) ‘Informational imperfections in the capital markets and macroeconomic fluctuations’, American Economic Review, Vol. 74, No. 2, pp.195–199.

Hart, O. (1995) Firms Contracts and Financial Structure, Oxford University Press. Hellmann, T.K. and Stilgitz, J.E. (2000) ‘Credit and equity rationing in markets with adverse

selection’, European Economic Review, Vol. 44, No. 2, pp.281–304. Hennessy, C. and Whited, T. (2007) ‘How costly is external financing? Evidence from a structural

estimation’, Journal of Finance, Vol. 62, pp.1705–1745. Hillier, B. (1997) The Economics of Asymmetric Information, 1st ed., MacMillan Press Ltd. Hirth, S. and Uhrig-Homburg, M. (2007) Optimal Investment Timing When External Financing

is Costly, Mimeo. University of Karlsruhe, Germany. Hoshi, T., Kashyap, A. and Scharfstein, D. (1991) ‘Corporate structure, liquidity, and investment:

evidence from Japanese industrial groups’, Quarterly Journal of Economics, Vol. 106, No. 1, pp.33–60.

Hovakimian, G. (2009) ‘Determinants of investment cash flow sensitivity’, Financial Management, Vol. 38, No. 1, pp.161–183.

Hovakimian, G. and Titman, S. (2006) ‘Corporate investment and financial constraints: sensitivity of investment to funds from voluntary asset sales’, Journal of Money, Credit, and Banking, Vol. 38, No. 2, pp.457–474.

Hubbard, R.G. (1998) ‘Capital-markets imperfections and investment’, Journal of Economic Literature, Vol. 36, No. 3, pp.193–225.

Islam, S. (2002) Investment-Cash Flow Relationship: International Evidence, PhD Thesis, Virginia Polytechnic Institute, Blacksburg, USA.

Jensen, M. and Meckling, W. (1976) ‘Theory of the firm: managerial behavior, agency costs, and ownership structure’, Journal of Financial Economics, Vol. 3, pp.305–360.

Kaplan, S. and Zingales, L. (1997) ‘Do financing constraints explain why investment is correlated with cash flow?’, Quarterly Journal of Economics, Vol. 112, No. 1, pp.169–215.

Kaplan, S. and Zingales, L. (2000) ‘Investment-cash flow sensitivities are not valid measures of financing constraints’, Quarterly Journal of Economics, pp.707–712.

Kiyotaki, N. and Moore, J. (1997) ‘Credit cycles’, Journal of Political Economy, Vol. 105, pp.211–248.

Mansour, W. (2009) On the Theory of Financing Constraints, PhD Thesis, Université de la Manouba, Tunisia, North Africa.

Modigliani, F. and Miller, M.H. (1958) ‘The cost of capital, corporation finance, and the theory of investment’, American Economic Review, Vol. 48, pp.261–297.

Moyen, N. (2004) ‘Investment-cash flow sensitivities: constrained versus unconstrained firms’, Journal of Finance, Vol. 59, pp.2061–2092.

Myers, S. (1984) ‘The capital structure puzzle’, Journal of Finance, Vol. 39, No. 3, pp.575–592. Myers, S. and Majluf, N. (1984) Corporate Financing and Investment Decisions When Firms Have

Information That Investors Do Not Have?, NBER Working Paper Series no. 1396. Stiglitz, J.E. and Weiss, A. (1981) ‘Credit rationing in markets with imperfect information’,

American Economic Review, Vol. 71, No. 3, pp.393–410.


Tirole, J. (2006) The Theory of Corporate Finance, Princeton University Press. Townsend, R. (1979) ‘Optimal contracts and competitive markets with costly state verifications’,

Journal of Economic Theory, Vol. 21, pp.265–293. Whited, M. (2006) ‘External finance constraints and the intertemporal pattern of intermittent

investment’, Journal of Financial Economics, Vol. 81, pp.467–502.

Notes 1Our theoretical set-up is primarily based on Hart (1995). 2Whited (2006) shows that the firm’s investment is characterised by lumpiness, since the firm judges it optimal to not invest to elude paying the extra-cost the non-residual claimant charges on the loanable funds.

3The most leading, distinguishable ‘teaching’ of Akerlof is showing that a situation with asymmetrical distribution of information can give rise to adversely selected markets. That is, risky borrowers may crowd out low-risky ones and take part of the same advantages. As it has been later demonstrated by Hellmann and Stiglitz (2001), three effects may occur in an adversely selected debt market. First, the price effect is brought forth by the fact that an increase in the debt price (i.e., lending rate) will increase the lender’s revenue. This effect is always positive. Second, the positive selection effect is brought forth if the lender loses entrepreneurs that are less profitable than the average, in terms of the risk–return couple. Third, the adverse selection effect is brought forth when losing entrepreneurs that are more profitable than the average.

4In concert with fact, Hovakimian argues that “Based on the interpretation proposed by Fazzari et al. (1988), investment cash flow sensitivity reflects the higher costs of external financing relative to internal financing, which may occur due to information asymmetries discussed by Myers and Majluf (1984) and Greenwald et al. (1984), or agency problems, discussed by Jensen and Meckling (1976).” (Hovakimian, 2009)

5Financing constraints are the outcome of a wedge of costs between internal and external funds. That is, financing constraints mean that the firm faces difficulties to raise external financing and thus due to the quantity credit rationing or to a large cost differential between internal and external funds. A financially distressed firm is not necessarily a financially constrained one. Indeed, the financial distress means that the firm experiences a crude shortfall in internal net worth. That is, it is in sufficiently bad shape, as claimed by Allayannis and Mozumdar (2004).

6The authors challenge the standard view by claiming that the connection between the investment-cash flow sensitivity and financing constraints depends on the classification scheme (Cleary et al., 2007).

7Moyen (2004) explains why the unconstrained firms have a higher investment-cash flow sensitivity in the following manner. Having a profitable set of investment opportunities, an average unconstrained firm issues debt, which inflates the cash flow sensitivity. Indeed, after raising debt, the firm can either increase its investment or dividends payments, which can be seen as a debt-inflating effect since not all funds are dumped into capital expenditures. In contrast, an average constrained firm is concerned with the allocation of its internal funds between investment and dividends since its access to debt is limited.

8There are two exceptions of the ex ante classification scheme. First, the endogenous switching regression approach (used among others by Hovakimian and Titman, 2006) does not require a sole criterion. It rather controls for a variety of indicators that altogether determine the regime of financing constraints to which a firm will belong. Second, the classification based on the membership into an industrial or financial group. The most cited example in the literature is the affiliation in industrial groups in Japan, which is better known as Keiretsu membership (See, for instance, Hoshi et al., 1991).

9For simplicity, we restrict the financing instruments to only debt. We further assume that the debt contract is homogeneous to elude embedding the free-riding problem.


10The standard CSV (costly state verification) problem is based on Townsend’s (1979) landmark paper.

11It is also possible to interpret ϕ in terms of private benefits à la Jensen and Meckling’s (1976) perks, i.e., appropriation of shareholders’ wealth by managers, e.g., psychic value, personal satisfaction of the entrepreneur, pecuniary benefits.

12It is obvious that the moral hazard problem precedes the CSV one since the ‘misallocation’ of the fraction ϕ is done before generating the revenue.

13See Hillier (1997). 14That is, the maximum sustainable debt level cannot exceed the upper bound of collateral with

respect to the parameter max .plgψ Some studies show that there is indeed an upper limit to the assets’ pledgeability. For instance, when studying the macroeconomic implications of limited borrowing, Kiyotaki and Moore (1997) show that some types of assets (e.g., human capital) are not perfectly appropriate and lending cannot be fully collateralised with assets. Accordingly, as in the model of Albuquerque and Hopenhayn (2004), “more lending can be sustained with the threat of depriving the borrower from its equity”.

15Equation (3) may be interpreted in terms of a quantity constraint imposed on the firm. It is possible to assume that financing becomes constrained (i.e., the firm pays an extra agency cost) if its pledgeable assets do not suffice the secured financing. So, it starts to implement costly external financing beyond that maximum sustainable cut-off, i.e., max .plgψ

16The borrowed funds in this equation amount to max ( , ),plghz R I Wψ which may be explained by the

fact that the investment only has a positive NPV in the occurrence of the high-state shock zh, as in Almeida and Campello (2007).

17We invoke here the classification of Cleary et al. (2007) for which the firm can be constrained either because its net worth slopes down or because capital markets’ borrowing conditions are tightening. This classification is consistent with Kaplan and Zingales (2000). It is, however, at odds with Fazzari et al. (2000) who consider that a firm with ample net worth is highly constrained since it chooses to construct a buffer of cash stock to overcome future downturns in available funds.

18As for Fazzari et al. (2000), they consider that a high level of net worth is symptomatic of financing constraints since the firm chooses to construct a buffer of cash stock to overcome the future, unexpected downturn in financial resources.

19In this discussion, we redefine the conditions identified by the authors using our notations. See the papers by Fazzari et al. (2000) and Kaplan and Zingales (2000) for the original notations.

20In a different result, Hirth and Uhrig-Homburg (2007) show that for high- and low-liquidity firms the sensitivities are increasing in the constraints. That is, the sensitivity is a positive function of the level of liquidity, no mind how big is its level.

21Cooper and Ejarque (2001) assume that the profit function is concave and its concavity reflects market power. They interpret the cash flow significance in terms of market power. In our case, to elude this possible interpretation, we rather imply that the functional form is convex to interpret cash flow in terms of financing constraints.

Is the investment-cash flow sensitivity still useful to gauge financing constraints?

Documents

Transcript of Is the investment-cash flow sensitivity still useful to gauge financing constraints?