Liquidity constraints, Investment and Ownership
(A Belgian high tech SMEs Panel Data Analysis)
Et-taoufik FATHI
PhD Student
Institut d’Administration et de Gestion – IAG, Université catholique de Louvain
Unité POGE
1, Place des Doyens 1348 Louvain-la-Neuve, Belgique
Tel: +32 (0) 10 47 83 53, Email: [email protected]
Benoît GAILLY
Professor
Institut d’Administration et de Gestion – IAG, Université catholique de Louvain
1, Place des Doyens 1348 Louvain-la-Neuve, Belgique
Tel: +32 (0) 10 47 84 20 Fax : +32(0) 10 47 83 24, Email: [email protected]
Abstract
The main objective of this paper is to confront theoretical and empirical results about the
determinants of investment decision of Belgian high tech SMEs. Limited research is available
regarding this subject, such as the paper of Manigart (2002) on unquoted Belgian companies,
and that of Van Cayseele (2002) on Belgian firms as a whole. We therefore believe that there
is an interest in developing this subject, which has been extensively addressed in the United
States, and to other developed countries by Fazzari, Hubbard and Petersen (1988), Rajan and
Zingales (1997, 2000) and Goergen and Renneboog (2001).
In this study, we used an accelerator – sales model to express the relationship between
investment and cash-flow. The investment is supposed, in this model, to be an increasing
function of sales, but the model does not include the company’s future growth opportunities.
Thus, a positive correlation between investment and generated liquidity is supposed to
highlight of the financing constraints. The results of our study show the existence, for the total
sample, of an direct correlation between the generated cash-flows and the level of capital
expenditures. The regressions also shows a larger and more significant coefficient in the case
of young SMEs comparatively to the oldest ones, which indicates that these young SMEs are
more affected by financing constraints.
Keywords
Fiancial constraints, High tech SMEs, Euler Equation, Investment, Accelerator-sales
model.
Liquidity constraints, Investment and Ownership
(A Belgian high tech SMEs Panel Data Analysis)
INTRODUCTION
There is an abundant literature relating to the relationship between investment policy and
cash-flow constraints in the context of large corporations. Nevertheless, little is known about
this relationship in the context of unquoted small and medium-sized enterprises. We believe
that this relationship is important to study, since this type of companies tend to be subjected to
a higher level of informational asymmetries, and thus, are supposed to be financially more
constrained.
The main objective of this paper is to confront theoretical and empirical results about the
determinants of investment decision of Belgian high tech SMEs. Limited research is available
regarding this subject, such as the paper of Manigart (2002) on unquoted Belgian companies,
and that of Van Cayseele (2002) on Belgian firms as a whole. We therefore believe that there
is an interest in developing this subject, which has been extensively addressed in the United
States, and to other developed countries by Fazzari, Hubbard and Petersen (1988), Rajan and
Zingales (1997, 2000) and Goergen and Renneboog (2001).
In this study, we used an accelerator – sales model to express the relationship between
investment and cash-flow. The investment is supposed, in this model, to be an increasing
function of sales, but the model does not include the company’s future growth opportunities.
Thus, a positive correlation between investment and generated liquidity is supposed to
highlight of the financing constraints.
The results of our study show the existence, for the total sample, of an direct correlation
between the generated cash-flows and the level of capital expenditures. The regressions also
shows a larger and more significant coefficient in the case of young SMEs comparatively to
the oldest ones, which indicates that these young SMEs are more affected by financing
constraints. This paper comprises four sections. The first section makes a review of the
empirical researchs on the dynamic behavior of investment decisions. The second section
presents the sample and define the variables of our regression. It also present the model used.
The third section presents and comments the statistics results. The fourth section draws the
conclusions.
1. Review Of The Relevant Literature
Many researchers have raised the problem of the financing constraints to which the SMEs are
subjected to justify the financial specificity of these companies. The financial literature
distinguishes three streams of research exploring this phenomenon, each one based upon a
basic assumption, which will be detailed hereafter. These streams also share a common
theoretical base, namely the fact that the imperfections (dysfunctions) of the financial market
create a disparity between the cost of the internal funds (retained benefit) and the cost of the
external funds (debt and new share issues). The presence of such disparity is often justified, in
the financial literature, by the presence of various transaction costs, such as flotation costs,
bankruptcy costs, and taxation. Some recent researches highlight the informational
asymmetries between the companies and the external suppliers of the funds to explain this
disparity. The problems of informational asymmetries accentuate the adverse selection and
moral hazard problems, which in their turn increase the cost of the external funds, thus
accentuating the credit rationing and discouraging the subscription for new share issues. This
mechanism prevent the external funds to be perfect substitute for the internal funds, which
disqualifies the famous theorem of Modigliali and Miller (1958) : the separation between
financing and investment choices.
A way of considering the relationship between the investment and financing decisions is
done, in the financial literature, by the analysis of the effects of the financing constraints on
the capital expenditures, which is commonly called : "The Investment-cash-flow sensitivity".
Indeed, the incidences of the informational asymmetries and the incitative mechanisms on the
investment were explored, recently, by several authors (Bernanke and Gertler, 1989; Gertler
and Hubbard, 1988; Calomiris and Hubbard, 1990; Gertler, 1992; Bernanke, Gertler and
Gilchrist, 1996 and 1999; Kiyotaki and Moore, 1997 and Greenwald and Stiglitz, 1988 and
1993). Although the models diverge in their details, two principal results emerge from this
literature (Galindo & Shiantarelli, 2002). First, unless the loans are entirely collateralized,
external funds remain more costly and expensive than the internal funds. Second, everything
else being equal, the premium for risk required on external funds is an inverse function of a
borrower’s net worth (assimilated to guarantees). Empirically, these models are tested on the
basis of firms samples which are supposed to be financially constrained. Several criteria are
used in the literature to categorise these companies into sub-groups according to the
likelihood of being financially constrained : the affiliation with industrial groups and banks,
the size and the dividends policy.
1.1 Three Hypothesis And One Same Logic
Carpenter, Fazzari and Petersen (1995) distinguish three different hypothesis which,
nevertheless, share the same theoretical bases:
- The bank lending hypothesis: it is mainly interested in the impact of the variations in credit
availability (monetary policy) on the financing of firms. In fact, the monetary policy can
affect, via the "broad channel of the credit", the cost differentials of the various financing
forms, mainly by influencing the net capital value of the company used as guarantee of its
loans. This mechanism is a powerful action tool of the monetary policy on firms investment,
because a weak variation of the interest rates can strongly affect the value of the collaterals,
and thus create a rationing of the credit offered to the company by the external funders.
Generally, this mechanism is namely known as "the financial accelerator of the monetary
policy" (Mairesse et al., 2001). This assumption refers to the "availability doctrine" 1 which
allots the decline of the companies activity in recession period to a fall of the bank credits
offer (Carpenter et al., 1995).
- The collateral hypothesis: it is interested in the effects of the variations of the collateral
value on the cost and availability of debts. The access to the credit will thus depend on the
firms characteristics and asset structure, which in turn will affect the firms investment
decision.
- The internal finance hypothesis: In this case, the companies are subjected to a rationing of
credit mainly because of imperfections of the financial market. The firms are constrained by
the lack of generated cash-flows. As a consequence of the unavailability of debt financing, the
investment depends, primarily, on the internal funds available..
1.2 The Importance of Generated Cashflows
Considering that financial markets are not perfect, the suppliers of funds can limit their offer
and thus profitable projects can be rejected for lack of financing. This phenomenon of
rationing is accentuated even more in the case of high tech entrepreneurial companies, which
invest enormously in specific assets such as the highly qualified human resources and R&D.
The existence of these financing constraints and their implications for the investment and
innovation at the firm level is an aspect which appears in several studies of corporate finance.
Since the Sixties, many studies have addressed this issue (Meyer and Kuh, 1957;
1
- This doctrine is a response of the monetarists to the phenomenon of low interest rate elasticity to the investments. The
basic idea it is that the efficiency of the monetary policy would be improved if the total demand is simultaneously influenced
by the interest rate (cost) and the credit offer (availability).
Duesenberry, 1958; Meyer and Glauber, 1964), but Harhoff (1997) note, nevertheless, that the
concept of "financing constraints" was developed and was explicitly put forward with the
works of Jaffee & Russell (1976), Keeton (1979) and Stiglitz and Weiss (1981). More over,
the paper of Fazzari, Hubbard and Petersen (from now FHP) of 1988 is considered, by far, to
be the first attempt to empirically test the proposals of the various theories. They initiated a
substantial empirical studies stressing the positive relationship between the firms’ generated
cash-flow and their capital expenditures (especially on fixed assets). However, there is
considerable debate about the interpretation of these empirical results. FHP consider this
positive relationship as a sign of the presence of financing constraints, while Kaplan and
Zingales (2000) interpreted this result differently; they show that this positive relationship is
still stronger in the case of the companies which, theoretically, are not likely to be subjected
to the financing constraints (Kaplan and Zingales, 1997). They explain this result by the
“excessive conservatism” of the managers who often prefer to be financed by internal funds
than by external funds (Kaplan and Zingales, 2000) and/or quite simply by a non-optimizing
behaviour regarding investment decision (Hines and Thaler, 1995).
A third explanation of this positive relationship was formulated by Jensen in 1986, namely the
so called “the theory of free cash-flow”. For Jensen, this positive relationship can reveal
problems of over-investment due to the agencies conflicts which are creaed by the separation
of ownership and control. In such context, the managers can act contrary to the interests of
shareholders and pursue other goals than maximizing the company’s value. Thus, the
managers will tend to over-invest and to adopt destroying value projects (negative NPV) as
long as these investments increase the size of the firm.
Fazzari et al. (1988) also showed that this positive relationship is stronger in the case of firms
with high growth and/or low levels of dividends. Fazzari and Petersen (1993) incorporate in
their basic model various sources of funds (especially working capital) and test the interaction
between the investment and these new financing sources. They concluded to a negative
correlation, especially between the investment and the working capital. Carpenter (1995), on
the other hand, analyses the effect of the debt variations on the investment. He finds that
firms with low growth and low rate of dividends distribution are, generally, more constrained
financially than other firms. Hoshi (1991) tests the effect of a given governance system on
this relation. He adds to the model the variables “nature” and “degree” of ownership
concentration, then tests his model in the Japanese context. He finds that firms belonging to
groups (Keiretsu) are financially less constrained than more independent companies. He
explained this result by the fact that among the members of the "Keiretsu" exists financial
institutions which easily agree to finance these firms, as they belong to the same group; the
"Keiretsu" plays, in fact, a role of informational asymmetries attenuator.
Goergen and Renneboog (2001) test their model within a specific governance framework
(Germany). They show that « the investment – cash flow sensitivity rises with increasing levels of
insider ownership ». On the basis of a sample of 198 Korean companies, Laeven (2002) shows
also that the large firms are financially more constrained than SMEs, and that the firms with a
concentrated ownership structure are financially more constrained than the firms with
dispersed ownership. He finds also that the firms belonging to “Chaebols” are more subject to
financing constraints than independent ones. In a continental Europe context (Germany)
Audretsch (2002) introduced the size of the firm and the institutional specificity to analyze the
relationship between liquidity and investment. The results show that the medium-sized
companies seem to be, financially, more constrained than smallest or largest ones. Gugler
(2003) applies a model of simultaneous equations to test this relationship in the context of
Austrian firms over the period 1991-1999; adopting the Grabowski and Mueller’s approach
(1972), he treats the investment decisions in tangible assets, the research and development,
and the dividends as jointly and simultaneously determined. The econometric results show
that ownership structure and control remains strong determinants of the firms dividend policy.
They conclude that the publicly held and controlled firms often fix a higher level of
distributed dividends than those of family businesses.
On the other side, the innovation aspect is often introduced in these studies by taking into
account, mainly in the tested econometric models, intangible investments (such as the past
R&D expenditures). Indeed, these investments are too risky and therefore hardly not used as
collateral to contract debt. Bernstein and Nadiri (1986), Hall (1992), Hao and Jaffe (1993),
Himmelberg and Petersen (1994) and Kathuria and Mueller (1995) showed that the effect of
cash-flow on the R&D investments is often positive.
1.3 The Belgian Context
Belgium has a continental Europe financial system (bank-based financial system), and often
the characteristics of such a system, opposed to the market-based financial system, make that
the relationship between the generated liquidity and the capital expenditures is affected. As
described by Van Cayseele (2002), Degryse and Jong (2001) this type of systems is
characterized by the presence of large block holdings, a reduced shareholders’ influence on
the management decisions and a relative absence of takeover defences. In such similar
system, the principal source of external funds consists of banking debts, and few firms are
quoted. This last phenomenon often implies methodological problems regarding the
implementation of some variables (such as the measurement of Tobin Q).
Barran (1998) uses an Euler equation model to estimate the relationship between liquidity and
investment of Belgian firms over the period 1984-1992; he uses the generalized moments
method (GMM:), and divided his sample into two sub-groups according to the association or
not of the company with coordination centers. He focused his analysis on the role of the
coordination centers in financing the investments and the incidence of their presence on the
relationship liquidity - investment. The empirical results showed a correlation between the
investment and the financial factors, both for the firms related to a coordination center and
for the independent firms.
Deloof (1998), on the other hand, was interested in the impact of the presence of the holdings
on this relationship for a sample of Belgian firms over the Eigthies. He finds that the holdings
and the groups play an important role in the financing of Belgian firms and that they play the
role of the substitute of the underdeveloped financial market (comparatively to the AngloSaxon markets). He concludes with the fact that the Belgian firms belonging to groups and/or
holdings are, generally, less constrained financially than other companies; a result close to
these of Hoshi (1991) in the Japanese context.
Van Cayseel (2002) adapted and extended the signalling model of Hadlock (1998) to
incorporate the takeover behaviour typical in high-tech sectors. His model both incorporates
imperfections in the capital market (asymmetric information) and managerial discretion.
Indeed, he introduced the variable "the past R&D expenditures" as a control variable for
investment opportunities. He also incorporated elements concerned with the firms governance
such as the ownership concentration and dispersion. He tested his model on a sample of
Belgian S.A. over the period going from 1994 to 1998. Van Cayseel shows that the
investment is largely predicted and explained by the R&D, the added value and the cash-flow.
In addition, He finds that the cash-flow influences more negatively the investment in
situations of concentrated ownership (the principal shareholder holds more than 50%) than in
situations of dispersed ownership (the principal shareholder holds less than 10%).
Manigart (2002) uses a modified sales accelerator model to test the relationship between
tangible investments and generated cash-flows for unquoted Belgian companies over the
period going from 1987 to 1997, while controlling the effect of the investment opportunities
by the incorporation of the past R&D expenditures. She shows that the investments in tangible
assets are positively related to the generated cash-flows. In addition, and contrary to the
common wisdom, this sensitivity is not reduced, but increased, when firms receive venture
capital. The presence of a venture capital (VC) does not reduce the financial constraints of the
Belgian firms (of the sample) as expected by the author. The idea that the VCs reduce the
"funding gap" is not confirmed, thus the firms backed by VCs remain more constrained
financially than other firms. On the other hand, the study shows that the intangible
investments (R&D) made by VC-backed firms are more important than those done by the
other firms.
In this paper, we test two hypotheses that Manigart (2002), Van Cayseel (2002) and Deloof
(1998) have already tested on a samples of Belgian firms. We will test these hypotheses in the
case of Belgian high tech companies and will incorporate in the model the governance and
control dimensions. The idea supported in this research is that the high tech sectors accentuate
the positive relationship between the generated cash-flow and the investment, an evident
consequence of the various problems of informational asymmetries and especially of the
nature of the investment which does not lend to be used as guarantee in the event of
liquidation. However, we suppose that this relationship is relatively attenuated in the presence
of specific funders (especially VCs).
Therefore, we advance the following hypothesis:
H1: The positive relationship between cash-flow and investment indicates the
presence of financing constraints, and these constraints are more intense in the case of the
young high tech companies than in the case of older ones.
H2: This relationship is deeply affected by the ownership structure. Indeed, we
suppose that:
H2-1: The positive relationship between internally generated cash flows and
investments is more attenuated in young high tech companies than in older ones. Two
reasons can be advanced to explain this fact. Firstly, the presence of VCs plays a
positive signalling role vis-à-vis the financial market, thus attenuating the
informational asymmetries between the company and the investors. Secondly, the VC
plays a "monitoring role" which reduce the over-investment problems.
H2-2: The investment is negatively correlated to the generated cash-flows in
the situation of diffused ownership structure, while in situation of concentrated
ownership structure the correlation is positive.
2. Methodology
The increasing availability of the panel data on firms in many countries has encouraged the
microeconometric studies of investment, implementing empirical specifications and different
theoritical models. Indeed, this type of data makes possible a suitable test of the longitudinal
implications of the models in the presence of informational asymmetries between the
borrowers and the lenders. The use of microeconomic data has several advantages: it
guarantees a more adequate variables measurement; the trans-sectional variations improve the
precision of the evaluations; and the potential biases resulting from the aggregation of the data
and simultaneity or problems of omitted variables can be better taken into account.
Nevertheless, the use of individual data involves also some problems: the most common is the
implicit bias problem in the composition of the samples and the short temporal dimension of
the panels.
Generally, four models are used to test the sensitivity of the capital expenditures to the
financing constraints (liquidity):
-
The neo-classical model (Jorgenson, 1963): the cost of capital is considered as the
main investment determinant, an economic principle highlighted by Keynes in 1936:
the investment is profitable as long as its return exceeds its cost. The neo-classical
model as formulated by Jorgenson (1963) allows to express the long term optimal
capital stock as that which equalizes its marginal productivity in value and its nominal
going cost (Mairesse et al.. 2001). Villieu (2000, p.26) specifies that the investment
function of Jorgenson generalizes the accelerate approach type, by giving him explicit
microeconomic bases and by integrating, beyond the demand, new investment
determinant, namely the cost of capital.
-
The sales accelerator model (Abel & Blanchard 1986) the investment is regarded as
an increasing function of the sales, but the model does not include the firm future
growth opportunities. The positive correlation between the investment and the
generated liquidity is supposed to highlight the financing constraints. Several authors
reproach to these two models the fact that they interpret the positive coefficient sign
binding the investment and the liquidity as being a sign of the financing constraints,
whereas this positive sign can clearly show an anticipation of real future profit
opportunities. In order to solve this methodological problem Abel and Blanchard
(1986) proposed their autoregressive model allowing to distinguish in the observed
profit data, the fundamental components of real profit opportunities, and on the other
hand transitory components indicating the financing constraints (Mairesse et al..
2001). In the same way, the Tobin’s Q Models have like empirical concern the
inclusion of future profitability and the capital stock level.
-
The model of Tobin’s Q: in this model future anticipations of growth and
profitability are captured by the introduction of MBR (Market to Book Ratio or
Tobin’s Q) as variable of control. Under the inter-temporal maximization assumption
of the company’s value with adjustment costs, the investment is related to a variable Q
defined as a ratio of the company’s marginal value resulting from the investment of an
additional unit of capital on the cost of this unit of capital. However, it is not easy to
implement this type of models, mainly because of measurement problems. This
problem is accentuated even more in the context of the continental Europe countries
where the majority of firms are not quoted.
-
The Euler-equation model (Bond & Meghir, 1994a,b): In the Nineties, many
attempts to estimate the investment behaviours were made according to the approach
known as the Euler equation. This equation, although derived from the inter-temporal
maximization of the company’s profits present value with explicit adjustment costs,
has the advantage of characterizing the capital stock evolution at each period without
utilizing the future anticipations. The main argument to use this methodological
approach is the fact that this model, by controlling implicitly all the anticipated
influences, is less affected by usual criticism on the excessive sensitivity of the
investment to the cash-flow. This model takes into account the informational
asymmetries between the lenders and the borrowers thus revealing the influence of the
financial position of the agents on the conditions of access to the external finance (cost
and availability), and also takes into account the introduction of the financial variables
into the investment equations, such as the generated cash flows and the firms’ debt
level.
In this study we use a sales accelerator model to express the relationship between investment
and cash-flow. Our basic model is as follows:
⎛ CF ⎞
⎛S⎞
⎛D⎞
⎛I ⎞
⎛I ⎞
+ α3⎜ ⎟
+α4⎜ ⎟
+ ψ t + ϕ i + ε it
+α2⎜
⎜ ⎟ = α1 ⎜ ⎟
⎟
⎝ K ⎠ it
⎝ K ⎠ i ,t −1
⎝ K ⎠ i ,t −1
⎝ K ⎠ i ,t −1
⎝ K ⎠ i ,t −1
In order to keep the possibility of a comparison with the results of other studies undertaken in
other countries, we adopted the same variables measures as those used by Bond & Meghir
(1994) and Goergen & Renneboog (2001):
I : investment of firm i in period t in tangible fixed assets
K : beginning-of-year net fixed assets or capital stock
CF : cash-flow
S : sales
D : debt
ψt : time-specific effects
φi : firm-specific effects
εit : disturbance term
3. The Data and The Empirical Results
3.1 Data
Belgian firms have to publish their annual report in a standardized note established by the
National Bank of Belgium,
These reports are annually published under a data-processing support (the Belfirst database).
This database contains accounting information of some 270.000 Belgian and Luxembourg
companies.We used this database to constitute our data sample for the empirical part of our
study. As we are interested only on high tech SMEs, we have make several selections and
cleanings to obtain our final sample.
The first step of our work consisted in selecting only the companies concerned with the high
tech sectors. The criterion applied is that applied by several researchers and in particular, S.
Walcott (2001), and consisting in making the selection on the basis of the compagnies’ SIC
code (Standard Industrial Code, see Appendix 1). The second step consisted in retaining in
our sample only the SMEs. For that, we used the European Commission’s criteria, namely the
companies which have a turnover lower than 40 million euros, a maximum of 250 employees
and who are independent. However, considering the nature of the database this last criterion
was not taken into account.
For the needs of the analysis, we removed all the companies which did not declare their fixed
assets stock (variable K), we imposed also a non-negative minimal limit on this variable to
avoid errors related to the encoding. We also removed of the sample all the companies having
negative debt ratios (a negative ratio means that the debt is negative, which can be granted
only to errors of encoding). After this cleaning, our final sample consists of 310 companies,
and our period of study goes from 1992 to 2002. Tables 1 and 2 show descriptive statistics of
our sample.
We used the OLS technique on one period lagged data to estimate our model. Initially, we
tested the equation using the total sample, then we distinguished our sample into two subgroups according to the age of the companies. The first group, that we called young SMEs
(JPME), includes all companies aged of less than 10 years. The second group, the aged SMEs
(NJPME), includes all companies aged of more than 10 years.
3.2 Empirical Results
This section discuss the main results obtained and will put them into the more general context
of the literature. Table 1 summarizes the descriptive statistics of the sample variables. Table 2
presents the results of the estimation of the investment equation, respectively for the whole
high tech SMEs (SME), the young high tech SMEs (JPME) and the old high tech SMEs
(NJPME).
High tech SMEs
The results show that the obtained coefficients correspond to the forecasts of the previous
studies in the field. The CF is positively correlated to the investment (0.056) and statistically
significant, a perfectly coherent result with the theoretical predictions. These results enable us
to confirm our basic assumption, namely the fact that high tech SMEs are confronted to
financing constraints. The turnover’s coefficient is also consistent with the theoretical
forecasts. The positive and statistically significant coefficient (0.031) shows the evidence of a
positive impact of the sales on the investment, indeed it has as much impact on investment
than cash-flow.
The debt is negatively correlated with investment (0.033), which is against the theoretical
predictions. We explain this result by the composition of this variable. To build the variable
we considered all the LT debts (commercial and financial debt) and we can hypothesize that the
two components of this variable are compensated and act in two different and opposed
directions. The majority of the studies which find a negative coefficient use only the LT
financial debt (from banks) as explanatory variable.
Young high tech SMEs
Theoretically, these firms are supposed to be subject to higher financial constraints than the
old ones, which would statistically imply a larger regression coefficients. The statistical
results corroborate this confirmation, indeed, the CF coefficient takes a positive sign (0.088)
and remains statistically significant. The value of this coefficient is clearly higher than that of
the coefficients relating to the total sample of SMEs and to the sample of old SMEs. This
result corroborates our assumption that young high tech SMEs are more confronted financing
constraints than others firms. In addition, the coefficient attached to S keeps a positive sign
(0.049), in accordance with the theory, and remains statistically significant. The debt
coefficient is also positively correlated with the investment but remains statistically nonsignificant.
Old high tech SMEs
The results show that all the coefficients signs are conform to the theoretical predictions and
remain statistically significant except for the S. The positive value of the CF coefficient shows
a positive impact of CF on the investment, but its value remains clearly lower than that
relative to young SME. In addition, the estimates show the positive impact of the sales on the
investment even if it remains statistically non-significant. The debt coefficient is positive,
which is not compatible with the theoretical predictions. We can hypothesize that the
composition of this variable (commercial and financial debt) makes that the result is so. A
comparison of the results indicates that young high tech SMEs are more confronted to
financing constraints than old high tech SMEs.
Conclusion and future research
The present paper has shed further light on the investment cash-flow sensitivity by focussing
on Belgian data. The empirical results show that high tech SMEs are confronted to serious
financing constraints. On the other side, the results show that the young high tech SMEs face
more financing constraints than the old ones. this can be explained by several factors: because
of the high risk which presents the investment in such firms at start-up stage, the absence of a
track record to evaluate them and of the weakness of the internal generated cash flows.
In this study we did not control the effect of the future investment opportunities. We intend to
incorporate to the model the past R&D expenditures (R&D/stock of capital) (Manigart, 2002)
as measure of the firm’s future growth and profitability (Van Cayseele, 2002; Titman &
Wessels, 1988). To take into account the effect of the ownership structure and the presence of
specific funders (VC especially) on the relationship investment - cash-flow, we intend to
incorporate to the model dummies relating to the percentages of the shares held by the various
shareholders and relating to the presence or not of the VC among the firm’s fund suppliers.
The variable (VC * CFit)/Ki,t-1 will measure the effect of the presence of VCs on the investment
- cash-flow relationship (VC is a dummy taking value 1 if the firm is financed by VCs and 0 if
not).
The ownership structure (concentration/dispersion) influences also the investment - cash-flow
relationship. We will measure the ownership concentration/dispersion by the percentage of
the shares held by the principal owner. The variable (PP(j) * CFit)/Ki,t-1 will measure the effect
of the concentration/dispersion of the ownership on this relationship, with J = 10, 49 and 50.
Indeed, PP10 means that the principal shareholder holds less than 10% (largely dispersed
ownership); PP49 means that the principal shareholder holds more than 10% but less than
50% (dispersed ownership) and PP50 means that the principal shareholder holds more than
50% (concentrated ownership).
Our final model to test in a future research will therefore be as follows:
⎛ I In tan g
⎛I ⎞
⎛I ⎞
+ α2⎜
⎜ ⎟ = α1⎜ ⎟
⎜ K
⎝ K ⎠it
⎝ K ⎠i,t −1
⎝
⎞
⎛ CF ⎞
⎛S⎞
⎛ D⎞
⎟
+ α3⎜
+ α4⎜ ⎟
+ α5 ⎜ ⎟
+
⎟
⎟
K ⎠i,t −1
K ⎠i,t −1
K ⎠i,t −1
⎝
⎝
⎝
⎠i,t −2
⎛ ( PPj * CF ) ⎞
⎛ (VC * CF ) ⎞
⎟
+ α7 ⎜
+ ψ t + ϕi + ε it
⎟
⎜
⎟
K
K
⎝
⎠
i
t
−
,
1
⎝
⎠i,t −1
α6 ⎜
The results presented in this paper have policy implications. If small high tech firms are
financially constrained and usually prefer using retained profits to raising debt finance, the
challenge for policy makers is to facilitate conditions under which owner-managers are able to
retain sufficient profits in their businesses to internally fund projects with positive net returns
(Heshmati, 2001). Therefore, industrial policies that provide incentives to retain profits and
encourage investment in growth-oriented strategies are important instruments perhaps with
major impacts on the capital structure and the investment policy of small high tech firms.
Another important area for policymakers is to improve the attitude of bank managers towards
small high tech businesses, still the principal source of external funds consists, in the
continental Europe systems, of banking debts, and few firms are quoted.
Table 1: Descriptive statistics of the sample
I/K
CF
S
D
Mean
0.3640
5.0063
0.5310
0.7861
Std. Dev.
Maximum
6.6667
77.000
20.500
67.250
Minimum
0.0000
0.0000
0.0000
0.0000
CF
S
D
1
0.172676
0.101013
1
0.076862
1
0.5276
0.5276
2.1772
3.9010
Table 2: The correlation Matrix
I/K
CF
S
D
I/K
1
0.270530
0.123442
0.069502
Table 3: Results of panel data analyses for the young, old and total SMEs sample
⎛ S ⎞
⎛D ⎞
⎛ I ⎞
⎛ I ⎞
⎛ CF ⎞
+ α 3⎜
⎟ + α5⎜
⎟ + ε it
⎜
⎟ = α1 + α 2⎜
⎟
⎟ + α4⎜
⎝ K ⎠ it
⎝ K ⎠ i ,t −1
⎝ K ⎠ i ,t
⎝ K ⎠ i ,t
⎝ K ⎠ i ,t
(I/K)i,t (PME)
0.105***
(I/K)i,t-1
(0.023)
4.51
0.056***
CFi,t
(0.004)
11.69
0.031
Si,t
(0.010)
2.84
0.033
D i,t
(0.012)
2.72
N observations
3100
R-squared
0.1057
Adjusted
R- 0.1037
squared
(I/K)i,t (NJPME)
0.080***
(0.026)
3.06
0.042***
(0.005)
4.51
0.017
(0.012)
1.38
0.045***
(0.012)
3.68
1881
0.0872
0.0842
(I/K)i,t (JPME)
0.132
(0.045)
2.93
0.088***
(0.010)
8.57
0.049
(0.020)
2.41
0.004
(0.029)
0.15
1220
0.1507
0.1448
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ANNEXE I: Source: The Bureau of the Census (www.census.gov) 2 et Susan Walcott (2001).
Code SIC
2833
2834
2835
2836
3571
3572
3575
3577
3578
3579
361
3651
3652
3661
3663
3669
3671
3672
3674
3675
3676
3677
3678
3679
3721
3724
3728
3761
3764
3769
3812
3821
3822
3823
3824
3825
3826
3827
3829
3841
3842
3843
3844
3845
3861
4812
4813
4822
4841
4899
7371
7372
7373
7374
7375
7376
7377
7378
7379
8711
8712
8713
8731
8732
8733
8734
2
Catégorie
Medicinal Chemicals and Botanical Products
Pharmaceutical Preparations
In Vitro and In Vivo Diagnostic Substances
Biological Products, Except Diagnostic Substances
Electronic Computers
Computer Storage Devices
Computer Terminals
Computer Peripheral Equipment, NEC
Calculating and Accounting Machines, Except Electronic Computers
Office Machines, NEC
Electrical and electronic equipment
Household Audio and Video Equipment
Phonograph Records and Prerecorded Audio Tapes and Disks
Telephone and Telegraph Apparatus
Radio and Television Broadcasting and Communications Equipment
Communications Equipment, NEC
Electron Tubes
Printed Circuit Boards
Semiconductors and Related Devices
Electronic Capacitors
Electronic Resistors
Electronic Coils, Transformers, and Other Inductors
Electronic Connectors
Electronic Components, NEC
Aircraft
Aircraft Engines and Engine Parts
Aircraft Parts and Auxiliary Equipment, NEC
Guided Missiles and Space Vehicles
Guided Missile and Space Vehicle Propulsion Units and Propulsion Unit Parts
Guided Missile Space Vehicle Parts and Auxiliary Equipment, NEC
Search, Detection, Navigation, Guidance, Aeronautical, & Nautical Systems and Instruments
Laboratory Apparatus and Furniture
Automatic Controls for Regulating Residential & Commercial Environments and Appliances
Industrial Instruments for Measurement, Display, and Control of Process Variables
Totalizing Fluid Meters and Counting Devices
Instruments for Measuring and Testing of Electricity and Electrical Signals
Laboratory Analytical Instruments
Optical Instruments and Lenses
Measuring and Controlling Devices, NEC
Surgical and Medical Instruments and Apparatus
Orthopedic, Prosthetic, and Surgical Appliances and Supplies
Dental Equipment and Supplies
X-Ray Apparatus and Tubes and Related Irradiation Apparatus
Electromedical and Electrotherapeutic Apparatus
Photographic Equipment and Supplies
Radiotelephone Communications
Telephone Communications, Except Radiotelephone
Telegraph and Other Message Communications
Cable and Other Pay Television Services
Communications Services, NEC
Computer Programming Services
Prepackaged Software
Computer Integrated Systems Design
Computer Processing and Data Preparation and Processing Services
Information Retrieval Services
Computer Facilities Management Services
Computer Rental and Leasing
Computer Maintenance and Repair
Computer Related Services, NEC
Engineering Services
Architectural Services
Surveying Services
Commercial Physical and Biological Research
Commercial Economic, Sociological, and Educational Research
Noncommercial Research Organizations
Testing Laboratories
- This list includes all the activities known as "high-intensive technology sectors". "They are defined as being industries
requiring a proportion higher than the average as a personnel of R&D, and an investment higher than the sectoral average in
R&D. These activities are included as a "high-tech" by at least 2 out of 6 nongovernmental sources (AEA, Milken
Carryforward, Office of Labor Statistics, Organization of the European Community Division OECD, Office of the Census,
Office of Management and Budget)"(Susan Mr. Walcott, 2001).