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Carmen Martínez-Carrascal and Annalisa Ferrando

THE IMPACT OF FINANCIAL POSITION

ON INVESTMENT: AN ANALYSIS FOR

NON-FINANCIAL CORPORATIONS

IN THE EURO AREA

2008

Documentos de Trabajo

N.º 0820

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THE IMPACT OF FINANCIAL POSITION ON INVESTMENT: AN ANALYSIS FOR NON-FINANCIAL CORPORATIONS IN THE EURO AREA

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THE IMPACT OF FINANCIAL POSITION ON INVESTMENT:

AN ANALYSIS FOR NON-FINANCIAL CORPORATIONS

IN THE EURO AREA

(*)

Carmen Martínez-Carrascal

(**)

BANCO DE ESPAÑA

Annalisa Ferrando

(***)

EUROPEAN CENTRAL BANK

Documentos de Trabajo. N.º 0820

(*) Acknowledgements: This paper was to a large extent conducted while Carmen Martínez-Carrascal was wor-king at the ECB. It has benefited from discussions with I. Hernando, M. C. Sánchez Carretero and P. Vermeulen and comments from an anonymous referee, from M. Andersson, C. Barceló, F. Drudi and the participants at the Workshop on Corporate Balance Sheet Data held at the ECB, at the XI Encuentro de Economía Aplicada and in an internal seminar in the Capital Markets and Financial Structure Division at the ECB. We also want to thank A. Dalamangas and S. Scopel for their help with the data. The views expressed are those of the authors and should not be attributed to the Banco de España or to the European Central Bank.

(**) Corresponding author. Servicio de Estudios, Banco de España. Alcalá, 50, 28014 Madrid, Spain. E-mail:

[email protected].

(***) Directorate Monetary Policy, European Central Bank, Kaiserstrasse 29, 30611, Frankfurt am Main, Germany. E-mail: [email protected].

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The Working Paper Series seeks to disseminate original research in economics and fi nance. All papers have been anonymously refereed. By publishing these papers, the Banco de España aims to contribute to economic analysis and, in particular, to knowledge of the Spanish economy and its international environment.

The opinions and analyses in the Working Paper Series are the responsibility of the authors and, therefore, do not necessarily coincide with those of the Banco de España or the Eurosystem.

The Banco de España disseminates its main reports and most of its publications via the INTERNET at the following website: http://www.bde.es.

Reproduction for educational and non-commercial purposes is permitted provided that the source is acknowledged.

© BANCO DE ESPAÑA, Madrid, 2008 ISSN: 0213-2710 (print)

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Abstract

This paper analyses the impact that fi rms’ fi nancial position has on investment decisions using panel data from a large sample of non-fi nancial corporations (around 120,000 fi rms) in six euro area countries (Belgium, Germany, France, Italy, the Netherlands and Spain). The results indicate that fi nancial position is important to explain capital expenditures, as fi nan-cial pressure appears relevant in explaining investment dynamics when it is proxied by cash

fl ow, indebtedness and debt burden. The results also show differences in the sensitivity of investment rates to changes in fi nancial pressure across countries, which appears to be especially large in the Netherlands and Italy and relatively small in Germany.

Keywords: fi nancial pressure, fi xed investment, balance sheet channel, panel data.

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Non-technical summary

Financial frictions can amplify the impact of changes in interest rates on economic

ac-tivity. Accordingly, understanding the way in which nancial conditions aect rms’ demand

of productive factors becomes relevant for an optimal design of monetary policy. In addition,

in the context of the euro area, the knowledge of potential dierences in the investment rate

sensitivity to changes in rms’ nancial position across countries or across dierent types of

rms is crucial for a better understanding of the impact of a single monetary policy.

This paper investigates the sensitivity of investment rates to changes inrms’nancial

position, using a large sample of non-nancial corporations in six major euro area countries

(Belgium, Germany, France, Italy, the Netherlands and Spain). We proxy nancial pressure

using three nancial ratios: protability, net indebtedness and the interest rate burden. The

expected relationship between therstnancial ratio and investment activity is positive:

nanc-ing constraints resultnanc-ing from asymmetric information problems imply thatrms tend to invest

more when they have more internal resources available. As for the indebtedness ratio, although

debt may have some desirable properties (it allowsnancing projects in the absence of internal

resources), the commitment to repay the debt may have a negative in uence onrms’ spending

decisions (it might make it more di!cult for rms to access additional credit to nance new

investment projects). The third ratio measuresrms’ capacity to meet interest payments with

their earnings, and is also expected to present a negative relationship with investment rates.

The results show thatrms’nancial position is important to explain their capital

ex-penditures since the threenancial ratios considered are found to be signicant when included in

an investment equation: indebtedness and debt burden are found to exert a negative impact on

investment, while cash ow is positively linked to it. Wend a certain degree of heterogeneity

across countries in the magnitude of this impact: rms in the Netherlands and Italy are found

to be the ones with the highest marginal impact ofnancial pressure on investment rates, while

the lowest has been found for Germanrms.

In the paper we also give an insight on how, by altering thenancial pressure experienced

byrms in servicing their debt, monetary policy may operate through the corporate sector. A

simple exercise quanties how much investment rates change across countries, ceteris paribus,

due to an increase in the cost of debtnancing. Overall, taking into consideration our estimates

on the sensitivity of investment to changes in the debt burden and the levels of this ratio in each

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1

Introduction

The analysis of thenancial position of non-nancial corporations and their responses to

nan-cial pressure are important elements in any assessment of the macroeconomic outlook, asrms’

nancial situation can conditionrms’ real decisions. For example, excessive indebtedness or a

high debt-service burden can have an adverse eect on investment spending, thereby

contribut-ing to deepen recessions or to delay or dampen upturns. Accordcontribut-ingly, understandcontribut-ing the way

in which nancial conditions aect rms’ demand of productive factors -and more specically

investment, which represents 20% of euro area GDP- becomes relevant for an optimal design of

monetary policy. In addition, in the context of the euro area, the knowledge of potential di

er-ences in the investment rate sensitivity to changes in rms’ nancial position across countries

or across dierent types of rms is crucial for a better understanding of the impact of a single

monetary policy.

As has been widely emphasized in the literature, credit market imperfections such as asymmetric information problems result in a wedge between the cost of funds raised externally (by issuing equity or debt) and funds generated internally (retained earnings). This wedge (the

externalnance premium) will depend on the borrowernancial position (for example, it can

depend on the level of net wealth that can be provided as collateral), resulting inrmnancial

situation being relevant in determining its investment decisions. As the balance sheet channel

literature emphasizes, the existence of this external nance premium implies that monetary

policy will be transmitted to rms not only through the traditional interest rate channel, but

also through the impact it has on this premium: higher interest rates increase debt servicing

payments, erode cash ow and reduce collateral values, something that increases the external

nance premium and squeezesrm demand for loans (thenancial accelerator mechanism).

From the seminal paper by Fazzariet al. (1988), most of the discussion on the impact of

credit market imperfections on corporate investment has relied on the analysis of the response

of capital expenditures to cash ow. The basic working hypothesis behind this strand of the

nancing constraints literature is that this response should be higher rms that face a larger

wedge between the cost of internal and external funds. However, much less work has been done

on the analysis that variables such as indebtedness or debt burden have on rms’ spending

decisions.

This paper analyses howrms’ nancial position aects their investment decisions. It

makes two contributions to the existing literature on this area. First, dierently from most

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focus on investment sensitivity to cash ow ratios but also on the impact of changes in debt burden and indebtedness on capital expenditures. Second, our analysis is based on a large panel

dataset with a high percentage of small and medium sizedrms (over 85% in four out of the

six countries considered -Belgium, France, Germany, Italy, the Netherlands and Spain, which

broadly represent 90% of euro area GDP-), which are in fact those thought to be more aected

by asymmetric information problems and hence are likely to face a higher external nance

premium. In contrast, much of the existing empirical work has been based on datasets with a

high proportion of large rms, which are likely to suer less from informational asymmetries

and have a better access to capital markets.

Looking at the results, we conclude thatrms’nancial position is important to explain

their capital expenditures: indebtedness and debt burden are found to exert a negative impact

on investment, while cash ow is positively linked to it. Wend a certain degree of heterogeneity

across countries in the magnitude of this impact: rms in the Netherlands and Italy are found

to be the ones with the highest marginal impact ofnancial pressure on investment rates, while

the lowest has been found for Germanrms.

The rest of the paper is structured as follows. Section 2 reviews the existing literature on

the link betweenrms’ investment decisions andnancial factors. Section 3 describes the data

used. Section 4 provides a descriptive analysis on the relationship between investment rates

and rms’ nancial position. Section 5 presents the model and the estimation method, and

the results are shown in Section 6. The potential reasons behind the dierences in the results

across countries are presented in Section 7. Finally, Section 8 summarises the main results and concludes.

2

Review of the literature

In the past years, a large body of the literature has provided robust empirical evidence that

nancial factors have a signicant impact on rms’ investment decisions. While traditional

research on investment was based on the neoclassical theory of optimal capital accumulation

(where, under the assumption of perfect capital markets, the cost ofnancing does not depend

on the rm’ nancial position), more recent literature has increasingly incorporated frictions

such as asymmetric information and agency problems as a source behind the relevance of the

degree of nancial pressure faced by the rm in determining the availability and the costs of

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while the typical Italian rm shows the highest one, in line with the higher indebtedness and

lower protability ratios observed in this country. Dierences in the debt structure of rms are

also playing a role in explaining debt burden dispersion across countries. For example, Italian

rms have traditionally relied on expensive short-term debtnancing, something that probably

contributes to their higher debt burden ratios (although this has changed in the recent years, when they have importantly reduced the weight of short-term debt on their liabilities). Likewise, the comparatively high reliance on inter-company loans in Belgium -a source of funds cheaper than bank loans- probably contributes to explain the relatively low debt burden observed in this

country. Non-nancial corporations in Germany are those more dependent on bank loans, while

French companies are those that rely comparatively more on securities other than shares as a

source of externalnancing2.

To sum up, Italy is the country in which the position of the medianrm seems

compar-atively weaker while the strongest position is observed for Frenchrms, which are characterised

by the lowest levels of indebtedness and interest burden and by relatively high growth rates of

sales and high protability and investment ratios.

4

The impact of

nancial variables on

rms’ investment

decisions: descriptive evidence

The descriptive analysis of the previous section has shown that there exists a noticeable

hetero-geneity in thenancial variables under consideration across countries not only in their

develop-ment over time but also in their levels. A key question to analyse is whether these dierences in

nancial position are going to have an impact onrms’ spending decisions and, more specically,

onrms’ investment rates.

A simple way to obtain some preliminary evidence about hownancial pressure aects

rms’ investment is to plot how the investment rate varies in each country acrossrms facing

dierent degree ofnancial pressure. For this purpose, Charts 6, 7 and 8 compare the median

level of the investment rate in each country for three dierent corporate groupings, which are

dened on the basis of their nancial position. The latter is proxied by cash ow (Chart 6),

indebtedness (Chart 7) and debt burden (Chart 8).

In particular, the dierent panels in Chart 6 present the median investment rate in each

2See Task Force of Monetary Policy Committee of the ESCB (2007) for a description of the liability composition of non-nancial corporations’ balance sheets in euro area countries in the period 1995-2005.

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country forrms with high cash ow -over assets- (above the 90th percentile), medium cash ow

(rms for which this ratio stands between the 45th and the 55th percentile) and low cash ow

(lower decile). As can be seen, there is a clear relationship between prots generated andrms’

capital demand, asrms with higher level of cash ow over their assets show higher investment

rates.

Chart 7 depicts the median investment rates forrms facing dierent degrees ofnancial

pressure when it is measured by the indebtedness level3. Although debt may have some desirable

properties (it allows nancing projects in the absence of internal resources), the commitment

to repay the debt may have a negative in uence onrms’ spending decisions. The descriptive

evidence shown in the chart points in this direction for Belgium, Germany and France, since

investment rates present a negative relationship with indebtedness. In the two rst of these

countries, a non-linear relationship seems to exist between indebtedness and investment rates,

since there are not marked dierences in investment rates for rms with a moderate and low

level of indebtedness while for highly indebted rms their demand for capital is substantially

lower. In Italy, the Netherlands and Spain the relationship derived from this descriptive analysis seems to be less clear-cut.

Chart 8 compares the investment rates using the relative burden of debt as a proxy for

nancial pressure. Firms with a higher debt burden in relation to their capacity to generate funds

have substantially lower investment rates in all countries. This simple descriptive analysis also indicates that in some countries (especially Belgium, the Netherlands and Spain, and somewhat

less clearly, Italy) the relationship betweennancial pressure and investment might be non-linear,

as no marked dierences in investment rates are observed between thoserms with the lowest

nancial pressure and those with average nancial pressure, while rms facing a high degree

of nancial pressure show substantially lower investment rates. This hypothesis has already

been tested in Hernando and Martinez-Carrascal (2008) for a dierent sample of Spanishrms,

where evidence supporting a non-linear relationship between investment and nancial position

was found.

Overall, this descriptive evidence suggests that nancial pressure can negatively aect

rms’ capital demand. The existence of a link betweennancial position andrms’ investment

rates becomes especially clear when nancial pressure is proxied by means of protability and

debt burden. The relationship becomes somewhat more blurred when the relationship between

3As in the analysis presented for protability,rms in three dierent deciles (the 10% ofrms with the lowest indebtedness, those for which this ratio stands between 45th and 55th percentiles of the distribution and, those in the higher decile) are considered.

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Table 1. Summary statistics

Belgium France Germany Italy the Netherlands Spain I/K investment rate mean 0.150 0.170 0.123 0.176 0.156 0.172 median 0.113 0.116 0.093 0.132 0.129 0.118

ǻy sales growth mean 0.015 0.023 0.017 0.000 0.019 0.030 median 0.020 0.023 0.018 0.008 0.018 0.029

(D-L)/A net indebtedness mean 0.517 0.433 0.563 0.623 0.512 0.475 median 0.529 0.449 0.551 0.661 0.528 0.499

db interest debt burden mean 0.198 0.183 0.291 0.318 0.186 0.267 median 0.115 0.093 0.176 0.222 0.120 0.176

CF/A profitability mean 0.073 0.089 0.069 0.054 0.097 0.083 median 0.065 0.078 0.067 0.042 0.090 0.071

Number of firms 3425 43880 532 27607 658 45880

Number of observations 26504 332082 3637 205406 4974 336001 Quoted firms in % of total firms 0.6 0.3 11.8 0.1 7.9 0.1 SMEs in % of total firms 86.6 96.2 35.7 96.8 35.1 98.2 Sectors (% firms)

Construction 8.4 11.1 6.2 6.1 5.6 12.2

Manufacturing 34.3 24.2 22.0 46.4 35.0 31.5

Services 15.4 24.9 30.5 9.0 10.8 17.8

Trade 33.2 34.1 11.8 33.5 36.8 31.8

Electricity, gas, water supply, 8.7 5.8 29.5 5.0 11.9 6.8 transport, storage and

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Table 2. Baseline specification

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error (I/K)it-1 0.168 0.127 -0.116 0.118 0.357 0.162** -0.065 0.170 0.041 0.128 0.203 0.148 (∆y)it 0.072 0.064 0.095 0.060 0.311 0.149** 0.430 0.126*** 0.078 0.088 0.100 0.086 (∆y)it-1 0.078 0.035** 0.091 0.034*** 0.146 0.189 -0.107 0.132 0.178 0.060*** 0.192 0.122 (k-y)it-1 -0.069 0.030** -0.060 0.026** -0.078 0.050 -0.099 0.055* -0.148 0.055*** -0.072 0.033** M1 M2 Sargan 0.00 0.17 0.64 0.00 0.05 0.10

Notes: All equations include time and sectoral dummies.Estimated coefficients and asymptotic robust standard errors reported. Estimation by GMM-SYSTEM estimator using the robust one-step method (Blundell and Bond, 1998; Arellano and Bond, 1998). Sargan is a Sargan Test of over-identifying restrictions (p-value reported). Mjis a test of jth-order serial

correlation in the first-differenced residuals (p-values reported). Instruments: in first-differences equation, following lagged values of the regressors: Belgium: (I/K) (t-5, t-6),ǻy (t-2 to t-4) (k-y) (t-4 to t-6); Germany: (I/K) (t-4),ǻy (t-2 to t-4) (k-y) (t-3 to t-5); France: (I/K) (t-6 to t-7),ǻy (t-6) (k-y) (t-5 to t-6); Italy: (I/K) (t-7),ǻy (t-6, t-7) (k-y) (t-5 to t-6); Netherlands: (I/K) (t-4, t-5),ǻy (t-2 to t-4) (k-y) (t-3 to t-4); Spain (I/K) (t-7),ǻy (t-6) (k-y) (t-6 to t-7). In levels equations, first differences of the regressors dated as follows: Belgium:ǻy (t-3); Germanyǻy (t-4); Franceǻy (t-5); Italyǻy (t-5); Netherlands:ǻy (t-4); Spain:ǻy (t-5).*,**,*** indicate significance at 10%,5% and 1% significance level, respectively. 0.16 0.80 0.00 0.00 0.23 0.07 0.00 0.17 0.15 0.00 0.30 0.738

Italy Netherlands Spain Belgium Germany France

Table 3. Baseline specification plus cash flow ratio (CF/A)

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error (I/K)it-1 0.180 0.127 -0.141 0.102 0.142 0.142 -0.105 0.171 0.112 0.099 0.265 0.140* (∆y)it 0.005 0.056 0.046 0.059 0.357 0.097*** 0.470 0.099*** 0.100 0.077 0.120 0.089 (∆y)it-1 0.037 0.027 0.063 0.031** 0.162 0.113 -0.143 0.124 0.105 0.040*** 0.237 0.093** (k-y)it-1 -0.044 0.021** -0.043 0.021** -0.112 0.048** -0.061 0.039 -0.090 0.032*** -0.041 0.023* (CF/A)it-1 0.487 0.174*** 0.275 0.160* 0.541 0.175*** 0.599 0.338** 0.373 0.209* 0.327 0.159** M1 M2 Sargan France Germany Spain 0.00 0.23 0.00 0.12 0.00 0.00 0.00 Netherlands Italy 0.00 0.15 0.77 Belgium 0.16

Notes: All equations include time and sectoral dummies. Estimated coefficients and asymptotic robust standard errors reported. Estimation by GMM-SYSTEM estimator using the robust one-step method (Blundell and Bond, 1998; Arellano and Bond, 1998). Sargan is a Sargan Test of over-identifying restrictions (p-value reported). Mjis a test of jth-order serial

correlation in the first-differenced residuals (p-values reported). Instruments: in first-differences equation, following lagged values of the regressors: Belgium: I/K (t-5, t-6),ǻy (2 to t-4), (k-y) (t-4 to t-6), CF/A (t-4, t-5); Germany: I/K (t-t-4),ǻy (t-2 to t-4) (k-y) (t-3 to t-5) CF/A (t-4 to t-6); France: I/K (t-6 to t-7),ǻy 6), (k-y) 5 to t-6), CF/A 4, t-5); Italy: I/K (t-7),ǻy (t-6, t-7), (k-y) (t-5 to t-6); Netherlands: I/K (t-4, t-5),ǻy (t-2 to t-4), (k-y) (t-3 to t-4) CF/A (t-4, t-5); Spain I/K (t-7),ǻy (t-6), (k-y) (t-6 to t-7), CF/A (t-5). In levels equations, first differences of the regressors dated as follows: Belgium:ǻy (t-3) and CF/A (t-5); Germanyǻy (t-4), CF/A (t-4); Franceǻy (t-5); Italyǻy (t-5), CF/A (t-3); Netherlands:ǻy (t-4), CF/A (t-3); Spain: ǻy (t-5), CF/A (t-3). *,**,*** indicate significance at 10%,5% and 1% significance level, respectively.

0.14 0.65 0.37 0.18 0.09 0.32 0.12

Table 4. Baseline specification plus indebtedness ratio ((D-L)/A)

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error (I/K)it-1 0.172 0.095* -0.139 0.108 0.159 0.123 0.049 0.121 0.030 0.091 0.203 0.140 (∆y)it 0.087 0.052 * 0.100 0.052* 0.489 0.125*** 0.536 0.076*** 0.158 0.077** 0.114 0.081 (∆y)it-1 0.081 0.025*** 0.096 0.033*** 0.337 0.150** -0.184 0.128 0.143 0.036*** 0.179 0.110 (k-y)it-1 -0.070 0.020*** -0.060 0.026** -0.049 0.016*** -0.059 0.016*** -0.096 0.028*** -0.074 0.029** ((D-L)/A)it-1 -0.055 0.031 * -0.022 0.115 -0.058 0.021*** -0.075 0.036** -0.109 0.081 -0.055 0.025** M1 M2 Sargan France Germany Spain 0.00 0.07 0.00 0.73 0.00 0.00 0.00 Netherlands Italy 0.00 0.22 0.87 Belgium 0.12

Notes:All equations include time and sectoral dummies. Estimated coefficients and asymptotic robust standard errors reported. Estimation by GMM-SYSTEM estimator using the robust one-step method (Blundell and Bond, 1998; Arellano and Bond, 1998). Sargan is a Sargan Test of over-identifying restrictions (p-value reported). Mjis a test of jth-order serial

correlation in the first-differenced residuals (p-values reported). Instruments: in first-differences equation, following lagged values of the regressors: Belgium: I/K (t-5, t-6),ǻy (2 to t-4), (k-y) (t-4 to t-6), (D-L)/A (t-3 to t-5); Germany: I/K (t-t-4),ǻy (t-2 to t-4), (k-y) (t-3 to t-5), (D-L)/A (t-3 to t-5); France: I/K (t-6, t-7),ǻy (t-6), (k-y) (t-5, t-6), (D-L)/A (t-4, t-5); Italy: I/K (t-7),ǻy (t-6, t-7), (k-y) (t-5, t-6) (D-L)/A (t-5); Netherlands: I/K (t-4, t-5),ǻy (t-2 to t-4), (k-y) (t-3, t-4), (D-L)/A (t-3 to t-5); Spain I/K (t-7),ǻy (t-6), (k-y) (t-6, t-7). In levels

0.133 0.89 0.05 0.30 0.353 0.39 0.056

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Table 5. Baseline specification plus debt burden ratio (db)

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error (I/K)it-1 0.155 0.106 -0.108 0.111 0.176 0.097* -0.198 0.122 -0.055 0.056 0.261 0.125** (∆y)it 0.073 0.055 0.078 0.053 0.398 0.128*** 0.299 0.080*** 0.094 0.079 0.093 0.060 (∆y)it-1 0.081 0.033** 0.057 0.029** 0.237 0.107** -0.088 0.082 0.165 0.044*** 0.093 0.063 (k-y)it-1 -0.076 0.029*** -0.030 0.017* -0.077 0.037** -0.123 0.034*** -0.115 0.041*** -0.030 0.022 (db)it-1 -0.067 0.037* -0.061 0.041 -0.068 0.038* -0.121 0.064* -0.165 0.079** -0.069 0.035* M1 M2 Sargan

Notes:All equations include time and sectoral dummies. Estimated coefficients and asymptotic robust standard errors reported. Estimation by GMM-SYSTEM estimator using the robust one-step method (Blundell and Bond, 1998; Arellano and Bond, 1998). Sargan is a Sargan Test of over-identifying restrictions (p-value reported). Mjis a test of jth-order serial

correlation in the first-differenced residuals (p-values reported). Instruments: in first-differences equation, following lagged values of the regressors: Belgium: (I/K) (t-5, t-6),ǻy (t-2 to t-4) (k-y) (t-4 to t-6), db (t-3 to t-5); Germany: (I/K) (t-4),ǻy (t-2 to t-4) (k-y) (-3 to t-5), db (t-5); France: (I/K) (t-6 to t-7),ǻy (t-6) (k-y) (t-5 to t-6); Italy: (I/K) (t-7),ǻy (t-6, t-7) (k-y) (t-5 to t-6), db(t-6); Netherlands: (I/K) (t-4, t-5),ǻy (t-2 to t-4) (k-y) (t-3 to t-4) db (t-3 to t-5); Spain (I/K) (t-7),ǻy (t-6) (k-y) (t-6 to t-7), db (t-6 to t-7). In levels equations, first differences of the regressors dated as follows: Belgium:ǻy (t-3), (D-L)/A (t-4); Germanyǻy (t-4) and db (t-2); Franceǻy (t-5), db (t-2); Italyǻy and db (t-5); Netherlands:ǻy and db (t-4); Spain: ǻy and db (t-2).*,**,*** indicate significance at 10%,5% and 1% significance level, respectively.

0.04 0.71 0.00 0.00 0.63 0.01 0.00 0.73 0.42 Spain 0.00 0.11 0.36 0.00 0.20 0.47 0.00 0.15 0.20

Belgium Germany France Italy Netherlands

Table 6. Impact of financial variables on investment. Differential impact for small and medium-size firms

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error Profitability 0.210 0.214 *** 0.516 0.215 ** 0.791 0.234 *** 0.306 0.343 0.698 0.229 *** 0.128 0.120 Diff. SMEs 0.332 0.201 * -0.461 0.288 -0.298 0.249 0.172 0.323 -0.475 0.247 * 0.169 0.118 Indebtedness -0.021 0.039 -0.069 0.126 -0.042 0.036 -0.065 0.031 ** -0.124 0.085 -0.059 0.061 Diff. SMEs -0.050 0.038 0.071 0.066 0.021 0.042 0.000 0.056 -0.043 0.079 0.022 0.057 Debt burden -0.003 0.048 -0.054 0.037 -0.056 0.051 -0.009 0.087 -0.118 0.081 -0.072 0.058 Diff. SMEs -0.094 0.052 * -0.013 0.058 -0.025 0.052 -0.119 0.085 0.039 0.099 0.009 0.056 Belgium

Note: Diff. SMEs captures, for each financial ratio, the differential impact of that ratio on investment rates for SMEs. *,**,*** indicate significance at 10%,5% and 1% significance level, respectively. Spain Netherlands Italy France Germany

Table 7. Impact of financial variables on investment, allowing different impact for different sectors

coeff std error coeff std error coeff std error coeff std error coeff std error coeff std error Profitability 0.453 0.156 *** 0.190 0.147 0.696 0.116 *** 0.800 0.229 *** 0.473 0.179 *** 0.452 0.116 *** Diff. sector 2 -0.072 0.079 0.075 0.070 0.225 0.060 *** 0.017 0.088 0.008 0.131 0.130 0.046 *** Diff. sector 3 -0.008 0.104 0.113 0.380 0.252 0.035 *** 0.223 0.124 * 0.021 0.230 0.119 0.040 *** Diff. sector 4 0.089 0.050 * 0.032 0.044 0.080 0.044 * 0.032 0.068 0.131 0.130 0.033 0.030 Diff. sector 5 -0.089 0.056 0.039 0.185 0.042 0.045 0.034 0.048 -0.165 0.104 0.008 0.026 Indebtedness 0.180 0.156 *** -0.330 0.147 -0.769 0.608 -0.039 0.229 *** -0.085 0.122 -0.015 0.116 *** Diff. sector 2 -1.513 0.079 0.294 0.070 1.557 1.739 -0.012 0.088 -0.007 0.165 0.096 0.046 *** Diff. sector 3 0.004 0.104 0.368 0.380 1.974 1.196 * 0.192 0.124 * 0.067 0.262 0.033 0.040 *** Diff. sector 4 0.057 0.050 * 0.334 0.044 1.086 0.671 -0.047 0.068 0.199 0.166 -0.006 0.030 Diff. sector 5 -0.527 0.056 0.206 0.185 0.823 0.850 -0.026 0.048 -0.164 0.140 -0.041 0.026 Debt burden -0.064 0.047 0.027 0.052 -0.111 0.035 *** -0.140 0.064 ** -0.109 0.052 ** -0.082 0.024 *** Diff. sector 2 -0.164 0.125 0.021 0.067 0.290 0.060 *** -0.176 0.116 -0.044 0.127 0.131 0.044 *** Diff. sector 3 -0.063 0.134 0.112 0.371 0.210 0.029 *** -0.284 0.154 * 0.002 0.239 0.085 0.036 ** Diff. sector 4 -0.200 0.234 -0.005 0.047 0.089 0.036 ** 0.092 0.067 0.135 0.123 0.022 0.028 Diff. sector 5 -0.165 0.080 -0.005 0.185 0.013 0.036 -0.010 0.073 -0.178 0.104 * -0.015 0.022 France Belgium

Note: Diff. sector j captures, for each financial ratio, the differential impact of that ratio on investment rates for sector j. Manufacturing sector is the reference sector (sector 1). Sector 2 includes firms in the electricity gas, water supply, transport, storage and communication sectors. Sector 3, 4 and 5 includes companies in the construction, services and trade sectors, respectively.*,**,*** indicate significance at 10%,5% and 1% significance level, respectively.

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Charts 1-5: Selected variables over time

Chart 1: Investment rate

Chart 2: Real sales (annual rate of growth)

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 1997 1998 1999 2000 2001 2002 2003 2004 2005 Belgium France Germany Italy the Netherlands Spain

-0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 1997 1998 1999 2000 2001 2002 2003 2004 2005 Belgium France Germany Italy the Netherlands Spain

Source: Amadeus, Bureau van Dijk and own calculations Source: Amadeus, Bureau van Dijk and own calculations

Chart 3: Profitability

Chart 4: Net indebtedness

0.02 0.04 0.06 0.08 0.1 0.12 1997 1998 1999 2000 2001 2002 2003 2004 2005 Belgium France Germany Italy the Netherlands Spain

0.3 0.4 0.5 0.6 0.7 0.8 1997 1998 1999 2000 2001 2002 2003 2004 2005 Belgium France Germany Italy the Netherlands Spain

Source: Amadeus, Bureau van Dijk and own calculations Source: Amadeus, Bureau van Dijk and own calculations

Chart 5: Interest debt burden

0 0.1 0.2 0.3 0.4 1997 1998 1999 2000 2001 2002 2003 2004 2005 Belgium France Germany Italy the Netherlands Spain

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Charts 6-8: Relationship between financial position and investment level

Chart 6: Cash flow and level of investment

Belgium France 0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e nt R a te

high cash flow medium cash flow low cash flow

0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e n t R a te

high cash flow medium cash flow low cash flow

Germany Netherlands 0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e nt R a te

high cash flow medium cash flow low cash flow

0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 Inv e st m e nt R a te

high cash flow medium cash flow low cash flow

Italy Spain 0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 Inv e st m e nt R a te

high cash flow medium cash flow low cash flow

0.00 0.05 0.10 0.15 0.20 0.25 0.30 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e n t R a te

high cash flow medium cash flow low cash flow

Source: Amadeus, Bureau van Dijk and own calculations

Note: The different panels present the median investment rate in each country for firms with high cash flow (above the 90th percentile), medium cash flow (firms for which this ratio stands between the 45th and the 55th percentile) and low cash flow (lower decile). The investment rate is defined as the ratio of gross fixed capital formation over capital stock, while cash flow is normalized by total assets.

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Chart 7: Indebtedness and level of investment

Belgium France 0.00 0.05 0.10 0.15 0.20 0.25 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e n t R a te

high indebtnes s ratio medium indebtness ratio low indebtness ratio

0.00 0.05 0.10 0.15 0.20 0.25 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e n t Ra te

high indebtness ratio medium indebtnes s ratio low indebtnes s ratio

Germany Netherlands 0.00 0.05 0.10 0.15 0.20 0.25 1997 1998 1999 2000 2001 2002 2003 2004 2005 Inv e st m e n t R a te

high indebtnes s ratio medium indebtnes s ratio low indebtnes s ratio

0.00 0.05 0.10 0.15 0.20 0.25 1997 1998 1999 2000 2001 2002 2003 2004 2005 In v e st m e n t Ra te

high indebtnes s ratio m

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