The deregulation of capital markets in France

Journal of Multinational Financial Management 10 (2000) 109 – 132 www.elsevier.com/locate/econbase

The deregulation of capital markets in France Benedicte Millet-Reyes * Long Island Uni6ersity School of Business, Public Administration, and Information Sciences, 1 Uni6ersity Plaza, Brooklyn, NY 11201 -5372, USA Received 13 November 1998; accepted 20 July 1999

Abstract This paper investigates how the deregulation of French capital markets affected corporate investment in the 1980s. Access to public financial markets may be less important in countries that have traditionally relied on institutional investors to finance their corporate investment projects. This should be true for France where, contrary to the US, banks and government agencies have always been involved in firms’ long term activities. In this study, French firms are categorized based on their ownership structure and trading characteristics. Two investment models are augmented with measures of corporate liquidity in order to test the role of internal funds on investment. Empirical results show that only small French firms trading on the secondary stock market have to rely on liquid assets to finance their capital expenditures. French firms with strong bank ties avoid this constraint since they are allowed to maintain higher debt levels. © 2000 Elsevier Science B.V. All rights reserved. JEL classification: G31; G32 Keywords: Deregulation; Liquidity; Investment

1. Introduction This paper studies the investment behavior of French corporations during the 1980s. This period was characterized by significant political changes leading to the privatization of French banks and the expansion of the Paris Stock Market. Three types of companies are examined in this paper: industrial groups with bank ties, * Tel.: + 1-718-4881150; fax: +1-718-4881125. E-mail address: [email protected] (B. Millet-Reyes) 1042-444X/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved. PII: S 1 0 4 2 - 4 4 4 X ( 9 9 ) 0 0 0 2 3 - 7

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industrial groups without bank ties, and independent firms. The first category consists of large corporations with institutional shareholders (banks, insurance companies, and government agencies). The second class of firms is limited to large industrial groups that do not have any significant link with France’s main institutional investors. The third category includes small and independent firms that do not belong to any consolidated group and do not have any large institutional shareholders in their ownership structure. First, this study investigates whether ownership structure had an impact on corporate investment in the 1980s. Bank owners can provide access to debt as well as monitoring of the firm. They are expected to mitigate the information and incentive problems that lead to sub-optimal investment behavior. In contrast, firms without any bank links are expected to face larger information asymmetries and agency conflicts. As a result, these companies have limited leverage and rely on internal funds to finance their capital expenditures. In a second step, I test whether access to public capital markets modified corporate investment during this period. In France, well-established firms are traded on the largest stock market where information asymmetries between owners and investors are limited. In contrast, younger firms are often traded on the second or over-the-counter market. They should be more financially constrained because of their limited access to external funds. Third, the period covered by this sample provides a good opportunity to study how French corporations adapted their investment behavior to the deregulation of the French economy. Well-established firms as well as growing companies looking for external investors benefitted from the liberalization of French capital markets. Last, this paper provides new evidence on the limited role of cash flow as a determinant of the level and timing of corporate investment. Cash and working capital variables are shown to be more consistent in their explanatory power. The remainder of this paper is organized as follows. Section 2 summarizes the existing literature on corporate investment. Section 3 describes key aspects of the French economy and capital markets during the 1980s. Comparison is made with the financing characteristics of Japanese and American firms. In Section 4, a panel of French companies is studied for the period 1987–1990. A Tobin’s Q model of investment is augmented to include measures of liquidity. First, the role of working capital and cash flow is tested on a sample split by shareholding characteristics. In a second step, stock exchange categories are used to differentiate corporate investment patterns. Last, this section examines how financing conditions evolved between 1983 and 1990. Section 5 complements the previous section by using an Euler equation approach. Since information on stock prices is not used in the specification of this model, the new sample covers a longer time period from 1983 to 1990. A borrowing limit is included in the Euler equation model, and the multiplier associated with this constraint is parameterized as a function of the company’s stock of liquid assets. Section 6 provides conclusions on the implications and restrictions of this study.

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2. Corporate investment theory Neoclassical investment models show that, when capital markets are assumed to be perfect, the financial structure of the firm is irrelevant to corporate investment decisions (Miller and Modigliani, 1958). More specifically, in the standard Q model, firms should invest until marginal Q is one. In the Euler equation model, financial factors such as debt limits and liquidity are not included when determining the firm’s cost of capital. However, asymmetric information and incentive problems may modify corporate investment behavior in two ways. First, providers of external finance may reduce the availability or increase the cost of debt for corporations whose profitability cannot be assessed (Myers and Majluf, 1984). As a consequence, companies with limited access to external finance often make sub-optimal investment decisions based on the availability of internal funds. Agency problems can also lead to inefficient investment behavior. As Jensen (1986) notes, management may act against the best interests of shareholders by investing the firm’s free cash flow in sub-optimal projects. The value-maximization goals of stockholders also conflict with those of debt-holders. Shareholders favor riskier projects, since limited liability means they do not have to bear the full cost of negative outcomes (Jensen and Meckling, 1976). Further, equity holders can appropriate wealth by distributing dividends instead of investing in projects whose returns would have to be shared with debt-holders. Therefore, a firm’s access to external funds may be limited by creditors who seek to reduce the scope for wealth transferring activities. Institutional ownership, especially from banks, can mitigate incentive conflicts and information asymmetries. First, because banks are more involved in the day-to-day activities of the company, they have better information on the firm’s investment policy and profitability. Second, they can also control managers’ consumption of perquisites and investment decisions. Finally, as both shareholders and debt-holders, banks can increase the firm’s leverage without being concerned about the owners’ incentives to appropriate wealth at the expense of creditors.

2.1. Tobin’s Q models with financing constraints Empirical specifications of Tobin’s Q models use market valuation of capital to control for investment opportunities. The impact of financial constraints is then measured by including measures of the firm’s liquidity. Fazzari et al. (1988) classify US corporations in terms of their payout ratios. Low payout firms are assumed to be financially constrained and show greater sensitivity of investment to cash flow. However, the empirical results of this study do not distinguish information problems from agency conflicts. Using the same panel of firms, Oliner and Rudebusch (1992) try to distinguish between possible sources of financial constraints. They proxy for the severity of information problems using data on the firm’s age, exchange listing, pattern of insider trading, and distribution of equity ownership. The potential for agency conflicts is measured by the proportion of shares held by

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the board of directors and the largest outside shareholders. Their results provide support for information asymmetries as a source of the finance hierarchy favoring internal funds. In their study of Japanese firms, Hoshi et al. (1991) investigate the role of bank ownership in facilitating access to debt. They demonstrate that firms belonging to keiretzu, Japanese industrial groups centered around banks, have higher debt ratios and depend less on internal liquidity to make investment decisions. Prowse (1990) also shows that Japanese banks mitigate agency conflicts by increasing their equity holdings.

2.2. Euler equation models with borrowing constraints Another way of testing the link between internal funds and investment is to modify the Euler equation model to include borrowing constraints. Hubbard et al. (1994) show that the neoclassical model without capital markets frictions is accepted for a sample of US manufacturing companies with high dividend payout. However, low payout firms, which are more likely to be financially constrained, reject the standard model but accept the augmented version with borrowing constraints. These results remain valid when the characterization of information asymmetries is modified: financially constrained firms can be defined as having higher interest coverage ratios, higher debt-to-asset ratios, or no bond rating (Whited, 1992). Access to external funds can also change over the lifetime of a corporation and modify the role of liquidity. Petersen and Rajan (1994) explain that smaller US firms rely on internal funds in their initial years. As a consequence, for such firms, higher debt levels are a sign of better credit availability, rather than that they have borrowed up to their credit limits. Changes in domestic capital markets can also modify the sources of external finance. Hoshi et al. (1990) study the deregulation of Japanese debt markets in the 1980s. They find that, during this period, mature and successful companies switched from bank loans to public debt in order to avoid the monitoring cost of bank financing. However, these firms also became increasingly sensitive to cash flows for their capital expenditures. In contrast, liquidity remained unimportant for companies that had maintained bank ties.

3. Capital markets and corporate financing in France

3.1. Ownership characteristics of French companies In France, corporate control has traditionally been held by family groups or the government. However, the political changes of the 1980s substantially modified the involvement of the state in the activities of French corporations. In 1981, a Socialist government was elected. They nationalized 43 companies, including the main banks, insurance companies and nine industrial groups which accounted for 20% of French industry sales. In 1986, the Socialist party lost the legislative elections, and the new right wing government reprivatized 13 companies including France’s largest

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banking groups: Paribas; Suez; Credit Commercial de France and Societe Generale (Fremont and Latapie, 1992). Despite these political and economic changes, France maintains major institutional differences with the US and Japan. First, the French government retains large equity positions in corporations, despite the recent privatization of 1986 and 1993. Second, unlike American institutional investors, French banks and insurance companies have been allowed to take shareholding positions in non financial companies of up to 5% of their own equity (this limit was increased to 15% in 1991). Other institutional investors consist mostly of national and regional government agencies. Investment funds are also more limited because pension provisions are principally run by state schemes. While French banks are an important source of external finance, they have not tried to participate as actively in the running of firms as German or Japanese banks have. However, this attitude has started to change in the 1990s, with banks moving more into the financial services markets and establishing investment funds based on government securities and company shares. Despite this evolution, most French industrial groups remain without any bank ties. Moreover, families still control some of the largest French corporations, as well as a large share of the firms traded on the second market.

3.2. Sources of external finance in France During the period 1970 – 1985, French and Japanese firms relied mostly on loans from financial institutions, whereas US corporations also used instruments like bonds and commercial papers. However, the deregulation of Japanese capital markets resulted in a decline of bank debt from more then 90% of corporate debt in 1975 toB50% in 1992 (Hoshi et al., 1993). The reliance on bonds increased from 3% in 1985 – 1986 to 6% in 1993 –1994 (OECD Statistics, 1994). In France, the development of capital markets provided new sources of external funds to companies. The introduction of the second market in 1983 and the privatizations of 1986 brought interest in the stock market. Family businesses started giving up some degree of corporate control in exchange for equity financing. In fact, share trading increased by 600% between 1983 and 1990. Increased reliance on public capital markets is reflected in these OECD Statistics: in 1985–1986, 24% of corporate financing was provided by equity, and only 1% by bonds. These numbers jumped to 38 and 7%, respectively, in 1993–1994. However, it should be emphasized that all French firms do not benefit in an equal way from the diversification of finance sources. First, the Paris Bourse is composed of three markets with different listing requirements. The ‘Cote Officielle’ is the main market and includes two types of transactions: monthly settlement or cash. Companies wishing to be listed on the Cote Offcielle must have distributed dividends for at least three consecutive years before listing, and must offer at least 25% of their capital. The monthly settlement section of this market is the oldest one, with the largest and most traded firms. The ‘Second Marche’ (Second Market) opened in 1983, and allows companies to offer only 10% of their capital without

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any dividend requirements. Last, there is an unregulated over-the-counter market, the ‘Hors Cote’. All stock exchange activities are subject to the oversight of the Commission de Operations en Bourse (COB), a state-appointed body similar to the US Securities and Exchange Commission. In 1990, 70% of the companies were traded on the main market, representing 93% of the French market capitalization. However, the growth in the second market has brought significant changes in corporate ownership and financing. A large number of the companies traded on this market were originally owned by families, but they have been able to raise more equity than the minimum requirements thanks in part to the interest shown by institutional investors.

4. Testing the impact of corporate ownership structure on investment

4.1. Sample construction This section analyses a sample of 123 non-financial French corporations, all publicly traded between 1983 and 1990. Subsidiaries of French and foreign companies are excluded from this project. The years 1983–1986 are used as instruments for the regressions run on the period 1987–1990. Accounting and financial information, as well as details on the ownership structure have been obtained from the reports published by the French company DAFSA. Sources and uses of funds, including investment expenditures, are provided for all companies. DAFSA also publishes a list of all French groups having more then ten subsidiaries. This list is used in this study to separate group firms from independent firms. The sample is split in three categories based on their ownership characteristics. The first sub-sample consists of 37 groups with bank ties. A firm is defined as having bank ties if the percentage of its shares owned by French banks is above 2% on average over the sample years. The second sub-sample includes 64 groups without significant bank links. The third category is limited to firms that do not belong to a group. For such companies, bank ownership is very low. Table 1 describes the ownership characteristics of each category. Groups with bank ties have an average institutional ownership of 18% (banks, insurance companies and government agencies combined). The average is only 2% for independent firms. These companies are largely owned by families or large private investors. Their size, measured by the beginning-of-period stock of tangible assets (LagK), is on average nine times smaller than that of groups with bank ties. Most industry classifications are represented in each firm subcategory. Table 2 shows that firms with bank owners sustain higher levels of leverage. The average debt-to-assets ratio for groups with bank ties is 18% higher than that of groups without bank ownership, and 50% higher than that of independent firms. Second, financially constrained firms should accumulate liquid assets in order to compensate for their restricted access to external funds. Adverse selection problems that affect lenders in credit markets may also be mitigated by the existence of liquid assets and collaterals. Three measures of corporate liquidity support this hypothesis. Working capital, liquidity and retained

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earnings are much larger for companies that do not have bank links. t-tests and non-parametric tests between the three sub-samples confirm that these differences are statistically significant.

4.2. A Tobin’s Q model with measures of corporate liquidity In this section, a Q model of investment is used, first on the whole sample, then on each category of firms. The reduced form equation used for empirical estimation is: Ii,t /Ki,t − 1 =c +ci +ct +b · Qi,t − 1 + ui,t

(1)

Ii,t, investment at time t for firm I; Ki,t − 1, physical capital stock at the end of period t−1; ci, firm specific effect; ct, year dummy; Qi,t − 1 (market value of equity+ book value of debt −book value of inventory) divided by book value of tangible assets at the beginning of period t. Cash flow working capital and lagged sales are then added to the model in order to estimate the effect of financing constraints on investment decisions. The resulting empirical specification is: It Si,t − 1 CFi,t WCi,t − 1 =c +ci +ct +b*Qi,t − 1 + g* + d* + o* + ui,t Kt − 1 Ki,t − 2 Ki,t − 1 Ki,t − 2

(2)

Table 1 Ownership structure by firm categories, 1987–1990 Variable

Groups with bank ties, 148 obs.

LagK (millions FRF) Mean 2161.4 Median 755.9 Bank ownership Mean (%) Median (%)

Groups without bank ties, 264 obs.

Independent firms, 80 obs.

3851.1 398.2

242.2 84.7

11 7

1 0

1 0

Institutional ownership Mean 18 Median 13

6 0

2 0

Nb. Institutional in6estors Mean 2.13 Median 2

0.67 0

0.50 0

Ownership by other firms Mean (%) 33 Median (%) 25

36 37

35 27

Family and indi6iduals Mean (%) Median (%)

12 0

17 5

5 0

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Table 2 Summary statistics by firm categories, 1987–1990a Variable

All firms

With bank

Without bank

Independent

In6estment/LagK Mean Median

0.38 0.33

0.37 0.34

0.38 0.33

0.38 0.33

Cash flow/LagK Mean Median

0.70 0.56

0.69 0.51

0.70 0.58

0.69 0.61

Output/LagK Mean Median

9.94 7.20

8.86 7.23

10.69 7.04

9.44 8.32

Interest co6erage Mean Median

0.34 0.20

0.29 0.24

0.32 0.18

0.48 0.22

Payout ratio Mean Median

0.09 0.11

0.10 0.10

0.06 0.11

0.13 0.09

Debt/LagK Mean Median

1.81 1.31

2.10 1.55

1.78 1.15

1.38 1.23

Liquidity/LagK Mean Median

1.58 1.12

1.10 0.90

1.73 1.13

1.93 1.57

Ret. earnings/LagK Mean Median

1.09 0.85

0.72 0.58

1.24 0.93

1.30 1.34

Working cap./LagK Mean Median

2.31 1.76

1.71 1.55

2.50 1.73

2.77 2.45

a Cash flow, operating income+depreciation; payout ratio, dividend/operating income; interest coverage, interest/(interest+cash flow); liquidity, cash+ST securities+accounts receivable−accounts payable; working capital, liquidity+inventory.

St − 1, lagged sales, CFt, cash flow in period t, WCt − 1, beginning of period working capital. The two measures of liquidity included in this regression create new problems of estimation because they can also proxy for investment opportunities. Although the Q variable used in this model is supposed to control for profitability, its empirical value may be biased because of stock market imperfections. As a consequence, variables measuring liquidity may be significant for all categories of firms, only because they proxy for future performance. In order to address this problem, this study tries to reduce endogeneity in two ways. First, a variable measuring the sales level at time t−1 is included in the

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regression in order to control for future demand for capital goods. Further, instruments based on lagged values of the dependent and independent variables are used to control for future profitability. The equations are then first-differenced in order to remove the firm’s specific effect. Estimation is made with the Generalized Method of Moments, since it allows for heteroskedasticity, autocorrelation, and the use of instrumental variables.

4.3. Empirical results Tables 3 – 6 present detailed regression results for the whole sample and for each category of firms. Estimated coefficients, standard errors, and tests of the overidentifying restrictions are given for each model specification. Firm specific effects are removed by first differencing the equation. Year dummies are included as regressors and instruments in all equations. The instruments used in all equations are: Q at t− 1; cash flow ratio at t − 2 and t− 3; investment ratio at time t− 2 and t− 3; retained earnings ratio at time t −2 and t− 3; liquidity ratio at t− 2 and t−3 and working capital ratio at time t −2 and t− 3. Table 3 GMM estimation of the Q model: all firms, 1987–1990a All firms

C

Qi,t

Coefficient s.e. x 25 =2.361

−0.038 (0.025)

0.037(*) (0.015)

Coefficient s.e. x 28 =7.655

0.005 (0.029)

Coefficient s.e. x 28 =8.026

−0.031 (0.024)

Coefficient s.e. x 28 =4.929

0.009 (0.024)

0.007 (0.013)

Coefficient s.e. x 28 =5.228

−0.008 (0.025)

0.021 (0.012)

0.008 (0.005)

Coefficient s.e. x 28 =7.445

−0.028 (0.022)

0.026(*) (0.013)

0.009 (0.007)

Coefficient s.e. x 27 =4.501

−0.001 (0.029)

0.015 (0.017)

0.005 (0.007)

a

Si,t−1/Ki,t−2

0.014 (0.017)

CFi,t /Ki,t−1

WCi,t−1/Ki,t−2

0.279(*) (0.128)

0.029(*) (0.014)

0.037 (0.028) 0.306(**) (0.116)

(*) and (**) indicate significance at the 5 and 1% levels.

0.033 (0.026)

0.242(*) (0.119) 0.012 (0.037) 0.268(*) (0.131)

0.018 (0.035)

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Table 4 GMM estimation of the O model: groups with bank ties, 1987-1990a With banks Coefficient s.e. x 25 =2.591 Coefficient s.e. x 28 =5.508 Coefficient s.e. x 28 =4.482 Coefficient s.e. x 28 =5.966 Coefficient s.e. x 28 =5.094 Coefficient s.e. x 28 =3.440 Coefficient s.e. x 27 =1.925 a

C

Qi,t

Si,t−1/Ki,t−2

0.017 (0.021)

0.017 (0.017)

−0.003 (0.018)

0.009 (0.011)

0.008 (0.020)

0.010 (0.014)

−0.002 (0.018)

0.004 (0.012)

−0.001 (0.018)

0.009 (0.011)

0.004 (0.006)

−0.028 (0.022)

0.026(*) (0.013)

0.015 (0.013)

−0.001 (0.029)

0.015 (0.017)

0.019(*) (0.008)

CFi,t /Ki,t−1

WCi,t−1/Ki,t−2

0.104 (0.104) 0.004 (0.017) 0.112 (0.099)

−0.011 (0.016)

0.109 (0.103) −0.036 (0.037) 0.144 (0.102)

−0.054(*) (0.024)

(*) and (**) indicate significance at the 5 and 1% levels.

As reported in the empirical literature, the Q coefficient is small but significant when estimated without any adjustment for capital markets imperfections. The lack of significance for the categories of groups with bank ties and independent firms is attributed to the small size of these two classes, since pooling observations from any two of these three sub-samples makes the statistical significance of Q reappear. Tables 3 – 6 also present results for the Q model augmented to include measures of liquidity. Under the hypothesis of perfect capital markets, even if the model generates biased results for each category, there should be no difference in the estimated liquidity coefficients of each class as long as the bias is the same. However, the assumption of frictionless markets does not hold for the sample studied here. Groups with bank ties behave differently than firms from the two other sub-samples. Their cash flow and working capital coefficients are small and not statistically significant. In contrast, cash flow matters for groups without bank ownership, and for independent firms. Working capital is significant only for the latter category. These results are consistent with the theoretical literature on agency conflicts and asymmetric information problems. First, the investment decisions of French firms with bank ties are not influenced by the availability of cash flow and working capital. This result could be attributed to the positive impact of bank shareholders who provide monitoring and easy access to debt. However, because French banks

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and institutional investors are often controlled by the state, the Q model of investment may not be the right structural approach for corporations with strong institutional ties. Such companies may be less responsive to private incentives such as market valuation and internal liquidity. As for the two other firm categories (groups without bank ties, and independent companies), two major results appear from the regression analysis. First, the coefficient on the cash-flow variable is higher for large groups (when lagged sales and working capital are included in the regression) than for independent firms. This result may support the hypothesis that large corporations suffer from significant agency conflicts related to the use of free cash-flow. It is also consistent with the international findings of Kadapakkam et al. (1998) showing that large firms rely more on cash flow than small firms. Second, the working capital variable is only significant for the category of small firms. This is consistent with the hypothesis that independent firms suffer from strong adverse selection problems. They retain higher stocks of liquid assets to finance their capital expenditures.

4.4. Corporate in6estment and public capital markets in France As explained in Section 3.2, France has three categories of stock markets with specific information requirements. Since these markets were started at different Table 5 GMM estimation of the Q model: groups without bank ties, 1987–1990a Without bank

c

Qi,t

Coefficient s.e. x 25 =2.948 Coefficient s.e. x 28 =6.480 Coefficient s.e. x 28 =11.637 Coefficient s.e. x 28 =2.463 Coefficient s.e. x 28 =5.342 Coefficient s.e. x 28 =11.830 Coefficient s.e. x 27 =2.172

−0.063 (0.040)

0.036(*) (0.017)

a

Si,t−1/Ki,t−2

0.033 (0.037)

0.004 (0.013)

−0.019 (0.032)

0.017 (0.014)

0.042 (0.039)

0.004 (0.015)

0.021 (0.034)

0.013 (0.011)

0.009 (0.008)

−0.018 (0.033)

0.018 (0.015)

0.008 (0.010)

0.046 (0.045)

0.001 (0.019)

0.001 (0.013)

CFi,t /Ki,t−1

WCi,t−1/Ki,t−2

0.267(*) (0.101) 0.013 (0.034) 0.425(**) (0.136)

(*) and (**) indicate significance at the 5 and 1% levels.

0.071 (0.040)

0.296(**) (0.100) −0.010 (0.048) 0.424(**) (0.149)

0.067 (0.057)

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Table 6 GMM estimation of the Q model: independent firms, 1987–1990a Independent

c

Qi,t

Coefficient s.e. x 25 =6.835 Coefficient s.e. x 28 =7.957 Coefficient s.e. x 28 =6.025 Coefficient s.e. x 28 =5.168 Coefficient s.e. x 28 =7.407 Coefficient s.e. x 28 =9.636 Coefficient s.e. x 27 =5.090

−0.047 (0.050)

0.065 (0.051)

−0.015 (0.045)

−0.010 (0.030)

−0.028 (0.046)

0.021 (0.035)

0.008 (0.044)

−0.046 (0.035)

−0.014 (0.044)

−0.006 (0.025)

0.007 (0.008)

−0.023 (0.044)

−0.009 (0.029)

−0.007 (0.010)

0.006 (0.045)

−0.044 (0.035)

−0.002 (0.008)

a

Si,t−1/Ki,t−2

CFi,t /Ki,t−1

WCi,t−1/Ki,t−2

0.307(*) (0.146) 0.123(*) (0.048) 0.347(*) (0.144)

0.073(*) (0.035)

0.294(*) (0.143) 0.077(**) (0.028) 0.338(*) (0.147)

0.076(*) (0.036)

(*) and (**) indicate significance at the 5 and 1% levels.

points in time, they also provide useful information on the age and size of their listed companies. In this section, I will use this criterion to proxy for the severity of information asymmetries between firms and external investors. The objective is to show that constrained firms accumulate liquid assets when they have poor access to public markets. In order to test this hypothesis, groups with bank ownership are removed from the sample, since their investment decisions are not sensitive to liquidity in this model. Further, they are often government controlled firms for which public trading has not been consistent. The remaining firms, groups without bank ties and independent firms, are split into two categories based on their stock exchange listing. The first sub-sample is restricted to companies traded on the monthly settlement market. As described in Section 3, they are all large and mature firms. The other sub-sample includes all other corporations traded on the cash, second market or over-the-counter markets. The monthly settlement market should allow companies to raise external funds more easily, since it deals only with well-established corporations. In contrast, smaller and less mature firms traded on the secondary markets should have limited access to external finance. Table 7 compares the characteristics of companies traded on the monthly settlement market to those of firms listed on smaller markets. A non-parametric Wilcoxon test shows that, although debt ratios for the two subsamples are not

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statistically different from each other, firms traded on the monthly settlement market have a lower interest coverage ratio. Moreover, these companies also retain lower stocks of liquidity and working capital. These results validate the hypothesis that information asymmetries between external providers of funds and a firm are mitigated when the company is traded on a mature and active stock market. Companies that do not benefit from a privileged position on capital markets face a higher cost of external finance and choose to rely on internal funds. Table 7 Summary statistics by categories of stock markets, 1987–1990a Variable

Without bank ties monthly settlement, 192 obs.

Without bank ties other trading markets, 152 obs.

LagK Mean Median

1 5112.2 955.0

359.9 74.4

In6estment/LagK Mean Median

1 0.40 0.35

0.35 0.29

Cash Flow/LagK Mean Median

1 0.76 0.61

0.62 0.56

Output/LagK Mean Median

1 9.61 7.00

11.39 7.55

Interest co6erage Mean Median

1 0.17 0 16

0.60 0.22

Payout ratio Mean Median

1 0.11 0.11

0.04 0.10

Debt/LagK Mean Median

1 1.64 1.02

1.74 1.29

Liquidity/LagK Mean Median

1 1.73 1.11

1.84 1.47

Ret. earnings/LagK Mean Median

1.27 0.88

1 1.22 1.12

Working cap./LagK Mean Median

2.63 1.77

a

2.48 1.92

Cash flow, operating income+depreciation; payout ratio, dividend/operating income; interest coverage, interest/(interest+cash flow); liquidity, cash+ST securities+accounts receivable−accounts payable; working capital, liquidity+inventory.

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Table 8 GMM estimation of the O model by stock market categories, 1987–1990a Firm category Monthly settlement Coefficient s.e. x 28 =13461 Coefficient s.e. x 28 =13172 Coefficient s.e. x 27 =10.634 Other markets Coefficient s.e. x 28 =5.090 Coefficient s.e. x 28 =4.697 Coefficient s.e. x 27 =4.035 a

C

Qi,t

Si,t−1/Ki,t−2

CFi,t /Ki,t−1

0.025 (0.034)

0.013 (0.013)

0.002 (0.007)

−0.009 (0.029)

0.018 (0.017)

−0.005 (0.010)

0.032 (0.033)

0.007 (0.015)

0.000 (0.009)

0.249 (0.147)

−0.016 (0.040)

0.007 (0.015)

0.020(**) (0.071)

0.054 (0.071)

0.022 (0.042)

−0.008 (0.018)

−0.003 (0.009)

0.019 (0.050)

−0.007 (0.035)

−0.004 (0.011)

WCi,t−1/Ki,t−2

0.236 (0.152) 0.010 (0.041) 0.018 (0.035)

0.188(*) (0.074) 0.122 (0.148)

0.202(*) (0.083)

(*) and (**) indicate significance at the 5 and 1% levels.

Empirical analysis is then conducted with the reduced form investment equations used in the previous section. Table 8 shows that the investment decisions of firms traded on the monthly settlement market are not based on their level of working capital or cash flow. In contrast, companies traded on less-established markets make their amount of investment dependent on their accumulation of working capital. Importantly, when the sample is split based on trading patterns, the statistical significance of the cash flow variable disappears in the Q model.

4.5. E6olution of corporate financing between 1983 and 1990 Economic changes and more active stock markets influenced the investment behavior of French companies between 1983 and 1990. As described in Section 3 of this paper, the ownership structure of French firms was altered by the privatization of banks and the growth of public shareholding. This section investigates whether these changes benefitted non-financial companies by decreasing their reliance on internal funds between 1983 and 1990. The sample used for that purpose consists of 109 French firms traded from 1981 to 1990. It excludes younger companies, especially the ones listed on the second market which opened in 1983. The data is then split into two categories. The first one consists of 49 firms which all had bank ties before 1986, when institutional ownership was strongly linked to government control. The other one consists of all companies without any bank ownership

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before 1986. The objective is to compare the period 1983–1985 to the period 1988 – 1990 (using 81 – 82 and 86–87 as instruments). Table 9 describes in more details the ownership characteristics of the two categories, as well as their evolution between 1983 and 1990. Institutional ownership declined for firms with bank ties, and increased for firms without bank ties. This reflects the diversification strategy implemented by recently privatized institutional investors. Table 10 provides summary statistics for the two subsamples. All measures of performance and liquidity improved between 1983 and 1990, regardless of the firm category. However, non-parametric tests show that some of these ratios are statistically different between the two types of companies. First, measures of liquidity, retained earnings, and working capital are systematically higher for firms without bank ties. However, debt levels are equivalent across the two sections, with a larger interest coverage for the latter category. Second, although companies without bank links improved their investment, cash flow and output ratios at the same rate as firms with bank shareholders, their levels of liquid assets increased at a slower pace during the period 1988–1990. These statistics support the hypothesis that companies without bank ties gained better access to capital markets during the late 1980s, thereby decreasing their need to accumulate internal funds. A Q model of investment is then augmented with sales, cash flow and working capital variables. Table 11 provides separate regression results for the two firm categories and the two time periods. The instruments used for this model are: Q at Table 9 Comparison of ownership structures between 1983–85 and 1988–90 Variable

Firms with bank ties 49 firms

Firms without bank ties 60 firms

LagK (millions FRF) Median 1988–1990

509.1

236.1

Bank ownership Mean: 1983–1985 (%) Mean: 1988–1990 (%)

8 7

0 1

Institutional ownership Mean: 1983–1985 (%) Mean: 1988–1990 (%)

14 12

2 4

Nb. Institutional in6estors Mean: 1983–1985 Mean: 1988–1990 Ownership by other firms Mean: 1983–1985 (%) Mean: 1988–1990 (%) Family and indi6iduals Mean: 1983–1985 (%) Mean: 1988–1990 (%)

1.93 1.44

0.49 0.70

37 44

38 36

6 6

10 12

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Table 10 Summary statistics by firm categories, 1983–85 versus 1988–90a Variable

Firms with bank ties

Firms without bank ties

In6estment/LagK 1983–1985 1988–1990

0.27 0.33

0.27 0.34

Cash flow/LagK 1983–1985 1988–1990

0.45 0.53

0.48 0.54

Output/LagK 1983–1985 1988–1990

7.59 6.88

7.78 7.14

Interest co6erage 1983–1985 1988–1990

0.22 0.19

0.26 0.21

Payout ratio 1983–1985 1988–1990

0.07 0.11

0.09 0.11

Debt/LagK 1983–1985 1988–1990

1.21 1.29

1.26 1.39

Liquidity/LagK 1983–1985 1988–1990

0.25 1.04

0.31 1.26

Ret. earnings/LagK 1983–1985 1988–1990

0.31 0.68

0.91 1.77

Working cap./LagK 1983–1985 1988–1990

0.63 1.54

2.48 1.92

a Cash flow, operating income+depreciation; payout ratio, dividend/operating income; interest coverage, interest/(interest+cash flow); liquidity, cash+ST securities+accounts receivable−accounts payable; working capital, liquidity+inventory; all ratios reported in this table are median values.

time t − 2; cash flow ratio at time t−1 and t− 2; investment ratio at time t− 1 and t− 2; retained earnings ratio at time t− 1 and t− 2; liquidity ratio at time t− 2; working capital ratio at time t − 2; and payout ratio at time t− 1 and t−2. GMM estimation of the coefficients leads to the rejection of the structural model for companies with bank links. This result validates the hypothesis that firms with bank ownership do not follow a neoclassical model of investment including stock market valuation. As mentioned before, this effect may be linked to the intervention of the French government in firms having significant links with banks and other institutional investors. In contrast, the Q model including liquidity variables is accepted for companies that did not have any bank ties before 1986. However, the impact of

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working capital on their investment decisions is only significant for the period 1983 – 1985, before the liberalization of the French economy. This result is consistent with the hypothesis that the same firms may have faced stronger problems of information asymmetries in the years preceding the expansion of the Paris Bourse.

5. Euler equation approach

5.1. Sample construction The goal of this section is to test the role of borrowing constraints on investment behavior with a structural form that does not include stock market valuation. Results based on the Tobin’s Q approach may be biased, especially if firms do not have access to the same stock exchange markets. For example, companies with bank ties are often linked to the government. For these firms, stock market valuation may not be an important component of their investment decisions. Also, smaller and younger companies may not have a well-established trading market. Consequently, the sample used to test the Euler equation model is slightly different from the one used in Section 4. First, since stock prices are not needed for this approach, a longer time period (from 1983 to 1989) can be included in this analysis. Firms are then divided in three sub-samples, using the same criteria as in Section 4.1. The first category consists of 34 groups having strong bank ties. The second category includes 70 groups that do not have bank links. The last sub-sample contains 18 independent firms without significant bank ties. Table 12 compares the financial characteristics of these three classes of firms. As shown in the previous Table 11 GMM estimation of the Q model, 1983–85 versus 1988–90a Firm category Firms without bank ties Coefficient 83–85 s.e. x 27 =7.940 Coefficient 88–90 s.e. x 27 =10.280 Other markets Coefficient 83–85 s.e. x 27 =15.885 Coefficient 88–90 s.e. x 27 =16.985 a

C

QI,t

0.287(**) −0.007 (0.096) (0.013)

−0.068 (0.142)

0.019 (0.012)

Si,t−1/Ki,t−2

0.033 (0.037)

0.487(**) (0.059)

Model Rejected Model Rejected

(*) and (**) indicate significance at the 5 and 1% levels.

CFi,t /Ki,t−1

0.019 (0.032)

−0.264(**) (0.106)

WCi,t−1/Ki,t−2

0.092(**) (0.028)

0.013 (0.016)

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Table 12 Summary statistics by firm categories, Euler equation 1983–1989a Variable

Groups with bank ties, 238 obs.

Groups without bank ties, 490 obs.

Independent firms, 126 obs.

Investment/LagK Cash flow/LagK Output/LagK Interest coverage Payout ratio Debt/LagK Liquidity/LagK Ret. earnings/LagK Working cap./LagK

0.32 0.50 7.81 0.22 0.08 1.47 0.60 0.45 1.21

0.32 0.57 7.79 0.19 0.10 1.20 0.84 0.80 1.52

0.34 0.57 7.72 0.22 0.08 1.40 1.34 1.03 1.98

a

Cash flow, operating income+depreciation; payout ratio, dividend/operating income; interest coverage, interest/(interest+cash flow); liquidity= cash+ST securities+accounts receivable−accounts payable; working capital, liquidity+inventory; all ratios reported in this table are median values. Table 13 Euler equation model, 1984–1989a

Adjustment cost Parameter a Markup Parameter m x24 = Upper tail area

Full sample

Groups with bank ties

Groups without bank ties

Independent firms

2.430 (1.739) 1.132(*) (0.100) 3.192 0.230

1.725 (1.198) 1.110(*) (0.058) 1.189 0.880

1.355 (2.110) 1.081(*) (0.111) 2.914 0.572

0.014 (0.523) 1.087(*) (0.043) 9.826 0.043

a (*) Indicates significance at the 1% level; standard errors are in parentheses; firm specific effects are removed by first-differencing the Euler equation; year dummies are included as regressors and instruments in all equations.

sections, stocks of liquidity, retained earnings and working capital are much larger for firms without bank ties, especially small and independent companies.

5.2. Model without a debt limit The model used in this section is based on the Euler equation, but it does not include any constraint on the use of external finance. This standard neoclassical model is described in Hubbard et al. (1994). Empirical estimation is made using the Generalized Method of Moments. The estimating equation has to be first-differenced in order to remove firm-level fixed effects. Twice-lagged instruments are used in order to ensure that they are orthogonal to the moving average error term. Regression results for this baseline Euler equation estimation are given in Table 13. The neoclassical model without a credit limit is accepted for all group firms, whether they have bank ties or not. However, it is rejected for the category of small

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and independent companies. This result shows that the hypothesis of perfect capital markets does not hold for firms that are a priori more likely to face information problems. Capital market frictions create a wedge between the cost of internal and external finance, thereby forcing these companies to rely on their cash flow and liquid assets to finance their investment projects.

5.3. Euler equation with borrowing constraints In this section, financial factors are added to the standard neoclassical model by including a limit on the use of debt. The Lagrange multiplier associated with this constraint is then parameterized as a function of the stock of liquid assets. This specification supports the hypothesis that small and independent firms rely more on internal funds to finance their investment projects. Therefore, one would expect increases in the stock of liquid assets to be a sign of stronger financing constraints. The model is described in Appendix A of this paper. Regression results are presented in Table 14. First, the model with a debt limit is rejected for the category of group firms that do not have any bank ties. This finding is consistent with the fact that the baseline Euler equation without a debt limit was accepted for this category. It also validates the evidence from the Q model presented in Section 4 suggesting that these companies are financially unconstrained. Second, the augmented model is accepted for the category of independent firms. Moreover, the sign of the two parameters linked to the debt constraint multiplier is positive. This result verifies the hypothesis that firms a-priori more likely to face adverse selection problems choose to accumulate liquid assets in response to their poor access to capital markets. Third, the model is also accepted Table 14 Neoclassical model with borrowing constraint, 1984–1989a

Adjustment cost Parameter a Markup Parameter m Parameter a1 Parameter a2 Parameter a3 x23 = Upper tail area a

Full sample

Groups with bank ties

Groups without bank ties

Independent firms

2.991 (1.870) 1.095(*) (0.148) 0.614 (0.341) −0.576 (0.705) −0.115 (0.154) 2.270 0.518

2.536 (2.637) 1.221(*) (0.224) 0.240 (0.434) −0.500 (1.603) −0.068 (0.362) 0.426 0.935

1.196 (0.708) −11.298 (12496.2) 1.000 (0.146) −0.003 (0.270) 0.002 (0.151) 49.642 0.000

1.478 (1.153) 1.104(*) (0.037) 0.830 (0.478) 0.252 (0.543) 1.061 (0.619) 0.226 0.973

(*) Indicates significance at the 1% level; standard errors are in parentheses; firm specific effects are removed by first-differencing the Euler equation; year dummies are included as regressors and instruments in all equations.

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for group firms with bank ties. However, the sign of the same two parameters is negative for this category of companies. This would indicate that an increase in the stock of liquid assets relaxes the constraint on external finance. Such result is consistent with the literature associating higher debt levels to poor financial health, but inconsistent with the fact that the same firms also accept the model without a credit limit.

6. The role of liquid assets as a measure of asymmetric information problems

6.1. Limitations of the cash flow 6ariable While Q models provide a straightforward way of including finance constraints, they also suffer from endogeneity problems. The coefficient of the cash flow variable may be biased because it also proxies for the profitability of investment. Gilchrist and Himmelberg (1995) try to eliminate this problem by constructing a better proxy for Q. After controlling for future investment opportunities, they find that cash flow still plays a significant role for companies with poor access to debt markets. However, Kaplan and Zingales (1997) question the use of investment-cash flow sensitivities as a monotonic measure of financing constraints. By reexamining the results of Fazzari et al. (1988), they argue that firms a priori classified as less financially constrained are in fact the ones exhibiting greater investment–cash flow sensitivity. The results presented in this paper also suggest that the use of cash flow does not reflect poor corporate access to external funds. French industrial groups trading on the largest stock exchange are also sensitive to flows of funds. Further, Euler equation models used in Section 5 do not respond to the use of cash flow as a measure of borrowing constraints.

6.2. Accumulation of liquid assets as a measure of financing constraints Financially constrained firms can offset the impact of cash flow shocks on investment by adjusting their stock of liquid assets. Fazzari and Peteresen (1993) argue that firms try to smooth investment in the short run in order to avoid rising adjustment costs in the long run. Because investment in working capital is reversible, it can be used as a source of internal funds instead of competing with fixed investment for the use of a limited pool of finance. The results presented in this paper confirm that only a priori constrained firms base their investment decisions on the availability of working capital and other liquid assets. Problems of asymmetric information seem to be the main source of financing constraints for these firms. They do not have institutional shareholders to provide external capital. Further, they are traded on smaller and more recent stock markets. In contrast, well-established industrial groups use Q and cash flow as determinants of their investment decisions. This suggests that flows of funds, rather than stocks of liquid assets, may measure agency conflicts in large structures. Managers make sub-optimal investments based on the availability of free cash-flow.

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In their international study, Kadapakkam et al. (1998) confirm these findings by showing that large firms rely more on cash flow than small firms.

7. Conclusion This paper provides strong empirical evidence that capital and ownership structure have influenced the investment behavior of French companies in the late 1980s. Because of its institutional differences with the US and Japan, France is an interesting example of how bank ownership and growing stock markets may affect corporate financing decisions. A Tobin’s Q model and an Euler equation approach were used to test the role of internal funds for different firm categories. The main objective of this study was to compare companies based on their ownership structure and access to public markets. The first criterion used to proxy for asymmetric information and agency problems isolated groups with institutional ties from privately owned groups and independent companies. The second criterion isolated well-established groups from younger companies. I showed that mature firms trading on the largest stock market did not need to rely on the accumulation of internal funds to finance their investment projects. In contrast, small and independent firms maintain high levels of working capital in order to offset their poor access to external markets. Groups with bank ties were shown to have better access to debt, but they did not respond well to the investment models used in this study. This paper also suggests that accumulation of liquid assets seems to be a consistent response to the existence of information asymmetries between providers of external funds and constrained firms.

Acknowledgements I am grateful to the center for International Business Education and the Chazen Institute of Columbia University for their financial support.

Appendix A This section describes the Euler equation model used in Section 5 of this paper. It is based on the approach taken by Hubbard, Kashyap, and Whited. The corporate demand for investment begins with an expression for the value of the firm. The net, after-tax return to the owners consists of capital appreciation and current dividends. In equilibrium, owners will maintain their claim in the firm if this return equals their required after-tax return Ri,t : (1 − c)(Et (Vi,t − 1 −Si,t + 1) −Vi,t )+ (1− u)Etdi,t + 1 = Ri,t Vi,t

(1a)

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where Si,t + 1 denotes the value of new shares issued at time t+ 1; c is the capital gains tax rate, u is the tax rate on dividends, and di,t + 1 is the dividends at time t+ 1. The owners and managers are assumed to be risk neutral and they have rational expectations. Solving 1 forward gives the following expression for the firm’s market value at time 0:

Vi,0 =E0 % t=0



t−1

5 bij

j=0

n 

1 −u d − Si,t 1 −c i,t



(2a)

where bi, j =1/(1 + Ri, j ). The firm maximizes its value given by Eq. (2) subject to five constraints. The first constraint is the capital stock accounting identity: Ki,t =Ii,t − 1 +(1 −d)Ki,t − 1

(3)

where Ki,t is the capital stock at the end of period t; Ii,t is the investment at time t; d is the constant rate of economic depreciation. The second constraint defines the firm’s dividends as the difference between cash inflows and cash outflows: di,t =(1 −rt )[F(Ki,t − 1, Ni,t ) − vtNi,t − 8(Ii,tKi,t − 1)− it − 1Bi,t − 1]+ Si,t + Bi,t −(1 −p et )Bi,t − 1 −pi,tIi,t

(4)

where rt is the corporate income tax rate? Ni,t is a vector of variable factors of production, vt, is a vector of real factor prices, F(Ki,t − 1, Ni,t ) is the firm’s revenue function (FK \0, FKK B0), Bi,t is the real value of net debt outstanding, it is the nominal interest rate, p et is the expected inflation rate at time t, pi,t is the price of capital goods relative to the price of output, 8(I K, Ki,t − 1) is the real cost of adjusting capital (8I \0, 8II \0, 8K B 0, 8IK B 0). The third constraint restricts dividends to be non-negative: di,t ]0

(5)

The fourth constraint limits share repurchases: Si,t ]S*

(6)

The fifth constraint prevents the firm from borrowing an infinite amount to pay out as dividends:



T−1

lim

T“



5 bij BiT =0

(7)

j=t

The sixth constraint puts a limit on the use of debt finance by assuming that the outstanding debt, Bit, must be less than a debt ceiling B *i,t: Bit 5B*it

(8)

Let lit be the Lagrange multiplier associated with constraint (5) on dividends, and vit the Lagrange multiplier associated with the constraint (8) on debt. Let m represent the ratio (1 − u)/(1 −c). Substituting (4) into (2), the first order conditions for Kit and Bit are:

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Etbit [(m + li,t + 1)/(m + li,t + 1) (FK (kit, Ni,t + 1) −8K (Ii,t + 1, Kit )+ (1− d) (8I (Ii,t + 1, Ki,t )+ pi,t + 1/(1− r)))] = 8I (Iit, Ki,t − 1) +pit /(1 −r)

(9)

(m +lit ) − bit (1 + (1 − r)it − p )Et (m+li,t + 1)− vit = 0 e t

(10)

8(Iit, Ki,t − 1) is parameterized so that adjustment costs will be linearly homogeneous in investment and capital. In that case, marginal and average Q will be equal: 8(Iit, Ki,t − 1) =(a/2)[(Iit /Ki,t − 1)− 6]Iit where 6 is the bliss point of this adjustment cost function. Let’s define zit =vit /(m + li,t + 1) Therefore, bit is equal to: bit =

1 −zit (m+ li,t ) Et (1 + (1 − r)it −p et ) (m+ li,t + 1)

(12)

Assuming rational expectations and an error term uncorrelated with any information known at time t, Eq. (9) becomes:





1 −zit 1 + (1 −r)it −p et

+(1 −d)



FK (Kit, Ni,t + 1)+

pi,t + 1 −n (1 − r)

n  −a

Iit

Ki,t − 1

   

−

a 2

Ii,t + 1 Kit

2

+ a(1− d)

pit + n = ei,t + 1 (1−r)

  Ii,t + 1 Kit

(13)

The marginal product of capital is then defined as: FK (Kit, Nit ) =

Yi,t + 1 −mCi,t + 1 Kit

(14)

where Y is output, m the price markup parameter over original cost, and C real variable costs. The last step parameterizes the multiplier associated with the constraint on debt financing, so that it varies with the stock of liquid assets at time t− 1, LIQ:

 

zit =a1 +a2

LIQ K

+a3 i,t + 1

  LIQ K

(15) 2,t + 1 i

The hypothesis is that financially constrained firms will have accumulated liquid assets in order to finance their investment projects. Replacing FK (Kit, Nit ) and zit by their definitions, and including them in Eq. (13), gives the estimating equation used in Section 5 of this paper.

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