Internal and External Capital Markets

Transcription

1 Internal and External Capital Markets Urs C. Peyer * Department of Finance INSEAD April 25, 2002 Abstract This study tests the proposition that firms that make efficient use of their internal capital markets can lower the cost of transacting in the external capital market. Using a large panel data set of diversified firms from , I show that diversified firms with an efficient internal capital allocation display a higher propensity to use external capital relative to comparable single segment firms. This result is robust to including other controls, such as measures of information asymmetry, capital needs, relative valuation and firm size. Further, a higher use of external capital by diversified firms relative to single segment firms is associated with a higher excess value, but only for efficient internal capital market users. I also demonstrate the robustness of these findings by employing a sample of firms that experience an increase in expected investment outlays. My findings support predictions from theoretical models, such as Stein (1997), and are consistent with the interpretation that diversified firms with an efficient internal capital market benefit from lower-cost access to external capital by alleviating information asymmetry problems between managers and investors. For helpful discussions and comments, I would like to thank Anil Shivdasani, Jennifer Conrad, Claudio Loderer, Henri Servaes, Steve Slezak and Marc Zenner, Mike Cliff, Eitan Goldman, Maria Nondorf, David Ravenscraft, Jeffrey Wurgler and seminar participants at Arizona State University, Boston College, Darden, Emory, Illinois, INSEAD, London Business School, University of Maryland, University of Miami, University of North Carolina, University of Pittsburgh, University of Toronto and Virginia Tech, the 2001 Young Scholar Conference at the College of William and Mary, the 2001 WFA meetings and the 14 th Australasian Finance and Banking Conference. An earlier version of this paper received the 2001 Trefftz Award. *Urs Peyer, Department of Finance, INSEAD, Boulevard de Constance, Fontainebleau, France. Tel +33 (0) ; Fax +33 (0) ; Urs.Peyer@insead.edu

2 Internal and External Capital Markets This paper examines the interaction between internal and external capital markets. For the purpose of this paper, I define an internal capital market as the mechanism by which headquarters allocates capital to the various divisions of the firm. If headquarters allocates investment to the divisions with the highest marginal return, then the firm uses its internal capital market efficiently. The primary question in this study is whether and how a firm s internal allocation is related to its transactions with the external capital market. Answering this question can help us to better understand how firms finance their investments. Specifically, are there differences between single segment and diversified firms in the sources of financing? What characteristics of diversified firms lead to more or less use of external capital? The answers are important in the light of theories that try to explain the benefits and costs of diversification. 1 A potential benefit of diversification is to establish an internal capital market (ICM). Creating an ICM can have at least two advantages. First, internal resource allocation can be more efficient than allocation performed by the external capital market. This issue is the focus of recent theoretical and empirical research investigating whether diversified firms use their ICMs to efficiently reallocate capital. Theoretical models and arguments predicting an efficiency gain from internal capital allocation are found in Weston (1970), Williamson (1970, 1986), Gertner et al. (1994) and Stein (1997). Alternative models based on agency conflicts emphasizing the drawbacks of internal allocation are developed by Scharfstein and Stein (2000) and Rajan et al. (2000). Empirical tests of these models by Lamont (1997), Shin and Stulz (1998), Scharfstein (1998) and Rajan et al. (2000), among others, suggest that capital is reallocated internally, but that, on average, the reallocation is inefficient. On the other hand, Maksimovic and Phillips (2001) and Khanna and Tice (2001) conclude that internal capital markets are working efficiently by reallocating capital away from low productivity to high productivity factories or stores. A second potential advantage of an ICM is its effect on transactions with external capital markets (ECM). Stein (1997) theoretically analyzes the interaction between the efficiency of internal capital allocation, the size of the ICM (number of divisions and their correlation in investment opportunities), the use of external capital and firm value. With information asymmetries and agency problems between managers and outside investors, firms can be financially constrained. Potentially, information asymmetry problems can be reduced through an ICM. Take an external investor who bases her decision about how much to lend to a firm on her 1

3 estimate of the firm s value-maximizing investment needs. According to the law of large numbers, the precision of the estimate of the optimal amount of capital increases with the number of projects in the firm if the projects capital needs are imperfectly correlated. The same logic applies to single segment firms. However, the ICM allows HQ to reallocate capital to the highest marginal return divisions. Investment in single segment firms cannot be reallocated across divisions, which exacerbates the under- and overinvestment problem. Thus, lending to a headquarters that oversees a portfolio of projects with imperfectly correlated capital needs, i.e., a diversified firm, is different from lending to a portfolio of single segment firms in that information asymmetry problems are less important. Therefore, diversified firms that allocate capital efficiently in the ICM and firms with larger ICMs, i.e., firms with more divisions and lower correlation of divisional investment opportunities, should be able to use more external capital. On the other hand, HQ of a more diversified firm might loose the ability to efficiently reallocate capital because HQ itself becomes less informed about all the possible investment opportunities. Thus the impact of size of the ICM on a firm s ability to raise external capital should differ by its monitoring technology, i.e., the efficiency of internal capital allocation. Diversified firms that are able to alleviate some of the information asymmetry and agency problems in transacting with the external capital market should have a higher value because they underinvest less and thus can raise external capital at a lower cost than single segment firms. However, inefficient ICM users should not be able to access more external capital because they do not have or do not use superior inside information about their projects. Thus, an external investor should not be willing to invest more capital in such firms, since headquarters does not allocate the capital in a value-maximizing fashion. The above arguments suggest interesting cross-sectional relationships between the efficiency of the internal capital allocation, the size of the ICM, the use of external capital and firm value. Analyzing these interactions will further our understanding of the potential costs and benefits of an internal capital market and hence diversification. I test the above arguments in two ways. First, I employ a panel of diversified Compustat firms from In this sample, diversified firms use, on average, less external capital than comparable single segment firms. However, the analysis indicates a significantly positive correlation between the efficiency of internal capital allocation, as proxied by the relative value added by allocation (RVA) of Rajan et al. (2000), and a firm s use of external capital. Moreover, diversified firms with a larger ICM use more external capital only if their internal capital allocation is efficient. Firms with a large ICM allocating capital inefficiently use significantly less external capital. In addition, the analysis also suggests that firms that allocate capital more 2

4 efficiently can reduce the impact of information asymmetry problems (e.g., Myers and Majluf, 1984) when raising capital externally. Further, I find a significant relationship between a firm s ICM characteristics, its use of external capital and excess value measures (Berger and Ofek, 1995; Lang and Stulz, 1994). Consistent with Rajan et al. (2000), it emerges that firms with a more efficient internal capital allocation display a higher excess value, and firms with a higher diversity in their investment opportunities (a proxy for the size of an ICM and potential agency conflicts) display a lower excess value. A new finding is that firms that use more external capital have a lower excess value. The important exceptions are firms with an efficient internal capital allocation and firms with both, an efficient internal capital allocation and a large ICM these firms are valued significantly higher if they use relatively more external capital. On average, such firms even have a positive excess value. The inferences from the first part of the paper, using panel data on all diversified firms, strongly support the predictions from Stein s (1997) model that firms with an efficient internal capital allocation and firms with larger, but still efficient ICMs can raise more external capital and that doing so increases firm value. I try to alleviate concerns of endogeneity and simultaneity using different econometric techniques. However, causality is difficult to establish in this framework. Therefore, I employ a second approach. Many theoretical models investigating the use of external capital rely on the assumption that a new, positive-npv project arrives unexpectedly and that the entrepreneurs wealth and/or the firm s internal funds are insufficient to cover the investment (e.g., Myers (1977), Myers and Majluf (1984), Li and Li (1996), Stein (1997)). In order to mimic more closely the setting in which these models are specified, I select a sample of diversified firms that operate in industries that receive a positive shock to investment opportunities, proxied by industry median q. To ensure that the change in q does not merely reflect a surprise in current cash flow, I require that the industry s median cash flow remain constant. This setting provides a natural experiment to investigate whether diversified firms that receive an unexpected valuable project use more or less external financing than comparable single segment firms. 2 Consistent with the findings of the panel data study, diversified firms use more external capital if their internal capital allocation is more efficient. Also, diversity has a positive effect only if the internal allocation is efficient; otherwise diversity negatively affects a firm s use of external capital. As expected from arguments such as Myers and Majluf (1984), firms with more information asymmetries use less external capital. This relation is alleviated only if firms internally allocate capital efficiently. In this setting, firms that are able to raise more external capital should find a profitable investment opportunity. Nevertheless, the use of external capital is only significantly positively related to excess value for firms with an efficient internal capital allocation and those with both, a higher 3

5 diversity and a more efficient internal capital allocation. In addition, changes in capital expenditures at the firm and segment level suggest that the external capital raised is used to increase investment. Taken together, the evidence from a sample of firms that experience an exogenous shock to investment opportunities suggests that ICM characteristics are important determinants of a diversified firm s ability to capture new growth opportunities by allowing the firm to use more external capital. These findings highlight an additional, related advantage for firms with an efficient ICM, namely easier access to external capital. Prior empirical research on the interaction between internal and external capital markets includes Comment and Jarrell (1995), Billett and Mauer (2002), Hadlock, Ryngaert and Thomas (2001), and Fee and Thomas (1999). The study most similar to mine is Comment and Jarrell (1995), who test Williamson s (1970, 1975, 1986) argument that firms with ICMs transact less in the external capital market. They find that, on average, diversified firms raise less external capital but return more to their outside investors, and they conclude that there is no clear evidence that diversification leads to less reliance on external capital markets. However, basing the conclusion purely on average comparisons between diversified and single segment firms is problematic in the light of findings by Rajan et al. (2000) and Scharfstein (1998) who show that firms are on average allocating capital inefficiently and by Berger and Ofek (1995) who find a valuation discount for the average diversified firm relative to single segment firms. I extend Comment and Jarrell s analysis in several ways. First, I investigate the effects of ICM characteristics such as size and efficiency on a firm s use of external capital. Second, I compare diversified firms to their single segment peers. Third, I control for other factors that may influence the use of external capital. Fourth, I relate the use of external capital to firm value. Berger and Ofek (1995) find that diversified firms use more debt, but conclude that the difference is economically insignificant. Hadlock et al. (2001) find a less negative announcement return to equity offerings for diversified firms than for single segment firms. Fee and Thomas (1999) show that diversified firms have lower measures of information asymmetry. They link those measures directly to excess value and find a negative relationship. My findings suggest that efficient ICM users can reduce the cost of information asymmetry. Therefore, besides the direct effect on pricing, there should also be an indirect effect through the firm s ability to raise more external capital. Billett and Mauer (2002) find that diversified firms can increase firm value if capital is transferred to segments with above-industry-average return on assets that would be financially constrained if the divisions were single segment firms. However, their study does not analyze 4

6 whether the transfers were made due to relaxed credit constraints at the firm level or whether free cash flow from other divisions was reallocated. The remainder of the paper is organized as follows. The next section briefly reviews underlying theories for my tests. Section 2 describes the sample, the tests, and the results for the panel data set. In Section 3, I describe tests and show results for the industry shock sample. Conclusions follow. 1 Underlying Theories In a world with perfect markets, it does not matter whether investment is funded by internal or by external capital markets. However, the source of financing can matter in the presence of informational asymmetry and agency problems. Stein (1997) considers a model where managers have better information about their projects success than external investors and use this information efficiently to allocate capital to the divisions with the highest marginal return. Furthermore, he assumes that managers derive private benefits that increase with the resources under their control and that their tendency to overinvest is costly, such that the external capital market may impose credit rationing. Under these assumptions, Stein shows that diversified firms can sometimes raise more external capital than single segment firms and that doing so increases firm value. A numerical example can help to illustrate the reasoning. Assume that there are two projects. These two projects can be owned individually by two single segment firms or a diversified firm can own both projects. Managers know which of the projects (if any) are going to be successful. External investors, however, only have an ex ante expectation about the probabilities of each project s success. Assume that the expected probability of a good outcome is p = 0.5 and that of a bad outcome is (1 p) = 0.5. Investment in the project can be either 1 or 2 units. In the bad state, investing 1 unit in a project results in a verifiable gross return (y 1 ) of 1.1, and investing 2 units results in y 2 = 1.9. Therefore, the optimal level of investment in the bad state is 1 unit. In the good state, I assume that the project s return is scaled up by a factor, θ = 1.4, such that θ (y 2 y 1 ) > 1, which implies that the optimal investment per project is 2 units in the good state. Without a revelation scheme, investment cannot be made state-contingent and external investors have no means of telling which projects are good or bad. Thus, the question an external investor faces is whether to invest 1 or 2 units per project when projects are organized as single segment firms. Investing 1 unit in a single project firm provides an expected NPV of pθ y 1 + (1 p)y 1 1 = Investing 2 units in a single project firm results in an expected NPV of pθ y 2 + (1 p)y 2 2 = Therefore, external investors optimally invest 5

7 only 1 unit in single segment firms. Information asymmetries and agency problems thus result in external capital constraints. If a diversified firm owns both projects, the external investor determines the optimal investment by computing the expected NPV per project for 2, 3 or 4 units of total capital raised. Under the assumption that outcomes are independent across projects, the value of having an ICM can be easily computed. If the external investor invests 2 units, the expected NPV is the probability weighted average of the projects returns. The assumption that headquarters allocates funds to the project with the highest marginal return, i.e., ICM efficiency, is now important in determining the expected NPV, which is 2(1 p) 2 y 1 + 2p 2 θ y 1 + 2p(1 p)θ y 2 2 = Per project, the expected NPV is 0.325, which is larger than the 0.32 that could be expected from a single segment firm realizing a project. 3 If the external investor invests 3 units, the expected NPV is (1 p) 2 (y 1 + y 2 ) + p 2 θ (y 1 + y 2 ) + 2p(1 p)(y 1 + θ y 2 ) 3 = Per project, the expected NPV has increased to The additional increase in value is due to the fact that, on average, more positive NPV projects can be realized and only in one instance (both projects in the bad state) is there more overinvestment compared to the previous scenario. As long as the expected benefit from realizing more positive NPV projects is bigger than the cost of overinvesting, a diversified firm can relax credit constraints relative to single segment firms. If the diversified firm was allowed to raise 4 units, however, the expected NPV would drop to 0.56, which results in an expected NPV per project of only In this case, no reallocation occurs because each project is always investing 2 units and a diversified firm is not more valuable than two separate singleproject firms. Thus far, the example has shown that a diversified firm with an efficient ICM can use more external capital and increase firm value. The increase in firm value has two sources. First, the ability to transfer funds to the highest marginal return project (winner picking) is valuable. The expected NPV per project increases from 0.32 for a single segment firm to for a diversified firm with an efficient ICM purely by combining two projects. Second, combining two projects under the supervision of one headquarters can result in lower costs of information asymmetries. In the example, the expected NPV per project of in a diversified firm with 2 units of investment increases to an expected NPV per project of 0.34 if the diversified firm receives 3 units of investment. This increase in value reflects a reduction in the cost of information asymmetry. 4 Note that this benefit only exists if the firm is using its ICM efficiently. Only then can the external investor benefit from headquarters superior information by delegating the investment allocation decision to management. To see this, assume the CEO has a pet project in which she always invests 2 units, regardless of the project s outcome. If the firm could raise 3 6

8 units of investment, then the expected NPV of the firm would be Per project that is an expected NPV of 0.30, which is lower than for a single project firm getting only 1 unit of investment per project. Hence, efficient internal allocation is an important characteristic of an ICM with respect to transactions in the external capital markets. Allowing headquarters to increase the number of projects under its control makes it even easier for outside investors to invest in the diversified firm. Assume an extreme case in which a diversified firm owns 100 projects and each project s outcome is independent. According to the law of large numbers, an external investor would now expect roughly 50 projects in the good state and 50 in the bad state. She would be willing to invest almost at the first-best level of, on average, 150 units. Therefore, a firm with a larger ICM should be able to use more external capital. However, this prediction is based on the assumption that HQ can monitor many divisions without a decrease in the quality of allocational efficiency. It also leads to the counterfactual prediction that one huge firm could maximize value by making information asymmetry issues unimportant. Extending the model, Stein (1997) shows that if monitoring becomes harder the more divisions a firm accumulates, then allocational efficiency decreases with the size of the ICM. This suggests that the size of an ICM might be non-linearly related to a firm s ability to use more external capital. Combining the two characteristics of an ICM, size and allocational efficiency, the model predicts that firms with an efficient internal capital allocation and a large ICM use the most external capital. Firms with a large ICM but inefficient allocation should use the least. Similarly, the use of external capital should have a positive effect on firm value if the firm has an efficient internal capital allocation or both an efficient internal capital allocation and a large ICM. A negative relation between the use of external capital and size of the ICM is predicted if the internal allocation is inefficient. While this example is clearly a simplified version of investment allocation, it serves to highlight that firms with efficient and larger ICMs (more divisions, and divisions with lesscorrelated outcomes) should be able to relax some of the credit constraints otherwise imposed on single segment firms and reduce the cost of information asymmetries. It also shows that the perproject value of the diversified firm that raises more external capital should be higher than that of both a diversified firm that does not raise more external capital and a single project firm. Other papers, such as Stulz (1990), Froot et al. (1993) and Li and Li (1996) argue that if diversification reduces cash flow volatility, the likelihood of over- and underinvestment is reduced, and cash flows are more certain to cover the existing debt. Therefore, newly raised external funds are less likely to be used to pay existing debt. This implies that a diversified firm 7

9 that has to finance a new, positive-npv project with external capital before the existing debt is due is more likely to receive external financing than is a single segment firm for a similar project. Fluck and Lynch (1999) show that firms acquire marginally profitable single segment firms that, because of agency problems, cannot find external financing as stand-alone firms. Within a diversified firm, however, the conglomerate can raise funds sufficient to finance the marginally profitable segment. Thus, diversified firms should be able to raise more external financing than comparable single segment firms, and this should be value enhancing, even though diversified firms might trade at a discount relative to their industry median peers. Matsusaka and Nanda (2001) model a firm s need to raise external capital for different levels of internal resources. They assume a fixed deadweight cost of external capital, independent of whether a diversified or single segment firm raises capital. In their model, an ICM is valuable because it allows the diversified firm to avoid external financing in more instances than single segment firms. However, there are cases where internal capital is insufficient and diversified firms raise more external capital than comparable single segment firms, and doing so is valuable. Matsusaka and Nanda conclude that efficient ICM firms do not necessarily access external capital markets less often. Their analysis, however, holds properties of the internal capital market constant, and does not address interactions between ICM and ECM for different organizational forms. Important for this study is their finding that the level of internal capital available is a significant determinant of external capital use. In summary, the tests focus on the following predictions: (i) Firms with an efficient internal capital allocation should be able to use more external capital. (ii) While more diversified firms will face more difficulty in allocating capital efficiently, those that are efficient should have a positive correlation between the size of the ICM and the use of external capital. (iii) Information asymmetry problems will drive a wedge between the cost of internal and external capital, as in Myers and Majluf (1984). These costs can be reduced if internal capital allocation is performed efficiently. Therefore, measures of information asymmetry should be negatively correlated with a firm s use of external capital, although, less so for firms with an efficient internal capital allocation, i.e., firms with better monitoring. With respect to firm value, the model predicts: (iv) a positive correlation between efficiency of internal capital allocation and firm value 5 (v) a positive relation between the use of external capital and value for efficient allocators, and for large diversified firms with an efficient internal capital allocation. 8

10 2 Panel Data Sample 2.1 Sample Selection I use all firms listed on Compustat s industry segment files (including research files) for Firms with incomplete segment information on sales, assets or capital expenditures are dropped, as are firms with segments in the one-digit SIC codes of 0, 6 or 9. 6 Firms with sales less than $10 million are also excluded. 7 Following Berger and Ofek (1995), I require the sum of the segment sales to be within 1% of the net sales for the firm and the sum of the segment assets to be within 25% of the firm assets. I apply a multiple to the remaining segment assets, such that the sum of the recomputed segment assets adds up to total assets. I further restrict the sample to firms with complete information on market value of equity and cash flow statement items. Diversified firms are also dropped from the sample if imputed values for the segments are missing. Imputed values are computed at the 3-digit SIC code level using only single segment firms (at least five) with available data to compute the industry median. 8 Additionally, firms are excluded if their one year lagged value(s) of the variables described below is (are) missing. In effect, this limits my sample to firms that survive any two-year period and have complete data available in both years. Furthermore, to reduce endogeneity concerns, I use lagged values as a proxy for ICM efficiency; therefore, I require that the lagged number of segments be at least two. 9 Finally, I require that the firms have daily stock returns available on CRSP for at least 30 days in the previous year in order to compute return volatilities. 10 Imposing all of the data requirements results in a sample of 8,538 diversified firm-years spread over the period Over the same time period, there are 34,065 single segment firms that pass the same screening process. The number of diversified firms is fairly evenly distributed over time (not shown). There are 4,983 firm-years with 2 segments, 2,341 with 3 segments, 903 with 4 segments and 312 with 5 or more segments. 2.2 Determinants of the Use of External Capital According to Stein (1997), the key drivers of a firm s use of external capital are the efficiency of the internal capital allocation, the size of the ICM, and the degree of information asymmetry. In addition, use of external capital can be affected by a firm s need for capital and its relative valuation. 11 I estimate the following cross-sectional regressions for firm i and year t: 9

11 Excess net external capital α + γ + γ + γ + γ (ICMsize) (ICMsize ICMefficiency ) (informatio (capital need) i, t 1 n asymmetry) i, t + γ + γ 9 2 i, t = (ICM size) i, t 1 (relative i, t 1 + γ 2 i, t 1 + γ 7 value) + γ 5 3 (ICMefficiency ) (ICMsize ICMefficiency ) (informati on asymmetry ICMefficiency ). i, t 1 The subsequent sections describe the proxies used for the above variables and their i, t 1 univariate statistics. Detailed definitions for all variables are given in Appendix Dependent Variable: Use of External Capital I compute a measure of net external capital raised by diversified firms in excess of that raised by single segment firms as follows. First, I compute net external capital as the proceeds from the sale of debt, common and preferred stock minus the amount of debt retired and common and preferred stock repurchased. To make the use of external capital comparable between diversified and single segment firms, I compute an imputed value of net external capital based on the median of single segment firms in the same 3-digit SIC code as the divisions of the diversified firm. I match the median ratio of net external capital to sales to the individual segments of the diversified firms according to year and industry. Then I multiply each segment s imputed ratio by segment sales and add up all of the imputed net external capital values to form a firm-level imputed net external capital amount. I call the final measure Excess Net External Capital (EEC) and compute it as follows: Excess net external capital = Net external capital Imputed Lagged book value of assets 2 i, t 1 + net external capital A positive EEC implies that a diversified firm raises more net external capital than do comparable single segment firms in its industries. Table 1 shows that the median and mean EEC for diversified firms are significantly below the median and mean EEC for single segment firms. The median for diversified firms is and is significantly different from zero, which is the median of single segment firms, by construction. The mean for diversified firms is and is significantly different from zero at the 1% level, but this average is still significantly below the single segment mean, which is Consistent with Williamson (1975) these numbers suggest that diversified firms use external capital markets less extensively than single segment firms. However, the use of external capital should depend on a firm s ICM characteristics. Thus a multivariate analysis is needed. Further, the univariate test statistics should be interpreted with caution because the panel data observations are not independent. i, t 1 (1) 10

12 2.2.2 Measures of the Size of the ICM The measure of size of the ICM has three basic aspects. The first is the number of different operations or divisions; the second is the correlation of investment opportunities between these divisions; the third is the size differences between the divisions. A measure of ICM size that encompasses all three aspects is diversity, used by Rajan et al. (2000). Diversity is defined as the standard deviation of the segment asset-weighted imputed q divided by the equally weighted average imputed segment q. There is a significantly positive median for diversity of (Table 1). A higher value of the variable can indicate more divisions, less dependence in the segments investment opportunities, and/or segments of more equal size. Thus, according to Stein (1997), a higher value of diversity should be positively related to EEC if and only if a firm is internally allocating capital efficiently. Alternative measures that capture individual aspects of ICM size are the number of business segments a firm reports or the inverse of the Herfindahl Index. For more detailed definitions see Appendix Measures of ICM Efficiency Stein (1997) shows that it is critical that headquarters be good at distinguishing between good and bad projects and that the internal allocation be efficient. An ICM is considered efficient if investment is allocated to the projects/segments with the highest marginal return. I use two proxies to measure the allocational efficiency of the ICM. The first measure is the relative value added by allocation (RVA) introduced by Rajan et al. (2000). I compute RVA as follows: RVA = ( q q) n ss n ss BA j Capex Capex j Capex Capex j j j j 1 w ss j ss 1 j= BA BAj BA j= BAj BA j j, where BA is book value of assets of the firm, BA j is the book value of assets of segment j, Capex is the firm s capital expenditures, ss ss Capex BA is the asset-weighted average ratio of j j single segment firms in the same industry as the segment of the diversified firm, w j is the ratio of segment j assets to firm assets, q j is the asset-weighted Tobin s q of single segment firms operating in the same three-digit SIC industry as segment j, and q is the segment sales-weighted q j s of the firm. BA, q j and w j are beginning-of-the-period values. The expression ss Capex Capex j j ss is a proxy for transfers made between segments of a BAj BA j diversified firm. It compares the segment s investment ratio to the asset-weighted average 11

13 investment ratio of single segment firms in the same industry. The latter serves as a proxy for what a segment s investment ratio would have been were it a stand-alone entity. ss n = Capex Capex j j wj is a proxy for the overall funds available to a diversified firm relative j ss 1 BA j BA j to its single segment peers. This term is subtracted from the industry-adjusted investment ratio to correct for potential differences in availability of total capital that should not count as transfers. ( q j q ) identifies segments within a firm that have better-than-firm-average investment opportunities. Thus, a firm with an efficient ICM should have a positive RVA because it transfers capital to segments with better-than-firm-average investment opportunities and invests more than single segment peers do in those segments. 12 A second measure of the efficiency of internal allocation, used by Peyer and Shivdasani (2001), is q-sensitivity of investment. q-sensitivity is defined as follows: n Capex Firm Capex Salesj q j q Firm Sales j= Sales j Firm Sales ( ), 1 where q j is the imputed Tobin s q of segment j and q is the segment sales-weighted q j s of the firm. Capex is the capital expenditures of the segment, and Firm Capex is the capital expenditures of the firm. This measure is positive if a segment with a q above the firm s average q has an above-firm-average investment ratio (capital expenditures/sales) and a segment with below-average q has a below-firm-average investment ratio. Therefore, q-sensitivity indicates whether headquarters has invested relatively more in the high-q segments of the firm and relatively less in the low-q segments based on the firm s available resources. A third measure is based on Maksimovic and Phillips (2001) and Schoar s (2001) analysis of the effect of differences in segment productivity. These papers suggest that a firm is efficiently allocating capital if more investment is allocated to divisions with above average productivity. As a proxy for segment productivity, Maksimovic and Phillips (2001) show that segment cash flow can be used. I construct a measure called cash flow-sensitivity as in Peyer and Shivdasani (2001), where the expression ( q j q ) in q-sensitivity is replaced with ( cf j cf ). cf j is the cash flow to sales ratio of segment j and cf is the average cash flow to sales ratio of the firm. This measure also serves as a robustness check because it does not rely on imputed values but rather on individual segment level information. 13 The measures of ICM efficiency use capital expenditures to proxy for segment investment. Because the amount of capital expenditures is, in part, determined by a firm s use of external 12

14 capital, the proxies for ICM efficiency are potentially simultaneously determined with my proxy for a diversified firm s use of external capital. To alleviate this problem, I use lagged values of the measures of ICM efficiency as instruments. Table 1 shows univariate statistics RVA, q-sensitivity and cf-sensitivity. RVA (cf-sensitivity) has a median of (0) and a mean of ( ) that is significantly negative at the 10% level. 14 Q-sensitivity has a median of 0 and a significantly positive mean of For single segment firms, these measures are always zero by definition. Also interesting are the univariate statistics in Panel B of Table 1. Mean and median EEC are reported for firms stratified by RVA and diversity. Consistent with Stein s (1997) predictions, diversified firms with positive RVA and a measure of diversity larger than the sample median diversity display the highest EEC. Firms with negative RVA and a measure of diversity larger than the median display the lowest EEC indicating that ICM size can have very different effects on a firm s use of external capital depending on the efficiency of internal capital allocation Measures of Information Asymmetry I use several measures for the degree of information asymmetry. First, I use the lagged ratio of intangibles to total assets, expecting it to be negatively related to EEC. The advantage of this ratio is that it is not affected by prices set in the external capital market, i.e., using this proxy, it should be possible to identify the degree of information asymmetry that exists between managers and outside investors. 15 A second set of proxies is based on prices. Following Dierkens (1991) and Fee and Thomas (1999), I compute residual variance and total variance of the daily stock returns over a calendar year prior to the fiscal year-end. I use a market model to extract daily residual returns and compute the variance over all of the available daily residual returns. The CRSP value-weighted index, including dividends, is used as a proxy for the market return. As shown in Table 1, the median daily residual variance (total variance) for diversified firms is ( ) and the median for single segment firms is ( ). As a third set of proxies, I use IBES analysts forecasts about a firm s earnings per share. I construct a standardized measure of analysts forecast dispersion using the standard deviation of the one-year-ahead forecast of earnings per share standardized by the absolute value of the average forecast. A higher value of this measure is expected to indicate greater information asymmetry because it reflects a wider range of forecasts about the future earnings of a company. The standardized analysts forecast dispersion could be computed for only 4,021 firm-years. For 3,370 firm-years, IBES information is missing. Another 1,147 observations are lost because only one analyst s forecast is available, and no standard deviation can be computed. 13

15 To test the argument made in section 1, that a diversified firm with an efficient internal capital allocation can alleviate the effect of information asymmetry on the firm s use of external capital, I compute the following interaction variable. I create a dummy variable (RVADUM t 1 ) that is equal to one if RVA at the beginning of the year (t-1) is greater than or equal to zero and interact it with a proxy for information asymmetry Measures of Capital Need Stein s (1997) theory is based on the assumption that an entrepreneur has to raise external capital for his projects because the financing needs exceed his personal wealth. Internally generated cash flow from previous years is exogenous to the model. Matsusaka and Nanda (2001) show that higher levels of internal capital reduce the need for costly external capital. As a proxy for internal capital available to the firm, I compute excess internal cash flow. Internal cash flow is defined as net cash flow from operations minus dividends. Excess internal cash flow is computed in a similar way as EEC. 16 I expect a firm with more excess internal cash flow to cover more of its capital needs with internal capital. Hence a negative relation between excess internal cash flow and EEC is expected, holding everything else constant. Table 1 shows that the median of excess internal cash flow is significantly positive for diversified firms. Further, both median and mean excess internal cash flow are higher for diversified firms than for single segment firms. The need for capital is also determined by the available growth opportunities. As a proxy for growth opportunities, I use the firm s Tobin s q at the beginning of the period. I expect firms with a higher q to be in greater need of capital, holding everything else constant. One complication in using q is that it might also be a proxy for information asymmetry. If so, one would expect a negative relation between q and EEC Measures of Relative Valuation Myers & Majluf (1984) show that firms that are overvalued are more likely to issue risky new securities. Findings by Lucas and McDonald (1990), Asquith and Mullins (1986), Mikkelson and Partch (1986), and Jung et al. (1996) confirm that firms are more likely to issue new securities when their relative valuation is high. I use the stock return over the prior fiscal year and lagged excess value as proxies for relative valuation. I follow Berger and Ofek (1995), and define excess value as follows: V Excess value = log I ( V ) n, and I ( V ) 1 Sales [ M ( V / ) ] = i = Sales i MS, where V is the sum of market value of equity and book value of assets less the book value of equity and deferred taxes, I(V) is the imputed firm value, Sales i is segment i s sales, M i (V/Sales) MS i 14

16 is the sales multiplier (calculated as the median of the single segment firms in the same 3-digit SIC code industry), and n is the number of segments per firm. An alternative way to compute excess value is developed by Lang and Stulz (1994). They compute excess value as the difference between Tobin s q of the diversified firm and the segment asset weighted average of imputed segment qs. Their imputed q is the average of the single segment firms qs. I compute the log of the ratio of the firm s Tobin s q to the sum of segment sales-weighted imputed qs. The imputed qs are median qs of single segment firms in the same 3-digit SIC code industry. A positive relation to EEC is expected if higher stock returns and excess values indicate higher relative valuations. 2.3 Results Table 2 reports the regression results of equation (1) with EEC as the dependent variable. Since the predictions relate to cross-sectional differences, Table 2 reports time-series averages of coefficients of cross-sectional regressions run year-by-year. The reported t statistics are based on the time-series variation in the coefficients. This procedure is similar to that of Fama and MacBeth (1973) and is also used in Rajan et al. (2000). 17 Models 1 4 show results using different measures of the size of the ICM. In model 1 the coefficient on diversity is significantly negative ( 0.003). However, the interaction term with allocational efficiency, RVADUM, is significantly positive (0.005). This supports the predictions, and is consistent with the univariate statistics in Panel B of Table 1. The results still hold even after introducing diversity squared as shown in model 2. Only firms with an efficient internal capital allocation display a significantly positive relation with EEC. Similar inferences can be drawn from the other two proxies of ICM size, the number of segments and the inverse of the Herfindahl Index. For example, model 3 shows that the coefficient on the number of segments is significantly negative ( 0.026) but the interaction with RVADUM is significantly positive (0.040). Increasing the number of segments from one to two, i.e. diversifying, decreases EEC by 0.026, unless the firm has a positive measure of RVA, in which case, EEC increases by an overall ( ). Given the average difference in EEC between single segment and diversified firms of 0.015, it seems that a change in the number of segments has an economically significant impact on a firm s use of external capital. The coefficients on the proxies for ICM efficiency are always positive and significant at the 5% level. In model 1, the coefficient on RVA is The point estimate suggests that a onestandard deviation increase (0.0195) in RVA increases EEC by Again, this corresponds to about the average difference in EEC between single segment and diversified firms. Model 5 uses 15

17 q-sensitivity instead, and finds a significant positive coefficient. Firms with a more efficient internal capital allocation use more external capital, consistent with Stein (1997). This conclusion is also supported by model 6 where the coefficient on cf-sensitivity is significantly positive (0.019). Thus, firms that allocate more investment to divisions with above firm average productivity use more external capital. 18 The measures of information asymmetry are expected to be negatively related to EEC. Of specific interest for the tests in this paper is whether diversified firms with a more efficient ICM display a less negative sensitivity to information asymmetry. Model 1 reports that the coefficient on the lagged ratio of intangibles to total assets ( 0.176), and the coefficient on residual variance ( 6.544) are significantly negative supporting Myers and Majluf (1984). Moreover, the coefficient on the interaction variable between the lagged ratio of intangibles to total assets and RVADUM t 1 is significantly positive (0.159). None of the implications change if total variance is used instead of residual variance, as shown in model 7. Model 8 shows that the standardized analysts forecast dispersion is significantly negatively related to EEC, with a coefficient of The coefficient on the interaction variable between the standardized analysts forecast dispersion and RVADUM t 1 is significantly positive (0.003). The finding that the interaction variables display a positive correlation with EEC is consistent with the notion that firms with an efficient internal capital allocation can overcome some of the information asymmetry problems in transacting with the external capital markets. The proxies for need for capital are excess internal capital and beginning-of-the-year Tobin s q. Excess internal capital is significantly negatively related to EEC in every model. The coefficient of in model 1 suggests that a firm that has one dollar more internal capital than a comparable single segment firm will use about 72.5 cents less external capital than its single segment peers. Note that this coefficient is also significantly different from one, thus further supporting the notion that market frictions make internal and external capital imperfect substitutes. Tobin s q is significantly positively related to EEC. The coefficients on the measures of relative valuation are significantly positive in all the models (in three cases, excess value is significant only at the 10% level). In model 1, the lagged annual stock return has a coefficient of 0.037, and is significant at the 1% level. The coefficient on lagged excess value is 0.009, and significant at the 5% level. Model 9 shows that the coefficient on lagged excess value computed according to Lang and Stulz (1994) is also significantly positive (0.037). These findings are consistent with the interpretation that firms are more likely to issue new securities when their relative valuation is high. 16

18 Overall, the regression results show that firms with more divisions and with more independent divisions use more external capital relative to their single segment peers only if the firm is allocating capital efficiently in its ICM. Also, such firms can alleviate the impact of information asymmetry problems when accessing external capital markets and use more external capital. These findings suggest that the use of external capital significantly depends on the characteristics of the ICM. 2.4 Robustness In this section I examine the robustness of the findings presented in Table 2 by investigating issues of supply and demand of external capital, including single segment firms in the analysis, employing a different econometric method and by using different definitions of the dependent variable. The exact definitions of the alternative dependent variables are given in Appendix 1. Table 1 reports their univariate statistics Supply and Demand of External Capital In essence, equation (1) is a reduced form of a supply equation and a demand equation for external capital. Thus, a priori, it is not clear whether the coefficients on ICM size and efficiency reflect supply side effects, as Stein s (1997) model would imply. I perform the following test to address the question of whether changes in the ICM characteristics affect the supply of external capital holding demand constant. I select a sample of diversified firms where the demand for external capital is held constant but ICM characteristics are allowed to vary. Thus, holding demand constant, the coefficients should reflect the effects of changes in the supply of external capital. This sample consists of firms where the change in Tobin s q, as a proxy for future investment opportunities, and the change in internal cash flow between two consecutive years is within plus or minus 5%. 330 firms pass this screen. Table 3 reports OLS regression results testing the following equation: EEC = α + β ( ICMsize) + β ( ICM efficiency ) + β3( ICMsize ICM efficiency ) + β4( informatio n asymmetry) + (1') β ( informatio n asymmetry ICM efficiency ) β ( internal cash flow) + β ( investment 7 2 opportunit ies) In Table 3, all three models display significantly positive coefficients on the change in diversity (0.035 in model 1) and the change in RVA (0.439 in model 1). Further, the coefficient on the change in residual variance is marginally significantly negative ( in model 1) indicating that firms with an increase in information asymmetry experience a reduction in the supply of external capital unless they improve their allocational efficiency (coefficient of

19 on the interaction variable between the change in residual variance and a dummy variable equal to one if RVA has increased). Models 2 and 3 additionally control for the changes in the demand for external capital. With the exception of the coefficient on annual return (0.069), no demand side coefficient is significantly different from zero. Furthermore, the increase in R-squared from adding all the controls for the demand of external capital is only a marginal from (model 1) to (model 2). In summary, the results reported here are at least not contradicting the notion that the market s supply of external capital is dependent on ICM characteristics Including Single Segment Firms Even though I have defined an ICM as the mechanism by which HQ can allocate capital to the different divisions, one could also argue that a single segment firm s management allocates capital in much the same way but just to different projects within the firm. Thus, the question arises whether single segment firms are really different from diversified firms in their ability to reduce the impact of information asymmetry on the use of external capital based on their allocational efficiency. The main measure employed thus far to proxy for the efficiency of internal capital allocation, RVA, is zero by definition for all single segment firms. To allow for cross-sectional variation among focused firms I employ a measure called the absolute value added by allocation (AVA is defined in Appendix 1) used by Rajan et al. (2000). Table 4 shows the results. As indicated by the coefficient on the multi-segment dummy of 0.011, diversified firms, on average, use less external capital than comparable single segment firms. This is consistent with the findings in the univariate analysis. AVA is significantly positively related to EEC with a coefficient of However, the interaction variable between AVA and the multi-segment dummy is not significantly different from zero. 20 More interestingly, for single segment firms with a positive AVA there is no significant reduction in the impact of information asymmetry on the use of external capital. This is in stark contrast to the positive and significant coefficient on the interaction variable between AVADUM, the multi-segment dummy and the measure of information asymmetry. The results suggest that there are differences in the effect of internal capital allocation between single segment and diversified firms. 21 Only in diversified firms do we observe a significant reduction in the impact of information asymmetry. The finding that AVA is positively related to EEC is probably less surprising because firms that invest more than the median single segment firm in the industry probably also use more external capital to finance their investment than the median firm. Such an almost mechanical relation is not present in the RVA measure, but it is precisely the reason why RVA is zero for all single segment firms. Thus, it is all the more 18

20 surprising that single segment firms cannot relax information asymmetry problems in the same way that diversified firms can. 22 Having shown that adding single segment firms has no effect on the inferences drawn solely based upon the cross-sectional analysis of diversified firms, I concentrate on diversified firms only Econometric Methodology As an alternative to reporting time-series averaged coefficients from year-by-year crosssections, model 1 of Table 5 shows results using firm fixed-effects regressions. The coefficients and their significance levels are very similar to those reported in Table 2. None of the above conclusions are affected. However, the coefficients on Tobin s q and excess value are now insignificant, and the coefficient on residual variance decreases (significant at the 10% level) Excess Net External Capital with Dividends and Interest EEC, as defined thus far, does not consider dividends and interest payments as a decrease in external capital. In model 2 of Table 5, the regressions are re-estimated using EEC including interest and dividends as the dependent variable. None of the coefficients are significantly different from the base case in model 2 of Table 2. Note that in this model, the definition of excess internal capital is altered to include interest and dividend payments Excess Net External Capital with Asset Sales EEC does not consider proceeds from asset sales as an increase in external capital. There are several reasons for this. First, determinants of asset sales are likely to be quite different from determinants of new debt and equity issues. For example, Shleifer and Vishny (1992) show that selling assets in a depressed industry can lead to relatively low sales prices because asset markets become very illiquid. Schlingemann et al. (2001) find evidence that asset market liquidity is an important determinant of which division is sold. In addition, Gertner et al. (1994) demonstrate that diversified firms, especially those with efficient internal capital allocation, can redeploy poorly performing assets internally and therefore reduce their transactions in the asset market. Thus, a firm that allocates capital efficiently is expected to raise more external capital in the financial markets but raise less capital by transacting in the asset markets. I use the sum of the Compustat items sale of property, plant and equipment and sale of investment as a proxy for asset sales, add it to net external capital raised, re-compute EEC and show the regression results in model 3 of Table 5. The main difference from the regression using the base definition of EEC is that the coefficient on RVA and its significance decrease. Thus, the asset market appears to be used differently by firms with an efficient internal capital allocation. However, a complete evaluation of these differences is beyond the scope of this paper. 19