Full-text source: WilsonSelect - Information Technology



Full-text source: WilsonSelect

The valuation of corporate R&D expenditures: evidence from investment opportunities and free cash flow.

Author: Szewczyk, Samuel H.; Tsetsekos, George P. Zantout, Zaher. Source: Financial Management v. 25 (Spring '96) p. 105-10 ISSN: 0046-3892 Number: BBPI96050854 Copyright: The magazine publisher is the copyright holder of this article and it is reproduced with permission. Further reproduction of this article in violation of the copyright is prohibited.

[pic]

Past research shows a significant market response to announced increases in R&D expenditures (Woolridge, 1988). However, the reaction depends on the firm's industry. The reaction is significantly positive for firms operating in high-technology industries but significantly negative for firms in low-technology industries (Chan, Martin, and Kensinger, 1990, and Zantout and Tsetsekos, 1994). This suggests the investment opportunities hypothesis that R&D investments by firms with promising growth opportunities are generally worthwhile, whereas other R&D investments may be wasteful.

We provide confirmatory evidence of this market reaction using a different measure of investment opportunities, Tobin's q. Tobin's q is the ratio of the market value of the firm's assets to their replacement cost. Chan, Martin, and Kensinger (1990) and Zantout and Tsetsekos (1994) proxy growth opportunities using a binary (high, low) technology variable. Tobin's q may be a better measure than a binary proxy because many firms operate in multiple industries, which makes industry classification problematic. Also, even if a firm operates in a single mature industry, it may have differentiating competencies to create growth.

We also examine whether free cash flow can explain cross-sectional differences in the market's response to R&D increases. Jensen (1986) argues that managers will invest free cash flow in wasteful investments rather than pay it out to shareholders. The potential agency costs of R&D investments are arguably higher, therefore, for high-free-cash-flow firms. On the other hand, R&D investments by low-free-cash-flow firms increase the chance the firm will seek new external financing. New external financing provides monitoring, and the firm's willingness to undergo such monitoring may be a favorable signal. Therefore, we would expect that announcement-period abnormal returns for increases in R&D will be inversely related to free cash flow.

Free cash flow agency costs may depend on the firm's investment opportunities. Firms with relatively more growth opportunities are less likely to have free cash flow. Therefore, the potential agency costs of R&D expenditures are lowest for low-free-cash-flow/high-q firms. The converse holds for high-free-cash-flow/low-q firms. Accordingly, the free cash flow hypothesis predicts positive (negative) announcement-period abnormal returns for low-free-cash-flow/high-q (high-free-cash-flow/low-q) firms.

Consistent with past work, we find a positive relation between the market's response to announcements of increases in R&D and Tobin's q. This relationship holds after taking into account the effect of other potential explanatory variables. We do not find evidence that free cash flow explains cross-sectional differences in abnormal returns. However, we do find a positive relation between the market's response and the announcing firm's debt ratio and level of institutional ownership of its equity. This finding is consistent with a broad interpretation of the free cash flow hypothesis. A high debt ratio implies precommitted future cash flows and greater institutional oversight, both of which can lower the expected agency costs of free cash flow.

I. SAMPLE SELECTION AND DESCRIPTIONWe obtained a preliminary sample of R&D increase announcements from the Dow Jones News Retrieval database and applied four screening criteria: 1) The announcement is an initial announcement of a future plan to increase R&D expenditures; 2) the announced plan does not involve funding from customers or from government contracts; 3) the announced plan does not pertain to a joint venture or a cooperative agreement with another firm; and (4) the announcing firm has sufficient data on the Center for Research on Security Prices (CRSP) tape.

Our final sample consists of 252 announcements made between June 1979 and December 1992 by 121 NYSE- and AMEX-listed firms. The announcements are fairly evenly distributed on a per-year basis, with years ranging from 4.4% to 10.7% of the sample. Table 1 reports the sample's industry classification distribution.

Tobin's q is computed using the Lindenberg and Ross (1981) algorithm with the modifications described in Lang, Stulz, and Walkling (1989).(FN1) The test variable for q is the average q for the three fiscal years prior to the announcement.(FN2) The cash flow ratio is defined for the fiscal year before the announcement. It is operating income before depreciation minus interest expense, taxes, preferred dividends, and common dividends, divided by the book value of total assets (Lang, Stulz, and Walkling, 1991).

Of the 252 announcements, 121 have sufficient COMPUSTAT data to calculate q and cash flow ratios.(FN3) The mean q is 1.52, with a standard deviation of 1.31 and a range of 0.33 to 6.80. The mean cash flow ratio is 8.67%, with a standard deviation of 3.58% and a range of 1.12% to 18.19%.

II. EMPIRICAL RESULTSThis section provides the empirical results, which support the investment opportunities hypothesis but not the free cash flow hypothesis.

A. AVERAGE SHAREHOLDER WEALTH EFFECTSTable 2 reports the cumulative average abnormal stock returns for sample firms based on standard event-study methodology. Sample firms realize, on average, a significantly positive abnormal two-day announcement-period stock return of 0.477%. This result is not caused by outliers. Of the abnormal returns, 60.7% are positive. No significant abnormal returns are observed preceding and following the announcement period.

B. ABNORMAL STOCK RETURN DIFFERENCES BETWEEN SUBSAMPLESFollowing Lang, Stulz, and Walkling (1991), we divide our sample by firms with high and low q (above vs. below one) and by firms with high and low cash flow (above vs. below the sample median, 8.6%). Table 3 reports cumulative average abnormal two-day announcement-period returns for the subsamples. In Panel A, the sample is partitioned by q and the cash flow ratio. In Panel B, the sample is partitioned jointly by q and the cash flow ratio. T-test results and nonparametric Wilcoxon tests for differences between subsamples are also given.

As can be seen in Panel A, high-q firms have a significantly positive average abnormal return of 0.929%. In contrast, low-q firms have an insignificant average abnormal return of -0.16%. The difference is significant and consistent with the investment opportunities hypothesis.

Panel A also reports comparisons based on the cash flow ratio. There is no significant difference between high- and low-cash-flow firms.

The results shown in Panel B provide a direct test of the free cash flow hypothesis, by examining the joint effect of cash flow and q. According to the free cash flow hypothesis, low-cash-flow/high-q firms have the lowest potential agency costs connected with R&D expenditures. This subsample has a significantly positive average abnormal return of 1.11%, the highest among the four subsamples. However, the difference between low-cash-flow/high-q and high-cash-flow/high-q firms is not significant.

Also according to the free cash flow hypothesis, high-cash-flow/low-q firms have the largest potential agency costs connected with R&D expenditures. This subsample has an insignificantly positive average abnormal return. Moreover, there is again no significant difference between low-cash-flow/low-q and high-cash-flow/low-q firms.

The results in Panel B, then, do not support the free cash flow hypothesis. They do, however, provide some support for the investment opportunities hypothesis. The differences between high- and low-q firms are of the expected sign for both high- and low-cash-flow firms, although the difference is significant only for low-cash-flow firms.

In summary, the evidence in Panels A and B of Table 3 supports the investment opportunities hypothesis. However, consistent with Vogt's (1994) finding, the results do not support the free cash flow hypothesis.

C. CROSS-SECTIONAL REGRESSION ANALYSIS OF THE ABNORMAL STOCK RETURNSTable 3 results do not control for other factors that could influence the market's response to announcements of R&D expenditure increases. In this section, we report four cross-sectional regressions, one of which tests the investment opportunities and free cash flow hypotheses while controlling for several other factors.

Table 4 shows the regression results. They are consistent with those of Table 3. The coefficient for q is significantly positive for each model in which that variable is included. The coefficient for the cash flow ratio is insignificant. The intercept in Model 3 represents low-cash-flow/high-q firms and is significantly positive. As in Table 3, firms with a low cash flow ratio differ significantly from those with high versus low q in Model 3.

Model 4 regresses abnormal returns against Tobin's q, cash flow ratio, and twelve other potentially influential variables. Following Chan, Martin, and Kensinger (1990), we include R&D intensity, R&D increase, and industry concentration in the model. Firm size is included because large firms may be more successful in developing and exploiting new technologies (Chauvin and Hirschey, 1993). The firm's debt ratio and dividend yield are included as alternative measures of free cash flow (Jensen, 1986) and investment opportunities (Smith and Watts, 1992), respectively. Managerial ownership, institutional ownership, board composition, and CEO duality are included to control for the impact of ownership and organizational structure on monitoring managers (Jensen and Meckling, 1976) and information signaling (Leland and Pyle, 1977). A dummy variable for the post-1985 period is used to control for Hall's (1993) finding that the stock market valuation of intangible capital fell by more than a factor of three after 1985. Finally, a dummy variable is included for whether the announcement was "contaminated" by other contemporaneously announced information.(FN4) Missing data for the control variables reduced the usable sample size to 63 for Model 4.

The Model 4 results are also consistent with those in Table 3. Even after controlling for other potentially influential variables, the coefficient for Tobin's q is again significantly positive. Three control variables have significant coefficients in Model 4: 1) the proportional R&D increase, 2) the firm's debt ratio, and 3) the firm's proportion of institutional ownership. The larger the R&D increase, the more favorable is the signal. The effects of a higher debt ratio and greater institutional ownership are consistent with a broader interpretation of the free cash flow hypothesis, despite the insignificance of the coefficient for the cash flow ratio. A higher debt ratio and greater institutional ownership can lower the expected agency costs of free cash flow.

III. SUMMARY AND CONCLUSIONSPrevious research is consistent with the investment opportunities hypothesis. There is a significant market price response to R&D increase announcements, which is positive for high-technology firms but negative for low-technology firms. This study provides confirmatory evidence of the investment opportunities hypothesis using a different measure of investment opportunities, Tobin's q. High-q firms have a significantly positive reaction to an R&D increase announcement. Low-q firms have a negative reaction to such announcements. We further show that the relationship holds even after controlling for the effect of other potentially influential variables.

The study also examines the free cash flow hypothesis, which predicts a differential announcement effect that depends on the firm's level of free cash flow. No cross-sectional differences in abnormal announcement-period returns are found. However, there is tentative evidence of an interaction between free cash flow and q. The difference between high-and low-q firms is most pronounced for firms with a low cash flow ratio. Also, we find positive effects for a firm's debt ratio and its proportion of institutional ownership. Therefore, we conclude that the evidence provides some support for a broad interpretation of the free cash flow hypothesis.

Added material.

Samuel H. Szewczyk is Associate Professor of Finance and George P. Tsetsekos is Professor of Finance at Drexel University, Philadelphia, PA. Zaher Zantout is Assistant Professor of Finance at Rider University, Lawrenceville, NJ.

Table 1. Sample Distribution by Industry Classification The sample consists of 252 R&D increase announcements made between June 1979 and December 1992 by 121 NYSE- and AMEX-listed firms. Observations that involve funding from customers or from government contracts or pertain to joint ventures or cooperative agreements with other firms are excluded.

(TABLE) Number of Announcing Number of Industry Firms Announcements Percent of Sample (%)Aircraft/defense 4 9 3.6Automotive 5 8 3.1Chemicals 19 37 14.7Electronics 7 13 5.2Food and beverage 6 7 2.8Fuel 2 2 0.8Information processing 14 24 9.5Instruments 19 34 13.5Machinery 5 6 2.4Paper and forest products 3 3 1.2Pharmaceuticals 21 72 28.6Primary metals 3 7 2.8Semiconductors 9 15 5.9Telecommunications 4 15 5.9Total 121 252 100.0.

Table 2. Cumulative Average Abnormal Returns The sample consists of 252 R&D increase announcements. Abnormal returns are computed as the prediction error in the market model. Day 0 in event time is date of the announcement's report on the Dow Jones News Wire. t-statistics are computed using the cross-sectional standard deviations. Percent positive is the percentage of abnormal returns having positive values.

(TABLE)Period Relative to the DJN Cumulative Average Announcement Abnormal Stock Return (%) t-Statistic Percent Positive (%) (-30, -1) -0.761 -1.16 46.4 (-20, -1) -0.262 -0.50 47.6 (-10, -1) 0.117 0.33 51.2 (0, 1) 0.477 2.21(FN**) 60.7 (2, 10) -0.198 -0.58 49.2 (2, 20) -0.689 -1.37 45.2 (2, 30) -0.759 -1.19 46.8.

FOOTNOTES*** Significant at the 0.01 level in a two-tailed test.

** Significant at the 0.05 level in a two-tailed test.

* Significant at the 0.10 level in a two-tailed test.

Table 3. Two-Day Cumulative Average Abnormal Stock Returns, by Tobin's q and Cash Flow Ratio The sample consists of the 121 R&D increase announcements with complete data on the firm's Tobin's q and the cash flow ratio. High- and low-q firms are defined by q being above or below one, respectively. High- and low-cash-flow firms are defined by a cash flow ratio being above or below the sample median, 8.6%. For each cell, the t-statistic and the number of observations are shown in parentheses. For comparisons of means, the t-statistic and the nonparametric Wilcoxon statistic are shown in parentheses. The results are the same assuming equal variances.

(TABLE) Panel A. Analysis of Subsamples Based on Tobin's q and the Cash Flow Ratio Tobin's q Cash Flow RatioHigh 0.929 0.499 (2.75(FN***), 58) (1.45, 60)Low -0.160 0.227 (-0.48, 63) (0.67, 61)Mean Difference 1.089 0.271 (2.30(FN**), 2.20(FN**)) (0.56, 0.24) Panel B. Analysis of Subsamples Based on Tobin's q and the Cash Flow Ratio Simultaneously High q Low q Mean DifferenceHigh Cash Flow Ratio 0.809 0.065 0.744 (1.84(FN*), 35) (0.12, 25) (1.06, 1.06)Low Cash Flow Ratio 1.111 -0.307 1.418 (2.07(FN**), 23) (-0.74, 38) (2.08(FN**), 1.93(FN**))Mean Difference -0.301 0.372 (-0.43, -0.67) (0.54, 0.27).

FOOTNOTES*** Significance at the 0.01 level in a two-tailed test.

** Significance at the 0.05 level in a two-tailed test.

* Significance at the 0.10 level in a two-tailed test.

Table 4. Cross-Sectional Regression Analyses of the Two-Day Cumulative Abnormal Stock Returns The sample consists of the 121 R&D increase announcements with complete data on the firm's Tobin's q and cash flow ratio. The number of observations for Model 4 is 63 because of missing data on some of the control variables. High- and low-q firms are defined by q being above or below one, respectively. High- and low-cash-flow firms are defined by a cash flow ratio being above or below the sample median, 8.6%. D1, D2, and D3 are dummy variables that, along with the intercept, partition the sample into the 2X2 making up subsamples. Firm size is the natural logarithm of the firm's market value of equity. Industry is defined by the four-digit SIC code. Industry concentration comes from the Census of Manufactures. R&D intensity is the firm's ratio of R&D to sales divided by the industry's average R&D to sales ratio. R&D increase is the announced percentage increase in the R&D budget. Debt ratio is the firm's total debt to total assets divided by the industry's average debt ratio. Dividend yield is the firm's dividend to price per share divided by the industry's dividend yield. Financial data come from COMPUSTAT. Managerial ownership is obtained from the most recent proxy statement before the announcement date. Institutional ownership is obtained from the most recent issue of Standard and Poor's Stock Guide before the announcement date. Board composition and the dummy variable indicating if the CEO is also the chairperson of the board are obtained from Moody's Industrial Manual. Period is a dummy variable for announcements made before and after 1985. t-statistics are shown in parentheses.

(TABLE) Model number 1 2 3 4Intercept -0.324 (-0.90) 0.007 (0.01) 1.111 (2.03)(FN**) -3.951 (-0.81)Tobin's q 0.451 (2.51)(FN***) 0.503 (2.55)(FN***) 1.128 (2.75)(FN***)Cash flow ratio -0.047 (-0.66) 0.008 (0.07)Dl (high q and high cash flow ratio) -0.302 (-0.43)D2 (low q and low cash flow ratio) -1.418 (-2.05)(FN**)D3 (low q and high cash flow ratio) -1.046 (-1.38)Firm size -0.296 (-0.72)Industry concentration -0.001 (-0.07)Firm R&D intensity 0.106 (0.21)R&D increase 0.076 (3.30)(FN***)Firm debt ratio 3.190 (3.15)(FN***)Firm dividend yield -0.145 (-0.37)Managerial ownership -0.030 (-0.74)Institutional ownership 0.060 (1.91)(FN*)Percentage outsiders on board -1.824 (-0.76)CEO also chairperson dummy -0.297 (-0.31)Period 0.007 (0.01)Contamination dummy -0.318 (-0.30)R2 5.01% 5.35% 4.65% 41.09%F-statistic 6.27(FN***) 3.34(FN**) 1.90 2.39(FN***)Number of observations 121 121 121 63.

FOOTNOTES*** Significance at the 0.01 level in a two-tailed test.

** Significance at the 0.05 level in a two-tailed test.

* Significance at the 0.10 level in a two-tailed test.

The authors are grateful to Mike Gombola, Fen-Yen Liu, and two anonymous referees for helpful comments and suggestions, and to Thanasis Mavrakis for research assistance. This paper was supported by summer research grants from Drexel University and Rider University.

FOOTNOTES1 Chung and Pruitt (1994) provide an alternative simplified method of approximating Tobin's q.

2 Tests using the latest one-year q do not differ substantially. The correlation coefficient between the one-year q and the three-year average q is 95.56%. See Lang, Stulz, and Walkling (1989) for a discussion of the advantages of using a three-year average.

3 The excluded firms have an average market value of $5,620 million. The 252 firms have an average market value of $6,274 million.

4 To determine whether an announcement was contaminated or not, we examined the Dow Jones News article supplying the R&D announcement and screened the Wall Street Journal Index for contemporaneous announcements. Of the 121 announcements screened, only 37 did not have contemporaneous announcements.

REFERENCESChan, S.H., J. Martin, and J. Kensinger, 1990, "Corporate Research and Development Expenditures and Share Value," Journal of Financial Economics (August), 255-276.

Chauvin, K. and M. Hirschey, 1993, "Advertising, R&D Expenditures, and the Market Value of the Firm," Financial Management (Winter), 128-140.

Chung, K.H. and S.W. Pruitt, 1994, "A Simple Approximation of Tobin's q," Financial Management (Autumn), 70-74.

Jensen, M., 1986, "Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers," American Economic Review (May), 323-329.

Jensen, M. and W. Meckling, 1976, "Theory of the Firm: Managerial Behavior, Agency Costs, and Ownership Structure," Journal of Financial Economics (October), 305-360.

Hall, B., 1993, "The Stock Market's Valuation of R&D Investment During the 1980's," American Economic Review (May), 259-264.

Lang, L., R. Stulz, and R. Walkling, 1989, "Managerial Performance, Tobin's q, and the Gains from Successful Tender Offers," Journal of Financial Economics (September), 137-154.

Lang, L., R. Stulz, and R. Walkling, 1991, "A Test of the Free Cash Flow Hypothesis: The Case of Bidder Returns," Journal of Financial Economics (October), 315-335.

Leland, H. and D. Pyle, 1977, "Informational Asymmetries, Financial Structure, and Financial Intermediation," Journal of Finance (May), 771-387.

Lindenberg, E. and S. Ross, 1981, "Tobin's q Ratio and Industrial Organization," Journal of Business (December), 1-32.

Smith, C. and R. Watts, 1992, "The Investment Opportunity Set and Corporate Financing, Dividend, and Compensation Policies," Journal of Financial Economics (January/March), 25-54.

Vogt, S., 1994, "The Cash Flow/Investment Relationship: Evidence from U.S. Manufacturing Firms," Financial Management (Summer), 3-20.

Woolridge, J.R., 1988, "Competitive Decline and Corporate Restructuring: Is a Myopic Stock Market to Blame?," Journal of Applied Corporate Finance (March), 26-36.

Zantout, Z. and G. Tsetsekos, 1994, "The Wealth Effects of Announcements of R&D Expenditure Increases," Journal of Financial Research (September), 205-216.

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download