2.1. R&D expenditures and Firm performances
Most of the previous empirical findings suggest that R&D investment has a positive impact on firm’s performances such as, market value, market share, market growth in sales and Tobin’s q. Chan et al. (1990) find that share-price responses to 95 announcements of increased R&D spending are significantly positive even when the announcement occurs in the face of an earning’s decline. These results suggest that investors look beyond the short term earning’s impact of major strategic investment when valuing a firm’s stock. Chauvin and Hirschey (1993) also find a significant and positive relationship between R&D expenditures and market value of approximately 1500 US firms over a 3-year period from 1988 through 1990. Their results suggest that investors evaluate the R&D effort of firms with a long-term perspective.
Lee and Shim (1995), show that the relationship between R&D activity and market growth in high-tech industries is positive and significant in both United States and Japan over a 5-year period from 1986 through 1990. Szewczyk et al. (1996) document significant positive
announcement effects associated with increases in firms’ R&D and investment opportunities.
They also report a significant relationship of the market’s response to R&D announcements to the firm’s debt ratio and the level of institutional ownership. Bae and Seungwook (2001) examine the effect of the degree of a firm’s multinationality on the firm’s R&D activities.
They show that R&D expenditures as a percentage of sales are, on average, significantly greater for Multinational corporations (MNCs) than for domestic corporations (DCs), indicating that MNCs are on average, more R&D intensive. After controlling for firm and market-related factors, R&D expenditures are found to have a persistently positive effect on the market value of both DCs and MNCs, with more pronounced effect for MNCs.
Several studies have used q to measure specific intangible assets, by taking the predicted value from a regression of Tobin’s q on accounting or survey measures of the intangible asset of interest. Examples are Hall (1993); Megna and Klock (1993, 2000); Cockburn and Griliches (1988); Wernerfelt and Montgomery (1988); Bharadwaj et al (1999); Christoffersen (2002); Villalonga (2004). For example, Megna and Klock (2000), investigate the measurement and valuation of intangible capital in the wireless telecommunications industry.
Four specific sources of intangible capital are investigated: advertising, research and development (R&D), radio spectrum licenses, and measures of installed customer base. All four sources of intangible capital explain a statistically significant portion of the variation in Tobin’s q, but the variation explained by R&D is subsumed by that explained by licenses.
Together, licenses and advertising explain over 60% of the variation in q, and licenses are the much more powerful predictor of the two. Bharadwaj et al (1999), however, show the coefficient for R&D in a model with Tobin’s q as the dependent variable is negative.
The general consensus of the previous studies is that R&D investment increases the firm performance such as, market value, market share, market growth in sales and Tobin’s q. A firm’s R&D activities may work as intangible capital stocks, barriers to entry for other firms,
or market demand factors that bring positive values to a firm’s performances.
2.2. Related to literature with Tobin’s q
When Tobin (1969) first introduced the concept of q (defined as the ratio of the market value to replacement values of a firm’s assets), his intent was to capture a firm’s propensity to invest. Since that time, it is used in the literature as a proxy for a number of diverse corporate phenomena, such as the relationship between managerial equity ownership and firm value (Morck, Shleifer and Vishy 1988 and Cui and Mak 2002), the measure of investment opportunities (Szewczyk et al 1996), industry concentration (Wernerfelt and Montgomery 1988), corporate diversification (Lang and Stulz 1994), information technology (IT) investments (Bharadwaj et al 1999) and research and development (Cockburn and Griliches 1988; Megna and Klock 1993) has also been examined using the Tobin’s q. In particular, the q ratio has been used as a measure of firm’s intangible value. The use of q for measuring intangible value is based on the assumption that the long-run equilibrium market value must be equal to the replacement value of its assets, giving a q value close to unity. Deviations from this relationship (where q is significantly greater than one) are interpreted as signifying an unmeasured source of value, and generally attributed to the intangible value of the firm investments (Bharadwaj et al 1999). Several studies have also explored the relationship q and intangible value to examine the effects of factors such as R&D, patents and IT that are considered to contribute significantly to a firm’s intangible value (Megna and Klock 1993;
Hall 1999; Bharadwaj et al 1999).
Tobin’s q typically estimated using one of two competing approaches. The first, referred as the computationally costly approach, uses an extensive of financial statement information as a starting point for estimating both market and replacement values. The data are then adjusted for factors that are likely to cause systematic divergences between market and accounting values. A typical representative is Lindenberg and Ross (1981) approach that in the approach,
market price are collected for each traded financial claim (i.e., common stock, debt, or preferred stock) of the firm. The market values for each claim are then summed as an estimate of the market value of the entire firm. The replacement value of the firm is estimated by adjusting the book value of assets for cumulative inflation and depreciation occurring between the time fixed assets are placed in service and the present. Although this approach results in the most defensible estimate of the market value of the firm, it has enjoyed limited use because of the lack of widespread availability of machine-readable data sources for market prices of corporate debt and preferred stock claims. In contrast, the second approach, referred to as the simple approach, uses a comparatively small set of financial statement data with minimal adjustments. A typical representative is Chung and Pruitt (1994) approach, the advantage of this approach is that it uses a simple formula that requires financial and accounting information available from the Compustat database and is highly correlated with q calculated by using the more traditional Lindenberg and Ross’s approach, more detail discussion will be presented in the next chapter.