Market expansion and R&D externality effect.
Jiang, Yi
ABSTRACT
I examine the externality effects of R&D investments. I find
that firms' future operating performance is positively related to
industry peers' R&D expenditures. Firms also tend to experience
positive abnormal returns following industry peers' high R&D
expenditures. This suggests that the market not only underreact to a
firm's own R&D investments, but also to industry peers'
R&D investments. Consistent with this notion, the market is
surprised by firms' earnings performance following high peer
R&D investments. Finally, I present evidence that the positive
externalities of R&D investments may be due to the market expansion
caused by technology advances.
JEL Classifications: O3, G1, G02
Keywords: R&D externality; market expansion; stock return
predictability
I. INTRODUCTION
An extensive literature in finance studies the valuation effects of
corporate decisions/actions such as investing, financing or payout
decisions, and whether the stock market immediately incorporates these
effects. Little attention, however, has been paid to the externality
effects of these decisions, i.e., how one firm's action affects the
valuations of its peer companies. This is an important gap to be filled
due to the significance of the topic. Studying externality effects
enhances our understanding of the economy-wide benefits or costs of a
certain corporate action and is therefore useful to regulators in
forming regulatory decisions. It is also useful to investors and
managers because they need to understand how (and how much) their peer
companies' actions will affect the valuation of their firms and
thus make more informed trading or managerial decisions.
Externalities of corporate decisions are plausible because peer
companies (typically those in the same industry) employ similar or
related raw materials and technologies/methods, and interact with same
groups of customers and suppliers. In different situations, externality
can be negative due to competition or positive if one firm's action
can benefit or damage the whole industry. There has been some (albeit
limited) evidence of such externalities. Hsu et al. (2010) and Braun and
Larrain (2009) show that peer companies experience negative stock price
reactions to IPOs in their industry, which is consistent with
IPO-induced competitive advantages. Lang and Stulz (1992) documents both
contagion and competitive effects for firms in the same industry upon
bankruptcy announcements.
In this study, I analyze the cross-firm valuation effect of an
important type of corporate investments in intangible
assets--firms' R&D spending. More specifically, I focus on the
intra-industry effect, i.e., how a firm's stock return is affected
by the R&D investments of firms in the same industry. A large body
of literature in economics (e.g., Hall (1993), Griliches (2002)) has
shown that R&D investments by private-sector firms generate positive
spillovers on the output growth and productivity increase within the
same industry, in the downstream industries, as well as across regions
and countries. Such spillovers are believed to be an important source of
endogenous economic growth (e.g., Romer (1990a; 1990b); Griliches
(1992)), and form the basic rationale for public policies on
private-sector R&D investments.
I add to this literature by studying the valuation impact of
firms' R&D expenditures on their peer companies in the same
industry. My focus on R&D expenditures offers several advantages.
Unlike the studies aforementioned that investigate firms' capital
market transactions, I study externalities of firms' internal
investments, which have no obvious market-timing motives. In addition,
Eberhart et al. (2004) argue that R&D investments are distinctive
from other long-term investments due to the stark contrast between its
tangible costs and intangible benefits. Since the market tends to
misreact to intangible information but not to tangible information
(Daniel and Titman (2001)), it is interesting to examine the
market's ability to incorporate the valuation impact of
R&D's intangible benefits, both on the investment firm itself
and on its peers.
Existing studies have documented that high R&D expenditures or
large R&D increases are associated with subsequent positive abnormal
stock returns as well as positive abnormal operating performance (see
Chan et al. (2001), Eberhart et al. (2004), Lev and Sougiannis (1996),
and Lev et al. (2005)). These findings suggest that the market tends to
underreact to the benefits of R&D expenditure. If R&D
investments have positive externalities and the market also underreacts
to such effects, then economists as well as investors may have
underestimated the social benefits of R&D expenditures. Such social
benefits should be taken into account in determining how to treat
R&D in accounting rules, e.g., whether to require firms to fully
expense their R&D expenditures or allow them to capitalize them in
financial statements. Such discussion is timely when lawmakers are
debating whether to extend certain tax cuts/benefits including R&D
credits.
Using a sample of Compustat firms for the period of 1975-2012, I
document evidence for positive externalities of R&D investments. I
find that firms' future operating performance is positively related
to peer firms' R&D investments. The results hold after I
control for a firm's own R&D expenditures. This suggests that
firms benefit from peers' R&D investments.
I then examine whether the stock market efficiently incorporates
such value implication. I find that firms tend to experience positive
abnormal returns in the year subsequent to high peer R&D
investments, suggesting that the market underreacts to the externalities
of R&D. Given that the valuation impact of the R&D externalities
has not been documented before, regulators, economists as well as
investors may have underestimated the benefits of R&D investments.
Consistent with the notion that the market underreacts to the
externality effects of R&D, I also find that the market is surprised
by firms' earnings performance following high peer R&D
investments. Specifically, future earnings surprises and abnormal stock
returns around earnings announcements are significantly positive where
industry peers have high R&D investments, whereas these measures are
insignificantly different from zero where industry peers have low
R&D investments.
Finally, I identify a channel through which the benefits of R&D
investments can spill over to other firms in the industry: advances in
technology expand the market demand. Consistent with this hypothesis, I
find that industry sales and employment grow faster when industry
R&D intensity is high; and that the positive externality effect on
operating performance is stronger where the market expands more.
II. DATA AND DESCRIPTIVE STATISTICS
The sample includes Compustat firms for the period from 1975
through 2012. I impose the following sample criteria. (1) I require that
the stock return data and financial statement data are available from
CRSP and COMPUSTAT. (In some subsample analysis I also require
analysts' earnings forecasts data are available from IBES.) (2) I
exclude any firm-year observations for which total assets (Compustat
variable AT) or sales (Compustat variable SALE) are either zero or
negative. (3) Following Fama and French (1993), I exclude firms with
negative book values of equity. (4) I also exclude firms with stock
price less than $5. (5) Utility firms (SIC=4900-4999) and financial
firms (SIC=6000-6999) are excluded since they operate in a regulated
environment and their characteristics differ substantially from
nonregulated firms. (6) For a firm-year (or industry-year) observation
to be included in the sample, I require the number of firms in the
industry to be at least ten in that year. Firms are classified into 48
industries based on Fama-French (1997). (7) I require that firms have
nonnegative R&D expenditures. Missing R&D expenditures are coded
as zero. The resulting full sample consists of 89,782 firm-year
observations for the period of 1975-2012. For the subsample analysis
that further requires analyst earnings forecast data from IBES, the
sub-sample consists of 47,053 firm-year observations.
I use three operating performance measures: gross profit margin
measured sales minus costs of goods sold, divided by sale; gross ROA as
sales minus costs of goods sold, divided by lagged assets; and sales
growth rate. (1) I also use three variables to measure market expansion:
industry sales growth as the growth rate of the aggregate industry
sales, Industry employment growth as growth rate of the aggregate
industry employment, and new firm entry as the number of new firms
relative to the number of all firms at the end of last year. R&D
expenditures are scaled by lagged sales (RDS), lagged assets (RDA), or
by lagged market value of equity (RDE).
When computing industry peers' R&D expenditures for firm
i, I use the mean RDS (or RDA, or RDE) for firms in the same industry
excluding firm i: the corresponding industry variables are IRDS (or
IRDA, or IRDE). In robustness checks, I use just industry R&D
leaders as the peer group, where leaders are those whose RDS (or RDA or
RDE) are among the top 30%. Results are robust.
In studying the impact of peer R&D investments, I also control
for a firm' own characteristics in addition to its own R&D
expenditures, including the firm size as the natural logarithm of market
value of equity (ln(size)), the leverage ratio (LEV), the book-to-market
ratio (ln(B/M)) and the average monthly stock return in the previous 12
month (PrRET). Variable definitions are also listed below. All variables
except for PrRET are winsorized at the 1% and 99% percentiles. (2) All
dollar values are in 2012 constant dollars.
Table 2 presents the summary statistics of these variables. I
report the mean, median, min, max and standard deviation of main firm
characteristics, market expansion variables, and operating performance
variables. The mean (median) gross profit margin, gross ROA, and sales
growth are 0.34(0.33), 0.47(0.42), 0.17(0.11). The mean (median)
aggregate sales growth rate is 14% (13%). The mean (median) industry
employment growth rate is 8% (6%). On average, 5% of new firms will
enter the industry each year. The mean (median) RDE, RDS and RDA are
0.06(0), 0.06(0) and 0.04 (0), respectively.
III. RESULTS
In this section I examine the R&D spillover effects. I analyze
the externality of R&D on corporate operating performance, stock
returns, and future earnings news. I also examine a possible channel for
the spillover effect.
A. Industry Peer's R&D Expenditures And Future Operating
Performance
I first examine the externality of R&D investments on corporate
operating performance. I hypothesize that a firm's operating
performance not only depends on its own R&D investments but also the
industry's R&D investments. To test the hypothesis, I estimate
the following regressions:
Operating [Performance.sub.i,t+k] = [b.sub.0] + [b.sub.1] x
R&[D.sub.peer,t] + [b.sub.2] x R&[D.sub.i,t] + [beta] x Controls
+ [e.sub.it] (1)
where operating performance measures are gross profit margin, gross
ROA or sales growth; k=1, 2 or 3 years; and peer firms include firms in
the same industry excluding firm i. Firm's own R&D intensity
measures are RDE, RDS, and RDA. Industry peer's R&D intensity
measures are IRDE, IRDA and IRDS, respectively. The control variables
are log of market capitalization (lnSIZE) and firm leverage (LEV). If
the competitive effect dominates the spillover effect, then
[b.sub.1]<0; if the spillover dominates the competitive effect, then
[b.sub.1]>0.
The regression results of Equation (1) are reported in Table 3.
Gross profit margin and Gross ROA are positively and significantly
related to industry peer's R&D intensity measures
IRDE/IRDA/IRDS for years t+1, t+2 and t+3, respectively (all of the
coefficients are significant at the 10% level). Those results are also
economically significant. For example, one standard deviation increase
in IRDS causes Gross profit margin, Gross ROA, and Sales growth to
increase by 2.5%, 3.6% and 3.3% in year t+1, respectively. In
comparison, the mean Gross profit margin, mean Gross ROA and Sales
growth are 0.34, 0.47 and 0.17, respectively in the full sample. Sales
growth is always positively related to industry peers' R&D
expenditures but most of the coefficients [b.sub.1] are not significant.
In general, these results suggest that there is positive externality of
R&D expenditures on industry peers' future operating
performance. Table 2 also shows that a firm's own R&D intensity
has positive effects on gross profit margin and sales growth in the next
3 years, but has insignificant effect on gross ROA.
The unique nature of corporate R&D activities suggest that the
stock market may not be fully efficient in valuing the spillover effect
of R&D investments. Indeed, the results documented above suggest
that R&D investments by industry peers do not immediately result in
tangible assets for the firms, and the cash flow benefit to firms may
take years to materialize. The three operating performance measures I
use reflect market expansion and productivity growth, the two possible
channels through which the real effect of R&D spillover takes place.
To capture the market expansion effect, I use a firm's annual sales
growth rate. To capture productivity growth, I include gross profit
margin and return on assets (ROA). The results are consistent with the
notion that industry peers' R&D activities have real spillover
effects on a firm's sales growth and profitability.
B. Industry peer's R&D expenditures and future stock
returns
I next examine the externality of R&D investments on
firm's stock returns. Specifically, I estimate the following
regression:
Stock [Returns.sub.i,t+k] = [c.sub.0]+[c.sub.1] x
R&[D.sub.peer,t] +[c.sub.2] x R&[D.sub.i,t] +[beta] x Controls +
[e.sub.it] (2)
where k=1, 2 or 3 years and control variables include log of market
capitalization (LnSIZE); log of book-to-market (LnB/M) and Momentum
(PrRET).
Existing studies show that a firm's future stock returns are
positively related to its R&D intensity, suggesting the market tends
to underreact to the information. If stock investors also tend to
underreact to a firm's industry peers' R&D intensity, then
the coefficient c1 will be significantly different from zero: c1>0 if
the spillover effect dominates the competitive effect, or c1<0 if the
competitive effect dominates the spillover effect.
The regression results are reported in Table 4. The coefficient on
IRDS is positive and significant for years t+1 and t+2, but is not
significant for year t+3. The coefficient on IRDA is positive and
significant for year t+1 and t+3 while the coefficient on IRDE is only
significant for year t+1. Overall, the results show that companies
experience positive abnormal returns in the first year after industry
peers' R&D expenditures, but not significantly so after that.
It suggests that the market underreact to the spillover effect for about
one year's time. Industry peer's R&D expenditures have
also a huge economic effect. In fact, a one standard deviation increase
in IRDE, IRDA and IRDS causes stock returns to increase by 29%, 17% and
45% in year t+1, respectively.
Consistent with prior studies (Chan, et al., 2001; Eberhart et al.,
2004; Lev and Sougiannis, 1996), I also find that a firm's own
R&D intensity has a positive impact on subsequent stock returns. The
impact of firm's own R&D intensity is also economically
important. A standard deviation increase in RDE, RDA and RDS causes
stock returns to increase by 7%, 36% and 8% in year t+1, respectively.
The signs and statistical significance for the coefficients of Ln(Size),
Ln(B/M), and PrRet are generally consistent with prior literature.
Particularly noteworthy is that the coefficient for peer's
R&D expenditures is significantly positive even after controlling
for firm's own R&D intensity. Thus, the economic benefit to
firms is stronger when there is an industry-wide R&D increase. This
reflects an industry-wide spillover effect. Whether industry peer's
R&D spending positively predict stock returns of a firm depends not
only on the significance of the real spillover effect mentioned above,
but also on the efficiency of inter-firm information transmission in the
financial market, i.e., on the efficiency of the financial market to
incorporate information about one firm's action on the cash flows
and risks of another. Specifically, in the valuation of a stock,
investors may underreact to the information that its industry
peers' increase in R&D investments; hence the stock may
subsequently experience positive abnormal returns. Indeed, the
documented results have shown that investors under-react to the
industry-wide R&D spillover effect: the intensity of peer's
R&D investments is positively related to subsequent abnormal stock
returns. Thus, understanding the cross-firm valuation consequences of
corporate R&D investments may be an important challenge for
investors.
C. Industry Peer's R&D Expenditures And Future Earnings
News
I have shown that firms experience positive abnormal returns
following their industry peers' high R&D investments. This
implies that the market does not fully incorporate the valuation
implications of industry peers' R&D expenditures immediately.
This further implies that investors may be surprised by their
firm's performance in the future. Since I can reasonably measure
market expectation and surprises with earnings, I test whether future
earnings surprises and market reactions to earnings announcements are
more positive for firms with higher peers' R&D investments.
I obtain actual earnings and analyst forecast data from IBES. I
examine earnings surprises and abnormal stock returns around annual
earnings announcements for three years. Earnings surprise is calculated
as the difference between actual earnings and mean analyst forecast
divided by the stock price five days prior to the announcement date.3
Earnings announcement abnormal return is the market-adjusted returns
calculated for the three days around the annual earnings announcement.
(4)
I divide sample firms into quintiles based on the industry
peers' R&D expenditures. For each quintile, I first compute the
cross-sectional mean of earnings surprise and earnings announcement
abnormal returns for each year, and then I compute the time-series
average of the annual cross-sectional means (the standard error of the
time-series average is based on the times-series standard deviation of
the annual cross-sectional means).
Table 5 presents these time-series averages of cross-sectional
means. Panel A reports the average earnings surprise for each peer
R&D quintile, as well as the difference between Quintile 5 and
Quintile 1. I find that for low peer R&D quintiles, the average
earnings surprises are not significantly different from zero. They
become significantly positive as I move to higher peer R&D
quintiles, and most strongly so for the Quintile 5: all earnings
surprises are significantly positive for quintile 5.
The difference between Quintiles 5 and 1 is significantly positive
for all the three industry R&D measures (IRDA/IRDE/IRDS) for year
t+2 and t+3, but is not insignificant for year t+1. The magnitudes of
the differences also increase from year t+1 to t+3. This seems to
suggest the benefits to a firm's earnings from peers' R&D
investments tend to surprise the market starting two years after the
R&D expenditures.
Results in Panel B of Table 4 indicate that firms' future
earnings abnormal returns tend to be positively related to industry
peers' R&D investments. Similar as the pattern in Panel A,
abnormal returns tend to be insignificantly zero in low peer R&D
quintiles but become significantly positive in high quintiles. The
differences in the abnormal returns between quintiles 5 and 1 are
significantly positive in most cases. In terms of the magnitude of the
difference, taking IRDS for example, the difference is a significant 36
basis point for year t+2 and a significant 79 basis point for year t+3.
In comparison, the average abnormal return for the sample is 22 basis
point for year t+2 and 7 basis points for year t+3.
The results documented above suggest that investors fail to
appreciate the positive implications of peer's current R&D
investment on future earnings. Specifically, investors underestimate
future earnings because they do not understand that R&D costs
incurred in the current period function more like an investment which
produces future revenue rather than an expense (which is matched against
current revenue). Then, investors reassess their earnings expectations
in future periods when the benefits are unexpectedly realized, leading
to a positive relation between future returns and current R&D (see
Lev and Sougiannis (1996), Eberhart et al. (2004), Lev et al. (2005)). I
confirm this relation and show that peer's current R&D
investment is positively associated with future earnings over several
subsequent years.
In summary, I show evidence in this subsection that investors are
surprised by firms' earnings performance following their peer
firms' R&D investments. This is consistent with the notion that
the market fails to immediately incorporate the externality effects of
R&D expenditures.
D. Industry Peer's R&D Expenditures And Market Expansion
I are also interested to explore what might drive this R&D
spillover effect. One plausible channel is that the industry investments
in R&D lead to innovations that expand the market and increase
market demand for the whole industry. For example, the success of iPhone
reignites the market interest in smart phones in general, and also opens
up an extended market that provides software for these smart phones. I
thus hypothesize that the market expands when industry peer's
R&D increases. To test the hypotheses, I estimate the following
regressions:
Market [Expansion.sub.i,.t+1 =[[alpha].sub.0] +[[alpha].sub.0] x
R&[D.sub.peer.t] +[beta] x Control variables +[e.sub.i.r] (3)
I measure market expansion in terms of industry sales growth,
industry employment growth, and the percentage of new firms enters the
industry. The regression results of Equation (3) are reported in Table
6. Industries with higher IRDE tend to have higher subsequent total
sales growth, total employment growth, and larger percentage of new
firms enter the industry. The coefficients on IRDA and IRDS are positive
and significantly associated with industry employment growth and new
firms entry, but are not significant for industry sales growth. In
general, the results are consistent with my prediction: the market for
an industry expands more when its R&D intensity is higher.
The intuition behind the result is the following. R&D
spillovers among firms have a positive market expansion effect. The
positive market expansion effect is due to the fact that R&D
investment performed by one firm will reduce costs of other firms, via
spillovers. The cost reduction of the firms due to spillovers will then
create new demand and translate in larger market shares, thus providing
a positive externality effect for the industry. Indeed, the above
results suggest that ideas and technology may spread from one firm to
another, resulting in economic growth for an entire industry, creating
new demand, and expanding the market.
E. Industry Peers' R&D Expenditures, Market Expansion And
Future Operating Performance
If the R&D expenditure benefits the whole industry through
market expansion, I also expect to see that the spillover effect on firm
performance is stronger when the market expands more. I therefore
estimate the following regressions:
Operating [Performance.sub.i,t+k] = [d.sub.0] + [d.sub.0] x R &
[D.sub.peer,t] + d2 x (R & [D.sub.peer,t] x [Market
Expansion.sub.t+k]) + [d.sub.3] x R&[D.sub.i,t] +[beta] x Control
variables + [e.sub.i,t] (3)
where operating performance measures are gross profit margin, gross
ROA or sales growth; and k=1, 2 or 3 years. The control variables are
log of market capitalization (LnSIZE) and firm leverage (LEV). If the
market expansion hypothesis holds, then [d.sub.2]>0.
The regression results of Equation (4) are reported in Table 7.
Taking IRDS for example (panel C), future operating performance is
always positively related to the interaction term of (industry sales
growth*IRDS) (8 out 9 coefficients are significant at the 10% level).
The coefficients on (industry employment growth*IRDS) are also
significantly positive in most cases. When the market expansion is
measured as the percentage of new publicly traded firms, I find the
results are relatively weaker: only future sales growth (but not profit
margin or ROA) is positively associated with the (new entry*IRDS).
Results are similar with IRDE (Panel A) and IRDA (Panel B). Those
results are also statistically significant. For example, one standard
deviation increase in (industry sales growth*IRDS) increases sales
growth by 2.9%, 3.4% and 4.0% in year t+1, t+2 and t+3, respectively. As
discussed previously, the positive market expansion effect is due to the
fact that spillovers among firms reduce their costs and increase their
market shares. Therefore, I expect a stronger spillover effect when the
market expands more. That is, I expect to see higher operating
performance for firms in the industry that experience stronger
productivity growth and larger market expansion. Overall, these results
are consistent with the market expansion hypothesis: industry
peers' R&D investments have a larger positive effect on a
firm's operating performance where the market expands more.
IV. CONCLUSIONS
In this study, I find evidence that R&D investments have
positive externality effects. Firms' future operating performance
is positively related to industry peers' (in terms of all peer
firms, or leaders in the industry) R&D expenditures. Further, firms
tend to experience positive abnormal returns following industry
peers' high R&D expenditures. This suggests that the market not
only underreact to a firm's own R&D investments (as suggested
by both previous and my studies), but also to industry peers'
R&D investments.
Consistent with the notion that the market underreacts to the
externality effects of R&D, I also find that the market is surprised
by firms' earnings performance following high peer R&D
investments. Specifically, I find that future earnings surprises and
abnormal stock returns around earnings announcements are significantly
positive when industry peers have high R&D investments; and these
measures are significantly higher than those firms whose industry peers
have low R&D investments.
I also identify a channel through which the benefits of R&D
investments can spill over to other firms in the industry: advances in
technology expand the market demand. Consistent with this hypothesis, I
find that industry sales and employment grow faster when industry
R&D intensity is high; and that the positive externality effect on
operating performance is stronger where the market expands more.
ENDNOTES
(1.) In robust checks, I also use EBIT (earnings before interest
and tax) margin and ROA. Results are robust. I choose to use gross
profit margin and gross ROA because EBIT is influenced by R&D
expenses.
(2.) I do not wonsorize PrRet to conform to the convention. Results
are robust if I do winsorize this variable as well.
(3.) My results are robust to earnings surprise measured using the
difference between reported earnings and consensus analysts' median
earnings forecast divided by the stock price five days prior to the
announcement date.
(4.) Market-adjusted returns are the differences between firm
returns and returns on the value-weighted NYSE/AMEX index, both
compounded over the [-1, +1] earnings announcement window.
Table 6
Operating performance, market expansion, and industry peer's R&D
expenditures
Panel A
R&D Measure: RDE(R&D/Market Cap)
Dependent variable: operating performance measures
for Year t+1
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDE 2.39 (***) 5.26 (**) 13.82 (***)
(2.64) (2.48) (3.47)
Industry sales
growth (*)IRDE 1.11 6.13 (***) 16.76 (***)
(1.43) (2.63) (4.59)
RDE 1.87 (***) 1.95 16.10 (***)
(3.42) (0.74) (4.18)
Ln(SIZE) 0.01 -0.44 (***) -0.76 (***)
(0.34) (-6.22) (-5.31)
LEV -0.41 -10.18 (***) -4.86 (***)
(-1.21) (-6.59) (-2.89)
Market expansion
measure: industry
employment growth
IRDE 2.78 (***) 6.72 (***) 14.66 (***)
(2.98) (2.75) (3.22)
Industry employment
growth
(*)IRDE 0.35 3.97 17.81 (***)
(0.42) (1.60) (4.56)
RDE 1.85 (***) 1.73 15.74 (***)
(3.46) (0.65) (4.03)
Ln(SIZE) 0.01 -0.44 (***) -0.78 (***)
(0.31) (-6.27) (-5.43)
LEV -0.40 -10.12 (***) -4.52 (***)
(-1.19) (-6.48) (-2.67)
Market expansion
measure: new entry
IRDE 3.52 (***) 7.73 (**) 13.54 (***)
(2.75) (2.44) (2.94)
New entry (*)IRDE -2.20 1.27 24.37 (***)
(-1.11) (0.29) (3.15)
RDE 1.82 (***) 1.43 15.68 (***)
(3.39) (0.54) (3.98)
Ln(SIZE) 0.02 -0.44 (***) -0.81 (***)
(0.49) (-6.34) (-5.44)
LEV -0.41 -10.14 (***) -4.94 (***)
(-1.22) (-6.48) (-2.94)
Dependent variable: operating performance measures
for Year t+2
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDE 4.10 (**) 10.05 (***) 13.65 (***)
(2.36) (3.56) (3.66)
Industry sales
growth (*)IRDE 1.99 (**) 7.55 (***) 18.44 (***)
(1.99) (2.58) (4.91)
RDE 2.56 (***) -2.32 16.49 (***)
(3.10) (-0.68) (4.39)
Ln(SIZE) 0.04 -0.7 (***) -1.18 (***)
(0.65) (-6.56) (-7.46)
LEV -0.78 -4.63 (**) -6.10 (***)
(-1.38) (-2.44) (-2.63)
Market expansion
measure: industry
employment growth
IRDE 4.36 (**) 11.27 (***) 14.97 (***)
(2.44) (3.58) (3.35)
Industry employment
growth
(*)IRDE 1.02 4.85 (*) 18.44 (***)
(0.93) (1.76) (4.07)
RDE 2.49 (***) -2.67 16.23 (***)
(3.14) (-0.78) (4.28)
Ln(SIZE) 0.04 -0.70 (***) -1.19 (***)
(0.64) (-6.81) (-7.52)
LEV -0.76 -4.55 (*) -5.89 (**)
(-1.34) (-2.35) (-2.50)
Market expansion
measure: new entry
IRDE 4.93 (**) 11.55 (***) 12.97 (***)
(2.32) (3.68) (3.42)
New entry (*)IRDE -0.19 5.09 30.74 (***)
(-0.10) (1.05) (2.73)
RDE 2.47 (***) -2.75 16.31 (***)
(3.14) (-0.80) (4.25)
Ln(SIZE) 0.04 -0.72 (***) -1.26 (***)
(0.67) (-7.10) (-7.81)
LEV -0.8 -4.53 (**) -5.91 (**)
(-1.42) (-2.33) (-2.52)
Dependent variable: operating performance measures
for Year t+3
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDE 6.10 (**) 10.95 (***) 11.02 (***)
(2.54) (2.83) (3.24)
Industry sales
growth (*)IRDE 2.75 (**) 7.74 (**) 20.63 (***)
(2.30) (2.29) (5.44)
RDE 3.16 (***) 6.42 (*) 15.61 (***)
(3.03) (1.77) (4.00)
Ln(SIZE) 0.11 -0.64 (***) -1.03 (***)
(1.33) (-4.58) (-6.63)
LEV -0.77 -1.30 -2.41
(-1.15) (-0.58) (-1.09)
Market expansion
measure: industry
employment growth
IRDE 6.23 (***) 12.16 (***) 12.16 (***)
(2.62) (3.12) (2.91)
Industry employment
growth
(*)IRDE 2.05 6.16 (*) 20.24 (***)
(1.53) (1.72) (4.17)
RDE 3.13 (***) 6.47 (*) 15.42 (***)
(3.04) (1.80) (3.90)
Ln(SIZE) 0.11 -0.64 (***) -1.03 (***)
(1.31) (-4.66) (-6.53)
LEV -0.77 -1.27 -2.24
(-1.14) (-0.56) (-0.98)
Market expansion
measure: new entry
IRDE 6.66 (***) 12.35 (***) 10.30 (***)
(2.87) (3.52) (2.72)
New entry (*)IRDE 1.35 9.21 36.50 (**)
(0.57) (1.42) (2.33)
RDE 3.22 (***) 6.39 (*) 15.69 (***)
(3.17) (1.76) (3.97)
Ln(SIZE) 0.10 -0.68 (***) -1.11 (***)
(1.21) (-5.11) (-7.11)
LEV -0.8 -1.25 -2.46
(-1.18) (-0.55) (-1.09)
Panel B
R&D measure: RDA (R&D/Assets)
Dependent variable: operating performance measures
for Year t+1
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDA 4.33 (***) 10.71 (**) 15.52 (***)
(2.76) (2.51) (2.61)
Industry sales
growth
(*)IRDA 1.14 5.67 (***) 16.28 (***)
(1.47) (2.68) (4.47)
RDA 6.02 (***) 9.00 50.67 (***)
(3.49) (1.50) (6.40)
Ln(SIZE) 0.02 -0.42 (***) -0.76 (***)
(0.51) (-6.03) (-5.58)
LEV 0.28 -10.53 (***) -0.22
(0.94) (-7.04) (-0.12)
Market expansion
measure: industry
employment growth
IRDA 4.89 (***) 12.31 (***) 15.98 (**)
(3.04) (2.66) (2.36)
Market expansion
measure: Industry
employment growth
(*) IRDA 0.19 3.84 (*) 16.94 (***)
(0.24) (1.66) (4.62)
RDA 6.00 (***) 9.30 50.04 (***)
(3.53) (1.50) (6.17)
Ln(SIZE) 0.02 -0.42 (***) -0.78 (***)
(0.48) (-6.03) (-5.68)
LEV 0.28 -10.49 (***) 0.01
(0.95) (-6.95) (0.01)
Market expansion
measure: new entry
IRDA 6.70 (***) 13.81 (**) 14.43 (**)
(2.91) (2.34) (2.13)
New entry (*)IRDA -4.05 (*) 3.26 21.32 (***)
(-1.68) (0.87) (2.95)
RDA 6.00 (***) 9.82 50.71 (***)
(3.45) (1.56) (6.22)
Ln(SIZE) 0.03 -0.41 (***) -0.81 (***)
(0.64) (-6.09) (-5.74)
LEV 0.28 -10.52 (***) -0.41
(0.94) (-6.99) (-0.23)
Dependent variable: operating performance measures
for Year t+2
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDA 7.06 (***) 17.96 (***) 16.16 (***)
(2.67) (3.22) (3.01)
Industry sales
growth
(*)IRDA 2.04 (*) 7.37 (***) 17.88 (***)
(1.92) (2.57) (4.86)
RDA 9.40 (***) 14.07 (*) 47.94 (***)
(3.38) (1.68) (6.43)
Ln(SIZE) 0.05 -0.67 -1.18 (***)
(0.79) (-6.63) (-7.76)
LEV 0.29 -5.66 (***) -1.88
(0.58) (-3.18) (-0.80)
Market expansion
measure: industry
employment growth
IRDA 7.46 (***) 19.41 (***) 17.83 (***)
(2.76) (3.26) (2.69)
Market expansion
measure: Industry
employment growth
(*) IRDA 0.91 4.77 (*) 17.95 (***)
(0.82) (1.75) (4.11)
RDA 9.20 (***) 14.75 (*) 47.45 (***)
(3.42) (1.71) (6.28)
Ln(SIZE) 0.05 -0.68 (***) -1.20 (***)
(0.78) (-6.87) (-7.85)
LEV 0.29 -5.68 (***) -1.76
(0.57) (-3.16) (-0.74)
Market expansion
measure: new entry
IRDA 9.83 (***) 20.55 (***) 16.22 (***)
(2.67) (3.32) (3.01)
New entry (*)IRDA -3.25 6.09 28.13 (**)
(-1.61) (1.03) (2.49)
RDA 9.15 (***) 15.17 (*) 47.16 (***)
(3.41) (1.76) (6.13)
Ln(SIZE) 0.05 -0.69 (***) -1.27 (***)
(0.81) (-7.12) (-8.09)
LEV 0.25 -5.65 (***) -1.87
(0.5) (-3.14) (-0.79)
Dependent variable: operating performance measures
for Year t+3
Gross profit margin Gross ROA Sales Growth]
Market expansion
measure: industry
sales growth
IRDA 10.30 (***) 21.78 (***) 15.33 (***)
(2.78) (2.88) (2.88)
Industry sales
growth
(*)IRDA 2.34 (***) 7.60 (**) 19.72 (***)
(2.10) (2.42) (5.46)
RDA 11.34 (***) 23.40 (***) 40.95 (***)
(3.64) (2.61) (4.77)
Ln(SIZE) 0.12 -0.62 (***) -1.02 (***)
(1.47) (-4.53) (-6.71)
LEV 0.53 -2.96 1.09
(0.86) (-1.38) (0.48)
Market expansion
measure: industry
employment growth
IRDA 10.4 (***) 23.26 (***) 17.2 (***)
(2.81) (3.10) (2.73)
Market expansion
measure: Industry
employment growth
(*) IRDA 1.79 6.39 (*) 19.65 (***)
(1.33) (1.88) (4.16)
RDA 11.25 (***) 23.68 (***) 40.65 (***)
(3.69) (2.62) (4.65)
Ln(SIZE) 0.12 -0.61 (***) -1.03 (***)
(1.46) (-4.59) (-6.64)
LEV 0.49 -2.96 1.25
(0.80) (-1.36) (0.54)
Market expansion
measure: new entry
IRDA 12.52 (***) 23.72 (***) 15.02 (***)
(3.09) (3.47) (2.81)
New entry (*)IRDA -3.19 6.64 32.33 (**)
(-1.18) (1.11) (2.14)
RDA 11.52 (***) 23.76 (**) 41.34 (***)
(3.86) (2.60) (4.71)
Ln(SIZE) 0.11 -0.65 (***) -1.11 (***)
(1.35) (-5.00) (-7.18)
LEV 0.50 -2.92 1.02
(0.79) (-1.36) (0.45)
Panel C
R&D Measure: RDS(R&D/Sales)
Dependent variable: operating performance measures
for Year t+1
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDS 0.51 (**) 1.46 (*) 1.14
(2.20) (1.80) (0.88)
Industry sales
growth (*) IRDS 1.28 6.27 (***) 16.91 (***)
(1.48) (2.90) (4.58)
RDS 8.75 (**) 13.99 (*) 77.59 (***)
(2.47) (1.90) (6.97)
Ln(SIZE) -0.01 -0.46 (***) -0.86 (***)
(-0.01) (-6.82) (-6.56)
LEV 0.15 -9.62 (***) -0.10
(0.49) (-6.64) (-0.06)
Market expansion
measure: industry
employment growth
IRDS 0.64 (**) 1.64 (*) 1.36
(2.12) (1.75) (0.95)
Industry
employment growth
(*) IRDS 0.59 4.21 (**) 17.11 (***)
(0.79) (2.22) (4.29)
RDS 8.75 (**) 14.17 (*) 77.76 (***)
(2.51) (1.90) (6.95)
Ln(SIZE) -0.01 -0.46 (***) -0.88 (***)
(-0.06) (-6.80) (-6.68)
LEV 0.15 -9.62 (***) 0.08
(0.49) (-6.58) (0.05)
Market expansion
measure: new entry
IRDS 0.53 1.92 (*) 0.11
(1.42) (1.72) (0.11)
New entry (*)IRDS 1.20 5.55 31.94 (***)
(0.95) (1.48) (3.10)
RDS 8.77 (**) 14.03 (*) 77.9 (***)
(2.49) (1.86) (6.79)
Ln(SIZE) -0.01 -0.47 (***) -0.91 (***)
(-0.04) (-6.84) (-6.79)
LEV 0.15 -9.64 (***) -0.16
(0.48) (-6.69) (-0.1)
Dependent variable: operating performance measures
for Year t+2
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDS 0.92 (**) 3.05 (*) 2.11
(2.07) (1.73) (1.27)
Industry sales
growth (*) IRDS 1.97 (*) 6.61 (**) 17.4 (***)
(1.82) (2.47) (4.88)
RDS 13.07 (**) 21.09 (**) 78.34 (***)
(2.48) (1.99) (7.45)
Ln(SIZE) 0.02 -0.75 (***) -1.29 (***)
(0.34) (-7.21) (-8.56)
LEV 0.01 -4.28 (**) -1.62
(0.01) (-2.51) (-0.72)
Market expansion
measure: industry
employment growth
IRDS 1.03 (*) 3.24 (***) 2.74
(1.93) (1.72) (1.28)
Industry
employment growth
(*) IRDS 1.28 4.51 (**) 17.64 (***)
(1.16) (2.00) (3.95)
RDS 12.99 (**) 20.66 (*) 78.17 (***)
(2.49) (1.92) (7.33)
Ln(SIZE) 0.02 -0.75 (***) -1.31 (***)
(0.29) (-7.45) (-8.76)
LEV 0.03 -4.28 (**) -1.45
(0.06) (-2.47) (-0.64)
Market expansion
measure: new entry
IRDS 1.92 3.59 (*) 1.05
(1.40) (1.68) (1.09)
New entry (*)IRDS 0.76 6.17 35.00 (***)
(0.27) (0.84) (2.78)
RDS 13.24 (**) 20.48 (*) 77.01 (***)
(2.57) (1.87) (6.98)
Ln(SIZE) 0.01 -0.78 (***) -1.38 (***)
(0.21) (-7.68) (-8.87)
LEV 0.01 -4.30 (**) -1.49
(0.01) (-2.47) (-0.66)
Dependent variable: operating performance measures
for Year t+3
Gross profit margin Gross ROA Sales Growth
Market expansion
measure: industry
sales growth
IRDS 1.27 (**) 3.99 (*) 1.63
(1.98) (1.72) (1.37)
Industry sales
growth (*) IRDS 2.09 (**) 5.24 (*) 18.53 (***)
(2.18) (1.97) (5.59)
RDS 17.54 (***) 17.98 66.15 (***)
(3.24) (1.62) (6.72)
Ln(SIZE) 0.08 -0.72 (***) -1.13 (***)
(1.00) (-5.11) (-7.85)
LEV 0.17 -1.20 1.08
(0.28) (-0.57) (0.50)
Market expansion
measure: industry
employment growth
IRDS 1.24 (**) 4.02 (*) 1.88
(2.02) (1.77) (1.39)
Industry
employment growth
(*) IRDS 2.17 (*) 4.30 18.49 (***)
(1.86) (1.60) (4.30)
RDS 17.44 (***) 18.00 66.49 (***)
(3.24) (1.61) (6.59)
Ln(SIZE) 0.08 -0.72 (***) -1.15 (***)
(1.00) (-5.22) (-7.90)
LEV 0.17 -1.22 1.20
(0.28) (-0.58) (0.55)
Market expansion
measure: new entry
IRDS 1.73 (*) 5.05 (*) 0.86
(1.72) (1.66) (1.24)
New entry (*)IRDS 2.30 3.61 35.42 (**)
(0.78) (0.55) (2.37)
RDS 17.69 (***) 17.46 66.20 (***)
(3.32) (1.54) (6.35)
Ln(SIZE) 0.07 -0.74 (***) -1.22
(0.87) (-5.56) (-8.47)
LEV 0.12 -1.27 1.08
(0.2) (-0.61) (0.51)
The sample contains 89,782 firm-year observations during 1975-2012.
The dependent variables are operating performance measures (Gross
profit margin, Gross ROA and Sales growth) for year t+1, t+2 and t+3,
respectively. I rescale the dependent variable by a factor of 100. That
is, I multiple the R&D measures by 100. The independent variables are
industry R&D measures, the interaction of industry R&D measures and
market expansion measures (Industry sales growth, Industry employment
growth, New firm entry), LnSIZE, and LEV. In Panel A, R&D measure is
RDE (R&D/Market Cap). In Panel B, R&D measure is RDE (R&D/Assets). In
Panel C, R&D measure is RDS (R&D/Sales). All variables are defined
as in Table 1. All variables are winsorized at the 1th and 99th
percentiles. A (***), (**), (*) denote significance at the 1%, 5%, and
10% levels, respectively. Numbers in parentheses are t-statistics.
REFERENCES
Braun, M., and B. Larrain, 2009, "Do IPO's Affect the
Prices of Other Stocks? Evidence from Emerging Markets." Review of
Financial Studies, 22(4), 1505-1544.
Chan, L., J. Lakonishok, and T. Sougiannis, 2001, "The Stock
Market Valuation of Research and Development Expenditures." Journal
of Finance 56(2), 431-2457.
Daniel, K., and S. Titman, 2006, "Market Reactions to Tangible
and Intangible Information." Journal of Finance 61, 1605-1643.
Eberhart, A.C., W.F. Maxwell, and A.R. Siddique, 2004, "An
Examination Of Long-Term Abnormal Stock Returns And Operating
Performance Following R&D Increases." Journal of Finance, 59,
623-651.
Fama, E., and K.R. French, 1993, "Common Risk Factors In The
Returns On Stocks And Bonds." Journal of Financial Economics, 33,
3-56.
Fama, E., and K. French, 1997, "Industry Costs of
Equity." Journal of Financial Economics, 43, 153-93.
Griliches, Z., 1992, "The Search for R&D Spillovers."
Scandinavian Journal of Economics, 94, 29-47.
Griliches, Z., 2002, "R&D, Education, and Productivity: A
Retrospective." The Economic Journal, 112, 153-155.
Hall, B., 1993, "The Stock Market's Valuation of R&D
Investment during the 1980's." American Economic Review, 83,
259-264.
Hsu, H.C., A.V. Reed, and J. Rocholl, 2010, "The New Game in
Town: Competitive Effects of IPOs." Journal of Finance, 65(2),
495-528.
Lang, L., and R. Stulz, 1992, "Contagion and Competitive
Intraindustry Effects of Bankruptcy Announcements: An Empirical
Analysis." Journal of Financial Economics, 32, 45-60.
Lev, B., and T. Sougiannis, 1996, "The Capitalization,
Amortization and Value-Relevance of R&D." Journal of Accounting
and Economics, 21, 107-138.
Lev, B., T. Sougiannis, and B. Sarath., 2005, "R&D
Reporting Biases and Their Consequences." Contemporary Accounting
Research, 22, 977-1026.
Romer, P.M., 1990, "Endogenous Technological Change."
Journal of Political Economy, 98, 571-5102.
Romer, P.M., 1990, "Capital, Labor, and Productivity."
Brooking Paper on Economic Activity: Microeconomics, 337-367.
Yi Jiang
Department of Finance, California State University, Fullerton SGMH
5160, Fullerton, CA 92831 yjiang@fullerton.edu
Table 1
Variable definition
Operating performance measures:
Gross profit margin (sales--costs of goods sold)/sales
Gross ROA (sales--costs of goods sold)/lag
assets
Sales growth (sales-lag sales)/lag sales
Market expansion measures:
Industry sales growth industry aggregate sales growth
Industry employment percentage change in total employees
growth
New entry number of new firms scaled by the
total number of firms in prior
year
Firm Characteristics:
RDE R&D expenditure scaled by lagged
market equity
RDS R&D expenditure scaled by lagged sales
RDA R&D expenditure scaled by lagged
assets
IRDE Industry mean (exclude firm i) RDE
IRDS Industry mean (exclude firm i) RDS
IRDA Industry mean (exclude firm i) RDA
Sum of long term debt and debt in
current liabilities, all divided by
LEV total assets
Ln(SIZE) log market capitalization
Ln(B/M) log book-to-market ratio
PrRET average monthly return during the
past 12 months (Momentum)
Table 2
Summary statistics
N Mean Median Min Max STD
Panel A: Operating
Performance Measures
Gross profit margin 89782 0.34 0.33 -0.47 0.84 0.22
Gross ROA 74171 0.47 0.42 -0.01 1.33 0.30
Sales growth 74171 0.17 0.11 -0.32 1.31 0.29
Panel B: Market
expansion Measures
Industry sales growth 87853 0.14 0.13 -0.02 0.44 0.10
Industry employment growth 87853 0.08 0.06 -0.06 0.34 0.08
New entry 87853 0.05 0.03 0.00 0.22 0.05
Panel C: Firm
Characteristics
RDE 74171 0.06 0.00 0.00 0.50 0.11
RDS 89782 0.06 0.00 0.00 1.23 0.20
RDA 74171 0.04 0.00 0.00 0.30 0.07
IRDE 86585 0.08 0.05 0.00 0.45 0.09
IRDS 88764 0.05 0.03 0.00 9.25 1.69
IRDA 86585 0.04 0.02 0.00 0.22 0.05
LEV 89553 0.22 0.20 0.00 0.64 0.18
Ln(SIZE) 89782 12.14 12.00 8.86 16.47 1.82
Ln(B/M) 81915 -0.59 -0.54 -2.62 0.98 0.82
PrRET 85143 0.26 0.12 -0.95 27.77 0.71
The table reports summary statistics of main firm characteristics,
market expansion variables, and operating performance variables for
sample firms over 1975-2012. Gross profit margin= (sales--costs of
goods sold)/sales. Gross ROA= (sales--costs of goods sold)/lag total
assets. Sales growth= (sales-lag sales)/lag sales. Industry sales
growth= (industry aggregate sales-lag industry aggregate sales)/lag
industry aggregate sales. Industry employment growth is the percentage
change in industry total employees ((industry total employees-lag
industry total employees)/lag industry total employees). New entry is
the number of new firms scaled by the total number of firms in prior
year. RDE is R&D expenditure scaled by lag market equity. RDS is R&D
expenditure scaled by lag sales. RDA is R&D expenditure scaled by lag
total assets. IRDE is firm i's industry peers' mean RDE. IRDS is firm
i's industry peers' mean RDS. IRDA is firm i's industry peers' mean
RDA. LEV is the sum of long term debt and debt in current liabilities,
all divided by total assets. Ln(SIZE) is the log of market
capitalization. Ln(B/M) is the log book-to-market ratio. Momentum
(PrRET) is the average monthly return during the past 12 months. All
variables (except for Momentum PrRET) are winsorized at the 1th and
99th percentiles.
Table 3
Operating performance and industry peer's R&D expenditures
Dependent variable: operating performance
measures for Year t+1
Gross profit Gross Sales
margin ROA Growth
R&D measure:
RDE(R&D/Market Cap)
IRDE 1.49 (**) 6.19 (***) 4.88 (*)
(2.43) (2.89) (1.80)
RDE 1.92 (***) 2.30 1.78
(2.80) (0.97) (0.72)
Ln(SIZE) 0.012 -0.61 (***) -1.08 (***)
(0.46) (-6.11) (-3.65)
LEV -0.42 -9.63 (***) -1.68
(-1.46) (-6.48) (-0.85)
R&D measure:
RDA (R&D/Assets)
IRDA 2.41 (***) 12.46 (***) 0.55
(2.86) (4.02) (0.12)
RDA 6.81 (***) 0.04 24.98 (***)
(3.68) (0.01) (3.54)
Ln(SIZE) 0.01 -0.60 (***) -1.10 (***)
(0.44) (-6.09) (-3.70)
LEV -0.16 -9.64 (***) -0.43
(-0.53) (-6.87) (-0.21)
R&D measure:
RDS (R&D/Sales)
IRDS 0.27 (**) 0.79 (*) 0.19
(2.50) (1.93) (0.38)
RDS 12.76 (***) 21.09 (***) 43.50 (***)
(3.97) (3.44) (4.23)
Ln(SIZE) 0.03 -0.64 (***) -1.11 (***)
(0.12) (-6.44) (-3.86)
LEV -0.02 -9.24 (***) 0.07
(-0.07) (-6.27) (0.04)
Dependent variable: operating performance
measures for Year t+2
Gross profit Gross Sales
margin ROA Growth
R&D measure:
RDE(R&D/Market Cap)
IRDE 3.63 (***) 7.30 (***) 5.59
(3.27) (2.64) (1.58)
RDE 3.18 (***) 0.74 2.45
(4.48) (0.30) (0.70)
Ln(SIZE) 0.04 -0.87 (***) -1.96 (***)
(0.85) (-6.89) (-4.03)
LEV -0.99 -6.59 (***) -9.13 (***)
(-1.13) (-4.52) (-2.83)
R&D measure:
RDA (R&D/Assets)
IRDA 5.57 (***) 19.12 (***) 5.51
(3.43) (3.88) (0.94)
RDA 11.76 (***) -10.50 17.40 (*)
(5.40) (-1.39) (1.90)
Ln(SIZE) 0.04 -0.86 (***) -1.96 (***)
(0.84) (-6.88) (-4.04)
LEV -0.52 -6.98 (***) -8.38 (**)
(-0.64) (-5.27) (-2.44)
R&D measure:
RDS (R&D/Sales)
IRDS 0.60 (*) 1.35 (**) 0.40
(1.79) (2.05) (0.65)
RDS 24.17 (***) 24.34 (***) 52.03 (***)
(4.79) (3.14) (2.82)
Ln(SIZE) 0.01 -0.91 (***) -2.03 (***)
(0.19) (-7.15) (-4.22)
LEV 0.17 -6.13 (***) -6.76 (*)
(0.31) (-4.29) (-1.88)
Dependent variable: operating performance
measures for Year t+3
Gross profit Gross ROA Sales
margin Growth
R&D measure:
RDE(R&D/Market Cap)
IRDE 3.11 (***) 9.12 (***) 5.69
(3.29) (2.74) (1.48)
RDE 3.82 (***) -0.25 4.49 (**)
(4.31) (-0.12) (2.21)
Ln(SIZE) 0.06 -0.99 (***) -1.48 (***)
(1.03) (-8.16) (-6.75)
LEV -0.94 -5.53 (***) -1.86
(-1.04) (-3.61) (-0.87)
R&D measure:
RDA (R&D/Assets)
IRDA 5.20 (***) 21.41 (***) 6.43
(3.45) (3.69) (0.99)
RDA 12.98 (***) -11.38 22.89 (***)
(4.18) (-1.23) (4.54)
Ln(SIZE) 0.06 -0.98 (***) -1.48 (***)
(1.07) (-8.15) (-6.78)
LEV -0.49 -5.76 (***) -1.14
(-0.58) (-4.03) (-0.53)
R&D measure:
RDS (R&D/Sales)
IRDS 0.80 (***) 1.86 (**) 0.97
(2.71) (1.98) (1.32)
RDS 21.81 (***) 27.20 (***) 56.02 (***)
(5.28) (2.84) (2.74)
Ln(SIZE) 0.04 -1.04 (***) -1.55 (***)
(0.64) (-8.39) (-7.08)
LEV -0.45 -4.93 (***) 0.35
(-0.55) (-3.24) (0.14)
The table reports operating performance regressions for sample firms
over 1975-2012. The sample contains 89,782 firm-year observations. The
dependent variables are operating performance measures (Gross profit
margin, Gross ROA and Sales growth) for year t+1, t+2 and t+3,
respectively. I rescale the dependent variable by a factor of 100. That
is, I multiple the R&D measures by 100. The independent variables are
R&D measures (R&D/Market Cap, R&D/Assets, R&D/Sales), LnSIZE, and LEV.
All variables are defined as in Table 1. All variables are winsorized
at the 1th and 99th percentiles. A (***), (**), (*) denote significance
at the 1%, 5%, and 10% levels, respectively. Numbers in parentheses are
t-statistics.
Table 4
Stock returns and industry peer's R&D expenditures
Dependent variable: Dependent variable:
stock return for Year t+1 stock return for Year t+2
R&D measure:
RDE
(R&D/Market Cap)
IRDE 0.33 (*) 0.28
(1.93) (1.53)
RDE 0.20 (***) 0.18 (**)
(3.21) (2.56)
LnSIZE -0.04 (***) -0.03 (***)
(-5.11) (-3.66)
LnB/M 0.03 (**) 0.02
(2.15) (1.41)
PrRET 0.05 (**) -0.01
(2.23) (-0.53)
R&D measure:
RDA
(R&D/Assets)
IRDA 0.24 (*) 0.18
(1.87) (1.52)
RDA 0.46 (***) 0.40 (**)
(2.88) (2.54)
LnSIZE -0.04 (***) -0.03 (***)
(-5.41) (-3.84)
LnB/M 0.03 (**) 0.02 (*)
(2.27) (1.90)
PrRET 0.04 (**) -0.01
(2.12) (-0.48)
R&D measure:
RDS
(R&D/Sales)
IRDS 0.44 (**) 0.38 (*)
(1.98) (1.80)
RDS 0.15 0.23 (*)
(1.52) (1.70)
LnSIZE -0.05 (***) -0.03 (***)
(-5.01) (-3.53)
LnB/M 0.01 0.01
(0.53) (0.29)
PrRET 0.06 (***) -0.01
(2.49) (-0.42)
Dependent variable:
stock return for Year t+3
R&D measure:
RDE
(R&D/Market Cap)
IRDE 0.22
(1.37)
RDE 0.07
(1.54)
LnSIZE -0.01 (**)
(-2.26)
LnB/M 0.03 (**)
(2.02)
PrRET -0.01
(-0.67)
R&D measure:
RDA
(R&D/Assets)
IRDA 0.20 (*)
(1.67)
RDA 0.12
(1.07)
LnSIZE -0.01 (**)
(-2.39)
LnB/M 0.03 (**)
(2.03)
PrRET -0.01
(-0.53)
R&D measure:
RDS
(R&D/Sales)
IRDS 0.24
(1.34)
RDS 0.09
(1.05)
LnSIZE -0.02 (**)
(-2.39)
LnB/M 0.02
(0.87)
PrRET -0.01
(-0.37)
The table reports stock returns regressions for sample firms over
1975-2012. The sample contains 89,782 firm-year observations. The
dependent variables are stock returns for year t+1, t+2 and t+3,
respectively. The independent variables are R&D measures (R&D/Market
Cap, R&D/Assets, R&D/Sales), LnSIZE, LnB.M, and Momentum (PrRET). I
rescale the industry R&D measures by a factor of 100. That is, I
multiple the industry R&D measures by 100. All variables are defined as
in Table 1. All variables (except for Momentum (PrRET)) are winsorized
at the 1th and 99th percentiles. A (***), (**), (*) denote significance
at the 1%, 5%, and 10% levels, respectively. Numbers in parentheses are
t-statistics.
Table 5
Industry peer's R&D expenditures and future earnings news
R&D measure: RDE(R&D/Market Cap)
Year t+1 Year t+2 Year t+3
Panel A.
Earnings
Surprise (%):
Quintile1 0.05 -0.05 -0.29
(0.47) (-0.36) (-1.29)
Quintile2 0.01 0.13 0.03
(0.01) (1.00) (0.22)
Quintile3 0.20 0.41 (*) -0.08
(0.67) (1.71) (-0.23)
Quintile4 0.19 (*) 0.29 (**) -0.51
(1.64) (2.13) (-1.09)
Quintile5 0.33 (**) 0.36 (**) 0.67 (**)
(2.19) (2.07) (2.21)
Quintile5-1 0.28 0.41 (**) 0.96 (***)
(1.56) (2.28) (2.72)
Panel B.
Earnings
announcement
abnormal
returns (%):
Quintile1 -0.01 0.11 -0.14
(-0.02) (0.95) (-0.84)
Quintile2 0.26 (**) 0.12 -0.00
(2.05) (0.75) (-0.01)
Quintile3 0.42 (**) 0.22 -0.06
(2.18) (1.37) (-0.38)
Quintile4 0.26 (*) 0.46 (*) -0.05
(1.74) (1.73) (-0.24)
Quintile5 0.58 (***) 0.43 (***) 0.35 (**)
(2.98) (2.76) (2.39)
Quintile5-1 0.58 (*) 0.32 (*) 0.50 (**)
(1.79) (1.74) (1.98)
R&D measure: RDA(R&D/Assets)
Year t+1 Year t+2 Year t+3
Panel A.
Earnings
Surprise (%):
Quintile1 0.03 -0.03 -0.07
(0.30) (-0.24) (-0.59)
Quintile2 -0.02 0.08 -0.41
(-0.16) (0.62) (-1.04)
Quintile3 0.16 0.36 (**) 0.20
(0.66) (2.16) (1.02)
Quintile4 0.15 (*) 0.20 -0.13
(1.79) (1.29) (-0.34)
Quintile5 0.32 (**) 0.43 (**) 0.54 (**)
(2.09) (2.08) (2.18)
Quintile5-1 0.28 0.46 (**) 0.61 (**)
(1.63) (2.11) (2.39)
Panel B.
Earnings
announcement
abnormal
returns (%):
Quintile1 0.04 0.01 -0.12
(0.27) (0.07) (-0.88)
Quintile2 0.11 -0.02 -0.07
(1.03) (-0.13) (-0.38)
Quintile3 0.33 (*) 0.20 0.07
(1.75) (1.08) (0.43)
Quintile4 0.51 (***) 0.27 (**) 0.07
(2.64) (2.32) (0.50)
Quintile5 0.54 (***) 0.37 (**) 0.38 (**)
(2.75) (2.42) (2.18)
Quintile5-1 0.50 (*) 0.37 (**) 0.50 (**)
(1.73) (2.01) (2.25)
R&D measure: RDS(R&D/Sales)
Year t+1 Year t+2 Year t+3
Panel A.
Earnings
Surprise (%):
Quintile1 0.07 -0.01 -0.07
(0.69) (-0.08) (-0.69)
Quintile2 0.03 0.12 -0.10
(0.32) (1.12) (-0.50)
Quintile3 0.26 0.39 -0.06
(1.16) (1.57) (-0.12)
Quintile4 -0.09 0.14 -0.31
(-0.51) (0.92) (-1.15)
Quintile5 0.37 (**) 0.39 (**) 0.56 (**)
(2.23) (2.25) (2.31)
Quintile5-1 0.30 0.39 (**) 0.63 (***)
(1.55) (2.19) (2.61)
Panel B.
Earnings
announcement
abnormal
returns (%):
Quintile1 0.11 -0.04 -0.29 (**)
(0.86) (-0.35) (-1.99)
Quintile2 0.33 0.19 0.07
(2.05) (1.27) (0.42)
Quintile3 0.32 0.41 -0.11
(1.48) (1.62) (-0.56)
Quintile4 0.19 0.41 (***) -0.20
(1.02) (2.65) (-1.15)
Quintile5 0.31 (**) 0.32 (**) 0.50 (***)
(2.32) (2.56) (3.44)
Quintile5-1 0.20 0.36 (**) 0.79 (***)
(1.35) (2.15) (4.89)
This table reports the earnings announcement abnormal returns and
earnings surprises by industry peer's R&D expenditures portfolios for
years t+1, t+2 and t+3. The sample contains 47,053 firm-year
observations. The earnings announcement abnormal return is
market-adjusted returns (differences between firm returns and returns
on the value-weighted NYSE/AMEX) calculated for the three days around
the annual earnings announcement date. The earnings surprise is
calculated as the difference between actual earnings and consensus
analyst mean forecast divided by the stock price five days prior to the
announcement date. Earnings data are from I/B/E/S. Earnings
announcement dates are obtained from COMPUSTAT. I divide sample firms
into quintile portfolios based on the industry peer's R&D expenditures.
Portfolio Quintile 5 contains highest industry peer's R&D expenditures
(IRDE, IRDA, or IRDS). Portfolio Quintile 1 contains lowest industry
peer's R&D expenditures (IRDE, IRDA, or IRDS). I report the time-series
mean of cross-sectional mean values for these portfolios. Panel A
reports the results for earnings announcement abnormal returns, and
Panel B reports those for earnings surprises. A (***), (**), (*) denote
significance at the 1%, 5%, and 10% levels, respectively. Numbers in
parentheses are t-statistics.
Table 6
Market expansions and industry peer's R&D expenditures
Industry Industry New
Sales Growth Employment Growth Entry
R&D measure:
RDE(R&D/Market Cap)
IRDE 4.78 (*) 6.18 (**) 7.13 (***)
(1.82) (2.26) (3.33)
Ln(SIZE) 0.22 (***) 0.17 (***) 0.01
(3.24) (3.09) (0.02)
LEV 0.25 0.43 0.04
(0.79) (1.09) (0.16)
R&D measure:
RDA(R&D/Assets)
IRDA 5.34 6.99 (*) 12.59 (***)
(1.23) (1.65) (3.46)
Ln(SIZE) 0.22 (***) 0.17 (***) 0.01
(3.25) (3.08) (0.09)
LEV 0.09 0.19 0.11
(0.28) (0.47) (0.44)
R&D measure:
RDS(R&D/Sales)
IRDS 0.75 1.77 (*) 1.40 (*)
(1.05) (2.5) (2.31)
Ln(SIZE) 0.22 (***) 0.16 (***) -0.01
(3.21) (3.03) (-0.45)
LEV 0.08 0.21 -0.69
(0.15) (0.34) (-1.45)
The table reports market expansion regression analysis for sample firms
over 1975-2012. The sample contains 89,782 firm-year observations. The
dependent variables are market expansion measures (Industry sales
growth, Industry employment growth, and new firm entry). I rescale the
dependent variable by a factor of 100. That is, I multiple the market
expansion measures by 100. The independent variables are R&D measures
(R&D/Market Cap, R&D/Assets, R&D/Sales), LnSIZE, and LEV. All variables
are defined as in Table 1. All variables are winsorized at the 1th and
99th percentiles. A (***), (**), (*) denote significance at the 1%, 5%,
and 10% levels, respectively. Numbers in parentheses are t-statistics.