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AS SES S ING THE IMPACT OF FEDERAL INDUSTRIAL
RES EARCH AND DEVELOPMENT COP END ITURE
ON PRIVATE RESEARCH AND DENIES OPMENT ACTIVITY
Frank R. Lichtenberg*
Graduate School of Business
Co lamb ia Univers ity
and
National Bureau of Economic Research
A number of studies have attempted deco determine how federal
expenditures for research and development (R&D) performed in industry
have affected the quanti~cy of private inures vent in R&D . The s tudies
have analyzed the statistical relationship be~cween federal and L
company R&D spending at the five, industry, and aggregate levels.
lathe possibility that priorate decisions to invest in R&D may be
influenced by federal industrial R&D spending is regarded as worthy
of careful investigations in part because numerous studies have
demonstrated that priorate R&D expenditure has ~ significant, posi~ci~re
imp ace on Coccal factor productivity (TEE). Although most analysts
have failed to find evidence of a similar direct productivity impact
of federal R&D expenditures, 2 federal R&D nevertheless may have a
considerate, e indirect impact (positive or negatived on IFP if it
influences private R&D investment decis ions .
Most9 if not all, of the econometric studies of the effect of
federal expenditures on private R&D resource allocation are
"reduced-form" is nature. They a~ctempt to determine the direction
and magnitude of the effect without providing an explicit theoretical
basis for a link between the two. The purpose of this paper is to
fondue ace, and to review or develop evidence concerning, several
maj or hypotheses that could account for the existence of such a
link. The implications of these hypotheses are investigated in the
context of a model predicated upon the assumption that priorate
sponsors of R&D allocate R&D resources optimally, that is, they
employ R&D resources until the point at which the expected marginal
re turns to R&:~) input equal ache marginal cost . This ~ equilibria "
* Financial support from ache National Science Foundation (aria grant
PRA 85-12979 deco ache National Bureau of Economic Research) and from
the MacAr thus Foundation Faculty Research Program at Columbia
Unifiers ity is gratefully acknowledged. Donald Siegel provided
capable research assistance. The remaining errors are Chose of the
author.
· 113 -
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FIGURE 1 Supply and Demand Model of Privately Financed R&D Output Quar.ti
Be termination and Price De te Ruination
$
P*
S
-
-
-
-
-
-
-
-
1
-
-
-
-
,,, !Q*
Quantity of privately financed
Red) output
- L 1 Lo -
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mode 1 o ~ priorate R&D resource allocation is sketched in ache next
section. In that section, three main hypotheses that could account
for the existence of a relationship between federal and private R&D
expend) Cure are offered ~ The three hypotheses, referred deco as
"crowding out, n "spill overs, ~ and "demand pu119 n are examined in
detail in subsequent sections. The section devoted to the
demand-pull hypothesis is the longest and the only one containing new
econometric evidence. Lee emphasis on that h~rpo~chesis reflects ache
belief that insufficient attention has been paid deco ache role of
federal demand for goods and serrices in stimulating pr~ra~ce R&D
investment. As a result, estimates of the relationship between
federal and private R&D have been misincerpre~ced as reflecting solely
the effects of federal R&I) on the supply (cost) of privately produced
innovations . The econometric evidence presented sugges ts an
alternative interpre~ca~cion. The final section provides a summary and
ten~cati~re cone lus ions .
THE MARKET FOR PRIVATE R&D OUTPUT
Economists engaged in the study of technical change sometimes find it
useful to represent research and development as a production
acti~ri~cy, an activity in which the services of R&D inputs (for
examples scientists and engineers, Rho plant) are employed deco produce
improvements in products or processes, which in turn constitute the
output of R&D3 The measurement of R&D output, of course, poses maj or
difficulties ~ In the absence of dla~ca on ache value, in cons Manic
dollars' of improvemen~cs in products and processes, chose interested
in measuring R&D output are confined to the analysis of " indicators"
o f R&D output, such as patent counts e
While economists are fully cognizant of ache serious problems
associated with measuring R&D outpu~c (and, hence, witch measuring
productivity of R&D inputs ), ache concept is both well defined and
useful enough to play a key role in this analysis. We
representation of R&D as an activity devoted to the production of R&D
output is useful because it enables one deco apply ~ appropriately, the
author believes ~ a standard economic model of the determination of
ache quantity and price of an indus~cry's output deco investigate ache
effects of federal R&D on equilibrium priorate R&D output. In the
standard textbook model, as depicted in Figure 1, the equilibrium
quantity and price of an indus~cry's output is determined by the
intersection of the industry supply and demand schedules. The supply
schedule is derived from the marginal cost schedules of ache
individual producers . The position ~ intercept) of ache supply
schedule depends on both input prices and input productivity;
increases in input prices shift the supply schedule up, and increases
in input productivity have the opposite effect. Offend the slope of
Ache supply schedule is hypothesized to depend on the time horizon,
with supply assumed to be less elastic (steeper) in the short run
than in the long run (in which case it may be perfectly elastic?.
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The primary reason for a less than perfectly elastic supply of output
in the short run is a Less than perfectly elastic supply (that is, a
short ° run immobility) of inputs .
This paper proposes Deco analyze the impact of contract R&D
expenditures on private R&D activity (both output and input) within
ache context of an equilibria model of industry output determination.
It is assumed that private sponsors of ~ produce Rho output until
the point at which the marginal cost of improvements in products and
processes eq,'= Is the (-expected) marginal retunes . Lee demand 5 or
marginal willingness to pay, for privately produced R&D output is
assigned to be a nonincreasing function of output. The marginal cost,
or supply, Of n irmova~cions " (R&D Otltpu~C), on the ocher hand, is
assumed to be a strictly increasing function of output. The latter
assumption may be justified on both theoretical and empirical
grounds . First, an ~ intangible ~ input critical to ache production of
industrial innovations - ~ the underlying scientific and technological
"knowledge base"--is, arguably, "quasi-fixed, n meaning that it is
more expens Eve to increase the stock of knowledge quickly than
slowly. Thus, increases in the employment of conventional R&D
inputs, such as scientists and laboratory equipment S are likely to be
subj ect to diminishing .returrts . Second, evidence will be presented
ehat the supply of conventional R&I) inputs is less than perfectly
elastic in tone short run. Additional ~ indirect) evidence of a
positively sloped supply schedule of R&D output is found in the work
of Nadiri and his colleagues. Their econometric studies suggest
that the level of R&D activity responds quite sluggishly deco its
hypothesized de~cerm~nants; the low observed ffspeed of adj,'-ct:ment" of
R&D spending to its long- run equilibrium level. is consistene with the
hypothesis of sharply increasing short-n~n marginal costs of
producing R&I) output.
Shifts in the supply of and the demand for priorate R&D output
result in changes in the equilibrium quantity and price of R&D
output. The next three sections outline in detail echoes hypotheses
chat imply that changes in federal R&D expenditure either cause
shifts in the pri~ra~ce R&D supply schedule, or are correlated witch
(but do not cause) shifts in the demand for privately produced
improvements in products and processes. Hence, each of the
hypotheses court account for Ache existence of a correlation between
federal and prince R&D. The first two hypotheses, referred to as
"crowding out A and "spi3~lo~rers," may be regarded as instances of Ache
general phenomenon of n economies ~ or diseconomies ~ of index try
growth,. a phenomenon perhaps first identified (or at least labeled)
by the eminent 19~ch-century economist Alfred Harshall. Economies
(diseconomies) of growth are said to occur when expansion in the
total output of an industry per se results in reductions (increases)
in each producer's unit cost of production According deco the
crowding-out hypothesis, increases in federal R&D expenditure impose
"external" (pecuniary) diseconomies on private R&D sponsors.
Spillo~rers, on ache other hand, may be interpreted as "internal"
~ technological) economies in the priorate production of R&D Output
generated by increased federal R&D expenditure.
- 115
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I e the supply-and-demand model of private R&D output
de~er=~nation is useful for evaluating some of the possible impacts
of federal R&D expenditure on private R&D activity, it is less well
suited to analyzing others. Two features of federal industrial it&l)
activity whose impact on private R&D it is difficult to assess ~ in
this framework and perhaps in general ~ are its relatively high degree
of concentration and its relative instability. As Table 1 indicates,
federal R&D ascends deco be performed by a smaller number of large
companies than privately sponsored R&D. Thus, increases in ache
federal share of total industrial it&l) expenditure would be expected
to result in an increased concentration of R&D resources. Table 2
illustrates the substantially greater volatility in the growth of
federal Red) than in the growth of company it&l) between L956 and
1983. Two measures of volatility, the coefficient of variation and
the range of the growth rate, are, respectively, 5 . 6 and 3 . ~ times as
large in ache case of federal R&D as they are for company R&D. This
contrast reflects the episodic nature of federal commitments to
devote resources to industrial Red). A troubling possibility is that
the relatively volatile pattern of federal investment destabilizes
the market for private R&~) output by increasing uncertainty about the
future course of technological change and, perhaps, as a result,
depresses the quantity of private R&D investment in the long run
CROWDING OUT
lye crowding-out hypothesis is that increases in federal R&D activity
increase ache private cost of producing R&D output by driving up the
prices of specialized R&D inputs. The hypothesis is predicated on
the assumption that federal and pri~ra~ce R&D employ similar types of
resources, such as scientists and engineers, the aggregate supply of
which is less than perfectly elastic. A graphic representation of
ache crowding - out phenomenon is gird in Figure 2 . Suppose, for
concreteness, that the graph represents ache market for R&D scientists
and engineers. The supply schedule of scientists and engineers is
labeled S. and the federal and priorate demand schedules are labeled
DO and Dp, respectively. 'the market-clearing wage race W is
determined by the in~cersection of ache supply schedule and the
aggregate demand schedule D ~ the horizon~cal sum of OF and I):, I,
and equilibrium employment in each of the two sectors* (L ~ and
L p) is found by evaluating ache demand schedules at ~ . An
outboard shift in DF would result in an increase in W and a
reduction in L p. The magni~cude of these effects depends, of
course, on the slopes of ache demand and supply schedules. Suppose
that these schedules are linear, so that they may be written as
follows:
supply: L aS t. bSW
federal demand: LF aF ~ by
priorate demand: Lp ~ ap - bpU bS, bF, bp 2 °
- 117 —
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TABLE 1 Comparison of the Extent of Concentration of Federal and Company
R&D Funds, 19 81
Federal
Funds
Percent of ~co~cal
R&D funds spent
by companies witch:
25, 000 or more employees 83
Fewer than 1, 000 employees 3
Percen~c of total
R&I) funds spent
by 20 largest
RED performers
Source:
.
68
65
6
41
Company
Funds
Research and Developmene in Industry, 1081 . NSF 83 - 325 .
Washington, DC: National Science Foundation, 1983, Tables B-
B-ll, B-7 9.
! 1 8 -
- _,
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TAB Lo: 2 Comparison of the Extent of Stability of the Growth in Real Federal
and Real Company R&D Spending, 1956~1983
Growth Rate
0 f Real Federal
ILL
Growth Race
of Real Company
8&1) Spending
Mean · O 021 O 049
S tandard deviation . 074 . 031
Coefficient of variation 3 O 52
DO 63
)£irlim~ ~ ~ t35 - . 028
Maximum O 231 . 090
Range .366 .118
Note ~
Federal and company R&D funds deflated using GNP implicit pric
deflator ~
..
Source: Research and DeveJopmenc in Indusery 1983
National Science Foundation, 1985.
- 119
-
Washington OC
.
e
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FIGtJRE 2 Marker for Scientists and Engineers: Impact of Shift in Federal
Demand from O~ to D F on Cage Rate and Private Employment of Sciert~cists
and Engineers
~~ t
4, It
\ · 1
OF l I ~ F
-
-
-
-
\.~
Dp ~
S
~ \ D 1)'
L'; Lp
- 190
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Representative terms from entire chapter:
perfectly elastic
The equilibrium condition is L - LF + Lp. The maricet-cl~aring
wage rat te is ~cher.efore
,,*_ aF + ap - aS
and the effect of a unit shift in the federal demand curve on W is
dW, 1
daF bS + bF ~ bp
This effect will be larger, the smaller each of the parameters b.
by and by is ~ that is, ache less elastic the supply and demand
schedules are ~ .
Unfortunately, very little is known about the values of the
demand parameters by and bp. In view of the national security
orientation of much federal R&D, and the limited incentives deco
minimize costs provided by federal con~cracting methods (for example,
cost-plus ), one might reasonably cony endure chat bF is fairly
small, perhaps very small, re latitude deco bp .
Me lack of info rmation about b is particularly unfortunate,
since the effect of a shift in federal demand on private RED
employment, A, is -bp.
Freeman analyzed the behavior of the markets for physicists and for
engineers and the role of federal R&~) spending in determining their
starting salaries during the period from the ~ ate ~ 940' s to the early
1970' s . He found that federal R&D spending played a preeminent role
in determining the starting salaries of both Occupations:
Changes in R&D expenditures were the chief factor influencing
[eng~sleers' star~cing] salaries during ache post-Uc~rld War II
period.. Me upswings and downswings in salaries car be traced
to changes in federal R&D policy.
And,
Changed demand, due primarily deco changes in federal §&1) spending,
was the chief source of changes in physics salaries.
~ Emphasis in original ~
Freeman estimated the elasticity of engineers' starting salaries with
respect deco federal R&D expenditure (both is constant dollars ~ to be
~ n the range . 26 to .41. In ache case of physicists, he estimated the
federal R&D elasticity of starting galaxies by decree tearer. The
estimated elasticities were in the ranges 0 34 deco .36 for individuals
with bachelor's degrees, .54 to .56 for these with master's degrees,
and .33 to 044 for those with Ph.D. 's. Freeman's estimates are
summarized in Table 3.
Federal obligations for R&D, in current dollars, have increased
from $38 0 7 bills on in fiscal year 1983 ~co an estimated $520 3 billion
in fiscal year 1985. This represents ~ nominal increase of about 30
percent or Lassoing a two-year increase in the price laurel of 10
percent or less ~ in increase in real federal R&D expenditure of at
least 20 percent. Freeman's estimates imply that the federal R&D
elasticity of both engineers' and physicists' starting salaries is in
the neighborhood of one third or perhaps somewhat higher. An
elasticity of one third would imply that the. growth in real federal
R&D spending between 1983 and 1985 has increased real starting
salaries by roughly 7 percent over two years (10 percent if we use
the estimated growth in R&D obligations to industrial firms).
Evidence about the effect of recent changes in the growth rate of
defense spending generally (not just federal R&D spending) on the
growth of engineers' and technicians' starting salaries has been
obtained from college placement officers. Real defense spending
increased rapidly beginning in about 1979 until this year when
Congress and the Reagan Administraelon agreed to end the buildup by
maintaining a zero race of real spending increase. College placement
officers report that increases in starting pay for engineers and
technicians, which "have ranged from ~ to 12 percent over the last
half-d~-n years, are expected to average only 3 percent his
year. n
— 122 -
D
TABLE 3 Estimates of Elasticities of Real Starting Salaries of Engineers
and Physicists with Respect deco Real Federal R&D Expenditures ~ estimates
refer co the period from the late 1940 ' s to the early 1970 ~ s
Es timated Range
of Elasticity
End neers . 26 ~ . 41
Physicists
B . S O . 34 - . 3 6
,Y . S O ~ S4 ~ . 5 6
Ph O D G ~ 33 ~ .44
Source: R. B. Freeman. "Supply and Salary Adjustments to the Changing
Science Manpower Marice~c: Physics, 1948 - 1973, American Economic
- Retries, Vol. 65, No. [(March 1975), pp. 27-39; and R.B.
Freeman. "A Cobweb Model of the Supply and Starting Salary of
New Engineers, " Industrial and Labor Relations Reviews,
Vol O 29, No . 2 (January 1976 ), pp . 236 - 248 .
~ 123 _
.o Cal company- funded R&D, total sales, and sales to the government
for over 9, 000 business segments, classified by extent of government
orientation. Government-or~ented segments are defined as Chose for
which the ratio of reported sales deco the government to the to Cal
segment sales was at least 10 percent. This definition was adopted
because a segment is required to disclose government sales only if
the ratio of ache latter deco total sales is at least 10 percent. 1
The ratio of topical government sales reported by govers~mes`t - oriented
segments to their total reported sales is S3 .5 percent; the
corresponding ratio for ocher segments is less than one half of one
percent . The average privately financed R&D inters icy of
go~rernment-oriented segments is lo 72 percent, compared deco a value of
O . 54 percent for other segments . lathe R&D intensity of go~rernment-
oriented segments is 3.19 times ~cha~c of other segments, reflecting
the fact that the total sales of ocher segments were 320 7 times those
of government-oriented segments, Anile the total R&D expenditure was
10.3 times as high. The estimated difference between the R&D
intensities of gover~en~c-oriented and other segments is almost
identical to the estimated difference between the "used" R&D
intens ities of defense and consumption expenditures implied by
Scherer's deco.
The substantial difference between the R&D intensity of federal
expenditures and that of other components of the GNP suggests dacha. it
is useful to represent the average private R&D intensity of the U. S .
economy as a weighted average of the two R&D in~censi~cies, with shares
in GNP as we fights:
CEt.D ~ C=FED GNPFEI:) ~ C9DNON
GNP GAPPED GNP GNPNON
crd ~ crdf ~ f + crud . ( 1
where CAD
GNP
CRDF£0
-
G=FED
, C8DNoN
GNENON
crd
crdf
crd-,
GNPNON
~-
GNP
f)
aggregate U. S . company- funded Red) expenditure
gross national product
company-funded R&D oriented toward federal
purchases of goods and services
federal purchases of goods and ser~r~ces
CAD - C3DrED
GNP ~ GAP FED
CRD / GNP
CRDFED / GAFFED
GNPFE~ / GNP
CADNoN / G~PNON .
- 138 -
Suppose Marc crdf and crdn are cons cants . Then, the above
equation imp lies that the variation over tinge in average R&D
intensity (crd) can be interpreted as attributable in part to
variance on in the federal share in GNP (f):
crd ~ Sac ~ ~ crdn + ~ crdf - crdn) . f ~ ~ ~
The regression of crd on f has been estimated using annual data for
the period 1956-1983. Because both series exhibit trend (positive in
the case of crd, 2:ega~cive in the case of f), a time trend is included
in the equation. In the presence of ache time trend, the
coefficient on f captures the effect of a deviation of f from its
trend value on the deviation of crd from its trend value. Loosely
speaking, the coefficient measures the short-run (transitory) . rather
than the long- run (permanent) influence of f on cord.
Estimates of the model are presented in Table 10. The estimated
coefficient on f is positive and its difference from zero is highly
statistically significant, a finding consistent witch the hypothesis
that changes in ache composition of final demand account for a
significant fraction of the short~run ~raria~cion in crd.2 lithe
point estimate of this coefficient, .036 9 is much larger- -about three
times larger- - than the estimated difference ~ crap - crdn) implied
by both the Scherer and the business segment data. This discrepancy
may reflect ache distinction between short-run and long~run effects on
R&D intensity of changing composition of demand. In any extent, all
the evidence presented points to the conclusion that the amount of
R&D expenditure firms choose taco sponsor, conditional on their total
Parolee of sales, depends upon the distribution of their sales between
government and other purchasers.
Because ache underlying priorate R&D irrtens icy of goods purchased
by the federal government is substantially higher than that of goods
purchased by other final demand sectors (households, stance and local
governments, for example), the equilibrium quan~ci~cy of private R&O is
likely to be influenced by the composition (federal versus other) as
well an the level of final demand. In econometric studies of the
determinants of private Red) expenditure, it is conventional to
control for total sales (at the firm or industry level) or GNP (~t
ache aggregate level) but not for the composition of sales or GNP.
Thus, these models embody the a priori restriction that a given
increase in federal sales or demand has ache same impact on priorate
R&D expenditure as a corresponding increase in nonfederal sales, a
res Friction that is unlike ly deco be true . lathe fo flowing evidence
suggests that inappropriate imposition of this restriction results in
seriously (upwardly) biased estimates of the partial effect of
federal R&D expenditure on priorate R&D expenditure.
Estimates (based on annual time series data for the period
1956 -1983 ~ of the regression of aggregate company- sponsored R&D
expenditure (CAD) an aggregate federal industrial R&D Expenditure
(=D), GNP, and a time trend can serve as a benchmark. The CRD,
- 139 -
T^~L~- ~ O Regression of Aggregate Company-Funded R&I) Intensity on Share of
.-ederal Defense Purchases in GNP, Annual Data, 1956-1983
Es ~ ima ted S tandard
NTar'~ble Coe~¢ic;-en~c Error t- "at 0
f O.03611 0.01016 3. 5~3
~ ime trend 0.00021 0.00002 10.054
interc ep sac - O . 415 0 . 042 6 - 9 . 7 3,
p ~ . .377 sad. error (p) ~ . 189
R2 ~ . 96 10
Notice: f is defined as ache ratio of federal purchases of goods and se~~.ces
to GNP.
1'.0
-
FRY, and SAP are all deflated us dung the GNP implicit price
deflator.' Because of the uncertainty about the timing of the
relationship between COD on the one hand, and E.RD arid GNP on the
o ther, a future and a past value, as well as the con~cemporaneous
value, of both FAD and GNP are included in the equation. Me
estimated equation was of the form:
So + 51E=~t + 1) + B2F~D(t) + B3=D(t ~ L)
1 ~ t2G~P(t) + <3GNP(t - 1)
+ /- t
Estimates of the effects of ERD and of GNP on COD are based on the
es timated sums of the corresponding coeff indents, that is ~ B
B2 ~ B3) and (~: + Y2 +~3) . respec~ci~rely. Estima~ces
of these suns, their standard errors, t- ratios, and associated
probability; values are shown in the left-hand Coleman of Table 11. In
this model, the point estimate of the son of the ED coefficients is
033, a value similar to (slightly larger than) th'8corresponding
parameter estimate obtained by Levy and Terleckyj using a similar
data- set and specification The estima~ced sum is highly
significantly different from zero, a finding also consisten~c with
Leery and Terleckyj ' s results .
The right-hand Calvin of Table 11 displays statistics about the
suns of coefficients when GNP is disaggregated into its components,
FEI)GNP (federal purchases of goods and services) and NONGNP (GNP -
FEDGNP). The res~criction Chat FEDGNP and NONGNP have identical
coefficients, imposed a priory in the lef~c-hand column estimates, is
no longer maintained in the right-hand column estima~ces. As
expected, the estimated sea of the coefficients on ache FEDGNP terms
is much larger- - about ten times larger - than the estimated son of
coefficients on the NONGNP terms. lathe hypothesis that the sues of
ache FEDGNP and NONGNP coefficients are identical may be rejected at
the . 05 significance level. It is the reduction (relative to the
restricted model) in the size and significance of ache sun of the FRD
coefficients that is of primary concern. The estimated effect of ERD
on CAD is only one shirt as large when FEDGNP and NONGNP are allowed
to have different coefficients as it is when these coefficients are
constrained to be equal. Moreover, the estimated see is
insignificantly different from zero. Even though FEDGNP appears, in
a highly restricted fashion, on the right-hand side of the restricted
model, the fact that FEDGNP is a relatively small fraction of total
GNP (in the neighborhood of 10 percent) implies that the restricted
model does not adequately control for variation in federal demand.
Relaxing the restriction in effect controls for the influence of
federal demand and makes it possible to obtain a truer estimate of
the partial effect of federal R&D expenditure on private R&D.
Because FRD is a component of FEDGNP (~hat is, federal purchases
of R&D services are included in total federal purchases of goods and
services), the statistical insignificance of FRD signifies not that
TABLE 41 S to tistics from Aggregate Real Comply- Funded R&D - Expends Cure
Regressions ~ ~ values in parentheses ~
Res tric~ced~
Made ~
Unres Eric ted
"ode t
Sum of FAD .330 .log
coefficients ~ ~ (2045) (0. 60)
~ ~ O 013 a ~ 280
Sum of GNP O 006
coe ~ficients ~ ~ c 19 ~
~ ~ ~ 125
Sin of FrDGNi . 052
coefficients (2 . 09 ~
~ ~ . 028
She of NONGNP . 005
coefficients ~ 0 . 9 2 ~
a ~ .187
YEAR . 301.7 327.0
( 1 e 54 ) ( ~ ~ 5 8 )
p ~ 404 ~ 173
(1~. 82) (O ~ 66)
Wrote: ~ denotes probability value for testing null hypothesis that sum of
corresponding coefficients equals zero.
- 142
-
~ has no effect on priorate it&l) expenditure, but rancher Chat one
cannot rej ect ache hypothesis that FRD has the same impact on private
R&D expenditure as do federal purchases of non-R6`D services and
products. In other words, the insignificance of AD implies that
federal R&D expenditures do not have an impact on prince R&D above
and beyond that of federal non-~&l) expenditures, although ache point
estimate of the impact is about three times as large. If a similar
model were es timated on a larger data set ~ for example, cross -
sectional or longitudinal data for a large number of firms ), the
estimated difference between the effects of federal R&D and non-A&D
purchases Light be significantly different from zero. Butch as in the
case here, controlling for ache composition of sales or demand. is
likely deco reduce the estimated effect of FRD on CRD substantially.
SUMMARY ANI) TENTATIVE CONCLUS IONS
It has been argued in this paper that there are two principal
mechanisms or paths by which federal industrial R&D may influence the
cost to private R&D sponsors of producing given improvements in
products and processes. Increases in federal R&D expenditure may, in
principle, increase the average and marginal cost of private R&D
performance by driving up the prices of R&D inputs of which the
supply is less than perfectly elastic. On the other hand, federal
R&D may lower private R&D costs by generating knowledge that is
useful in the priorate production of innovations, hence raising the
producti~ri~cy of privately employed R&D inputs.
There is reasonably strong econometric evidence supporting the
hypothesis that increases in federal R&13 result in significan~cly
higher ~ starting) salaries of scientists, engineers, and technical
personnel, at least in the short run. Because the supply of
technical manpower is much more elastic in the tong run than it is in
the short run, the effect on wages and salaries of a federal R&D
increase is probably much smaller in the long run than it is in ache
short run, and it may even be zero.
Evidence regarding ache incidence of cost-reducing (from the
perspective of private R&D sponsors ~ spillovers from federal R&D is
extremely limited. Data on the distribution of contract R&D by
restages of R&D, on the distribution of property rights to
government-financed contractor inventions' and on the extent of
licensing of government-owned patents all suggest that most federal
industrial R&D expenditure produces little or no spillover. It is
probate ly the case, however, that a small fraction of federally
supported R&D generates very large spillo~rers (some of which may be
negative ~ . I.c does not appear pass ible Deco estimate directly, from
data actually or even po~centially available, the magr~i~cude of private
R&D cost reduction yielded by the "average" dollar of federal R&D
expend) ture .
- 143 ~
Because it is not feasible to observe or directly estimate the
net effect of federal R&D on the supply schedule of private R&D
output, a number of inves tigators have attempted to draw ind~rec t
inferences about this effect from estimates of the reduced- form
relationship between privately funded and federally funded R&D
expenditures, controlling only for focal demand. If the demand for
privately produced innovations were stable, or if shifts in demand
were uncorrelatad Erich changes in federal R&D, then the finding of a
significant positive relationship between federal and company Rap)
expenditure would provide rather strong evidence of spillovers. It
has been demonstrated here, however, that changes in real federal R&D
spending are correlated with changes in the composition of final
demand, which shift the aggregate demand for private R&D Output.
When statistical controls for the composition as well as for the
level of demand are used, the hypothesis that federal R&D expenditure
has ache same effect on priorate R&D expenditure as federal expenditure
on non-A&D services and products (which stimulates considerably more
private R&D than other components of final demand) cannot be
rej ected. Because federal R&D expenditures are a relatively small
fraction of total federal. purchases of goods and services, and do no
appear to have ~ significan~cly larger effect on pri~ra~ce R&D than
federal nonskid purchases, one must consider. and take account of
government procurement behavior as a whole, and not just R&D
contracting, deco understand the extent and nature of federal influence
on private decisions to invest in R&D.
144
NOTES AND REFERENCES
For a critical review of some of this literature, see F.
Lichtenberg;. 'the Relat' onship Between Federal Contract R&D and
Company R&D. ~ In American Economic Association Papers and
Proceedings. Nashville, TN: May 1984.
See, for example, Z. Griliches and F. I-ichtenberg. "R&D and
Productivity- at ache Industrial Level: Is There Still a
Relationship? " In ~R&D, Parents, and Productive By. Evinced by
Z. Griliches. Chicago: University of Chicago Press, 1984.
3 . There also are problems associated with measuring ache quant' ty of
~ real ~ R&D input emp toyed for a particular purpose . Three such
problems are worth noting. First, there may be problems of
measuring total R&D expenditure in current dollars. A recent
National Science Foundation report ~ see A Comparative Analysis
of Information on National Industrial R&D Expenditures. NSF
85 - 311. t~ashing~con, DC: National Science Foundation, 198S
retreats discrepancies between es timatPs of R&D expenditure
reported by firms in their responses to the NSF/Census RD- ~
survey and Chose reported in 10-K reports to ache Securities and
Exchange Commission; evidently, these discrepancies are due
large ty to different treatment o f expenditures on " engineering
and routine technical ser~rices.'' Second, there are problems
associated with the deflation of nominal R&D expenditure required
to obtain an index of real R&D input . ~ Industry- specific R&D
deflators, however, have been developed recently by Mansfield;
see E. Mansfield. "Price Indexes for R and I) Inputs, 1969-83. "
video. ~ Third, the segregation of tomcat. R&D expenditures into
company- and go~rernmen~c- funded components, particularly at the
firm or industry Petrel, is problematic. The difficulty arises,
in part, because of the way in which Independent Research and
De~relopmen~c (IR&D) expenditures are reported in the official
(NSF) R&D statistics. (For a detailed discussion of this issue,
see J. Reppy. The IRKS Pro gram of the Departmen~c of Defense. ~
Cornell University Peace Studies Program Occasional Paper No. 6,
March 1976; and J. Reppy. "Defense Department Payments for
'Company-Financed' R6iD, ~ Research Policy, Vot. 6(1977), pp.
396-410.) Serious as these problems of R&D input measurement
are, they pale in comparison deco the conceptual and practical
difficulties of measuring R6:D output.
4. See, for example, M. Nadiri and I. Prucha. "Comparison and
Analysis of Productivity Growth and R&D Investment in ache
Electrical Machinery Industries of the United States and Japan. "
Pacer presented at ache National Bureau of Economic Research
Conference on Productivity Growth in Japan and the United States,
Cambridge, MA, August 25 - 28, 1985 .
~ 145 —
~ .
E. Mans fly eld. "Commentary: Capital Formation, Technology, and
Economic Policy. n In "Industrial Change and Public Policy, " from
~ shakos in sponsored by the Federal Reserve Bank of Kansas City,
Missouri, 1983, p. 261.
The smaller be is, the greater do /da~ is, the wage
increase resulting from a given federal demand shifts but
ache smaller the private employment response to a gives wage
increase . S ince the latter is a first ~ order effect and the
former is a second~order effect, for gibes bS and bF, the
absolute value of P is increasing in be,:
P _ - (1 + S + F ) i
daF bp bp
7 . R. B. Freeman. "A Cobweb Model of ache Supply and Starting Salary
of New Engineers," Industrial and Labor Reasons Review,
Vo: . 29, No ~ 2 ( 1976 ), p ~ 244.
8 . R. B Freeman. "Supply and Salary Adjustments to the Changing
Science Manpower Market: Physics, 1948-1973, n American:
Economi c Revi en, To 1 . 6 i, No . 1 (March 19 7 5 ), p . 3 7 .
9. Federal obligations Go industrial firms for R&D, in current
dollars9 have increased more rapidly°°about 40 percent from
$18 0 6 billion deco an estimated $270 7 billion.
10. See 'For Military Suppliers, Growth Uncertainties, n New Fork
Times, Section 12 (October 13, 1985 ), p . 10 . Research and
development, or the management or ad~m~nis~cration of R&D, was the
"primary work activityn of 62 percent of the 186,000 engineers
reported deco be working in the area of national defense in 1982
(see 1982 Postcensal Sunder of Scientists and Engineers. NSF
84- 330. Washington, DC: Na~ciona1 Science Foundation, 1984,
Table Be 13) . Hence, most of the changes in engineering salaries
associated with changes in overall defense spending probably are
at~cribu~cable to changes is defense R&D expenditure.
11. M. Shankerman and A. Palces. "Estimates of the false of Percent
Rights in European Countries during the Post-1950 Period. ~
National Bureau of Economic Research Forking Paper No. 16SO, June
1985, pp. 19-21.
. Product and Service Codes. Fairfax, VA: Federal Procurement
Da~ca Center, 1982, p. 8.
3. Annual Report on Gotrernmenc Parent Policy. Washington, DC:
Federal Council on Science and Technology, December 1971 and
December 1972 combined.
— 1' 6 —
14 . Government and Technical Progress: A Cross - Indusery
Analysis. Edited by R. Nelson. New York: Person Press,
1982.
15. Jacob Schmookler. Invenriora and Economic Growth. Cambridge,
but\ Harvard Unifiers ity Press, 1966 .
16. M. KAmien and N. Schwartz. market Structure and Innovation.
Cambridge: Cambridge University Press, 1982, p. 36.
17. D. Mowery and N. Rosenberg. "The Influence of Market Demand Upon
Innovation: A Critical Review of Some Recent Empirical S tudies, "
Research Policy, sol . 8 ( 1979 ), pp . 102 -15 3 .
18. Ibid.
19. F.~.. Scherer. "Using Linked Patent arid R&D Data to Measure
Interindustry Technology Flows." In R&D, Parents, and
Productivity. Edited by Z. Griliches. Chicago: IJni~rersi~cy of
Chicago Press, 1984.
20. National Science Board. Science Indicators, 1982.
Washington, DC: U. S . Government Printing Office, 1983, pp . 7-8 .
21. A relatively small number of segments for which the ratio is
be low 10 percent also report government sales .
22. In view of the rule for reporting government sales, this is a
lower bound estimate of the true ratio for other segments.
I t is cus tomary, and appropriate, when analyz ing re la~cionship s
among time series, to de trend or otherwise render stationary the
series. Inclusion of the time trend reduced substan~cially, but
did not eliminate, serial correlation of ache residuals, so an
adjustment for first-order serial correlation was made in
es timating the mode l .
24. The partial r2~ ~c2/(t2 + resid. do f. ~ ~ on f is . 34.
25. An equation is which CRD is expressed as a function of FRD and
GNP (or itch components ~ may be interpreted as the reduced form of
a system of supply and demand (of private RED output) equations
in which "D appears in (shifts) the supply equation and GNP
appears in the demand equation. Such a system may be represented
as fo flows:
supply) Ps ~ aO + alC8D + a2FRD
(demand) PD ho + b~CRD + b2GNp
where PS denotes the " suppl3r price " (marginal cost), and PD
the " demand price n (marginal returns ), of private R&D output .
equilibrium, PS ~ P:> Equating the right-hand sides of the
supply and demand equations, and soldering for CRD,
_ ~ 4 7 —
COD (50 ~ Do) 2 ~ + 2~ GL;?
(~1 - b:) (~1 ~ bl) (a1 - b: )
GNP mav be expressed as the soul of two co~npones~ts, FEDGNP
~ federal purchases of goods and services ~ and NONGNP (GNP
F_DGNP). The evidence cited above suggests that a billion-dollcar
increase in FEDGNP strifes the demand for private R&D output
substantially more than a corresponding increase is NONGNP does.
Hence, the restriction that F£DGNP and NONGNP have identical
coefficients in the demand equation should be relaxed ~ and
tested). Since FIND is correlated fairly highly with FEDGNP,
relaxing this restriction is likely to have a nontrivial effect
on the size and significance of the reduced- foot coefficient on
FEDRD .
26. Unfortunately, Mansfield' s it&D-deflator time series begins one y
in 1969. See E. Mansfield. "Price Indexes for R and I) Inputs,
1969 - 83 . " Video .
27. lathe author experimented witch a large number of alternative
specifications and found that estimates of stems of coefficients
were much less sensitive to minor changes in equation
specification than were estima~ces of individual coefficients.
28 . D. L eve and N. Teriecicyj . "Effects of Government R&D on Or ~ date
R&D Investment and Productivity: A Macroeconomic Analysis,"
Bead Journal of Economics,, Vol. 14~1983~, pp. S51-561.
Because values corresponding to periods ~ ~ + 1 ), ~ t), and ~ t - 1 )
of FRD, FEDGNP, and NONGNP are included as regressors, and each
of these series is fairly smooth 5 individual coefficients Thor
example, the coefficient on FEDGNP(~c) ~ are estimated imprecisely.
Thus, tt is nor possible to rej ect the hypothesis tha. (using
variable names to represen~c the names of their respective
coefficients) FEDGNP (~c + j ~ - NONGNP (t ~ j ), j - -1, O. 1-- the
hypothesis that one would test by comparing ache residual sums of
squares of the restricted and unrestricted models. The
hypothesis ~; (FEDGNP(t + j ~ ° NONGNP(t + j ~ ~ ~ O. however, can
jest,
be rej ected at the 5-percent level of significance .
30. Because, however, as is observed below, FED is a component of
FEDGlJP, Me point estimate of the effect of Fed on CRD is
. 161 ~ ~ .109 + . 052), about half of ache estimated effect in the
restricted model.
31.
Disaggregating GNP into its components also has the (desirable)
effect of reducing the extent of serial correlation of =he
res iduals substantially .
— 148 —
