The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.
REGIONAL ECO N O M IC ISSUES
W o r k in g P a p e r S e r ie s
D e te r m in in g M a n u fa c tu r in g O u tp u t
fo r S ta te s an d
R e g io n s
Philip R. Israilevich and William A. Testa
FEDERAL RESERVE B A N K
O F C H IC A G O
W P- 1989/4
D e t e r m in in g
and
M a n u f a c t u r in g
O u tp u t fo r S ta te s
R e g io n s
Phillip R. Israilevich and William A. Testa*
I. T h e C e n s u s value added: w h a t is w r o n g ?
Much of what we think we know concerning the changing geography of
manufacturing may need to be re-examined. The regional analyst’s chief
measure of manufacturing output, the Census’ “value added” , has a strong
bias across the U.S. geographic landscape.
The existing method of measuring value added (VA) mis-apportions a large
part of manufacturing output to states and regions. The part in question
comprises the activity of the “ auxiliary” establishments of manufacturing
firms—i.e. corporate headquarters functions, research and development ac
tivity, data processing, and warehousing. To illustrate, we refer to two ex
amples from the 1982 C ensus o f M anu factu rers. In Detroit, auxiliary’s
payroll share in total manufacturing payroll was 28 percent, while in
Buffalo, N .Y ., this figure was only 4 percent. Being a large center of
interstate companies serving the auto industry, the Detroit area conducts
R & D and performs headquarters’ activities to facilitate operating or pro
duction plants throughout the nation. Therefore, V A created by auxiliaries
in Detroit is “exported” to other states. However, the Census V A do not
account for this exported V A created in Detroit. Conversely, the Census
V A in Buffalo will include “imported” V A because operating units there
are consuming services from auxiliaries located elsewhere. Manufacturing
output is overcounted in Buffalo and undercounted in Detroit.
In the following discussion, the existing Census methodology and data base
are explained. In addition, the significance of the auxiliary establishments
are illustrated with published statistics and economic literature. In part III,
based on a statistical model, the difference between the Census and true
V A is found to be highly significant. Further, the role of auxiliaries fluc
tuates both short and long term, indicating that the bias embedded in
’“The authors are economists at the Federal Reserve Bank of Chicago. They thank John
Dodds, Chief of the Enterprise Statistics Division, Bureau of the Census, for helpful comments
and insights. Appreciation is also expressed to Tirza Haviv for able research assistance.
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
1
Census V A will misguide analysts in a wide array o f topics, part IV. Part
V evaluates two potential methods of correcting the problem. To conclude,
the importance of the correctly measured V A for various regional research
endeavors is presented.
II. T h e C e n s u s “value a d d e d ” defined
The Census Bureau does not directly gather and compile information on
V A. Rather, the Bureau constructs V A based on the value of manufactured
shipments—data which is reported directly by manufacturing operating
plants. For purposes of measuring manufacturing output, the value of
shipments alone is not useful because it often includes the value of pur
chased materials and intermediate manufactured goods. Accordingly, if
one were to sum up the value of shipments across plants to arrive at total
output, one would be double counting. For example, an intermediate good
would be counted twice—once at its plant of origin and shipment and once
again at the plant where it becomes a component of another manufactured
good(shipment).
For this reason, the cost of purchased materials and
intermediate goods are subtracted from reported values of manufacturing
shipments at each plant to arrive at “value added” . V A is, then, a residual,
representing the incremental value “added” or contributed to the product
by the manufacturing firm.1 In its favor, summing up V A across plants
does not amount to double counting because any intermediate manufac
tured goods are correctly counted at their plant of origin and henceforth
netted out as intermediate goods at later stages of production in other
manufacturing plants.
The nub of the measurement problem is that Census V A includes, not only
the incremental value made to the product at the production plant, but also
the contribution to value made by the firm overall. The problem is one of
geography and not a problem of summation to national industry totals.2
The V A of each firm is allocated to states and regions solely on the basis
of where the company’s operating plants are located.3 But the geography
of the firm (including its auxiliary establishments) can be quite different
from that of operating plants at which the firm’s V A data is reported.
For example, a manufacturing product’s design and engineering may orig
inate at the firm’s R & D center and not at the plant location. Similarly, the
product’s advertising and image may be fashioned at an out-of-state sales
office or corporate headquarters of the manufacturing firm. All these ac
tivities which are attendant to production activity do legitimately comprise
a product’s value as actually recorded from plant level data. But no V A
at all is reported and recorded by auxiliary establishments.
FRB CH ICAGO W orking Paper
February 1989 , W P -1989-4
2
Table 1
S e le c te d s t a t is t ic s o f a u x ilia r y e s ta b lis h m e n ts
f o r m a n u f a c t u r in g f ir m s —1 9 8 2
Establishments*
Number
Share
Employees
Number
Share
(000's)
Total manufacturing
-Administrative and managerial
-Office and clerical
-Research, development & testing
-Warehousing
-Electronic data processing
-Other activities
9,676
7,792
6,157
1,967
2,087
2,357
4,353
100.0
80.5
63.6
20.3
21.6
24.4
44.9
1,276.0
501.4
255.2
158.3
57.4
56.8
247.0
100.0
39.3
20.0
12.4
4.5
4.5
19.4
*l\lote: Detailed establishment data exceed totals and sum to more than 100% because
some establishments participate in more than one activity.
SOURCE: U.S. Dept, of Commerce, Bureau of the Census, 1982 Census of Manufacturing
Subject Series Vol. 1, p. 1-100.
Activities at auxiliary establishments support the manufacturing production
activities of the firm. Among the various types of auxiliary activities, ad
ministrative and managerial activities were most prominent in 1982, fol
lowed by general office and clerical, and thirdly by research, development
and testing (Table 1). All of these activities are reflected in the value of
product shipments from production plants (i.e.“operating establishments”)
even though the location of auxiliary establishments is frequently (but not
always) located elsewhere. The size of V A originating with auxiliary es
tablishments can be significant. Auxiliary payroll amounted to almost 11
percent of total manufacturing firm payroll in 1986. In individual regions,
auxiliary payroll stretched as high as 49 percent for the State of Delaware
and 54 percent in the Stamford, Connecticut, SM SA in 1982. For individ
ual industries, the evidence on the significance of auxiliary activities is also
striking (Table 2). Disaggregating total manufacturing into its 19 major
components, a wide ranging importance of auxiliary payroll is revealed.
For example, some industries which fall under the “chemicals industry”
banner report over one-fourth of total payroll at auxiliary establishments
and some industries in “petroleum and coal products” report over one-third
of payroll outside of operating establishments.
Here is one way to verify that the current Census procedure actually allo
cates V A as we believe it does, in proportion to operating establishments
and not to auxiliary activity. Using auxiliary payroll and operating estab
lishment payroll as proxies for their respective overall activity or V A , we
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
3
Table 2
A u x ilia r y p a y r o ll as a p e r c e n t o f t o t a l in d u s tr y p a y r o ll
b y in d u s tr y —1 9 8 6
Petroleum and coal products
Chemicals and allied products
Tobacco products
Instruments and related products
Electric and electronic equipment
Food and kindred products
Leather and leather products
Total manufacturing
37.9
27.6
26.5
13.6
13.3
13.0
11.5
10.7
Stone, clay, and glass prods.
Machinery, except electrical
Miscellaneous manufacturing industries
Textile mill products
Transportation equipment
Rubber and misc. plastic products
Apparel and other textile products
Paper and allied products
Printing and publishing
Lumber and wood products
Primary metal industries
Fabricated metal products
10.5
9.4
8.4
8.2
7.6
7.5
7.5
7.4
5.7
5.4
5.2
5.1
SOURCE: U.S. Dept, of Commerce, Bureau of the Census, 1986 Annual Survey of Man
ufactures, M 86(AS)-1, Table 1-6, 1988.
regress both types of payroll on reported V A for the 1982 cross section of
states. Similarly, we do the same for the 1982 cross section of SMS As.
As expected we find that reported V A correlates very significantly with
operating payroll while auxiliary activity (payroll) has no significant influ
ence:
OLS
regression
States:
SMSAs:
auxiliary
payroll
operating
payroll
241.8
(.68)
-.42
(-.94)
2.43
(38.10)
.99
47
5.45
(.08)
.12
(.70)
2.37
(68.17)
.99
172
constant
adj./?2
n
In studying the corporate organization of the manufacturing firm, some
regional analysts have recognized that diverse activities are undertaken
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
4
within firms and industries in producing a single product. Moreover, these
activities are often sited spatially apart from each other—even across state
borders and regional divisions. Industry studies by economic geographers
have documented spatial separation of activities within single corporate
entities. For example, the R & D functions of pharmaceutical firms in Great
Britain have been studied extensively. For this industry, studies report that
basic research—that of a generally applicable nature—is frequently under
taken at large centralized R & D facilities of large pharmaceutical firms
while, at the same time, specific and applied R & D is overwhelmingly con
ducted at the production plant site (Howells 1984). Meanwhile, studies of
manufacturing establishments have reflected the cumulative importance of
such establishment specialization to regions. Jusenius and Ledebur (1976)
were among the first to document specialization by the U.S. South Region
in branch plant production establishments of U.S. manufacturing firms
(1976). More recently, Malecki (1986) has distinguished regional special
ization in corporate headquarters versus branch plants across U.S. regions
for four high tech manufacturing industries: computers, semiconductors,
medical instruments, and computer software. But despite this wide recog
nition of regional specialization in diverse manufacturing activities, data
covering V A in manufacturing has continued to be distributed to U.S. re
gions according to the location of production activity alone.
III. Statistical evidence of census versus true value a d d e d
It is reasonable to expect that the Census V A is underestimated in places
such as Detroit and overestimated in Buffalo relative to the “true” (but
unknown) V A . However, the problem may be insignificant if certain con
ditions hold true. Specifically, if the proportion or split of activity between
auxiliaries and operating units is largely the same in each SM SA, then the
difference between the Census and true V A will be insignificant; i.e. oper
ating plant activity serves as a good “allocator” of total firm activity to
SM SAs and states. Accordingly, we will try to determine whether the ex
ample of Detroit and Buffalo is generally the case or whether a propor
tionate distribution of the Census and true V A can be expected.
In estimating V A as the residual between value of shipments and plant
materials of operating units, the Census is assuming that:
1. the auxiliaries have no effect on the SM SA V A or
2. the auxiliaries have the same or proportionate effect
as the operating unit.
FRB CH ICAGO W orking Paper
February 1989, W P -1 989-4
5
Table 3
E m p lo y m e n t a n d p a y r o ll in m a n u f a c t u r in g a u x ilia r ie s
fro m 1958 to 1986
Employees
Number
Payroll
Percent of
total mfg.
1,283.2
1,276.0
1,074.2
994.3
830.9
726.5
602.1
Percent of
total mfg.
(m illio n s)
(0 0 0 's )
1986
1982
1977
1972
1967
1963
1958
Dollars
7.0
6.7
5.5
5.2
4.3
4.3
3.8
48,292.9
38,220.3
21,981.2
13,772.3
8,727.9
6,615.5
4,473.7
10.7
10.1
8.3
7.9
6.6
6.6
5.7
SOURCE: U.S. Dept, of Commerce, Bureau of the Census, Census of Manufacturers
(various issues).
The first assumption can be rejected since the auxiliaries payroll comprises
a sizable part of total V A (Table 3).
The second assumption can be tested if we assume that the changes in V A
of both types of units, operating plants and auxiliary establishments, can
be approximated by changes in their respective payroll. Based on assump
tion (2), we formulate the following null hypothesis.
H 0 : the Census determined V A and true V A are the same.
The verity of this hypothesis implies that the elasticities of the V A with re
spect to auxiliaries and operating units payrolls are the same. A dollar of
either auxiliary payroll or operating payroll will contribute equally to a
region’s manufacturing VA.
This statement can be formally tested as the following regression equation:
(1)
V = c
+
b aA + b 00
where
V
= V A in logarithmic form
A = payroll for auxiliaries in logarithmic form
FRB CH ICAGO W orking Paper
February 7989, W P -1989-4
6
O = payroll for operating units in logarithmic form
Equation (2) was estimated for both SM SAs and States. There were 172
SM SAs and 46 states which disclosed auxiliary payroll. The estimated resuits are:
SMSAs:
c = 1.149
(12.3)
ba = 0.031
(2.4)
bQ = 0.941
(49.3)
adj. R 2 = 0.97
States:
c = 1.197
(9.5)
b a = 0.006
(0.3)
bQ = 0.961
(39.3)
adj. R 2 = 0.99
For SM SAs, coefficients for auxiliary and operating units payrolls are both
significant and strongly different (ba is 30 times smaller than b0). Therefore
the H 0 hypothesis is rejected. For states the rejection of the H 0 hypothesis
is even more obvious, since ba is positive and significant while ba is insig
nificantly different from zero (i.e. the hypothesis that b0 is infinitely larger
than ba cannot be rejected). Formal tests on the equality of the two coef
ficients lead to the same conclusion.4
To test the H 0 hypothesis, we had to assume that the payrolls of operating
plants and auxiliary establishments parallel their respective V A for each
state and metro area. However, if this assumption is relaxed, it is still evi
dent that the H 0 would be rejected. It is inconceivable that differences in
payroll/value added could offset the large differences between elasticities
of auxiliary and operating unit payrolls which were uncovered in the re
gression estimation.
The observed geographic distribution of auxiliary activity varies quite
widely across states and across metropolitan areas. Here are the summary
statistics for state and SM SAs in 1982:
States
auxiliary payroll/
total payroll
Standard
deviation
High
Low
.083
.080
.498
0
46
.099
.088
.534
.005
172
Mean
n
SMSAs
auxiliary payroll/
total payroll
Moreover, a cursory view of the distribution of auxiliary payroll suggests
a systematic bias across the U.S. landscape (Figure 1). States in the New
England and Middle Atlantic regions are domicile to inordinately large
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
7
numbers of auxiliary establishments. Similarly, several Northern states in
cluding Delaware, Illinois, New Jersey, Michigan, Ohio and Pennsylvania
display manufacturing sectors which are highly intensive in auxiliaries.
Meanwhile, states in the South and especially those of the East South
Central Region have a dearth, tending instead to specialize in operating
establishments. Accordingly, we would expect that, in measuring manu
facturing output data, the N orth and M idw est actually have greater levels
than currently reported while manufacturing activity in the South is overstated.
IV.
Secular a n d cyclical behavior of auxiliary activity: t w o
sources of bias
The payroll of employees at auxiliaries has been growing steadily over the
past 25 years, now accounting for almost 11 percent of the total industry
payroll in comparison to 6 percent in 1958 (see Table 3). To the extent that
auxiliary activity is skewed toward particular regions, then, long run growth
in manufacturing across regions will be biased. For example, in a region
experiencing rapid growth in auxiliary establishments, output growth will
biased downwards over time.
Distortion of output changes over the course of the business cycle can also
be demonstrated. Analysts have long puzzled over the severity of the
business cycle in manufacturing regions (Borts 1960) (Bolton 1978). In
general, they have found that, due to the sensitivity of durable goods sales
during business downturns, manufacturing regions undergo wide fluctu
ations in economic activity over the course of the business cycle.
In measuring the volatility of any region with the Census V A , cyclical
volatility will be overstated. V A is based on fluctuations in activity at op
erating plants over time. But operating or production activities will likely
be more cyclical than the manufacturing sector overall, thereby overstating
cyclical swings. This also implies that a greater intensity of auxiliary ac
tivities in a region will magnify the cyclical bias.
One hypothesized reason for heightened volatility of operating plants in
comparison to auxiliary establishments concerns widely-held beliefs about
segmented labor markets between the skilled and the highly skilled worker.
With downturns in sales, production workers are more likely to be laid off
in comparison to more highly skilled white collar workers at auxiliary fa
cilities (Williamson et. al. 1975). If employees at auxiliary establishments
acquire “ firm-specific” skills to a greater extent than production workers
at operating plants, it will be advantageous for the firm to retain auxiliary
workers even when their presence is not required by current production
FRB CH ICAGO W orking Paper
February 1989 , W P -1989-4
8
W o rk in g P a p e r
1989\ W P -1 9 8 9 -4
FRB C H IC A G O
Fe b ru a ry
P ercent of M anufacturing Payroll at A u x ilia ry E s ta b lis h m e n ts —1982
levels. If skills are firm-specific and not transferrable by the employee to
other firms, the firm must partly pay for training. Accordingly, firms will
be reluctant to lay off such workers during downturns for fear that they
will need to retrain new workers once economic conditions improve.
Evidence to this effect can be seen by regressing business cycle measures
on the percent of the nation’s manufacturing payroll or employment at
auxiliary establishments (Table 4). The business cycle effect emerges quite
clearly once the secular time trend of auxiliary employment is taken into
account. Using the change in real gross domestic product to measure the
national business cycle, it is seen that business downturns tend to raise the
share of manufacturing employment at auxiliaries. Apparently, employees
at operating establishments are “last hired-first fired’'’ in relation to em
ployees of auxiliaries.
A binary variable was also included to test the hypothesis that reporting
of auxiliary activities by establishments differs in Census years (1958, 1963,
1967...) from Annual Survey o f M a nu factu res years (1959, 1960, 1961...).
It is apparent that the self-identification of auxiliaries is consistent in this
respect.
In both the long run and the short run, the Census V A has a strong regional
bias relative to the true but unknown manufacturing output.
V. Correcting the problem: T w o A p p r o a c h e s
Since the strong statistical difference between the Census and true V A is
evident and important, the next question is whether the true V A can be
estimated with greater accuracy. Nothing short of overhauling the Census
methodology itself will settle the ultimate questions concerning the actual
geography of U.S. manufacturing in comparison to its currently reported
value. Two approaches can be identified. We will argue that one of them,
which is now in operation, is deficient while the third, which is now pro
spective, holds great promise.
The Bureau of Economic Analysis, U.S. Dept, of Commerce, attempts to
rectify the mis-apportionment of V A by manipulating aggregate regional
data with national ratios (1985). However, their methodology to do so can
only be correct under some highly stringent assumptions—assumptions
which existing evidence suggests are not valid.
As their first step, BE A multiplies each state’s V A (for a given industry)
by a national factor which nets out the V A contribution made by auxiliary
establishments. But this adjustment can only be correct if the proportion
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
10
Table 4
O L S r e g r e s s io n e q u a t io n : a u x illia r y
s h a r e o f m a n u f a c t u r in g p a y r o ll a n d e m p lo y m e n t 1 9 5 8 -8 6
Payroll
(PCTAUXP)
Employment
(PCTAUXJ)
-4.03
(-22.19)
-2.51
(-24.46)
YEAR
.0021
(22.65)
.0013
(25.01)
CHGGDP
-.046
(-1.44)
-.042
("2.31)
.001
(.77)
-.0002
(-.08)
29
29
R2
.951
.960
Durbin-Watson
1.43
1.33
Intercept
CENS YEAR
Number of Observations
G lo s s a ry o f V a r ia b le s
PCTAUXP
percent of total manufacturing payroll (all industries)
occupied by auxiliary establishments
PCTAUXJ
percent of total manufacturing employment (all industries)
occupied by auxiliary establishments
YEAR
a time trend; value equal to current year
CHGGDP
percentage growth in U.S. gross domestic product
In constant dollars (1982 =100)
CENS YEAR
a binary variable, one if census year, zero otherwise
of total V A contributed by auxiliaries is identical for each state. But this
is the problem itself! As we have demonstrated earlier in this paper, re
gional specialization in auxiliary versus operating establishments can be
quite sharp.
In a second stage of estimation, the B E A method re-allocates the nation’s
V A of auxiliaries to states, adding it back into the estimated V A of oper
ating establishments. For each industry, the method assumes that each
state or region has the same relation between auxiliary V A and auxiliary
FRB CH ICAGO W orking Paper
February 7989, W P -1989-4
11
payroll as the nation. Then the re-allocation of V A to states and regions
is performed according to the reported payrolls (of auxiliaries) o f each in
dustry in the state.
The key assumption o f this second stage, that V A can be spatially allocated
in proportion to payroll for broad industry categories, is not necessarily
erroneous. But it is an assumption that remains untested. Only an analysis
using the micro data can validate or reject the second B E A assumption.
The deficiencies of using aggregate data strongly suggest the use of Census
data at the establishment level to re-compile V A for states and regions.
One obvious but unworkable method would be to sum the factor payments
at each establishment—both operating and auxiliary establishments alike.
(V A is equivalent to the sum of factor payments including wages, rental,
capital costs, and profits.) Unfortunately, this approach must be discarded
because several individual data items on factor payments are not gathered
by the Census.
However, using existing data from the Census, the analysis can be con
ducted on the company level. The Census collects payroll and other data
on each establishment which the Enterprise Statistics Division subsequently
combines to portray a company structure. Each company can be viewed
as a unit with observation comprised of both operating and auxiliary facil
ities.
The true V A for the company (and each product) is known from
existing data (using the residual method). The remaining problem is to
apportion each company’s V A according to the contribution of each of its
establishments.
For the companies with an intricate and integrated structure, the flow of
services from auxiliary to operating units will be difficult to determine.
This problem is compounded because many operating plants are multi
product units—defined by a single industry code, yet producing products
outside that industry as well. Therefore, an auxiliary service provided to
an operating unit will have to be subdivided into as many components as
there are products produced by the operating unit. N o data series of such
detail exists to determine service correspondence between operating and
auxiliary units. However, by combining companies into an industry sam
ple set, one can estimate the relationship between auxiliary and operating
units in creating V A using econometric techniques. Finally, stepping back
once again and viewing each establishment separately, data can be re
combined once again to estimate true V A for an SM SA or state.
FRB CHICAGO W orking Paper
February 1989 ; W P -1989-4
12
VI. Conclusions: implications for regional research
A correct accounting of manufacturing output will affect the outcomes of
current regional research: the existing distribution of manufacturing in the
U.S. and the importance of manufacturing to regional economic base,
movement of manufacturing activity across regions over time, regional
productivity differences, and finally, the determination of linkages between
auxiliary services and operating units located in different regions.
To illustrate, a heated debate currently focuses on whether the nation’s
manufacturing sector has been diminishing over time while a parallel
question has been raised for the nation’s manufacturing intensive
regions—especially the Midwest (Hill and Negrey 1987) (Schnorbus and
Giese 1987). As evidenced by declining shares of employment and income,
the Midwest has undoubtedly lost a significant share o f the nation’s man
ufacturing activity. However, revised data may indicate that the losses have
been overstated. If the older industrial belt has retained auxiliary activities
even while production operation has decentralized, the method by which
V A is currently reported would have failed to notice it.
Generally speaking, regions which have witnessed a relative decline (rise)
in the share of manufacturing vis a vis other industry sectors probably are
understating (overstating) the extent that manufacturing fortunes influence
the regional economy.
Revised data may also contribute to a better understanding of the growth
process among regions. Some analysts believe that the spread of manu
facturing from the Northeast-Midwest manufacturing belt to outlying U.S.
regions has taken place within a “product cycle” process (Norton and Rees
1979).5 Historically, the Northeast-Midwest served as the nation’s innova
tive center—creating new technologically-advanced industries. Over time,
in order to economize on costs, these industries outsourced their routinized
production operations to the peripheral regions of the South and West.
Initially, growth in peripheral regions was composed o f branch plant
openings— usually production plants of firms headquartered in the North
east and Midwest Regions. A recent acceleration in manufacturing growth
in peripheral regions is seen as a reversal in regional roles; the Southwest
and West finally having reached a critical mass of technology and
infrastructure so as to spawn their own high-growth industries.
A more precise measure of output may also change conclusions of papers
devoted to the regional productivity measurement (Hulten and Schwab
1984) (Beeson 1987). While several different measures of productivity have
been examined, they all focus on a region’s manufacturing output in re-
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
13
lation to input such as labor and capital. To the extent that the observed
output trends are not reliable, conclusions regarding regional performance
and competitiveness will neither be reliable. Our data, for instance, sug
gests that productivity in a num ber o f N orth ea st and M id w estern sta tes is
understated (the numerator, V A , is underestimated) in these studies.
One of the more intractable problems in modelling regional economies has
been trying to observe the economic linkages and trade flows between re
gions in services. The interregional flow of goods can be observed from
Census o f Transportation data while the flow of services cannot. The cor
porate linkages between operating plants and auxiliaries of manufacturing
firms would fill in part of this puzzle. Accordingly, interregional inputoutput models, which attempt to examine the economic linkages across re
gions, could be specified more fully.
Estimated relationships can be
expressed in the form of export from regions with auxiliary services to re
gions with operating units. This information can be incorporated into the
multiregional input-output model, which will allow analysts to estimate the
effect of the change of the output of operating units in one region on the
auxiliary, say, employment in another region.
In a broader context, observing whether these operating-auxiliary linkages
are widening in distance over time would reflect on the question of whether,
because of enhanced transportation and communication ability, the service
sector can be thought of as an “export base” for regions.6 Over time, are
regions with specialized service sectors serving customers which are farther
apart in distance?
Footnotes
1 Another problem which we will not address in this essay concerns the fact that
this Census Bureau definition also includes the value of services purchased by the
manufacturing firm outside the company from either service firms or other man
ufacturing firms. Also, the Census does not subtract out the materials costs of
auxiliary establishments. Both of these practices lend an upward bias to the
Census concept of VA.
2 Others have taken up the possible biases in the national measures of manufac
turing output (Mishel 1988). Mishel argues that manufacturing growth has been
overstated at the national level by the BEA. This results from a failure to properly
deflate the value of intermediate components in manufacturing over time.
Foreign-source components are routinely deflated by a domestic price deflator—a
procedure which Mishel believes has understated the foreign content of domes
tically manufactured goods and concurrently overstated the value of domestic
manufacturing activity.
FRB CH ICAGO Working Paper
February 1989, W P -1989-4
14
3 With existing data collection procedures, the distinguishing of auxiliaries from
similar activities which take place at production plants is somewhat capricious.
Often, by the choice of the survey respondents, auxiliary activities which take
place at the same site as the production plant can be combined and reported with
the activities of production plant activity. In this paper, we single out auxiliary
establishments because they are most likely to be located at disparate sites from
production plants...the nature of the problem is most easily communicated by
making the auxiliary vs. non-auxiliary distinction. In much of our other work,
we will rather distinguish nonproduction activity from production activity re
gardless of whether the nonproduction activity is reported by auxiliary or by
production establishment.
4 Equation 1. can be rewritten as:
y
— c
+
b a( A
+ 0 ) + y ()0 =
c
+
b aA
+
(b a
-f yo)0
It is obvious, that the equality between two coefficients can not be rejected if y 0
is insignificantly different from zero. See Pindyck and Rubinfeld (1981). In both
cases of SMSA and states y Q had t-statistics 30 and 23 respectively.
5 In this instance, the division between VA attributable to auxiliaries vs. operating
plants for each region could be used to test for “role reversal” or changing spe
cialization of regions over time.
6 Some analysts have long maintained that regional economies can be understood
by focusing on “export base”, the key industries for which the region produces
and trades with the rest of the nation or world. Typically, the export base has
comprised manufacturing, mining, and farming although many service sectors are
now also receiving such recognition. For seminal discussions see North, (1955)
and Tiebout (1956).
References
Beeson, Patricia, “Total Factor Productivity Growth and Agglomeration Econo
mies in Manufacturing, 1959-73”, J o u r n a l o f R e g i o n a l S c i e n c e , 27 (1987),
183-199.
Bolton, Roger, “Review of Literature on Regional Econometric Models and Re
gional Business Cycles,” working paper, Williams College, Williamstown,
Mass., 1978.
Borts, George H., “ Regional Cycles of Manufacturing Employment in the United
States, 1941-1953”, J o u r n a l o f t h e A m e r i c a n S t a t i s t i c a l A s s o c i a t i o n , 55,
(1960), 151-211.
Hill, Richard Childand Cynthia Negrey, “Deindustrialization in the Great
Lakes”, U r b a n A f f a i r s Q u a r t e r l y , 22, (1987), 580-597.
Howells, J.R.L., “The Location of Research and Development: Some Observa
tions and Evidence from Britain”, R e g i o n a l S t u d i e s , 18, (1984), 13-29.
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
15
Hulten, Charles R. and Robert M. Schwab, “Regional Productivity Growth in
U.S. Manufacturing: 1951-78,” A m e r i c a n E c o n o m i c R e v i e w , 74 (1984),
152-161.
Jusenius, Carol L. and Larry C. Ledebur,
A
M y th
in
th e
M a k in g :
The
S o u th e rn
, Washington D.C., U.S.
Dept, of Commerce, Economic Development Administration, November,
1976
E c o n o m ic C h a lle n g e a n d N o r th e r n
E c o n o m ic D e c lin e
Malecki, Edward J., “Industrial Location and Corporate Organization in High
Technology Industries”, E c o n o m i c G e o g r a p h y , 61, (1985)
Mishel, Larrence R., M a n u f a c t u r i n g
Washington D.C., 1988.
N u m b ers
, Economic Policy
Institute,
North, Douglas C. , “Location Theory and Regional Economic Growth”, J o u r n a l
o f P o l i t i c a l E c o n o m y , 63, 1955.
Norton, R.D. and J. Rees “The Product Cycle and the Spatial Decentralization
of American Manufacturing”, R e g i o n a l S t u d i e s , 13, (1979), 141-151.
Pindyck, R.S. and D.L. Rubinfeld, E c o n o m
McGraw-Hill, New York, 1981.
e tric
M o d e ls
a n d E c o n o m ic
F o re ca sts,
Schnorbus, Robert H. and Alenka S. Giese, “Is the Seventh District’s Economy
Deindustrializing?”, E c o n o m i c P e r s p e c t i v e s , (1987), 3-9.
Tiebout, Charles M. , “Exports and Regional Economic Growth”,
P o l i t i c a l E c o n o m y , 64, (1956).
Jo u rn a l
o f
U.S. Department of Commerce, Bureau of the Census, A n n u a l S u r v e y o f M a n u
f a c t u r e s , 1959-62, 1964-66, 1968-71, 1973-76, 1978-81, 1983-86. Washington
D.C.: U.S. Government Printing Office, various years a.
U.S. Department of Commerce, Bureau of the Census, C e n s u s o f M a n u f a c t u r e s ,
1958, 1963, 1967, 1972, 1977, 1982. Washington D.C.: U.S. Government
Printing Office, various years b.
U.S. Department of Commerce, Bureau of Economic Analysis, E x p e r i m e n t a l E s
t i m a t e s o f G r o s s S t a t e P r o d u c t b y I n d u s t r y , Bureau of Economic Analysis
Staff Paper 42, BEA-SP85-042, U.S. Dept, of Commerce, May, 1985.
Williamson, O.E. , M.L. Wachter, and J. Harris, “Understanding the Employ
ment Relation: The Analysis of Idiosyncratic Exchange”, T h e B e l l J o u r n a l
o f E c o n o m i c s , 6 (1975), 250-278.
FRB CH ICAGO W orking Paper
February 1989, W P -1989-4
16
@FedFRASER