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REGIONAL ECON OM IC ISSUES
W orking P ap er S e r ie s
Metro Area Growth from 1976 to 1985:
Theory and Evidence
William A Testa
.
FEDERAL RESERVE B A N K
OF CHICAGO
WP- 1989/1
M e t r o
T h e o ry
A r e a
G ro w th
a n d
fro m
1 9 7 6
to
1985:
E v id e n c e
William A. Testa*
Over the past 15 years, the process of regional change has been most un
favorable to regions in the Midwest. In particular, the economy of the
eastern part o f the Midwest—the East North Central Region (encompassing
Ohio Indiana, Michigan, Illinois, and Wisconsin) has steadily declined.
This region’s share of national employment fell from 20 percent to 17 per
cent between 1972 and 1987. While the West North Central has fared
somewhat better, agriculturally-oriented states such as Iowa and Nebraska,
have generally paralleled the decline observed in the Midwest’s industrial
belt.
In response to lagging job opportunities in the Midwest, policymakers have
put much effort into development programs intended to ignite robust eco
nomic growth in the Midwest or, at least, to maintain the existing job base.
This study is intended to help shape these programs by identifying the
forces o f regional change, thereby suggesting more effective policy levers to
stem the region’s decline.
T h e o r i e s o f r e g io n a l c h a n g e
In identifying potential policy levers, several economic theories explaining
regional growth differences have been forwarded. In summary, it is prob
ably safe to say that none of them have proven to be universal in explaining
the U.S. experience. However, elements of all of them are consistent with
the experiences of particular regions during particular time periods. In
brief, the following theoretical frameworks are most prevalent in explaining
the U.S. regional experience in recent decades.
Neoclassical Theory: In its most basic form, this set of ideas considers
factors of production—especially labor and capital—to be mobile across re
gions. Labor will move to regions where real wage rates are highest. In
*The author is Senior Economist at the Federal Reserve Bank of Chicago. The views and
findings herein do not necessarily reflect the views of management of the Federal Reserve Bank.
He thanks Joseph Crews, Alenka S. Giese and Natalie A. Davila for their research assistance
and Stephanie Boykin for manuscript preparation.
FRB CH ICAG O W orking Paper—January 1989
1
turn, capital will flow to regions of highest return. Under the most com
mon assumption of one commodity which is produced by the same tech
nology in all regions, differences in factor returns are determined by
regional differences in endowments of labor and capital. So long as factor
returns such as wages differ across regions, this theory would predict that
labor will migrate to high wage regions of capital abundancy while capital
would flow to low-wage regions o f labor abundancy.1
In examining the U.S. growth experience, this neoclassical growth mech
anism has been related to the migration of the Southern poor to the facto
ries o f the North during the 1950s and 1960s in search of high wages. Also,
the strong capital investment observed in the South during the 1950s, 1960s,
and 1970s can be partly attributed to low wages in that region. In general,
the per capita income convergence observed across U.S. regions in this
century has been related to neoclassical mechanisms.
Export-Base Theory recognizes that regions will specialize in certain indus
try products for reasons which are difficult to specify including historical
accident, favorable location with respect to transport, endowment of a
unique factor o f production, or increasing returns to scale of an industry
or group of industries. These industry products or services of specialization
form the “economic base” of the region and these goods are traded rather
than nontraded. Export base theory posits that a region’s growth in em
ployment and income can be best understood in terms of changes in de
mand for the region’s traded goods by the rest of the world and nation or
changes in competitive position which influence the quantity demanded.
Empirically, divergences in regional growth can often be understood by a
region’s mix of industries. In recent years, for example, the nation’s in
creasing proclivity for foreign autos and domestic defense expenditure
would be key features in explaining the relative decline in Michigan’s
economy and the relative rise in the coastal economies.
Product Cycle Theory suggests that industries and their attendant products
undergo distinct stages or phases of a “life cycle” beginning with an inno
vative stage.
A t this initial stage, factor costs are of little relevance.
Rather, specialized factor inputs such as entrepreneurial and innovative
personnel, specialized business services, access to suppliers, access to
emerging technological advances and ideas, and specialized financial ser
vices are critical. A t the initial innovative stages and later in the early
growth phases, the process technology of the industry cannot be transferred
to another location.
But later, as the process of production becomes
standardized, the industry can become mobile in seeking locations where
production costs are lowest. Because regions will maintain advantages in
different factor costs, production will be spun out to low cost regions or
even overseas. Examples from the U.S. experience have been the textile
industry’s exodus from New England to the South Atlantic states and
FRB CH ICAGO W orking Paper—January 1989
2
overseas. More recently, the production segment of the U.S. computer and
the semiconductor industry has reportedly moved along the product cycle
in such a fashion.
While regions generally share the same fate as their industries, the recent
New England experience has shown that a developed region’s capacity to
innovate is not so permanently and easily eroded by the passing o f a single
set o f industries through a product cycle. The technological legacy of a
once-developed region may become the wellspring of a new set of indus
tries. This observation has led others to assert that regions undergo waves
or cycles o f growth and development.2
In other respects, the product cycle theory is not sufficiently developed to
be useful as a predictive theory of regional growth. N o t all industries pro
ceed through a product cycle (Malecki 1985) and evidence is lacking as to
which industries the product cycle applies. Moreover, once a region has
experienced decline (as its major industries move out through a product
cycle), no guidance is offered on the conditions under which these regions
will rejuvenate or if they will do so at all.
Industrial Location Theory suggests that any regional growth theory must
be reconciled with the micro decisions of each individual firm. In market
economies, firms are thought to maximize their own profits (and minimize
costs) in making capital investment decisions, including location alterna
tives. In turn, firm location and expansion decisions accompany employ
ment opportunities for a mobile labor force.
While it is recognized that different types of firms respond to particular
factor costs and conditions, the basic set of locational cost conditions can
be generalized to include access to inputs and markets, labor, energy,
transport, construction and lease costs, and those myriad services, regu
lations, and costs which are often influenced by state and local govern
ments. These costs, including tax levels and structure, service provision,
environmental regulation, fiscal inducements and financial subsidies, and
labor insurance, are often included under the popular rubric of “ business
climate” . Business climate factors are often the focus of state/local officials
because these factors can be influenced via the state/local government
process or in partnership with the private sector.
In addition to cost oriented features, a separate set of growth factors can
be included under the rubric business climate. State and local governments
have become active in business promotion. Prominent examples of such
“demand side” policies are export or trade missions overseas; lobbying the
federal government for a more favorable federal funds flow or identifying
early procurement contract opportunities for regional industries; and “buy
local” programs to increase the home demand for the region’s products.
FRB CH ICAGO W orking Paper—January 1989
3
E m p i r i c a l s tu d ie s a s a f r a m e w o r k
Within the body of empirical literature, the econometric specifications of
regional growth range from purely ad h oc or intuitive empirical equations
which are loosely based market frameworks (Plaut & Pluta 1983;
Wasylenko 1984; Browne et al 1980; Kieschick 1981; et, al.) to carefully
developed foundations based on micro theory of firm location behavior,
specific functional forms, and statistical models (Carlton 1979; Hodge 1981;
Crihfield 1985; Bartik 1985). Nonetheless, the functional forms that are
ultimately used for statistical estimation often end up being very similar.
The dependent variable, or what the analyst is trying to explain, is usually
measured by either the growth rate in output or the growth rates of the
factor inputs o f labor and capital across regions.3 Regional variation in
growth rates are then “explained” by such factors as wages, energy costs,
state-local taxes, labor climate, access to markets, climate, and an everexpanding host o f measures.
One characteristic of much empirical work has been to assume that regions
are slow to equilibrate differences in cost factors.
This means that
“ static” specifications of the empirical models have been generally dis
carded (i.e., an equation that would explain levels of employment based on
concurrent levels of wages and other factors). Rather, one-term changes in
the dependent variable are hypothesized to be chiefly determined by be
ginning period differences in factor costs (Wheat 1973, 1987; Plaut and
Pluta 1983; Wasylenko 1984). Beginning-period regional cost differences
are represented, for example, by relative wages, unionization levels, taxes,
energy costs, and the like. Most studies assume that these cost differences
are persistent and fairly constant thoughout the subsequent period of
growth. While one can easily imagine that growth would additionally be
determined by concurrent changes in factor costs (Plaut & Pluta), such
considerations are usually neglected because of a scarcity of data observa
tions.4
A recent innovation in this literature recognizes the simultaneous equations
bias in those formulations which use “change in employment” as the de
pendent variable. The theoretical underpinning suggests that these specifi
cations are measuring the regional derived demand for labor and, in turn,
the demand for labor depends on relative wages. But if so, then the wage
is simultaneously determined with local supply of labor so that inclusion
of wages in the single-equation estimation will yield inconsistent parameter
estimates.5 As a result, some studies have used more appropriate statistical
techniques such as instrumental variables to correct for simultaneous
equations bias (Crihfield 1985; Papke 1984).6
FRB CH ICAGO W orking Paper—January 1989
4
Similar to much o f the existing literature, we estimate a “disequilibrium”
model where economic performance (or growth) across SM SAs (Standard
Metropolitan Statistical Areas) can be observed to adjust to initial period
relative factor costs. While our empirical specifications are largely ad hoc,
(i.e. the equations will not follow directly from a formal model using spe
cific functional forms of a production function), the general form of our
equations are similar to those grounded in economic theory (Engle 1974;
Crihfield 1985; Papke 1984).
The econometric specification chosen is in linear form; percentage change
in employment is a linear function of beginning period levels of input costs
(C) and other growth factors (OTH). Each metro area accounts for one
observation so that the database can be considered as cross-sectional rather
than time-series.
P C H E M P i = a + bCi + c(077Z}) + e{
The linear form rather than log-linear is chosen insofar as some observa
tions of employment change are negative, particularly for the manufactur
ing industry. Accordingly, the logarithm o f these observations cannot be
calculated. N o other functional forms were attempted.
In an alternative specification, output growth substitutes for employment
growth as the dependent variable.
Output is measured by percentage
change in value added in manufacturing-value added measuring the sum
o f factor payments which is, in practice, roughly equivalent to the value of
manufacturing output less purchased inputs.
The employment growth
equations represent labor demand equations for a region. Theory suggests
that we attempt some statistical techniques to account for the simultanity
bias in these employment equations. In fact, corrections for these consid
erations have been made. However, the results reported here are of the
ordinary least squares variety. It is noted that our results are robust with
respect to estimating methods.7
The observations are drawn from the 75 largest SM SAs (Appendix I).
SM SAs are economic regions having a common pool of labor, common
statewide regulations, and common resources. While these areas have been
criticized as economic units due to their proximity to other urban areas with
which they are closely entwined, metro areas are more reasonable as econ
omies than either counties, cities, or states—other geographic units for
which data for important variables are available.
The analysis was conducted for large industry categories: total employ
ment, manufacturing and nonmanufacturing employment, and also manu
facturing output. Owing to regional differences in business cycle timing
and severity, a period of some length is required to capture secular growth
FRB CH ICAGO W orking Paper—January 1989
5
trend differences. Growth in employment was measured in percentages for
the 1976-85 period from C ou n ty Business P atterns data. Unfortunately,
manufacturing output for metro areas has not been reported since 1982, so
tills six-year time period is regrettably short. The 9-year period can be
considered sufficient to capture the effects of regional cost differences on
regional growth trends. A period that is too long may violate the assump
tion that observed regional cost differences are constant over the period of
study. Some analysts have used longer periods (Crihfield 1984; Wheat
1973, 1986) and others have used shorter periods (Plaut and Pluta 1983 and
Wasylenko 1984).
S t a tis tic a l r e s u lts
The equations reported in Tables 1 and 2 are ordinary least squares esti
mates where the dependent variable is expressed in percentage change from
the beginning year to the endpoint year. The equations were checked for
the common cross-sectional data problems o f multicollinearity and
heteroskedasticity.8
The overall statistical results explain much of the variation in metro area
growth over the 1976-85 period. “Explained variations” of between .4 and
.5 are reported for the employment equations. These statistics are sub
stantial for cross-sectional type analysis. In comparison, the manufacturing
output equation does not perform as well, exhibiting an R 2 slightly under
.3. This may be due to the shorter time period for which output data is
available. Leonard Wheat (1986) has criticized Plaut and Pluta (1983) and
others for using a short time period for this type of model because “cyclical
effects, strikes, random spurts, and other short-run anomalies overshadow
long-run trends” .
The equations reported were arrived at from experimentation and
iteration—there is no pretense that these are the outcomes of single “roll
of the dice” as set forth from a structural model. A cross-section database
was constructed covering many potential factors of importance which were
gleaned from existing studies. In the course of this process, considerable
care was taken in choosing and constructing variables that were thought to
measure the concept that theory would suggest had an influence on regional
growth differences.
Some variables were ultimately dropped because
collinearity between independent variables degraded the estimates of re
maining coefficients. (See Table 3 for correlation coefficients of all the re
tained variables.) In clear cases of bivariate collinearity, the variable that
was retained had the greatest economic content and the most straightfor
ward interpretation. For example, unionization variables were dropped in
favor o f wages.
FRB CH ICAGO W orking Paper— January 1989
6
Table 1
O L S reg ressio n equatio n:
Em p lo ym en t and output g ro w th in m an u factu rin g
Percent change in
manufacturing employment
(1976 to 1985)
Percent change in
manufacturing output
(1976 to 1982)
1.04**
(3.34)
Labor Costs
(WM76MFG)
.95**
(2.27)
-0.15**
(-2.76)
Intercept
-.18**
(-2.45)
-130.35*
(-3.72)
-149.11*
(-3.22)
Access to Technology
(TECH)
.04
(1.13)
.07
(1-36)
Defense Spending
Per Capita (DOD)
.0001
(1.21)
-.00002
(-.14)
Educational Expenditure
Per Pupil (EDEXP)
.0002*
(1-78)
.0001
(60)
Tax Growth
Per Capita (CHTX)
-.003**
(-2.06)
-.0001
(-.07)
Unemployment
Insurance (UIMAN)
-21.95
(-1.84)
Market Maturity
(MARKET)
Export
Orientation (XMFGEMP)
R2
2.88
(-18)
.03**
(2.27)
.03*
(1.71)
.44
.29
‘ Significant at the 10 percent level.
“ Significant at the 5 percent level.
FRB CH ICAGO W orking Paper—lanuary 1989
7
Table 2
O L S reg ressio n equation:
To tal and n o n m an u factu rin g em ploym ent g ro w th 1976 to 1985
percent change in
total employment
percent change in
nonmanufacturing employment
1.01**
(5.63)
1.03**
(6.15)
Labor Costs
(WM76MFG)
-0.007**
(-3.71)
-0.007**
(-4.02)
Market Maturity
(MARKET)
-91.66**
(-3.73)
-52.40**
(-2.27)
Access to Technology
(TECH)
0.04
(1.52)
0.03
(1.29)
Defense Spending
Per Capita (DOD)
0.0002**
(2.31)
0.00002**
(2.29)
Educational Expenditure
Per Pupil (EDEXP)
0.0001 *
(1.76)
0.0001 *
(1.84)
Intercept
Tax Growth
Per Capita (CHTX)
-0.002**
(-2.28)
R2
0.48
-0.0001 **
(-2.22)
0.41
‘ Significant at the 10 percent level.
“ Significant at the 5 percent level.
FRB CH ICAGO W orking Paper—january 1989
8
Table 3
C orrelation m atrix
(2)
(3)
(5)
(6)
(8)
(9)
-0.11
-0.54
0.43
-0.12
-0.51
0.40
-0.45
-0.49
0.40
0.05
0.39
0.01
-0.11
1.00
(4)
(7)
(10)
(13)
(12)
1.00
-0.38
-0.35
-0.29
0.65
-0.41
-0.39
-0.13
1.00
-0.34
-0.24
0.01
1.00
0.73
-0.10
1.00
-0.10
1.00
3. PCNM
4. PCVA
0.68
0.67
5. WM76MFG
6. UPLTW
7. CHTX
8. MARKET
9. DOD
-0.04
0.32
0.14
-0.04
0.33
0.41
0.03
0.13
-0.03
0.32
0.25
0.07
0.14
0.08
0.22
0.26
0.33
0.22
0.17
0.46
0.30
0.47
0.17
-0.24
0.03
0.00
-0.39
-0.29
-0.30
0.02
0.10
0.01
0.04
0.12
0.39
0.05
0.34
0.27
0.47
0.19
0.19
0.39
1.00
0.85
0.05
1.00
0.98
1.00
2. PCMFG
-0.41
0.08
1.00
0.92
(11)
0.14
1.00
d)
1.00
1. PCTOT
0.17
10. EDEXP
11. TECH
12. UIMAN
10
.0
13. XMFGEMP
Glossary of variables in regression equations
CHTX
Percent change in per capita state and local taxes from fiscal 1976-77 to fiscal 1984-85
EDEXP
Education expenditure per pupil in A.D.A. 1976-77
DOD
Per capita procurement and payroll by the Department of Defense in 1977
MARKET
Ratio of value added (in $ millions) in manufacturing to population in the metro area
TECH
Total number of scientists and engineers engaged in research and development per
1,000 of the population, 1974
UPLTW
Index of average hourly earnings of unskilled plantworkers, 1975-76
WM76MFG
Average hourly wages, all manufacturing industries, 1976
XM FG EM P
Percent of total m anufacturing em ploym ent related to exports, 1 9 7 6
PCMFG
Percent change in manufacturing employment, 1976-1985
PCTOT
Percent change in total employment, 1976-1985
PCNM
Percent change in non-manufacturing employment, 1976-1985
PCVA
Percent change in value added in manufacturing, 1976-1982
UIMAN
Average statewide unemployment insurance rate (as a fraction of total wages) for 1975,
1976, and 1977 in the manufacturing sector
FRB CH ICAGO W orking Paper—January 1989
9
D i s c u s s i o n o f fin d in g s
An interpretation and discussion of the regression coefficients is presented
below.
L a b o r co sts
Labor costs are invariably considered in statistical studies of growth. This
is not surprising since labor costs comprise a large share of production
costs. For example, manufacturers paid out 48 percent of value added to
employee compensation in 1984. This share is possibly higher for service
industries which tend to be more labor intensive than manufacturing. Sig
nificant regional wage differences have been widely observed by researchers
(See A C IR 1980 for a review) even though wages have displayed some
convergence over the course of the century. Moreover, a significant body
of research finds no real regional wage differences once education and ex
perience of workers is taken into account (Dickie and Gerking 1987).
Opinions remain somewhat divided on the importance of wage differences
on regional growth disparities but evidence strongly suggests that wages do
matter. The heavy weighting of labor-related costs in business climate
rankings indicates that the popular wisdom equates high wage rates with
poor business climate. For example, the Grant-Thornton annual M a n u
fa ctu rin g C lim ates S tudy (1988) assigns over 40 percent of its factor weights
to labor costs—and this excludes labor productivity and availability indica
tors. Econometric studies beginning with Victor Fuchs (1962) have impli
cated wages as affecting manufacturing employment growth across regions.
Leonard Wheat’s analysis stands out as a well-known study rejecting the
importance of wage differences. However, his study does report a state’s
degree of unionization as highly significant (see also Bartik 1985) and these
two variables are highly correlated in his study (rho = .73), as well as in
our own study. Roger Schmenner’s extensive interview studies of manu
facturing branch plant decisions identified labor-related costs as very im
portant (1982).
The estimations in Tables 1-2 report labor costs to be highly significant
over the study period. As calculated in elasticity form (at the mean values
of observations), employment growth was most responsive to labor costs
for both the manufacturing and nonmanufacturing sectors (Table 4). The
labor cost measures in the estimating equations represent the costs of
hourly workers rather than salaried professionals. This suggests that the
attraction of locations in the South for low-cost routinized production op
erations, such as branch plants and production facilities of mature indus
tries, continues to be a major force in regional growth disparities into the
1980s.
FRB CH ICAGO W orking Paper— January 1989
10
Table 4
P o in t e la s t ic it ie s o f g r o w t h f a c t o r s
(as evaluated at the mean)
Manufacturing
employment
Nonmanufacturing
employment
Labor Cost
4.9
Labor Cost
1.4
Educational
Spending
4.4
Educational
Spending
.5
Markets
1.9
Markets
.3
Tax Growth
1.4
Tax Growth
.3
Unemployment
Insurance Tax
1.4
Defense
Spending
.1
Export
Orientation
1.1
Technology*
Access
.1
Technology*
Access
.5
Defense Spending*
Per Capita
.3
*The underlying coefficient is not statistically significant at the 10 percent level
using a two-tailed test.
FRB CH ICAGO W orking Paper— January 1989
11
M a rk ets
By market influence, we mean the relative balance in the beginning period
between the demand for goods (and services) and the supply (Wheat 1986).
Strong demand relative to accessible supply will exert a market pull to at
tract suppliers to a more proximate location to the metro area.
In Leonard Wheat’s recent study, a local market variable is constructed
based on a state’s ratio of personal income to manufacturing employment
(and also on distance to the manufacturing belt) as a proxy for demand to
supply imbalance. Unlike the approach of Plaut and Pluta (1983), who
weight these two market components of supply and demand by their dis
tance from each and every state, Wheat asserts that it is local
demand/supply rather than national market pull that exerts the most in
fluence on growth.
Following Wheat, and after some experimentation with both approaches,
we also settle on a variation of the “local market pull” , using manufactur
ing value added per metro area resident as our market measure. Although
the point elasticity of the market variable ranks only third among growth
factors (Table 4), the market variable enters first in a stepwise regression
equation. One cannot decompose the explained variation in the regression
attributable to each variable. However, the market variable, when entered
alone, accounts for approximately one-half of the explained variance of the
overall regression. N o other variable (alone) performs in this fashion so
that, at an intuitive level, it appears that regional differences in market pull
accounted for much of the interregional differences in growth over the
sample period.
As a matter o f conjecture, the market variable is thought to account for two
distinct influences
in the equations.
First,
enhancements in
transportation—especially the advent of cheap and fast truck transport over
the course of this century—is thought to have magnified the market pull of
populous regions such as the South (Chinitz and Vernon 1960). With rail
as the dominant mode of shipment, the relative costs of long haul shipments
from the core manufacturing belt was fairly low compared with short haul
transport. This is because, with rail transport, terminal costs are fairly
high. With truck transport, terminal costs are much lower so that short
haul transport from factory to market compares more favorably with long
haul transport. As a result, the coming of interstate truck transport greatly
enhanced the attractiveness of building branch manufacturing plants closer
to the markets of final destination. This implies that, regardless of any
migration of people to the South and West in this century, strong forces
of market pull have been exerted because of changing transport technology
and investment in infrastructure (highway).
FRB CH ICAGO W orking Paper—January 1989
12
A second influence behind market pull has been the migration of people to
warmer climates which has accompanied the rising incomes of retirees and
the attraction o f population to the resource-rich Western states. Some
studies such as Wheat’s have accounted for these two influences separately.
In the current study, our sole market variable, value added per capita, is
pulling double duty.
It must also be noted that the two influences are simultaneous; growth in
supply attracts population growth in search of jobs which, in turn, further
enhances market pull. Some analysts have modelled this process as a si
multaneous system of job and population growth (Steinnes 1984).
U n e m p l o y m e n t in s u r a n c e ta x e s
State-by-state differences in unemployment insurance systems greatly con
cern many business groups and state chambers of commerce. This is espe
cially so for those industry groups, such as construction and manufacturing,
which tend to pay higher-than-average U I rates. The employment volatility
of these industries is usually reflected in higher tax rates because state tax
rates are “experience rated”—based on the unemployment history o f indi
vidual firms. Accordingly, U I tax rates will often comprise a higher frac
tion o f wage costs for firms in manufacturing and other plant-type
industries.
Concern over unemployment insurance costs are expressed by manufactur
ers in the Grant-Thomton annual study of manufacturing climates. Input
into this business climate ranking is provided by 36 associations represent
ing manufacturers around the country. In the 1988 edition of the study,
average benefits per covered worker are given a weight of 5.1 percent of the
overall index and the net worth of the state unemployment insurance trust
fund is weighted at 4.6 percent.
Few statistical studies of regional growth differences consider U I tax rates.
A statistical study by Roger W. Schmenner (1987) and others’ using an hi
erarchical or two-stage sequential approach, examines the plant location
decisions of 114 branch plant openings by Fortune 500 manufacturing firms
during the 1970s.
In the model, the unemployment insurance tax rate is
measured by average unemployment compensation benefits paid per em
ployed worker. This is a fairly cost-relevent measure reflecting current plus
expected U I system liabilities to employers. However, little evidence is
found in the Schmenner study that U I costs are influential in the decision
to open branch manufacturing plants.
FRB CH ICAGO W orking Paper— January 1989
13
Using employment data from 1973 to 1980, a study by Michael Wasylenko
investigates the factors surrounding differences in growth among the 48
states on the U.S. mainland (1984). Major industry sectors under consid
eration include manufacturing, transportation, administrative and auxiliary
employment, wholesale trade, retail trade, services, finance-insurance-realestate, and total (employment). The measure of unemployment insurance
is reported to be dropped from inclusion in the final results with no expla
nation. Presumably, the variable displayed a perverse sign or collinearity
with another variable(s). It should be noted that the particular measure
of unemployment burden on employers, which is the average benefit paid
to a worker receiving benefits, is not well chosen. A state with very gener
ous benefits could burden firms very slightly if that state is experiencing
high growth and low unemployment. This would tend to lessen the popu
lation of unemployed workers and hence concomitant tax rates.
A 1985 study by Timothy Bartik examines how corporate location decisions
for new branch plants (using the same database as Roger Schmenner) are
influenced by unionization, taxes, and other characteristics of states. The
study results show no detrimental impact of high state U I tax rates on plant
location. In fact, the sign o f the U I variable is unexpectedly positive for
one of the reported estimating equations.
In contrast to these existing studies, our results indicate that U I taxes neg
atively influence employment growth over the 1976-85 period.
These
findings hold true for the manufacturing sector where, because the tax rates
are often higher, one would most expect that high tax rates deter employ
ment expansion.
Unlike those measures used in the previous studies, our measure of the UI
tax burden is industry-specific and mirrors the employer’s cost perspective.
Still, this variable merits further investigation in that it is probably suscep
tible to simultaneous bias. Slow growth causes high U I tax rates. While
we account for this by choosing beginning period values of U I tax, the
causation we measure could be reversed to the extent that growth in a re
gion is serially correlated from one period to the next (i.e. slow growth in
the prior period accounts for high initial values of U I tax rates which, in
turn, are correlated with slow growth over the subsequent period of study).
O r ie n ta tio n to m a n u fa c tu r e d e x p o r ts
Throughout the 1970s, and peaking in 1980, the international trade share
of U.S. output climbed steadily upward—imports and exports alike (Hervey
1986). Subsequently, merchandise exports fell off rapidly under the weight
o f a rising dollar and significant import penetration. As a percent of
FRB CH ICAGO W orking Paper—January 1989
14
GNP-output, merchandise exports had fallen to roughly the same level by
1984 as they had been in 1976.
In addition to their importance to the nation’s economy, manufacturing
exports have been demonstrated to greatly effect job generation in state
economies. A t least two studies have documented a significant relationship
between a state economy’s export orientation and economic growth
(Crihfield 1985; Manrique 1987).
It is not surprising, then, that state policies have placed greater resources
in recent years into stimulating state exports abroad. For example, one
analyst reports that between 1976 and 1980 alone, the number o f overseas
offices maintained by state governments tripled (Posner 1981). A t least one
study has uncovered a link between state export promotion activity and
actual state export activity (Coughlin and Cartwright 1987). In our model,
metro area export orientation is measured by the percent of an area’s
manufacturing employment directly related to exports in 1976. The coef
ficient on this variable is found to be statistically significant in both the
manufacturing employment equation and in the manufacturing output
equation.
Consequently, the role of exports in state economic growth
merits some attention as a factor that can be influenced by state and local
policy.
A c c e s s t o t e c h n o lo g y
The high tech boom of the late 1970s and early 1980s furthered public
awareness o f the importance o f technology to regional development. Those
flourishing regional economies which we know so well in California and
Massachusetts serve as a frequent reminder that a region’s technological
base (and institutions) are important to economic growth—even to the ex
tent that new industries can arise from the infrastructure legacy of longdeparted manufacturing industries. Technological factors are now
recognized in business climate studies. The recent Ameritrust/SRI “ Indica
tors of Economic Activity” lists nine measures o f regional technological
capacity. The importance of technology in regional economic revival has
even been noted overseas: “Places in America where modern manufactur
ing has taken root and grown fastest tend to have three things in common:
a handful of firms strong in one particular field; technical expertise on tap
at a nearby engineering school or big government laboratory; and imag
inative local bankers and investors” .9
To date, the importance of technology access to regional growth remains
anecdotal rather than statistical (Markusen and Hall 1985; Sirbu et al 1976;
Office o f Technology Assessment 1984). However, the strength of the re
cent regional growth success stories, along with the well-documented his-
FRB CH ICAGO W orking Paper—January 1989
15
tones o f the importance o f technology in their success, suggests that metro
area accessibility to technology through joint ventures with universities and
government labs, private consulting with university faculty, and interaction
among industrial R & D facilities should possibly be included in future sta
tistical studies.
In attempting to measure a metro area’s access to technology, comprehen
sive and condensable measures are not plentiful. A special survey con
ducted by the National Science Foundation for 1974 reported on the
number of scientists and engineers who are actually engaged in research and
development activity by metro area. The coefficient of this measure proved
to be quite robust over the course of alternative estimating equations.
While the coefficients are not significant as reported in Tables 1-2, the co
efficient sign remains consistently positive across industry sectors.
However, while the presence of R & D activities can be measured, individual
program initiatives that attempt to accelerate technological transfer from
lab to market are not accounted for in these measures. Measurement re
finements which account for public policy influence may yield more (or less)
significant results.
S t a t e -lo c a l ta x e s a n d s p e n d in g
“ ...relative growth in manufacturing employment from 1939 to 1953
has not been highest where per capita state and local tax collections are
lowest...
...relative growth in manufacturing employment from 1939 to 1953
has not been highest where increases in per capita state and local tax col
lections have been held lowest...”
Clark C. Bloom— 1956
“ ...an inverse relationship exists between changes in state relative tax
burdens and state relative economic growth...” Robert J. Genetski— 1983
“ ...economic growth varies inversely with the burden of state and local
government taxes; the fastest growing states, by and large, are states with
relatively low tax rates....Even more important, changes in tax burden are
strongly inversely related to economic growth...” Richard K. Vedder— 1981
The above passages exemplify the long-standing debate over the role of
state-local taxes (and spending) in economic growth. Evidence and argu
ment are as diametrically opposed today as 30 years ago. It would not be
difficult to unearth one hundred or more statistical studies with the evi
dence weighing significantly on either side.
Despite the apparent conflict in the literature, we know more than the body
of conclusions from these studies suggests. A look at the problems inherent
FRB CH ICAGO W orking Paper—January 1989
16
in answering the question “do taxes matter?” helps to understand the con
flicting results which have emerged.
Many statistical studies, such as the ones cited above, perform only simple,
one-by-one correlations between tax levels and economic growth. Because
there are many influences on differential regional growth (and more im
portant ones as well), the impact, if any, of tax levels or tax growth on re
gional economic growth will be seriously distorted by such methods.
However, it is not only statistical technique that has given rise to the con
flicting evidence in the literature, but also the complexity of the question
and the fact that taxes are not the primary determinant of regional growth
differences. State and local taxes are usually a small fraction of total costs.
Estimates of 3-4 percent of total costs are common. For this reason, some
major research efforts have felt justified in neglecting taxation altogether
in statistical studies (Fuchs 1962).
However, some researchers have recently argued that, while taxes are in
deed a small part of total costs, differences in taxes are larger relative to
profits and thus they do influence relative rates of return to capital (and
profit) by location (Papke 1984). Measurements of “ business taxes relative
to business income” (Wheaton 1983) have also been shown to be larger
than the taxes-to-total-cost measurements which were often cited in earlier
studies (Cornia, Testa, Stocker 1978).
Subsequently, researchers have
carefully measured tax rates as they influence the price o f capital and they
have entered them into statistical forms intended to explain location of
capital investment. A t least one study found that, in using this careful
measure (and correcting for simultaneous equation bias), location of in
vestment expenditures is significantly related to the after-tax return on a
marginal investment (Papke 1984).
A second reason why tax levels are not thought to be important, and where
statistical studies err, is that higher levels of taxation are frequently associ
ated with higher levels of spending for services which, in turn, benefit
businesses directly (e.g. highways and sanitation) or indirectly by enhancing
quality of life (e.g. education and recreation) and thereby lower the level
of wages necessary to compensate the workforce (Hoehn, Berger, and
Blomquist 1987). As a result, it is not surprising to find some studies re
porting that tax levels enhance economic growth rather than exert a fiscal
drag (Romans and Subrahmanyam 1979; Plaut and Pluta 1983).
In considering that public services can have value, one would also expect
businesses to value certain types of services more than others. This has been
accounted for in empirical studies by including variables to measure the
composition of state-local government expenditures (Plaut & Pluta 1983;
Newman 1983; Romans and Subrahmanyan 1979; Wasylenko 1984; Helms
1985). The idea here is that highway and education and infrastructure
FRB CH ICAGO W orking Paper—January 1989
17
spending will more significantly benefit business than welfare spending and
recreation. By accounting for these spending patterns in the estimating
equation, the influence of tax levels can presumably be measured more ac
curately.
A third reason for the conflicting evidence on the tax-growth relation, and
one which has gained recent popularity in tandem with federal tax reform,
is that state and local tax structures are important rather than simply tax
levels. Accordingly, studies focusing on tax levels alone will tend to be
mis-specified. Some analysts contend that these differences in tax structure
differ by region so as to cause differences in economic growth across re
gions (Vedder 1981; Wasylenko 1984). Tax structure differences must then
be accounted for in statistical studies which have, in fact, included variables
such as the marginal corporate income tax rate (Kieschnick 1981) and the
percentage of revenue raised from individual income taxes (Waslyenko
1984).
The statistical results reported in Table 1-2 show that tax growth is signif
icantly related to regional growth. One interpretation is that those metro
areas that were not able to hold their initial tax burdens in check ultimately
paid a price in terms of lower subsequent growth.
This result is very close to those results reported by others who have cor
related personal income growth by state along with the growth in “taxes
per $1000 of personal income” (Genetski 1982; Vedder 1981). The latter
studies have found strong negative correlations between personal income
growth and measured growth in tax burden. However, such results have
been strongly criticized as displaying reverse casualty. Over relatively short
time periods, such as the length of a business cycle or less, one would find
that slow-growing regions might necessarily experience increasing tax ef
fort. As income falls, public expenditure needs fall less rapidly, driving up
the tax rate. But such an observation hardly implies a direction of causality
from tax burden to growth.
In deference to these criticisms of the existing tax growth literature, statelocal taxes were measured on a per capita basis in the estimations presented
here. A region experiencing economic decline would not experience the
dramatic short term drop in population (so much as income) so that there
would not tend to be an automatic increase in tax burden in response to
lagging growth. For this reason, we believe our results to be more mean
ingful than those others, such as Wasylenko (1984), which have measured
tax burden using income-type measures in the denominator. In alternative
and unreported specifications, the best available measures of tax burden
levels were also entered into the empirical work including A C I R s measure
of tax burden and William Wheaton’s careful measurements of business
tax/business income. That tax levels did not turn out to be a significant
FRB CH ICAGO W orking Paper—January 1989
18
variable in our estimations is a bit difficult to explain, (although Michael
Wasylenko reports a similar result in his recent examination o f state eco
nomic growth). The most straightforward explanation is that differences
in taxes reflect monies needed to pay for regional differences in demand for
local public goods. If so, variables reflecting regional differences in taste
would need to be included if tax levels were to display significant coeffi
cients.
Other studies have found that the composition o f public spending also af
fects economic growth. For example, Romans and Subrahmanyam report
that transfer payments per dollar of state income are negatively related to
growth. Michael Wasylenko reports education spending as a fraction of
state income to be positively correlated with growth. We part slightly with
Waslyenko by specifying the educational spending (elementary and sec
ondary) variable more closely to service output—i.e. educational spending
per pupil. Similar to Wasylenko’s recent analysis o f state economic growth,
we find that the education coefficient has been positive and significant in
accounting for metro area growth.1
0
F e d e r a l s p e n d in g
The search for explanations of differential rates o f regional growth fre
quently leads to the uneven geographic incidence of federal spending across
the U.S. landscape. An extensive study by the Advisory Commission on
Intergovernmental Relations (1980) documents the markedly changing in
cidence o f federal spending away from Midwest and toward the South and
West over the period from 1952 up through the mid-1970s. Coupled with
a strong growth in the level of federal spending in the post-WW II era, the
federal government is often accredited or blamed for an implicit industrial
targeting that favors the Sunbelt (Markusen 1986).
Among major categories of federal spending, defense spending grew most
rapidly during the period of study; the defense budget growth has out
stripped G N P growth in every year from 1978 to 1986. Moreover, defense
outlays occupied almost 28 percent of federal government outlays in 1986.
For these reasons, we chose per capita outlays by the Dept, of Defense as
an important measure of federal spending incidence in metro areas.
This component of the federal budget was found to exert a positive and
significant impact on employment growth over the 1976 to 1985 period.
Whether or not such job gains were offset or augmented by other federal
spending and regulatory programs cannot be answered with our limited
data set.
FRB CH ICAGO W orking Paper—January 1989
19
C o n c l u s i o n s a n d p o li c y im p lic a t io n s
Using metro area economies as observations, a cross-sectional study of
growth over the 1976 to 1985 period is able to identify several key elements
that account for regional growth differences in recent years. Regional dif
ferences in wages and education exert strong hypothetical point impacts on
metro area growth. Meanwhile, in terms of actual impacts on growth over
the 1976-85 period, regional differences in market pull were highly influen
tial.
Among policy variables that can be manipulated by state and local offi
cials; unemployment insurance, tax growth, educational spending, a state’s
propensity to exports overseas, and technology can be listed as potentially
important. However, several significant influences, including wages and the
market pull of developing regions, will be more difficult for slow-growing
regions to manipulate. These factors can possibly be maneuvered by tighter
reins on alternative policy instruments.
For example, educational im
provement can potentially improve labor productivity, thereby offsetting
labor cost disadvantages in some regions.
F o o tn o te s
1 Results of the theorem are modified under differing assumptions about factor
mobility, transport costs, differences in technology, and multifactor production.
2 See Douglas E. Booth, “Regional Long Waves and Urban Policy,” Urban
Studies. Vol. 24 No. 6, December 1987, pp. 447-459.
3 In the bibliography, see references to Crihfield, Steinnes, Fuchs, Borts and Stein,
Papke, Wasylenko, Kieschnick, Plaut and Pluta, Wheat, ACIR, Kahley, Newman,
and Browne. One exception remains—the work of Carlton who formulates a sta
tistical model using conditional logit analysis on the probability of firm birth and
expansion in any given region (Carlton 1979). Similarly, other studies have bor
rowed this basic framework and have estimated it using more refined statistical
specifications (Bartik 1985).
4 One exception is Crihfield (1985) who had a sufficient number of data observa
tions to include both the initial period level of relative costs along with changing
relative costs.
5 It is more accurate to say that most empirical work purportedly measures shifts
over time in demand for labor and supply of output.
FRB CH ICAG O W orking Paper—January 1989
20
Equations explaining output per se do not suffer from this simultaneous equations
bias because the price of output (i.e. demand for output facing a single small re
gion) can be assumed to be fixed for a small region selling to a national or inter
national market.
6 Using the instrumental variables approach, John Crihfield used six to seven
variables to identify labor demand (i.e. to shift the supply of labor), depending
on the specification chosen. The variables included state income taxes as a frac
tion of state personal income, local prices as reflected in housing rents, local
government expenditures as a fraction of local personal income, state government
expenditures as a fraction of state personal income, nominal social security pay
ment in the locality, the local unemployment rate, and local real wages in 1960.
Leslie Papke chose the unemployment rate and the percent of workforce
unionized to create an instrument for wages in that study (1984).
7 Instruments for wages were constructed using tax effort, unionization, unem
ployment insurance system generosity, and unemployment rate (see Appendix II).
8 In such cases, like the present, where the size of the observations varies mark
edly, there may be reason to suspect some heteroskedascity in the error terms.
Accordingly, the residuals were plotted against the population of the SMS A in
1976. No heteroskedasticity was evident. Bartlett’s test was performed over the
top and bottom one-third of this ranked sample. The hypothesis that the error
variances were equal could not be rejected at the 5 percent significance level.
As in all cross-sectional samples, multicollinearity lowers the efficiency of the
parameter estimates. As seen by the correlation coefficients of the independent
variables, bivariate collinearity does not appear to be a severe problem. In addi
tion, analysis of the type practiced by Belsley-Kuh-Welsch suggested that severe
collinearity was not present in the reported equations.
9 Automation Alley: “Rust bowls can regain their shine by playing to their in
dustrial strengths,” Economist , April 11-17, 1987.
1 The educational spending per pupil variable has been criticized as measuring a
0
single input among many in the production of education rather than an output
of education. Unfortunately, output variables are difficult to measure. In this
study, the percent of the adult population with at least a high school education
was attempted as a replacement for educational spending. These latter results
were consistent with the results reported herein.
FRB CH ICAGO W orking Paper— January 1989
21
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H istorica l P ersp ective , Washington, D.C., June, 1980.
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Estimates o f the Effects o f Unionization, Taxes, and Other Charac
teristics of States” , Journal o f Business and E con om ic Statistics Jan.
1985, pp. 14-22.
Belsley, David A., Edwin Kuh, and Roy E. Welsch, R egression D iagn ostics ,
John Wiley & Sons, New York, 1980.
Bloom, C. C., S ta te and L o ca l T a x D ifferentials and the L ocation o f M a n
ufacturing, Studies in Business and Economics, Bureau of Business
and Economic Research, University of Iowa, No. 5, 1956.
Borts, George H. and Jerome L. Stein, E con om ic G row th in a F ree M a rk e t,
Columbia University Press, New York, 1964.
Brown, Lynn E., et. al., “ Regional Investment Patterns,” N ew England
E co n o m ic R ev iew , Federal Reserve Bank of Boston, July/Aug. 1980,
pp. 5-23.
Carlton, Dennis W., “Why New Firms Locate Where They Do:
An
Econometric M odel” Interregional M o v e m e n ts and R egion al G row th ,
pp.
13-50.
William
C.
Wheaton
ed.,
The
Urban
Institute,
Washington, D.C., 1979.
Carlton, Dennis W., “The Location and Employment Choices of New
Firms:
An Econometric Model With Discrete and Continuous
Endogenous Variables,” The R eview o f E con om ics and S tatistics , Vol.
65 (August 1983), pp. 440-444.
Chinitz, Benjamin, and Raymond Vernon, “Changing Forces in Industrial
Location,” H arvard Business R ev iew , Vol. 38, 1960 pp. 126-136.
Cornia, Gary C., William A. Testa and Frederick D. Stocker, S ta te-L o ca l
Fiscal Incentives and E con om ic D evelo p m en t , The Academy for Con
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Coughlin, Cletus C. and Phillip A. Cartwright, “An Examination of State
Foreign Export Promotion and Manufacturing Exports,” Journal o f
R eg ion a l S cien ce, Vol. 27, No. 3, pp. 439-450.
Crihfield, John, A n E m pirical A n a lysis o f R egion a l D em a n d and Sup p ly
F unctions, Ph.D. Dissertation, University o f Chicago, Chicago, IL
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Dickie, Mark, and Shelby Gerking, “Interregional Wage Differentials: An
Equilibrium Perspective,4 Journal o f R egion al S cien ce, Vol. 27, No.
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Engle, Robert F., “A Disequilibrium Model of Regional Investment,”
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1 9 2 9 , Yale University Press, New Haven, C T , 1962.
Genetski, Robert J. and Lynn Ludlow, “The Impact of State and Local
Taxes on Economic Growth,” H arris E con om ics, December 17, 1982,
pp. 1-15.
Grant Thornton, M anu factu rin g C lim ates S tu d y , Grant Thornton, Chicago,
1988.
Hall, Peter, and Ann R. Markusen, “High Technology and Regional-Urban
Policy,” in Peter Hall and Ann Markusen eds., Silicon Lanscapes,
Allen R. Unwin Inc., Winchester, M A , 1985.
Helms, L. Jay, “The Effect of State and Local Taxes on Economic Growth:
A Time-Series Cross-Section Approach,” The R eview o f E con om ics
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Hervey, Jack L., “The Internationalization of Uncle Sam” , E con om ic P e r
spectives, Federal Reserve Bank of Chicago, Vol. X, No. 3, May/June
1986, pp. 3-14.
Hodge, James H., “A Study of Regional Investment Decisions” in J.
Vernon Henderson ed., R esearch in Urban E con om ic, JAI Press, 1981,
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Hoehn, John P., Mark C. Berger, and Glenn C. Blomquist, “A Hedonic
Model of Interregional Wages, Rents, and Amenity Values,” Journal
o f R eg ion a l S cien ce, November 1987, pp. 605-620.
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Kahley, William J., C om parative A dvantage and S tate E m p loym en t C h ange,
Working Paper 86-2, Federal Reserve Bank of Atlanta, Jan. 1986.
Kieschnick, Michael, T a x es and G row th : Business Incentives and E con om ic
D e v elo p m en t, Council o f State Planning Agencies, Washington, D.C.,
1981.
Malecki, Edward J., “Industrial Location and Corporate Organization In
High Tech Industries,” E con om ic G eorg a p h y, October, 1985.
Manrique, Gabriel G, “ Foreign Export Orientation and Regional Growth
in the U.S.,” G row th and C h an ge, Winter 1987, pp. 1-12.
Markusen, Ann, “Defense Spending and the Geography o f High Tech In
dustries,” in John Rees ed., T ech n olog y, R egion s, and P o licy, Rowman
& Littlefield, Totowa, N.J., 1986.
Newman, Robert J., “Industry Migration and Growth in the South” , R e
view o f E con om ics and Statistics, 65, 1983, pp. 76-86.
Olson, Mancur, The R ise and D eclin e o f N a tion s , Yale University Press,
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Papke, James A., and Leslie E. Papke, M ea su rin g D ifferential S ta te -L o ca l
T a x Liabilities and Their Im plications F o r Business Investm ent and
P lant L oca tion , Center for Tax Policy Studies, Purdue University,
West Lafayette, IN, 1986.
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ing Activity: New Evidence” in Indiana's R evenue S tructure: M a jo r
C om p on en ts and Issu ed P art II, James A. Papke ed., Center for Tax
Policy Studies, West Lafayette, IN, 1984, pp. 115-130.
Plaut, T. R., and J. E. Pluta, “ Business Climate, Taxes and Expenditures,
and State Industrial Growth in the U.S.,” Southern E con om ic Journal
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B usiness Topics, vol. 28, Summer, pp. 43-49.
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o f a Technology Oriented Com plex: Lessons fro m N orth American and
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FRB CH ICAGO W orking Paper—January 1989
25
Appendix I
Metropolitan areas included in the statistical analysis
(ranked by 1976 SMSA population)
1976 SMSA
Population
1976 SMSA
Population
New York
Chicago
Los Angeles
Philadelphia
Detroit
Boston
Oakland (w/S.F.)
San Francisco (w/Oak.)
Washington, D.C.
Dallas (w/Ft. Worth)
Fort Worth (w/Dallas)
Houston
St. Louis
Pittsburgh
Baltimore
Minneapolis
Newark
Cleveland
Atlanta
Columbus
Anaheim
San Diego
Miami
Denver
Seattle
Milwaukee
Tampa-St. Petersburg
Cincinnati
Buffalo
Kansas City
Riverside
Phoenix
San Jose
Indianapolis
New Orleans
Portland
Hartford
San Antonio
9,605,000
7,003,800
6,981,500
4,784,500
4,414,500
3,930,400
3,156,400
3,156,400
3,056,500
2,603,400
2,603,400
2,389,900
2,367,300
2,313,800
2,144,100
2,042,300
1,990,000
1,955,200
1,849,300
1,806,600
1,776,000
1,655,900
1,465,400
1,442,400
1,431,500
1,428,500
1,427,100
1,379,100
1,322,400
1,290,300
1,262,900
1,257,300
1,210,100
1,156,800
1,117,000
1,103,600
1,059,900
993,600
FRB CH ICAGO W orking Paper—January 1989
Rochester
Sacramento
Louisville
Fort Lauderdale
Memphis
Providence
Dayton
Salt Lake City
Birmingham
Albany
Norfolk
Toledo
Greensboro
Oklahoma City
Nashville
Jacksonville
Akron
Syracuse
Scranton
Gary-Hammond
Allentown
Charlotte
Orlando
Tulsa
Richmond
Omaha
Jersey City
Grand Rapids
Greenville
Raleigh-Durham
West Palm Beach
Tucson
Fresno
Oxnard-Ventura
Knoxville
Harrisburg
Austin
978,700
902,960
895,300
886,300
880,500
862,500
835,200
802,500
802,300
799,700
787,300
782,100
776,200
772,900
769,700
716,100
663,900
648,000
643,600
635,900
627,500
605,800
601,400
596,300
596,100
579,800
579,700
567,000
534,700
483,700
480,500
467,300
460,800
459,500
443,200
432,600
410,800
26
Appendix II
In stru m en tal va ria b le s reg ressio n equ atio n :
Em ploym ent and o u tp u t g ro w th in m an u factu rin g
Percent change in
manufacturing employment
(1976 to 1985)
Percent change in
manufacturing output
(1976 to 1982)
Intercept
1.12**
(2.94)
1.26**
(2.46)
Labor costs
(W M 7 6 M FG )
-.1 7 * *
(2.10)
- .24**
( 2.03)
Market maturity
(M A R K ET )
A ccess to technology
(T EC H )
137.7**
(3.88)
-1 5 3 .4 **
( 3.26)
.04
(-91)
.07
(1.30)
Defense spending
per capita (D O D )
.0002
(1.34)
.00001
( .0 7 )
Educational expenditure
per pupil (ED EX P )
.0002
(1.37)
.0005
( 28)
Tax growth
per capita (C H TX )
- .0 0 2
(1.43)
.0007
( 44)
Unemployment
insurance (U IM A N )
Export
orientation (X M FG EM P )
R2
- 1 4 .9
(- 1 .8 4 )
.03**
(2.14)
.41
11.16
(67)
.03
(1.51)
.28
‘ Significant at the 10 percent level.
“ Significant at the 5 percent level.
FRB CHICAGO Working Paper—lanuary 1989
27
Appendix II (cont'd)
In stru m e n ta l v a ria b le s r e g re ssio n e q u a tio n :
T o ta l an d n o n m a n u fa c tu rin g e m p lo y m e n t g r o w th 1976 to 1985
Percent change in
total employment
Percent change in
nonmanufacturing employment
1.10**
(5.67)
1.10**
(5.97)
Labor costs
(W M 76M FG )
-0 .0 0 8 **
( - 3 .6 3 )
-0 .0 0 7 **
( - 3 .4 8 )
Market maturity
(M A R K ET)
-9 7 .8 1 **
( - 4 .0 5 )
-6 2 .9 2 **
(- 2 .7 5 )
A ccess to technology
(T EC H )
0.04
(1.59)
0.03
(1.33)
Defense spending
per capita (D O D )
0.0002**
(2.36)
0.00002**
(2.37)
Educational expenditure
per pupil (ED EX P )
0.0002*
(1.81)
0.0001 *
(1.84)
Intercept
Tax growth
per capita (C H TX )
R2
-0.001 *
(- 1 .7 5 )
-0 .0 0 0 1 *
( - 1 .6 4 )
0.47
0.38
‘ Significant at the 10 percent level.
“ Significant at the 5 percent level.
NOTE: The wage variable is created as an instrument by regressing unemployment rate, tax
burden, Ul generosity, and unionization on the wage index, UPLTW and WM76MF6.
FRB CHICAGO Working Paper—January 1989
28
@FedFRASER