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In recent years, the concept
of "industry cluster" has gained great currency. In his 1990
book, The Competitive Advantage of
Nations, Harvard's Michael Porter
defined and developed the concept
based on his detailed analysis of
regional economies and markets
throughout the world. In the course
of his work he noted the importance
of markets, work force skills,
suppliers, technology, infrastructure,
and other features that industries
share in common. As clusters evolve
and strengthen they develop competitive
advantages in the marketplace.
Other analysts have built on and
modified Porter's work to come up
with varying models of cluster
structure and function, but they all
share a basic trait: a holistic approach
to understanding the competitive
strengths and weaknesses of
regional economies through identification
of vertically integrated industry groups which include those firms
which sell their goods or services
outside the region, the local suppliers
and subcontractors who work
with these firms, and the economic
foundations (e.g., capital, infrastructure,
skilled workforce) which are
essential to the success of the
cluster industries.
Cluster Definition
Strictly speaking, a cluster is not
an alternative definition of an
industry. Rather a cluster represents
a group of firms, or a pronounced
geographic concentration of
"production chains" for one product
or a range of products, as well as
linked institutions that influence the
competitiveness of these concentrations
(e.g. education, infrastructure,
and research programs). A cluster
denotes an area of unusually high
and diverse industrial activity. The
steel industry in the Pittsburgh
region, the apparel industry in New York City, the machine tool industry
in the Connecticut River Valley, the
insurance industry in greater
Hartford are classic examples of
clusters.
Clusters evolve over time, often
slowly. Worldwide, they can be
found in urban areas, rural areas,
and spanning both urban and rural
areas. A salient feature of economic
clusters, at their more advanced
stages, is that their elements are
mutually supporting. Michael Porter
notes that "Once a cluster forms, the
whole group of industries becomes
mutually supporting. Benefits flow
forward, backward and horizontally."
Proximity to customers or suppliers
(called value-added chains), markets,
sources of information and technology
interact to encourage growth.
Successful cluster growth depends
on the strength and vitality of
all three components. To the extent
that one or more components is
weak, the overall competitiveness of
the cluster is diminished. Without
healthy clusters, the rest of
Connecticut's economy cannot
prosper. When clusters perform
well, other businesses, such as
restaurants and retail shops, thrive.
By selling most of their product to
customers outside the state, clusters serve as the bedrock of the Connecticut
economy.
Connecticut's Clusters
Identifying clusters is not picking
winners or losers. Connecticut's
clusters were identified based on
their importance to the Connecticut
economy--not whether they have
stronger growth prospects. Cluster
identification merely acknowledges
the dominant role of a particular
group of industries in the state's
economy, it does not connote a most
favored industry or target industry
status. In fact, some of the clusters
that have been identified have been
losing jobs for several years, making
it more imperative than ever to fully
understand the dynamics of
Connecticut's economic base industries.
Building on the 1993-94 study
carried out by the Connecticut
Economic Conference Board, the
Department of Economic and
Community Development has
updated the listing of the state's
industry clusters. Based primarily
on the "location quotient" methodology
(See "Defining a Location Quotient (LQ)" below), the initial set of
industry clusters was modified
slightly to produce the following set
of clusters:
- Telecommunications and Information
- Financial Services
- Health Services
- High Technology
- Manufacturing
- Tourism and Entertainment
Each cluster is comprised of a
number of detailed industries,
ranging from 5 in the health services
area to more than 20 in the manufacturing
cluster. Combined, the
clusters account for more than 45
percent of state output and around
40 percent of state employment.
These industries represent the top
layer of the cluster pyramid described
above. Work is currently
underway to identify the linkage
industries and to carry out a detailed
analysis of the comparative performance
of each of the detailed industries
comprising the clusters.
Just as economies and industries
grow and change over time, so too will our list of clusters. The concept
of an industry cluster is, by its very
nature, dynamic...one which constantly
evolves to respond to the
challenges and opportunities of
market forces, technological innovations
and shifts in consumer and
business demand.
The identification of clusters is
just the first step in an ongoing
process to develop strong, competitive
industries in Connecticut. The
next step involves setting up of
industry cluster councils, volunteers
who will work with their peers and
with representatives of the public
sector to identify and improve those
factors which may be affecting
Connecticut's economic competitiveness.
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The first step in identifying the industries which comprise any cluster was to determine those which are in the
economic base or traded-sector; that is, the industries that are selling goods and services to national and
international markets as opposed to those that are producing for local consumption. A commonly used method
for identifying economic base industries involves the calculation of a location quotient.
A location quotient (LQ) is a process which compares the concentration of an industry at a regional level to the
concentration of the same industry at the national level. The LQ formula is:
LQ = % of CT employment in industry I divided by % of United States employment in industry I.
A location quotient greater than 1.0 indicates that the industry is more dominant in the state economy than it
is nationally. Although LQ's are an imperfect tool for describing a regional economy and estimating exports, they
are widely used because they are inexpensive, reflect indirect imports, and apply to both goods and services. All
employment above the level necessary to set an industry's LQ equal to 1.0 can be considered export employment.
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(Portions of this article are drawn from the
following sources:
Industrial Strength Strategies, Stuart A.
Rosenfeld, Aspen Institute, 1995 and
Understanding State Economies through
Industry Studies, John M. Redman, CGPA,
1994.
The Connecticut Department
of Economic and Community
Development announced that
Connecticut communities authorized
710 new housing units in
August 1996, a 7.1 percent
decrease compared to July 1996
when 764 were authorized.
The Department further indicated
that the 710 units permitted
in August 1996 represent a
decrease of 20.1 percent from the
889 units permitted in August
1995, and that the year-to-date
numbers are down 13.2 percent,
from 5,706 in 1995 to 4,955 in
1996.
Reports from municipal officials
throughout the state indicate that Litchfield County showed the
greatest percentage increase in
August compared to August 1995:
39.2 percent. New Haven County
reported the greatest percentage
decline: 45.6 percent.
New Haven County documented
the largest number of new, authorized
units in August with 160.
Fairfield County followed with 149
units and Hartford County had
143 units. Shelton led all Connecticut
communities with 28
units, followed by Trumbull with
21 and Southbury with 18.
The permit activity figure for
August included the following
statewide amounts by structure
type: detached single-family units, 645; attached single-family
units, 55; two unit structures,
2; three and four unit structures,
3; structures containing
five or more units, 5.
Year-to-date totals indicate
that Hartford County has issued
the most building permits
through the first eight months
of 1996 with 1,154, followed by
New Haven County with 1,018,
and Fairfield County with 991.
Southington authorized 137
new units during this period,
followed by Rocky Hill with 125,
Shelton with 122, and
Wallingford with 118.
It is well-known that a major
cost of doing business is the
cost of labor. Not so widely known
is that there are data available
that measure the change in labor
costs. Developed in the early
1970's by the United States Department of
Labor's Bureau of Labor Statistics
(BLS), the Employment Cost Index
(ECI) provides a timely, accurate,
and comprehensive indicator of
change in the cost of labor, and
can be a helpful tool for businesses,
planners, and policy
makers. Among the data that are
available are measures of the
change in wages and salaries, and
in employer costs for employee
benefits, as well as the change in
total compensation costs.
For purposes of the Employment Cost Index,
wages and salaries are defined
as the hourly straight-time wage
rate or, for workers not paid on
an hourly basis, straight-time
earnings divided by the corresponding
hours. Employee
benefits covered by the Employment Cost Index are:
paid leave; supplemental pay
(e.g., overtime); insurance
benefits; retirement and savings
benefits; legally required benefits
(e.g., social security,
Federal and State unemployment
insurance, workers' compensation);
and other benefits (e.g.,
severance pay). Total compensation
costs are the aggregate of
wages and salaries and employee
benefits.
The Employment Cost Index provides an array of
data for the national civilian
economy. This includes both the
total private economy and the
public sector-excluding farms,
households, and the Federal
government. Data are also developed
for regions of the country
(Northeast, South, Midwest, and
West). Connecticut is part of the
Northeast Region which includes
the New England states, New York,
New Jersey and Pennsylvania.
However, regional data is limited to
information on total compensation
costs and wage and salary costs,
and is available only for private industry workers.
Each quarter, data are collected
for the pay period including the
12th day of the survey months of
March, June, September, and
December. Nearly 21,000 occupations
within about 4,100 sample
establishments in private industry
and nearly 6,000 occupations
within about 900 sample establishments
in State and local governments
are surveyed. Within an
establishment, spEmployment Cost Indexfic job categories
are selected to represent
broader occupational definitions.
Beginning with the March 1990
Employment Cost Index release, indexes were rebased
to June 1989=100. Starting with
the December 1990 Employment Cost Index release, seasonally adjusted data became
available for selected Employment Cost Index reports.
Seasonal adjustment removes the
effects of events that follow a more
or less regular pattern each year
making nonseasonal patterns
easier to spot.
As a further benefit to the user
of the data, Employment Cost Index information is
available by industry, occupation,
and union/non-union affiliation.
The following is a sampling of the
information found in the Employment Cost Index for
June 1996.
The June 1996 Employment Cost Index level for all
civilian workers in the nation, at
129.2, was 2.9 percent higher than
in June 1995. Wage and salary
costs rose 3.2 percent over the
year, while benefit costs rose 1.8
percent.
For private industry workers
nationally, total compensation
costs increased 2.9 percent, but
wages and salaries increased 3.4
percent over the year ending June
1996, up from 2.9 percent for the
June 1994-June 1995 period.
This was the largest 12-month
increase since March 1992. By
comparison, total compensation
costs in the Northeast increased
more slowly, 2.4 percent. The
region's wage and salary costs
increased by 3.2 percent during
this period. Benefit costs increased
1.7 percent, compared with a 2.6
percent increase for the 1994-95
period, reflecting slower rising
costs for health benefits, unemployment
insurance and workers'
compensation.
Total compensation costs in
service-producing industries
increased 3.0 percent compared
with 2.7 percent for goodsproducing
industries. Wages
and salaries increased 3.5
percent in service-producing
industries, compared with 3.0
percent in goods-producing
industries. In contrast, benefit
increases were larger for goodsproducing
industries (2.0
percent), than for serviceproducing
industries (1.6
percent).
Compensation costs for whitecollar
workers increased 3.0
percent compared with 2.6 percent
for blue-collar workers and 2.0
percent for service occupations.
Among the major occupational
groups, sales occupations had the
largest increase, at 3.7 percent,
while machine operators, assemblers,
and inspectors had the
smallest increase, at 1.9 percent.
Compensation cost gains over
the year ending June 1996 were
higher for union workers (3.1
percent) than for non-union
workers (2.8 percent). This pattern
held for the service-producing
industries (3.7 percent for union
and 2.8 percent for non-union),
but not for goods-producing
industries (2.5 percent for union
and 2.8 percent for non-union).
(extracted from United States Bureau of Labor Statistics reports)
Connecticut's coincident
employment index moved,
once again, to its highest level in
the current recovery with the
release of the (preliminary) July
data, having not fallen on a
month-to-month basis since
December 1995. The leading
index, however, fell somewhat from
its peak during June.
The coincident index, a gauge
of current employment activity,
rose slightly in July, continuing
the strong upward movement that
emerged in 1996. The 1996 experience
follows weak upward movement
in the coincident index in the
early phases of the current recovery.
The bottom line? The economy
continues to motor ahead.
The leading index, a barometer
of future employment activity, has
bounced around considerably
during 1996. It reached its highest
level in the current expansion in
June. Thus, the decline in the
index this month is not too surprising.
The crucial issue is
whether the trend is up or down
over the next several months.
The 1996 debate has waxed and waned over whether the
national economy is overheating.
The Federal Reserve has received
intense scrutiny by so-called "Fed"
watchers. At this writing, the Fed
chose not to boost short-term
interest rates in September, even
though many had called for a hike.
Fed Chair Greenspan wants to nip
any inflation bud before it can
bloom. The question, at the moment,
is if and when the Fed
should unsheathe the pruning
shears.
Whatever the Fed does or does
not do affects the Connecticut
economy. National events filter into
our economy with some lag.
Unfortunately, our recovery from
the most recent Great Recession
was delayed and weaker than
normal. Our recovery only picked
up its pace in 1996. Thus, the
latest action (inaction) by the Fed
was welcomed news in Connecticut.
The party may not yet be over.
The coincident employment
index rose from 83.0 in July 1995
to 88.3 in July 1996. All four index
components continued to point in
a positive direction on a year-overyear
basis with higher nonfarm
employment, higher total employment,
a lower total unemployment
rate, and a lower insured unemployment
rate.
The leading employment index
rose from 86.1 in July 1995 to
88.2 in July 1996, or somewhat
below its previous peak of June
1996. All five index components
sent positive signals on a yearover-
year basis with a higher
average work week of manufacturing
production workers, lower
initial claims for unemployment
insurance, higher Hartford help
wanted advertising, a lower shortduration
(less than 15 weeks)
unemployment rate, and higher
total housing permits.
Source: Connecticut Center for Economic Analysis, University of Connecticut. Developed by Pami Dua [(203) 322-3466,
Stamford Campus (on leave)] and Stephen M. Miller [(860) 486-3853, Storrs Campus]. Tara Blois [(860) 486-4752, Storrs
Campus] provided research support.
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