LOCATION QUOTIENT TECHNIQUE
Quotient Technique is the most
commonly utilized economic base analysis method. It was developed in part to
offer a slightly more complex model to the variety of analytical tools
available to economic base analysts. This technique compares the local
economy to a reference economy, in the process attempting to identify
specializations in the local economy. The location quotient technique is
based upon a calculated ratio between the local economy and the economy of
some reference unit. This ratio, called an industry "location
quotient" gives this
technique its name.
Unlike the Assumption Technique, the Location Quotient Technique does not assume
that ALL employment in each industry is Basic or Non-Basic. Instead, location
quotients are calculated for all industries to determine whether or not the
local economy has a greater share of each industry than expected when
compared to a reference economy. If an industry has a greater share than
expected of a given industry, then that "extra" industry employment
is assumed to be Basic because those jobs are above what a local economy
should have to serve local needs.
For example, suppose a local economy has
5% of its workforce in computer manufacturing and the national economy has
only 0.05% of its workforce in computer manufacturing. This technique assumes
that the local economy would have that same percentage of its workers in the
computer manufacturing industry to serve its local needs for computers. Any
employment over and above the expected percentage (in this case 0.05%) is
therefore considered to consist of basic sector jobs because these workers
are assumed to be exporting their goods and services to non-local areas. If
the percentages had been identical or if the local percentage had been lees
than the reference percentage, then the analyst would conclude that the local
area has no basic sector employment for that industry as the area can only,
at best, meet their local demand and not export these goods and services.
To calculate any location quotient the
following formula is applied. Note that in this formula we are comparing the
Regional Economy (often a county) to the National Economy. Location quotients
may also be calculated that compare the county to a state.
Industry I in Year T
Industry I in Year T
in Year T
in Year T
Examining this formula more closely, we
see that to allocate employment to the basic and non-basic sectors, location
quotients are calculated for each industry. Simply stated, the location
quotient method compares Local Employment to National Employment. The LQ
provides evidence for the existence of basic employment in a given industry.
Interpreting the Location Quotient is
very simple. Only three general outcomes are possible when calculating
location quotients. These outcomes are as follows:
LQ < 1.0
LQ = 1.0
LQ > 1.0
LQ < 1.0 = All Employment is
A LQ that is less than zero suggests that local employment is less than was
expected for a given industry. Therefore, that industry is not even meeting
local demand for a given good or service. Therefore all of this employment is
considered non-basic by definition.
A LQ = 1.0 = All Employment is Non-Basic
A LQ that is equal to zero suggests that the local employment is exactly
sufficient to meet the local demand for a given good or service. Therefore,
all of this employment is also considered non-basic because none of these
goods or services are exported to non-local areas.
A LQ > 1.0 = Some
Employment is Basic
A LQ that is greater than zero
provides evidence of basic employment for a given industry. When an LQ >
1.0, the analyst concludes that local employment is greater than expected and
it is therefore assumed that this "extra" employment is basic.
These extra jobs then must export their goods and services to non-local areas
which, by definition, makes them Basic sector employment.
When the LQ is calculated to be greater
than 1.0, it has been determined that some
of that industry's employment is Basic. However, it is must be emphasized
that a LQ > 1.0 does not mean that all that industry's employment is basic
in nature. Recall that it is assumed that any employment
"below" an LQ of 1.0 is Non-Basic; those jobs serve local demand.
Only those jobs over and above what was expected for the region can be
identified as Basic sector jobs.
Because of the assumptions of the
Location Quotient approach, a second formula must be applied to determine the
number of Basic sector jobs when the LQ is greater than 1.0. This formula is
For an example of the Location Quotient
technique applied to a single industrial sector, visit the King County-WA State LQ
Example Page. To see the technique
applied with the United States as a comparison region, visit the King County-US LQ Example
An Important Caveat: Carefully Choose Your Geographic Units
As with any of the Economic Base Methods, the
choice of your data and, more importantly, your comparison area can greatly
affect your results. As seen in the LQ example,
the use of Washington State may compromise our Industry Code 37 Basic sector
employment results. Like King County, it is likely that the entire State of
Washington has a greater than average number of Transportation Equipment
manufacturing jobs, mainly because of Boeing's existence in the State.
This greater than expected Transportation
Manufacturing Employment in the State affects the calculation of the Location
Quotient, which then has a direct effect upon the calculated number of Basic
sector jobs for this industry. In short, we may have underestimated the
number of Basic sector jobs for this industry by using the State of
Washington as our reference region; the large number of Transportation
Manufacturing jobs in King County does not appear to be that unique when
compared to the State as a whole.
Pairing the Location Quotient and Assumption Techniques
It is also important to note that the
Location Quotient Technique is often paired with the Assumption Technique to
provide a more complete set of results. Some industries can clearly and correctly
be identified as Basic and other can be identified as Non-Basic.
For example, SIC Code 70 (Hotels and
Lodging) is generally assumed to be Basic sector employment, regardless of
its calculated LQ, because this industry, by definition, largely serves a
non-local demand. Similarly, Local Government employment is always assumed to
be Non-basic because these jobs, again by definition,serve local demand. By
pairing the assumptions of these different techniques a more reasonable and
accurate assessment of the local economy is possible.
theory behind the location quotient
quotient formula and the possible results of the LQ calculation
of calculated LQ's for each industry; Assigning employment to the Basic and
calculation of Basic sector employment by industry
the Location Quotient method, especially in the choice of your reference
The use of the
Assumption Technique and the Location Technique in tandem
refinements to the Location Quotient technique (from Klosterman reading)
"The location quotient approach estimates the basic
employment in each industry by relating an industry's local employment share
to its national employment share." (Klostermann, p. 149)
rely upon comparisons between a smaller local unit (like a county) and a
larger geographic unit (like a State or the entire United States) to gain a
better understanding of local conditions. This technique is very useful
because it allows the planner to identify and interpret differences between
local conditions and regional/national conditions. In our example here, the
location quotient technique allows the local planner to identify the
strengths (the specializations) within the local economy.
the comparison between a local unit and a larger unit, a simple ratio can be
calculated. This can very quickly an easily summarize the local condition.
The specific industry location quotients do this for the local economy.
"real world" can be very messy and distinct boundaries between
regions, industries, and employment are difficult to draw, a combination of
methods or approaches is often necessary. Therefore, a good planner is one
that is willing to combine and utilize the different tools and methods at
What are the
key assumptions of this technique?
Location Quotient for an industry is determined to be greater than 1.0, is
all of that industry's employment assumed to be Basic? Why or why not?
Why is it
often best to pair the Assumption and Location Quotient Techniques?
examples of industry's (other than Hotels and Government) that are best
assessed by the Assumption Technique, regardless of their calculated Location
refinements to the LQ technique does Klosterman indicate might be used by
analysts? Why does he suggest that these refinements are necessary?
Isserman, Andrew M. 1977. "The
Location Quotient Approach for Estimating Regional Economic Impacts." Journal of the American Institute of Planners
Klosterman, Richard E. 1990. Community and Analysis Planning Techniques.
Rowmand and Littlefield Publishers, Inc. Savage, Maryland. See Chapter 10.
Klosterman, Richard E., Richard K. Brail,
and Earl G. Bossard. 1993. Spreadsheet
Models for Urban and Regional Analysis.