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May 2011
The most common mistake in pricing jobs by geography is using data cuts for broad metropolitan
areas, states, and geographic regions that contain locales with dissimilar pay rates. The problem
with using broad geographic areas for compensation benchmarking is that they often include a mix of
high and low paying areas and fail to capture differences between their composite local markets.
This article provides examples of how wages can vary significantly within broad geographic areas
and solutions for accurate geographic benchmarking.
Geographic Pay Zones combine national data from Geographic Locales and zip codes
with similar pay rates. They provide large geographic data cuts and are useful for organizations
that want to create geographic pay differentials. Pay Zones span the highest paying areas
[i.e., Pay Zone 1] through the lowest paying areas [i.e., Pay Zone 5].
We assign an [M] Geographic Pay Zone to Geographic Locales that contain
a “mix” of pay rates.
Click here to
learn more about terminology used in this article and U.S. geographic data cuts
in Culpepper Compensation Surveys.
Broad metropolitan areas in the U.S. are typically represented by Combined Statistical
Areas (CSAs). Combined Statistical Areas are defined by the U.S. Office of Management
and Budget (OMB) and used by the U.S. Department of Labor (DOL), Bureau of Labor
Statistics (BLS), and U.S. Census Bureau.
A CSA is a broad metro area containing multiple contiguous counties. CSAs combine adjacent geographic
areas that share both economic and social ties and a moderate degree of employment
interchange. However, CSAs were not designed for compensation analysis. A majority of CSAs
contain a “mix” of dissimilar pay rates, making them unsuitable for geographic benchmarking.
For example, the WA: Seattle-Tacoma-Olympia CSA [M] includes the following Metropolitan
Statistical Areas (MSAs) and Divisions (DIVs) across the greater Seattle metropolitan
and Puget Sound area (Figure 1):
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WA: Seattle-Tacoma MSA [M]
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WA: Seattle DIV [2]
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WA: Tacoma DIV [3]
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WA: Mount Vernon MSA [2]
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WA: Bremerton MSA [3]
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WA: Olympia MSA [4]
The problem with using the WA: Seattle-Tacoma-Olympia CSA [M] for compensation benchmarking is that
it aggregates data from locations with dissimilar pay rates.
Use the most specific and defined Geographic Locale that does not “mix” pay rates.
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Metropolitan Statistical Areas (MSAs) are smaller than affiliated CSAs and more precise for
geographic benchmarking.
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Metropolitan Divisions (DIV), located within large MSAs, provide the most precise geographic
pay rates within large metro areas.
Alternatively, you should consider using geographic zone-based regional and national data cuts that
only combine data from locations with similar pay rates. Examples:
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Northwest Region [2]: Combines data from all zip codes and locales in the Northwest with pay rates in Pay Zone 2.
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Pay Zone 2: Combines data from all zip codes, locales, and regions with pay rates in Pay Zone 2.
Almost every U.S. state with more than one Metropolitan Statistical Area (MSA) has a
mix of dissimilar pay rates.
Virginia, for example, contains a mix of pay from Pay Zone 2, Pay Zone 3, Pay Zone 4, and
Pay Zone 5 (Figure 2). Using statewide data will inflate market data for lower paying areas
(e.g., Virginia-Beach Norfolk MSA [5]) and decrease market data for higher paying areas
(e.g., Washington-Arlington and Northern VA MSAs [2]).
This is a good example of how state-level geographic data cuts typically fail to capture differences
between local markets within a state.
Use specific Geographic Locales (e.g., VA: Virginia Beach-Norfolk MSA [5]), zone-based
Geographic Regions (e.g., Northeast Middle Atlantic [5]), or
national Geographic Pay Zones (e.g., Pay Zone 5).
Similar to the problem of using state-level data, using broad regional data cuts that do not account
for dissimilar pay rates artificially lowers wage data for the highest-paying locales in the region
and inflate wage data for lower-paying locales in the region.
The Southeast region contains a mix of metropolitan statistical areas with pay rates ranging
from Pay Zone 2 through Pay Zone 5 (Figure 3). Using region-wide data for the Southeast
will inflate market data for lower paying areas (e.g., TN: Chattanooga MSA [5]) and decrease
market data for higher paying areas (e.g., GA: Atlanta MSA [3]).
Note: States in the Southeast region include: Alabama, Arkansas, Florida, Georgia, Kentucky,
Louisiana, Mississippi, South Carolina, and Tennessee.
Instead of using broad regional data cuts with a diverse mix of pay rates, Geographic Regions in
Culpepper Compensation Surveys are carefully constructed to only combine Geographic Locales
with similar pay rates.
For example, Figure 4 shows a map of the Southeast region with Geographic Locales in Pay Zone 5.
The Southwest region contains a mix of metropolitan statistical areas with pay rates across all five Geographic Pay Zones (Figure 5).
Note: States in the Southwest region include: Arizona, California, Colorado, New Mexico,
Nevada, Texas, and Utah.
The Northwest region contains a mix of metropolitan statistical areas with pay rates ranging
from Pay Zone 2 through Pay Zone 5 (Figure 6).
Note: States in the Northwest region include: Idaho, Oregon, and Washington.
The Midwest region contains a mix of metropolitan statistical areas with pay rates ranging
from Pay Zone 2 through Pay Zone 5 (Figure 7).
Note: States in the Midwest region include: Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri,
Ohio, and Wisconsin.
The Northeast/Middle Atlantic region contains a mix of metropolitan statistical areas with pay rates ranging
from Pay Zone 2 through Pay Zone 5 (Figure 8).
Note: States in the Northeast/Middle Atlantic region include: Connecticut, Delaware, Maine, Maryland,
Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont,
Virginia, West Virginia, and the District of Columbia.
The Plains region contains a mix of metropolitan statistical areas with pay rates ranging
from Pay Zone 2 through Pay Zone 5 (Figure 9).
Note: States in the Plains region include: Kansas, Montana, Nebraska, North Dakota, Oklahoma,
South Dakota, and Wyoming.
The Non-Contiguous United States, including Alaska, Hawaii, and Puerto Rico, contains a mix
of metropolitan statistical areas with pay rates in Pay Zone 1, Pay Zone 2,
Pay Zone 3 and Pay Zone 5.
In closing, compensation for specific jobs in local markets can vary and be impacted by a variety of
factors, including company size, industry sector, talent availability, cost of living, and health of
local economies.
Compensation professionals should carefully consider differences within broad geographic areas they
are benchmarking and make sure they are not mixing locations with different pay rates.
Data Source: Culpepper Operations, Technology, and Life Science Compensation Survey database.
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