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Using the Census Bureau's Metropolitan Statistical Areas (MSAs) can produce misleading results
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Location is the dominant factor influencing market pay rates for most nonexecutive jobs. Culpepper and Associates’ annual analysis of technology and life science industry wages in the U.S. demonstrates the importance of considering the impact of geography on compensation.
For 2010, the geographic pay analysis of participating companies in Culpepper Compensation Surveys confirms that Silicon Valley and San Francisco in the California Bay Area continue to have the highest market wage levels in the United States. Pay rates in these technology-driven markets average 126.6 percent of the U.S. national average (see Table 1).
Other high-paying locations include Boston, Denver/Boulder, New York City, Seattle and Washington, D.C. Pay levels in these markets run about 108 percent of the national average.
One common method of analyzing pay by geography is using Metropolitan Statistical Areas (MSAs) defined by the U.S. Census Bureau. While MSAs might be popular for determining geographic pay differentials, MSAs were not designed for pay analysis and do not always provide precise geographic breakouts.
Culpepper's analysis of individual cities and large metropolitan areas across the U.S. reveals significant pay differences among locales within a number of large metro areas. Examples of some large metro areas where MSAs are inappropriate to use for geographical pay analysis include:
Examples of large metro areas where MSAs are appropriate to use for geographical pay analysis include Atlanta, Boston, Dallas/Fort Worth, Denver/Boulder and Minneapolis/St. Paul. Because the pay levels are similar for the core city and combined adjacent cities and counties, the MSA for each of these markets is suitable to use for geographic data cuts.
One of the most common mistakes in pricing jobs by geography is using data cuts for states or broad geographic regions. The problem with using broad regions is that they fail to capture differences among local markets within a state or region.
For example, using a broad geographic data cut for the Midwest region will decrease wage data artificially for the highest-paying locales in the region (Chicago, Minneapolis/St. Paul) and inflate wage data for lower-paying locales (Cincinnati, Cleveland/Akron, Detroit/Ann Arbor) and rural areas in the region.
There are three types of U.S. geographic data cuts that Culpepper has found to be effective. Each step up, from geographic locale to geographic area to pay zone, provides a larger grouping of geographic data with similar pay rates.
The Culpepper Geographic Pay Index (CGPI) is an index that measures relative pay rates of different geographic locations. CGPI scores are based on the work location and cash compensation of individual employees collected from participating companies in Culpepper Compensation Surveys. Scores are used to allocate locales with similar pay rates to larger geographic areas and pay zones.
Average Pay Rate of Work Location
U.S. National Average Pay Rate
Table 1 provides average CGPIscores for six pay zones in the United States. Each pay zone includes groupings of locales and areas with similar pay rates. The data source is the Culpepper Compensation Operations, Technology, and Life Science U.S. Surveys as of January 2010.
U.S. Market Wage Levels by Geographic Pay Zone
Geographic Area [Pay Zone]
State: Geographic Locale
Pay Zone 1. CGPI Range: 112.0%+ of National Average.
Average CGPI = 126.6% of National Average.
California Bay Area 
CA: Bay Area: San Francisco
CA: Bay Area: Silicon Valley
Pay Zone 2. CGPI Range: 106.0 to 111.9%. Average CGPI = 107.8%.
California Bay Area 
CA: Bay Area: East
CA: Bay Area: North
DC: Washington, D.C. Metro (DC-MD-VA)
NY: New York City
CA: Santa Barbara/San Luis Obispo
Non-Contiguous U.S. 
Pay Zone 3. CGPI Range: 100.0 to 105.9%. Average CGPI = 102.2%.
MN: Minneapolis/St. Paul
NJ: Atlantic City
NY: Long Island
PA: State College
NC: Research Triangle
CA: Los Angeles Metro
CA: San Diego
TX: Dallas/Fort Worth
Pay Zone 4. CGPI Range: 95.0 to 99.9%. Average CGPI = 97.6%.
MI: Detroit/Ann Arbor
MO: Kansas City (KS & MO)
CT: Bridgeport/New Haven
MA: New Bedford/Fall River
MT: Metro Areas
FL: Boca Raton/Palm Beach
FL: Lakeland-Winter Haven
FL: Port St. Lucie/Sebastian
CO: Fort Collins
UT: Salt Lake City
Non-Contiguous U.S. 
HI: Hawaii & U.S. Pacific Islands
Pay Zone 5. CGPI Range: 90.0 to 94.9%. Average CGPI = 92.2%.
IA: Cedar Rapids
IA: Des Moines
IA: Quad Cities (IA & IL)
IN: South Bend
MI: Grand Rapids
MN: St. Cloud
MO: St. Louis
VA: Norfolk/Virginia Beach
WA: Bellingham/Mount Vernon
FL: Daytona Beach/Palm Coast
FL: Fort Myers/Naples
FL: Tampa/St. Petersburg
LA: New Orleans
TN: Johnson City/Kingsport/Bristol
CO: Colorado Springs
NM: Las Cruces/White Sands
TX: San Antonio
Pay Zone 6. CGPI Range: < 90.0%. Average CGPI = 88.3%.
IN: Fort Wayne
MI: Kalamazoo/Battle Creek
MO: Columbia/Jefferson City
WI: Eau Claire
WI: Green Bay/Appleton
ID: Idaho Falls/Pocatello
OK: Oklahoma City
SD: Sioux Falls
AR: Little Rock
FL: Fort Lauderdale/Broward
LA: Baton Rouge
NC: Rocky Mount/Greenville
NV: Las Vegas
TX: Corpus Christi
TX: El Paso
Non-Contiguous U.S. 
PR: Puerto Rico & U.S. Virgin Islands
Geographic location is the prevalent factor influencing market pay rates for most nonexecutive jobs. Compensation for specific jobs in local markets can vary and can be impacted by a variety of other factors, including job level, company size, industry sector, talent availability, cost of living and health of local economies.
Culpepper and Associates conducts worldwide salary surveys and provides benchmark data for compensation and employee benefit programs.
Reposted with permission
Source: Culpepper Compensation Survey, January 2010, www.culpepper.com
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