Census Data – Then and Now
January 24, 2013
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I hope that everyone had a relaxing holiday filled with good cheer and joy spent with friends and family. May the New Year bring you good health, happiness, and an inbox void of any correspondence from the Department of Labor!

It has been ten years since the 2000 census data was released. We have been preparing our Affirmative Action Plans (AAPs) using old data, expecting to see significant changes in the minority and female workforce representation when the 2010 data was released. So now the data is available and we are waiting to find out from the OFCCP when we have to apply the new data in our availability analyses when updating our AAPs. Obviously, there is nothing stopping you from using the most up-to-date EEO data now; however, the OFCCP typically gives contractors 12 months to implement the changes. Continue reading to find out the implications of the new data on your plans. Comparison tables have been created to evaluate the 2000 to 2010 data based on different locations and occupations.

Before delving into the data comparisons, it is important to prepare for implementing the new American Community Survey (ACS) and to know what data is available. The Equal Employment Opportunity Tabulation has been generated from the yearly ACS rather than the decennial census. This data is based on the five-year period estimate rather than a point-in-time estimate. Data was collected continuously from independent monthly samples over 60 months from January 2006 to December 2010. The complete EEO Tabulation was released late December 2012. The Disabilities Employment Tabulation (based on data from 2008 – 2010) will be released in the spring 2013.

Differences between the 2000 and 2010 census data
  • Two new variables are available – citizenship (U.S. citizen or not a U.S. citizen) and unemployment (currently employed, currently unemployed and worked in the last year; or currently unemployed and last worked one to five years ago).
  • Change in levels of geography – includes estimates and percentage of the labor force for all counties and places with 50,000 or more people.
    • National
    • All States, DC, and Puerto Rico
    • Change from Metropolitan Statistical Areas (MSA) or Primary Metropolitan Statistical Areas (PMSA) to Core Based Statistical Areas (CBSA). A CBSA can be either Metropolitan or Micropolitan areas.
    • Counties and EEO county sets.
    • Places (within States appear to be mostly cities, towns, and municipalities).
  • Provides statistics by location-based geography – residence, worksite, worksite or commuting flow.
  • Tables may include citizenship, educational attainment, industry, age, earnings, and unemployment status.
  • 488 census occupation codes based on 2010 Standard Occupational Classification. The codes and crosswalks are available at http://www.census.gov/people/io/.
  • The 2010 EEO Tabulation is available at http://factfinder2.census.gov/.

Similarities between the 2000 and 2010 census data
  • Both produce estimates on characteristics from a sample of the population.
  • Race and ethnicity information are the same.
    • Two or more races include White and Black (Black or African American), White and American Indian Alaskan Native (AIAN), White and Asian, Black and AIAN, and balance of Not Hispanic or Latino.
    • For Hawaii only – Native Hawaiian and Other Pacific Islander (NHPI) and White, NHPI and Asian, and NHPI and Asian and White.
  • Most occupation codes are similar, but some codes have changed. A zero has been added to most of the 2000 census codes.

Comparisons

Charts 1 and 2 below show the difference between the 2000 and 2010 census data in large metropolitan areas for two positions: one professional and one administrative support. Using the same occupations, Charts 3 and 4 display the difference between the census data by counties in more remote areas. Chart 5 compares the minority and female representation in management occupations in the United States. All locations and occupations were randomly selected.

Observations by Metropolitan Areas

Two positions, Computer Software Engineers and Secretaries and Administrative Assistants, were selected for comparison because one is a professional and one is an administrative support occupation. In the larger metropolitan areas identified below, the minority representation increased from 2000 to 2010 in both occupations, but female representation decreased in all locations for Computer Software Engineers and in all locations for Secretaries and Administrative Assistants, except for San Francisco.
  • For the Computer Software Engineer (Software Developers, Applications and Systems Software in 2010) occupations, the increase in minority representation ranged from 22.6% to 56.4%. The decrease in female representation in each of the four metropolitan areas was minor with decreases of less than 10% in all locations, except for 19.7% in Orlando, FL.

  • Similar minority and female representation changes occurred for the Secretaries and Administrative Assistants, with uneven growth in minority representation, ranging from a low of 5.6% in Chicago, IL to a high of 39.9% in Orlando, FL. There were insignificant decreases of less than 1% in female representation in all locations, except for San Francisco with an increase in representation by 3.1%.

Chart 1 - 2010 EEO Tabulation Table Set 1 – EEO-ALL01R (by Residence) Metro Areas compared to Census 2000 EEO Residence Data Results
Occupation Category – Computer Software Engineers (102 – 2000) Software Developers, Applications and Systems Software (0120 – 2010)
Chart 1


Chart 2 - 2010 EEO Tabulation Table Set 1 – EEO-ALL01R (by Residence) Metro Areas compared to Census 2000 EEO Residence Data Results
Occupation Category – Secretaries and Administrative Assistants (570 – 2000) - (5700 – 2010)
Chart 2


Observations by Counties

In the smaller counties identified below, the minority and female representation in the Computer Software Engineer and Secretaries and Administrative Assistants positions showed no consistent growth patterns.
  • In the four counties, minority representation increased for Computer Software Engineers in all locations except for Clay County, MN. Female representation increased slightly (less than 5.9%) in two counties and decreased in two, by 24.8% and 100%.
    • In 2000, in Clay County, MN, there were 85 computer software engineers, including nine minorities and 39 females; however, in 2010, there were only four and none of which were minority or female. I can only assume that the company that employed these technical professionals had a significant reduction in business or project work in this area.
  • For Secretaries and Administrative Assistants in the identified counties, there was an equal mix of growth and drop in minority and female representation. As was evident for Computer Software Engineers, there was a corresponding decrease (33.8%) in minority representation in Clay County, MN. The minority progress in IN and NM were minor with increases of less than 10%. Albeit high in the first place, female representation increased by less than 5% in NY and MN, decreased slightly in IN, and remained the same in NM.

Chart 3 - 2010 EEO Tabulation Table Set 1 – EEO-ALL01R (by Residence) Counties compared to Census 2000 EEO Residence Data Results
Occupation Category – Computer Software Engineers (102 – 2000) Software Developers, Applications and Systems Software (0120 – 2010)
Chart 3


Chart 4 - 2010 EEO Tabulation Table Set 1 – EEO-ALL01R (by Residence) Counties compared to Census 2000 EEO Residence Data Results
Occupation Category – Secretaries and Administrative Assistants (570 – 2000) - (5700 – 2010)
Chart 4


Observations by U.S. Totals for Management positions

In each of the identified management occupations, the minority representation increased; however, not significantly. Eight of the 10 management occupations had an increase in female representation ranging from a low of 1.5% to a high of 22.7%.
  • For minorities, the largest increase in representation occurred in the Computer and Information Systems Managers (47.2%) and Financial Managers (37.9%) occupations, followed by Construction Managers (35.3%). The smallest increase in minority representation occurred in the Human Resource Managers (11.6%) occupations.
  • Female representation decreased in the Administrative Services Managers (13.6%) and Miscellaneous Managers (28.7%) occupations. The largest increase in representation occurred in the Architectural and Engineering Managers (22.7%), Chief Executive and Legislators (18.1%), and General and Operations Managers (11.0%) positions. The smallest increase in female representation occurred in the Computer and Information Systems Managers (0.7%), Financial Managers (1.5%), and Marketing Managers (2.8%) occupations.

Chart 5 - 2010 EEO Tabulation Table Set 1 – EEO-ALL01R (by Residence) Counties compared to Census 2000 EEO Residence Data Results
Miscellaneous Management Occupations
Chart 5


Overview and Impact on Affirmative Action planning

Minority and female representation in the larger geographic locations, metropolitan areas and U.S., displayed the largest growth in minority and female representation. Across all locations, increases in minority representation were greater than that for females. The smaller counties exposed inconsistent growth and even pockets of depressed markets.

I think that everyone assumed that the minority representation in all locations would have increased significantly since 2000. However, as the small sampling of occupations and locations above indicates, that is not the case. Fears of the census data leading to new goals across all job groups may not be realistic. Companies that have had a lack of success in goal attainment may actually find an explanation for the lack of qualified minority and/or female candidates based on the 2010 statistics.

Disclaimer: The foregoing has been prepared for the general information of readers of The OFCCP Digest and is not being represented as being all-inclusive or complete. The above comparisons have been abridged from the full 2000 and 2010 census EEO tables. Analogies and assessment made in this paper are associated with the random sampling of geographic locations and occupations and may not necessarily apply to other locations and/or occupations not addressed.