Creative Class County Codes


Table of Contents


Richard Florida's Rise of the Creative Class makes a compelling argument that urban development now depends on novel combinations of knowledge and ideas, that certain occupations specialize in this task, that people in these occupations are drawn to areas providing a high quality of life, and that the essential development strategy is to create an environment that attracts and retains these workers. While developed with urban areas in mind, this thesis may be particularly relevant in rural areas, which lose much of their young talent as high school graduates leave for college, the armed forces, or "city lights."

Our analysis of recent development in rural U.S. counties, which focuses on natural amenities (for which ERS has also computed county-level scores) as quality-of-life indicators, supports the creative class thesis (see Recasting the Creative Class to Examine Growth Processes in Rural and Urban Counties  PDF icon (16x16) and The Creative Class: A Key to Rural Growth). A repetition for urban counties also shows a strong relationship between creative class presence and growth, although creative class employment plays a smaller role. However, our results depend on a recast creative class measure, which excludes from the original Florida measure many occupations with low creativity requirements and those involved primarily in services to the residential community (i.e., with numbers roughly proportional to population). Our measure conforms more closely to the concept of creative class and proves to be more highly associated with regional development than the original Florida measure.

Other work by Florida has demonstrated that a critical subset of the creative class is that comprised of fine, performing, and applied artists. His "Bohemian index"—the share of employment in arts occupations—is strongly associated with new firm formation and high-tech specialization in metropolitan areas. ERS research (see Emoting with their feet: Bohemian attraction to creative milieu 16x16 - PDF , Journal of Economic Geography, August 2007) confirms that nonmetro counties with a surplus of artists tend to have higher rates of employment growth and new firm formation. The creative class codes data file also breaks out the share of employment in the arts.

Identifying Creative Occupations Using 2000 Census Data

O*NET, a Bureau of Labor Statistics data set that describes the skills generally used in occupations, was used to identify occupations that involve a high level of "thinking creatively." This skill element is defined as "developing, designing, or creating new applications, ideas, relationships, systems, or products, including artistic contributions." See examples of occupation's O*NET skill ranking for the "thinking creatively" descriptor.

The O*NET compendium, previously known as the Dictionary of Occupational Titles, is produced by the Employment and Training Administration, U.S. Department of Labor, and provides comprehensive information on the functional requirements of more than 1,000 detailed occupations. The creativity measure provides a quantitative, though arguably imperfect, reference for assessing the creativity requirements among summary occupations that typically require a high degree of education.

Refining the Occupation Classification

Occupations were removed from consideration in the creative class measure—even if they typically required high levels of creativity—when their numbers are generally proportional to the residential population they serve (such as schoolteachers, judges, and medical doctors). Specifically, the measure excludes the summary "health care practitioners and technical occupations" group and schoolteachers and aides in the "education, training, and library" occupational group. We argue that such economic reproduction character does not disqualify college professors and "librarians, curators, and archivists" as their services are often provided to a nonresident population. Purging legal support occupations and judges while retaining lawyers might be questioned. However, the important role that lawyers play in devising solutions to new problems created by economic development is a compelling argument for their inclusion.

"Life, physical, and social science technicians" are excluded from the recast classification due to generally low requirements for creative thinking, although technicians in "architecture and engineering occupations" are retained due to higher requirements for creative thinking. This same justification for exclusion applies to "business operations specialists" and "other financial specialists" within the "business and financial operations" occupational group. Within "management occupations," "farmers and farm managers" are excluded due to low creativity requirements of farmers as reported in O*NET. However, management positions in public administration that would be appropriately excluded given the economic reproduction criterion are not separated from other management positions in the classification and so are retained. "Supervisory sales" creates a problem as many small business owners fall in this category, yet in the 2000 Census of Population, the category is mixed with other sales occupations (although not retail sales and cashiers). We have kept this larger category in the recast creative class as we are uncomfortable with excluding small business owners.

Creative class as reformulated by ERS

Occupation title    Standard Occupation Code (SOC)   
Management occupations:   
Top executives    11-1000   
Advertising, marketing, promotions, public relations, and sales managers    11-2000   
Financial managers    11-3030   
Operations specialties managers, except financial managers    11-3010, 11-3020, 11-3040 through 11-3070   
Other management occupations, except farmers and farm managers    11-9020 through 11-9190   
Business and financial operations occupations:   
Accountants and auditors    13-2011   
Computer and mathematical occupations:   
Computer specialists    15-1000   
Mathematical science occupations    15-2000   
Architecture and engineering occupations:   
Architects, surveyors, and cartographers    17-1000   
Engineers    17-2000   
Drafters, engineering, and mapping technicians    17-3000   
Life, physical, and social science occupations:   
Life and physical scientists    19-1000 and 19-2000   
Social scientists and related workers    19-3000   
Legal occupations:   
Lawyers    23-1011   
Education, training, and library occupations:   
Postsecondary teachers    25-1000   
Librarians, curators, and archivists    25-4000   
Arts, design, entertainment, sports, and media occupations:   
Art and design workers*    27-1000*   
Entertainers and performers, sports, and related workers*    27-2000*   
Media and communications workers    27-3000 and 27-4000   
Sales and related occupations:   
Sales representatives, services, wholesale and manufacturing    41-3000 and 41-4000   
Other sales and related occupations, including supervisors    41-1000 and 41-9000   
*These two categories comprise the arts occupation subset.   

Using the occupations as detailed in the table, data from the 2000 Census of Population, summary file 4 was compiled for 3,139 counties (due to small sample size there are no data for Kalawao, HI, and Loving, TX). The share of the employed population 16 years and older in these occupations represents the ERS measure of creative class.

The creative class measure was also constructed for 1990. Creative class occupations from the finest level of detail in the 2000 Census occupational data (93 occupations) were used to define the 1990 creative class, constructed from 1990 Equal Employment Opportunity special tabulation files, much more disaggregate data (512 occupations). A major change in the Standard Occupational Classification codes between 1990 and 2000 complicated the construction of comparable measures, as the 2000 occupations did not correspond to summary 1990 occupations. The majority of the codes in 2000 could be constructed from the disaggregate 1990 data, but a number of detailed 1990 occupations were distributed across creative class and non-creative class occupational codes in 2000. Conversion factors that partitioned the 1990 data to correspond with the 2000 codes were computed from the U.S. Census Bureau's Technical Paper #65 ( The Relationship Between The 1990 Census and Census 2000 Industry and Occupation Classification Systems ) for "managers and administrators, n.e.c., salaried;" "inspectors and compliance officers, except construction;" and "sales representatives, mining, manufacturing, and wholesale."

The change in the Standard Occupational Classification also affected the compilation of arts occupations as a subset of the creative class. Within the 93 detailed occupations included in the 2000 Census STF4 file, "Art and design workers" and "Entertainers and performers, sports, and related workers" are the only two categories that are not substantially co-mingled with non-arts occupations. The corresponding 1990 occupational categories are "Designers," "Painters, sculptors, craft-artists, and artist printmakers," "Photographers," and "Artists, performers, and related workers, n.e.c.," "Musicians and composers," "Actors and directors," "Dancers" and "Athletes." The 2000 aggregation does not allow purging athletes from the data series, though they comprise a minimal share of the total, nor does it allow the inclusion of authors who are co-mingled with the considerably larger number of technical writers.

These refinements resulted in an estimated creative class share of the workforce of 21 percent in 1990 (23 percent in metro areas and 14 percent in nonmetro areas) and 25 percent in 2000 (27 percent in metro and 17 percent in nonmetro).

Updating the Creative Class Codes with 2007-11 American Community Survey Data

Updating the 2000 Census creative class data with 2010 Census creative class data is not possible because the long form sent to 1 in 6 households to collect detailed data such as occupation is no longer used. Instead, the American Community Survey (ACS)—a continuous survey that samples 1 in 40 households each year—now provides the detailed data that had been collected through the long form. While this major change in data collection strategy greatly increases the timeliness of these detailed data for the nation, States, and large cities, generating reliable estimates for smaller settlements and nonmetropolitan counties requires pooling 5 years of ACS data. By pooling 5 years of data, taking into account nonresponse, we can achieve an effective sampling rate of about 1 in 11 households. Thus, the latest update provided is for pooled data collected for 2007 through 2011. 

The change from the decennial Census summary file 4 to the 5-year pooled ACS file also affected the level of detail of occupational categories that are published and made available to the public. The 93 occupations in the 2000 summary file 4 have been collapsed into 26 occupations in the publicly available ACS file which is too coarse an aggregation to construct a creative class measure that is comparable. ERS ordered a special tabulation from the Census Bureau that uses unpublished disaggregated occupational categories to replicate the 2000 creative class measure. The specification by detailed occupational category from the latest 2010 Standard Occupation Classification used in the 2007-11 ACS ( SOC Code to Census Code Crosswalk Excel icon (16x16) ) is available on the Census website, and also provided below:

Occupation 2010 Description    2010 Census Code   
Total Creative Occupations    Sum of all rows   
Total Artistic Occupations    Sum of artistic subgroups   
Chief executives and legislators    0010, 0030   
General and operations managers    0020   
Advertising and promotions managers    0040   
Marketing and sales managers    0050   
Public relations and fundraising managers    0060   
Administrative services managers    0100   
Computer and information systems managers    0110   
Financial managers    0120   
Compensation and benefits managers    0135   
Human resources managers    0136   
Training and development managers    0137   
Industrial production managers    0140   
Purchasing managers    0150   
Transportation, storage, and distribution managers    0160   
Construction managers    0220   
Education administrators    0230   
Architectural and engineering managers    0300   
Food service managers    0310   
Gaming managers    0330   
Lodging managers    0340   
Medical and health services managers    0350   
Natural sciences managers    0360   
Property, real estate, and community association managers    0410   
Social and community service managers    0420   
Emergency management directors    0425   
Miscellaneous managers, including funeral service managers and postmasters and mail superintendents    0325, 0400, 0430   
Accountants and auditors    0800   
Computer and information research scientists    1005   
Computer systems analysts    1006   
Information security analysts    1007   
Computer programmers    1010   
Software developers, applications and systems software    1020   
Web developers    1030   
Computer support specialists    1050   
Database administrators    1060   
Network and computer systems administrators    1105   
Computer network architects    1106   
Computer occupations, all other    1107   
Actuaries    1200   
Operations research analysts    1220   
Miscellaneous mathematical science occupations, including mathematicians and statisticians    1210, 1230, 1240   
Architects, except naval    1300   
Surveyors, cartographers, and photogrammetrists    1310   
Aerospace engineers    1320   
Biomedical engineers and agricultural engineers    1330, 1340   
Chemical engineers    1350   
Civil engineers    1360   
Computer hardware engineers    1400   
Electrical and electronics engineers    1410   
Environmental engineers    1420   
Industrial engineers, including health and safety    1430   
Marine engineers and naval architects    1440   
Materials engineers    1450   
Mechanical engineers    1460   
Petroleum, mining, and geological engineers, including mine safety engineers    1500, 1520   
Miscellaneous engineers, including nuclear engineers    1510, 1530   
Drafters    1540   
Engineering technicians, except drafters    1550   
Surveying and mapping technicians    1560   
Agricultural and food scientists    1600   
Biological scientists    1610   
Conservation scientists and foresters    1640   
Medical scientists and life scientists, all others    1650, 1660   
Astronomers and physicists    1700   
Atmospheric and space scientists    1710   
Chemists and materials scientists    1720   
Environmental scientists and geoscientists    1740   
Physical scientists, all other    1760   
Economists    1800   
Psychologists    1820   
Urban and regional planners    1840   
Miscellaneous social scientists, including survey researchers and sociologists    1815, 1830, 1860   
Lawyers    2100   
Postsecondary teachers    2200   
Archivists, curators, and museum technicians    2400   
Librarians    2430   
Library technicians    2440   
Artists and related workers    2600 - Artistic Subgroup   
Designers    2630 - Artistic Subgroup   
Actors    2700 - Artistic Subgroup   
Producers and directors    2710 - Artistic Subgroup   
Athletes, coaches, umpires, and related workers    2720 - Artistic Subgroup   
Dancers and choreographers    2740 - Artistic Subgroup   
Musicians, singers, and related workers    2750 - Artistic Subgroup   
Entertainers and performers, sports and related workers, all other    2760 - Artistic Subgroup   
Announcers    2800   
News analysts, reporters and correspondents    2810   
Public relations specialists    2825   
Editors    2830   
Technical writers    2840   
Writers and authors    2850   
Miscellaneous media and communication workers    2860   
Broadcast and sound engineering technicians and radio operators and media and communication equipment workers, all other    2900, 2960   
Photographers    2910   
Television, video, and motion picture camera operators and editors    2920   
First-line supervisors of retail sales workers    4700   
First-line supervisors of non-retail sales workers    4710   
Advertising sales agents    4800   
Insurance sales agents    4810   
Securities, commodities, and financial services sales agents    4820   
Travel agents    4830   
Sales representatives, services, all other    4840   
Sales representatives, wholesale and manufacturing    4850   
Models, demonstrators, and product promoters    4900   
Real estate brokers and sales agents    4920   
Sales engineers    4930   
Telemarketers    4940   
Door-to-door sales workers, news and street vendors, and related workers    4950   
Sales and related workers, all other    4965   

The major benefit accompanying the special tabulation is the provision of standard errors accompanying each creative occupation and arts occupation estimate. The standard errors provide information on the reliability of the estimate. Since the estimate is derived from a sample of the population, it might vary substantially if the size of the total sample is relatively small and if the phenomenon of interest is relative rare. For example, suppose the true share of artists is 0.01 or 1 in 100 employees in a county. If a county has 1100 total employees, then the estimate will be based on about 100 respondents. By the luck of the draw, the sample chosen for the county could contain no artists, 1 or more artists, or (improbably) all 11 artists. The standard error provides an exact statistical measure of the reliability of the estimate. This is very valuable in comparing creative or arts occupation shares between 2007-11 and 2000, as a nominal increase or decrease in share may be due solely to sampling error. Formulas for comparing estimates across time periods incorporating standard error are provided in Appendix 4 of A Compass for Understanding and Using American Community Survey Data: What Researchers Need to Know PDF icon (16x16) .

For a complete discussion of ERS research on the creative class, see Recasting the Creative Class To Examine Growth Processes in Rural and Urban Counties 16x16 - PDF , by David A. McGranahan and Timothy R. Wojan, Regional Studies Vol. 41 No. 2, pp. 197-216, April 2007.

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Last updated: Friday, July 10, 2015

For more information contact: Tim Wojan and David McGranahan

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