employed workers, job-seekers, and labor force nonparticipants, and (2) measures of the share of overall employment consisting of various broad (or detailed) occupational categories, such as professional and technical occupations; clerical, administrative, and sales occupations; precision production, craft, and repair occupations; operators, fabricators, and laborers; service occupations; and farm occupations.
Both types of measures have strengths and limitations. Human capital variables, such as schooling or experience, measure the credentials that workers bring to the job. These measures are useful for roughly comparing education and experience requirements among various occupations, but they do not tell us why these occupations employ workers with these credentials—that is, what job tasks the workers in these occupations perform that demand the levels of educational attainment or experience that they possess.
Broad occupational categories, by contrast, provide a more precise sense of what tasks workers do on the job—for example, accountants perform bookkeeping and other quantitative and analytical reasoning tasks—but these occupational categories do not facilitate comparisons of job skill requirements across jobs. For example, how do the skill requirements of operators, fabricators, and laborers compare with those of workers in farm occupations? To answer this question rigorously requires a common metric or taxonomy that classifies occupations into their constituent task requirements. Such a taxonomy should be based on sound social science and grounded empirically in direct measurements of the job tasks, aptitudes, and duties of incumbents in each occupation.
Since its inception in 1999, O*NET has become the primary database used by labor market researchers to assess how the skill requirements of jobs in the United States have changed over the recent past and how these requirements are likely to evolve. Relative to human capital measures and occupational categories, O*NET has three key strengths for this kind of research:
It offers the only contemporaneous U.S. data source that comprehensively measures what workers in America do at their jobs. That is, to the panel’s knowledge, O*NET does not have any close substitutes or close competitors as a source of information on the content of jobs performed by the U.S. workforce.1
Two additional sources of data on job task requirements are: (1) the Skills, Technology, and Management Practices (STAMP) written and fielded by Handel (2007, 2008a, 2008b); and (2) the Princeton Data Improvement Initiative Survey (PDII), which contains a number of questions on job tasks, many of which are adapted from the STAMP (see Autor and Handel, 2009). These data sources have the virtue of offering respondent-level (rather than exclusively occupational-level) measures of job tasks. However, both STAMP and PDII are essentially