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Recent occupation concepts applied to historical U.S. Census data

Recent occupation concepts applied to historical U.S. Census data. Peter B. Meyer US Bureau of Labor Statistics (but none of this represents official measurement or policy; Views and findings are those of the author not the agency) RC33 2008, Naples, Sept 3, 2008. Outline

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Recent occupation concepts applied to historical U.S. Census data

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  1. Recent occupation concepts applied to historical U.S. Census data Peter B. Meyer US Bureau of Labor Statistics (but none of this represents official measurement or policy; Views and findings are those of the author not the agency) RC33 2008, Naples, Sept 3, 2008 • Outline • Brief history of U.S. Census occupations • Can standardize to recent definitions? • Issues: working wives, native Americans, slaves, children, others

  2. An ideal occupation variable . . . Would extend over a long period using the same category system That enables comparison over time to see causes and effects of: • Unionization • Licensing • Technological change • And more Examining individuals, holding occupation constant; Or within and between occupations Can we assign current occupation concepts to past Censuses? Efforts include occ1950, covering 1850-present (by Sobek) and occ1990, covering 1960-present (by Meyer and Osborne). These put harmonize the occupations for those respondents listed as having occupations at the time. But: Who was counted as having an occupation? How did that change?

  3. U.S. Census occupation history(the historical process recording the data) • Census starts in 1790, for political districting and taxation. • Most Native Americans (Indians) were not counted. • 1850: Free male respondents first asked for their “Profession, occupation, or trade” by U.S. marshals. Occupations were not categorized. • 1850s: International conferences on occupation collection in Censuses • 1860: All free respondents asked for occupation; household head, usually male, is counted distinctively. • 1870: Slave category disappears. • 1870: Classification of occupations into 338 categories. • Since 1870: The category system changed every decade since then. • 1880: Data collectors now political appointees not judicial aw enforcers • 1902-10: Now permanent civil service bureau collects data and categorizes into occupations. Quality improves. • 1940: Switch to “labor force” definitions and concepts, de-gendered • Since 1940: Relatively stable definitions and practices. • Since 1970: With each new system “dual-coded” data are now available.

  4. Many working women did not have a recorded occupation in 1900 • My main source: Bose (2001) • Many women in 1900 who would now count as employed did not count as employed in the 1900 Census. • Working on family farm (est. 16.9% of US women age 15-64) • Taking in boarders; taking care of other people’s children (3.9%) • Outwork, e.g. sewing at home, or running a shop (3.1%) • Her corrected figures are not far from the comparable measures available from Australia which used two similar occupation concepts Other sources: Sobek (1997), Goldin (2001), Abel and Folbre (1983), Deacon (1985)

  5. More changes in boundary of who has an “occupation” • Indians – slow transition into occupation, since the early Census (for more see Snipp and Hacker) • Slaves, till 1870 – not recorded as having an occupation • Children – minimum age for recorded occupation jumps around, varying from 10 to 16 until 1910 • People who were disabled, retired, students, institutionalized, or seasonal workers were less likely using post-1940 “labor force” definitions to have an occupation. (Anderson, 1980, p.24)

  6. In other cases, boundary did not change • Unemployed men – May report an occupation • Non-citizens, border-crossers -- Household location matters; employer's location does not matter. • Working illegally or avoiding tax - Can have a Census occupation, without a legal implication, butuntil 1880 Census enumerators were law enforcement officials. • Volunteers or hobbyists -- Not counted as in an occupation unless they report as self-employed • Apprentices – yes, if paid. If not paid, might be conceived of as students. • Homeless; traveling; or can't locate -- Can have an occupation based on information from others or remote location. • Refused to answer -- Historically a small category. Enumerator may receive information from others. Possibly a growing category.

  7. Rough magnitude of boundary changes

  8. Tentative conclusions • Can potentially do a good job matching current job categories back to 1970 using “dual-coded” data sets. • It is realistic to apply current occupation categories back to 1940 • Before 1930, might adjust for adult women in home-based economy and Indians • Before 1870, occ data was not categorized and there were slaves • In 1850 maybe only 35% of population would have a Census occupation; now over 60%. • With more research, it is feasible to get better at this.

  9. The information coders have

  10. Tangential motivation:Example of standardizing • In 1960 Census, “lawyers and judges” was one category • Later, “lawyers” and “judges” were separate • We can impute which 1960 ones are judges for standardizing comparisons to later data. • In 1970-1990 these variables predict who’s called a judge: • Employed in public sector, especially in state government • Older • Employed in state government • High salary income • Low business income • Educated less than 16 years • Employed at time of survey

  11. Information used when coding • “what kind of work" • “most important activities or duties" • employer name • “what kind of industry” • home city and state • years of education • age • sex • before 1994, had income too This information is available when choosing “industry” and “occupation”  • Tens of thousands of job titles are mapped to a code in a reference book they have, if industry matches what is expected. • Some cases may be "autocoded" by software; coder checks. • Coder with two years experience should assign 94 codes per hour with 95% “accuracy”, which is checked. • Cases not meeting the rules go to “referralist” (specialist) • They have 9+ years of experience.

  12. Problems faced by referralists • Having to hurry • Ambiguity; too little information from respondent • “computer work" for “kind of work” • "water company" for industry or employer • "surveyor" occupation • "boot" vs "boat" in handwriting • exaggeration (example: dot com businesses) • Referralists confer with each other routinely, but sometimes make different choices from one another

  13. Can standardize occupation categories over time that look like recent ones? • IPUMS (Matt Sobek) defined occ1950 for 1850-present • Meyer and Osborne (2005) defined 1990-based classification from 1960 to present. Plan to improve, correct, and extend that. Let us look at recent Census practices occupation variable. • Census “coders” in a single location assign 3-digit industry and occupation codes • They follow carefully documented practices. • I interviewed four experienced ones. • They work just north of Louisville, in Jefferson, Indiana

  14. Newly Imputed Judges Using that information in a logistic regression, can assign some to new “judges” category. Seems to be 80% accurate. In this case, can estimate a time series of earnings separately for judges and lawyers more accurately. Let us go back to look at the earlier period to see how far it is from this data-processing world.

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