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Local Area Estimates

Local Area Estimates. ICESA LMI Directors’ Meeting October 2000. Setting the scene. Oregon Workforce Investment Board Seven Regional Workforce Investment Boards Nine Local Workforce Investment Boards Five Metropolitan Statistical Areas Thirty-Six Counties. Unemployment and Labor Force

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Local Area Estimates

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  1. Local Area Estimates ICESA LMI Directors’ Meeting October 2000

  2. Setting the scene ... • Oregon Workforce Investment Board • Seven Regional Workforce Investment Boards • Nine Local Workforce Investment Boards • Five Metropolitan Statistical Areas • Thirty-Six Counties

  3. Unemployment and Labor Force Current Industry Employment Occupational Employment Covered Employment and Payrolls Occupational Wages Industry and Occupational Projections Educational and Skill Requirements Current Data Availability-- Statewide

  4. Current Data Availability • Workforce Regions: • Unemployment and Labor Force • Current Industry Employment • Occupational Employment • Covered Employment and Payrolls • Occupational Wages • Industry and Occupational Projections • Educational and Skill Requirements, by Occupation

  5. Unemployment and Labor Force Current Industry Employment Occupational Employment Covered Employment and Payrolls Current Data Availability -- MSAs

  6. Current Data Availability -- County • Unemployment and Labor Force • Current Industry Employment • Covered Employment and Payrolls And we receive continuing pressure in regard to occupational information, projections, and wages, at the county level.

  7. Current Industry Employment Estimates ... • Monthly … on same timeline as MSA estimates. • Use same methodology as state and MSA CES estimates … • solicitation / survey response methods • estimating procedures • benchmarking

  8. “CES” operations in Oregon • Statewide: • 127 estimating cells • 94 published cells • MSAs: • 254 estimating cells • 204 published cells

  9. “CES” operations in Oregon • Counties: • 631 estimating cells • 638 published cells • Deschutes (the largest non-MSA county) has 25 estimating cells and 22 published cells. • Wheeler (the smallest county) has 10 estimating cells and 11 published cells.

  10. Benton County … a typical large county: • Sample size = 258 • Number of estimating cells = 29 • Number of published cells = 19 / 31 • Estimating techniques used: • sample based link (21) • historical trend plus sample (7) • seasonal trend plus sample (1)

  11. Baker County … a typical small county: • Sample size = 114 • Number of estimating cells = 23 • Number of published cells = 13 / 22 • Estimating techniques used: • sample based link (9) • historical trend plus sample (8) • seasonal trend plus sample (6)

  12. Local estimates -- the real world • We have to accept that local estimates … ie small area estimates … will always be a combination of statistical purity and analyst judgment. • Sample based link … • Historical or seasonal trend ... • Newspaper reading … • Last week’s Chamber meeting …

  13. The NORC methodology County estimate = sample employment + nonsample predicted employment + supplemental add-ons Nonsample predicted employment = nonsample ES-202 data * (weighted statewide sample CES employment) / (weighted statewide sample ES-202 employment)

  14. Key Lines from the July 2000 NORC Report • “… estimates are reasonable … but different enough from link relative estimates to cause trend disruptions” • “More examination of micro data is needed …” • “Rules for handling problem data are more complex than expected.” • “The capability for user-defined add-ons also provides flexibility for analyst intervention should the need arise.”

  15. Key Lines from the July 2000 NORC Report • “The estimator in SDE is based on the premise that sample CES records can be cleanly matched to their counterparts in the ES-202.” • “The SDE estimates … did not take into account major local changes to individual firms that had occurred since the benchmark period.” • “The add-on capability will also enable the LMEs to make corrections to the data where significant errors or changes warrant.”

  16. Key Lines from the July 2000 NORC Report • “Several counties … major employers closed, and the closure is not reflected in the ES-202 data that SDE used.” • “Most (users) agreed that the link-relative estimator is problematic in small domains … were open-minded about the synthetic estimator, providing they could fix the auxiliary data (ES-202) as they have in the past.”

  17. The underlying issues ... • Current CES-based methodology … works great. • NORC-developed methodology … looks great … may well work excellently. • Note … we (Oregon) have no disagreement with the NORC project … it’s excellent. • But in either case … you’ve got to have sample firms … and you’ve got to have hand-add abilities.

  18. An aside on probability sampling tests … • Medford, OR MSA • Existing CES sample for wholesale trade: • 17 reporters, 17% of employment … for SIC 50 • 14 reporters, 27% of employment … for SIC 51 • Probability CES sample for wholesale trade: • 7 reporters, 8% of employment … for SIC 50 • 8 reporters (representing only 3 firms), 10% of employment … for SIC 51.

  19. Moving forward ... • CES Policy Council • Options and Possibilities • At least two choices for methodology • BLS-sanctioned additional sample • State-supported additional sample

  20. One example ... • BLS “allows” additional sample for non-BLS, non-MSA areas … • State responsible for funding and resources to support the additional sample … • May or may not use BLS forms / phone systems. • ACES serves as the data storage and manipulation system.

  21. Your comments are important. • CES Policy Council meets, for the first time, November 8 and 9. • Send your thoughts to Graham Slater … • Graham.J.Slater@state.or.us

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