Show Me the Data:Where Do I Find It?

1st Joint Workforce and Economic Development Conference

Austin, Texas June 26, 2003

Richard Froeschle, DirectorCareer Development Resources(CDR)

rich@cdr.state.tx.us(512) 491-4941

How can economists, working with the same data, reach such widely different

conclusions?Anonymous, Augusta, Georgia

Economists are a lot like chefs. You can give a dozen good chefs exactly the same ingredients and equipment and staff and be amazed at the variety of stuff they cook up!

Marilyn Vos Savant--Parade Magazine

 

Data Come in All Types

Electronic versus Hardcopy Will you analyze further or just report? Excel, database, text file? Will hardcopy or a .pdf do?

Spatial (GIS) vs. Tabular vs. Narrative Reports

How do you want to view data? Is it for end-users or decision-makers?

Government Sources (public) versus Corporate (private)

Cost of data: Free vs. fee, confidentiality, coverage issues. How much is data worth?

Statistical Data versus Intelligence

Tradeoff of data collection cost and decision-making power. More data, more useful information, better analysis?

  

What do you want…How do want it?Raw data tables Unformatted, convenient to producer not

user, requires manipulation to become information e.g. BLS, O*NET

Self-manipulated outputs

Interactive data downloads based on special requests for geography, detail, time, formats e.g. TRACER WIN

Existing off-the-shelf reports

End user reports, tabular data designed to address common data queries, e.g. SOCRATES reports, EEO reports

“No how, No way” data items

Data not routinely collected through any formal program or process e.g. skill sets for unemployed, underemployment rate, benefits by region. Might be survey time!

Estimates vs. Counts vs. Outputs

How much does accuracy matter? Does it make a difference if your data is a SWAG, census, sample/subset, estimate?

Occupational Employment data

DOT & OES are dead! O*NET/SOC 3.0- federal occupational classification system, 1,100 occupations X 800 characteristics, KSAs

SOC-Standard Occupational Classification system (1998) Census 2000 SOC 2.0 (1997)

Texas occupational projections by LWDB, SOC (2000-2010)Texas occupational wages (2001), by LWDB, SOC, Wage

Information Network (WIN), detailed wages by industry by occupation by LWDB

National projections (2000-2010) by SOC, earnings, U rates

www.twc.state.tx.us www.bls.gov

Industrial Employment data

NAICS- North American Industry Classification system replaces SIC codes, phased in, full use by 2003, reflects new technology industries, similar to harmonized codes for imports (NAFTA)

ES-202 Industry employment and wages by county (TWC/LMI)

CES/BLS-790 Industry employment by MSA/average weekly wages/hours

On-line Employer database (inquire only) TRACER/SOCRATES

Other LMI Initiatives

TRACER II on-line LMI inquiry system---WIN Wage data

iOSCAR on-line O*NET assessment & career search (iOSCAR.org)

Labor Supply data http://DECIDE.cdr.state.tx.us

Emerging occupations Biotech, High TechSOCRATES- Projections (tables & graphs),

Occupational Profiles, County Narrative Profiles, Shift-share analysis, Regional Targeting, interactive industry/occupation matrix

Sources for LMI Data

• SOCRATES Website

– http://socrates.cdr.state.tx.us• TRACERII LMI inquiry system at:

www.tracer2.com• DECIDE labor supply, postsecondary outcomes:

http://decide.cdr.state.tx.us• Career Development Resources (CDR) Website

http://www.cdr.state.tx.us/• iOSCAR skills transferability software

http://www.iOSCAR.org

“Torture numbers and they will confess to anything.”

Gregg Easterbrook

Turning data into information, and then into intelligence,

requires an understanding of data sources and limitations and a

clear objective of what you want to achieve using data.