Performance Webinar #3

Focusing on Average Earnings

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Webinar Layout

Slide Area

AttendeeList

ChatRoom

Notes

Connection Status

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To chat, type text into the text box. When asking a questions, be sure to identify your State.

Select whom you wish to chat with by using the To: drop-down menu.

Click the arrow button

Chat Feature

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Background

Three Performance Management Conferences held in February/March, 2006 focused on revised performance and reporting policies

Follow-up from conferences included requests for performance-related webinars around specific topic areas

Today’s webinar is the third in a series of 6 webinars hosted by ETA Performance Specialists

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Future planned webinars

September, 2006 – VETS Performance/Reporting Issues

October, 2006 – Certificates and Training for Adults and Dislocated Workers

November, 2006 – Innovative Practices to Improve State Performance

December, 2006 – Open for suggestions (send to ETAperforms@dol.gov)

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Webinar Outline

Brief History of Earnings Outcomes Training and Employment Guidance Letters (TEGL):

7-99 15-03 28-04 17-05

Data Sources National Results Analyzing Outcomes

Lower Living Standard Income Level (LLSIL) Subject Matter Experts:

BLS Quarterly Census of Employment and Wages (QCEW) New York State (Average Earnings’ Forecasting Model)

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Our Speakers . . .

Ron Fionte Branch Chief, Bureau of Labor and Statistics

(BLS)

Bill Meehan Principal Economist, Division of Research

and Statistics, New York State

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History of Earnings Outcomes

TEGL 7-99 Average Earnings Change (Adult, Older Youth) Earnings Replacement Rate (DW, TAA, NEG) Effective 7/1/2000. Rescinded by TEGL 17-05

TEGL 15-03 Earnings Increase 1 & 2 (Adult, Older Youth, DW, TAA,

VETS) Never fully implemented. Rescinded by TEGL 28-04

TEGL 28-04 Six Months Earnings Increase (Adult, DW, TAA, Wagner-

Peyser, VETS) Effective 7/1/2005. Rescinded by TEGL 17-05

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TEGL 17-05

Average Earnings (Adult, DW, NEG, TAA, Wagner-Peyser, VETS)

Of those who are employed in the 1st, 2nd and 3rd quarters after the exit quarter:Total earnings in the second quarter plus total earnings in the third quarter after the exit quarter divided by the number of participants who exit during the quarter.

Effective Date: 07/01/2006

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TEGL 17-05 Older Youth

Earnings Change: Older Youth

Of those who are employed in the 1st quarter after the exit quarter and who are either not enrolled in post-secondary education or advanced training / advanced training-occupational skills training in the 3rd quarter after the exit quarter or are employed in the 3rd quarter after the exit quarter: [Total post-program earnings [earnings in quarter 2 + quarter 3 after exit] minus pre-program earnings [earnings in quarter 2 + quarter 3 prior to participation] divided by the number of older youth participants who exit during the quarter.

Effective Date: 07/01/2006

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Data Sources

Wage Records UI Wage Records Additional Wage Record Data Sources:

Automated Record Matching / Data Sharing Systems (WRIS and FEDES)

OPM, USPS, US DoD, Railroad Retirement System, State New Hires Registry and State Department of Revenue or Tax

Supplemental Sources (only for grantees that do not have access to wage records, e.g. NFJP, SCSEP, INAP)

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UI Wage Records

Primary data source Includes private sector and non-profit

sector Also includes government employer wage

reports: State Local Judicial, and Public School

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Additional Wage Record Data Source:

WRIS & FEDES

WRIS (Wage Record Interchange System) Created to facilitate the interstate exchange of

UI wage data 50 states participating

FEDES (Federal Employment Data Exchange System)

Focused on providing access to employment records maintained by the following agencies:

Office of Personnel Management (OPM) Department of Defense (DOD) and United States Postal Service (USPS)

29 states participating

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From Data Sources to Benchmarks

Wage data are collected, compiled and compared to established benchmark standards for purposes of data analysis

Two primary data sets used for establishing benchmark standards for purposes of analysis are: Lower Living Standard Income Level (LLSIL) Quarterly Census of Employment & Wages

(QCEW)

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Data and methodology: Based on the 1981 lower living family budget (BLS) BLS still provides data to ETA which publishes the

LLSIL Uses the “Poverty Guidelines” issued by HHS Annual updates based partially on the Consumer Price

Index for All Urban Consumers (CPI-U) Data are presented by geographic region and for 23

selected Metropolitan Statistical Areas (MSA)

NOTE: This data should not be used for statistical purposes due to the nature of the base calculation which has not been updated since 1981.

Lower Living Standard Income Level (LLSIL)

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Program uses: 70% LLSIL used by WIA to define:

low income individual disadvantaged youth disadvantaged adult

Used in eligibility determinations under Work Opportunity Tax Credit (WOTC)

Since the 70% LLSIL is used as an eligibility gateway to services under WIA Adult, the average earnings outcome should approach or exceed the one-half the 70% LLSIL rate

Lower Living Standard Income Level (LLSIL)

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National Results

Average 6-Month Earnings

$0

$5,000

$10,000

$15,000

$20,000

$25,000

2002 2003 2004

Program Year

WIA Adult WIA DW

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National Results

Average 6-Month Earnings

$0

$5,000

$10,000

$15,000

$20,000

$25,000

2002 2003 2004

Program Year

WIA Adult WIA DW LLSIL70%

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National Results

Average 6-Month Earnings

$0

$5,000

$10,000

$15,000

$20,000

$25,000

2002 2003 2004

Program Year

WIA Adult WIA DW QCEW LLSIL70%

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Quarterly Census of Employment and Wages (QCEW)

Ron FionteBranch Chief

Bureau of Labor Statistics (BLS)

(617) 565-2335

fionte.ronald@bls.gov

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The Quarterly Census of Employment and Wages Program: What is it?

A quarterly census of employers covered under Unemployment Insurance Tax laws, and Federal employers covered under Unemployment Compensation for Federal Employees.

not a sample

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QCEW Output:Macrodata & Microdata

Macrodata Output: Published data summed by location,

industry and ownership Number of establishments, monthly

employment, and quarterly wages Summed by geographical area, industry

(NAICS) code and ownership

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QCEW Output:Macrodata & Microdata

Microdata Output: Confidential establishment level data;

generally for internal use only Sample frame for establishment surveys Geocode-able, providing a detailed

mapping reference

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Macrodata Output: Employment

All workers covered by UI laws and on the payroll as of the pay period including the 12th of the month.

Includes full and part time and those on paid leave. Does not include those on unpaid leave.

Published 3 ways: Monthly per quarter, quarterly averages, annual averages.

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Macrodata Output: Total Quarterly Wages

Total amount paid to covered workers during the quarter, regardless of when the services were performed.

Bonuses, overtime, and severance pay are included.

Possible that wages are counted for workers not included in employment total (if they never worked in a pay period including the 12th)

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QCEW Program Macrodata: What’s it used for?

•Provides detailed industry employment and wages data down to the county level*.

•As a benchmark for other BLS programs.

•Input to Bureau of Economic Analysis’ (BEA) Personal Income and Gross Domestic Product statistics.

•Input to other BLS programs: LAUS, MLS.*subject to confidentiality restrictions

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UI Tax Rate & Actuarial Analysis

UI-Covered Employment

Local Area Unemployment

Personal Income (BEA)

Gross Domestic Product (BEA)

Economic Forecasting

Current Employment Statistics

Occupational Employment Statistics

Job Creation/Destruction•Size Class Dynamics•Business Survival Rates

Geocoded Establishments

Occupational Employment Statistics

Occupational Safety and Health Statistics

Current Employment Statistics

National Compensation Survey

Industrial Price Program

Occupational Safety and Health Statistics

Programmatic Uses

Benchmarking(Employment Base)

General Economic Uses

QCEW Data

Analytical Uses Sampling

Mass Layoff Statistics

State Revenue Projections

Jobs Openings & Labor Turnover Survey

Job Openings & Labor Turnover Survey

Quarterly Press Releases, Annual Employment and Wages

Local Economic Development Indicators

• Clusters Analysis• Shift Share• Industry Diversity Indexes• Location Quotients

Federal Funds Allocation$175 Billion

(HUD, USDA, HCFA/CHIP)

Minimum Wage Studies

Uses of QCEW, Quarterly Census of Employment and Wages Data

Local Economic Impact Response Planning

Local Government Services Planning

Interagency Data Uses• Improve CPS After 2000 Census• LEHD• Industry Code Sharing

Local Transportation Planning

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Pre- vs. Post-Program Earnings’ Analysis

Bill MeehanPrincipal Economist

Division of Research and Statistics,

New York State Department of Labor

(518) 457-1300

us0bpm@labor.state.ny.us

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How Pre-Program Earnings Relate to Post-Program Earnings

Pre-program earnings can be a predictor of post-program earnings. In general: The higher the pre-program earnings of a

group of participants, the higher the post-program earnings

The lower the pre-program earnings of a group of participants, the lower the post-program earnings

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How Much Higher; How Much Lower?

In the Adult program in PY 2005 in New York State: A 1 dollar change in pre-program earnings

resulted in: a 50 cent change in post-program earnings

In the Dislocated Worker program in PY 2005 in New York State: A 1 dollar change in pre-program earnings

resulted in: a 30 cent change in post-program earnings

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How Was the Relationship Determined?

Simple observation of an apparent relationship between pre- and post-program earnings

Relationship was recognized under JTPA The 30 cent and 50 cent relationships

were determined using a regression analysis with pre-program earnings as the independent variable and post-program earnings as the dependent variable

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How strong is the relationship between pre- and post-program earnings?

The magnitude of the relationship (50 cents for Adults and 30 cents for DWs) was strongest in the middle earnings range of pre-program earnings

Not as strong in the low end individuals with no pre-program earnings had much

higher post-program earnings Or in the high end

an increase in earnings in the higher range of the pre-program earnings ($15,000+) leads to an increase in post-program earnings, but not as much of an increase as in the lower pre-program earnings range

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Pre- and Post-program Earnings in Recent Years in New York State --

AdultsAVERAGE PRE AND POST PROGRAM EARNINGS

PY2005 Qtr 31 PY 2004 PY 2003

Pre-ProgramEarningsRange Individuals

AveragePre Program

Earnings

AveragePost Program

Earnings Individuals

AveragePre

ProgramEarnings

AveragePost

ProgramEarnings Individuals

AveragePre

ProgramEarnings

AveragePost

ProgramEarnings

TOTAL 18,028 $ 6,905 $ 11,462 19,812 $ 7,125 $ 11,493 27,087 $ 6,367 $ 10,812

$0 4,841 $ - $ 9,428 5,183 $ - $ 9,885 7,738 $ - $ 9,057

$1-$2,500 2,710 $ 1,140 $ 8,343 2,786 $ 1,152 $ 7,975 4,128 $ 1,135 $ 7,766

$2,501-$5,000 2,151 $ 3,707 $ 8,594 2,261 $ 3,739 $ 8,713 3,361 $ 3,708 $ 8,294

$5,001-$7,500 1,761 $ 6,231 $ 9,891 2,087 $ 6,214 $ 9,658 2,747 $ 6,191 $ 9,343

$7,500-$10,000 1,561 $ 8,720 $ 10,975 1,856 $ 8,726 $ 10,912 2,327 $ 8,711 $ 10,626

$10,001-$15,000 2,296 $ 12,326 $ 13,320 2,615 $ 12,348 $ 12,969 3,238 $ 12,306 $ 13,023

> $15,000 2,708 $ 22,352 $ 20,226 3,024 $ 22,505 $ 19,919 3,548 $ 22,036 $ 19,810

1 Source: PY 2005 Qtr 3 WIASRD. Includes exiters from 4/1/2004 to 3/31/2005

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General Performance Issues

QUESTIONS?

ETAPerforms@dol.gov