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Tangled Up in Data image 

Tangled Up in Data? — Putting Workforce Data to Work in Employment & Education Programs

 In this U.S. Employment and Training Administration (ETA) Webinar, we show you how to use workforce data to identify growing and in-demand jobs, determine which of them are “good” jobs, and ascertain what preparatory education and training are needed to qualify for them.  Drawing upon the best governmental and private sector sources, we explain them, outline their strengths and limitations, provide guidance on oft-used terms like “high growth” and “good jobs,” and help you to avoid common pitfalls. 

The Webinar also identifies some of the best multi-purpose E-Tools that incorporate workforce data, job ads, and other job-related information in one place — including a new resource that explains what kind of information is available from different E-Tools. 

See especially the 

 

1. Webinar PowerPoint and Transcript.  The oral presentation (which you can access through either the recording or the transcript) has information and advice beyond that covered in the PowerPoint.  For your convenience, we’ve annotated the transcript with references to the PowerPoint slides, which closely mimics the experience of listening to the recording while taking much less of your time.  

2. Workforce Data, Job Openings and Other Information Available from Selected Federal Multi-Purpose E-Tools.

Workforce Data Presentation Outline

New Quick-Lesson Workforce Data Podcast Series

The U.S. Employment and Training Administration has just issued a new series of podcast instruction guides to help you identify and use labor market and workforce statistics.  The presentations are written simply, and presume no previous subject matter or statistical knowledge.  They should prove helpful for a broad variety of audiences and purposes, including grant applications; targeting growing industries and occupations; pinpointing labor market hardship; state and regional planning; and assessing program effectiveness.

 

Each is comprised of  a podcast roughly 10 minutes long plus a transcript of 2-3 pages.  The podcast and transcript can be used either separately or together:  the links can't be accessed from the podcasts, but the podcasts include visuals not available in the transcripts.

 

Some provide an overview of a topic (like unemployment data), while others explain in a step-by-step manner how to obtain a specific type of data or to use a specific data tool.  Each topical presentation includes basic definitions, a brief historical background, links to the most important sources (especially for state and local data), and practical tips on how to interpret and use the data and avoid common mistakes.  The tool- and data-specific presentations are designed to enable you to obtain useful data by the end of the lesson.

 

ETA intends to produce more of these presentations, but these exist now.  You can also access all of them from our Quick-Lesson Podcast folder.

New 2013 Podcasts

  1. Unemployment data
  2. Dislocated worker data
  3. Employment projections
  4. Industry data
  5. Geographic data
  6. Economic data

 2011 Podcasts

  1. The Data Dozen: Key Workforce Data and Information Sites
  2. Using E-Tools to Identify Growing Industries
  3. Using E-Tools to Identify Industry Concentration Ratios
  4. Using E-Tools to Identify Occupations  

Unemployment Rates 1890-2012

2013 Lower Living Standard Income Level Guideline Issued

 

Lower Living Standard Income Level (LLSIL) Guidelines are used by state and local employment programs to determine income eligibility for Workforce Investment Act (WIA) programs for youth and certain adult services, in addition to the Work Opportunity Tax Credit.

The link provided includes the 2013 Federal Register Notice announcing the LLSIL, as well as the guidelines for previous years.

See 2013 LLSIL Guidelines.

 

ETA has also issued special tabulations of combined 5-year samples (using 2006-11 data) of the U.S. Census Bureau’s American Community Survey (ACS), which are in part based on the LLSIL Guidelines.  Combined 5-year samples are necessary to attain a sufficient sample size to present usable data.

 

These special tabulations include separate sets of tables for the nation, states, counties, and other types of localities. ETA has also provided special tabulations for Native Americans.  For each type of geography, there are tables on all persons, the poor, persons earning less than 70 per of the LLSIL, and other data. 

 

See Data on Economically Disadvantaged Youth and Adults for WIA.  

 

 

If you want to find information on skills and educational attainment, ETA’s guide to the relevant sources will allow you to shed light on labor or skill shortages, skill mismatches, and skill deficiencies.  Skimming for Skills provides links to surveys, reports and customized data tools.

Each entry notes whether the survey or source supplies information on current or projected employment, job openings, occupational or industry data, and earnings.  Skill-related topics include information on the education, training or skills required for jobs; educational attainment; educational field (e.g., college major) or coursework; and the skills individuals possess, including skill assessments.  For sources that collect information on educational credentials, a detailed definition is provided.  Each entry also lists availability at the national, state or local level, and the time period covered.

Due to public interest in possible skill shortages and mismatches, the guide is organized to enable users to ascertain whether each source contains supply and demand information.  More than three dozen sources are included, encompassing the U.S. Census Bureau, the U.S. Labor and Education Departments, real-time data private sector sources, and two important studies of the skills of postsecondary students. 

For the user’s convenience, the numerous skill-related sources are classified by those pertaining to adults, postsecondary students, secondary students, and longitudinal surveys that span ages from student to adult.  The guide concludes with a list of supplementary resources for understanding occupational, industry and instructional classification codes; science, technology, engineering, and math (STEM) classifications; and other sources on state and local workforce data and how to use it.

 

For selected national educational attainment and employment data, see ETA’s We’ve Got Your Number(s) — Key Workforce Trends.  For research on skills issues, see ETA’s Skill Shortage, Mismatch and Deficiency Repository. For overviews of several of the most important sources on skills, see our new High School Test Scores in 8 Subjects, High School Coursework Over 3 Decades and NOT Hitting the Books — Limited Homework and Studying Time in High School and College.

 

Unemployment Rates 1890-2012

Unemployment Rates 1890-2012

NOT Hitting the Books — Limited Homework and Studying Time in High School and College

 

In considering the skills possessed by U.S. workers, one important but oft-neglected factor is the effort made to acquire knowledge and skills.  The time that students devote to homework and studying outside of class time is probably the best measure of such effort.  ETA has produced 3 tables and 4 charts showing homework/study patterns since 1978 for high school students and since 2002 for college seniors, and reviewed the existing research. The pattern shows limited homework/study time for both high school and college students, far below the peaks reached during the 1960s. This is troubling because skill mastery is impossible without sufficient practice. 


See NOT Hitting the Books — Limited Homework and Studying Time in High School and College. NOTE: THE 3 TABLES ARE PRESENTED IN 3 SEPARATE TABS -- GO TO THE BOTTOM OF THE TABLE TO SELECT A DIFFERENT TAB.

 

High School

 

Among 17 year-old students (most of whom are juniors), since 1978 only between 10 and 13 percent reported that they did more than 2 hours of homework on an average night.  Since 1999, about three times this proportion (38-40 percent) reported doing no homework at all on an average night — mostly because no homework was assigned.  Since 1996, almost two-thirds of high school students have done less than an hour of homework nightly.

 

Since 1984, changes in the amount of homework time for 17 year-olds have been fairly modest, but have tended toward less homework.  Since then, students have been less likely to be assigned homework, and homework time peaked in 1984.  Since 1978, the U.S. National Assessment of Educational Progress (NAEP) has asked 17 year-old students, “How much time did you spend on homework yesterday?”  Using NAEP’s five breakdowns (no homework assigned, assigned but not done, less than 1 hour, 1-2 hours, and more than 2 hours), the U.S. Employment and Training Administration (ETA) has produced a table and two charts, including broader categories showing trends for no homework, an hour or less (including no homework), and more than an hour.  

 

A recent NCES survey of parents of 9th to 12th graders found that 73 percent of parents thought the amount of homework assigned was "about right" (the study didn't report the proportions who thought that the amount was too much or too little). See Parent and Family Involvement in Education (p. 9).

 

A 2003 scholarly examination concluded that during the post-World War II period, high school homework effort likely peaked during the 1960s before dropping sharply in the late 1960s and early 1970s.  The authors also concluded that little change occurred between 1972 and 1980.  Survey data indicate that only during the 1960s did 20 percent or more of high school juniors spend more than 2 hours nightly on homework, and that in the late 1940s and early 1950s even less than 10 percent did this much homework. See A Nation at Rest: The American Way of Homework. 

 

It should be noted that since the early 1980s, in-school coursework for high school students has moved in the opposite direction — becoming more demanding over time.  See High School Coursework Over 3 Decades.

 

College  

 

Study time outside college classes fell markedly between the early 1960s and the early 2000s, probably by about half, but appears to have gradually risen since 2004.  However, 2012 study time remains well below that of a half century ago — 24.5 hours weekly then vs. 15.5 hours now. 

 

The data for college study time is not as good as that for high school, as it’s necessary to rely upon different surveys that study different schools (some of the samples are not random) at differing ages.  For example, some studies include all full-time college students regardless of age, while others study a specific cohort at about the same age.  Some include solely freshman, some solely seniors, while others cover freshman through seniors.  

 

Therefore the findings should be interpreted cautiously, but the changes have nonetheless likely been dramatic.  The survey data may in fact understate their degree, as the 1961 survey covered freshman only, who are known to study less time than upperclassmen.  In 1961, 67 percent of college freshman studied more than 20 hours weekly, with the share dropping to 44 percent by 1979, about 20 percent by 1988, and to an even lower point by the early 2000s.  At the lower end of the spectrum, only 7 percent of college freshman studied 5 or fewer hours weekly in 1961, with that share rising to 14 percent in 1979, 16 percent in 1988, and to about one-fourth by the early 2000s.

 

After 2000, data from two sources became available — whose findings differ significantly.  A UCLA survey of full-time college seniors (which began in the mid-1980s) found that in 2009 (the latest published data), 28 percent studied 5 or fewer hours weekly, while 12 percent studied more than 20 hours.  In contrast, the National Survey of Student Engagement (NSSE, which began in 2000 and has a much larger sample of schools), reported only 16 percent of college seniors studying 5 or fewer hours weekly, and 23 percent studying more than 20 hours.

 

The latest scholarly review of college study time, The Falling Time Cost of College (2010), reviewed data no later than the early 2000s.  Since both of the more recent surveys (UCLA and NSSE) are not based on randomly sampled schools, the authors were careful to analyze only the schools included in other surveys — for the NSSE, this had the effect of very slightly reducing the numbers compared with the total national results. 

 

ETA has collected and graphed the data for all recent years published on the Web sites for the UCLA (2006-9) and NSSE (2002-12) surveys.  Following an increase in study time from 2006-7 in the UCLA survey, almost no change occurred in the next 3 years.  In contrast, the NSSE shows a gradual rise in study time since 2004, with most of the post-2008 increase concentrated among the most studious (more than 20 hours weekly).  However, data from both sources should be treated cautiously, as they reflect not a random sample but voluntarily participating schools.

 

The NSSE also includes other important information on skills and effort which we have summarized in the table.  Over the 2002-12 span, only about half of seniors reported writing any papers of at least 20 pages (the study also includes data on papers of 5-19 pages and fewer than 5 pages, not included in our table).  Only about 10 percent of seniors reported completing more than 4 papers of at least 20 pages — which for a full-time courseload would mean an average more than one such paper per course.

 

About two-fifths of college seniors report having taken foreign language courses, although the proportions dipped slightly in 2011 and 2012 compared to earlier years. 

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