The views expressed in this publication are those of the authors and do ...

The views expressed in this publication are those of the authors and do not necessarily represent those of Lumina Foundation,

the Bill and Melinda Gates Foundation, or the U.S. Department of Education, their officers, or employees.

CAREER CLUSTERS

FORECASTING DEMAND FOR

2008- HIGH SCHOOL THROUGH 2018 COLLEGE JOBS

Title

Contents

iii Acknowledgments

v Illustrations

10 1: Key Messages

14 2: Earning Middle-Class Wages: Career Clusters and the MET

? Opportunities for those with a high school diploma or less still exist but are quickly declining. ? Jobs for high school graduates and dropouts are concentrated in four career clusters. ? The best opportunities for high school dropouts or high school graduates are in maledominated fields. ? Although some high school jobs exceed the Minimum Earnings Threshold (MET), these jobs are declining. ? Women need postsecondary education to earn wages that men with a high school diploma earn. ? Some middle-skills jobs exceed the MET. ? Postsecondary education increases opportunity and access. ? Jobs for workers with some college/no degree or an Associate's degree are concentrated in six career clusters (compared to four for workers with a high school diploma or less). ? A Bachelor's degree or better guarantees access to all career clusters. ? A Bachelor's degree or better offers accessibility to all high-paying jobs within career clusters, but it is not a guarantor. Occupation matters. ? Most jobs for workers with a Bachelor's degree or better pay wages exceeding the MET.

38 3: FORECASTING EMPLOYMENT DEMAND BY CAREER CLUSTER

? Current supply of secondary and postsecondary CTE graduates by career cluster

46 4: LOOKING FORWARD TO 2018: EMPLOYMENT PROJECTIONS FOR CTE

? Size, educational characteristics, and trends in employment in CTE career clusters

66 5: EXAMINING WAGES AND CAREER CLUSTERS

? There is a wide distribution of wages across career clusters.

? Across time, wage growth is best in Business, Management, and Administration; Finance; Health Science; Information Technology; and Law, Public Safety, Corrections, and Security.

? Occupation matters.

? STEM and Information Technology are the best-paying career clusters for middle skills.

? The gender wage gap by career cluster ranges between $2,000 and $69,000.

? Disaggregating by career cluster and age reveals occupational bias in the gender wage gap.

? High-Demand Versus High-Wage Jobs

81 6: FORECASTING DEMAND CLUSTER BY CLUSTER THROUGH 2018

? Career Cluster 1: Agriculture, Food, and Natural Resources ? Career Cluster 2: Architecture and Construction ? Career Cluster 3: Arts, A/V Technology, and Communications ? Career Cluster 4: Business, Management, and Administration ? Career Cluster 5: Education and Training ? Career Cluster 6: Finance ? Career Cluster 7: Government and Public Administration ? Career Cluster 8: Health Science ? Career Cluster 9: Hospitality and Tourism ? Career Cluster 10: Human Services ? Career Cluster 11: Information Technology ? Career Cluster 12: Law, Public Safety, Corrections, and Security ? Career Cluster 13: Manufacturing ? Career Cluster 14: Marketing, Sales, and Service ? Career Cluster 15: STEM (Science, Technology, Engineering, and Mathematics) ? Career Cluster 16: Transportation, Distribution, and Logistics

Career Clusters: Forecasting Demand for High School Through College Jobs, 2008?2018 ii

iii Career Clusters: Forecasting Demand for High School Through College Jobs, 2008?2018

Acknowledgments

We would like to express our gratitude to the individuals and organizations that have made this report possible. First, we thank Lumina Foundation and the Bill and Melinda Gates Foundation for their support of our research over the past few years, and in particular, we are grateful for the support of Jamie Merisotis, Hilary Pennington, Holly Zanville, Parminder Jassal, and Ann Person. We are honored to be

partners in their mission of promoting postsecondary access and completion for all Americans.

Acknowledgments

Although the analysis, conclusions, and recommendations in this report should be viewed as the responsibility of the authors, the content has bene ted enormously from assistance from others. We would like to thank the following members of the National Association of State Directors of Career Technical Education Consortium (NASDCTEc) for their area-matter expertise and early comments on the content of the report:

? John Fischer, State Director of Career & Technical Education, Vermont Department of Education;

? Katherine M. Oliver, Assistant State Superintendent, Career Technology and Adult Learning, Maryland Department of Education;

? Mark Williams, Division Administrator, Career Development Division, Illinois State Board of Education.

We thank Stephanie Soutouras Schlick for editing the report, and research analyst Michelle Melton and program coordinator Laura Meyer for their early compilation and coordination for the layout and printing of the report.

We also wish to thank the following sta members of the Association of Career and Technical Education--Pete Magnuson, Lauren Schultz and Kirsten Sundell of the National Research Center for Career and Technical Education (NRCCTE) for critiquing content and facilitating printing and design.

Career Clusters: Forecasting Demand for High School Through College Jobs, 2008?2018 iv

v Career Clusters: Forecasting Demand for High School Through College Jobs, 2008?2018

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