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The Value of Extended Time Span Coverage on Career Pathway: The Case for Sustained Investment in State Longitudinal Integrated Data Systems REPLACE THIS.

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Presentation on theme: "The Value of Extended Time Span Coverage on Career Pathway: The Case for Sustained Investment in State Longitudinal Integrated Data Systems REPLACE THIS."— Presentation transcript:

1 The Value of Extended Time Span Coverage on Career Pathway: The Case for Sustained Investment in State Longitudinal Integrated Data Systems REPLACE THIS BOX WITH YOUR ORGANIZATION’S HIGH RESOLUTION LOGO REPLACE THIS BOX WITH YOUR ORGANIZATION’S HIGH RESOLUTION LOGO Ting Zhang Assistant Professor, Dept of Finance & Economics; Associate Director, Jacob France Institute Merrick School of Business, University of Baltimore Abstract Results This study illustrates the value of extended time span coverage of state longitudinal education and workforce data system to inform and improve the effectiveness of future high impact expenditure decisions. It used an analytical 29-year data file created by the author that links seven already in-place education and workforce administrative record sources. Relying on the path dependency theory, multi-level mixed effect logistic and multi-level mixed effect linear regression models are used to test three hypotheses. The findings are consistent with the hypotheses: inclusion of the multiple steps along a postsecondary education pathway and prior job histories are both critical to understanding workforce outcomes mechanisms; it takes time for the employment outcome effect to be evident and strong following education attainment. The study concludes with research limitations and implications for decision makers to call for retaining and investing in administrative records with extended time span coverage, particularly for the already-in-place historical administrative records. Coefficients from the Hierarchical Modeling Introduction Limitation of the Study and Future Studies Prospects for future federal investment in state data system integration will depend upon the case that is made for doing so, justifying this allocation over popular competing alternatives. There is limited evidence that a strong case has been made for continued federal funding and successful promotion of state funding. However, essential components needed to make a strong case for future investment can be drawn from existing administrative data sources. This study delivers new evidence of state education and workforce integrated data system value through extended time span coverage that helps to inform and improve the effectiveness of future high impact education and workforce expenditure decisions. Data limitation: No college degree information between 1984 and 1993 Only tracks students with degrees in universities and colleges of one state No information on those who moved out of the region or not employed by the Federal civilian agencies. Neither self-employed and not covered by the UI law No clear clue at what time of the year a student was awarded a college degree Future studies: investigation into industry details or occupation nuances enrollment discipline impacts Conclusions Theoretical Framework & Hypotheses My findings are consistent with the stated hypotheses. Inclusion of the multiple steps along a postsecondary education pathway is critical to understanding workforce outcomes mechanism. The overall earnings gain from the first degree is higher than that from the latest degree The first degree, rather than the latest degree, has an impact on employment propensity. Prior job histories matter. Higher earnings before the latest college degree & more years employed before the latest degree are associated with a higher employment propensity and higher earnings after the latest degree year, The first job searching difficulty and earnings at 1 year after the first degree year also attribute to workforce outcomes after the latest degree. It takes time for the employment outcome effect to show up following education attainment. The college degree history impact tends to be more pronounced and stronger for 5 years, sometimes 3 years after than 1 year after the latest degree year. This holds true not only for the impact of the latest degree, but also most of time true for the impact of the first degree. Extended time span coverage of a longitudinal integrated data system is needed for prior college degree pathway, prior job history information, or for employment outcome to show up. Extended time span of longitudinal integrated data system that covers multiple steps of degree histories and at least 5 years of employment information after the latest degree often requires at least 1-2 decades of data information from an entering cohort, not just 5 years as the total time span for a data system. It is through extended time span coverage of a longitudinal integrated data system that the rich nuances interpreting the mechanisms of education ROI can be revealed. The study illustrates the value of extended time span coverage of the state education and workforce integrated data system, to communicate with decision makers who make prudent investments in public education and training to achieve complementary economic growth and citizen well-being goals. Decision makers’ role in retaining and investing in those administrative records with extended time span coverage is critical. Theories: Path dependency theory; Career development theory: “continuous lifelong process” extended time effect of one’s education credentials Hypotheses: More than the latest degree information is relevant for accurate estimation of workforce outcomes. Educational attainment information that occurred before the latest degree is critical for calibrating workforce outcome mechanism. Prior employment and earnings history matters when estimating workforce outcomes that are attributed to a defined level of educational attainment. It takes time for workforce outcomes to appear after the most recent education credential has been recorded Table 1. Label in 24pt Calibri. Methodology The Cohort Study Design fall 1984 first-time enrollees in Maryland’s public community colleges (N=28,295) Born 1933 through 1967 The Data UI wage records of matched 7 states/districts; FEDES; QCEW, matched to UI wage records; EIS, DIS The Model Mixed-effect Logistic Regression for Employment Propensity Mixed-effect multi-level Linear Regression for Job Tenure and Earnings Selected References Contact Andrews, R., Li, J., & Lovenheim, M. F. (2014). Heterogeous paths through college: detailed patterns and relationships with graduation and earnings. NBER Working Paper Series. College Board, 2016, The College Board, Annual Survey of Colleges; Trends in Student Aid 2015. Bound, J., Lovenheim, M., & Turner, S. (2009). Why have college completion rates declined? An analysis of changing student preparation and colligiate resources. Cambridge, MA: Working Paper 15566, National Bureau of Economic Research. Carnevale, A. P., Smith, N., & Strohl, J. (2010). Help wanted: Projections of jobs and educational requirements through Washington, D.C.: Georgetown University: Center on Education and Workforce. Hansen, L.S. (1976). “Career Development Education: Humanizing Focus for Educators,” Journal of Career Development, June : 42-48, doi: / Holzer, H. (2014). Improving Employment Outcomes for Disadvantaged Students. Washington, D.C.: The Hamilton Project, The Brookings Institution. Holzer, H. J., & Nightingale, D. S. (2009). Strong students, strong workers: models for student success through workforce development and community college partnerships. Washington, D.C.: Center for American Progress. Holzer, H. J., Lane, J. I., Rosenblum, D. B., & Andersson, F. (2010). Where are all the good jobs going? New York: Russell Sage Foundation. Jepsen, C., Troske, K., and Coomes, P. (2014), “The Labor-Market Returns to Community College Degrees, Diplomas, and Certificates,” Journal of Labor Economics, Vol. 32, No. 1, pp Stevens, D. and Zhang, T. (2014), “Toward A Case for Sustained Investment in State Longitudinal Integrated Data Systems,” U.S. DOL ETA. Ting Zhang Department of Finance and Economics, University of Baltimore Website: Phone:


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