Retirement Benefits and Teacher Retention: A Structural Modeling Approach

David Knapp ; Kristine M. Brown ; James Hosek ; Michael G. Mattock ; Beth J. Asch

RAND Corporation

RAND Corporation

关键词: Retirement and Retirement Benefits;    Chicago;    RAND-initiated;    Teachers and Teaching;    Education Policy;    Wages and Compensation;    Teacher Incentives;   

DOI  :  10.7249/RR1448
ISBN  :  9780833094513
RP-ID  :  RR-1448-RC

学科分类：自然科学（综合）

美国|英语

来源: RAND Corporation Published Research

【 摘 要 】

Recently, many state governments have legislated reductions in teachers' retirement benefits for new and future employees as a means of addressing the large unfunded liabilities of their pension plans. However, there is little existing capacity to predict how these unprecedented pension reforms — and, more broadly, changes to teacher compensation — will affect teacher turnover and teacher experience mix, which, in turn, could affect the cost and efficacy of the public education system. This research develops a modeling capability to begin filling that gap. The authors develop and estimate a stochastic dynamic programming model to analyze the relationship between compensation, including retirement benefits, and retention over the career of Chicago public school teachers. The structural modeling approach used was first developed at RAND for the purpose of studying the relationship between military compensation and the retention of military personnel and is called the dynamic retention model, or DRM. Although the peer-reviewed literature on teachers includes research on retirement benefits and the timing of retirement, the research does not model compensation and retention over the length of the career from entry to exit (into retirement or an alternative career), and it has limited capability to predict the effect of compensation and retirement benefit changes on retention. By comparison, the DRM is well suited to these tasks, and the DRM specification developed here for Chicago teachers fits their career retention profile well.