In recent years, the U.S. government has proposed substantial investments in the renewable energy and energy efficiency sectors as well as in educational and workforce training programs. While policymakers are moving ahead with policies targeting green job creation, there is little consensus on how green jobs may be defined, whether and how they can be measured, and how to evaluate the effect of public spending intended to increase their numbers. This thesis begins with a review of the literature on green jobs as well as literature on occupational choice, which will serve as the theoretical framework for the empirical work. It will then analyze employment trends using a two-sector model to investigate whether the private sector anticipates increased demand for green jobs. Probit and linear probability models are developed to relate green job definitions to age and other factors. The data used are from the 2003–2010 Annual Social and Economic Supplements to the Current Population Survey as published by the University of Minnesota’s Minnesota Population Center. The results of the models suggest that younger workers are not moving into green jobs faster than older workers, which implies that private sector workers do not anticipate increasing demand for green jobs. The primary conclusion is that more research is needed to suitably define green jobs before they can be adequately measured to evaluate public policy programs. Recommendations are made including a multi-dimensional gradient index for greenness of jobs for use in conjunction with existing occupational and industry classification codes.
|Advisor:||Carrington, William, Ferrara, Joseph|
|Department:||Public Policy & Policy Management|
|School Location:||United States -- District of Columbia|
|Source:||MAI 49/05M, Masters Abstracts International|
|Subjects:||Environmental economics, Labor economics, Public policy|
|Keywords:||Energy policy, Green collar jobs, Green jobs, Labor policy, Rational expectations, Regression analysis|
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