Dislocated Worker Human Capital Depreciation and Recovery

Previous studies have estimated the human capital depreciation of women re-entering the work force after voluntary, lengthy interruptions. Those studies have found reduced real wages and furthermore the decrease is positively related to the length of the interruption. Upon re-entry, however, real wages grow rapidly as human capital is restored. This paper develops a model of the wage histories of dislocated workers. Similar to labor force re-entrants, those dislocated workers who become re-employed would experience wages below their final wage prior to dislocation and the decrease should be associated with the length of dislocation. However, the model suggests that since the career disruptions are involuntary and since occupational shifts generally occur, recovery will not be rapid nor complete. The model is estimated with data from a sample of workers in Ohio who had been dislocated and received services under Title III of the Job Training Partnership Act (JTPA). This data set has the limitation that the observations are for workers who chose to receive services, but it also has the advantage that the effects of a variety of training interventions on outcomes can be determined

Student Loans and the Dynamics of Debt

The papers included in this volume represent the most current research and knowledge available about student loans and repayment. It serves as a valuable reference for researchers and policymakers who seek a deeper understanding of how, why, and which students borrow for their postsecondary education; how this borrowing may affect later decisions; and what measures can help borrowers repay their loans successfully.https://research.upjohn.org/up_press/1249/thumbnail.jp

Moving Beyond Niche Models: Habitat Suitability for Nesting White-Headed Woodpeckers

Ecological niche models of habitat suitability are attractive due to their conceptual interpretation and use of presence-only data. Niche models have potential to exploit a variety of presence-only data sources, such as museum records, limited effort surveys, ancillary field observations, and citizen science programs. Limitations of niche models, however, substantially reduce their utility in management situations, in particular, the inability to independently evaluate habitat covariates for their relative influence. Generalized linear models, i.e., logistic regression, provide this ability, but require both presence and absence data. We present an approach that overcomes the limitation of niche models while retaining the use of presence-only data. The generation of pseudo-absences, derived from areas of low suitability as determined by the niche model, allow use of logistic regression to produce robust models of habitat suitability. The approach also has the added benefit of reducing contamination (false absences) among absence data that occurs with simple random sample approaches. We discuss the pseudo-absence approach in an example of modeling habitat suitability for nesting white-headed woodpeckers (Picoides albolarvatus)