Agricultural Economics Department

 

Date of this Version

8-2016

Citation

Bader, Jordyn. 2016. "The Influence of Projection Bias on Outcomes of Healthcare Financial Incentive Programs." Master's thesis, University of Nebraska–Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agricultural Economics, Under the Supervision of Professor Christopher Gustafson. Lincoln, Nebraska: August 2016

Copyright (c) 2016 Jordyn Bader

Abstract

This thesis contributes to the behavioral health literature and literature regarding healthcare financial incentive programs by discussing the influences of the behavioral economic concept of projection bias on programs designed to recruit healthcare providers to rural or under served areas. First, I propose an adaptation to the model of projection bias by introducing a term that captures variability in individuals’ propensity to exhibit projection bias based on the amount of effort expended in predicting future preferences. Next, I conduct a probit model regression to observe what incentive program design features and participant characteristics are likely to influence the probability of exhibiting projection bias and therefore affect the efficacy of two incentive programs. Results suggest that incentive programs targeted to students are more likely to experience higher magnitudes of projection bias among participants, resulting in higher default rates, compared to professional-targeted programs. This is potentially due to the temporal gap, or length of time between when an individual decides to participate in the incentive program, thereby agreeing to practice in a shortage area in the future, and carrying out the service obligation. Furthermore, within the student-targeted program, the longer the training of participants, the more prone they are to exhibit projection bias and default on their obligation. This research also includes a survival analysis to identify what variables are related to a longer length of practice in one’s initial shortage area.

Advisor: Christopher Rand Gustafson

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