Doctoral Dissertation Research in Economics: Reference-Dependent Effort Provision under Heterogeneous Gain Loss Attitudes

University Of California-San Diego, La Jolla CA

Investigators

Abstract

Understanding how individuals make decisions in the face of uncertainty is a core issue in economic research. While earlier economic theory postulated full rationality, researchers have advanced upon these classical models by introducing the idea of reference-dependent decision making. These models, rooted in the intuition that individuals compare their outcomes to some reference point, have been used in a number of contexts, ranging from the putting behavior of professional golfers (Pope and Schweitzer, 2011) to the job search behavior of unemployed workers (DellaVigna et al, 2017). The original reference-dependent models suffered from one major drawback, however: in failing to specify a fixed reference point, they left open a substantial degree of freedom. Theoretical advancements sought to shut this downfix this problem, culminating in models of expectations-based reference dependence (notably, Koszegi and Rabin, 2006 – KR). By endogenizing the reference point as rational expectations, this model generated new and, testable implications, garnering mixed experimental support. However, these prior studies are potentially confounded by an assumption of universal loss aversion, in which outcomes falling below the reference point are assumed to feel worse than those above the reference point. Contrary to this assumption, empirical and experimental evidence suggests that roughly 30% of individuals are instead “gain -loving”.” Importantly, prior work by the authors suggests that a small minority of gain -loving participants can skew aggregate predictions of the model (Goette et al, 2019). In this project, the research team will provide additional evidence of how heterogeneity in these gain-loss attitudes confounds tests of KR, and design an experimental paradigm to overcome these confounds in the context of effort provision. A better understanding of the distribution of gain-loss preferences is particularly important when considering a number of key policy questions, as these reference-dependent models have proven to be invaluable in settings such as unemployment insurance and health insurance decisions. In order to accomplish the stated goals, this project will focus on updating an existing experimental paradigm so as to account for the confound ofthat is heterogeneity in gain-loss attitudes. A two-stage experiment is thus proposed, wherein a measure of the participant’s gain-loss attitude is recovered from first stage choices, and the hypothesis is tested in the second. Specifically, participants will first be asked questions of the form: “How many tasks are you willing to work at wage X?”. The wages will either be deterministic (e.g. 20 cents per task) or stochastic (e.g. with 50% chance, the wage will be 10 cents per task and with 50% chance it will be 30 cents per task). This variation will allow the authors to build a structural model and recover the key behavioral parameter of gain-loss attitudes alongside a cost of effort function. Participants are asked a slightly different question in the second stage, adapted from Abeler et al (2011): “How much are you willing to work if your wage is a 50% chance of 25 cents per task, and a 50% chance of Y dollars regardless of the number of tasks?”. The key treatment will be randomly varying Y from a small ($5) to a large amount ($20). KR predicts that loss averse agents should work harder as Y increases, while gain loving agents should work less hard. By using the previously measured gain-loss attitude, this project is able to directly test whether individuals with different preferences respond differently as predicted by the theory. The resulting evidence will help clarify the mixed results from the prior paradigm, as well as providing evidence of whether KR is predictive of behavior after controlling for the confounding heterogeneity in gain-loss attitudes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.