Research
Working Papers
Behavioral - Experimental Economics
Abstract. A principal can influence an agent’s actions through monetary incentives (Mechanism Design) or Bayesian persuasion (Information Design). This paper provides an experimental comparison of the two incentive structures. In a theoretically equivalent setup principals extract higher rents by persuading than incentivizing agents. We find support for Bayesian persuasion in ID, however the equivalence breaks down in MD due to agents’ high monetary demands. Behavioral differences arise from the distinct nature of the contractual agreements in ID and MD, and differential perceptions of informational versus monetary compensations. Our findings motivate further theoretical comparisons and expose practical considerations in the two environments.
Info:
- Coauthors: Giorgio Coricelli & Alexander Vostroknutov
- Material: [Pdf] [Slides] [Online supplemental material]
- Under review at peer-reviewed journal.
- Awarded best third year paper award from the department of economics, USC
- Presented at the 93rd conference of the Western Economic Association International (WEAI)
- Presented at the 5th Workshop on Behavioral Game Theory of the University of East Anglia (UAE)
- Presented at the 2019 ESA North American Meetings at Loyola Marymount University (LMU)
Abstract. Skewness is pervasive across financial instruments, and the literature has documented that many investors seek idiosyncratic skewness in their portfolios. In response, there are some theoretical models that study implications of the preference for skewness, but using utility functions where the preference for right skewness is hard-wired. Drawing from status concerns, we derive a utility function reminiscent of Friedman and Savage (1948) that leads the investor to demand skewness –right or left skewness. We then consider a parsimonious set of securities that allow the investor to select the exact optimal level of right or left skewness. Our analysis yields a rich set of results broadly consistent with empirical observations.
Info:
- Coauthors: Suk Lee, Fernando Zapatero and Aleksandar Giga
- Material: [Draft in preparation]
Applied Microeconomics
Abstract. We examine the determinants of life satisfaction. While past literature has utilized reduced form cross-sectional and time-series models, we examine life satisfaction partly through a structural perspective. We propose a structural model of how an individual evaluates her life satisfaction as a linear combination of satisfaction with k domains of life, each of which is evaluated separately. Our main focus is on the modeling of satisfaction with income. In our model, individuals evaluate their income satisfaction as their ranking in a perceived income distribution. In this perceived income distribution, two critical components are the reference weights, representing the weight that the incomes of others play in one’s perception of incomes, and a memory function, rep- resenting the weight that past perceived income distributions play in one’s perceived income distribution. We apply this framework to an innovative dataset from the Gallup World Poll, which contains a number of vignettes describing life situations of hypothetical individuals. The model is used to explain how respondents rate the life satisfaction of the hypothetical individuals. As a result we are able to estimate the importance of relativity concerns and habit formation in determining the rating of life satisfaction. Simulations illustrate how life satisfactions in countries are affected by economic growth, income inequality and one’s position in the income distribution.
Info:
- Coauthor: Arie Kapteyn
- Material: [Pdf] [Slides]
- Presented at the 6th conference of the International Association of Applied Econometrics (IAAE)
- Presented (twice) at the USC department of economics, student brown-bag seminar.
Abstract. This paper aims for providing comprehensive understanding of the effect of affordable housing policy in the City of Los Angeles. In particular, we investigate the impact of affordable housing buildings on local neighborhood property prices. Despite its long history and importance, little is known about the locational choice of affordable housing and its impact on proximal neighborhoods. we combine extensive micro data with Geographic Information System (GIS) and modern econometric techniques to address this question. In summary, we find that the effect of affordable housing on house prices negative across LA, with a median impact of about -2.5%. The individual impacts vary widely affordable housing project, with an inter-quartile range of -20% to +10%. The most extreme impacts are not evenly distributed across LA. The highest positive impacts occur near East Hollywood while the hardest-hit neighborhoods are in Downtown LA by Skid Row. Median house price impacts vary considerably across Council Districts. Senior Housing projects have no effect on property prices, while Large Family and Special Needs projects have negative effects on nearby houses of about -5% and -15%, respectively. Affordable housing projects constructed in the early 2000’s impact neighborhoods more negatively than recently built developments. Finally, size matters as the effect on neighborhood house prices worsens as the number of units within the affordable housing project increases. This unit-impact effect is particularly strong for Special Needs – type affordable housing which caters towards drug rehabilitation and homelessness.
Info:
- Coauthors: Rashad Ahmed, Mathew Kahn & Eunjee Kwon
- Material: [Report for the City of Los Angeles] [Slides]
- Presented at the Los Angeles city hall as a report for the city of LA
- Presented at the Data Science Federation of Los Angeles meeting as a report for the city of LA
Work in progress
Abstract. Coordination problems represent some of the main causes of efficiency losses in most societies. Previous studies have shown that experimental subjects fail to utilize recommendations, communication, or even informative signals as coordination devices. In this paper, we explore experimentally how two different priming phases (Training or Frustration) may boost participants’ subsequent coordination using an unindicative sunspot. We use as a coordination environment the repeated ‘Battle of the Sexes’ game with random matching. Due to low participant numbers and restrictions on the number of periods we could implement we fail to get significant results, however we do observe that priming participants using an initial training period significantly boosts their subsequent coordination in the latter stages of the experiment.
Info:
- Coauthors: Isabel Onate & Xiaoyu Zhou
- Material: New experiment being designed [Draft available upon request]
Interdisciplinary works (with colleagues from CS and Psychology)
Abstract. The rise of massive academic digital archives, fed by a “publish or perish” academic culture, has given us an opportunity to understand the dynamics of academic discourse. Here we present a publication corpus representing at least 100 of the most prominent researchers across economics, psychology, and computer science, and a supplemental abstract corpus covering additional authors. We demonstrate that differences between disciplines, previously studied with network and content-based approaches, also manifest in different writing styles and behavioral signatures.
Info:
- Coauthors: Matt Baucum, Nathan Bartley, Mohammad Atari
- Material: [Pdf] [Poster]
- Awarded best class paper award in CSCI 626
- Presented at SPSP 2018 Psychology of Language preconference (by Mohammad Atari)
Abstract. As computer scientists turn their expertise toward building systems with social good applications, it is important that just, or fair, decision making is part of the design process. It is also important to give policy makers the ability to view and consider the tradeoffs between accuracy and fairness that must be made when making decisions with a biased dataset. In this paper, we define a concept called α-fairness, which is a way to communicate how much fairness is enforced. We then propose and implement a framework which uses α-fairness to adaptively illustrate the tradeoffs of accuracy and fairness, which we define as statistical parity for the sake of this paper. The model is adaptive in that it can be trained just once and then run on any test set at an arbitrary level of α without being retrained.
Info:
- Coauthors: Sarah Cooney, Hanpeng Liu, Shunsuke Saito & Seb Arnold
- Material: [Slides]
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