Studies on the Data-Driven Economy and School Choice

PI Last Name: Che

Title: Studies on the Data-Driven Economy and School Choice

Proposal ID: 1851821

Abstract

The research consists of several projects. The first project looks at how data-driven recommendations inform our decisions and how decisions in turn affect what data is collected for the recommendations. This project is useful in understanding and evaluating the implications of the rapidly growing information technology and its use to guide our every day decisions. The developed framework also advances the knowledge on how internet platforms may collect data from individuals and use them to recommend products or to make hiring decisions. The second project looks at school applications by students and considers that students make mistakes in these applications. These mistakes in turn affect forecasting reforms in the application procedures. The third and fourth projects are theoretical tools that will be useful for researchers that work in related areas.

The first project develops a conceptual framework for understanding data-driven recommendations that increasingly guide our every-day decisions by considering the feedback mechanism between the recommendations and our decisions. Understanding this feedback process identifies the nature of externalities and potential inefficiencies, leading to deeper understanding and possible policy implications about the new markets guided by data-driven recommendations. The research also addresses the concern that the increasing reliance by employers on third-party algorithms to screen job candidates may adversely affect inclusion in employment. The second project advances mechanism design in school choice by considering that students make mistakes in applications and uses this framework for school matching based on rankings and lottery. The third and fourth projects advance the state-of-the-art research in dynamic persuasion and monotone comparative statics analysis topics that are of central interest in economic theory.

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.