Incentives for Digital Monitoring: A Privacy Model Restricted; Files Only

Langham, Ansley (Spring 2025)

Permanent URL: https://etd.library.emory.edu/concern/etds/xd07gv301?locale=en++PublishedPublished
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Abstract

As concerns grow about consumer data protection in the United States, prominent legal scholars have proposed the establishment of fiduciary duties, including a duty of loyalty, for companies that collect and use client data. This paper develops a stylized model to understand the ex-ante incentives of behavioral-advertising companies in the online marketplace when faced with information constraints. By considering and simulating how individuals’ distinct preferences over data-driven personalization might be aggregated by a firm (e.g. Meta), this thesis explores complications of and opportunities for information-restriction as a form of regulation in an increasingly-online world. 

Table of Contents

Table of Contents

Contents

1 Introduction 1

2 Context 3

2.1 The Politics of Data Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.2 Related Modeling Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3 The Model 9

3.1 Model Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.2 Maximizing Social Welfare With Uniform Ads . . . . . . . . . . . . . . . . . 11

3.3 Firm Observation of Prior With Uniform Ads . . . . . . . . . . . . . . . . . 12

3.4 Utility Functions For Customer-Indexed Ads . . . . . . . . . . . . . . . . . . 16

4 Simulations 17

4.1 Defining Ex-Ante Information Levels . . . . . . . . . . . . . . . . . . . . . . 17

4.2 Defining an Ensemble of Firm Strategies . . . . . . . . . . . . . . . . . . . . 19

4.3 Simulation Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4.4 Firm Payoffs for Unimodal Beta Distributions . . . . . . . . . . . . . . . . . 24

4.5 Varying Parameters for Customer Preference Distributions . . . . . . . . . . 28

5 Implications and Conclusion 31

6 Appendix 34

6.1 Additional Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

6.2 Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Bibliography 42

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