An Informational Theory of Privacy
Bibliographic Data
| ID | 9707601 |
|---|---|
| Authors | Ole Jann (0000-0002-6198-3819, CERGE-EI), Christoph Schottmüller (0000-0001-6059-1090, University of Cologne and TILEC) |
| Year | 2020 |
| Volume | 130 |
| Issue | 625 |
| Pages | 93-124 |
| Publication date | 2020-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Economic Journal (JOURNAL) |
| Journal identifiers | ISSN: 0013-0133 • E-ISSN: 1468-0297 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/ej/uez045 |
| OpenAlex | W2545148967 |
| Language | EN |
| References cited | 21 |
Privacy of consumers or citizens is often seen as an inefficient information asymmetry. We challenge this view by showing that privacy can increase welfare in an informational sense. It can also improve information aggregation and prevent inefficient statistical discrimination. We show how and when the different informational effects of privacy line up to make privacy efficient or even Pareto-optimal. Our theory can be applied to decide who should have which information and how privacy and information disclosure should be regulated. We discuss applications to online privacy, credit decisions and transparency in government
Business · Computer security · Economics · Information asymmetry · Information privacy · Internet privacy · Microeconomics · Pareto principle · Personally identifiable information · Privacy by Design · Privacy policy · Transparency (behavior · Auction Theory and Applications · Computer Science · Consumer Market Behavior and Pricing · Privacy, Security, and Data Protection
| Citation velocity | historical |
|---|---|
| Highly cited | No |