| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w19433 |
| 来源ID | Working Paper 19433 |
| Privacy and Data-Based Research | |
| Ori Heffetz; Katrina Ligett | |
| 发表日期 | 2013-09-12 |
| 出版年 | 2013 |
| 语种 | 英语 |
| 摘要 | What can we, as users of microdata, formally guarantee to the individuals (or firms) in our dataset, regarding their privacy? We retell a few stories, well-known in data-privacy circles, of failed anonymization attempts in publicly released datasets. We then provide a mostly informal introduction to several ideas from the literature on differential privacy, an active literature in computer science that studies formal approaches to preserving the privacy of individuals in statistical databases. We apply some of its insights to situations routinely faced by applied economists, emphasizing big-data contexts. |
| 主题 | Econometrics ; Estimation Methods ; Data Collection ; Microeconomics ; Economics of Information ; Other ; Culture |
| URL | https://www.nber.org/papers/w19433 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/577109 |
| 推荐引用方式 GB/T 7714 | Ori Heffetz,Katrina Ligett. Privacy and Data-Based Research. 2013. |
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