Our mission is to create and make accessible novel data on the dynamics of the labor markets, we work with research networks and statistical agencies, developing appropriate statistics to inform policy makers, researchers, and simply people seeking knowledge. We emphasize and meet the requirements of stakeholders: users as well as providers, balancing the utility of the data with the confidentiality of the people and businesses whose activities the data describe.
Labor Dynamics Institute
Latest News
Assistant Copy Editor for the Journal of Privacy and Confidentiality
JPC Vol 9 Issue 1 just published
Closed: LDI Replication project hiring Undergraduate Researchers for Summer 2019
Journal of Privacy and Confidentiality
Models of Linked Employer-Employee Data
Dec 21, 2018
Friday, December 21, 2018
LDI graduate researcher in the European Central Bank's Summer Graduate Research Programme
LDI Research
NSF-Census Research Network - Cornell node
The Labor Dynamics Institute and partners have embarked on a number of projects as part of the NSF-Census Research Network. Our node's research focuses on data curation and metadata exploration models in the presence of distributed (and secure) curation of confidential data, and on new models using computational statistics algorithms based on boosting to improve the integration, editing, and imputation models that assemble the micro-data used in the Census Bureau's longitudinally linked employer-employee database. Read more...
NSF-Census Research Network - Coordinating Office
In addition to hosting one of the NCRN nodes, LDI and NISS are the Network's Coordinating Office (NCRN-CO). The NCRN-CO is a value-added activity, helping the NCRN nodes to leverage each other's research achievements and leading to scientific and societal impact that exceeds the sum of the individual impacts. Read more...
Synthetic Data Server
The Synthetic Data Server makes synthetic data products by the U.S. Census Bureau available to interested researchers in a controlled environment. Read on...
Recent Documents from LDI
- How Protective Are Synthetic Data?
This short paper provides a synthesis of the statistical disclosure limitation and computer science data privacy...
Thu, Jun. 13, 2019 - metajelo: A Metadata Package for Journals to Support External Linked Objects
We propose a metadata package that is intended to provide academic journals with a lightweight means of registering,...
Thu, Apr. 11, 2019 - Why the Economics Profession Must Actively Participate in the Privacy Protection Debate
When Google or the U.S. Census Bureau publish detailed statistics on browsing habits or neighborhood characteristics,...
Tue, Mar. 05, 2019