This grant supports work by V. Joseph Hotz at Duke University, Ruobin Gong at Rutgers University, and Ian Schmutte at the University of Georgia, who are leading an initiative through the National Bureau of Economic Research (NBER) to support research on privacy-protecting methods of data analysis. Of particular interest are how different implementations of such methods manage the inevitable trade-off between privacy and accuracy. Grant funds will allow the team to commission 18 research papers, including an NBER working paper series and an NBER proceedings volume; organize two in-person conferences and two virtual meetings on topics surrounding the use of privacy-protected data in empirical research; and foster interactions among researchers in economics, statistics, and computer science. Funding will be used primarily to cover expenses associated both with the commissioned papers and with the research conferences.