Walter R. Mebane Jr.
Faculty Associate, CPS
Professor, LSA Political Science
Professor, LSA Statistics
Walter Mebane Jr.'s current research focuses on election forensics, which describes a growing body of work devoted to using statistical methods to try to determine whether the results of an election are accurate. His current project "Positive Empirical Models of Election Frauds" attempts not only to estimate the incidence and magnitudes of any frauds that occur, but also to be able to recover what the election results would have been in the absence of frauds. This project will improve the Election Forensics Toolkit that was originally produced for the USAID.
- RIDIR: The Sub-National Data Archive System for Social and Behavioral Data. (Kenneth W. Kollman, Nahomi Ichino, Brian K. Min, Mai Hassan, Kevin Michael Quinn, M. Anne Pitcher, Robert J. Franzese Jr., Allen D. Hicken, Yuri Zhukov, Walter R. Mebane Jr., Yuki Shiraito, Christopher Jennings Fariss) 2019-2021. NSF.
- Election Forensics Statistical Testing. (Walter R. Mebane Jr.) 2018-2019.
- Libya Election Forensics. (Walter R. Mebane Jr.) 2017-2018. USAID.
- Positive Empirical Models of Election Frauds. (Walter R. Mebane Jr.) 2015-2019. National Science Foundation.
- Mebane Jr., Walter R. 2015. "Can Vote Counts' Digits and Benford's Law Diagnose Elections?" Pp. 212-222 in Benford's Law : Theory and Applications, edited by Miller, Steven J. Princeton: Princeton University Press.
- Mebane Jr., Walter R., and Paul Poast. 2013. "Causal Inference without Ignorability: Identification with Nonrandom Assignment and Missing Treatment Data." Political Analysis 21(2): 233-251.
- Mebane Jr., Walter R. 2011. "Comment on "Benford's Law and the Detection of Election Fraud"." Political Analysis 19(3): 269-272.
- Mebane Jr., Walter R., and Jasjeet S. Sekhon. 2011. "Genetic Optimization Using Derivatives: The rgenoud Package for R." Journal of Statistical Software 42(11): 1-26.