Francesca Molinari is an Italian economist and economic statististician specializing in theoretical and applied econometrics, whose research topics include risk aversion, survey methodology, and set identification. She is H. T. Warshow and Robert Irving Warshow Professor of Economics and Professor of Statistics at Cornell University.[1]

Education and career

Molinari earned a laurea in economics from the University of Turin in 1997, a master's degree from CORIPE Piemonte in 1998, and a Ph.D. from Northwestern University in 2003.[1] Her dissertation, Contaminated, Corrupted, and Missing Data, was supervised by Charles F. Manski.[2] It won the Arnold Zellner Thesis Award in Econometrics and Statistics of the Business and Economic Statistics Section of the American Statistical Association.[3]

She became an assistant professor of economics at Cornell University in 2003, was tenured as an associate professor in 2009, added a joint appointment in statistics in 2013, and was promoted to full professor in 2014. She was given the H. T. Warshow and Robert Irving Warshow Professorship in 2017.[1]

Book

With Ilya Molchanov, Molinari is the coauthor of the book Random Sets in Econometrics (Econometric Society Monographs, 60, Cambridge University Press, 2018).[4]

Recognition

Molinari was elected as a Fellow of the International Association for Applied Econometrics in 2019,[5] and as a Fellow of the Econometric Society in 2020.[6]

References

  1. 1 2 3 Curriculum vitae (PDF), June 2021, retrieved 2021-07-15
  2. Francesca Molinari at the Mathematics Genealogy Project
  3. "Arnold Zellner Thesis Award in Econometrics and Statistics", Business and Economic Statistics Section, American Statistical Association, retrieved 2021-07-15
  4. Reviews of Random Sets in Econometrics: Schmidt, Hans-Jürgen, Zbl 06854451; Stoleriu, Iulian, MR3753715
  5. Fellows, International Association for Applied Econometrics, retrieved 2021-07-15
  6. The Econometric Society Announces its 2020 Fellows, Econometric Society, retrieved 2021-07-15
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.