Email mikkel [at]
mikkel [at]
1 (510) 725-8297
Department of Economics
UC Berkeley
530 Evans Hall #3880
Berkeley, CA 94720-3880

I am a Ph.D. candidate in Economics at UC Berkeley.

I will be available for interviews at the AEA/ASSA Annual Meeting in Chicago (January 6-8, 2017). 

My research interest is in Econometrics.


This paper considers a new class of robust estimators in a linear instrumental variables (IV) model with many instruments. The estimators are generalized method of moments (GMM) estimators, and the class includes the limited maximum likelihood estimator (LIML) as a special case. Each estimator in the class is consistent and asymptotically normal under many instruments asymptotics, and this paper provides consistent variance estimators that are of the "sandwich" type and can be used to conduct asymptotically correct inference. Furthermore, this paper characterizes an optimal robust estimator among the members of the class. Compared to LIML, the optimal robust estimator is less influenced by outliers and more efficient under thick-tailed error distributions. In an empirical example (Angrist and Krueger, 1991), the optimal robust estimator is approximately 80% more efficient than LIML.


"Universal Investment in Infants and Long-run Health" (with Jonas Hjort and Miriam Wüst) (forthcoming in American Economic Journal: Applied Economics

Mikkel Sølvsten