Teaching
Instructor - Columbia University
Data Analysis for Policy and Decision Making II
This is an intermediate-level course in non-experimental quantitative research methods, especially those related to education policy. The class examines such topics as residual analysis, modeling non-linear relationships and interactions using regression, logistic regression, missing data analyses, multilevel models, and principal components analysis. The course interweaves several concepts: framing research questions; using moderately advanced statistical approaches; learning to manipulate a large-scale longitudinal database; designing empirical tests to examine policy issues with appropriate statistical techniques; and interpreting and conveying research results to diverse audiences.
Teaching Assistant - Columbia University
Quantitative Methods for Evaluating Education Policies and Programs
Data Analysis for Policy and Decision Making II
Teaching Assistant - Universidad de Chile
Labor Market & Labor Economics
Issues in Social Project Evaluation
Econometrics I
Economics 101
Labor Economics
Labor Economics
Calculus II