AQA2-lab

This is the page is dedicated to the lab session of the course Applied Quantitative Analysis-II at New York University.

Applied Quantitative Analysis-II (AQA2)

AQA2 is a graduate-level core quantitative method course for the Master program Applied Quantitative Research at NYU Sociology. Professor Mike Hout is the main instructor, and I am the teaching assistant.

Contents

1. Review of regression analysis -- OLS, Logit, Probit basics
2. Generalized linear models -- Logit, Probit regression models, interpreting odds ratios
3. Interpreting regression results -- marginal effects of linear/non-linear equations, interaction effects
4. Latent variable regression -- single index model
5. Discrete choice model -- Ordered, Multi-nomial Logit/Probit models
6. Non-parametric estimations -- Kernel methods, Local Polinomials, Spline function
7. Regression partitioning and decompositions -- direct/indirect effects, omitted variable bias
8. Missing data issues -- MAR, MACR, MNAR, multiple imputations
9. Treatment effects -- counterfactuals, PS-matching
10. Panel data -- Pooled regression, GLS, Fixed/random effects, hierarchical models
11. Instrumental variables -- LATE, 2-stage-least-sqaures
12. Special topics: Time-series with covid-19 data