New developments in econometrics Guido Imbens, Harvard (website) and Jeffrey Wooldridge, Michigan State (website) 16 - 18 June 2009
Programme
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Presentation slides
Lecture 1: estimation of average treatment effects under unconfoundedness, part I
Lecture 2: estimation of average treatment effects under unconfoundedness, part II
Lecture 3: linear panel data models I
Lecture 4: linear panel data models II
Lecture 5: instrumental variables with treatment effectheterogeneity: local average treatment effects
Lecture 6: nonlinear panel data models
Lecture 7: cluster sampling
Lecture 8: discrete choice models
Lecture 9: stratified sampling
Lecture 10: partial identification
Lecture 11: difference-in-differences estimation
Lecture 12: regression discontinuity designs
Lecture 13: Bayesian inference
Lecture 14: control function and related methods
Lecture 15: weak instruments and many instruments
Lecture 16: quantile estimation
Lecture 17: generalized method of moments and empirical likelihood
Lecture 18: missing data
Lecture notes
Lecture notes 1: estimation of average treatment effects under unconfoundedness, part I
Lecture notes 2: estimation of average treatment effects under unconfoundedness, part II
Lecture notes 3: linear panel data models I
Lecture notes 4: linear panel data models II
Lecture notes 5: instrumental variables with treatment effectheterogeneity: local average treatment effects
Lecture notes 6: nonlinear panel data models
Lecture notes 7: cluster sampling
Lecture notes 8: discrete choice models
Lecture notes 9: stratified sampling
Lecture notes 10: partial identification
Lecture notes 11: difference-in-differences estimation
Lecture notes 12: regression discontinuity designs
Lecture notes 13: Bayesian inference
Lecture notes 14: control function and related methods
Lecture notes 15: weak instruments and many instruments
Lecture notes 16: quantile estimation
Lecture notes 17: generalized method of moments and empirical likelihood
Lecture notes 18: missing data
