目次

Volume I Stata basics Data management and graphics Linear regression basics Linear regression extensions Simulation Linear regression with correlated errors Linear instrumental-variables regression Linear panel-data models: Basics Linear panel-data models: Extensions Introduction to nonlinear regression Tests of hypotheses and model specification Bootstrap methods Nonlinear regression methods Flexible regression: Finite mixtures and nonparametric Quantile regression Programming in Stata Mata Optimization in Mata Volume II Nonlinear optimization methods Binary outcome models Multinomial models Tobit and selection models Count-data models Survival analysis for duration data Nonlinear panel models Parametric models for heterogeneity and endogeneity Randomized control trials and exogenous treatment effects Endogenous treatment effects Spatial regression Semiparametric regression Machine learning for prediction and inference Bayesian methods: Basics Bayesian methods: Markov chain Monte Carlo algorithms