Chapters
1
Getting Started: Interface, Do-Files, Log Files
Navigate the Stata environment, write reproducible do-files, and capture output with log files.
2
Data Management: Import, Clean, Reshape
Import data from multiple formats, handle missing values, reshape between long and wide, and merge datasets.
3
Descriptive Statistics & Visualization
Summarize data with tabstat, create publication-quality tables, and build histograms, scatter plots, and combined graphs.
4
Linear Regression: OLS & Diagnostics
Estimate OLS models, test for heteroskedasticity and omitted variables, compute VIF, and interpret residual plots.
5
Panel Data Methods: FE, RE, Hausman
Declare panel structure with xtset, estimate fixed and random effects, run Hausman tests, and use reghdfe for high-dimensional FE.
6
Instrumental Variables & Endogeneity
Implement 2SLS with ivregress, test for weak instruments, run overidentification tests, and use ivreg2 for robust IV estimation.
7
Limited Dependent Variables
Estimate logit, probit, tobit, and multinomial models. Compute marginal effects and interpret coefficients correctly.
8
Time Series & Forecasting
Set up time-series data, use lag and difference operators, estimate ARIMA and VAR models, and test for unit roots.
9
Causal Inference: DID, RDD, Matching
Implement difference-in-differences, regression discontinuity, and propensity score matching with modern Stata packages.
10
Advanced Topics: GMM, SFA, Heckman
Estimate GMM with xtabond2, stochastic frontier models, Heckman selection corrections, and bootstrap inference.