Stata Empirical Research Guide | Regression Analysis, Panel Data and Causal Inference
How to write Stata empirical thesis? This guide covers Stata operations, regression analysis (OLS/Logit/Tobit), panel data models (fixed/random effects), instrumental variables, and causal inference.
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How to write Stata empirical thesis? This guide covers Stata operations, regression analysis (OLS/Logit/Tobit), panel data models (fixed/random effects), instrumental variables, and causal inference.
- Complete Stata workflow from data import to regression output
- Fixed effects vs random effects and Hausman test criteria
- Common model commands: Logit, Tobit, panel data
- Stata is the most popular software in econometrics and empirical research.
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Related workflows and reference pages
What this page helps you do first
- Complete Stata workflow from data import to regression output
- Fixed effects vs random effects and Hausman test criteria
- Common model commands: Logit, Tobit, panel data
Why is Stata preferred over SPSS for empirical papers
Stata is the most popular software in econometrics and empirical research. Its advantages over SPSS: reproducible commands (.do files); richer statistical methods especially for causal inference and panel data; stronger data processing capability for large-sample micro data.
Basic Stata operations
- [Import Excel] import excel "data.xlsx", sheet("Sheet1") firstrow
- [Descriptive statistics] summarize Y X1 X2 X3, detail
- [Correlation matrix] pwcorr Y X1 X2 X3, star(0.05)
- [OLS regression] regress Y X1 X2 X3, robust
- [Logit regression] logit Y X1 X2 X3, robust
Frequently asked questions
- Should I use robust standard errors in Stata regression?
- Almost always yes in empirical papers. Ordinary standard errors assume homoscedasticity, but real data almost always has heteroscedasticity. The robust option adjusts for this. Nearly all top journal empirical papers require robust standard errors.