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Stata Code Library — Ready-to-Run Recipes
4 ready-to-run snippet(s) · curated with sample data, dataset sources & use cases
Econometrics🎓 Beginner
OLS Regression with Robust SELinear regression with heteroskedasticity-robust standard errors and esttab table.
EconometricsBeginner
OLS Regression with Robust SE
Linear regression with heteroskedasticity-robust standard errors and esttab table.
🎯 Use Case
Basic causal/descriptive regressions on micro/macro data.
👥 Audience
Econ undergrad/grad students; policy analysts.
Data to use with this code
wages.csv · csv
id,wage,educ,exper,female 1,12.5,12,5,1 2,18.7,16,8,0 3,9.3,10,3,1 4,22.4,18,12,0 5,14.1,12,6,1
clear all
set more off
import delimited "wages.csv", clear
reg wage educ exper female, vce(robust)
estimates store m1
esttab m1, b(3) se(3) star(* 0.10 ** 0.05 *** 0.01)📤 Expected Outputs
- Regression table with robust SEs
Econometrics🎓 Intermediate
Panel Fixed Effects (xtreg, fe)Two-way fixed effects panel regression with clustered SEs.
EconometricsIntermediate
Panel Fixed Effects (xtreg, fe)
Two-way fixed effects panel regression with clustered SEs.
🎯 Use Case
Country-year, firm-year, or district-year panels.
👥 Audience
Applied econometricians.
xtset id year
xtreg y x1 x2 i.year, fe vce(cluster id)
estat ic📤 Expected Outputs
- FE coefficients
- AIC/BIC
Health / Social🎓 Intermediate
Logistic Regression + Marginal EffectsLogit model with average marginal effects (margins, dydx).
Health / SocialIntermediate
Logistic Regression + Marginal Effects
Logit model with average marginal effects (margins, dydx).
🎯 Use Case
Binary outcomes — adoption, employment status, disease presence.
👥 Audience
Health and social science researchers.
logit outcome age i.sex educ income, vce(robust)
margins, dydx(*) post
esttab, b(3) se(3) star(* 0.10 ** 0.05 *** 0.01)📤 Expected Outputs
- Logit coefficients
- Average marginal effects
Public Health🎓 Advanced
DHS Survey Design + svy: tabDeclare DHS complex survey design and compute weighted prevalence.
Public HealthAdvanced
DHS Survey Design + svy: tab
Declare DHS complex survey design and compute weighted prevalence.
🎯 Use Case
Nationally representative estimates from DHS, MICS, LFS.
👥 Audience
Public health & demographic researchers.
Data to use with this code
gen wt = v005/1000000
svyset v021 [pweight=wt], strata(v023) singleunit(centered)
svy: tab v201 v025, row ci📤 Expected Outputs
- Weighted cross-tab with 95% CI
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