By name: stata description: > Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 17+ community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code. triggers: - stata - .do file - do-file - regress - regression in stata - panel data - fixed effects - reghdfe - estout - esttab - outreg2 - difference-in-differences - event study - propensity score - rdrobust - synthetic control - xtset - merge - reshape - collapse - egen - ssc install - mata - putexcel - putdocx - graph export - survival analysis - heckman - tobit - logit - probit - arima - var model - gmm estimation - bootstrap stata - survey weights - multiple imputation - lasso stata
Stata Skill
You have access to comprehensive Stata reference files. Do not load all files. Read only the 1-3 files relevant to the user's current task using the routing table below.
Critical Gotchas
These are Stata-specific pitfalls that lead to silent bugs. Internalize these before writing any code.
Missing Values Sort to +Infinity
Stata's . (and .a-.z) are greater than all numbers.
* WRONG — includes observations where income is missing!
gen high_income = (income > 50000)
* RIGHT
gen high_income = (income > 50000) if !missing(income)
* WRONG — missing ages appear in this list
list if age > 60
* RIGHT
list if age > 60 & !missing(age)
= vs ==
= is assignment; == is comparison. Mixing them up is a syntax error or silent bug.
* WRONG — syntax error
gen employed = 1 if status = 1
* RIGHT
gen employed = 1 if status == 1
Local Macro Syntax
Locals use `name' (backtick + single-quote). Globals use $name or ${name}.
Forgetting the closing quote is the #1 macro bug.
local controls "age education income"
regress wage `controls' // correct
regress wage `controls // WRONG — missing closing quote
regress wage 'controls' // WRONG — wrong quote characters
by Requires Prior Sort (Use bysort)
* WRONG — error if data not sorted by id
by id: gen first = (_n == 1)
* RIGHT — bysort sorts automatically
bysort id: gen first = (_n == 1)
* Also RIGHT — explicit sort
sort id
by id: gen first = (_n == 1)
Factor Variable Notation (i. and c.)
Use i. for categorical, c. for continuous. Omitting i. treats categories as continuous.
* WRONG — treats race as continuous (e.g., race=3 has 3x effect of race=1)
regress wage race education
* RIGHT — creates dummies automatically
regress wage i.race education
* Interactions
regress wage i.race##c.education // full interaction
regress wage i.race#c.education // interaction only (no main effects)
generate vs replace
generate creates new variables; replace modifies existing ones. Using generate on an existing variable name is an error.
gen x = 1
gen x = 2 // ERROR: x already defined
replace x = 2 // correct
String Comparison Is Case-Sensitive
* May miss "Male", "MALE", etc.
keep if gender == "male"
* Safer
keep if lower(gender) == "male"
merge Always Check _merge
merge 1:1 id using other.dta
tab _merge // always inspect
assert _merge == 3 // or handle mismatches
drop _merge
preserve / restore for Temporary Changes
preserve
collapse (mean) income, by(state)
* ... do something with collapsed data ...
restore // original data is back
Weights Are Not Interchangeable
fweight— frequency weights (replication)aweight— analytic/regression weights (inverse variance)pweight— probability/sampling weights (survey data, implies robust SE)iweight— importance weights (rarely used)
capture Swallows Errors
capture some_command
if _rc != 0 {
di as error "Failed with code: " _rc
exit _rc
}
Line Continuation Uses ///
regress y x1 x2 x3 ///
x4 x5 x6, ///
vce(robust)
Stored Results: r() vs e() vs s()
r()— r-class commands (summarize, tabulate, etc.)e()— e-class commands (estimation: regress, logit, etc.)s()— s-class commands (parsing)
A new estimation command overwrites previous e() results. Store them first:
regress y x1 x2
estimates store model1
Routing Table
Read only the files relevant to the user's task. Paths are relative to this SKILL.md file.
Data Operations
| File | Topics & Key Commands |
|---|---|
references/basics-getting-started.md |
use, save, describe, browse, sysuse, basic workflow |
references/data-import-export.md |
import delimited, import excel, ODBC, export, web data |
references/data-management.md |
generate, replace, merge, append, reshape, collapse, recode, egen, encode/decode |
references/variables-operators.md |
Variable types, byte/int/long/float/double, operators, missing values (.<.a), if/in qualifiers |
references/string-functions.md |
substr(), regexm(), strtrim(), split, ustrlen(), regex, Unicode |
references/date-time-functions.md |
date(), clock(), %td/%tc formats, mdy(), dofm(), business calendars |
references/mathematical-functions.md |
round(), log(), exp(), abs(), mod(), cond(), distributions, random numbers |
Statistics & Econometrics
| File | Topics & Key Commands |
|---|---|
references/descriptive-statistics.md |
summarize, tabulate, correlate, tabstat, codebook, weighted stats |
references/linear-regression.md |
regress, vce(robust), vce(cluster), test, lincom, margins, predict, ivregress |
references/panel-data.md |
xtset, xtreg fe/re, Hausman test, xtabond, dynamic panels |
references/time-series.md |
tsset, ARIMA, VAR, dfuller, pperron, irf, forecasting |
references/limited-dependent-variables.md |
logit, probit, tobit, poisson, nbreg, mlogit, ologit, margins for nonlinear |
references/bootstrap-simulation.md |
bootstrap, simulate, permute, Monte Carlo |
references/survey-data-analysis.md |
svyset, svy:, subpop(), complex survey design, replicate weights |
references/missing-data-handling.md |
mi impute, mi estimate, FIML, misstable, diagnostics |
references/maximum-likelihood.md |
ml model, custom likelihood functions, ml init, gradient-based optimization |
references/gmm-estimation.md |
gmm, moment conditions, estat overid, J-test |
Causal Inference
| File | Topics & Key Commands |
|---|---|
references/treatment-effects.md |
teffects ra/ipw/ipwra/aipw, stteffects, ATE/ATT/ATET |
references/difference-in-differences.md |
DiD, parallel trends, event studies, staggered adoption |
references/regression-discontinuity.md |
Sharp/fuzzy RD, bandwidth selection, rdplot |
references/matching-methods.md |
PSM, nearest neighbor, kernel matching, teffects nnmatch |
references/sample-selection.md |
heckman, heckprobit, treatment models, exclusion restrictions |
Advanced Methods
| File | Topics & Key Commands |
|---|---|
references/survival-analysis.md |
stset, stcox, streg, Kaplan-Meier, parametric models |
references/sem-factor-analysis.md |
sem, gsem, CFA, path analysis, alpha, reliability |
references/nonparametric-methods.md |
kdensity, rank tests, qreg, npregress |
references/spatial-analysis.md |
spmatrix, spregress, spatial weights, Moran's I |
references/machine-learning.md |
lasso, elasticnet, cvlasso, cross-validation |
Graphics
| File | Topics & Key Commands |
|---|---|
references/graphics.md |
twoway, scatter, line, bar, histogram, graph combine, graph export, schemes |
Programming
| File | Topics & Key Commands |
|---|---|
references/programming-basics.md |
local, global, foreach, forvalues, program define, syntax, return |
references/advanced-programming.md |
syntax, mata, classes, _prefix, dialog boxes, tempfile/tempvar |
references/mata-introduction.md |
Mata basics, when to use Mata vs ado, data types |
references/mata-programming.md |
Mata functions, flow control, structures, pointers |
references/mata-matrix-operations.md |
Matrix creation, decompositions, solvers, st_matrix() |
references/mata-data-access.md |
st_data(), st_view(), st_store(), performance tips |
Output & Workflow
| File | Topics & Key Commands |
|---|---|
references/tables-reporting.md |
putexcel, putdocx, putpdf, LaTeX integration, collect |
references/workflow-best-practices.md |
Project structure, master do-files, version control, debugging, common mistakes |
references/external-tools-integration.md |
Python via python:, R via rsource, shell commands, Git |
Community Packages
| File | What It Does |
|---|---|
packages/reghdfe.md |
High-dimensional fixed effects OLS (absorbs multiple FE sets efficiently) |
packages/estout.md |
esttab/estout: publication-quality regression tables |
packages/outreg2.md |
Alternative regression table exporter (Word, Excel, TeX) |
packages/asdoc.md |
One-command Word document creation for any Stata output |
packages/tabout.md |
Cross-tabulations and summary tables to file |
packages/coefplot.md |
Coefficient plots from stored estimates |
packages/graph-schemes.md |
grstyle, schemepack, plotplain — better graph themes |
packages/did.md |
Modern DiD: csdid, did_multiplegt, did_imputation (Callaway-Sant'Anna, de Chaisemartin-D'Haultfoeuille, Borusyak-Jaravel-Spiess) |
packages/event-study.md |
eventstudyinteract, eventdd — event study estimators |
packages/rdrobust.md |
Robust RD estimation with optimal bandwidth (rdrobust, rdplot, rdbwselect) |
packages/psmatch2.md |
Propensity score matching (nearest neighbor, kernel, radius) |
packages/synth.md |
Synthetic control method (synth, synth_runner) |
packages/ivreg2.md |
Enhanced IV/2SLS: ivreg2, xtivreg2 with additional diagnostics |
packages/xtabond2.md |
Dynamic panel GMM (Arellano-Bond/Blundell-Bond) |
packages/binsreg.md |
Binned scatter plots with CI (binsreg, binstest) |
packages/nprobust.md |
Nonparametric kernel estimation and inference |
packages/diagnostics.md |
bacondecomp, xttest3, collinearity, heteroskedasticity tests |
packages/winsor.md |
Winsorizing and trimming: winsor2, winsor |
packages/data-manipulation.md |
gtools (fast collapse/egen), rangestat, egenmore |
packages/package-management.md |
ssc install, net install, ado update, finding packages |
Common Patterns
Regression Table Workflow
* Estimate models
eststo clear
eststo: regress y x1 x2, vce(robust)
eststo: regress y x1 x2 x3, vce(robust)
eststo: regress y x1 x2 x3 x4, vce(cluster id)
* Export table
esttab using "results.tex", replace ///
se star(* 0.10 ** 0.05 *** 0.01) ///
label booktabs ///
title("Main Results") ///
mtitles("(1)" "(2)" "(3)")
Panel Data Setup
xtset panelid timevar // declare panel structure
xtdescribe // check balance
xtsum outcome // within/between variation
* Fixed effects
xtreg y x1 x2, fe vce(cluster panelid)
* Or with reghdfe (preferred for multiple FE)
reghdfe y x1 x2, absorb(panelid timevar) vce(cluster panelid)
Difference-in-Differences
* Classic 2x2 DiD
gen post = (year >= treatment_year)
gen treat_post = treated * post
regress y treated post treat_post, vce(cluster id)
* Modern staggered DiD (Callaway & Sant'Anna)
csdid y x1 x2, ivar(id) time(year) gvar(first_treat) agg(event)
csdid_plot
Graph Export
* Publication-quality scatter with fit line
twoway (scatter y x, mcolor(navy%50) msize(small)) ///
(lfit y x, lcolor(cranberry) lwidth(medthick)), ///
title("Title Here") ///
xtitle("X Label") ytitle("Y Label") ///
legend(off) scheme(s2color)
graph export "figure1.pdf", replace as(pdf)
graph export "figure1.png", replace as(png) width(2400)
Data Cleaning Pipeline
* Load and inspect
import delimited "raw_data.csv", clear varnames(1)
describe
codebook, compact
* Clean
rename *, lower // lowercase all varnames
destring income, replace force // convert string to numeric
replace income = . if income < 0
* Label
label variable income "Annual household income (USD)"
label define yesno 0 "No" 1 "Yes"
label values employed yesno
* Save
compress
save "clean_data.dta", replace
Multiple Imputation
mi set mlong
mi register imputed income education
mi impute chained (regress) income (ologit) education = age i.gender, add(20) rseed(12345)
mi estimate: regress wage income education age i.gender