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

.

.a

.z

* 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

==

=

==

* WRONG — syntax error
gen employed = 1 if status = 1

* RIGHT
gen employed = 1 if status == 1

Local Macro Syntax

Locals use

`name'

$name

${name}

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.

c.

i.

* 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

replace

generate

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()

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

references/basics-getting-started.md

use

save

describe

browse

sysuse

references/data-import-export.md

import delimited

import excel

export

references/data-management.md

generate

replace

merge

append

reshape

collapse

recode

egen

encode

decode

references/variables-operators.md

byte

int

long

float

double

.<.a

if

in

references/string-functions.md

substr()

regexm()

strtrim()

split

ustrlen()

references/date-time-functions.md

date()

clock()

%td

%tc

mdy()

dofm()

references/mathematical-functions.md

round()

log()

exp()

abs()

mod()

cond()

Statistics & Econometrics

references/descriptive-statistics.md

summarize

tabulate

correlate

tabstat

codebook

references/linear-regression.md

regress

vce(robust)

vce(cluster)

test

lincom

margins

predict

ivregress

references/panel-data.md

xtset

xtreg fe

re

xtabond

references/time-series.md

tsset

dfuller

pperron

irf

references/limited-dependent-variables.md

logit

probit

tobit

poisson

nbreg

mlogit

ologit

margins

references/bootstrap-simulation.md

bootstrap

simulate

permute

references/survey-data-analysis.md

svyset

svy:

subpop()

references/missing-data-handling.md

mi impute

mi estimate

misstable

references/maximum-likelihood.md

ml model

ml init

references/gmm-estimation.md

gmm

estat overid

Causal Inference

references/treatment-effects.md

teffects ra/ipw/ipwra/aipw

stteffects

references/difference-in-differences.md

references/regression-discontinuity.md

rdplot

references/matching-methods.md

teffects nnmatch

references/sample-selection.md

heckman

heckprobit

Advanced Methods

references/survival-analysis.md

stset

stcox

streg

references/sem-factor-analysis.md

sem

gsem

alpha

references/nonparametric-methods.md

kdensity

qreg

npregress

references/spatial-analysis.md

spmatrix

spregress

references/machine-learning.md

lasso

elasticnet

cvlasso

Graphics

references/graphics.md

twoway

scatter

line

bar

histogram

graph combine

graph export

Programming

references/programming-basics.md

local

global

foreach

forvalues

program define

syntax

return

references/advanced-programming.md

syntax

mata

_prefix

tempfile

tempvar

references/mata-introduction.md

references/mata-programming.md

references/mata-matrix-operations.md

st_matrix()

references/mata-data-access.md

st_data()

st_view()

st_store()

Output & Workflow

references/tables-reporting.md

putexcel

putdocx

putpdf

collect

references/workflow-best-practices.md

references/external-tools-integration.md

python:

rsource

Community Packages

packages/reghdfe.md

packages/estout.md

esttab

estout

packages/outreg2.md

packages/asdoc.md

packages/tabout.md

packages/coefplot.md

packages/graph-schemes.md

grstyle

schemepack

plotplain

packages/did.md

csdid

did_multiplegt

did_imputation

packages/event-study.md

eventstudyinteract

eventdd

packages/rdrobust.md

rdrobust

rdplot

rdbwselect

packages/psmatch2.md

packages/synth.md

synth

synth_runner

packages/ivreg2.md

ivreg2

xtivreg2

packages/xtabond2.md

packages/binsreg.md

binsreg

binstest

packages/nprobust.md

packages/diagnostics.md

bacondecomp

xttest3

packages/winsor.md

winsor2

winsor

packages/data-manipulation.md

gtools

rangestat

egenmore

packages/package-management.md

ssc install

net install

ado update

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