/stata

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`, `margi