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Stata

by StataCorp LLC · Application · also known as Stata/BE, Stata/SE, Stata/MP, StataNow

Commercial statistical software from StataCorp widely used in economics and social science, with editions BE/SE/MP, a command language, Mata and comprehensive PDF manuals

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Link verified Nov 2, 2026

Overview

Stata is StataCorp's commercial statistics package, a standard tool in economics, epidemiology and the social sciences. Users work through a command language in a console and do-files, complemented by menus and a graphical interface; the Mata matrix language supports programming. Its documentation is unusually complete: every installation includes more than thirty PDF manuals with methods, formulas and worked examples, covering base reference, data management, graphics, time series, panel data, causal inference and treatment effects, survival, structural equation modelling, Bayesian analysis, multiple imputation and, in recent releases, machine learning through H2O.

Stata 19 is the current release, with StataNow delivering features between releases. Three editions share one feature set and differ in dataset limits and parallelism: Stata/BE for mid-sized data, Stata/SE for larger data on a single core, and Stata/MP licensed per core count. All run on Windows, macOS and Linux, and licences are sold as annual or perpetual single-user, student and volume/campus arrangements with quotes for organizations.

Stata's strengths are reproducible do-files, a large user-written package ecosystem (SSC) and careful documentation; its limits are cost, the proprietary binary format and a single-dataset-in-memory model that makes very large data awkward compared with R or Python.

Capabilities

  • Command language with do-files and Mata programming
  • Panel, time-series and causal-inference estimators
  • Treatment effects, SEM, Bayesian and survival analysis
  • Publication graphics and customizable tables
  • Machine learning via H2O integration (Stata 19)
  • Multicore execution in Stata/MP
  • Extensive PDF documentation with methods and formulas
  • User-written packages via SSC

Typical workflows

  1. Panel regressions with clustered errors for an applied-economics paper
  2. Teaching introductory econometrics with do-files
  3. Difference-in-differences and treatment-effect estimation

Strengths

  • Thorough, consistent documentation
  • Reproducible scripts and stable syntax across versions
  • Large base of published replication code

Limitations

  • Commercial licence per user or core
  • Proprietary file format (.dta)
  • Single dataset in memory by default
  • Edition limits on variables and observations

Prerequisites

  • Licence (annual or perpetual)
  • Windows, macOS or Linux

Who it is for

  • Economists and social scientists
  • Epidemiologists and public-health researchers
  • Students in quantitative programs

Alternatives & comparison

R (with fixest) and Python's statsmodels are free, open-source alternatives with broader programming ecosystems; EViews is a comparable commercial package oriented to time-series forecasting; gretl is a free GUI econometrics program that can exchange data with Stata.

  • EViews

    Commercial Windows econometrics package for time-series estimation, forecasting and macro modelling, sold as single-user, volume, University and free Student Lite editions

    ProprietaryPaid
  • fixest

    R package for fast estimation of OLS, GLM, Poisson, IV and difference-in-differences models with many fixed effects, clustered errors, multiple estimations and publication tables

    Open sourceFree
  • gretl

    Free, GPL-licensed cross-platform econometrics program with a GUI, the hansl scripting language and estimators for time series, panels and limited dependent variables

    Open sourceFree
  • linearmodels

    Python package by Kevin Sheppard adding panel data, instrumental-variable, system (SUR/3SLS) and asset-pricing estimators missing from statsmodels

    Open sourceFree
  • R

    Language and environment for statistical computing and graphics, with the CRAN package archive and a strong base in academic statistics and econometrics

    Open sourceOpen source
  • statsmodels

    Python library for estimating statistical and econometric models with R-style formulas, rich result summaries and tests: OLS, GLM, discrete choice, ARIMA, state space, VAR and more

    Open sourceFree
Compare Stata with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

Confidence
High
Reviewed
Nov 1, 2026
Links
Verified · Nov 2, 2026

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