{
  "slug": "stata",
  "name": "Stata",
  "aliases": ["Stata/BE", "Stata/SE", "Stata/MP", "StataNow"],
  "vendor": { "name": "StataCorp LLC", "slug": "statacorp", "website": "https://www.stata.com" },
  "homepage_url": "https://www.stata.com/",
  "docs_url": "https://www.stata.com/features/documentation/",
  "pricing_url": "https://www.stata.com/order/",
  "product_type": "application",
  "product_status": "active",
  "summary": "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",
  "description": "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.\n\nStata 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.\n\nStata'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"],
  "workflows": ["Panel regressions with clustered errors for an applied-economics paper", "Teaching introductory econometrics with do-files", "Difference-in-differences and treatment-effect estimation"],
  "advantages": ["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"],
  "audiences": ["Economists and social scientists", "Epidemiologists and public-health researchers", "Students in quantitative programs"],
  "alternatives": ["r", "statsmodels", "eviews", "gretl", "fixest"],
  "comparison_notes": "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.",
  "categories": [{ "slug": "math-stats-tools", "primary": true }, { "slug": "econometrics-causal-inference" }],
  "tags": ["econometrics", "causal-inference", "time-series", "macos"],
  "use_cases": ["estimate-causal-effects", "write-papers"],
  "operating_systems": ["windows", "macos", "linux"],
  "execution_modes": ["local"],
  "interfaces": ["desktop", "cli"],
  "deployment_models": ["desktop"],
  "integrations": ["H2O", "Python (PyStata)", "Java plugins", "ODBC", "SSC package archive"],
  "data_formats": [".dta", "CSV", "Excel", "SAS/SPSS import", "ODBC"],
  "languages": ["Stata", "Mata", "Python (via PyStata)"],
  "source_model": "proprietary",
  "pricing_model": ["paid", "academic", "enterprise"],
  "pricing_checked_at": "2026-11-02",
  "self_hostable": true,
  "sources": [
    { "url": "https://www.stata.com/", "type": "official_site", "title": "Statistical software for data science | Stata", "supports": ["name", "summary", "vendor", "capabilities"], "checked_at": "2026-11-02" },
    { "url": "https://www.stata.com/features/documentation/", "type": "official_docs", "title": "Documentation | Stata", "supports": ["capabilities", "docs_url"], "checked_at": "2026-11-02" },
    { "url": "https://www.stata.com/products/which-stata-is-right-for-me/", "type": "official_docs", "title": "Which Stata is right for me?", "supports": ["aliases", "operating_systems", "limitations"], "checked_at": "2026-11-02" },
    { "url": "https://www.stata.com/order/", "type": "pricing_page", "title": "Buy or upgrade Stata", "supports": ["pricing_model"], "checked_at": "2026-11-02" }
  ],
  "confidence": "high",
  "discovery_method": "editorial-research",
  "depth": "standard",
  "editorial_status": "reviewed",
  "visibility": "public",
  "featured": false,
  "author": "batch-E"
}