SAS/ETS® Software Features

High-performance econometrics

  • Procedures enabled for high performance in a single-server SMP environment:
    • HPCOUNTREG for high-performance count regression.
    • HPSEVERITY for high-performance loss distribution/severity.
    • HPQLIM for high-performance qualitative and limited independent variable models.
    • HPCDM for high-performance compound distribution modeling.
    • HPCOPULA for high-performance Copula simulation.
    • HPPANEL for high-performance panel data models.
  • TMODEL (experimental) incorporates high-performance computing techniques and offers new features that enhance the functionality of PROC MODEL

      Cross-sectional econometric methods

      • Truncated regression (with Bayesian estimation options).
      • Censored regression (with Bayesian estimation options).
      • Bivariate probit.
      • Bivariate tobit.
      • Stochastic frontier production and cost models.
      • Multivariate limited dependent models.
      • Multivariate Bayesian econometric models.
      • Regression with heteroscedastic and autocorrelated consistent standard errors.
      • Sample selection and switching regression models.
      • Logit/probit with heteroscedastic errors.
      • Instrumental variables (2SLS, 3SLS, LIML, FIML, K-Class, MELO, GMM).
      • Seemingly unrelated regression (SUR, ISUR).
      • Multinomial/conditional logit.
      • Heteroscedastic extreme value model.
      • Mixed logit model.
      • Multinomial probit model.
      • Nested logit model.
      • Simulation and prediction tools.
      • Copula estimation and simulation.
      • Loss/severity modeling with censoring/truncation and regression effects.
      • Poisson (zero inflated Poisson) regression.
      • Negative binomial (zero inflated negative binomial) regression.
      • Qualitative and limited dependent variable models with endogenous explanatory variables.
      • Spatial econometric models.

          Time series analysis

          • ARIMA (ARIMAX) models.
          • Dynamic regression and transfer function models.
          • X-12-ARIMA.
          • Polynomial distributed lag models.
          • Unobserved components models.
          • Linear state space models.
          • Vector autoregressive models.
          • Vector error correction models.
          • Bayesian vector autoregressive models.
          • Vector autoregressive moving average models.
          • Multivariate GARCH models.
          • Exponential smoothing with optimized smoothing weights.
          • Spectral analysis.
          • Time series data mining tools.
          • Spectral and cross-spectral analysis.

          Panel data econometrics

          • Pooled and between estimators with robust standard errors.
          • One- and two-way fixed effects regression with robust standard errors.
          • One- and two-way random effects regression with robust standard errors.
          • Autoregressive and moving average models.
          • Dynamic panel GMM.
          • Poisson (zero inflated Poisson) with fixed/random effects.
          • Negative binomial (zero inflated negative binomial) with fixed/random effects.
          • Linear state space panel data model.

          Time series data tools

          • Transactional accumulation.
          • Seasonal adjustment.
          • X-11, X-12 seasonal adjustment.
          • Series imputation/extrapolation.
          • Time series frequency manipulation.
          • Time series differencing and transformations.

          Data acquisition tools

          • FAME, DRI, Standard & Poor's (COMPUSTAT), FactSet, Haver Analytics DLX and CRSP.
          • Bureau of Economic Analysis, Bureau of Labor Statistics.
          • Federal Reserve Economic Data (FRED).
          • International Monetary Fund (IMF), Organization for Economic Cooperation and Development (OECD), and World Bank Group Open.
          • Weather related databases: World Weather Online, NOAA Severe Weather Data Inventory (SWDI) web service.


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