Model, forecast and simulate complex economic and business scenarios using huge amounts of observational data. SAS Econometrics provides a broad array of econometric techniques to help you understand the impact that economic and marketplace factors have on your business so you can plan better for the future.
Demo
Explore the capabilities of SAS® Econometrics.
SAS Econometrics helps organizations model, forecast and simulate complex economic and business scenarios to plan for changing marketplace conditions. Learn about the software's powerful capabilities, including the new procedures and actions available in SAS Econometrics 8.2 – such as compound distribution modeling, regression models for spatial data, hidden Markov models and time series analysis. You'll also get an overview of how SAS works with open source technologies.
Key Features
- Hidden Markov models. Model and predict hidden Markov models (HMM) with the powerful new HMM procedure. The initial (8.2) release supports discrete-state Gaussian models, and many more model types will be added in subsequent releases. This method can handle very big data, scaling to millions of time points.
- Spatial econometrics modeling. Take advantage of data with a spatial element (e.g., location and mapping data) using the CSPATIALREG procedure to conduct spatial regressions. This enables you to include spatial information in your analysis, and improve the econometric inference and statistical properties of estimators.
- Econometric models for cross-sectional data. Conduct cross-sectional data analysis using the following included models: count regression, severity regression, qualitative and limited-dependent variables, and copula methods with compound distribution.
- Panel data econometric models. Analyze data that combines both time series and cross-sectional dimensions with these included models: panel data models, count regression models and regression models for qualitative and limited-dependent variables.
- Forecasting models for time series data. Use state-of-the-art techniques for modeling complex economic and business scenarios to analyze the impact that specific events might have over time. Time series models include user-defined ARIMA and exponential smoothing models. Time series analysis includes decomposition capabilities and diagnostic testing.
- Open, cloud-enabled, in-memory engine. Take advantage of high availability, faster in-memory processing and native cloud support of the SAS Viya engine. SAS Econometrics procedures are available for both public and private cloud delivery in a scalable and elastic environment. And all analytical assets are managed within a common environment to provide a single, governed model inventory across applications.
- Includes all SAS/ETS® procedures. SAS Econometrics provides access to all procedures in SAS/ETS, enabling you to address virtually any econometrics and time series analysis challenge.
This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.
Recommended Resources
Learn why SAS was named a Leader in The Forrester Wave™: Predictive Analytics and Machine Learning Solutions, Q1 2017.
Ask questions, share tips and more in the SAS Forecasting and Econometrics Community.
