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FOCUS AREAS

Econometrics and Time Series

The SAS® System includes powerful software for econometric and systems modeling, financial analysis and reporting, time series analysis and automatic forecasting, and access to commercially available economic and financial databases. You can specify, estimate, and simulate complex nonlinear models using simultaneous equations with dynamic or lagged relationships. You can create econometric models of the entire economy of a country or of individual market segments, physical models, biological models to simulate living processes, and ecological models to represent systems in nature. In addition, the software has new features for handling estimation and simulation of systems of first-order differential equations.

Econometric and Time Series Analysis

SAS/ETS® software provides tools for a wide variety of applications in business, government, and academia. It is designed for financial analysts working with business data in time series, forecasters constructing forecasts using time series techniques, and econometricians building complex economic models. SAS/ETS software is useful whenever it is necessary to analyze or predict processes that take place over time, such as analyzing pollution emissions data or modeling the dynamics of drug metabolism. Other applications are forecasting electricity demand, industrial production, and oil prices, planning inventories, monitoring thermal emissions, or analyzing the effect of drunk driving laws on highway accident rates.

Forecasting System

SAS/ETS software includes a point-and-click application for exploring and analyzing univariate time series data. You can use graphical and statistical techniques to select, fit, evaluate, and compare different forecasting models. Or use the automatic model selection facility to select the best-fitting model for each time series. The Time Series Forecasting System supports a wide range of models, including a variety of time trends, exponential smoothing, Winters method, interventions, ARIMA, and dynamic regression models.