RATS Standard 7
Introduction
RATS provides an interactive editor that allows you to quickly experiment with different models or procedures, without having to repeat earlier steps each time, with the batch mode automatically able to read and execute instructions from one or more input files, and saves the output to disk.
Perform many estimation techniques such as, multiple regressions, including stepwise regressions with autoregressive errors and heteroscedasticity correction, Two-stage least squares for linear, non-linear, and autocorrelated models and Maximum likelihood estimation, supporting a wide variety of problems including ARCH, GARCH and related models. Also includes varying Time Series Procedures, forecasting models, high-quality time series graphs and X-Y scatter plots, with options including dual-scale graphs and multiple graphs per page, great import/export capabilities and easily customisable data transformations.
Estimation Techniques
- Multiple regressions including stepwise
- Regression with autoregressive errors
- Heteroscedasticity/serial-correlation correction, including Newey-West
- Non-linear least squares
- Two-stage least squares for linear, non-linear, and autocorrelated models
- ARCH and GARCH estimation (univariate and multivariate)
- Seemingly unrelated regressions and three-stage least squares
- Non-linear systems estimation
- Generalized Method of Moments
- Maximum likelihood estimation
- Constrained optimization
- Built-in hypothesis testing
- Logit and probit models
- Censored/truncated data
- Fixed/random effects estimators
- Non-parametric regressions
- Kernel density estimation
- Robust estimation
- Recursive least squares
- State-space models
- Neural network models
- Linear and quadratic programming
Time Series Procedures
- ARIMA models including multiplicative seasonal models, with support for arbitrary lag structures.
- Transfer function/intervention models
- Vector autoregressions, including structural VAR’s
- Impulse responses, variance decompositions
- Error correction models
- Kalman filter
- Spectral analysis
Forecasting
- Time series models
- Regression models
- Exponential smoothing
- Simultaneous equation models (unlimited number of equations)
- Simulations with random or user-supplied shocks
- Forecast performance statistics