Econometric Modeling with Matlab. State-Space Models

By B Noriega

Econometrics Toolbox provides functions for modeling economic data. You can select and estimate economic models for simulation and forecasting. For time series modeling and analysis, the toolbox includes univariate Bayesian linear regression, univariate ARIMAX/GARCH composite models with several GARCH variants, multivariate VARX models, and cointegration analysis. It also provides methods for modeling economic systems using state-space models and for estimating using the Kalman filte. You can use a variety of diagnostics for model selection, including hypothesis tests, unit root, stationarity, and structural change.The more important topics in this book are the next: -"State-Space Models?" -"Kalman Filter?" -"Explicitly Create State-Space Model Containing Known Parameter Values"-"Create State-Space Model with Unknown Parameters" -"Create State-Space Model Containing ARMA State" -"Implicitly Create State-Space Model Containing Regression Component"-"Implicitly Create Diffus State-Space Model Containing Regression Component"-"Implicitly Create Time-Varying State-Space Model" -"Implicitly Create Time-Varying Diffus State-Space Model" -"Create State-Space Model with Random State Coefficient -"Estimate Time-Invariant State-Space Model" -"Estimate Time-Varying State-Space Model" -"Estimate Time-Varying Diffus State-Space Model" -"Estimate State-Space Model Containing Regression Component"-"Filter States of State-Space Model" -"Filter Time-Varying State-Space Model" -"Filter Time-Varying Diffus State-Space Model" -"Filter States of State-Space Model Containing Regression Component"-"Smooth States of State-Space Model" -"Smooth Time-Varying State-Space Model" -"Smooth Time-Varying Diffus State-Space Model" -"Smooth States of State-Space Model Containing Regression Component"-"Simulate States and Observations of Time-Invariant State-Space Model"-"Simulate Time-Varying State-Space Model" -"Simulate States of Time-Varying State-Space Model Using Simulation Smoother"-"Estimate Random Parameter of State-Space Model" -"Forecast State-Space Model Using Monte-Carlo Methods" -"Forecast State-Space Model Observations" -"Forecast Observations of State-Space Model Containing Regression Component"-"Forecast Time-Varying State-Space Model" -"Forecast State-Space Model Containing Regime Change in the Forecast Horizon"-"Forecast Time-Varying Diffus State-Space Model" -"Compare Simulation Smoother to Smoothed States" -"Rolling-Window Analysis of Time-Series Models" -"Assess State-Space Model Stability Using Rolling Window Analysis" -"Choose State-Space Model Specificatio Using Backtesting"

• Format: Paperback
• Language: English
• ISBN: 1799064182
• ISBN13: 9781799064183
• Release Date: January 1
• Publisher: Independently Published
• Length: 196 Pages
• Weight: 0.65 lbs.
• Dimensions: 0.5" x 6.0" x 9.0"