The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

State Space Models

  • Andrew Harvey
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2269

Abstract

The state space form opens the way to the statistical treatment of a wide range of dynamic models in a unified framework. For models formulated in unobserved components it offers algorithms for filtering, signal extraction and prediction. Data irregularities can be handled and recent work on computational methods has extended the range of nonlinear and non-Gaussian models that can be adopted for practical use.

Keywords

ARIMA models Dynamic stochastic general equilibrium (DSGE) models Finite sample computation Hodrick–Prescott filter International Labor Organization (ILO) Kalman filter Linear rational expectations model Markov chain Monte Carlo Maximum likelihood Mean square errors Missing observations Nowcasting Output gap Particle filtering Phillips curve Prediction Smoothing State space form State space models State vector Stochastic volatility models Structural time series models Wiener–Kolomogorov (WK) filter 

JEL Classifications

D4 D10 C22 C23 C51 
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Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Andrew Harvey
    • 1
  1. 1.