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.
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Harvey, A. (2018). State Space Models. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2269
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2269
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