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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Bibliography
Durbin, J., and S. Koopman. 2001. Time series analysis by state space methods. Oxford: Oxford University Press.
Harvey, A. 1989. Forecasting, structural time series models and Kalman filter. Cambridge: Cambridge University Press.
Harvey, A. 2006. Forecasting with unobserved components time series models. In Handbook of economic forecasting, vol. 1, ed. G. Elliot, C. Granger, and A. Timmermann. Amsterdam: North-Holland.
Harvey, A., and C.-H. Chung. 2000. Estimating the underlying change in unemployment in the UK (with discussion). Journal of the Royal Statistical Society, Series A 163: 303–339.
Harvey, A., and G. de Rossi. 2006. Signal extraction. In Palgrave handbook of econometrics, vol. 1, ed. K. Patterson and T. Mills. Basingstoke: Palgrave Macmillan.
Harvey, A., T. Trimbur, and H. van Dijk. 2007. Trends and cycles in economic time series: A Bayesian approach. Journal of Econometrics 140(2): 618–649.
Kohn, R., C. Ansley, and C.-H. Wong. 1992. Nonparametric spline regression with autoregressive moving average errors. Biometrika 79: 335–346.
Koopman, S., and A. Harvey. 2003. Computing observation weights for signal extraction and filtering. Journal of Economic Dynamics and Control 27: 1317–1333.
Kuttner, K. 1994. Estimating potential output as a latent variable. Journal of Business and Economic Statistics 12: 361–368.
Orphanides, A., and S. van Norden. 2002. The unreliability of output gap estimates in real-time. Review of Economics and Statistics 84: 569–583.
Pfeffermann, D. 1991. Estimation and seasonal adjustment of population means using data from repeated surveys. Journal of Business and Economic Statistics 9: 163–175.
Sargent, T. 1989. Two models of measurements and the investment accelerator. Journal of Political Economy 97: 251–287.
Smets, F., and R. Wouter. 2003. An estimated dynamic stochastic general equilibrium model of the euro area. Journal of the European Economic Association 1: 1123–1175.
Shephard, N. 2005. Stochastic volatility. Oxford: Oxford University Press.
Whittle, P. 1984. Prediction and regulation, 2nd ed. Blackwell: Oxford.
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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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