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State Space Methods in RATS

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  • Doan, Thomas

Abstract

This paper uses several examples to show how the econometrics program RATS can be used to analyze state space models. It demonstrates Kalman filtering and smoothing, estimation of hyperparameters, unconditional and conditional simulation. It also provides a more complicated example where a dynamic simultaneous equations model is transformed into a proper state space representation and its unknown parameters are estimated.

Suggested Citation

  • Doan, Thomas, 2011. "State Space Methods in RATS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i09).
    • Handle: RePEc:jss:jstsof:v:041:i09
    DOI: http://hdl.handle.net/10.18637/jss.v041.i09
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    References listed on IDEAS

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    1. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874.
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    Cited by:

    1. William A. Barnett & Isaac Kalonda Kanyama, 2013. "Time-varying parameters in the almost ideal demand system and the Rotterdam model: will the best specification please stand up?," Applied Economics, Taylor & Francis Journals, vol. 45(29), pages 4169-4183, October.
    2. William A. Barnett & Isaac Kalonda Kanyama, 2013. "Time-varying parameters in the almost ideal demand system and the Rotterdam model: will the best specification please stand up?," Applied Economics, Taylor & Francis Journals, vol. 45(29), pages 4169-4183, October.
    3. Joseph Fairchild & Jun Ma & Shu Wu, 2015. "Understanding Housing Market Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(7), pages 1309-1337, October.

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