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On Discrete Sampling Of Time-Varying Continuous-Time Systems


  • Robinson, Peter M.


We consider a multivariate continuous-time process, generated by a system of linear stochastic differential equations, driven by white noise, and involving coefficients that possibly vary over time. The process is observable only at discrete, but not necessarily equally-spaced, time points (though equal spacing significantly simplifies matters). Such settings represent partial extensions of ones studied extensively by A.R. Bergstrom. A model for the observed time series is deduced. Initially we focus on a first-order model, but higher-order models are discussed in the case of equally-spaced observations. Some discussion of issues of statistical inference is included.

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  • Robinson, Peter M., 2009. "On Discrete Sampling Of Time-Varying Continuous-Time Systems," Econometric Theory, Cambridge University Press, vol. 25(04), pages 985-994, August.
  • Handle: RePEc:cup:etheor:v:25:y:2009:i:04:p:985-994_09

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    References listed on IDEAS

    1. Hillier, Grant H., 1987. "Classes of Similar Regions and Their Power Properties for Some Econometric Testing Problems," Econometric Theory, Cambridge University Press, vol. 3(01), pages 1-44, February.
    2. Kleibergen, Frank, 2007. "Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics," Journal of Econometrics, Elsevier, vol. 139(1), pages 181-216, July.
    3. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, July.
    4. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    5. Trevor S. Breusch, 1986. "Hypothesis Testing in Unidentified Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 635-651.
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