; ; ; "ActiveFedora::Aggregation::ListSource" . a , ; "Instrumental Variable Estimators for State Space Models"; ; "batchuser@example.com"; "Aoki, Masanao"; "Federal Reserve Bank of Minneapolis"; "C32 - Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models", "O00 - Economic Development, Innovation, Technological Change, and Growth", "C52 - Model Evaluation, Validation, and Selection"; "The state vector in the innovation representation is asymptotically the most efficient instrumental variable estimator for the observation matrix C. The paper compares small sample properties of IV estimators for C, the dynamic matrix A and other matrices with the system theoretic estimators described in Aoki (1987) by a small scale Monte Carlo simulations. The IV estimators appear to be about the same as the system theoretic ones as far as their small sample properties are concerned. The covariance matrix of the state vector calculated from the IV point of view are also compared with the solutions of the Riccati equations. The simulation results show that they have quite similar sample means and standard deviations. This method of calculating the state vector covariance matrices may be computationally faster than solving the Riccati equation by the Schur decomposition algorithm."^^; "1989-11-01"; "2019-05-21T19:34:00.310724681+00:00"^^; "https://doi.org/10.21034/dp.19"; ; "https://creativecommons.org/licenses/by-nc/4.0/"; "Wed Apr 22 16:47:39 2020"; "https://creativecommons.org/licenses/by-nc/4.0/"; "Research Paper"; "31"; "Discussion paper (Federal Reserve Bank of Minneapolis. Institute for Empirical Macroeconomics)"; "019"; ; ; ; ; "Federal Reserve Bank of Minneapolis. Institute for Empirical Macroeconomics"; "Published in: Conte, G., A. M. Perdon, and B. Wyman, eds. _New Trends in Systems Theory_. Springer, 1991. https://doi.org/10.1007/978-1-4612-0439-8_8."^^; ; "Publication" . ; .