@TechReport{	  it:2022-008,
  author	= {Torsten S{\"o}derstr{\"o}m and Umberto Soverini},
  title		= {Analyzing the Parameter Bias when an Instrumental Variable
		  Method is Used with Noise-Corrupted Data},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Systems and Control},
  year		= {2022},
  number	= {2022-008},
  month		= oct,
  abstract	= {When an output error model is fitted to data with
		  noise-corrupted inputs using a prediction error method, a
		  bias occurs. It was previously shown that the bias is of
		  order $O(1/\delta)$ for a small pole-zero separation
		  $\delta$. These notes examine the same problem when an
		  instrumental variable model is fitted. A similar result is
		  shown to hold for the instrumental variable case.}
}