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M. Cedervall and P. Stoica, “System Identification from Noisy Measurements by Using Instrumental Variables and Subspace Fitting,” Circuits, Systems, and Signal Processing, Vol. 15, No. 2, 1996, pp. 275-290. doi:10.1007/BF01183780

has been cited by the following article:

• TITLE: Extending Instrumental Variable Method for Effective Economic Modelling

  AUTHORS: Shi Zheng, Xia Jin, Wen Zheng

  KEYWORDS: ARX Modeling; Parametric Estimation; Instrumental Variable Method; Northeastern Economy; Exogenous Variables

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.5 No.4, April 19, 2012

  ABSTRACT: Economic modeling that yields practical value must cater for effects caused by exogenous variables. AutoRegressive eXogenous approach (ARX) has been widely used in regional economic studies. Instrumental Variable Method is regarded as a preferential method to parametric estimation in ARX modeling. However, traditional instrumental variable methods can only handle single variable which has limited its capability. This paper presents an extended instrumental variable method (EIVM) which is based on multiple variables. This provides the capability of taking into account of exogenous variables and reflects better the economic activities. A case study is conducted, which illustrates the application of the EIVM in modeling Northeastern economy in China.