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.
Highlights
Economic modeling that yields practical value must cater for effects caused by exogenous variables
Instrumental Variable Method is regarded as a preferential method to parametric estimation in ARX modeling
This paper presents an extended instrumental variable method (EIVM) which is based on multiple variables
Summary
Economic modeling that yields practical value must cater for effects caused by exogenous variables. Many linear models such as time series, regression and econometric models can describe the relationship between system inputs and outputs. Such systems reflect the simple relationship between cause and effect, are the result of Newtonian mechanical causation theory. ARX models were employed in regional economic administration in 2007 [4,5]. Our aim is to present 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
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