Instrumental Variables Estimation of Systems of Simultaneous Equations: Interrelation of Methods

Authors

  • Lyudmila O. Babeshko Department of Data Analysis, Decision-Making and Financial Technology, Financial University under the Government of the Russian Federation, Moscow
  • Vera V. Ioudina Department of Mathematics, Texas State University, San Marcos
  • Maria Y. Mikhaleva Department of Data Analysis, Decision-Making and Financial Technology, Financial University under the Government of the Russian Federation, Moscow
  • Irina V. Orlova Department of Data Analysis, Decision-Making and Financial Technology, Financial University under the Government of the Russian Federation, Moscow

DOI:

https://doi.org/10.6000/1929-7092.2019.08.69

Keywords:

System of simultaneous equations, instrumental variables method, parameter constraints, parameter estimates, autocovariance matrix of parameter estimates.

Abstract

The article is devoted to the interrelation between methods of estimating parameters of simultaneous equations. Simultaneous equations model (SEM) is commonly used to model complex socio-economic phenomena. SEM is a set of linear simultaneous equations in which response variables are among explanatory variables in each equation of regression. This causes the problem of endogeneity and leads to biased and inconsistent estimation of parameters. There is a number of special methods to solve the problem of endogeneity of regressors: method of instrumental variables (IV), indirect least squares method (ILS), two-stage least squares method (2SLS), and three-stage least squares method (3SLS). In this article, the relationship between 2SLS and IV, ILS and 2SLS, ILS and OLS with restrictions on structural parameters, as well as the equivalence of point estimates of parameters and autocovariance matrices, is shown using empirical example.

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Published

2019-10-02

How to Cite

Babeshko, L. O., Ioudina, V. V., Mikhaleva, M. Y., & Orlova, I. V. (2019). Instrumental Variables Estimation of Systems of Simultaneous Equations: Interrelation of Methods. Journal of Reviews on Global Economics, 8, 797–802. https://doi.org/10.6000/1929-7092.2019.08.69

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