VERIFICATION OF AN ECONOMETRIC MODEL BASED ON A PRIORI CONSTRAINTS ON THE STRUCTURAL PARAMETERS
Abstract
The article describes a method for verification of a statistical model, which, firstly, is represented by the time series of original data and, secondly, is linear in the estimated parameters. Experience in statistical calculations on real empirical data shows that the most well-known and conventionally used in the econometric modeling of mathematical-statistical methods (least squares, maximum likelihood method, and similar methods) often do not ensure successful verification of theoretically required forms of econometric models. The developed method which is called an alternative method of linear regression (AMLR) provides an account of a priori restrictions on the absolute values and signs of the parameters identified by the model. The AMLR based on the concept of best linear index, is known in the theory of statistics from the end of the 1950s. Mathematically AMLR it based on the method of principal components. The article analyzes conditions for applying the AMLR in econometric modeling and methods of transformation of the initial statistical information to ensure correct application of the developed evaluation procedures.
Special problems of the proposed method are to determine the level of accuracy of approximation of the dependent variable of the model. In this regard, to assess the level of precision of the statistical model verifiable by using the AMLR, was developed an original method of decomposition of the time series on the regular and stochastic components. The author analyzes the properties of the proposed method of decomposition and gave a numerical illustration of its use in econometric calculations.
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Review
For citations:
Suvorov N.V. VERIFICATION OF AN ECONOMETRIC MODEL BASED ON A PRIORI CONSTRAINTS ON THE STRUCTURAL PARAMETERS. Voprosy statistiki. 2016;(11):53-66. (In Russ.)
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