ФОРМАЛЬНЫЕ ТЕСТЫ ВЫБОРА СПЕЦИФИКАЦИИ МОДЕЛИ

Abstract

The paper examines the construction of an econometric model of the dependence of the money supply aggregate M0 on nominal wages according to Russian Federation data. The problem of choosing a model specification is solved within the framework of formal tests, the algorithms of which are implemented in the R software environment. In practice, as a rule, the true model is unknown and as a result, a model is estimated that only approximately corresponds to the process that generates the data. To date, a number of approaches have been developed for testing the correctness of the choice of specification, both for nested and nonnested competing models. To test nested models, hypotheses are formulated in the form of restrictions on parameters, which are tested, for example, using a standard Ftest for comparing long (unrestricted) and short (restricted) regression models. Comparison of nonnested models is based on the formation of artificial embedding models – hybrid models that are tested using a nonnested Ftest or Jtest (Davidson, Mackinnon) [3, 9]. The Jtest uses only one constraint to make a reasonable choice of model, which leads to an increase in its power compared to a nonnested Ftest with a large number of additional regressors [2]. To select a functional form from a set of competing nonnested models, the BoxCox procedure is used, based on a formalized algorithm for selecting a linearizing transformation from a wide family of powerlaw transformations [1]. To compare linear and loglinear models, a simplified procedure proposed by Zarembka Paul [6] has found wide practical application. When constructing the econometric model under study using the listed procedures for selecting a functional form, the set of competing models included: a paired linear regression model; loglinear model, distributed lag model and autoregressive model.