The Significance of Econometric Models in the Process of Forecasting Economic Indicators
The article researches the econometric model as one of the most common methods used to analyze and predict the complex development of society.It is considered the principles which are the basis for forecasting: the maximum required amount of information about patterns; the past period adequately characterizes the future period; sample data should be informative in relation to a given general population; All predictions have some degree of aging.It is noted that in the consistency of econometric models includes regression and balance equations that quantitatively measuring relationships and proportions between macroeconomic variables in all phases of the reproduction process.One of the main approaches in determining the relationship between the studied indicators in the econometric model is correlation-regression analysis.It should be noted that the variables included in the econometric models are divided into the following groups:- external variables (exogenous) - variables that are defined out of this model and are considered adjusted; - variables based on indirect data; - linear and nonlinear time trends; - artificial variables expressing qualitative or immeasurable factors; - other auxiliary variables, such as autoregressive variables, etc; - internal variables (endogenous) - variables that are determined by the corresponding equations of the model and are the subject of research. These mainly include the volume of national production, unemployment, employment, exchange rate, etc; - predefined variables are exogenous and lag (taken late) endogenous variables; - explaining variables are predefined variables and endogenous variables that are substituted into the corresponding equations from other model equations.It is substantiated the expediency of using econometric models in the economy, which allows to highlight and formally describe the most important, the most significant connections of economic variables and objects, as well as to gain new knowledge about the object by inductive way
Year of publication: |
2022
|
---|---|
Authors: | Hrynchuk, Tetiana ; Hulivata, Inna ; Husak, Liudmyla |
Publisher: |
[S.l.] : SSRN |
Subject: | Prognoseverfahren | Forecasting model | Wirtschaftsindikator | Economic indicator | Makroökonometrie | Macroeconometrics | Ökonometrisches Modell | Econometric model | Wirtschaftsprognose | Economic forecast |
Saved in:
freely available
Extent: | 1 Online-Ressource (5 p) |
---|---|
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 07, 2022 erstellt |
Other identifiers: | 10.2139/ssrn.4227114 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014236235
Saved in favorites
Similar items by subject
-
A new version of MODTRIM II : an overview of the model for short-term forecasts
De Ketelbutter, Bart, (2014)
-
Empirical models and policy making : interaction and institutions
Butter, Frank A. G. den, (2000)
-
Econometric model performance in forecasting and policy assessment
Spivey, Walter Allen, (1979)
- More ...