The Practical Use Of The Linear Multiple Regression In The Complex Gdp Analysis

Ligia Dudu () and Raluca Georgiana Moscu ()

Knowledge Horizons - Economics, 2016, vol. 8, issue 2, 74–79

Abstract: The economic and social phenomena meet the influence of several factors, and their contribution is more difficult to argue only through the dependence analysis of two variables. Using the simple regression model explains in a small contribution the factors of an economical result that evolving differently from year to year, provided that the factors are found together, in various proportions, in each economic outcome. Most often we use the multifactorial approach to analyze the evolution of a phenomenon. This article highlights the effective possibilities to use the multiple linear regression model in the analysis of gross domestic product. To emphasize the practical aspects related to the use of multiple linear regression in the macroeconomic analyzes, we have developed a practical study in which we defined as dependent variable the GDP, and the fluctuations will be explained by more causal variables. We used data with a yearly frequency, the economy of Romania and to compare we deflated, taking as a basis 1990. The objectives of this analysis are to determine the function that describes the best relationship between the indicators undergoing analysis, to observe the link that Is established between them and to estimate an econometric statistically significant valid model.

Keywords: Gross domestic product; multiple regression; households consumption; public consumption; investments; change in inventories; exports variation; gross disposable income; coefficient; significant (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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