An overview of econometrics and regression analysis and the relationship with marketing

Abstract

Although many econometric methods express the use of statistical models, some specific characteristics of economic data distinguish econometrics from other branches of statistics. Economic data are mainly observational rather than derived from controlled experiments. Since the economic units interact with each other, the observed data are indicative of a complex economic equilibrium and not a simple communicative behavior caused by advancement or technology. Therefore, econometrics creates methods to identify and estimate models with multiple unknowns, so the purpose of this study was to review econometrics and regression analysis and its relationship with marketing. This study was conducted in 1402 by reviewing sources and theses published and available domestically related to econometrics and searching in Normex, Megiran and Ganj databases with keywords econometrics, regression analysis and marketing. From economic reasoning They are not used for model selection, especially for deciding which variables to include in a regression. In some cases, economic variables cannot be experimentally manipulated as treatments that are randomly assigned to individuals. In such cases, economists rely on observational studies, often using data sets with many highly correlated variables, resulting in a large number of models with similar explanatory power but different variables and regression estimates. As with other forms of statistical analysis, highly specified econometric models may show an ambiguous relationship in which two variables are related but causally unrelated. Some economists fail to report effect size estimates (apart from statistical significance) and discuss their economic significance.