Measuring the effectiveness of fiscal policy tools in financing public budget deficits of selected developed countries for the period (2002-2019) (Entrepreneurship Journal for Finance and Business, 2022)
The research aims to analyze the content of the theoretical relationship between fiscal policy and the public budget deficit by defining the concept, types and tools of fiscal policy on the one hand, and the concept and types of public budget deficit and methods of financing it on the other hand, as well as building a measurement model to study and analyze the effectiveness of these tools in financing public budget deficits for selected advanced countries during the period (2002-2019), and through the use of modern economic measurement tools within the software (Stata 14.2 & EViews 12) and using the (Panel Data) data collection method, a (CD-Test) test for cross-sections was conducted as an initial step to determine the tests that will be used In order to find out the static of the variables and whether they fall within the tests of the first or second generation, and after making sure that there is no reliability between the cross-sections, the Levin, Lin and Chu (LLC) test was used, If its results showed that some variables have a unit root, that is, some variables are stationary in the level and others are stationary in the first difference, and accordingly, this will lead us to include these variables in the model, and we will have a dynamic model, and in this case we will deal with the models of temporal slowdown and the best example On that, it is the auto-regressive distributed lag model for dynamic panel data model (Dynamic Panel ARDL Model) and with its three estimators, which are the mean group estimator (MGE), pooled mean group estimator (PMGE) and the dynamic fixed effects estimator (DFEE). The Husman Test has been used. In order to differentiate between the three capabilities; The test showed that the combined group mean estimator (PMGE) is the best. The Husman Test was used to compare the three estimators; The test showed that the pooled group mean estimator (PMGE) is the best.