The Effectiveness of Fiscal Policy Tools in Addressing the Glitches in Public Budget Deficit of Selected Developing Countries for the Period (2002-2019)

The Effectiveness of Fiscal Policy Tools in Addressing the Glitches in Public Budget Deficit of Selected Developing Countries for the Period (2002-2019)

The research aims to measure the effectiveness of fiscal policy tools in regarding the glitches in public budget deficit of selected developing countries during the period (2002-2019), and through the use of modern economic measurement tools within the software (Stata 14.2 & EViews 12). Using th...

Full description

Saved in:
Bibliographic Details
Published in:Tikrit Journal of Administrative and Economic Sciences Vol. 18; no. 58, 1; pp. 93 - 112
Main Authors: Hussein, Ahmed Ibrahim, Abdullah, Hashim Mohammed
Format: Journal Article
Language:English
Published: 30-06-2022
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The research aims to measure the effectiveness of fiscal policy tools in regarding the glitches in public budget deficit of selected developing countries during the period (2002-2019), and through the use of modern economic measurement tools within the software (Stata 14.2 & EViews 12). Using the data collection method (Panel Data), CD-Test for cross-sections as an initial step to determine the tests that will be used to find out whether the variables are still variables. And whether they fall within the first or second generation tests. After making sure that there is no dependence between the cross sections, the Livn, Lin and Chu (LLC) test was used, as its results showed that some variables have a unit root, that is, some variables are static in the level and others are static in the first difference. Therefore this will lead us to include these variables in the model, and we will have a dynamic model. In this case, we will deal with time-delay models, and the best example of this is the Autoregressive Distributed Time Gap model for the Dynamic Panel ARDL data with its three estimators. Which are the mean group estimator (MGE), the combined mean estimator (PMGE) and the dynamic static effects estimator (DFEE), Husman test was used to compare the three estimators; The test showed that the combined group mean estimator (PMGE) is the best.
ISSN:1813-1719
DOI:10.25130/tjaes.18.58.1.6