Optimization of the challenges facing the Iraqi economy based on the values of returns in 2000-2020

Economic Annals-ХХI: Volume 194, Issue (11-12), Pages: 4-12

Citation information:
Alyaseri, N. H. A. (2021). Optimization of the challenges facing the Iraqi economy based on the values of returns in 2000-2020. Economic Annals-XXI, 194(11-12), 4-12. doi: https://doi.org/10.21003/ea.V194-01

Nagham Hameed Abdulkhudhur Alyaseri
PhD (Economics),
Lecturer,
Economics Department,
Faculty of Administration & Economics,
Wasit University
Central Str., Kut, 52001, Iraq
nabedalkhdar@uowasit.edu.iq
ORCID ID: https://orcid.org/0000-0001-8784-9047

Optimization of the challenges facing the Iraqi economy based on the values of returns in 2000-2020

Abstract. In this paper, the situation in the Iraqi economy for the period of 2000-2020 has been analyzed using three hybrid models. The research hypothesis was launched from the necessity of interaction between the activity of the Iraqi market for securities and the local financial and economic institutions. The hypothesis has been verified accordingly using Kolmogorov-Smirnov Test, normality test and Multicollinearity Test. The statistical analysis was based on the three mathematical models to expect return and risk values of Iraqi money market. Three basic models (optimization (BO), Optimized Return Value (ORV), General Optimization Risk (GOR)) have been conducted to optimize and analyze the given data accordingly. The research reached several conclusions, the most prominent of which is the limited economic role of the Iraqi market for securities; the potential exposure to negative effects that could be produced by international crises because of the expected openness, due to the possibility of illegal capital movements resulting in irrational speculation; the difficulty of implementing monetary and financial policies, due to vulnerability to international challenges.

Keywords: Iraq; Monetary Policy; International Crisis; Vulnerability; Linear Optimization; GDP Optimization; Statistical Analysis; Hybrid Models; Normality Tests

JEL Classification: E24; G21

Acknowledgements and Funding: The author received no direct funding for this research.

Contribution: The author contributed personally to this work.

Data Availability Statement: The dataset is available from the authors upon request.

DOI: https://doi.org/10.21003/ea.V194-01

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Received 16.09.2021
Received in revised form 14.10.2021
Accepted 20.10.2021
Available online 27.12.2021