A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran

Money demand is one of the most important economic variables which are a critical component in appointing and choosing appropriate monetary policy, because it determines the transmission of policy-driven change in monetary aggregates to the real sector. In this paper, the data of economic indicators...

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Main Authors: Sayyed Abdolmajid Jalaee, Alireza Shakibaei, Hamid Reza Horry, Hossein Akbarifard, Amin GhasemiNejad, Fateme Nazari Robati, Naeeme Amani Zarin
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:MethodsX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016121000194
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spelling doaj-772ff3eb2f62472c89dc91567b2327e92021-01-18T04:10:35ZengElsevierMethodsX2215-01612021-01-018101226A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in IranSayyed Abdolmajid Jalaee0Alireza Shakibaei1Hamid Reza Horry2Hossein Akbarifard3Amin GhasemiNejad4Fateme Nazari Robati5Naeeme Amani Zarin6Department of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranCorresponding author.; Department of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, IranMoney demand is one of the most important economic variables which are a critical component in appointing and choosing appropriate monetary policy, because it determines the transmission of policy-driven change in monetary aggregates to the real sector. In this paper, the data of economic indicators in Iran are presented for estimating the money demand using biogeography-based optimization (BBO) algorithm, particle swarm optimization (PSO) algorithm, and a new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm (BBPSO). The data are used in two forms (i.e. linear and exponential) to estimate money demand values based on true liquidity, Consumer price index, GDP, lending interest rate, Inflation, and official exchange rate. The available data are partly used for finding optimal or near-optimal values of weighting parameters (1974–2013) and partly for testing the models (2014–2018). The performance of methods is evaluated using mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). According to the simulation results, the proposed method (i.e. BBPSO) outperformed the other models. The findings proved that the recommended method was an appropriate tool for effective money demand prediction in Iran. These data were the result of a comprehensive look at the most influential factors for money market demand. With this method, the demand side of this market was clearly defined. Along with other markets, the consequences of economic policy could be analyzed and predicted.• The article provides a method for observing the effect of economic scenarios on the money market and the analysis obtained by this proposed method allows experts, public sector economics, and monetary economist to see a clearer explanation of the country's liquidity plan.• The method presented in this article can be beneficial for the policy makers and monetary authorities during their decision-making process.http://www.sciencedirect.com/science/article/pii/S2215016121000194Metaheuristic methodMoney demandMonetary and fiscal policiesOptimization algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Sayyed Abdolmajid Jalaee
Alireza Shakibaei
Hamid Reza Horry
Hossein Akbarifard
Amin GhasemiNejad
Fateme Nazari Robati
Naeeme Amani Zarin
spellingShingle Sayyed Abdolmajid Jalaee
Alireza Shakibaei
Hamid Reza Horry
Hossein Akbarifard
Amin GhasemiNejad
Fateme Nazari Robati
Naeeme Amani Zarin
A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
MethodsX
Metaheuristic method
Money demand
Monetary and fiscal policies
Optimization algorithm
author_facet Sayyed Abdolmajid Jalaee
Alireza Shakibaei
Hamid Reza Horry
Hossein Akbarifard
Amin GhasemiNejad
Fateme Nazari Robati
Naeeme Amani Zarin
author_sort Sayyed Abdolmajid Jalaee
title A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
title_short A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
title_full A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
title_fullStr A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
title_full_unstemmed A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran
title_sort new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in iran
publisher Elsevier
series MethodsX
issn 2215-0161
publishDate 2021-01-01
description Money demand is one of the most important economic variables which are a critical component in appointing and choosing appropriate monetary policy, because it determines the transmission of policy-driven change in monetary aggregates to the real sector. In this paper, the data of economic indicators in Iran are presented for estimating the money demand using biogeography-based optimization (BBO) algorithm, particle swarm optimization (PSO) algorithm, and a new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm (BBPSO). The data are used in two forms (i.e. linear and exponential) to estimate money demand values based on true liquidity, Consumer price index, GDP, lending interest rate, Inflation, and official exchange rate. The available data are partly used for finding optimal or near-optimal values of weighting parameters (1974–2013) and partly for testing the models (2014–2018). The performance of methods is evaluated using mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). According to the simulation results, the proposed method (i.e. BBPSO) outperformed the other models. The findings proved that the recommended method was an appropriate tool for effective money demand prediction in Iran. These data were the result of a comprehensive look at the most influential factors for money market demand. With this method, the demand side of this market was clearly defined. Along with other markets, the consequences of economic policy could be analyzed and predicted.• The article provides a method for observing the effect of economic scenarios on the money market and the analysis obtained by this proposed method allows experts, public sector economics, and monetary economist to see a clearer explanation of the country's liquidity plan.• The method presented in this article can be beneficial for the policy makers and monetary authorities during their decision-making process.
topic Metaheuristic method
Money demand
Monetary and fiscal policies
Optimization algorithm
url http://www.sciencedirect.com/science/article/pii/S2215016121000194
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