EVALUATION OF ARTIFICIAL NEURAL NETWORK-PANEL DATA HYBRID MODEL IN PREDICTING IRAN'S DRIED FRUITS EXPORT PRICES

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TOHIDI AMIRHOSSEIN; ZARE MEHRJERDI MOHAMMAD REZA; MEHRABI BOSHRABADI HOSSEIN; NEZAMABADI POUR HOSSEIN

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Journal: Journal of Quantitative Economics Year:2015 | Volume:12 | Issue:3 (46) Page(s): 95-116

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Title

EVALUATION OF ARTIFICIAL NEURAL NETWORK-PANEL DATA HYBRID MODEL IN PREDICTING IRAN'S DRIED FRUITS EXPORT PRICES

Author(s)

TOHIDI AMIRHOSSEIN | ZARE MEHRJERDI MOHAMMAD REZA | MEHRABI BOSHRABADI HOSSEIN | NEZAMABADI POUR HOSSEIN | Issue Writer Certificate

Keywords

EXPORT PRICESQ2

ARTIFICIAL NEURAL NETWORKQ2

PREDICTIONQ2

Abstract

In many studies, in order to predict economic variables, quantitative methods based on time series data or cross-section data are mostly used. Time series data or cross-section data do not control the heterogeneity of countries, and there exists the possibility of obtaining the risk of biased results. Panel data provides more informative data and a higher level of freedom so it leads to more precise results and PREDICTIONs. In this study, while considering the significant role and proportion of dried fruits in non-oil exports, the synthetic ARTIFICIAL NEURAL NETWORK-panel data method has been used to predict the price of pistachio, raisin and date exports. Then the PREDICTIONs were compared, using the accuracy criteria, with the regression model (the two-way error component model). The data from ten target markets for each of the dried fruits from 1992 to 2012 was used, and the results of this study show that the new and synthetic ARTIFICIAL NEURAL NETWORK- panel data method has a better performance in predicting the price of Iran's pistachio, raisin and date exports than that of the regression method. Therefore, it is suggested that exporters, policy makers, and researchers use this method in order to predict economic variables.

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APA: Copy

TOHIDI, AMIRHOSSEIN, ZARE MEHRJERDI, MOHAMMAD REZA, MEHRABI BOSHRABADI, HOSSEIN, & NEZAMABADI POUR, HOSSEIN. (2015). EVALUATION OF ARTIFICIAL NEURAL NETWORK-PANEL DATA HYBRID MODEL IN PREDICTING IRAN'S DRIED FRUITS EXPORT PRICES. JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW), 12(3 (46)), 95-116. SID. https://sid.ir/paper/110728/en

Vancouver: Copy

TOHIDI AMIRHOSSEIN, ZARE MEHRJERDI MOHAMMAD REZA, MEHRABI BOSHRABADI HOSSEIN, NEZAMABADI POUR HOSSEIN. EVALUATION OF ARTIFICIAL NEURAL NETWORK-PANEL DATA HYBRID MODEL IN PREDICTING IRAN'S DRIED FRUITS EXPORT PRICES. JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW)[Internet]. 2015;12(3 (46)):95-116. Available from: https://sid.ir/paper/110728/en

IEEE: Copy

AMIRHOSSEIN TOHIDI, MOHAMMAD REZA ZARE MEHRJERDI, HOSSEIN MEHRABI BOSHRABADI, and HOSSEIN NEZAMABADI POUR, “EVALUATION OF ARTIFICIAL NEURAL NETWORK-PANEL DATA HYBRID MODEL IN PREDICTING IRAN'S DRIED FRUITS EXPORT PRICES,” JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW), vol. 12, no. 3 (46), pp. 95–116, 2015, [Online]. Available: https://sid.ir/paper/110728/en

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