Determining Revealed Comparative Advantage and Target Markets for Iran's Stone Fruits
Publish Year: 1392
نوع سند: مقاله ژورنالی
زبان: English
View: 74
This Paper With 12 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JASTMO-16-2_001
تاریخ نمایه سازی: 1 آذر 1402
Abstract:
This study investigated the export status of stone fruits in Iran during ۱۹۹۷ to ۲۰۱۰. Export trends and revealed comparative advantage of indices, namely, Revealed Comparative Advantage (RCA), Revealed Symmetric Comparative Advantage (RSCA), and Relative Export Advantage (RXA) as well as Trade Mapping (TM) were investigated for cherries, plums, peaches, and apricots. Target markets for these products were ranked using numerical taxonomies. The results showed that Iran had export's comparative advantage for stone fruits only in ۲۰۰۷ and ۲۰۱۰. But, this index had a positive growth for the stone fruits in those years, indicating an increasing trend in the export status of these products. Trade mapping analysis indicates that although the export market for these products has declined during the period studied, Iran has taken a greater share of the market and is among the winner groups. The principal export markets in decreasing order were found to be Germany, The UK, France, Italy, the Netherlands, Russia, Saudi Arabia, Bahrain, Switzerland, the UAE, and Afghanistan.
Keywords:
Export revealed comparative advantage , market structure , RCA , RSCA , RXA , Stone fruits , Target markets , TM
Authors
H. Khaksar Astaneh
Department of Urban Economics, Iranian Academic Center for Education, Culture and Research (ACECR), Mashhad, Islamic Republic of Iran.
M. Yaghoubi
Department of Economics, University of Sistan and Baluchestan, Zahedan, Islamic Republic of Iran.
Vahid Kalateharabi
Department of Economics, University of Sistan and Baluchestan, Zahedan, Islamic Republic of Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :