Volume 19, Issue 3 (2019)                   QJER 2019, 19(3): 145-161 | Back to browse issues page

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Pishbahar E, Bodagh S, Dashti G. Forecasting Iran's Agricultural Sector Growth: Using Mixed-frequency Data Sampling (MIDAS) Model. QJER 2019; 19 (3) :145-161
URL: http://ecor.modares.ac.ir/article-18-19545-en.html
1- Associate Professor of Agricultural Economics, University of Tabriz, Tabriz, Iran , pishbahar@yahoo.com
2- M.A. Student of Agricultural Economics, University of Tabriz, Tabriz, Iran
3- Professor of Agricultural Economics, University of Tabriz
Abstract:   (6933 Views)
Today, forecasting of economic and commercial variables as an important scientific field is developing, and forecasting of macroeconomic variables is of special importance for planners, policy makers and economic enterprises. The agricultural sector, as a producer of strategic products and provider of food for the growing population, has a great influence on economic, social and political decisions. Considering the importance of the agricultural sector in Iran as well as the existence of different and uncontrollable influential factors, the researchers who focus on agricultural sector’ growth, try to use methods of forecasting in order to get results close to reality, reduce the prediction errors, and design policies and plans to improve the place of this sector. In this paper, the mixed frequency data-sampling model (MIDAS) has been used to predict the growth of agricultural sector’ value added. Comparison of the model predictions with actual data indicates the predictive power of the model. This model has predicted the growth rate of agricultural sector's value added over the period 2017-2021 by 3.215%, 2.53%, 2.92%, 5.29%, and 5.99%, respectively.
 
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Article Type: Original Research | Subject: Economics
Received: 2018/04/28 | Accepted: 2019/07/30 | Published: 2019/07/30

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