رحمان عرفانی مقدم

Agriculture sector is one of the most important sectors in the country’s economy having a big contribution in employment of the whole country and despite the lack of some basic requirements regarding the existing global conditions inevitably we have to get help of it to cope with the challenges of employment in the country. Therefore, investigating and recognizing the effective factors on agricultural sector employment seems necessary. With respect to the significance of the issue, Regarding the importance of the issue, the present study examines the effects of credits and facilities on employment in the sub-sectors of agriculture (agriculture, livestock and fisheries) using combined data for the period of 1991-2016. Results revealed that the granted credits to the agricultural sector have a significant positive effect on the labor demand of agricultural sub-sectors. Therefore, accurate monitoring on how to use the granted credits, appraisal of the credit schemes and attention to the optimal distribution of credit regarding the economic potentials are among those that have to be taken into consideration in order to have more efficiency.

The purpose of this study was to investigate the effect of real exchange rate uncertainty on Iran's agricultural imports for the period of 1977-1389 and predict the level of Iranian agricultural imports by 1404 using GARCH, VAR, VECM and ANN methods. For this purpose, a generalized autoregressive conditional heterogeneity variance model was used to index the real exchange rate uncertainty, using autoregressive patterns and vector error correction for estimating co-integration and short-term and long-term coherent relationships and finally for prediction of artificial neural network method. The results showed that there is an indirect relationship between the real exchange rate fluctuations and consumption pattern of the society on agricultural imports and the direct relation between oil revenue variable and the absorption variable on agricultural imports. Then, comparing the efficiency of self-regression models and Vector Error Correction Model and artificial neural network, a neural network designed to predict the import of Iranian agricultural sector for the period 1396 to 1404 was used under a scenario and exogenous predictions were .....