فصلنامه اقتصاد کشاورزی
سال هفدهم شماره 1 (بهار 1402)

Therefore, the efficient use of production resources in the process of sustainable development is of considerable importance. Thus, this study was conducted to evaluate the technical efficiency, environmental efficiency and the factors affecting them, as well as to measure the economic loss of using detrimental inputs in rainfed wheat production in Ahar county.

In this study, pesticide and fertilizer inputs were considered as environmentally detrimental inputs in rainfed wheat production, and technical and environmental efficiency were estimated separately. Therefore, it was estimated from a stochastic frontier Translog function using data related to 217 rainfed wheat farmers in Ahar county in the crop year of 2020-2022 to evaluate the technical efficiency and environmental efficiency of production.

Based on the results of inputs of tractor, seeds and manure and detrimental factors of pesticides and fertilizers had a significant effect on wheat production. The results of the technical and environmental efficiency showed that the quantity of environmental efficiency was lower than technical efficiency. With the increase in the use of detrimental inputs, fertilizer and pesticides, the production of environmental efficiency decreases. Based on the average technical efficiency of 66/06 and environmental efficiency of 49/36%, it is possible to increase both efficiency. In other words, by destroying inefficiency, farmers can increase their production by 34% with the same inputs.

Suggestion: 

According to the results, the amount of land, family members with high education and pest damage were factors affecting the efficiency, therefore benefiting from the agriculture science and knowledge and timely dealing with pest damage can improve the efficiency. Considering that the use of pesticides and fertilizers while Pollution the product leaves significant environmental damage, therefore, in order to make the product production process as economical as possible, instead of promoting alternative methods, chemical control, biological and integrated pest control should be carried out.

Systematic and non-systematic risks have influence on decisions in agriculture sector. Evaluating the performance of different crops in terms of returns and risk using appropriate performance indices is important. Such evaluation provides the necessary information to change crop pattern to a pattern that meets the risk conditions of each region and help to reorganize the crop production. Accordingly, this study aims to evaluate the performance of major crops in different provinces of Iran based on Portfolio Performance Evaluation Indicators and then to develop a pattern corresponding to these indicators for different major production regions of the country, using data for 2001 to 2019 period. The results of this study show that there is no proportionality between the high Sharpe ratio and the share of cultivated area in the provinces of the country, i.e. that the largest share of cultivated area in a province does not belong to the crops that have the highest Sharpe ratio. This result indicates that farmers do not act correctly in taking into account the cost of risk in choosing the crops to produce. Accordingly, changes in crop pattern and increasing the knowledge of farmers on the risk consideration is recommended.

The experience of many countries in the world shows that expanding the degree of trade openness through increasing access to international markets has brought acceleration of economic growth and prosperity of employment in urban and rural areas. In this study, the effect of trade openness of the agricultural sector on rural unemployment in Iran was evaluated. For this purpose, the annual time series statistics of 1986-2018 and the Autoregressive Distributed Lag (ARDL) approach were used. The results showed that in the short-term, increasing the degree of trade openness of the agricultural sector will reduce the rate of rural unemployment in the country. Nevertheless, in long-term periods, increasing the degree of trade openness of the agricultural sector will increase the amount of rural unemployment in Iran. The results also showed that in the short and long-term, with the increase in the growth of the GDP of the agricultural sector, the amount of rural unemployment in Iran will decrease. Also, by reducing the degree of dryness of the environment in the short and long-term, unemployment in rural areas will be reduced. Nevertheless, the growth of rural population does not show a significant effect on the increase of rural unemployment in the country. Finally, in order to reduce rural unemployment in the country, it was suggested to continue and increase the payment of employment creation and investment facilities in the agricultural sector with the aim of increasing the penetration of user jobs in rural areas, especially in long-term periods.

In recent years, the Iran Commodity Market has always been associated with price destabilizing fluctuations. Thus, it is need to use machine Learnings in the form of forecasting methods to recognize early events and prevent damage caused by these fluctuations. Considering the important position of the pistachio trading ring in the Iran Commodity and also the need to use appropriate tools to correctly diagnosis the future price, The purpose of this study is to design and build a suitable hybrid model based on XGBoost and compare its performance with other machine learning models in order to accurately forecast the future price of pistachio. In this study, software’s of Matlab, Rapid Miner and Scikit learn were used to build the proposed hybrid model. The results of applying the wavelet theory showed that the error value of price data was reduced and the data had a stable trend (white noise). Also, the results of the Performance of Auto-Encoder network and the Genetic algorithm showed that the optimal lag of one is the best input variable for forecasting the future price of pistachios in the period under review. Based on goodness of fit indices, the proposed model of this study, Wavelet-XGBoost in comparing to other data mining models, had a better performance in forecasting the future price of pistachios. Also, out-of-sample forecasting with the selected model showed that the forecasted new prices have little difference with the real data, which indicates the efficiency and accuracy of the selected hybrid model. According to the obtained results, it is strongly recommended to use the proposed model based on XGBoost algorithm to forecast the price of other agricultural products.

Banks are considered as one of the most important sources of financing in various economic and social fields in many developing countries such as Iran. In this regard, financing the production units of the agricultural sector is one of the most important issues in managing the banking and economic system of a country. Since access to credits provided by banks to finance the needs of people and manufacturing enterprises in various sectors such as agriculture sector provides more investment and improves the agricultural industry and leads to economic growth and development. Hence, the main purpose of this study is to investigate the factors affecting the supply of banking credits in the Agricultural Bank of Iran. To this, the data from 2007 to 2021 and the panel data approach have been used. The results show that non-current receivables have a negative effect and interest rates on bank credits, provincial inflation, GDP growth and bank size have a positive effect on the supply of credits of the Agricultural Bank in Iran. The study of Iran's economic situation shows that despite the important role of bank credits in the process of economic growth and development, the country's economy has not been able to make optimal use of the benefits of bank credits to elimination deficiencies and financing needs of the agricultural sector. Accordingly, it is suggested that monetary and banking policymakers pay special attention to this issue.

Energy is one of the most important inputs of agricultural production, the consumption of which is directly related to increasing demand for various products in this sector. In this regard, due to the implementation of various phases of targeted subsidies law, energy consumption pattern has been changed in this sector, so the present study intends to show the effect of increasing the final demand of selected agricultural products on direct and indirect uses. In order to achieve the objectives of this research, the latest supply and consumption tables (2016) were used. Therefore, first the supply and consumption tables were integrated, then the effect of increasing demand for cereals, livestock and other agricultural products on the consumption of liquefied petroleum gas, diesel, gasoline, electricity, refined and distributed gas and other products were investigated. The results showed that with the increase in demand for agricultural products, diesel is still the most widely used energy carrier directly. But directly and indirectly, liquefied petroleum gas has the highest consumption coefficients among energy carriers for the agricultural sector. Therefore, based on the analysis of the results, it is suggested that appropriate measures be taken according to the type of product, energy consumption ratios, energy resources, as well as various subsidy policies. Also pay sufficient attention to the role of energy carriers such as liquefied gases that are used indirectly.