تعداد نشریات | 161 |
تعداد شمارهها | 6,532 |
تعداد مقالات | 70,501 |
تعداد مشاهده مقاله | 124,098,613 |
تعداد دریافت فایل اصل مقاله | 97,206,244 |
تحلیل انواع کارایی توام با ریسک تولید گندم در منطقه سیستان | ||
تحقیقات اقتصاد و توسعه کشاورزی ایران | ||
مقاله 12، دوره 54، شماره 1، فروردین 1402، صفحه 201-220 اصل مقاله (1.66 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijaedr.2022.341903.669143 | ||
نویسندگان | ||
علی سردارشهرکی* 1؛ زهرا غفاری مقدم2 | ||
1گروه اقتصاد کشاورزی، دانشکده اقتصاد و مدیریت دانشگاه سیستان و بلوچستان، زاهدان، ایران | ||
2گروه اقتصاد کشاورزی پژوهشکده کشاورزی پژوهشگاه زابل، زابل، ایران | ||
چکیده | ||
گندم یکی از محصولات مهم زراعی منطقه سیستان است که علاوه بر سطح زیر کشت بالا، نقش بسزایی در اقتصاد این منطقه دارد. بررسی کارآیی این محصول میتواند نقشی بهسزا در راستای افزایش تولید آن داشته باشد از این رو در پژوهش حاضر به بررسی انواع کارایی تؤام با ریسک تولید پرداخته شده است. برای تحقق اهداف مذکور، از روش تحلیل مرزی تصادفی (SFA) استفاده شد. اطلاعات و دادههای مورد نیاز از طریق تکمیل پرسشنامه در 3 شهرستان زابل، زهک و هیرمند از 250 بهرهبردار گندم در سال زراعی 1399- 1398 جمع آوری شد. نتایج نشان داد در روش تحلیل مرزی تصادفی با در نظر گرفتن 3 نوع کارآیی، شهرستان زهک با مقدار 87 و 47 درصد بیشترین کارآیی فنی و اقتصادی و شهرستان هیرمند با مقدار 58 درصد بیشترین کارایی تخصیصی را داشتهاند. نتایج تحلیل ریسک تولید نشان داد که نهاده دفعات آبیاری در هر سه شهرستان مذکور آثار منفی بر ریسک تولید داشته است. نتایج حاصل از تخصیص اقتصادی و تخصیصی نشان میدهد که آشنایی کشاورزان با اصول و فنون تولید علمی و نحوه مدیریت صحیح منابع و عوامل تولید در حد قابل قبولی نیست، بنابراین، توصیه میشود برگزاری دورههای آموزشی و ترویجی مناسب باعث آشنایی کشاورزان با نحوه استفاده بهینه از عوامل تولید و در نهایت منجر به بهبود کارایی فنی، تخصیصی و اقتصادی گندمکاران خواهد شد. با توجه به اینکه نهاده آب یک نهاده ریسک کاهنده است، استفاده از فناوریهای جدید آبرسانی و روشهای بهزراعی با توجه به شرایط آب و هوایی منطقه توصیه میشود. | ||
کلیدواژهها | ||
تحلیل مرزی تصادفی؛ ریسک تولید؛ سیستان؛ کارایی | ||
مراجع | ||
Abedi, S. (2016). Investigating the comparative advantage of biotechnologybased agricultural production (case study: whea and corn in Fars province). Iranian Agricultural Economics and Development Research. 3: 569-579. (In Persian) Akite, I., Okello, D. M., Kasharu, A., & Mugonola, B. (2022). Estimation of profit efficiency of smallholder rice farmers in Uganda: A stochastic frontier approach. Journal of Agriculture and Food Research. 8, 100315. Alam, M. A., Guttormsen, A. G., & Roll, K. H. (2019). Production risk and technical efficiency of tilapia aquaculture in Bangladesh. Marine Resource Economics. 34(2), 123-141. Ali, I., HUO, X. X., Khan, I., Ali, H., Khan, B., & Khan, S. U. (2019). Technical efficiency of hybrid maize growers: A stochastic frontier model approach. Journal of Integrative Agriculture. 18(10), 2408-2421. Alikhani, L., Dashti, Gh., & Raheli, JH. (2016). Technical efficiency and production risk of cold- water fish farms in the Kamyaran County, Journal of Animal Science Research. 25(2), 1-12 (in Persian). Alropy, E. T., Desouki, N. E., & Alnafissa, M. A. (2019). Economics of technical efficiency in white honey production: Using stochastic frontier production function. Saudi journal of biological sciences. 26(7), 1478-1484. Angulo-Meza, L., Gonzalez-Araya, ´ M., Iriarte, A., Rebolledo-Leiva, R., Soares De Mello, J. C., 2019. A multiobjective DEA model to assess the eco-efficiency of agricultural practices within the CF + DEA method. Comput. Electron. Agric. 161, 151–161. Battese, G. E., & Broca, S. S. (1997). Functional forms of stochastic frontier production functions and models for technical inefficiency effects: a comparative study for wheat farmers in Pakistan. Journal of productivity analysis. 8(4), 395-414. Benedetti, I., Branca, G., & Zucaro, R. (2019). Evaluating input use efficiency in agriculture through a stochastic frontier production: An application on a case study in Apulia (Italy). Journal of Cleaner Production. 236, 117609. Biswas, B., Mallick, B., Roy, A., & Sultana, Z. (2021). Impact of agriculture extension services on technical efficiency of rural paddy farmers in southwest Bangladesh. Environmental Challenges. 5, 100261. Branca, G., Arslan, A., Paolantonio, A., Grewer, U., Cattaneo, A., Cavatassi, R., & Vetter, S. (2021). Assessing the economic and mitigation benefits of climate-smart agriculture and its implications for political economy: A case study in Southern Africa. Journal of Cleaner Production. 285, 125161. Carrer, M. J., de Souza Filho, H. M., Vinholis, M. D. M. B., & Mozambani, C. I. (2022). Precision agriculture adoption and technical efficiency: An analysis of sugarcane farms in Brazil. Technological Forecasting and Social Change. 177, 121510. Chandel, R., Khan, A., Li, X., & Xia, X. (2022). Farm-Level Technical Efficiency and Its Determinants of Rice Production in Indo-Gangetic Plains: A Stochastic Frontier Model Approach. Sustainability. 14, 2267. Chandio, A.A., Jiang, Y., Gessesse, A.T., Dunya, R., 2019. The nexus of agricultural credit, farm size and technical efficiency in Sindh, Pakistan: a stochastic production frontier approach. Saudi Soc. Agric. Sci. 18, 348–354. Chang, H. H., & Wen, F. I. (2011). Off‐farm work, technical efficiency, and rice production risk in Taiwan. Agricultural economics. 42(2), 269-278. Chen X, Cui Z, Fan M, Vitousek P, Zhao M, Ma W, Wang Z, Zhang W, Yan X, Yang J, Deng X, Gao Q, Zhang Q, Guo S, Ren J, Li S, Ye Y, Wang Z H, Huang J L. )2014(. Producing more grain with lower environmental costs. Nature. 514, 486. Battes, G.E. & Coelli T.J. (1995). A model for technical inefficiency effect in a Stochastic Frontier Production Function for Panel data. Empirical Economic. 20(2), 325-332. Battes, G.E. & Coelli T.J. (1992). Prediction of Rim-Plevel Technical Efficiency with a Generalized Frontier Production Function and Panel Data. Journal of Econometrics. 38, 387-399. Coelli, T., Rao, D.S.P. & Battese, G.E. (2002). An introduction to efficiency and productivity analysis. Kluwer Academic Publisher U.S.A.sixth printing. 132-166. Deng, X., Gibson, J. (2019). Improving eco-efficiency for the sustainable agricultural production: a case study in Shandong, China. Forecast. Soc. Chang. 144, 394–400. Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society: series A (General), 120(3), 253-281. Faryadras, V., Hosseini, S., Salami, H. and Yazdani, S. (2018). Analysis of regional effects of wheat market liberalization in Iran. Agricultural Economics and Development. 103: 145-170. (In Persian) Ganji, N., Yazdani, S., & Saleh, E. (2018). Identification of Factors Affecting the Efficiency of Water Intake in Wheat Production in Alborz Province (Data Envelopment Analysis Approach). Iranian Journal of Agricultural Economics and Development Research. 2-49(1), 13-22. (In Persian) Ghader zadeh, H. & Zareei, F. (2020). Comparing of Economic Efficiency of Different Irrigation Systems of Alfa- Alfa Farms in Qorveh-Dehgolan Plain. Iranian Journal of Agricultural Economics and Development Research. 2(51-2), 231-242. (In Persian). Gong, B., (2018). Agricultural reforms and production in China: changes in provincial production function and productivity in 1978–2015. Dev. Econ. 132, 18–31. Hakimi pour, N., (2018). Comparative analysis of the efficiency of large industries in the provinces of Iran in development programs after the revolution using the random frontier method. Economic Policy. 10(20), 191-213. (In Persian) Hossein Zad, J., & Alfi, KH. (2017). Simultaneous Assessment of production Risk and Inefficiency Simultaneously in Ardebil potato Farms. Iranian journal of agricultural economics and development research. 47(3), 589-597. (In Persian) Just, R.E., & Pope, R.E. (1978). Stochastic representation of production functions and econometric implications. Journal of Econometrics. 7, 67–6 Kara, A. H., Shamsudin, M. N., Mohamed, Z., Latiff, I. B., & Seng, K. W. K. (2019). Technical efficiency and production risk of rice farms under Anchor Borrowers Programme in Kebbi State, Nigeria. Asian Journal of Agricultural Extension, Economics & Sociology. 31(4), 1-12. Khan, A., Huda, F. A., & Alam, A. (2010). Farm household technical efficiency: A study on rice producers in selected areas of Jamalpur District in Bangladesh. European Journal of Social Sciences. 14(2), 262-271. Khan, M. A., Begum, R., Nielsen, R., & Hoff, A. (2021). Production risk, technical efficiency, and input use nexus: Lessons from Bangladesh aquaculture. Journal of the World Aquaculture Society. 52(1), 57-72. Khoshnevisan, B., Rafiee, Sh., Omid, M., Mousazadeh, H., Shamshirband, S. and Hamid, S.H.A. (2015). Developing a fuzzy clustering model for better energy use in farm management systems. Renewable and Sustainable Energy Reviews. 48: 27-34. Available at https://doi.org/10.1016/j.rser.2015.03.029 Kumbhakar, S. C. (2002). Specification and estimation of production risk, risk preferences and Meeusen, W., & van Den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International economic review. 435-444. Mishra, A. K., Rezitis, A. N., & Tsionas, M. G. (2019). Estimating technical efficiency and production risk under contract farming: A Bayesian estimation and stochastic dominance methodology. Journal of Agricultural Economics. 70(2), 353-371. Onumah, E. E., Onumah, J. A., & Onumah, G. E. (2018). Production risk and technical efficiency of fish farms in Ghana. Aquaculture. 495, 55-61. Rana, J., Kamruzzaman, M., Sharna, S. C., & Rana, S. (2021). Growth and efficiency analysis of tobacco production in Bangladesh: a non-parametric approach. SN Business & Economics. 1(12), 1-19. Rashidghalam, M., Dashti, GH & Pishbahar, E. 2019. Technical Efficiency of Cotton Production in Iran Using Panel Data Models, Agricultural economic and development. 27(105), 59-90. Saha, A. (2001). Risk in HYV and traditional rice cultivation: an enquiry in West Bengal agriculture. Indian journal of agricultural economics. 56(1), 57-70. Sardarshahraki, A. (2011). Evaluation of the efficiency of vineyards in Sistan region using random boundary methods and data envelopment analysis. Master Thesis in Agricultural Economics, Sistan and Baluchestan University, Iran. (In Persian). Schawltz, T.W. 1975. The value of the ability to deal with disequilibria, Journal of Economic Literature. (13)3, 827-846. Schmidt, P., & Lovell, C. K. (1979). Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers. Journal of econometrics. 9(3), 343-366. Statistics and Information Technology Office of the Ministry of Jihad Agriculture, 2020. Agricultural Statistics of Crops for the Crop Year 1399-1399, Tehran, Ministry of Jihad Agriculture, Deputy of Planning and Economy. (In Persian). Tan, S., Heerink, N., Kuyvenhoven, A., & Qu, F. (2010). Impact of land fragmentation on rice producers’ technical efficiency in South-East China. NJAS-Wageningen Journal of Life Sciences. 57(2), 117-123. Tiedemann, T., & Latacz‐Lohmann, U. (2013). Production risk and technical efficiency in organic and conventional agriculture–the case of arable farms in Germany. Journal of Agricultural Economics. 64(1), 73-96. Tleubayev, A., Bobojonov, I., & Götz, L. (2022). Agricultural Policies and Technical Efficiency of Wheat Production in Kazakhstan and Russia: Evidence from a Stochastic Frontier Approach. Journal of Agricultural and Applied Economics. 1-15. Tong, Q., Swallow, B., Zhang, L., & Zhang, J. (2019). The roles of risk aversion and climate-smart agriculture in climate risk management: Evidence from rice production in the Jianghan Plain, China. Climate Risk Management. 26, 100199. Villano, R., & Fleming, E. (2006). Technical inefficiency and production risk in rice farming: evidence from Central Luzon Philippines. Asian economic journal. 20(1), 29-46. Xu L, Yuan S, Man J. 2020. Changes in rice yield and yield stability in China during the past six decades. Journal of the Science of Food and Agriculture. 100, 3560–3569 | ||
آمار تعداد مشاهده مقاله: 377 تعداد دریافت فایل اصل مقاله: 239 |