آثار افزایش قیمت حامل‌های انرژی بر مقدار تولید گندم در استان فارس: کاربرد تابع تولید غیرمستقیم

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری بخش اقتصاد کشاورزی دانشگاه شیراز

2 استاد بخش اقتصاد کشاورزی دانشگاه شیراز

چکیده

در این مطالعه پس از جمع­آوری داده­های مقطعی سال زراعی 94- 1393 از 201 تولیدکننده گندم آبی در منطقه فسا به روش نمونه­گیری تصادفی خوشه­ای چند­مرحله­ای، آثار افزایش قیمت حامل­های انرژی بر میزان تولید گندم بررسی شد. برای محاسبه کاهش تولید گندم براثر افزایش قیمت حامل‌های انرژی، با برآورد تابع هزینه ترانسلوگ و استفاده از روابط موجود بین سهم نهاده­ها و تابع تولید غیرمستقیم، کشش تولید نسبت به قیمت نهاده برآورد شد. نتایج نشان داد با افزایش 100 درصدی قیمت گازوئیل و برق مقدار تولید گندم به ترتیب 38/4 و 12/23 درصد در هر هکتار کاهش می‌یابد، لذا افزایش قیمت برق در مقایسه با نهاده گازوئیل، آثار محسوس­تری بر کاهش تولید گندم دارد. بنابراین، پیشنهاد می­شود اعمال این سیاست بر نهاده برق با احتیاط بیشتر و برنامه­ریزی­های دقیق­تری­ صورت گیرد. از طرفی نظر به نقش مؤثر گندم در اقتصاد کشور باید با سازوکارهای مناسب از تولید این محصول حمایت شود. با توجه به وجود ویژگی بازده نسبت به مقیاس صعودی تولید گندم در استان فارس دولت می‏تواند با اعطای اعتبارات به تولید گندم زمینه پذیرش تغییر فناوری تولید برای مصرف بهینه حامل­های انرژی جهت کاهش هزینه­ها و حفظ تولید گندم را فراهم سازد. در نهایت، با توجه به راهبردی بودن محصول گندم و وجود تعداد زیاد تولیدکنندگان این محصول پیشنهاد می‌شود که دولت در سطح خرد برای کاهش ریسک تولیدکنندگان گندم از آنها حمایت کند.

کلیدواژه‌ها


عنوان مقاله [English]

The Effects of Increase in Energy Carrier Prices on Wheat Production in Fars province: Application of Indirect Production Function

نویسندگان [English]

  • hassan azarm 1
  • M. Bakhshoodeh 2
1 . Ph.D. Student, Department of Agricultural Economics, Shiraz University, Shiraz, Iran
2 Professor of Agricultural Economics, Department of Agricultural Economics, Shiraz University, Shiraz, Iran
چکیده [English]

In this study the effects of increase in energy carrier prices on wheat product in Fasa county of Fars province was investigated. Data were collected from 201 irrigated wheat producers in 2014-15 applying multistage random cluster sampling. In order to calculate the reduction of wheat production due to the increase in energy prices, output elasticity with respect to input prices was calculated by estimating translog cost function and using relationship between the share of input and indirect production function. The results indicated that a 100 percent increase in the price of gas oil and electricity, wheat production reduces by 4.38 and 23.12 percent per hectare, respectively. The increase in electricity prices compared to gas oil has more significant effects on reducing the production of wheat. Therefore, it is suggested this policy be applied to the electricity with more caution and more precise planning. On the other hand, considering the significant role of wheat in the country economy, the production of this product should be supported by proper mechanisms. With increasing returns to scale of wheat production in Fars province, the government can grant credits to provide conditions for farmers to adopt technology change for optimizing consumption of energy in order to reduce costs and keep producing of wheat provide. Finally, with regard to the strategic nature of wheat and the large number of producers, it is suggested that the government support them at micro level to reduce the risk of wheat producers.

کلیدواژه‌ها [English]

  • Energy Carriers
  • Translog Cost Function
  • Indirect Production Function
  • Share of Input Cost
  • Returns to Scale
  1. Abbasinejad, H. and Vafinajari, D. (2004). Efficiency and energy efficiency in different economic sectors and estimation of input and energy elasticity in the industry and transportation industry by TSLS (1350-1389). Agricultural Research Journal, 66:113-137. (Persian)
  2. Abedi, S. and Tahamipoor, M. (2014). Estimation of the value of carbon dioxide shade in wheat production with the distance function approach. Second National Conference on Engineering and Agricultural Management of the Environment and Sustainable Natural Resources of Tehran, Feb. 20, Shahid Beheshti University. (Persian)
  3. Amadeh, H., Ghazi, M. and Abbasifar, Z. (2009). Investigating the relationship between energy consumption and economic growth and employment in different sectors of Iran's economy. Journal of Economic Research, 86: 1-38. (Persian)
  4. Bokusheva, R. and Kumghakar, S. (2008). Modeling farms’ production decisions under expenditure constraints. 107th EAAE Seminar, Modeling of Agricultural and Rural Development Policies, Sevilla, Spain.
  5. Christensen, L.R. and Greene, W.H. (1976). Economies of scale in US electric power generation. J. Political Economics, 84: 655–676.
  6. Coyle, B.T. (1990). Expenditure constraints and profit maximization in U.S. agriculture: comment. American Journal of Agricultural Economics, 72: 734-737.
  7. Dongdong, M. and Gary, K.K. (2012). Modeling static and intertemporal import demands: the indirect production function approach. M.S Thesis. University of Macau.
  8. Energy Balance Sheet. (2011). Deputy minister of electricity and energy of the ministry of energy. Tehran, Available at: http://www.pep.moe.org.ir. (Persian)
  9. Fare, R. and Sawyer, C. (1988). Expenditure constraints and profit maximization in U.S agriculture: comment. American Journal of Agricultural Economics, 70: 953-54.
  10. Food and Agriculture Organization. (2008). Statistical database. Available at: http://www.fao.org.
  11. Ghasemian, S.D., Hoseini, S.S. and Darijani, A. (2011). Investigating the role of prices of energy carriers (fuel machines) on the cost of wheat in Gorgan. Abstract of Articles of the First Transnational Congress of Optimization of the Production Chain. Distribution and Consumption in Food Industry, Gorgan University of Agricultural Sciences and Natural Resources. (Persian)
  12.  Hozhabrkiyani, K. and Ranjbari, B. (2001). Investigating the long-term relationship between energy, labor and capital inputs in agricultural sector. Quarterly Journal of Agricultural Economics and Development, 35:39-64. (Persian)
  13.  Hilmer, E. and Holt, M.T. (2005). Estimating indirect production functions with a more general specification: An application of the Lewbel model. Journal of Agricultural and Applied Economics, 37:102-121.
  14. Iran Farmer's House, (2015). Agricultural statistics. Available at: http://www.khanehkeshavarz.ir. (Persian)
  15. Judge, G. G., Hill, R. C., Griffiths, W., Lütkepohl, H. and Lee, T. C. (1988). Introduction to the theory and practice of econometrics. 2nd Edition. New York:Welly.
  16. Karkacier, O., Goktolga, Z. G. and Cicek, A. (2006). A regression analysis of the effect of energy use in agriculture. Energy Policy, 34: 3796–3800.
  17. Kumghakar, S. C. (2008). Background, estimation and interpretation of indirect production function. Keynote Address at the HAWEPA 2nd Halle Workshop on Efficiency and Productivity Analysis, May 26-27.
  18. Ministry of Agriculture Jihad. (2013). Office of statistics and information technology. Available at: http:// www. maj.ir.
  19. Ministry of Energy. (2010). Tehran energy balance sheet. Available at: http:// www. pep.moe.org.ir. (Persian)
  20. Mosavi, N., Farajzadeh, Z. and Taheri, F. (2012). The welfare effects of reducing energy subsidies in the agricultural sector of Iran. Journal of Agricultural Economics and Development, 4:298-306. (Persian)
  21. Obeng, K. (2009). Indirect production function and the output effect of public transit subsidies. Transportation, 38(2): 191-214.
  22. Pishbahar, E., Kohnehpoushi, A. and Hoseinzad Firozi, G. (2016). Estimation of indirect production functions and investigating the existence of budget constraints on crop production of water wheat and drym in Kurdistan Province. Journal of Agricultural Economics Research, 31(8): 37-56. (Persian)
  23. Peyman, M., Rouhi, R. and Alizadeh, M. (2005). Determination of energy consumption in traditional and semi-mechanized methods for rice production (Case study in Guilan province). Journal of Agricultural Engineering Research, 6: 67-80. (Persian)
  24. Salami, H. and Rafee, H. (2010). Investigation of the financial constraint and its effect on reducing the production of rice in the north: application of indirect production function. Journal of Agricultural Economics and Development (Agricultural Sciences and Technology), 1: 107-112. (Persian)
  25. Sharzaei, G.H., Ghetmiri, M. A. and Rastifar, M. (2003). Investigating the structure of production and cost of rice product of the case study in Guilan Province. Journal of Agricultural Science and Technology, 1: 45-57. (Persian)
  26. Taheri, F. and Mosavi, N. (2010). Investigating the role of energy in the value added of the agricultural sector in Iran. Journal of Agricultural Economics Research, 2: 45-60. (Persian)
  27. Taheri, F., Mosavi, N. and Rezaee, M. (2010). The effect of energy subsidy elimination on rape seed production costs in Marvdasht city. Journal of Agricultural Economics Research, 2: 77-89. (Persian)
  28.  Tavanir Company. (2015). New statistics. Available at: http:// www.tavanir. org.ir. (Persian)
  29. Yazdani, S., Shahbazi, H. and Kavosi Kalashami, M. (2010). Investigation of indirect production function and budget constraints on Cotton production in Khorasan province. Journal of Agricultural Economics and Research, 4:425-433. (Persian)