محاسبه و تحلیل بهره‌وری کل عوامل تولید مرغداری‌های گوشتی ایران: کاربرد شاخص فیرو پریمونت

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه تبریز

چکیده

زمینه مطالعاتی: افزایش جمعیت جهان و محدودیت منابع تولید، اهمیت و لزوم ارتقای بهره‌وری را بیش از پیش مورد توجه قرار داده است همچنین با توجه به اینکه رشد بهره‌وری عوامل تولید در بخش کشاورزی از مولفه‌های اثرگذار در فرایند توسعه اقتصادی می‌باشد، لذا بهبود بهره‌وری مستلزم شناخت اجزاء و بررسی تغییرات آن می‌تواند راهنمایی در جهت نیل به توسعه اقتصادی باشد. هدف: مطالعه حاضر با هدف محاسبه و تحلیل بهره-وری کل عوامل تولید مرغداری‌های گوشتی صورت گرفت. روش‌کار: هدف اصلی این مقاله محاسبه و تجزیه بهره‌وری کل عوامل تولید با بهره‌‌گیری از روش تحلیل پوششی داده‌ها و شاخص فیرو پریمونت می‌باشد. بدین منظور داده‌های مورد نیاز برای دوره زمانی سال‌های 94-1375 تهیه گردید. نتایج: بر اساس یافته‌های تحقیق طی دوره مورد مطالعه میانگین شاخص بهره‌وری کل عوامل تولید برای مرغداری‌های گوشتی سیر صعودی داشته و به طور میانگین نسبت به سال پایه رشدی برابر با 3/10 درصد داشته است. میانگین کارایی بهره‌وری کل عوامل تولید (TFPE) نیز در بین مرغداری-های گوشتی مورد مطالعه ایران کمتر از یک و برابر با 606/0 می‌باشد که این امر بیانگر این است که کارایی بهره‌وری کل عوامل تولید در طول این دوره نسبت به سال پایه کاهش یافته است. همچنین نتایج حاصل از کارایی مقیاس پسماند و کارایی ترکیبی پسماند بیانگر این است که مرغداری‌‌های گوشتی مورد مطالعه از نظر ترکیب نهاده‌ها و ستاده در اثر پیشرفت تکنولوژی به صورت کارا عمل نکرده‌اند. بررسی کارایی مقیاس ستاده‌گرا نیز موید آن است که در استان‌های مورد مطالعه نزدیک به یک می‌باشد و اختلاف چشمگیری با عدد یک (کارایی مناسب) نداشته‌اند. همچنین تغییر تکنولوژی عاملی موثر در افزایش بهره‌وری مرغداری‌های گوشتی در طی دوره مورد مطالعه می‌باشد. نتیجه‌گیری نهایی: نتایج حاکی از آن است که نیل به افزایش بهره-وری در مرغداری‌ها نیازمند توجه به تکنولوژی مناسب می‌باشد. همچنین کمک‌های دولت و سرمایه‌گذاری بخش خصوصی، گامی مهم در جهت ارتقای مقیاس واحدهای مرغداری‌های گوشتی کشور به شمار می‌رود.

کلیدواژه‌ها


عنوان مقاله [English]

Comparison and Analysis of Total Factor Productivity of Broiler Chicken Productions in Iran: The Application of Fare-Primont Index

نویسندگان [English]

  • Ghader Dashti
  • Farina Saei
  • Fatemeh Sani
University of Tabriz
چکیده [English]

Introduction: increasing the population and scarcity of resources, shows the importance and necessity of productivity. Considering the productivity of the agricultural factors in Iran being the biggest economic sector in Iran. Enhancement of interest is required to know the components and investigate the changes in the direction of achieving economic development. Productivity change is a crucial aspect of structural change .studies show that most of the people in the world, and especially developing countries suffering from scarce of protein, so animals protein has important role in humans health and life and its quality and amount must be optimal. the poultry industry is the one of the most important sectors in the agricultural and is the one of the important protein source because of that in large amount of investments that have been done in the field of poultry farms. therefore, for improving productivity requires to understanding of components and studying its changes can lead to economic development.
Material and methods. The objective of the article is to assess comparsion and analysis of total factor productivity of broiler chicken production. This article estimated total factor productivity (TFP) change and its components technological change and efficiency change.so decomposed these changes into technical change, technical efficiency change, and scale and mix efficiency change in broiler chicken farms by using Fare-primont TFP indexes For this. The Färe-Primont Indices based on non-parametric Data Envelopment Analysis (DEA) Productivity measures of a decision making unit (DMU) that can be expressed as the ratio of an output quantity change index on an input quantity change index, can be referred to as ‘multiplicatively complete’ and does not require price information. Indeed, it relies to on non-linear weighting functions and normalized shadow) prices. in this way Input and output quantity data were included for labor, bird seed, fuel, and chicken meat using records from the results of a sample survey of industrial broiler chicken farms in the provinces of Iran during 1994-2015.
Results and discussion: Results in the Broiler chicken farms indicated that during the period, Total Factor Productivity index of chicken broiler has been increased in some years. The annual average growth of total factor productivity in broiler farms in Iran broiler farms is 10.3%, which is different in provinces. Markazi province has the highest TFP equal to (0.88). and Bushehr and Hormozgan have the lowest TFP respectively. the average of efficiency of productivity (TFPE) is also less than one and equal to 0.60 that shows the efficiency of productivity efficiency of the total factors productivity has decreased during the years which compared with the base year. Output-Oriented of (OSE) amount of scale efficiency is smaller than one in this study shows although have not been efficient but there is no significant difference with the number one (appropriate efficiency). The highest of scale efficiency is (0.98) belongs to Kerman and Yazd provinces, as well as has the lowest scale efficiency among the studied provinces is in Bushehr Province (0.74). And the findings show that technology changes are the most effective factor in increasing the total factor productivity factors in broiler chicken farming in Iran provinces. Finally efficiency and total factor productivity among the studied provinces are different and there is a direct relationship between low productivity and low efficiency.
Conclusion: the results indicate that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. For example, using of pure breeds And effective can improve conversion factor of the birds seed. Investment by government and private sector can improve the scale of the Broiler chicken farms units in Iran. as the fuel uses the most consumption among the inputs in this study. According to results scarcity of fuel and using birds seed over of optimal, so wasting can be stopped by increasing the efficiency of heating equipment in Broiler chicken farms. it this way it found that technical efficiency was a determinant factor and resulted in a decreasing in the performance of well - studied ones. also low efficiency in some provinces is a serious problem. and it is suggested to increase their efficiency by determining the optimal size of their performance in provinces with low - scale efficiency.
Conclusion: the results indicate that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. For example, using of pure breeds And effective can improve conversion factor of the birds seed. Investment by government and private sector can improve the scale of the Broiler chicken farms units in Iran. as the fuel uses the most consumption among the inputs in this study. According to results scarcity of fuel and using birds seed over of optimal, so wasting can be stopped by increasing the efficiency of heating equipment in Broiler chicken farms. it this way it found that technical efficiency was a determinant factor and resulted in a decreasing in the performance of well - studied ones. also low efficiency in some provinces is a serious problem. and it is suggested to increase their efficiency by determining the optimal size of their performance in provinces with low - scale efficiency.
Conclusion: the results indicate that for achieving of high total factor productivity in Broiler chicken farms in Iran, we need more attention to technology in this part. For example, using of pure breeds And effective can improve conversion factor of the birds seed. Investment by government and private sector can improve the scale of the Broiler chicken farms units in Iran. as the fuel uses the most consumption among the inputs in this study. According to results scarcity of fuel and using birds seed over of optimal, so wasting can be stopped by increasing the efficiency of heating equipment in Broiler chicken farms. it this way it found that technical efficiency was a determinant factor and resulted in a decreasing in the performance of well - studied ones. also low efficiency in some provinces is a serious problem. and it is suggested to increase their efficiency by determining the optimal size of their performance in provinces with low - scale efficiency.

کلیدواژه‌ها [English]

  • Broiler chicken
  • Fare-Primont Index
  • Productivity Efficiency
  • Residual Scale Efficiency
  • Total factor productivity
Abadi HA, Pourraberi, MM, 2009. Effects of herd density, some blood metabolites and carcass index of male broiler chicks (In Persian).
Amini A and Farhad Kia A, 2010. Evaluating developments in the oil sector productivity indexes and recommendations for improving the efficiency of the fifth development plan, Tehran: Office of Planning vice president of strategic planning and monitoring.
Arnade C.A.1994. Using data envelopment analysis to measure international efficiency and productivity. In: Technical Bulletin No. 1831, United States department of agriculture, Economic Research Service, Washington DC.
Baležentis T. 2015. The Sources of the Total Factor Productivity Growth in Lithuanian Family Farms: A Färe-Primont Index Approach. Prague Economic Papers 2015: 225-241.
Baradaran V. Ghodsi Y 2016, Productivity and Efficiency Analysis of Poultry in Iran Provinces, Animal Science Journal (Pajuhesh & Sazandegi). 117: 77-94 (In Persian).
Christensen L.R. 1975. Concepts and measurement of agricultural productivity and capacity of U.S. agriculture. American Journal of Agricultural Economics, 57: 910-915.
Dashti GH, Sani F؛ Ghahramanzadeh M and Sani R, 2019.Measuring and decomposing total factor productivity growth of industrial dairy farms in Iran. Animal Science Journal (Pajouhesh & Sazandegi) 129: 61-76. (In Persian).
Esfehani S.M.J and Khazaei J, 2011. Factors affecting on efficiency of broiler producers in southern Khorasan. Journal of Agricultural Economics Research 4: 165-180. (In Persian).
Färe, R., Grosskopf, S and Roos, P. 1998. Malmquist productivity indexes: a survey of theory and practice. In R. Färe, S. Grosskopf, R. R. Russell (eds), Index numbers: Essays in honour of Sten Malmquist. Springer, 127-190.
Ghaderpour Kh 2017. Measuring and decomposing cotton factors productivity changes in major provinces of Iran Thesies. M.S of Agricultural Economics, Production Economics and Management of Agricultural Units. University of Tabriz.Iran. . (In Persian).
Hervé Dakpo K, Desjeux a, Y P, Jeanneaux BP, LATRUFFE L, 2016. Productivity, efficiency and technological change in French agriculture during 2002-2014: A Färe-Primont index decomposition. 10èmes Journées de Recherches en Sciences Sociales Paris, La Défense, France.
IKE PC and Ugwumba COA, 2011. Profitability of Small Scale Broiler Production in Onitsha North Local Government Area of Anambra State, Nigeria. International Journal of Poultry Science, 10: 106-109
I.R. Iran Statistical Center, 2017. Statistical yearbook 2017-2018. Presidency of I.R.I. Plan and budget organization, Tehran, Iran. Available online at: https://www.amar.org.ir/english/ Iran-Statistical Yearbook (In Persian).
Jahangard E, Taee H, Naderi M. 2012. Analysis of Factors Affecting Total Factor Productivity in Iran's Economy. Quarterly Journal of Business Research, 16(63), 51-85, (In Persian).
Khan F, Salim R, Bloch, H. 2015. Nonparametric estimates of productivity and efficiency change in Australian Broadacre Agriculture. Australian Journal of Agricultural and Resource Economics 59: 393-411.
Kiani A. 2008a.TFP and MIRR in the agricultural crop sub-sector of Sindh. European Journal of Social Sciences, 7(1): 43-57.
Kijek A, Kijek T., Nowak A., Skrzypek A. 2019: Productivity and its convergence in agriculture in new and old EU member states. Agricultural Economics – Czech, 65: 01–09.
Mahfouzian M. 2012. Assessing Efficiency of Private and Public Banks with Hicks-Moorsteen Approach. M.S of Development Economics & Planning Thesies. Faculty of economics & Accounting-Department of Economics. Islamic Azad University of Tehran. (In Persian).
Mashayekhi S, Pasandideh M, Fatemi SJ, 2015. Economic analysis of chicken meat production in Behbahan Township. Animal Science Journal (Pajouhesh & Sazandegi). 109: 133-142. . (In Persian).
Minegishi, Kota & Jette-Nantel, Simon, 2019. Productivity Decomposition with Parametric and Nonparametric Frontiers: Application to Wisconsin Dairy Production. Annual Meeting, February 2-5, 2019, Birmingham, Alabama. Southern Agricultural Economics Association. 284-298.
O’Donnell CJ, 2008. An aggregate quantity-price framework for measuring and decomposing productivity and profitability change, Centre for efficiency and productivity analysis working papers WP07/2008. Universityof Queensland, Queensland.
O’Donnell CJ, 2010. Measuring and decomposing agricultural productivity and profitability change. The Australian Journal of Agricultural and Resource Economics 54: 527–560.
O’Donnell CJ, 2011a. The Sources of Productivity Change in the Manufacturing Sectors of the U.S. Economy. Centre for Efficiency and Productivity Analysis Working Papers WP07/2011. University of Queensland.
Rafiee A, 2011. Agricultural bank. Directorate General for Economic Studies and Studies (In Persian).
Sabetian shirazi A, Mohamadi H, Dehghanpour H. 2011. Measurement of different types of efficiency in broiler chicken units in Fars province, Journal of Agricultural economics and Development, No; 21(81): 1-22 (In Persian).
Sanzidur R and Salim R. 2013.Six Decades of Total Factor Productivity Change and Sources of Growth in Bangladesh Agriculture (1948–2008) Journal of Agricultural Economics 64: (2), 275-294.
Sedghi N and Sadeghi A. 2014. Measuring and Analyzing Factors Affecting Productivity Case Study: Poultry Farms of Khorasan Razavi Province. Szczecin، International Center of Academic Communication (ICOAC), (In Persian).
Tozer P and Villano R, 2013. Decomposing productivity and efficiency among western Australian grain producers. Journal of Agricultural and Resource Economics 38: 312–326.