Measuring the Efficiency of Date Crop by DEA (Data Envelopment Analysis) Window (Case Study: Khuzestan Province)

مجله اقتصاد و توسعه کشاورزی

Article 5, Volume 33, Issue 2 - Serial Number 44, July 2019, Pages 177-190   

Document Type: Research Article

DOI: 10.22067/jead2.v0i0.78829

Author

D. Modhej^*

Sosangerd Branch, Islamic Azad University

Abstract

Introduction: Agriculture is the most important part of Iran economy. The agricultural sector always has an important role in supplying the essential elements of life and human well-being, so utilizing its capabilities is necessary to fulfill the development goals. Because of the growth population, the food supply is increasing and due to resource constraints, existing resources should be used efficiently to maximize possible production. Therefore, checking the efficiency of agricultural producers can be useful. Dates as one of the horticultural products due to its nutritional properties, and preservation of the environment have a special status in Iranian agriculture. Cultivating dates in Iran, especially in the southwestern regions (Abadan, Khoramshahr, Shadegan), date back to 6,000 years ago. According to the official statistics of the Food and Agriculture Organization (FAO) of United Nations, Iran has the world's first position in terms of date’s cultivation. Iran is ranked in the second place after Egypt in terms of production and exports with 16.5% of the world's exports. Khuzestan province with 37492 hectares of cultivation is one of the most important areas of production dates in the country. According to the official statistics, Khuzestan province by producing 15.2% of one million ton of country's date has the highest production in the country. Unfortunately, in recent years, salinity of water and dust adversely affected the production and quality of dates in Khuzestan province. Evaluating the performance of this product in Khuzestan province due to its importance in terms of cultivation, production and employment is so significant for the economy of the country. The aim of this study is to determine the efficiency of 8 date’s producers in Khuzestan province during the agricultural period 2010-2017.
Materials and Methods: Data Envelopment Analysis (DEA) is a management tool employed to estimate the efficiency of number of decision making units (DMU’s). DEA can be used to calculate the efficiency measures, and has a wide applicability in various service and industry sectors. The first model in DEA was presented in the CCR paper (after Charnes, Cooper and Rhodes1978) to produce the efficiency of DMUs under constant returns to scale (CRS) assumption. Subsequently, Banker et al. (1984) proposed a variable returns to scale version of the CCR model which was named BCC model. Since in real situations, variable returns to scale is more flexible so in this study BCC model is used. Suppose there is a set of n peer DMUs,  each using m inputs to produce s outputs and also assume  be the input and output vectors for DMUj, respectively, such that and . The input-oriented and output-oriented BCC models evaluate the efficiency of DMU0 by solving the following linear programs respectively: 
 
The choice of input- or output-oriented models depends upon the production process characterizing the firm (i.e. minimize the use of inputs to produce a given level of output or maximize the level of output given levels of the inputs). DEA window analysis is based on a dynamic perspective, regarding the same DMU in different period of time as entirely different DMUs. The benefit of this method is to describe the dynamic change of the efficiency of each DMU comprehensively, both horizontally and vertically. More importantly, the number of DMU is increased in this method; hence, it enhances the discriminating power by increasing the number of DMUs when a limited number of DMUs is available. Consider a set of DMUs in period of time. Every DMU has m kinds of input and s kinds of output. Let  denotes the level of input or output for DMU n in t period of time, then input vector and output vector will be presented as:Consider the window starts at the time point of, and the window width is, then input and output  matrix of each window will be presented as
The input-oriented BCC model of DEA window problem for is given by solving the following linear program:
Where .And the output-oriented BCC model is as follows:
Discussion of Results and Conclusion: Land area (ha); Water consumption (cubic meters); Animal manure (tons); Labor (person-days); Machinery (Hours); Fertilizer (kg) as well as pesticides (L) are used as indicators of inputs. Meanwhile, Performance (kg) and Gross profit (Rials) are regarded as two output indicators. Since beneficiaries have more control over the inputs than the outputs, the input-oriented DEA windows model is applied to evaluate the efficiencies of 8 date producers in Khozestan province during 2010-2017. By solving 144 models, the average performance of each window and the average annual provide a basis for measuring and comparing the performance of producers. Results showed that two producers were at full technical efficiency level in 2013, moreover none of the producers during 2010-2012 and 2014-2017 were full technically efficient. In period 2010-2012, efficiency of producers had small variation and the average annual efficiency of producers was much higher in comparison with period 2014-2017. Several factors cause the huge difference in performance over these two periods. Among these factors, one can mention dust in Khuzestan province, Dust particles reduce the harvest and the quality of the product. Another reason is the drought of the last two years. Reducing rivers water has made irreparable impacts on the agriculture of the region.

Keywords

Date; Data Envelopment Analysis; Efficiency; Khozestan; Window Analysis

References

1- Abedpoor A.R., Asadabadi E., and Sha'banali Fami H. 2017. Analysis factors affecting Date production efficiency in Bam country: with DEA approach. Iranian Journal of Agricultural Economics and Development Research 48(3): 507-518. (In Persian with English abstract)

2- Azizi J., and Yazdani S. 2007. Evaluating the earning sustainability of Iranian date export. Journal of Agricultural Science 13(1): 1-19. (In Persian)

3- Banker R.D., Charnes A., and Cooper W.W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30: 1078–1092.

4- Charnes A., Clark C.T., Cooper W.W., and Golany B. 1985. A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces. Annals of Operations Research 2(1): 95–112.

5- Charnes A., Cooper W.W., and Rhodes E. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2: 429–444.

6- Farrell M.J. 1957. The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, General 120(3): 253–281.

7- Ganji N., Yazdani S., and Saleh I. 2018. Identifying factor affecting efficiency of water use in wheat production, Alborz province (Data Envelopment Analysis Approach). Iranian Journal of Agricultural Economics and Development Research 49(1): 13-22. (In Persian with English abstract)

8- Hosseini Y., Mohebi A., Pozesh Nezhad Shirazi M., Rejali F., Tehrani M.M., and Basirt M. 2016. Introduction to conditions of date cultivation, Agricultural education publication, Tehran. (In Persian)

9- Karimi F., Pirasteh H., and Mehdi Zahedi K. 2008. Determination of Wheat Agriculture Efficiency Based on Two Factors Time and Risk by Using Interval Data Envelopment Analysis and Window Data Envelopment Analysis. Agricultural Economic and Development 64: 139-159. (In Persian)

10- Mehrabi Boshrabadi H., and Pakravan M. 2009. Calculation efficiency and returns to scale of sunflower producers Khoy County. Journal of Economics and Agricultural Development 23(2): 95–102. (In Persian)

11- O'Neill S., and Matthews A. 2001. Technical change and efficiency in Irish agriculture, The Economic and Social Review. Economic and Social Studies 32(3): 263-284.

12- Sengupta J.K. 1995. Dynamics of data envelopment analysis: Theory of systems efficiency. Boston: Kluwer Academic Publishers, Dordrecht, London.

13- Sepehrdoust H., and Hamzeali Dastjerdi H. 2014. Efficiency Measurement of Agricultural Sub-Sector's Activities; Using Window Analysis Method. Journal of Agricultural Science and Sustainable Production 23(4.1): 131-141. (In Persian with English abstract)

14- Shahnavazi A. 2017. Determination the efficiency of arable crops in Iranian agriculture. Iranian Journal of Agricultural Economics and Development Research 48(2): 227-240.(In Persian)

15- Shafieyan A. 2017. Date palm. Ministry of Agriculture Jahad, Department of Horticulture. (In Persian)

16- Tomaa E., Dobrea C., Donaa I., and Cofasa E. 2015. DEA Applicability in Assessment of Agriculture Efficiency on Areas with Similar Geographically Patterns. Agriculture and Agricultural Science Procedia 6: 704–711.