Designing a Mathematical Programming Model to Optimize the FGT Poverty Index in Rural Areas of Behbahan

Document Type : Research Paper


1 MSc Student, Department of Agricultural Extension and Education, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Molasani, Iran.

2 Associate Professor, Department of Agricultural Economics, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Molasani, Iran.

3 Assistance Professor, Department of Agricultural Economics, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Molasani, Iran.


One of the most important factors that improve most indicators of poverty is increasing the income of the study population. In the agricultural sector, this can be achieved through proper resource management and appropriate cultivation pattern. The current study presents a mathematical programming model that aims to optimize the Foster, Greer and Turbek (FGT) poverty index by generating higher income by providing an optimal cultivation model. To evaluate the ability of the proposed model, rural areas of Sardasht, Langirat suburbs, Dodangeh and Tashan were selected from Behbahan city. To calculate the poverty line, the method of daily caloric requirement, which is estimated from the nutritional performance matrix, was used. The required data were collected through the Jihad Agricultural Service Centers of this city in the 2017-2018 crop year and the Statistics Center of Iran and analyzed by Excel and GAMS software. The results showed that in the proposed model, while profits increased by 10.47%, the area under wheat and alfalfa decreased and the area under watermelon and sugar beet increased. In this model, the amount of water consumed decreased by about 0.5%. Also, by averaging the FGT index in both current and optimal models, it was found that the numerical value of this index (the value of the objective function) in the whole city has decreased from 3.47 to 0.03. Therefore, the optimal model, while increasing farmers' incomes, has reduced poverty and also reduced the use of scarce water inputs. Therefore, promoting the optimal model obtained in this study is recommended by the Agricultural Jihad Organization.


Adams, J., & H., R. (2003). Economic Growth, Inequality, and Poverty : Findings from a New Data Set Retrieved from World Bank Policy Research Working Paper Series:
Alkire, S., & Foster, J. (2011). Understandings and misunderstandings of multidimensional poverty measurement. Journal of Economic Inequality, 9(2), 289-314.
Alkire, S., & Santos, M. E. (2013). Measuring acute poverty in the developing world : robustness and scope of the Multidimensional Poverty Index. OPHI working paper no. 59. Oxford Poverty & Human Development Initiative (OPHI).  
Almas, I., Kjelsrud, A., & Somanathan, R. (2013). A behavior –based approach to the estimation of poverty in India. CESifo working paper series, 4122.
Anríquez, G., & Stamoulis, K. (2007). Rural development and poverty reduction: is agriculture still the key? (2521-1838). Retrieved from
Arshadi, A., & Karimi, A. (2013). The study of poverty in rural and urban areas in iran during five-year development plan. Journal Of The Marco And Strategic Policies, 1(1), 23-42. Retrieved from
Arsyad, M., Pulubuhu, D. A. T., Kawamura, Y., Maria, I. L., Dirpan, A., Unde, A. A., . . . Yusuf, S. (2020). The role of public health services (PHS) in agricultural poverty alleviation. Enfermería Clínica, 30, 194-197.
Arzrom Chiller, N. (2005). Various dimensions of poverty in Iran. Economic Research Collection, 92, 21- 27.
Bani Asadi, M., & Zare Mehrjerdi, M. R. (2010). Studying The Effects Of Optimal Cultivation Pattern On Rural Poverty: Case Study Of Orzoo’iyeh District In Baft (Kerman–Iran). Agricultural Economics: Iranian Journal Of Agricultural Economics (Economics And Agriculture Journal), 4(2), 209-226. Retrieved from
Bazrafshan, J. A. V. A. D., Tuolabi Nejad, M., & Sadeghi, K. H. A. D. I. J. E. (2017). Analysis of the relationship between sustainable land manage-ment and crop yield and evaluating its effects on food security of households in rural Eastern Miyankoh (Poldokhtar City). Journal of Rural Research, 8(2), 346-363.
Devkota, R. P., Bajracharya, B., Maraseni, T. N., Cockfield, G., & Upadhyay, B. P. (2011). The perception of Nepal’s Tharu community in regard to climate change and its impacts on their livelihoods. International Journal of Environmental Studies, 68(6), 937-946.
Eftekhari, S. F., & Karami, A. (2014). Investigating factors affecting poverty in rural areas of Kohgiluyeh And Boyerahmad Province. Agricultural Economics:(Economics And Agriculture Journal), 8(1), 139-156.
FAO. (2005). Spurring economic growth through agricultural investment. Retrieved Sept 10, 2017 from
Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761-766.
Fotros, M.H, & Ghodsi, S.G. (2018) Comparing multidimensional poverty of female and men headed households in urban and rural areas in Iran by Alkire-Foster method. Social Welfare Journal, 18 (69), 185-227.
Hosseini-Yekani, S.-A., & Kashiri kolaei, F. (2017). Investigating the effect of crop price fluctuations on the optimal cropping pattern in Sari. Agricultural Economics, 11(2), 75-94.
Khodadad Kashi, F., & Heydari, K. (2009). The measurement of poverty indices based on Iranian household nutrition. Economic Research Review, 10(3 (34)), 205-231.
Khoshnood, A. (2019). Poverty in Iran: A critical analysis. Middle East Policy, 26(1), 60-74.
Mardani, M., Nikouei, A., Ziaei, S., & Ahmadpour, M. (2016). Codifying regional cropping pattern of agricultural and horticultural products in Isfahan Province: Multi-objective structural planning approach. Agricultural Economics & Development, 30(3), 188-206.
Mardani Najafabadi, M., Ziaee, S., Nikouei, A., & Ahmadpour Borazjani, M. (2019). Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems, 173, 218-232.
Mohamadiyan, S., & Negahdari, E. (2018). Study of poverty indicators in the urban areas of hormozgan province using linear expenditure system (les) during 4th and 5th development plans: Household budjet survey. SOCIAL WELFARE, 18(68 #P00393), 201-223.
Mortazavi, S. A., Seraj Zadeh, F., & Shokohi, M. (2011). The relationship between income inequality and economic growth in urban and rural areas of Iran: Application of Kuznets curve. Journal Of Agricultural Economics Research, 3(1), 165-180.
Mosleh, Z., Salehi, M. H., Amini Fasakhodi, A., Jafari, A., Mehnatkesh, A., & Esfandiarpoor Borujeni, I. (2017). Sustainable allocation of agricultural lands and water resources using suitability analysis and mathematical multi-objective programming. Geoderma, 303, 52-59.
Mousavi, S. N., Mobseri, M., & Akbari, S. (2011). The effects of optimum cropping pattern water consumption, income and rural poverty: A case study of Kazeroon region. Agricultural Economics & Development, 25(2), 219-226.
Naderi Mahdei, K., Motaghed, M., Shahbazi Gigasari, H., & Abdi, E. (2015). Optimal Cropping Pattern in Bahar County. Journal of Applied Economics Studies In Iran, 3(12), 167-184.
Namara, R. E., Hanjra, M. A., Castillo, G. E., Ravnborg, H. M., Smith, L., & Van Koppen, B. (2010). Agricultural water management and poverty linkages. Agricultural Water Management, 97(4), 520-527.
Osama, S., Elkholy, M., & Kansoh, R. M. (2017). Optimization of the cropping pattern in Egypt. Alexandria Engineering Journal, 56(4), 557-566.
Ren, C., Guo, P., Tan, Q., & Zhang, L. (2017). A multi-objective fuzzy programming model for optimal use of irrigation water and land resources under uncertainty in Gansu Province, China. Journal of Cleaner Production, 164, 85-94.
Rowntree, B. (2000). Poverty: A Study of Town Life. Macmillan, London, Qouted in Ravallio: Policy Press.
Sethi, L. N., Panda, S. N., & Nayak, M. K. (2006). Optimal crop planning and water resources allocation in a coastal groundwater basin, Orissa, India. Agricultural Water Management, 83(3), 209-220
Saadi, H., Azizi, M., & Azami, M. (2014). Extension educational and farmer households food security (case study Ghorveh county). Iranian Journal of Agricultural Economics and Development Research (IJAEDR), 45(3).483-499.
Shirvanian, A., & Ismaili, A. (2009). The impact of changes in prices on rural poverty (Case study: Fars Province). Iranian Journal of Agricultural Economics and Development researches, 40(2), 13-25.
Statistical Center of Iran. (2016a). Indicators of the Millennium Development Goals of the Islamic Republic of Iran. Theran: Country Planning and Budget Organization
Statistical Center of Iran. (2016b). Statistical Yearbook of Khuzestan Province. Khozestan, Iran.
Van Hop, N. (2007). Fuzzy stochastic goal programming problems. European Journal of Operational Research, 176(1), 77-86
Zhang, F., Zhang, C., Yan, Z., Guo, S., Wang, Y., & Guo, P. (2018). An interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint for crop monthly water allocation. Agricultural Water Management, 209, 123-133.
Zhang, J. (2016). Weighing and realizing the environmental, economic and social goals of tourism development using an analytic network process-goal programming approach. Journal of Cleaner Production, 127, 262-273