Factors Affecting Land Allocation to Saffron and its Expansion in Marand County, Iran
الموضوعات :
کلثوم عزیزی میزاب
1
(دانش آموخته کارشناسی ارشد مدیریت کشاورزی، واحد تبریز، دانشکاه آزاد اسلامی، تبریز، ایران)
Azadeh Falsafian
2
(استادیار، گروه مدیریت، ترویج و آموزش کشاورزی، واحد تبریز، دانشکاه آزاد اسلامی، تبریز، ایران)
الکلمات المفتاحية: saffron, Marand, Land Allocation, Heckman’s two-step procedure,
ملخص المقالة :
Currently, water, as the most limiting factor in production, determines the priority of planting in different areas of Iran. Saffron is one of the good candidates for drought conditions since it has high economic value and low water requirements that can help with sustainable development. By identifying the factors influencing the decision on saffron cultivation and its expansion, appropriate policies can be implemented to improve the planting of this crop. Marand, located in East Azarbaijan Province, Iran, is one of the areas where farmers have started to grow saffron in recent years. The allocation of 68 hectares of agricultural land to this crop has turned the county into the hub of saffron production in the northwest of the country. This study investigated the factors affecting the decision on saffron cultivation and its development in Marand. To this end, a total of 140 farmers from two groups of saffron growers and non-saffron growers were chosen, and the Heckman’s two-step procedure was then employed. The results of estimating the first step of the Heckman procedure showed that age, familiarity with saffron growing, attending saffron training courses, the number of extension courses, marketing status, and profit status of saffron all had a positive effect on the decision on growing saffron. Moreover, the results of estimating the linear pattern of the second phase corroborated the view that the farmer’s education level, the total area under agricultural and horticultural cultivation, as well as features of agricultural land had a positive impact, and access to water resources had a negative effect on the cultivation area of saffron.
Abrishami, H. (2011). Principles of Econometrics (Vol. II). Tehran University Press, Iran.
Bakhshi, N. (2011). Identifying factors affecting the development of canola in the counties of Tabriz and Marand. Unpublished Thesis, Tabriz University, Faculty of Agriculture, Tabriz, Iran.
Bergtold, J. S., Duffy, P. A., Hite, D., & Raper, R. L. (2012). Demographic and management factors affecting the adoption and perceived yield benefit of winter cover crops in the southeast. Journal of Agricultural and Applied Economics, 44(1), 99-116.
Davidson, R., & Mackinnon J.G. (1984). Convenient specification tests for logit and probit models. Journal of Economics, 25(3), 241-262.
Greene, W. (1993). Econometric Analysis. 2nd ed., Macmillan Publishing Company Inc., New York, USA.
Hayati, B. Ehsani, M. Ghahramanzadeh, M. Raheli, H., & Taghizadeh, D. (2010). Factors affecting willingness to pay to Elgoli and Mashrouteh parks of Tabriz: Heckman two-step method. Journal of Agricultural Economics and Development, 24(1), 91 -98.
Keil, A., Saint-Macary, C., & Zeller, M. (2009). Maize boom in the uplands of Northern Vietnam: Economic importance and environmental implications. Discussion Paper No. 4/2008, Department of Agricultural Economics and Social, Universität Hohenheim, Germany.
Marand Agriculture Department (2013). Agricultural statistics. Unpublished report, IT center, Marand.
Salami, H., & Einollahi, M. (2001).The use of econometric model Tobit and Heckman two-step procedure to determine the factors affecting sugar beet cultivation in the province of Khorasan. Iran Journal of Agricultural Science, (32)2, 433-445.
Shafiee, L. (2007). Identifying factors affecting the development of olive cultivation in the province. Journal of Agricultural Economics and Development, 58, 1-22.
Wekesa, E., Mwangi, W., Vekuijl, H., Danda, K., & De Groote, H. (2003). Adoption of maize production technologies in the coastal low lands of Kenya. Kenya Agricultural Research Institute (KARI) & International Maize & Wheat Improvement Center (CIMMYT). 1 – 34.
