Agricultural Economics and Development

Agricultural Economics and Development

The Effect of Climatic Variables on Probability of Pea Cultivating Decision and Its Yield in Iran: Application of Spatial Heckman Model

Document Type : Original Article

Authors
Gh. Dashti 1
Kh. Alefi 2
M. Ghahremanzadeh 3
1 Professor, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Iran
2 PhD Graduate, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Iran
3 Associate Professor, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Iran
10.30490/aead.2020.252691.0
Abstract
Legumes, as the second most important source of food after grains, account for 770,000 hectares of annual crops cultivation area in Iran. About 61.3 percent of the legumes cultivation area was allocated to the pea production, some 97.7 percent of which included the rainfed legumes. Given the high contribution of rainfed cultivation, it is expected that climate change will have a major impact on the yield of pea. So, this study aimed at investigating the effect of climate change on the probability of deciding to cultivate pea product and its yield using the spatial Heckman model. The model was estimated by using agronomic data of pea and meteorological and geographical information of 336 counties of the country during 2012-2013. According to the study findings, spatial contiguity, human influence index and wind speed affected the probability of deciding to cultivate the pea plant, and the spatial contiguity, wind speed, precipitation and irrigation were the most important factors affecting the pea yield. Therefore, production of drought resistant varieties of chickpea as well as more attention to the management of water resources and application of efficient water storage methods in the production areas of this product such as Kermanshah, Lorestan, Kordestan and West Azarbayjan provinces were recommended.
Keywords
Probability of Decision
Cultivation
Pea
Climate Change
Yield
Spatial Heckman Model
  1. Adams, R.M., Hurd, B.H., Lenhart, S. and Leary, N. (1998). Effects of global climate change on agriculture: an interpretative review. Climate Research, 11(1): 19-30.
  2. Alizadeh, P. and Ghorbani, M. (2016). Alignment of regional management maize production and climate change in Iran (spatial panel approach). Agroecology, 6(2): 74-89.(Persian)
  3. Ayouqi Pourtafti, H. (2013). Evaluating the impact of climate change on Canadian prairie agriculture, Doctoral Dissertation, University of British Columbia.
  4. Belloumi, M. (2014). Investigating the impact of climate change on agricultural production in eastern and southern Africa. Fifth World Congress of Environmental and Resource Economists, Istanbul, Turkey.
  5. Case, A. (1992). Neighborhood influence and technological change. Regional Science and Urban Economics, 22(3): 491-508.
  6. Chou, C. and Lan, C.W. (2012). Changes in the annual range of precipitation under global warming. Climate, 25(1): 222-235.
  7. Daneshvar, M.R.M., Bagherzadeh, A. and Khosravi, M. (2013). Assessment of drought hazard impact on wheat cultivation using standardized precipitation index in Iran. Arabian Journal of Geosciences, 6(11): 4463-4473.
  8. Flores‐Lagunes, A. and Schnier, K.E. (2012). Estimation of sample selection models with spatial dependence. Applied Econometrics, 27(2): 173-204.
  9. Guiteras, R. (2009). The impact of climate change on Indian agriculture. Manuscript, Department of Economics, University of Maryland, College Park, Maryland.
  10. Heckman, J. (1976). The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement, 5: 475-492.
  11. Huang, W., Deng, X., Zhan, J. and Lin, Y. (2009). Estimating the effects of climatic change on grain production: spatial versus non-spatial models. Biomedical Engineering and Informatics, BMEI'09. 2nd International Conference on. IEEE.
  12. IPCC (2007). Climate change - synthesis report. Fourth Assessment Report of the Intergovernmental Panel of Climate Change, Rome.
  13. Iran Meteorological Organization (2015). Available at: http://www.irimo.ir. (Persian)
  14. Koocheki, A. and Nassiri Mahallati, M. (2016). Climate change effects on agricultural production of Iran: II. predicting productivity of field crops and adaptation strategies. Iranian Journal of Field Crops Research, 14(1): 1-20. (Persian)
  15. Koocheki, A., Nassiri Mahallati, M. and Jafari, L. (2015). Evaluation of climate change effect on agricultural production of Iran: I. predicting the future agroclimatic conditions. Iranian Journal of Field Crops Research, 13(4): 651-664. (Persian)
  16. LeSage, J.P. and Pace, R.K. (2009). Introduction to spatial econometrics. CRC Press, Taylor and Francis Group, Boca Raton.
  17. Mahmoodi, A. and Parhizkari, A. (2016). Economic analysis of the climate change impacts on products yield, cropping pattern and farmer's gross margin (case study: Qazvin plain). Economic Growth and Development Research, 1(2): 25-40. (Persian)
  18. Masoodian, S.A. (2012). Iran weather. Esfahan: Sharieye Toos Publications. (Persian)
  19. Ministry of Agriculture – Jahad. (2015). Available at: www.maj.ir. (Persian)
  20. Moradi, A.M., Akhtarkavan, M., Ghiasvand, J. and Akhtarkavan, H. (2008). Assessment of direct adverse impacts of climate change on Iran. WSEAS International Conference on Cultural Heritage and Tourism, Heraklion, Crete Island, Greece: 89-94.
  21. Nwachukwu, I.N., Ezeh, C.I. and Emerole, C.O. (2012). Effect of climate change on cocoa productivity in Nigeria. African Crop Science Journal, 20(2): 487-491.
  22. Schlenker, W., Hanemann, W.M. and Fisher, A.C. (2006). The impact of global warming on US agriculture: an econometric analysis of optimal growing conditions. Review of Economics and Statistics, 88(1): 113-125.
  23. Shahraki, J., Sabouhi, M. and Yaghoubi, M. (2017). The impacts of climate change on wheat production: a stochastic production function approach. Natural Environment Hazards, 6(11): 69-84. (Persian)
  24. Shirgholami, H. and Ghahreman, B. (2005). Study of time trend changes in annual mean temperature of Iran. Water and Soil Science, 9(1): 9-23. (Persian)
  25. Ward, P.S., Florax, R.J. and Flores-Lagunes, A. (2014). Climate change and agricultural productivity in Sub-Saharan Africa: a spatial sample selection model. European Review of Agricultural Economics, 41(2): 199-226.
  26. Zare Abyaneh, H. (2013). Evaluating roles of drought and climatic factors on variability of four dry farming yields in Mashhad and Birjand. Water and Soil Science, 1(23): 39-56. (Persian)
  27. Zhang, P., Zhang, J. and Chen, M. (2017). Economic impacts of climate change on agriculture: the importance of additional climatic variables other than temperature and precipitation. Environmental Economics and Management, 83: 8-31.
  28.  Azarakhshi, M., Farzadmehr, J., Eslah, M. and Sahabi, H. (2013). An investigation on trends of annual and seasonal rainfall and temperature in climatologically different regions of Iran. Range and Watershed Management, 1(66): 1-16. (Persian)
  29.  Hosseini, S.S., Nazari, M.R. and Araghinejad, Sh. (2013). Investigating the impacts of climate on agricultural sector with emphasis on the role of adaptation strategies in this sector. Agricultural Economics Reserch, 1(44): 1-16. (Persian)
  30. Parhizkari, A., Mahmoodi, A. and Shokat Fadaee, M. (2017). Economic analysis of the effects of climate change on available water resources and agricultural products in the watersheds of Shahrood. Agricultural Economics Research, 9(33): 23-50. (Persian)
  31. Pishbahar, E., Darparnian, S. and Ghahremanzadeh, M. (2015). Effects of climate change on maize yield in Iran: application of spatial econometric approach with panel data. Agricultural Economics Research, 7(26): 83-106. (Persian)
  32. Tahamipour, M. and Salami, H. (2014). Determining the same risk areas for potato yield frost risk in Iran: the application of spatial econometrics. Agricultural Economics, 8(Special Issue): 55-67. (Persian)