Study of the Factors Affecting the Adoption Speed of New Wheat Seeds in Savojbolagh Township (Application of Survival Analysis)

مجله اقتصاد و توسعه کشاورزی

Article 3, Volume 32, Issue 2 - Serial Number 40, July 2018, Pages 123-137   

Document Type: Research Article

DOI: 10.22067/jead2.v32i2.67165

Authors

R. Moghaddasi; Zh. Kamaei^*

Science and Research Branch of Islamic Azad University

Abstract

Introduction: Agriculture as one of the important Iranian economic sectors is in transition from traditional to industrial stage. Despite of many critical obstacles such as, drought and severe water shortage, prevalence of traditional irrigation methods and low level of irrigation efficiency, small farm plots and low level of farmers' education, self-sufficiency in main food items including wheat is defined as one of the goals with high priority in the five years national development plans. Due to above mentioned challenges government is not able to increase wheat acreage (extensive farming) thus, producing more from each unit of land (intensive farming) should be chosen as the best policy. In this course, it is indispensable to transfer available technical knowledge (such as new improved seeds) from research institutes to agricultural fields, and this should be seriously followed in national development programs. By this way, one question of high importance from policy making point of view is that what are the main factors determining rate and speed of adoption of new seeds by farmers? So the main objective of the present study was set to identify main influential drivers on speed of adoption of some recently developed wheat seeds in city of Savojbolagh, Alborz province.
Materials and Methods: The present research not only introduces application of the so-called survival analysis method in Iranian agricultural economics literature for the first time, but also tries to explore the main affecting variables on the speed of adoption of five newly introduced improved wheat seeds (Bahar, Pishtaz, Pishgam, Parsi, and Sivand) by local farmers in city of Savojbolagh, Alborz province. The required data was collected via field survey and interview by 140 wheat growers selected by simple random sampling during 2015/16 cropping year. Dependent variable is defined as the difference (number of days) between times of supplying new seed in the region and time that farmer decided to apply it. Initial list of regressors (selected based on review of relevant literature) includes: age and sex of farmer, family size, education, yield, farming experience, acreage, experience in wheat farming, distance of farmer's home from offices (both in rural and urban areas) supplying new seeds and some qualitative variables controlling for attendance in extension and training workshops, insured crop, land ownership and farming as the main job.
In the estimation process, different functional forms used in previous studies, were estimated via both backward elimination and forward selection algorithms in order to find the best explanatory variables for each model. Furthermore, suitable model specification is opted based on common model selection criteria including: Akaike Information Criteria (AIC), Schwarz Bayesian Criteria (SBC) and Likelihood Ratio (LR).
Results: Main results confirmed superiority of the Weibull model over its competing alternatives in terms of explaining power, economically, statistically and econometrically sound estimates. This is in line with previous works. To be specific, significant coefficients were found for non-farm income (qualitative variable), yield, farmer's experience and education, and training courses (qualitative variable). These positively and significantly affect the reduction of the time required to new seeds being adopted by farmers. Here, production per hectare (yield) has the greatest impact in terms of parameter magnitude. This suggests that the more productive seed would be adopted in a relatively shorter time. On the other hand, taking farming as the main job and the distance from home to urban shops offering new seeds revealed negative impact on the time to adopt improved seeds. Moreover, land ownership, farmer's age, crop insurance, quality of the seeds, and the distance from home to local shops presenting new seeds were found to be ineffective as far as the adoption time of new seeds was concerned.
Discussion: Given the significant contribution of farming experience and attendance in training courses into the reduction of required time to accept new seeds, it is recommended to take advantage of the experiences of pioneers in the use of new wheat seeds in training other farmers and provide a basis for practical experience exchange among wheat growers. Here, the Ministry of Jihad-Agriculture (deputy in extension and education affairs) plays a key role. It should allocate required budget for setting workshops introducing new seeds to farmers. Moreover, simplicity of access to new seeds is another influential factor suggesting increase in the number of offices providing new seeds as another policy recommendation. This could be done as a public-private participatory (PPP) action. In order to be a job creative policy, it is highly recommended to engage agriculture- educated students into the process.

Keywords

survival analysis; Cox and Weibull model; Technology; Savojbolagh township

References

1- Abbring J.H., and Van Den Berg G.J. 2007. The unobserved heterogeneity distribution in duration analysis, Biometrika, 94(1), 87-99

2- Abramowitz M., and Stegun I. A. 1972. Handbook of mathematical functions with formulas, graphs and mathematical tables, Dover, New York.

3- Abyar A. 2014. Application of models in the analysis of spatial survival data, M.Sc. Thesis, Tarbiat Modares University, Tehran. (In Persian)

4- Ahsanuzzaman A. 2015. Duration analysis of technology adoption in Bangladeshi agriculture, Agricultural and Applied Economics Association Annual Meeting, At San Francisco, CA, USA.

5- Akinola A.A. 1987. An application of probit analysis to the adoption of tractor hiring services scheme in Nigeria, Oxford Agrarian Studies, 16, 70-82.

6- Amirnezhad H., Rafiee H., and Rezapoor S. 2009. Factors affecting acceptance of insurance by rape-growers of Amol Township. Journal of Agricultural Science, No. 19. (In Persian)

7- Ansari M., and Zare A. 2009. Determining the Factors Affecting the Selection and Transfer of Technology: Iran Khodro Body Production Line, Executive Management Research Journal, No. 1. (In Persian)

8- Baghestani A., Gohari M., Arooji A., and Aminpoor M. 2014. Prediction error estimation of survival time and its application in survival analysis of patients with colon cancer, Scientific and Research Journal of University of Medical Sciences at Ilam, No. 3. (In Persian)

9- Cox D. D., and Snell E. J. 1989. The Analysis of Binary Data, Chapman and Hall.

10- Cox D. R. 1972. Regression models and life-tables. Journal of the Royal Statistical Society, Series B, 34, 187-220.

11- Cox D. R. 1975. Partial Likelihood. Biometrika, 62, 269–276.

12- Dadi L., Burton M., and Ozanne A. 2004. Duration analysis of technological adoption in Ethiopian agriculture, Journal of Agricultural Economics, 55(3):613-631. ·

13- Dinpanah Gh. R. F., Chizari M., and Badraghe A. 2009. Investigation of factors affecting acceptance of technology by wheat growers in Isfahan Township. Scientific and Research Journal of Islamic Azad University (Tabriz Branch), No. 9. (In Persian)

14- Ebrahimi N. 2010. Regression modeling of flexible survival. MS Thesis, Tarbiat Modares University, Tehran. (In Persian)

15- Feder G., and Slade R. 1984. The acquisition of information and the adoption of new technology. American Journal of Agricultural Economics, 66, 312-320.

16- Felistus M. 2009. An analysis of factors influencing adoption of the recommended maize technologies package in Makuyu division, Murang’ a south Didtrict, Kenya. School of Humanities and Social Sciences in Partial Fulfillment of the Requirements for the Award of the Degree of Master of Arts of Kenyatta University.

17- Hanagal D. 2011. Modeling survival data using frailty models, CRC press, Taylor and Frances Group.

18- Heidari N. 2011. Determination and evaluation of water use efficiency of some major crops under farmers management in Iran, No. 2. 43-57. (In Persian)

19- Jansen H.G.P. 1992. Inter-regional variation in the speed of modern cereal cultivars in India. Journal of Agricultural Economics, 43, 88-95.

20- Kafle B., and Shah P. 2012. Adoption of improved potato varieties in Nepal: A case of Bara district. The Journal of Agricultural Sciences, No1. 22-37.

21- Khedmat H., Panahian M., Amini M., Izadi M., Naseri M. H., and Ghayoomi M. H. 2007. Probability of survival of permanent personnel of the armed forces and other people with gastric cancer hospitalized in Baqiyatallah hospital during 2000-2005, Military Medicine, No. 3, 167-177. (In Persian)

22- Kleinbaum D.G., and Klein M. 2006. Survival analysis: a self-learning text, Springer press.

23- Mariano M., Villano R., and Fleming E. 2012. Factors influencing farmers’adoption of modern rice technologies and good management practices in the Philippines. Journal of Agricultural Systems, No. 110: 41–53.

24- Moghaddasi R., and Naraghi N. 2011. Investigating influential factors on adoption of Parsi and Sivand wheat varieties in Alborz province (case of Savojbolagh Township). M.Sc. thesis, Islamic Azad University, Science and Research Branch. (In Persian)

25- Noorafkan Z., Yavarai P., Roshandel Gh., Khalili D., Behnampoor N., and Zaeri F. 2013. Estimation of survival of patients with esophageal cancers and some of associated problems in Golestan Province (Iran) in 2008, Iranian Journal of Epidemiology, No.9. 11-18. (In Persian)

26- Parhizkari A., and Sobuhi M. 2013. Economic analysis of the effects of development of technology and mechanization on agricultural productions in Qazvin province, Journal of Agricultural Economics Researches, No. 20. 1-23. (In Persian)

27- Pazuki A., and Sohani M. 2013. Phenotypic evaluation of scutellum-derived calluses in indica’ rice cultivars (PDF). Acta Agriculturae Slovenica, No.2. 239–247.

28- Pishbin S. 2011. Analysis of the acceptance of the technology of wheat planting by hybrid tillage planter machine in Fars province (Iran) using regression models with virtual dependent variable. Ph.D dissertation, Islamic Azad University, Science and Research Branch. (In Persian)

29- Polson R.A., and Spencer D.S.C. 1991. The technology adoption process in subsistence agriculture: the case of cassava in Southwestern Nigeria, Agricultural Systems, 36(1): 65-78.

30- Rajayee Fard A., Moghimi Dehkordi B., Tabatabaee H., Zeighami B., Safayee A., and Tabei Z. 2008. Survival analysis modeling using Cox model in patients with gastric cancer, Iranian Journal of Epidemiology, Vol. 3, 19-24. (In Persian)

31- Semnani S., Arabali A., Keshtkar A., Behnampoor N., Besharat S., and Roshandel G. 2009. Nitrate and nitrite contents of drinking water resources of urban districts across Golestan province (Iran) and the occurrence of esophageal and gastric cancers, Journal of University of Medical Sciences at Kerman, No. 16, 281-291. (In Persian)

32- Sharma L.K., Sharma A., Chandargi D.M., and Khurana G.S. 2002. Farmers’ characteristics and adoption of Kharif maize technology. Indian Research Journal of Extension Education, 38(1&2): 88-89.

33- Soltanian A., Mahjoob H., Goodarzi S., Nabipoor A., and Jamali M. 2009. 5-year survival of myocardial infarction patients residing in Bushehr seaport, Scientific Journal of University of Medical Sciences and Health Services at Hamedan, No. 16. (In Persian)

34- Census of Agriculture. 2014. Statistical Center Of Iran. (In Persian)

35- Weir S., and Knight J. 2000. Education externalities in rural Ethiopia: Evidence from average and stochastic frontier production functions’, Oxford: Center for the study of African Economies, mimeo.

36- Wienke A. 2011. Frailty models in survival analysis. Institute of medical Epidemiology, Biostatistics, and informatics, University Halle- Wittenberg, Germany.

37- Zare V. 2008. Investigation of the factors affecting acceptance of mechanized corn planting in Kerman Township, 5th National Congress on Agricultural Machineries and Mechanization, Ferdowsi University, Mashhad, Iran. (In Persian)