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Analysis of Factors Affecting Canola Plantation Development in Tabriz and Marand Counties, Iran

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  • Dashti, Ghader
  • Hayati, Babollah
  • Bakhshy, Noushin
  • Ghahremanzadeh, Mohammad

Abstract

This study identifies and analyzes factors influencing canola plantation development in Tabriz and Marand Counties. The Censored Model was used to analyze cross-sectional data collected from 372 farmers using a questionnaire. Due to the weakness of the Tobit model in separating factors affecting the adoption decision of farmers and factors affecting the rate of adoption, the Heckman Model was employed to separate the contributions made by these factors. The results of estimated Probit model in the first stage of the Heckman Approach showed that machinery ownership had an important effect on canola adoption, as a 1% increase in machinery ownership had led to 0.158% increase in canola adoption probability. Contact with extension agents, farm income proportion, education, and farmers’ experience influenced canola plantation probability positively, and the age and number of fragmentations had a negative impact on it. The significance of inverse Mill’s ratio indicates that the factors affecting the decision to start planting and the amount of canola plantation are not the same. The Heckman’s second step estimation results indicated that the loan amount, canola relative benefit, and family labor had a positive effect, and that machinery cost and farm distance from the road had a negative effect on canola acreage. Relative benefit was the most effective element, as 1% increase in relative benefit results in a 0.342% increase in canola plantation.

Suggested Citation

  • Dashti, Ghader & Hayati, Babollah & Bakhshy, Noushin & Ghahremanzadeh, Mohammad, 2017. "Analysis of Factors Affecting Canola Plantation Development in Tabriz and Marand Counties, Iran," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 7(1), March.
    • Handle: RePEc:ags:ijamad:262623
    DOI: 10.22004/ag.econ.262623
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    1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    2. Caviglia, Jill L & Kahn, James R, 2001. "Diffusion of Sustainable Agriculture in the Brazilian Tropical Rain Forest: A Discrete Choice Analysis," Economic Development and Cultural Change, University of Chicago Press, vol. 49(2), pages 311-333, January.
    3. Ibrahim, Mohammed & Florkowski, Wojciech J. & Kolavalli, Shashidhara, 2012. "Determinants of Farmer Adoption of Improved Peanut Varieties and their Impact on Farm Income: Evidence from Northern Ghana," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125000, Agricultural and Applied Economics Association.
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