Adoption intensity and efficiency of improved technologies in Lower Shivalik Hills

Abstract

Agricultural technologies are seen as an important means for alleviating poverty in most of the developing countries. However, the rate of adoption of farm technologies has remained at low level. Present study conducted during 2016-19 in lower Shivalik hills of Uttarakhand which aims at shedding some light on the driving forces that influence the intensity of technology adoption using econometric models like quantile regression (QR) model since it produces different effects along the distribution (quantile) of the dependent variable. Improved varieties of two major crops (Rice and Wheat) of lower Shivalik hills of Uttarakhand have been enlisted. Kendall Tau estimation has been used to measure the extent of association of explanatory variables with the adoption level. To estimate sustaining productivity (economic efficiency) of selected technologies (varieties) and to identify best suited available technology, Seeming Unrelated Regression (SUR) model was used as it estimates the parameters of all equations simultaneously. The estimates of quantile model show that operational land holding, extension contact, family type, house type and farm assets had significant influence on intensity of adoption. Besides, findings of SUR model identified PB-1121 of rice and HD-2967 of wheat the best suitable varieties. The paper also suggested some farm policy-related issues for the welfare of the farmers under study.

Keywords

• Adoption intensity
• Economic Efficiency Measure
• Quantile Regression
• SUR Model