@article{Wani_Bhat_Baba_2021, title={Ex-ante and Ex-post Evaluation of Advanced Production System Module in Saffron (Crocus sativus) in India using Consumer Surplus Model and Propensity Score Matching}, volume={34}, url={https://www.bjas.bajas.edu.iq/index.php/bjas/article/view/443}, DOI={10.37077/25200860.2021.34.2.10}, abstractNote={<p style="text-align: justify;">A very important breakthrough in saffron cultivation and production was achieved by Sher-e- Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K) when the university developed a production system module in saffron which brought substantial increase in productivity of saffron during last two decades. The adoption of the technology was observed to have a very significant impact on the social dynamics of the saffron producing region demanding its ex-ante and ex-post evaluation vis a vis non adopters of the technology. With this in mind consumer surplus model and propensity score matching methods were employed on a sample of 447 respondents of which 286 were adopters and 161 non-adopters (control group) drawn from a population of 753 saffron growers in the saffron belt of Jammu and Kashmir producing 99% of the total saffron production in the country. The results revealed that average productivity of the spice increased from 2.57 kg.ha<sup>-1</sup> to 6.05 kg.ha<sup>-1</sup>, with 1-2 kg.ha<sup>-1</sup> in the first year to 10-12 kg.ha<sup>-1</sup> in fourth year against control group, however, the investment cost estimates recorded increase of 5.9% under ex-ante and 13.6% under ex-post evaluation while adopting new technology, which however, got compensated through realizing higher productivity and increased employment to the tune of 40.6 and 28.3 per cent  man-days/ha respectively under ex-ante and ex-post  evaluation. The results further revealed, NPV, BCR, IRR of Rs. 399 crores, 110, 154% against Rs.249 crores, 69, 134% respectively under ex-ante and ex-post evaluation of the technology.</p>}, number={2}, journal={Basrah Journal of Agricultural Sciences}, author={Wani, Masudul H. and Bhat, Arshad and Baba, Sajad H.}, year={2021}, month={Nov.}, pages={118–132} }