potential technology adoption: index for improved targeting: a village level proxy assessment using...
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By Parvesh Kumar Chandna, Andy Nelson, Sohel Rana, Marie-Charlotte Buisson, Sam Mohanty, Nazneed Sultana, Deepak Sethi, T.P. Tuong Revitalizing the Ganges Coastal Zone Conference 21-23 October 2014, Dhaka, Bangladesh http://waterandfood.org/ganges-conference/TRANSCRIPT
Poten&al technology adop&on Index for improved targe&ng :
IRRI
CPWF Team : Parvesh Kumar Chandna, Andy Nelson, Sohel Rana, Marie-‐Charlo:e, Sam Mohanty Nazneen Sultana, Deepak Sethi, T.P. Tuong
A village level proxy assessment using the past adop&on rates of agricultural technologies
? ?
? ? ? ?
Village level census data is there
Some farmers have adopted improved technologies in the past
But some did not ?
Can I use past trends?
Perhaps yes – Lets Discuss with CPWF/WLE team
Adop(on Targets 100000????
Why not to con
duct a
quick and d
irty exercise
Objec(ve :
To develop a proxy index to iden(fy areas having high poten(al for adop(on of new technologies using the past adop(on rates and farmer response to different technologies
IRRI
v Study Area v Datasets used
v Methods
v Results
v Conclusion
IRRI
Bangladesh Barisal
IRRI
Datasets & Parameters used
• Agricultural (2008) and Popula(on census data (2011)
• Developed a mouza level database of more than 61,000 mouzas of Bangladesh
• We have entered more than 60 parameters to develop this socio-‐economic database
• Irriga(on Pumps, Tractor, Power (ller, Paddy thrasher, Seeder, Other Agri. Instrument, percent area under HYVs in AUS, Aman, Boro – 12 parameters
IRRI
Datasets: few examples
Pumping sets
Power (llers
HYVs
Methods
PTAI uses composites of Standard Z score to logically combine the selected parameters
Composite Standard Score Classes
Low = < 0.5
Medium = -‐0.5-‐0.5
High = 0.5-‐ 1.5
Very High = > 1.5
Poten&al Technology Adop&on Index
Z score values
GIS Lab, SSD, IRRI-‐ Parvesh Kr Chandna@2014 – Unpublished
IRRI
Farmers from 623 villages (out of 3523 villages), are fast adaptor to new technologies, covering an area of 2,00,000 ha
Results…
Conclusion PTAI, a proxy index can be a very handy tool in absence of detailed bio-‐physical datasets PTAI can be used for quick dissemina(on In favourable area where score is high or very high. Composite Index of Ex. Domains+PTAI will further improve the chances of improved targe(ng Further study is needed to validate and improve the Index
Thank you