Advertisement
Advertisement

More Related Content

Similar to Potential technology adoption: Index for improved targeting: A village level proxy assessment using the past adoption rates of agricultural technologies(20)

More from International Water Management Institute (IWMI)(20)

Advertisement

Recently uploaded(20)

Potential technology adoption: Index for improved targeting: A village level proxy assessment using the past adoption rates of agricultural technologies

  1. 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  
  2. ?   ?   ?   ?  ?  ?   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  conduct  a   quick  and  dirty  exercise  
  3.     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
  4.     v               Study  Area   v               Datasets  used     v               Methods     v               Results   v               Conclusion       IRRI
  5. Bangladesh   Barisal   IRRI
  6. 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
  7. Datasets:    few  examples   Pumping  sets   Power  (llers     HYVs  
  8. 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  
  9. 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…  
  10. 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        
  11. Thank you
Advertisement