Improving Smallholder Agriculture Via Video-Based Group Extension
Providing technical advice at scale poses operational challenges, particularly with respect to managing a sufficiently large staff. Technology may help, but risks reducing efficacy given reduced customization and human interaction. We tested a video added onto standard human-provided extension services promoting a climate-smart practice, System Rice Intensification in India. Using frequentist statistical methods, we find large but imprecisely estimated treatment effects: the 95% confidence interval is 10kgs to 500kgs and 717Rps to 9650Rps for output and profits, respectively. However, our data are not normally distributed: specifically, key outcomes have fat tails. A Bayesian hierarchical model finds smaller but more precise treatment effects: analogous 95% intervals from -8kgs to 70kgs and -193Rps to 1380Rps. We also test two messaging sub-treatments designed to address commonly cited constraints to adoption: labor needs and self-efficacy. A frequentist analysis shows no added gains, while the Bayesian shows an added benefit when delivered in tandem
Year of publication: |
2023
|
---|---|
Authors: | Baul, Tushi ; Karlan, Dean ; Toyama, Kentaro ; Vasilaky, Kathryn N. |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Toyama, Kentaro, (2014)
-
Myths about ICT for the other billions
Toyama, Kentaro, (2010)
-
Text-Free User Interfaces for Illiterate and Semiliterate Users
Medhi, Indrani, (2007)
- More ...