The economy in merged districts is largely driven by the agriculture sector. However, the agricultural productivity is not as strong as the potential of success in the sector. Interventions focused on resolving the issues faced by farmers on grassroots level are the need of the hour. Some of these interventions were discussed in the policy webinar called “Use of Evidence in Agricultural Programs” organized by Merged Areas Governance Project (MAGP) of United Nations Development Programme (UNDP). The webinar was part of an on-going policy seminar series centered around behavioral interventions and field experiments in the agricultural sector of developing countries.
Government officials, researchers and development practitioners debated the steps of a comprehensive roadmap of behavioral interventions and field experiments.
In his opening remarks, KP Agriculture, Livestock Fisheries & Cooperatives Department Secretary Muhammad Israr reiterated government’s commitment to revolutionizing the agriculture sector via effective, result-oriented schemes and use of technology. “An integrated approach was adopted to improve the livelihood opportunities, designing area-specific projects based on the local resource base”, he said. “One way in which this was achieved was through providing improved seeds of maize, wheat, potato and vegetables along-with tool kits and pesticides and weedicides to farmers,” he added, sharing that the department plans to take on innovative interventions to amend the behavior of farmers to undertake novel technologies in near future.
Commending the government on its efforts, UNDP Agriculture Specialist Shad Muhammad shed light on the challenges in the MAs including various behavioral biases, risk and ambiguity perceived by farmers, their limited knowledge and skills, and severe credit constraints faced by agricultural producers. UNDP Agriculture & Horticulture Specialist Dr Tigran Melkonyan, who was also the keynote speaker in the panel, presented the main components of designing effective interventions. This includes identifying and collecting data on agricultural practices and potential outcomes, and establishing a scientific basis for the intervention, formulating a hypothesis, and testing statistical procedures to estimate the efficacy of the intervention. Building on those results, Melkonyan said an actionable plan of the intervention and procedures can be created to effectively monitor implementation.