Escaping Famine Through Seasonal Migration
In: Yale University Economic Growth Center Discussion Paper No. 1032
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In: Yale University Economic Growth Center Discussion Paper No. 1032
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Working paper
In: Journal of development economics, Band 153, S. 102710
ISSN: 0304-3878
In: Asian Development Review 37:2, 2020
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In: NBER Working Paper No. w24193
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In: The Economic Journal, Band 122, Heft 565, S. 1143-1176
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In: Economic Development and Cultural Change, Band 59, Heft 4, S. 723-751
ISSN: 1539-2988
In: Applied economic perspectives and policy, Band 45, Heft 4, S. 1863-1879
ISSN: 2040-5804
Abstract75% of the world's poor reside in rural areas where the local economy is tied to agriculture. We interpret new panel data on COVID‐19 from Nepal and Bangladesh in relation to agricultural seasonality. Conditions in April–June 2020 were comparable to a typical lean season even though the pandemic arrived at harvest time. Income losses stem from both depressed local employment as well as lower migration and remittances. We also document indirect adverse health impacts on nutrition and mental health. Findings are specific to the nature of economic activity at harvest, and effective pandemic policy must evolve with the agricultural season.
In: American economic review, Band 111, Heft 6, S. 1918-1943
ISSN: 1944-7981
Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low. (JEL O13, O18, O33, Q12, Q16)
In: CEPR Discussion Paper No. DP15994
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In: Journal of development economics, Band 153, S. 1-10
ISSN: 0304-3878
World Affairs Online
In: Journal of development economics, Band 143, S. 102380
ISSN: 0304-3878
In: Journal of development economics, Band 143
ISSN: 0304-3878
World Affairs Online
SSRN
Working paper
In: NBER Working Paper No. w26082
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Working paper
In order to induce farmers to adopt a productive new agricultural technology, we apply simple and complex contagion diffusion models on rich social network data from 200 villages in Malawi to identify seed farmers to target and train on the new technology. A randomized controlled trial compares these theory-driven network targeting approaches to simpler strategies that either rely on a government extension worker or an easily measurable proxy for the social network (geographic distance between households) to identify seed farmers. Our results indicate that technology diffusion is characterized by a complex contagion learning environment in which most farmers need to learn from multiple people before they adopt themselves. Network theory based targeting can out-perform traditional approaches to extension, and we identify methods to realize these gains at low cost to policymakers.
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