TY - JOUR
T1 - Social Learning and Farm Technology in Ethiopia
T2 - Impacts by Technology, Network Type, and Poverty Status
AU - Liverpool-Tasie, Lenis Saweda O.
AU - Winter-Nelson, Alex
N1 - Funding Information:
Department, Addis Ababa University (AAU), the Centre for the Study of African Economies (CSAE), University of Oxford and the International Food Policy Research Institute (IFPRI). Funding for ERHS data collection was provided by the Economic and Social Research Council (ESRC), the Swedish International Development Agency (SIDA) and the United States Agency for International Development (USAID); the preparation of the public release version of these data was supported, in part, by the World Bank. AAU, CSAE, IFPRI, ESRC, SIDA, USAID, and the World Bank are not responsible for any errors in these data or for their use or interpretation. We thank the IFPRI, Addis Ababa Office for their assistance in the execution of the household survey in two of the 15 ERHS peasant associations. We also thank Christopher Barrett and two anonymous referees for comments on an earlier draft.
PY - 2012/10
Y1 - 2012/10
N2 - Improved farm technologies in Ethiopia display high levels of promise and low rates of adoption. This article studies the impact of social networks on technology adoption focusing on social learning through networks based on physical proximity and those based on intentional relationships. Impacts by network type, technology, and asset poverty status are explored. Social learning is more evident for households not in persistent poverty, for more complex technologies, and within networks based on intentional relationships rather than proximity. Results indicate that technology diffusion in Ethiopia is likely to be enhanced if extension can target intentional networks, rather than spatial clusters.
AB - Improved farm technologies in Ethiopia display high levels of promise and low rates of adoption. This article studies the impact of social networks on technology adoption focusing on social learning through networks based on physical proximity and those based on intentional relationships. Impacts by network type, technology, and asset poverty status are explored. Social learning is more evident for households not in persistent poverty, for more complex technologies, and within networks based on intentional relationships rather than proximity. Results indicate that technology diffusion in Ethiopia is likely to be enhanced if extension can target intentional networks, rather than spatial clusters.
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U2 - 10.1080/00220388.2012.693167
DO - 10.1080/00220388.2012.693167
M3 - Article
AN - SCOPUS:84868704485
SN - 0022-0388
VL - 48
SP - 1505
EP - 1521
JO - Journal of Development Studies
JF - Journal of Development Studies
IS - 10
ER -