A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers

Bibliographic Details
Main Authors: Ma, Xingliang, Shi, Guanming
Format: Journal Article
Language:Inglés
Published: Wiley 2015
Subjects:
Online Access:https://hdl.handle.net/10568/150872
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author Ma, Xingliang
Shi, Guanming
author_browse Ma, Xingliang
Shi, Guanming
author_facet Ma, Xingliang
Shi, Guanming
author_sort Ma, Xingliang
collection Repository of Agricultural Research Outputs (CGSpace)
format Journal Article
id CGSpace150872
institution CGIAR Consortium
language Inglés
publishDate 2015
publishDateRange 2015
publishDateSort 2015
publisher Wiley
publisherStr Wiley
record_format dspace
spelling CGSpace1508722024-11-15T08:52:34Z A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers Ma, Xingliang Shi, Guanming agricultural technology technology transfer farmers soybeans innovation adoption structural dynamics genetically modified organisms structural change bayesian theory seed technology 2015-01-01 2024-08-01T02:54:07Z 2024-08-01T02:54:07Z Journal Article https://hdl.handle.net/10568/150872 en Limited Access Wiley Ma, Xingliang; and Shi, Guanming. 2015. A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers. Agricultural Economics 46(1): 25-38. https://doi.org/10.1111/agec.12124
spellingShingle agricultural technology
technology transfer
farmers
soybeans
innovation adoption
structural dynamics
genetically modified organisms
structural change
bayesian theory
seed technology
Ma, Xingliang
Shi, Guanming
A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title_full A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title_fullStr A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title_full_unstemmed A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title_short A dynamic adoption model with Bayesian learning: An application to U.S. soybean farmers
title_sort dynamic adoption model with bayesian learning an application to u s soybean farmers
topic agricultural technology
technology transfer
farmers
soybeans
innovation adoption
structural dynamics
genetically modified organisms
structural change
bayesian theory
seed technology
url https://hdl.handle.net/10568/150872
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AT shiguanming adynamicadoptionmodelwithbayesianlearninganapplicationtoussoybeanfarmers
AT maxingliang dynamicadoptionmodelwithbayesianlearninganapplicationtoussoybeanfarmers
AT shiguanming dynamicadoptionmodelwithbayesianlearninganapplicationtoussoybeanfarmers