This article proposes a model of technology adoption that integrates demand for individual traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics. The model is applied to recent genetically modified corn adoption data from Minnesota and Wisconsin farmers, using a mixed-multinomial logit (MMNL) model to estimate the effects of traits and farm and farmer characteristics on adoption outcomes. This approach allows explicit recovery of estimates of farmers' shadow prices for individual technology traits. Results show the importance of producer and regional heterogeneity in preferences for seed traits. Copyright Copyright 2009 Agricultural and Applied Economics Association.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.