This research is a meta-analysis that focuses on farmers’ willingness to accept adopting sustainable practices. We use a set of meta-regressions and statistical tests to analyze 59 studies providing 286 WTA estimates. Our aim is to examine gaps in the literature of sustainable agriculture adoption and highlight the major findings of peer-reviewed works. We found evidence for significant methodological factors affecting WTA values, and the presence of unique Willingness to Accept mean value that would be the true proxy for how much farmers’ must be compensated to adopt sustainable agriculture practices.

We investigate US consumers' willingness to pay for cotton apparel production and country of origin attributes. Using a choice‐based conjoint experiment and information treatments, we examine the preferences of 727 US shoppers for the attributes: cotton fiber production systems and country of manufacture of the cotton fiber. Random utility theory is the basis for the survey's responses analysis to estimate willingness to pay (WTP) values for the attributes. Choices made by consumers are modeled using a mixed logit model in WTP space estimated using simulated maximum likelihood procedures. Results show that consumers are willing to pay more for cotton apparel from the United States than apparel from other countries, and more for apparel made from fiber produced in organic systems than in conventional systems. Only some subgroups of consumers were found to be affected by exposure to an information treatment regarding potential labor exploitation in cotton farms and textile mills. [EconLit Citations: D12].

This article introduces concepts related to carbon sequestration, credits, and markets to help Extension agents, farmers, and concerned residents to better understand how agriculture can help to mitigate climate change, and thus become a part of Florida’s carbon economy. Written by Young Gu Her, Tara Wade, Sawssan Boufous, Jehangir Bhadha, and Michael Andreu, and published by the UF/IFAS Department of Agricultural and Biological Engineering, May 2022.

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