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2008•RePEc: Research Papers in EconomicsRequires access

A Binary Logit Analysis of Factors Impacting Adoption of Genetically Modified Cotton

Swagata Banerjee, Steven W. Martin

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Abstract

Agricultural Resource Management Survey (ARMS) data for 2003 were used to estimate two binary logit models for two definitions of genetically modified (GM) cottonseed adoption. Results indicate conservation tillage did not positively affect adoption of GM cotton with either of these definitions, while adoption of GM cotton in the previous year did. Refuge cotton also did not affect these adoption decisions for the study year.

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What this paper is about

Agricultural Resource Management Survey (ARMS) data for 2003 were used to estimate two binary logit models for two definitions of genetically modified (GM) cottonseed adoption. Results indicate conservation tillage did not positively affect adoption of GM cotton with either of these definitions, while adoption of GM cotton in the previous year did. Refuge cotton also did not affect these adoption decisions for the study year.

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Available abstract

Agricultural Resource Management Survey (ARMS) data for 2003 were used to estimate two binary logit models for two definitions of genetically modified (GM) cottonseed adoption. Results indicate conservation tillage did not positively affect adoption of GM cotton with either of these definitions, while adoption of GM cotton in the previous year did. Refuge cotton also did not affect these adoption decisions for the study year.

Key concepts: Binary logit model, Logit, Affect (linguistics), Bt cotton, Mixed logit, Logistic regression, Cottonseed, Agricultural economics

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