Conversion to Organic Farming in the Continental United States: A Geographically Weighted Regression Analysis
Organic agriculture has expanded greatly over the past decades, but the rate of conversion has not been evenly distributed across the United States. Measures of spatial concentration such as local Moran's I show that the highest rates of conversion are clustered in the Western United States, especially California, Washington, and Oregon, but also on the East Coast in New England. The influence of several variables on the spatial distribution of organic conversion is first explored through ordinary least squares regression analysis and then through a more localized technique called geographically weighted regression (GWR). Of the analyzed factors, share of existing organic farms, prevalence of full-time operators, and average farm size were found to be significant determinants of organic agriculture conversion rates. Furthermore, results show that spatial dependence is highly influential on the distribution of farms that are converting to organic production, suggesting the existence of relevant agglomeration effects. The GWR model suggests significant variation in the relationship between average farm size and conversion rates: The relationship is negative in most of the country and positive only in the Northeast and parts of the Western United States. These results highlight the need to consider local models in conjunction with global regression techniques for a better understanding of the spatial relationship between conversion to organic production methods and potential determinants. © 2013 Copyright Taylor and Francis Group, LLC.
geographically weighted regression, location quotient, organic agriculture, organic conversion, spatial dependence
Taus, Alina; Ogneva-Himmelberger, Yelena; and Rogan, John, "Conversion to Organic Farming in the Continental United States: A Geographically Weighted Regression Analysis" (2013). International Development, Community, and Environment. 305.