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This study investigates the economic outcomes of organic farming controlling for the four major aspects of a cropping system, including climate, genotypes, management and soil. Considering possible variations in treatment responses, this study also presents empirical evidence of heterogeneous treatment effects associated with spatial agglomeration or farm covariates.

Rice farm households data taken from the 2015 Agriculture Census is merged with township-level seasonal weather data, crop suitability index and average income per capita in Taiwan. To address the selection bias problem, the authors apply the Probit-2SLS instrumental variable (IV) method in the binary treatment model under homogeneous and heterogeneous assumptions.

It is found that organic farming leads to a significantly positive effect on rice farms' economic performances in terms of cost reduction and profit growth. This positive treatment effect is more sizable with spatial agglomeration. Furthermore, the treatment effect of organic farming is found to vary with the farm characteristics such as farmland area and the number of hired workers.

Two important implications for the promotion of sustainable agri-food production are inferred: (1) establishing organic agriculture specialized zones may benefit rural development; (2) providing economic incentives to small farms to expand their scale may be a more effective policy means to promote sustainable agri-food production.

The findings in this study complement the body of knowledge by drawing insights from the agriculture census data and providing profound evidence of the heterogeneous outcomes of organic farming due to spatial clustering and farm covariates.