What Determines How Green Crop Farming Can Get? Spatial Factors or Green Awareness Spillovers

Abstract

This study intends to examine if traditional local factors (climatic conditions) and/or green awareness spillovers contribute to the spatial dependency of farmland allocated to organic farming after its uptake in Taiwan. To investigate the push and pull factors to improving the policy targeting for environmentally-friendly farming practices, we employ both data-driven and model-driven approaches to conduct the spatial analyses of the adoption intensity of organic farming. Based on township-level data constructed from 213,534 rice farm households drawn from the 2015 Agriculture Census data, we find high-high clusters (hot spots) are mostly in the northern and the eastern parts of Taiwan, whereas the majority of low-low clusters (cold spots) locates in central and southern Taiwan. The results from the spatial lag Tobit regression estimation provide empirical evidence supporting the role of local climatic conditions and green awareness spillovers in explaining the spatial patterns of organic agriculture in Taiwan. In light of the stylized fact that the majority of the rice farm household in Taiwan is small with 84% has farmland area less than one hectare, the findings provide practical references to policy practitioners in tailoring farm program or policies in line with the notion of inclusive and sustainable development.

Keywords: adoption intensity, exploratory spatial data analysis, green awareness spillover, organic farming, spatial lag Tobit model