Spatial Distribution Characteristics and Influencing Factors of the Success or Failure of China’s Overseas Arable Land Investment Projects—Based on the Countries along the “Belt and Road”

Abstract

As globalization continues, overseas arable land investment is becoming a viable option for China to alleviate its agricultural growth constraints, and the “Belt and Road” initiative offers plenty of opportunities for China to invest in overseas arable land. This study used data from the Land Matrix, KOF, World Bank, CEPII, UNCTAD and other databases to analyze the spatial distribution characteristics and factors influencing the success or failure of China’s overseas farmland investment projects in countries along the “Belt and Road” project through spatial analysis and the Logit model. The results show that North America has the largest share of production versus contracted acreage in current acreage investment cases, and Asian projects have the highest success rate. Both successful and failed projects in China regarding arable land investment are highly correlated spatially and characterized by a strong concentration and low uniformity of distribution, with differences in the degree of concentration in Asia, Africa and other regions. The contracted area, host country participation and host country resource endowment, business environment and institutional quality have significant, inverted “U-shaped”, negative and positive effects on project success, respectively. In addition, the involvement of the host country has a significant negative impact on the success of investment projects in Africa, and the length of investment and the type of investment purpose have a significant positive and negative impact on the success of investment projects in Asian countries. Therefore, China’s overseas arable land investment should be based on a full examination of existing investment projects in each country, the selection of host countries with abundant resource endowments and a good business environment and institutional environment and the adoption of a model suitable for each location to carry out investments according to local conditions.