Evaluation of International Investment Potential in Agriculture Based on the Random Gravity Model and Analysis of Influencing Factors

This study employs the stochastic frontier gravity model to evaluate the international investment potential of Xinjiang's agriculture and to analyze policy effects. Panel data from 2005 to 2023 between Xinjiang and its major agricultural investment partner countries were used to construct the model. Parameters were estimated using the Maximum Likelihood Estimation (MLE) method, focusing on variable significance and technical inefficiency terms to assess investment potential. Policy variables were further dis aggregated to examine the effects of different policies on agricultural international investment. Results show that Xinjiang has significant agricultural investment potential. Central Asian countries, Russia, and Pakistan are identified as key regions with high investment potential. Economic scale and population size have positive impacts on investment, while geographical distance has a negative effect. Policy factors are also found to play a crucial role, with free trade zones showing the most significant promotional effect. This study contributes to the literature by addressing the efficiency aspects often overlooked in previous research and offers methodological innovation and practical policy implications for attracting international investment and promoting agricultural modernization in Xinjiang.