## 4 Conclusions  
Based on the panel data of China's 20 dominant corn producing provinces, this study employs the ESDA method to explore the TRD of the CPC across the country and in various regions for the period between 2008 and 2018. Furthermore, a spatial panel measurement model is constructed to analyze the influence mechanism of sensitive factors on the CPC. The results firstly indicate that the production costs in China and the three major corn producing regions have a fluctuating upward trend from 2008 to 2018, which is mainly related to the surge in labor prices. Secondly, the CPC is observed to have significant spatial differences and generally show a trend of gradual increase from the east to the west. Over time, the number of relatively high-cost provinces has increased. Moreover, all of these provinces are located in the southern mountainous and hilly corn region, indicating that the gap in the CPC in this region is widening in comparison to other regions. Thirdly, the CPC between various regions has spatial correlation, and the spatial agglomeration characteristics are relatively stable. Lastly, factors such as the scale of land management, labor structure, degree of mechanization, and economic conditions have a considerable impact on the CPC in China. Among the above factors, the scale of land management, the degree of mechanization, and economic conditions have a negative impact on the CPC. Conversely, labor structure has been shown to have a positive impact on the CPC. Based on the above analysis, the following policy recommendations are put forward. Firstly, agricultural mechanization technology must be improved and promoted in order to reduce labor costs for corn production. Rising labor costs are the primary reason for the increase in the CPC in China. Thus, reducing the dependence of corn production on manual operations to save labor costs is the main way of lowering the CPC. The above may be achieved by strengthening agricultural machinery research, promoting agricultural mechanization technology, and encouraging farmers to use agricultural machinery for agricultural production. Secondly, this paper suggests the expansion of the land management scale and an increase in the level of large-scale corn production. To fully release the economic benefits of production scale, the paper recommends implementing large-scale planting in the northern spring corn area and the Huang-huai-hai summer corn area according to the local conditions. Furthermore, the transformation of land suitable for machinery should be accelerated to, in turn, provide conditions for expanding the scale of production. Thirdly, the current study proposes the improvement of social and economic conditions. Farmers should be encouraged to increase their investment in land and technology to match technology input with labor input, thereby reducing the CPC. Lastly, our study points to the need for further research in three directions. Firstly, our measurement of the CPC is not ideal, as a result of the cost subsidy in corn production not being available in the official statistical data set. Therefore, survey data of grain households, which include the cost subsidy, should be obtained in further studies of the temporal and spatial differences of China's CPC. Secondly, future research should focus on agricultural mechanization development in the southern mountainous and hilly area, which will aid the reduction of the CPC in this area. Finally, the paper has focused solely on four factors affecting the CPC. Other factors that were not considered may cause spatial differences in the CPC in various regions and demand further study. S.O. : conceptualization, methodology, visualization, writing--original draft, and writing--review and editing. J.H. : supervision, and writing--review and editing. M.Y. ([PERSON]): supervision, conceptualization, and writing--review and editing. M.Y. ([PERSON]): funding acquisition, supervision, conceptualization, and writing--review and editing. J.L. : supervision, and writing--review and editing.