###### Abstract  
The corn production cost (CPC) in China is related to national food security. However, there are few studies on the temporal and regional differences (TRD) and sensitive factors in the CPC. In this paper, the TRD of the corn production cost across various regions, as well as over the entirety of the country from 2008 to 2018, is presented. It is based on the GIS exploratory spatial data analysis method (ESDA). Simultaneously, a spatial panel model is established to conduct an empirical analysis of the main factors affecting the CPC. The results from the period in question show that the CPC in China and the three major production regions present a fluctuating growth trend, mainly associated with the increase in labor prices. Moreover, the CPC exhibits significant spatial differences, and demonstrates an overall trend of gradual increase from the east to the west. Over time, the number of relatively high-cost provinces has increased. All are located in southern mountainous and hilly corn areas. In addition, the CPCs of various regions are spatially correlated. Factors such as the scale of land management, the degree of mechanization, and socioeconomic conditions have a significantly negative impact on the CPC in China. Furthermore, the labor structure has a notably positive impact on the CPC. com production cost; temporal and regional differences; sensitive factors; spatial panel model 202212020 January 202220 January 202220 January 202220 January 202220 January 202  
major regions account for 47.74%, 37.67%, and 10.24% of the total planting area [1]. In these three regions, the CPCs are too high, while the benefits are too low [5]. In turn, this severely affects the international competitiveness of Chinese corn production. Therefore, studying the temporal and spatial differences and causes of the CPC has both theoretical and practical significance for improving the efficiency of corn production, extensively reducing the CPC in various regions of China, improving the international competitiveness of Chinese corn and increasing the incomes of grain farmers. Previous studies concerning the CPC had mainly focused on the following aspects. Firstly, the focus was placed on the analysis of the comparative advantage of the CPC [6; 7; 8]. In other words, studies compared the differences in corn production cost structure between China and other developed countries based on either macro data or field survey data. Secondly, previous research dealt with the cost efficiency analysis of corn production [9; 10]. The DEA and other quantitative analysis methods were utilized to measure the cost efficiency index of corn production and analyze the contribution of factor inputs to cost efficiency. Lastly, analysis regarding variation in the CPC was conducted [11; 12; 13]. Considering the economic development cycle and other factors, studies examined the laws and trends of changes in the CPC. However, few studies analyzed the spatial distribution and change characteristics of the CPC from a spatial perspective. With respect to research related to sensitive factors, most scholars tended to discuss them at the theoretical level [14; 15; 16; 17; 18; 19], proposing that factors such as the scale of land management, labor, technical conditions, and the economic environment significantly affect the CPC. Furthermore, many scholars conducted quantitative analyses [15; 16], where the research methods primarily included descriptive statistical analysis, the double logarithmic linear regression model, stochastic frontier cost function model, etc. All the above methods commonly assumed that the regional variables were independent of each other and thus failed to consider the possibility of spatial dependence. Due to the previously discussed research gap, this article attempts to use statistical and ESDA analysis methods to systematically explore the characteristics of the temporal and regional differences of the CPC in China.