For the earnings of the credit departments of the basic farmers' association (FA) in Taiwan, it has a great difference between urban areas and rural areas. Earnings of the FA in metropolitan area or adjacent metropolitan area are higher than that of the areas away from the metropolitan or pure agricultural areas. However, for the researches on the past, it did not consider the adjacent effect among the basic financial units. Therefore, this study will examine the spatial correlations and its adjacent effects with the spatial model. With 245 FA as a sample, independent variables are the ratio of deposit to loan, non-performing loan ratio (NPL ratio), and total revenue of the FA. Dependent variable is the earnings. From the results of the empirical study, it finds that earnings with high degree of spatial correlation. It shows that has a similarity among adjacent township areas and with phenomenon of agglomeration. From scatter diagram of the LISA on the earnings, the FA fall on the HH quadrant concentrated in northern area and fall on the LL quadrant concentrated in middle and southern areas. As to the model, after adding spatial factor to the model, it can increase the coefficient of determination. From parameter of test results, it shows that a very significant negative relationship between NPL ratio and earnings, and a highly significant positive relationship between total revenue and earnings. It is consist with the practices. However, for the traditional regression model will overestimate the impact of independent variable on the dependent variable, such as the impact of NPL ratio on the earnings, higher than spatial lag model 14.86%, higher than spatial error model 5.52%. For the impact of total revenue on the earnings, traditional regression model is higher than spatial lag model 9.53%, higher than spatial error model 4.57%.