In spatial econometric models, the specification of the spatial weight matrix is of notable influence on the model estimation result. Therefore, how to specify a reasonable spatial weight matrix has long been one of the important issues in spatial data modeling. In this article, we construct a distance decaying spatial weight matrix with a controlling parameter. This spatial weight matrix has better adaptability and interpretability. Based on the constructed spatial weight matrix, a new spatial lag model is proposed and its maximum likelihood estimation procedure is formulated. Furthermore, a simulation study and real-life data analysis are conducted. The results demonstrate that the maximum likelihood estimation of the new model performs well in estimating the model parameters and the constructed spatial weight matrix can efficiently fit the spatial autocorrelation among the observations of dependent variables.