Aiming at the limitations of the static grey clustering method, a grey possibility clustering method is proposed to solve the problems of panel data, synthetically considering the growing trend, index weight, and time weight. In this method, the development factor is defined to express development tendency for observed values. Subsequently, according to the time weight in different time point, each index value of the evaluation object is aggregated into development action value by growing factor, and development action values are aggregated to obtain information assemble values for reducing the dimension of the panel data. Meanwhile, the index weights in different time points are determined by using the proposed method. Apart from these above index weights, the comprehensive weight for the whole time period is measured by minimizing the sum of squares of deviations. Furthermore, the information assemble values after information aggregation are clustering analyzed by utilizing the grey possibility function. Finally, the experimental results generated by using the economic and social data from China's 10 cities in 5 years verify the practicality and effectiveness of this proposed model, and the proposed model realizes the grey possibility function clustering for panel data.