Random Effects Model in Panel Data: Empirical analysis based on Poverty Governance in China

Due to the panel data has dual dimensions of cross-sectional data and time series data, the estimation method of it has rigorous mathematical derivation and is widely used in empirical studies of economics and social sciences. Thus, this paper focuses on the application of panel data in empirical analysis. For this reason, this paper first described the panel data in detail, and explained the application conditions and mathematical derivation steps of fixed effect model and random effect model in detail. Secondly, taking the poverty alleviation experience from China as an empirical test, we explained how the poverty alleviation data can be applied to the panel data requirements, and used Hausmann test to determine the random effect model which is contrary to the estimation of the fixed effect model commonly used in economic theory. The result showed that the random effects model can fit the data well and also provide an empirical basis for the choice of governance strategies in poverty governance. Therefore, the research results further deepen the study of application scenarios of panel data analysis, and provide reference significance in the theoretical and practical aspects of poverty alleviation.