Chapter 5 describes the empirical strategy (including empirical models, variables, and data, etc.) used to analyze the effects of green trade barriers on corporate's pollution emissions. Overall, the study employs a two-step approach. First,Propensity Score Matching (PSM) is used to mitigate sample selection bias by matching enterprises exposed to green trade barriers with those not exposed, based on similar characteristics. Second, a Difference-in-Differences (DID) method is applied to estimate the causal impact of green trade barriers on pollution emissions. The study further includes a series of control variables such as enterprise size, age, capital intensity, financing constraints, and industry factors to account for potential confounders. The dataset is derived from several sources, including the China Industrial Enterprise Database and the WTO Environmental Database. Our empirical research framework provides insights for assessing how green trade barriers influence pollution reduction efforts among manufacturing firms.