Spatio-temporal Modeling Method Driven by Policy Variables and its Application in APEC Effect Evaluation

To address air pollution, the Chinese government has implemented a series of stringent energy-saving and emission-reduction measures to mitigate environmental damage. To gain a deeper understanding of the impacts of these policies on air quality, this paper proposes a policy evaluation framework based on a class of spatio-temporal model incorporating exogenous variables.

By integrating the generalized Yule-Walker estimation method, it innovatively addresses the challenges of estimating exogenous variables within the model. Through theoretical derivations, simulation experiments, and empirical analysis, the reliability and applicability of the proposed model are validated. Notably, in evaluating air quality management policies during the 2014 APEC summit, this study provides more detailed quantitative results, revealing the heterogeneous impacts of policy implementation across different times and regions.