The Modeling And Application Of Interactive Fixed Effects Counterfactural Model In Policy Evaluation

The counterfactual framework is an important part of causal inference.It comes from the field of micro-project evaluation and has become the mainstream in macro-policy evaluation.Due to the strict assumptions and insufficient macro data,traditional methods like DID and PSM are not suitable for macroeconomic policy evaluation.Scholars have developed many other methods such as PSM-DID and synthetic control.The article first sorts out the"counterfactual",method in policy evaluation.Then introduces the interactive fixed effect counterfactual model.Based on the previous research,the article combines the panel interactive fixed effect model,the panel smooth transition regression model and the counterfactual framework to establish a nonlinear counterfactual model with interactive fixed effects,and proves the identifiability of the average treatment effect on the treated.Next,it compares the new model with some commonly used methods such as DSGE model,DID and synthetic control method,which proves that it has certain comparative advantages in terms of robustness,operability and interpretability.The Monte Carlo simulation was used to do quantitatively analysis under finite samples.As an empirical illustration,the article uses the new method to evaluate the impact of "Withdraw County to Set District" policy.Then uses DID and IFE without covariates as robustness examination.The results show that the policy has a significant negative impact on rural per capita net income.Finally,give some policy recommendations.