Global Endogenous Variate

Global endogenous variates represent variables within a system whose values are determined by internal factors within the system itself, rather than external influences. Current research focuses on mitigating the challenges posed by endogeneity in various contexts, including time series forecasting (using transformer architectures like TimeXer), causal inference (addressing issues in LLM-simulated experiments and loan pricing), and econometrics (developing methods like environment-invariant linear least squares and instrumental variable techniques). Addressing endogeneity is crucial for accurate modeling and prediction across diverse fields, improving the reliability of causal inferences, economic forecasts, and personalized pricing strategies.