Econometric Theory publishes original, rigorous research that advances the theoretical foundations of econometrics across all major areas of the field. The journal’s mission is to publish research of the highest scholarly quality that strengthens the probabilistic and statistical underpinnings of econometric methodology and provides a solid foundation for modeling, estimation, prediction, and inference. It recognizes the central role of theoretical econometrics in economics, business, and other social sciences, and increasingly in multidisciplinary settings involving statistics, data science, machine learning, and selected natural sciences. The journal welcomes contributions addressing modern challenges arising from large-scale data, high-performance computing, and artificial intelligence, and encourages connections with related disciplines such as probability theory, statistics, mathematical finance, and computational economics. It values work that unifies, extends, or reinterprets econometric theory through new perspectives, generalizations, or more elegant methods, and encourages submissions that contain practical applications of new theory and promote best practices in econometric analysis. In addition to original research articles, the journal also publishes historical studies on the evolution of econometric thought and interviews with leading scholars.