For millions of immigrants, arriving in a new country means navigating not just cultural shifts but economic hurdles.

Today's students upload content to an AI and present its analysis as their own thinking. Research reveals why this cognitive ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Led by Dr Michael Short, the project focused on developing a methodology to inform carbon reduction planning for Ashford and St. Peter’s Hospitals NHS Foundation Trust (ASPH), using detailed analysis ...

Large language models (LLMs) enable researchers to analyze text at unprecedented scale and minimal cost. Researchers can now revisit old questions and tackle novel ones with rich data. We provide an ...

This document describes the technical needs that have given rise to a Fund’s technical assistance (TA) project for the development of a customized structural micro-founded (DSGE) model in the Ministry ...

In the natural sciences, a laboratory experiment can isolate variables, various particles and their movements. Similarly, the employment of an econometric model is an attempt to produce an economic ...

This is the seventh in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of ...

SOE Dean Professor Li Jia is building critical knowledge of AI to further the School’s research excellence in econometrics and international trade. SMU Office of Research – When Professor Li Jia was ...

Having spent over 2 decades in banking and financial services, I have seen how financial models evolve, but never at the speed seen today. AI is reshaping credit risk assessment, offering a more ...

The global banking sector is navigating unprecedented challenges volatile markets, evolving regulatory demands, and increasing customer expectations for speed and accuracy. Traditional risk assessment ...