In today’s digital economy, data have become a valuable commodity. However, understanding data requires statistical knowledge and econometric application. This course is designed primarily to impart applied statistical and econometric knowledge to handle data using a number of econometric software. The main purpose of this course is to develop careers for professionals not only in the field of economic data analysis, but also in many social sectors and more importantly, the emerging multi-disciplinary sectors of data science. Such course is available in various universities, but the pluralistic nature of this course will be a value addition to the existing state of art.
This is an applied quantitative course using cutting-edge methods, including econometrics, statistical software applications (STATA, R, EViews, etc) and computational and programming tools (e.g. Python). What distinguishes these modules is the adoption of the modern learning-by-doing approach to teaching econometrics, which emphasizes the application of econometrics to real world problems. The focus is on understanding the theoretical aspects that are critical in applied work, the ability to correctly interpret empirical results and to unmask the various technical nuances for precise understanding.
Underpinning this program is a strong emphasis on quantitative skills applicable to the private and public sectors as well as a focus on faculty and student research.