Construction of Index Numbers using Dummy Variables

Dr Sonia Goel commenced the session by explaining the concept of dummy variables, which are binary variables used to represent categorical data. Various methods for constructing indices using dummy variables were discussed, including the weighted average method, factor analysis, and principal component analysis (PCA). Dr Sonia Goel elaborated on the steps involved in each method and highlighted their respective advantages and limitations.

The webinar showcased several real-world applications of indices constructed using dummy variables. Examples included consumer price indices, quality of life indices, and economic sentiment indices. Participants gained insights into how these indices are used in policy-making, market analysis, and academic research. Dr Sonia Goel also addressed common challenges encountered in index construction, such as data quality issues, selection bias, and multicollinearity. Best practices for mitigating these challenges were discussed, emphasising the importance of robust data collection methods and rigorous statistical analysis.

The webinar concluded with an interactive Q&A session, where participants had the opportunity to ask questions and seek clarification on key concepts and practical applications.

Participants gained a deeper understanding of the role of dummy variables in index construction and learned about different methods and best practices. The webinar served as a valuable resource for researchers, analysts, and practitioners involved in index construction and statistical modelling.