I am currently engaged in a research project for my PhD where I am preparing a pseudo-panel for conducting a differences-in-differences (diff and diff) analysis. However, I have encountered certain challenges that I would like to discuss and seek guidance on.
Firstly, I have a set of binary variables that need to be aggregated to form the pseudo-panel, but I am unsure of the best approach to tackle this process. I would appreciate suggestions or recommended methodologies for effectively aggregating these binary variables.
Additionally, some of these binary variables are interrelated, and my intention is to perform an exploratory factor analysis (EFA) with them. However, I have come across literature suggesting that conducting EFA with binary variables over multiple years may introduce inconsistencies in the data. Could anyone provide insights on how to handle this situation or if there is a more suitable alternative?
I appreciate any contributions or recommendations that you may offer to overcome these challenges in my research.
Best regards,
Firstly, I have a set of binary variables that need to be aggregated to form the pseudo-panel, but I am unsure of the best approach to tackle this process. I would appreciate suggestions or recommended methodologies for effectively aggregating these binary variables.
Additionally, some of these binary variables are interrelated, and my intention is to perform an exploratory factor analysis (EFA) with them. However, I have come across literature suggesting that conducting EFA with binary variables over multiple years may introduce inconsistencies in the data. Could anyone provide insights on how to handle this situation or if there is a more suitable alternative?
I appreciate any contributions or recommendations that you may offer to overcome these challenges in my research.
Best regards,
