I have a panel data of 200 individuals around 100 weeks. A latent ability issue for individual may cause the estimation for one IV biased. This IV is continuous variable.
Except for panel fixed-effect model, I also try to use propensity score matching (PSM) to handle this endogeneity issue. My first question is, is PSM an appropriate approach?
If doable, my plan is to discretize this IV into a binary treatment variable. In this case, the treatment variable for one individual may be different in different periods (e.g., 1 in period 1, 0 in period 2, ..., 1 in period 10....). But I'm not aware of any package can deal with this situation.
Any direction to proceed is appreciated. And any other identification strategy to solve this latent ability issue is also welcome deeply.
Question also posted here,https://stats.stackexchange.com/ques...ing-by-periods
Except for panel fixed-effect model, I also try to use propensity score matching (PSM) to handle this endogeneity issue. My first question is, is PSM an appropriate approach?
If doable, my plan is to discretize this IV into a binary treatment variable. In this case, the treatment variable for one individual may be different in different periods (e.g., 1 in period 1, 0 in period 2, ..., 1 in period 10....). But I'm not aware of any package can deal with this situation.
Any direction to proceed is appreciated. And any other identification strategy to solve this latent ability issue is also welcome deeply.
Question also posted here,https://stats.stackexchange.com/ques...ing-by-periods
