I have a longitudinal dataset, which contains observations of individuals between 2008-2017. I want to examine only one year period, but it contains too few observations, that is why I have decided to combine all the years to make a pool. However, now, I am not sure what kind of regression to choose in order to find out the relationship between the dependent and independent variables. The types of variables are illustrated in the table below:
| Response variable | dummy |
| Variable of interest | dummy |
| Control variables | different ones (dummy, float, etc.) |
2) May I just use probit regression by not paying attention to years while using the pool regression (similar to that one I would use if I worked with cross-sectional data)?
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