I was wondering if it makes sense to run a linear regression when my dependent variable only has 20 observations in total (I do have it for 6 years).
This is the scenario: 20 observations consists which is one observation for every neighborhood in a certain city. Furthermore, I have 6 independent variables with just as many datapoints (which makes sense since I have data for each neighborhood). There is really also no way to increase the datapoints, unless I look at street level data (which I do not have).
I was wondering if it is still possible (since it does represent each part of the city) to draw a useful conclusion from said linear regression.