Hello everyone, referring to my current study mentioned here: https://www.statalist.org/forums/for...c-price-method

Currently, I have a total of 5 housing variable, 14 distance variable (12 are distance to parks), and 12 size of parks variables. The data is for 6 years and there are 645 observations. My initial plan was to only look at the distance of the closest park and its respective size (not to include all 12 parks). However, I noticed that the two specific variables are not significant. Explains why I decided to include all parks variables in the analysis.

The plan was to run three separate models (Model 1 consist of housing variables; Model 2 consist of housing and distance variables; Model 3 consist of housing and size of parks variables).

I did not experienced any problems with the first two models whereby I ran the Pooled OLS, xtreg, re and xtreg, fe. However, coming to the third model the minute I ran regress for housing and size variables, the results informed me all of the size variables were removed due to collinearity. Likewise for re. I know it does so for fe as the size variables are time invariant in which some of them are the same throughout the years (correct me if my definition is wrong).

I have also done the necessary test to identify which model between the three are more advisable to be used.

I don't plan on using xtreg, be as the OLS and random effect model is much efficient (?).

Would appreciate if anyone could provide comments or advice on the matter.