Feature Selection Phase I am trying to predict the overall age of an opportunity (creation date - closing date) this is my response variable

lets say an opportunity  passes through 3 stages
to close

For example: Opp x stayed in


stage 1 : 30 days
stage 2 : 10 days
stage 3:  20 days


At stage 3 I might close it same date or wait some time

so if I waited some time to close, it will be createdon: 22/11/2018 &amp; closedon:9/2/2019

There is opp y , where i close it in same date of stage 3, so createdon:22/11/2018 and closedate: 21/1/2019

Summary

+---------+--------+--------+--------+--------+
| OppName | oppAge | stage1 | stage2 | stage3 |
+---------+--------+--------+--------+--------+
| x       |     79 |     30 |     10 |     20 |
| y       |     60 |     30 |     10 |     20 |
+---------+--------+--------+--------+--------+


my question is :


Can I include stage1,2,3 as my independent variables to create a regression model?
They seem to nearly make the model ideal, so is it better to include maybe only stage 1? without 2 &amp;3


Work Done ,Added Edits


I transformed stages to a categorical nature, for example &lt;30 days to 1 month
30-60 day transformed it to 1-2months and so on

 +-----------+
|  stage1   |
+-----------+
| &lt;1month   |
| 1~2months |
| 6~7months |
+-----------+

Then I did one-hot encode to the stages like stage 1
Then I stopped ,wasn't sure whether to include everything or what?
One-hot encode those three Stage variables instead of including all three of them. And again, include any of those at all, ONLY if they hold relevance so a pre-hand PCA won't be a bad idea overall.