We loaded the z-tree output files into excel separately and dropped the unnecessary variables

Then we calculated the effective price in excel for POM and PM treatments where price matching was available.
Then we loaded the excel files into Stata separately and created the effective price for O and PO in Stata. 
The rest can be found in the do-file attached here. 

Variables:
"p1" is the price that the subject chose whereas "p2" is the opponent's price.
"x1" is the output that the subject chose whereas "x2" is the opponent's quantity.
"Subject" is the subject ID and is used for creating unique "id" across treatments.
"Group" is the number for each group (of two players in each period)
"section" is the id for the block of six subjects who interacted with each other. This is our cluster level for the regression models
"pi1" is the profit for the subject whereas "pi2" is the profit for the opponent in the group.
"sigma1" is subject's choice for whether to price match or not. 1 means that the subject chose to price match. "sigma2" is that of the opponent
"p" is the market price once the market clears within each group. 