I am looking to calculate the equilibrium price, i.e an optimal price that I can set without affecting demand and maximize revenue.
I've gathered historical data: occupancy rates, asking rents for different property types by submarket / market and have a bunch of other data including local economic variables, new construction, location characteristics etc. Here's how I am thinking about estimating the demand function -
First predict demand, occupancy rates using Regression with fixed effects and historical prices for a particular property type in a given submarket. The training data for this is last 5+ years of historical data.
Approx. Model specification:
Dp = bo + b1*(Econ) + b2*Supply + b3*Loc + b4*Price t + b5*Price t-1 + b6*Price t-2
With this, I can get an estimate of how much price can change without significantly affecting quantity demanded. The assumption here is all else being equal. However, supply/vacancies changes.
So, my question is how would you model this? Are there any other analytical/ML approaches to model this and calculate equilibrium price?