#StackBounty: #regression #machine-learning #econometrics #regularization Prediction model with constraint / penalty

Bounty: 50

I am attempting to predict rental price (Sq/ft) for a Retail space. I have a vector of demand / economic variables and other control variables such location and time fixed effects. I’d like to add a constraint to the model for balancing loss due to vacancy.

The data is at monthly level.

Model specification:

Pt = b0 + b1*Dt + b2*Lt + b3*Vt + b4*St + b5*Sup + e 


Pt = Rental Price
St = Type of the space - categorical variable 
Dt = Demand variables
Lt = Location variables
Sup = Available comparable supply / Vacancy
Vt = Loss due to vacant days ($) 

Vt is the constrain in the model. 

I am looking for advise on:

  1. Appropriate model to use (Linear or Non-Linear) and metrics to use for evaluation.
  2. How to treat constraint variable? Regularization or other approaches?
  3. Fit a model separately for space type or if included as a variable, how do I estimate the effect of each space type (categorical variable) separately?

Get this bounty!!!

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