I have daily sales data and stock availability for items in a supermarket chain. My goal is to estimate the sales quantity elasticity with respect to availability (represented as a percentage). With this model, I want to understand how a 1% change in availability impacts sales. Currently, single-variable regressions yield low R-squared values. Should I include lagged sales values in the regression to account for other endogenous factors influencing sales? This would isolate availability as the primary exogenous variable
Well, I don't get a clear picture of the variables you are considering for your study. Since you are considering daily data and you have more than one variable you can either apply non-linear ARDL(s) or multivariate volatility models depending on the objectives of your study. Bear in mind that the pre-tests are highly instrumental to the choice of models.
Best wishes!
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