Hi, I am using Stata 13 and I have some sales data from a few stores. I scaled the sales data by store size and plotted it over time. I just wanted to get a feel for the data. It looks a bit funny (see the graph below).

There are a few stores that do not have any (what seems like) seasonal fluctuation over time. I wonder if there is any smart way to identify these stores systematically? My initial idea was to identify them by variance. Here is what I did:
But that is such a crude way of doing it. Any idaes? I think it is a very interesting problem 
Thank you in advance! /R
There are a few stores that do not have any (what seems like) seasonal fluctuation over time. I wonder if there is any smart way to identify these stores systematically? My initial idea was to identify them by variance. Here is what I did:
Code:
gen year_month = mofd(Date)
format year_month %tm
*scale monthly sales by size
gen monthly_sales_by_size = monthly_sales/Size
*Some graphs to get a feel for the data
line monthly_sales_by_size year_month
*get variance by store
bysort Store: egen sales_variance = sd(monthly_sales_by_size)
sum sales_variance
drop if sales_variance <0.005
line monthly_sales_by_size year_month, legend(size(medsmall))

Thank you in advance! /R

Comment