I am modeling ridership data for specific routes by month over a number of years. Some routes have as little as about 1000 riders per month while other routes may have over 20,000 riders per month. I have been looking at different approaches to model this data including a panel data model and a generalized linear data model (poisson family). However, I have found some information that says you should only use the poisson family when you have a small range in data for the y variable.
Is there a better approach to modeling count data with a large range of y values than Poisson?