I have a time-series of monthly revenues for a department in our company. As we are a service provider, management had the idea that this department’s revenue might be predictable by macroeconomic factors. In order to evaluate that, I have downloaded monthly stock prices of S&P 500 constituents that are in our client base. I have made a fixed effects regression that says that stock returns are negatively correlated with our revenues, which might be plausible for whatever reason (maybe they need more services when things are not going great?). However, I’m wondering if it’s valid to run the regression if a variable is a constant per cross-section in the panel.
My data structure is like below and I aggregated the data by ISIN, such that each ISIN gets its own time-series.
So department revenue changes every month, whereas stock returns vary among the ISINs of course. My model would be something like:
department_revenue ~ stock_return
Please help me out here, is there a fundamental flaw in my approach or do I worry for no reason?