I have a panel data in which I observe 1500 companies and many individuals work for those companies for multiple periods. I have explanatory variables at both individual (e.g. race, age, education) and company level (e.g. company age, R&D investment, spending on advertising, industry). So there are different types of explanatory variables i.e. continuous, categorical, binary. In this dataset, same individual might work for more than one company at the same time (given that some of them are consultants). My dependent variable is sales per year.
By using this data, I want to make a prediction of the dependent variable and want to test the importance of each explanatory variable. Does anyone know which models would be more suitable and where I could find a reliable material on this topic? I was thinking about applying RNN to panel data (how to do it ?) but also open to other suggestions.
I know still ML and econometrics are not talking to each other with regard to causality but do you know any recent paper/ development related to this issue?