Hello All,

I'm working on a research project which will seek to compare the benefits of an additional year of military service vs. an additional year of education on individuals who have completed active duty military service and are now considered veterans. The question would be posed as "How does an additional year of military service affect later income (once a veteran and civilian) as compared to an additional year of education?" My econometrics class has dictated the use of multiple linear regression OLS as the analysis tool so that's mostly decided. The dataset I've compiled is also cross-sectional. I was hoping for some assistance with my thought on how to go about the model construction and econometric analysis. I'm looking for a ceteris paribus relationship of each, not just a connection. My thought was to construct one multiple linear regression model that substitutes in years of military service for education level, with other control variables entered into the model to attempt to remove as much bias on each as possible. However, in the model I can never hold either of the variables I want to compare (education or years of military service) constant because then I can't compare them. So my plan would be as follows:

Model: wage income = b0 + b1 (years of military service) OR (years of education) + b2 age + b3 sex + b4 race + b5 marriage status + potentially other controls

In the same model, I'd find the b1 for an additional year of military service and its effect on income, then do the same for education on income. I could then perform a comparison between the two as well as discussing results and issues.

My data would come from the US Census bureau 1990 census where I could generate a random sample of individuals and their years of military service (numeric from 0-20), years of education (numeric from 0-20), age (numeric), sex (binary 0 for M, 1 for F), race (I'd construct a set of dummy binary variables to regress onto this), marriage status (single or married 0 or 1), and other data if other valuable controls should be added. Cross-sectional, all data from 1 time period.

I'd plan on filtering the data to only include:
Veterans (nobody should be active duty or have never served)
Ages 25-65 (to allow for full potential educational attainment)
Employed persons only (nobody without a job)
Wage income > 0

Is this the correct approach to answer the question I'm targeting with the specified methods? Suggestions are appreciated if I have incorrect thought processes.

Thanks