Dear Members of Statalist

I am using the difference-in-difference method and here is the context. We had companies that were paying their executives with shares from 2005-2010, from 2011 to 2017 they stopped. So I want to examine how this change or how this stoppage of Share Compensation affect firm performance. In short I want to investigate how the change (from paying shares to not paying shares to executives) affect firm performance. So my variable of interest is ShareCompensation*Post. Post is a dummy of 1 to represent the period after the removal of share compensation. I have 2 options to represent the Share Compensation variable (1) Option 1; it can be a dummy variable of 1 to represent companies that were paying Share Compensation to executives and then stopped from 2011-2017 and 0 for companies that never paid Share Compensation in both periods. (2) Option 2; The second option to represent Share Compensation variable is to measure it as a continuous variable, as the number of shares paid to executives (i.e 500 shares, 260 shares,123,000 shares).or the sensitivity of the shares to performance

Questions
  • When I run separate regressions based on option 1 (using dummy variables) and option 2 (number of shares, which is a continuous variable) I get conflicting or contradictory results. My question is between these two options of measuring ShareCompensation, which one is better and more suited for the difference-in-difference regression in my case. Is it normal for the two options to give contradictory results.
  • If you are running a regression using the two options, would you use the same command, in other words does any one of them require a different treatment.
  • Any references would also be appreciated.
Your assistance will be greatly appreciated