For a paper I'm investigating the effectiveness of monetary policy (Quantitative Easing) during the Covid-19 crisis. I want to compare the pre-pandemic period with the pandemic period. To do so, I simply split the sample so that I can clearly compare the full period, pre-pandemic and pandemic period. I use a simple OLS regression, and have based the sample split on a paper that does something similar.
However, my supervisor suggested to use an interaction term with dummy that indicates the Covid-19 period, because I have only 16 observations for the Covid-19 period. I used both methods, and the results are actually quite similar: the coefficients, sd's and significance are almost identical and there are only some minor differences.
The question: could anyone tell me which method is best, and why? And, what is a logical reason to split the sample instead of using an interaction term with a dummy.