Simulating macro / benchmark data
I think yes. Macroeconomists usually build DSGE models to predict short-run fluctuations. Calibrating the data is the part of the process. After using numerical methods to run the models, researchers check the moments of the simulated values. This is a way to examine whether the simulated data represents real life outcomes.

However, every economic situation differs so you have to choose wisely the simulated data depending on your research every time. I mean the growth was huge in the 1950s in the US, but today the main objective is to kill the deflation monster.

Here's the benchmark model by Hansen and Wright (1992):



$\sigma$ denotes standard deviation, $Y,C,I$ and $L$ are macroeconomic variables.