This might sound like a silly question to many of you, but I am addressing the comments of a referee regarding a study I'm trying to publish and I remained a little puzzled about this issue.
Let's assume I have set up a simplified model that processes biophysical and socioeconomic data to analyze an issue attaining water management. Biophysical data (mainly topographic, climatic, and hydrological) are available at relatively high resolution (0.25 or 0.5 degree), while socioeconomic data are available at country resolution. The model was set up to run at gridcell resolution (0.25 degree), but, of course, all the cells of the same country share the same values of the socio-economic variables. However the process is run for each individual cell and the results are different from cell to cell, even in the same country.
In my manuscript, I claim that the resolution of my study is a quarter degree. This sentence is contested by a referee that states: "The resolution of the results of a given study is actually defined by the coarsest dataset that the study uses (not the finest). Part of the data used are available only at country level, so the spatial resolution of their results is at that level, not finer."
Now, I understand that coarse biophysical data (precipitation, temperature, land use, ....) should be eventually downscaled to be used in a gridded modeling approach, but what about variables like "corruption" or "quality of the institutions"? Does a downscaling of such variables make any sort of sense? What finally determines the spatial resolution of a study?