This paper illustrates, based on an example, the importance of consistency between empirical measurement and the concept of variables in estimated macroeconomic models. Since standard New Keynesian models do not account for demographic trends and sectoral shifts, I propose adjusting hours worked per capita used to estimate such models accordingly to enhance the consistency between the data and the model. Without this adjustment, low-frequency shifts in hours lead to unreasonable trends in the output gap, caused by the close link between hours and the output gap in such models. The retirement wave of baby boomers, for example, lowers US aggregate hours per capita, which leads to erroneous permanently negative output gap estimates following the Great Recession. After correcting hours for changes in the age composition, the estimated output gap closes gradually instead following the years after the Great Recession.
