Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/176992 
Year of Publication: 
2018
Series/Report no.: 
IMFS Working Paper Series No. 121
Publisher: 
Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), Frankfurt a. M.
Abstract: 
The paper illustrates based on an example the importance of consistency between the 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, the authors proposes 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 U.S. 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.
Subjects: 
low frequency trends
demographic trends
hours per capita measurement
output gap estimates
DSGE models
Bayesian estimation
JEL: 
C54
E32
J11
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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