The Output Gap: Method Choice, Data Revisions, and Policy Implications

This paper compares eight widely used methods for estimating the output gap, ranging from simple deterministic trends to state space models, using both revised and real time U.S. quarterly data from 1980 onward. The resulting measures differ heavily across approaches. Average gap estimates vary by nearly four percentage points, volatility differs by an order of magnitude, and correlations across methods span from strongly positive to negative. Stability across data vintages also varies substantially. Hamilton type filters show relatively strong agreement between real time and final estimates, while simpler trend based methods are considerably less stable. These differences matter for empirical inference. The choice of output gap measure has important implications for Phillips curve estimates and for forecasting performance. Beveridge Nelson decompositions display strong predictive power for inflation when estimated using revised data but perform less well in real time, whereas refined Beveridge Nelson and modified Hamilton filters deliver more consistent results across vintages. Time varying analysis shows that the relationship between economic slack and inflation strengthens during periods of macroeconomic stress, including the early 1990s recession, the global financial crisis, and the post-pandemic period, rather than declining monotonically. For output growth forecasting, HP filter gaps reduce forecast errors using revised data, while unobserved components models perform best in real time. Although Beveridge Nelson based measures are informative for inflation, they tend to worsen growth forecasts. Combining forecasts across gap measures, particularly using Bates Granger weights, yields more reliable performance by offsetting weaknesses of individual methods. Overall, the findings highlight that methodological uncertainty in measuring slack translates directly into policy uncertainty, cautioning against exclusive reliance on any single output gap estimate.