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Analytically, we show that the X\u201011 adjustment filter both reduces the magnitude of change at turning points and reduces the depth of recessions, with specific effects depending on the length of the recession. A Monte Carlo analysis using Markov\u2010switching models confirms these properties, with particularly undesirable effects in delaying the recognition of the end of a recession. However, seasonal adjustment can help to clarify the true regime when this is well underway. These results continue to hold when a seasonally non\u2010stationary process with regime\u2010dependent mean is misspecified as one with deterministic seasonal effects. The empirical findings, based on four coincident US business cycle indicators, reinforce the analytical and simulation results by showing that seasonal adjustment leads to the identification of longer and shallower recessions than obtained using unadjusted data. 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