We study panel data regression models when the shocks of interest are aggregate and possibly small relative to idiosyncratic noise. This speaks to a large empirical literature that targets impulse responses via panel local projections. We show how to interpret the estimated coefficients when units have heterogeneous responses and how to obtain valid standard errors and confidence intervals. A simple recipe leads to robust inference: including lags as controls and then clustering at the time level. This strategy is valid under general error dynamics and uniformly over the degree of signal-to-noise of macro shocks.