Six pigeons were exposed to concurrent variable‐interval schedules in which the programmed reinforcer ratios changed from session to session according to a pseudorandom binary sequence. This procedure corresponded to the stochastic identification paradigm (“white‐noise experiment”) of systems theory and enabled the relation between log response ratios in the current session and log reinforcer ratios in all previous sessions to be determined. Such dynamic relations are called linear transfer functions. Both non‐parametric and parametric representations of these, in the form of “impulse‐response functions,” were determined for each bird. The session‐to‐session response ratios resulting from the session‐to‐session pseudorandom binary variations in reinforcer ratios were well predicted by the impulse‐response functions identified for each pigeon. The impulse‐response functions were well fitted by a second‐order dynamic model involving only two parameters: a time constant and a gain. The mean time constant was 0.67 sessions, implying that the effects of abrupt changes in log reinforcer ratios should be 96% complete within about five sessions. The mean gain was 0.53, which was surprisingly low inasmuch as it should equal the sensitivity to reinforcement ratio observed under steady‐state conditions. The same six pigeons were subjected to a similar experiment 10 months following the first. Despite individual differences in impulse‐response functions between birds within each experiment, the impulse‐response functions determined from the two ex