Abstract
Many social processes may be studied as collections of binary series. The processes which generate such series may be heterogeneous over the population, non‐stationary over time and may exhibit a feedback effect, such as “cumulative inertia.” Methods, using maximum likelihood estimation, are developed which model arbitrary heterogeneity and non‐stationarity to provide an effective test of the presence of “true contagion” or feedback effects. Where absent, a parametric form of the heterogeneity mixing distribution may be empirically identified using moment derived criteria. Application to ten year migration histories for 10,000 residents of Wisconsin, U.S.A., identifies “true contagion” amongst the younger, but not the older, residents for both owners and renters. An Su type distribution is identified as appropriate for modelling the heterogeneity amongst the older renters whereas the older owners are shown to be homogeneous.
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