In this paper the authors describe the application of spatial choice models to microlevel intermetropolitan migration destination choice data from the US Public Use Microdata Samples (PUMS) for the period 1985 - 90. The metropolitan and the microlevel data facilitate an analysis incorporating well-defined geographic units and their respective attributes, as well as an analysis disaggregated by the personal factors of migrants. The PUMS files provide one of the richest sources of national-level migration microdata in terms of geographic resolution, the number of individual or household characteristics recorded, sample size, and availability. The focus of the modelling exercise is to examine the performance of competing-destinations migration models which are based on the assumption that migrants process spatial information hierarchically. To date the only empirical testing of such models has been undertaken with aggregate spatial flow data, so the PUMS data provide a unique opportunity to examine the behaviour of the competing destinations framework in more detail. The authors provide information on the determinants of intermetropolitan migration within the USA and on the validity of the theoretical foundations of the competing-destinations framework. Traditional spatial choice models are shown to be severely misspecified and the distance-decay parameter estimates from such models to be potentially biased in such a manner that they exhibit the well-known 'spatial structure' effect. This effect does not appear when the parameters are estimated from competing-destinations models.