Repeated surveys and the Kalman filter

The time-series nature of repeated surveys is seldom taken into account. The few studies that do so smooth the period-wise estimates without using the cross-sectional information. This leads to inefficient estimation. We present a statistical model of repeated surveys and construct a computationally simple estimator based on the Kalman filter algorithm. The method efficiently uses the whole underlying data set, but only the first and second moments of the data are required for computational purposes.