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Estimating Population Change from Repeated Surveys

9th December 2011 3pm, University of Southampton 58/1007

Yves Berger, University of Southampton

Measuring change over time is a central problem for many users of social, economic and demographic data and is of interest in many areas of economics and social sciences. Smith et al. (2003 JRSS-D) recognised that assessing change is one of the most important challenges in survey statistics. The primary interest of many users is often in changes or trends from one time period to another. A common problem is to compare two cross-sectional estimates for the same study variable taken on two different waves or occasions, and to judge whether the observed change is statistically significant. This involves the estimation of the sampling variance of the estimator of change. Estimation of this variance would be relatively straightforward if cross-sectional estimates were based upon the same sample. Unfortunately, cross-sectional estimates are calculated from not completely overlapping samples of units, because of rotations used in repeated surveys. We show how multivariate regression could be used to estimate the variance of change between cross-sectional estimates.