SURVEY REWEIGHTING FOR TAX MICROSIMULATION MODELLING

Tax microsimulation models are based on large-scale cross-sectional survey data. Each individual or household has a sample weight provided by the statistical agency responsible for collecting the data. The typical starting point is to use weights that are inversely related to the probability of selecting the individual in a random sample, with some adjustment for non-response. It has become common for agencies, using “minimal” adjustments, to produce revised weights to ensure that, for example, the estimated population age/gender distributions match population totals obtained from other sources, in particular census data. Such calibration methods appear to be well known among survey statisticians, a highly influential paper being that by Deville and Särndal (1992).²