The Performance of Multivariate Calibration on Ratios, Means and Proportions

Abstract

In this paper, the calibration approach is revisited in order to allow new calibration weights that are subject to the restriction of multiple calibration equations on a vector of ratios, means and proportions. The classical approach is extended in such a way that the calibration equations are not based on a vector of totals, but on a vector of other nonlinear parameters. We stated some properties of the resulting estimators and carry out some empirical simulations in order to asses the performance of this approach. We found that this methodology is suitable for some practical situations like vote intention estimation, estimation of labor force, and retrospective studies. The methodology is applied in the context of the Presidential elections held in Colombia in 2014 for which we estimated the vote intention in the second round using information from an election poll, taking the results from the first round as auxiliary information.

Keywords

• Calibration
• Survey sampling
• Ratio estimation
• Nonlinear estimation
• Monte Carlo simulation