Using nonparametric methods in social surveys: an empirical study

The most common form of data for socio-economic studies comes from survey sampling. Often the designs of such surveys are complex and use stratification as a method for selecting sample units. A parametric regression model is widely employed for the analysis of such survey data. However the use of a parametric model to represent the relationship between the variables can be inappropriate. A natural alternative is to adopt a nonparametric approach. In this article we address the problem of estimating the finite population mean under stratified sampling. A new stratified estimator based on nonparametric regression is proposed for stratification with proportional allocation, optimum allocation and post-stratification. We focus on an educational and labor-related context with natural populations to test the proposed nonparametric method. Simulated populations have also been considered to evaluate the practical performance of the proposed method. Copyright Springer Science+Business Media B.V. 2013