Nonparametric estimation of individual food availability along with bootstrap confidence intervals in household budget surveys

Abstract

An additive nonparametric model is proposed for the analysis of household budget surveys data whose estimation reduces to least squares. Parameter estimates are biased. A first-order approximation for the bias is obtained and it is used to bias correct the residuals of the model in order to construct bootstrap confidence intervals for the model parameter estimates. The results show somewhat shorter intervals than pointwise intervals which are based on a normal approximation with less bias.Nonparametric models Least squares Bias Bootstrap confidence intervals