Evaluation of the Fourth Millennium Development Goal Realisation Using Robust and Nonparametric Tools Offered by Data Depth Concept

TL;DR

This paper presents a robust, nonparametric evaluation of the Fourth Millennium Development Goal's success in reducing child mortality, utilizing advanced data depth techniques for more convincing results than classical methods.

Contribution

It introduces a novel application of data depth-based multivariate tools for evaluating development goal outcomes, enhancing robustness and interpretability.

Findings

More convincing evidence of goal achievement using data depth methods

Robust analysis reduces sensitivity to outliers and assumptions

Demonstrates the effectiveness of nonparametric tools in policy evaluation

Abstract

We briefly communicate results of a nonparametric and robust evaluation of effects of \emph{the Fourth Millennium Development Goal of United Nations}. Main aim of the goal was reducing by two thirds, between 1990--2015, the under five months child mortality. Our novel analysis was conducted by means of very powerful and user friendly tools offered by the \emph{Data Depth Concept} being a collection of multivariate techniques basing on multivariate generalizations of quantiles, ranges and order statistics. Results of our analysis are more convincing than results obtained using classical statistical tools.