Measuring pro-poor growth: a comparative study and a fuzzy logic-based method

Abstract

Purpose

This paper has two purposes. The first is to provide a critical evaluation of current methods of measuring monetary versus non-monetary pro-poor growth. The second is to propose an alternative method based on the fuzzy logic aggregation approach, which allows including both monetary and non-monetary indicators simultaneously for measuring the “global pro-poor growth”.

Design/methodology/approach

The methodology that we propose is based on the fuzzy logic approach to aggregate both monetary and non-monetary indicators simultaneously and thus to calculate the “Global Welfare Index”. This index will be considered as the main global wellbeing indicator based on which a “Global Growth Incidence Curve” is constructed to analyze the pro-poor growth. 10; Also, an application of the main previous procedures for measuring monetary vs non-monetary pro-poor growth is presented to compare their results and to discuss their advantages and limitations.

Findings

Empirical validation using Tunisian data reveals that on one hand, results of the pro-poor growth analysis are very sensitive to the used measurement method and may lead to different conclusions. On the other hand, our alternative procedure may provide a more appropriate analysis of pro-poor growth given that it takes into consideration the multidimensional aspect of poverty while remaining faithful to the fundamental principle of pro-poor growth measurement.

Originality/value

The proposed method for constructing the “Global Growth Incidence Curve” is original given that it presents a new procedure to take into account both monetary and non-monetary indicators simultaneously, which allows having a more global view of the phenomenon. Also, the comparative study of the different proposed methods in the literature of measuring pro-poor growth is useful to identify their limitations and advantages.

Citation

Kacem, R.H. and Kacem, S.B.H. (2021), "Measuring pro-poor growth: a comparative study and a fuzzy logic-based method", African Journal of Economic and Management Studies, Vol. 12 No. 1, pp. 137-150. https://doi.org/10.1108/AJEMS-03-2020-0094