Assessing Efficiency of Public Poverty Policies in UE-28 with Linguistic Variables and Fuzzy Correlation Measures

Abstract

The present study analyzes the efficiency of social expenditure by EU-28 countries within the period 2014–2018 to reduce poverty. The data are provided by programs European Union Statistics on Income and Living Conditions (EU-SILC) and European System of Integrated Social Protection Statistics (ESSPROS) of Eurostat. We first calculate the Debreu–Farrell (DF) productivity measure similarly to our previous work, published in 2020, for each EU-28 country and rank these poverty policies (PPPs) on the basis of that efficiency index. We also quantify the intensity of the relationship between efficiency and the proportion that each item of social expending suppose within the overall. When evaluating public policies within a given number of years, we have available a longitudinal set of crisp observations (usually annual) for each embedded variable and country. The observed value of variables for any country for the whole period 2014–2018 is quantified as fuzzy numbers (FNs) that are built up by aggregating crisp annual observations on those variables within that period. To rank the efficiency of PPPs, we use the concept of the expected value of an FN. To assess the relation between DF index and the relative effort done in each type of social expense, we interpret Pearson’s correlation as a linguistic variable and also use Pearson’s correlation index between FNs proposed by D.H. Hong in 2006.

Keywords

• fuzzy sets
• fuzzy numbers
• linguistic variables
• fuzzy data analysis
• correlation between fuzzy variables
• poverty policy