Comparing Small Area Techniques for Estimating Poverty Measures: the Case Study of Austria and Spain

Abstract

The Europe 2020 Strategy has formulated key policy objectives or so-called “headline targets” which the European Union as a whole and Member States are individually committed to achieving by 2020. One of the five headline targets is directly related to the key quality aspects of life, namely social inclusion; within these targets, the European Union Statistics on Income and Living Condition (EU-SILC) headline indicators atrisk-of-poverty or social exclusion and its components will be included in the budgeting of structural funds, one of the main instruments through which policy targets are attained. For this purpose, Directorate-General Regional Policy of the European Commission is aiming to use sub-national/regional level data (NUTS 2). Starting from this, the focus of the present paper is on the “regional dimension” of well-being. We propose to adopt a methodology based on the Empirical Best Linear Unbiased Predictor (EBLUP) with an extension to the spatial dimension (SEBLUP); moreover, we compare this small area technique with the cumulation method. The application is conducted on the basis of EU-SILC data from Austria and Spain. Results report that, in general, estimates computed with the cumulation method show standard errors which are smaller than those computed with EBLUP or SEBLUP. The gain of pooling SILC data over three years is, therefore, relevant, and may allow researchers to prefer this method.

Keywords

• small area estimation
• poverty
• EU “headline targets”
• regional level
• NUTS-2
• inequality
• SEBLUP
• cumulation
• SILC
• Austria
• Spain