OECD Statistics Working Papers
The OECD Statistics Working Paper Series - managed by the OECD Statistics and Data Directorate – is designed to make available in a timely fashion and to a wider readership selected studies prepared by staff in the Secretariat or by outside consultants working on OECD projects. The papers included are of a technical, methodological or statistical policy nature and relate to statistical work relevant to the organisation. The Working Papers are generally available only in their original language - English or French - with a summary in the other.
Joint Working Papers:
Testing the evidence, how good are public sector responsiveness measures and how to improve them? (with OECD Public Governance Directorate)
Measuring Well-being and Progress in Countries at Different Stages of Development: Towards a More Universal Conceptual Framework (with OECD Development Centre)
Measuring and Assessing Job Quality: The OECD Job Quality Framework (with OECD Directorate for Employment, Labour and Social Affairs)
Forecasting GDP during and after the Great Recession: A contest between small-scale bridge and large-scale dynamic factor models (with OECD Economics Directorate)
Decoupling of wages from productivity: Macro-level facts (with OECD Economics Directorate)
Which policies increase value for money in health care? (with OECD Directorate for Employment, Labour and Social Affairs)
Compiling mineral and energy resource accounts according to the System of Environmental-Economic Accounting (SEEA) 2012 (with OECD Environment Directorate)
- ISSN: 18152031 (online)
- https://doi.org/10.1787/18152031
Measuring Income Inequality and Poverty at the Regional Level in OECD Countries
These estimates confirm that there are significant variations in levels of income inequality within countries, and that regional breakdowns are useful for understanding sources and patterns of income disparities and poverty. For most of the countries relying on survey data for measuring income distribution, standard cross-sectional indicators of income inequality and relative poverty at this regional level are estimated with low precision in the smallest regions due to small samples. This has two main implications for data producers and analysts. First, systematic reporting of confidence intervals is needed to make meaningful comparisons of inequality levels across regions and with respect to the national averages. Second, averaged measures for multiple years or small area estimation methods should be considered as means for obtaining more robust measures. The issues related to the estimation of standard errors for three-year averages in rotational panel surveys and to the definition of the computational sampling structure for sub-national estimates are discussed in the paper.
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