Unpacking National Well-being System: An Exploratory Data Analysis of OECD How’s Life Indicators

Strelkovskii, N. ORCID: https://orcid.org/0000-0001-6862-1768, Rovenskaya, E. ORCID: https://orcid.org/0000-0002-2761-3443, & Zelingher, R. (2024). Unpacking National Well-being System: An Exploratory Data Analysis of OECD How’s Life Indicators. In: 2024 Measuring Progress Annual Workshop, 7 June 2024, Luxenbourg.

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Abstract

Multi-dimensional well-being has recently gained traction as a holistic framework to assess the progress of nations towards increasing the quality of life of their citizens. While numerous countries have begun integrating well-being into their policy frameworks, a gap persists in understanding interconnections among various well-being dimensions as well as in patterns of the well-being in different contexts. Recognizing these patterns is pivotal for harnessing synergies and navigating potential trade-offs, ensuring well-being for all. To address this knowledge gap, our study delves into the National Well-being System (NWS) using the OECD Well-being Framework and OECD How’s Life indicators. We analyze a subset of the OECD indicators for multiple countries, based on the data availability and our aim to balance the economic, social, natural, and human capital dimensions. Starting from a detailed correlation analysis, we further employ time series clustering and panel data analysis. Our findings reveal two distinct country clusters each exhibiting different patterns of well-being. Major socioeconomic events, such as the Great Recession and the COVID-19 pandemic, alter the composition of these clusters reflecting their deteriorating impact on well-being. Our insights underscore the value of comprehensive NW data and a systems thinking approach in developing informed and impactful well-being policies.

Item Type: Conference or Workshop Item (Paper)
Research Programs: Advancing Systems Analysis (ASA)
Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT)
Advancing Systems Analysis (ASA) > Exploratory Modeling of Human-natural Systems (EM)
Depositing User: Luke Kirwan
Date Deposited: 25 Jun 2024 15:27
Last Modified: 27 Jun 2024 13:11
URI: https://pure.iiasa.ac.at/19836

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