Mind the Gap: Identifying Latent Objective and Subjective Multi-Dimensional Indices of Well-Being

Abstract

Within the OECD Better Life Initiative, the Better Life Index (BLI) represents a major attempt to measure well-being and societal progress beyond GDP, following up the recommendations outlined in the Stiglitz-Sen-Fitoussi Commission report. Using a Structural Equation Modeling (SEM) approach, we estimate BLI as a latent construct starting from eleven underlying dimensions of well-being. This method, based on variance-covariance matrices, allow us to study the interrelations and causal-relationships across well-being determinants and across the underlying drivers of well-being. In our analysis we utilize two different comparable OECD datasets for the year 2012, one based on average country-level data reflecting well-being outcomes, the other one on microdata reflecting people's stated preferences on well-being indicators. In order to deal with the idiosyncratic structures of the datasets, we apply two Structural Equation Modeling techniques - bootstrapped SEM and Generalised SEM MIMIC - to estimate the relative weights and rankings of BLI dimensions. We then build an 'objective' BLI measure predicted from the national-level data, whereas a 'subjective' BLI is obtained using the new OECD microdata. Finally, we conclude our analysis comparing the objective and subjective BLI dimensions weights and country rankings and discussing the main policy implications.