Better understanding the drivers of subjective well-being Introduction

The present section is concerned with analyses examining the drivers of subjective well-being. If identifying vulnerable groups and international benchmarking are core elements of monitoring well-being, better understanding the drivers of subjective well-being can help to explain some of the differences observed over time or between groups - both within and among nations. This analysis might then suggest areas where policy interventions and individual life choices might raise levels of subjective well-being overall.

This section is organised in three parts. It begins with an overview of what better understanding the drivers of well-being means in practice, and the types of drivers typically examined in such analyses - including other high-level well-being outcomes, life events and more specific policy interventions. The use of subjective well-being data to inform the appraisal, design and evaluation of different policy options, as well as to examine policy trade-offs, is also described.

Key methods involved in the analysis of subjective well-being drivers are then covered in the second part of this section. This includes discussion of data requirements and the types of survey design that facilitate causal interpretations, as well as brief consideration of the types of statistical analysis involved in these investigations. Finally, the third part of this section discusses the challenges associated with interpreting analyses of the drivers of subjective well-being. The fundamental questions addressed are what size of impact can be expected? and how can the impacts of different drivers be compared? Key issues considered include interpretation of regression coefficients, the generalisability of results, the risk of error in the measurement of both drivers and outcomes, and the time frames under investigation.