Policymakers need to implement wellbeing policies based on a better understanding of the mechanisms through which subjective wellbeing interacts with many of the variables found in the empirical research that are correlated with it.
“Wellbeing” is increasingly advocated as a more appropriate target for shaping public policy than conventional economic metrics, and has attracted significant policy attention and advocacy. The adoption of wellbeing policies is attractive given the desirability of going ‘beyond GDP’ in order to assess progress. A range of wellbeing metrics based on large-scale surveys is increasingly available, enabling a large and growing body of empirical investigation. But some caution is needed before concluding that specific policies are the right ones to improve wellbeing.
One concern with this push to implement wellbeing public policy (WPP) is that policymakers may start making decisions impacting citizens’ lives based on ‘black box’ relationships. Numerous commentators have noted that the subjective wellbeing (SWB) literature in particular has (deliberately and for defensible reasons) taken an empirical approach largely free of theory to studying relationships of interest. This means that we lack, among other things, an understanding of the mechanisms through which SWB interacts with many of the variables found in empirical research to be correlated with it.
In other words, work on SWB policy lacks knowledge of the pathways that reliably connect cause and effect. Such an understanding is widely thought to be necessary for evidence-based pursuits, be it in medicine, care, or policy. Most of the headline findings in the SWB literature, such as the u-shaped relationship between age and life satisfaction, the Easterlin paradox, and adaptation, could potentially be explained by multiple underlying drivers. So policy that takes no account of this risks pulling the wrong lever, as it were, with unintended consequences.
For example, consider the extension of ‘social prescribing’ to support people’s mental health or wellbeing in the face of their complex needs. This involves linking patients in primary care to sources of support within their community. There is no systematic evidence of the efficacy of such programmes, although there are some long-established, well-regarded local schemes. The advocacy of social prescribing seems to rest on atheoretical assumptions about a consistent positive link between the various kinds of interventions that come under the social prescribing rubric and wellbeing outcomes.
One theoretical explanation for this observed link, from social psychology, is that group membership is in itself a source of wellbeing. Other theories might justify social prescription with different underlying drivers of wellbeing change, such as self-expression through the arts, cortisol reductions from group exercise, reading self-help books, the ‘eco-therapy’ of being in green space, or educational opportunities.
If one of these underlying mechanisms is responsible for wellbeing change then merely prescribing something social will have little effect. What we need here is a theory of SWB that isolates its different potential drivers so that precise hypotheses can be tested regarding why a particular policy has an impact.
These concerns are relevant even for the few causal claims currently made in the SWB policy literature, and for lines of inquiry that take care to address simultaneity or two-way relationships. This is because the kind of empirical relationships captured in the broad WPP literature are vulnerable to structural breaks known in the context of macroeconomics as the Lucas critique, and also identified in the more recent literature on the use of data science in decision making.
Concisely, an estimated relationship between SWB and some policy variable, like education, might depend on the influence of many other variables, such as prevailing macroeconomic conditions, geographic factors like local industries, social factors like community infrastructure and culture, political and policy factors like tax and transfer settings, and individual factors like personality type. A change in any of these structural items may change the estimated relationship between wellbeing and whatever covariate policymakers might target to improve it. A theoretical understanding of wellbeing would help navigate the thicket of possible influences and adjust policy accordingly.
We elaborate these arguments concerning the need for more theory and mechanistic evidence in WPP in a new working paper, available here. We illustrate the way wellbeing data can be used to justify contrasting policies, and argue for due caution in interpreting reduced form empirical results in wellbeing, unless justified by a theory that imposes structure on them. In the absence of theory, there is substantial risk of empirical results pertaining to wellbeing lacking robustness, persistence, or generalizability.
Our argument that SWB theory is not ready for policy complements recent analyses arguing that SWB measurement is not ready for policy, and that more ethical analysis needs to be done to bridge wellbeing science into WPP. There is an important research agenda to develop and test theoretical models of the determinants of wellbeing.
However, we want to stress that our argument is not a counsel of perfection. Structural breaks are an unavoidable feature of most social scientific analysis. Precise mechanistic analysis of social phenomena is also notoriously difficult, and yet we seem to be able to incrementally improve policy effectiveness. Central bankers, for example, seem more in control today than during the great depression, despite the extreme difficulty associated with experimental analysis of macroeconomics. Our intention is simply to explain why caution is required with WPP at this juncture and outline how future research could ameliorate that need to be cautious.
Working paper: Wellbeing public policy needs more theory