The COVID-19 pandemic has shone a spotlight on how governments formulate their policies and has led to a widespread discussion about the social contract and what really matters. Increasingly, people are keen to know what and who is being considered when the government makes policy decisions that affect the lives of its citizens. In addition, there have been a number of calls from social scientists more recently to place wellbeing at the centre of policy analysis.
Traditionally, policies will be considered using cost-benefit analysis. Put simply, this is the process of measuring the benefits of a policy relative to its costs. This includes costs and benefits that are easily measured directly in monetary units, as well as less tangible costs and benefits, such as nature or health, which are then converted into monetary units where possible. Policies with the best benefits to costs ratios are the ones that are chosen to be put into action.
Most policymakers will agree that the objective of public policy is to maximise human welfare across the population. Since this is the case, measuring wellbeing more directly in policy analysis is likely to an improvement as compared with more traditional approaches which essentially look to proxy welfare . The new methods being proposed focus on producing a metric to measure how we can live long, healthy and happy lives. This combines life expectancy with measures of subjective wellbeing to produce wellbeing-adjusted life years (either known as WELLBY’s or WALY’s). In this way cost-benefit analysis can be used in very similar ways to the current approaches, except with wellbeing units playing the central role.
Both the current approach and the new wellbeing approach are not without their challenges. We outline these in detail in the paper but we briefly summarise some of the challenges below:
+ Methodological challenges in policy analysis
- Valuing statistical lives: Since policies affect human lives, it is necessary to try to value each persons life. Depending on the method used, the valuation figure can vary widely.
- Equality: Policies will impact different groups of society unevenly and it is important to capture this in the analysis.
- Sustainability: Policies may impact both current generations and future generations. It is a challenge to consider the extent to which this should be considered in the analysis. For example, a policy could reduce wellbeing today, in order to reap wider wellbeing improvements in future years.
- Isolating impacts: Often, a policy change will impact wellbeing across a number of dimensions that might be inter-related. It is important to isolate the individual impact of each of these dimensions on wellbeing, to avoid double-counting in the analysis.
- Uncertainty: Due to uncertainty about the future, often, assumptions need to be made in the analysis, and forecasts may prove to be inaccurate. These inaccuracies could significantly impact the policy proposal and lead to unintended consequences that weren’t considered in the analysis.
We conclude our article by giving our views on how best to structure policy analysis in order to improve lives. We split this into three categories.
+ A new policy framework for improving lives
The policy strategy
We believe that a dashboard of economic and social indicators should be created, which will require the government to form a policy strategy that is both values and data driven. The data production would be managed by the national statistical office, and governments would be required to create transparent objectives for policy, based on the trends in the data. This would need to be updated periodically, in order to respond to changes.
How to structure policy analysis
We believe that the following filtration process should be used for sorting policies (in order of preference).
First, where the wellbeing effects can be estimated, this should be used above any other approach. This should be considered the gold standard in policy analysis.
Second, where wellbeing effects are difficult to estimate, but we are confident that the monetary approach accurately captures the welfare effects of a policy, then we should use this method instead.
Third, where neither approach is adequate, this should be flagged as a future area of wellbeing research. We support the recent suggestion to create a wellbeing policy agency that will help to generate new evidence to be used in policy analysis.
+ Creating an environment for progress in policy
Outside of the policy analysis we believe there are a few ways that should help to create an environment for progress in policy.
- Effective transparency: Public officials should be transparent about the indicators and method that is used when making policy decisions. Effective transparency matters in a world of increasing information. This means layered information for different audiences and being clear aboutwhere the uncertainties lie.
- Evaluation and feedback: The policy process should produce a discussion paper where experts are able to comment on a policy action before it is put into place. This will reduce the likelihood of unintended consequences and refine the quality of the proposal.
- Diversity: The group of people who produce policy proposals should be as representative of the population they are producing these proposals for as possible. Greater diversity of thought, background and experiences will help to create more sophisticated, balanced and fair policy proposals.
+ Facing methdological challenges
- The question of valuing statistical lives is a difficult one. Current approaches using wellbeing units better match the observed valuation that can be inferred during the pandemic. These methods will need to be refined further however. Importantly, we believe that valuing Life years is a more proportionate and fair approach than valuing lives. This view is supported by the general public.
- We believe that the empirical approach during the policy analysis process should be adjusted for instances where investments today have large impacts on future generations (e.g. climate change). In these cases, the discount rate should be near to zero.
- Regarding distributional concerns, it is our view that these should be included within the empirical framework of the policy analysis where it is possible to do so. In cases where this is not possible, it is important that these remain considered qualitatively within the analysis. For example, in a case where a policy only has a small net social welfare benefit but is likely to negatively effect a marginalised group in society, this qualitative analysis could shift the policy to be rejected.
The slides from the presentation in the video above are available here. Or, to read the full research article, please click on the link below.