Q3 2021: The determinants of national wellbeing

In our previous research, we have dedicated much of our time to studying the determinants of wellbeing at the individual level. We used the main findings from this research to build the Exploring Happiness Index, that allows individuals to track their wellbeing over time. We are now turning our attentions to wellbeing on a national level. That is, we are looking to identify what exactly it is that causes citizens in one country to be happier than another.

The best source of data regarding countries wellbeing is the Gallup World Poll and these data are summarised each year in the World Happiness Report. In the survey, Gallup asks people to imagine a ladder, with the lowest rung representing the worst possible life and the highest rung representing the best possible life. The scale of this ladder is from 0- 10. The results show a large amount of variation across countries.

Through data analysis, it is possible to identify a range of factors that explain a significant proportion of the variance in average wellbeing across countries. The World Happiness Report identifies six factors, which when taken together, explain 76 per cent of the variation in average wellbeing across countries. Those six factors are as follows:

• Trust: which can be measured in a number of different but typically by using measures of perceptions of corruption. See full definition.

• Generosity: the proportion of people who have donated money in the present month.

• Social support: the proportion of people who have relatives or friends they can count on to help them whenever they need them.

• Freedom: the proportion of people who are satisfied with their freedom to choose what they want to do with their life.

• Health: years of healthy life expectancy.

• Income: GDP per capita.

The findings from this research tend to be supported by other empirical analyses that consider the main determinants of national wellbeing (e.g. OECD (2012). However, this topic is much less well researched than the topic of wellbeing at the individual level. There remains scope for additional empirical analyses that test whether additional variables or different groups of variables could be more effective at explaining the variation in national wellbeing.

In this research article we also discuss wellbeing inequality. We reiterate that progress should be measured against the goal of both a high average level of wellbeing within a country and a low level of variation around this mean.

We conclude the article by discussing two areas where further research would prove useful. The first is the extent to which cultural factors play an important role in determining national wellbeing. As shown in the chart above, Latin American and Caribbean countries have a high level of wellbeing, given their income level. This may be due to cultural factors but further research is necessary to confirm this hypothesis.

The second is the relationship between environmental quality and wellbeing. The implications of climate change are likely to increasingly impact our daily lives and therefore we could expect this to become an increasingly important factor in determining national wellbeing in the future. This remains speculative for now, but will be an important area of research in the years ahead.

Q1 2021: Policy analysis to improve human lives

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).

1. 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.

2. 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.

3. 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.

Responding to Climate Change

As of March 2019, 195 UN members have signed the Paris Agreement. The long-term goal of this agreement is to keep the increase in global average temperatures to well below 2 degrees Celsius above pre-industrial levels, and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius. 

This paper shows that if we continue with our current policies we can expect temperatures will rise to between 3.1-3.7 degrees Celsius by the year 2100. And even if we put in place all of the national pledges that countries have committed to recently, temperatures are expected to increase to between 2.6-3.2 degrees Celsius - far above the “well below 2 degrees Celsius” target.

There are now currently ongoing discussions between policymakers as to what is the most effective way in which policies should be designed to achieve the goals set out in the Paris Agreement. The two main policies being discussed is a carbon tax or a range of targeted infrastructure government spending projects combined with regulation, such as the ‘Green New Deal’ that is being proposed by Democrats in the US. 

The carbon tax is an efficient way to create a reduction in pollution and force firms and individuals to develop more environmentally friendly alternatives to carbon. It’s not only this; it’s very difficult to foresee what could be the full economic benefits of the tax due to the billions of knock-on effects it will have across the economic system. For example, it may encourage people to use greener modes transport such as cycling or walking which will lead to health benefits that go beyond the reduction in pollution. 

The main criticism of this policy is that firms’ production may simply shift to countries that don’t have carbon taxes. Therefore, until all of the countries in the world adopt the tax, it’s not likely to work. In addition, the cost of adopting such a tax has the potential be quite expensive (depending on how it is designed), reducing its efficiency. Related to this, there are lots of questions surrounding the optimal design for this tax, how do you determine the correct tax rate? Do you tax every carbon emitter in the country or only the largest producers of carbon? How do you prevent tax evasion from carbon production in an efficient way? 

Then for the alternative policy: from an ideological perspective, this policy is based around large government injections into the economy in order to structurally shift towards a green and renewable based economic system. The benefits are clear from developing a policy framework under this goal; the criticism is that current plans in this area have been vague and its highly likely to be a large political challenge to gain widespread support for this due to the lack fo tangible benefits today from implementing these policies.

Before we offer our view in this debate, we’d like to briefly just explain why as an organisation that focuses on happiness economics research we are discussing this topic in the first place. From a happiness economics perspective there is no greater pressing issue than climate change at the moment. Improvements in quality of life, development and wellbeing all fall second in line to risks faced by not acting now to protect the future of the planet.  This is not an overdramatic or pessimistic statement; it’s a realistic one based on the facts – the diagram in Figure 1 in the article below shows this quite clearly.

In terms of a policy response our view is that both a carbon tax and a targeted infrastructure plan should be put in place, in as many countries as is feasible. The carbon tax should be a starting point and should be implemented swiftly – the optimal design of this policy could be debated for decades, it will never be perfect, but its implementation will represent a large step in the right direction. Then in terms of the infrastructure spending plans, this should be done by taking the revenues from the carbon tax (and additional government spending, where possible) to change the structure of high-carbon producing economies to become green and renewable based.

Our view is that the best way that this can be implemented is through a top-down approach with government co-ordination with industries to find intelligent solutions for facilitating these structural changes. For example, governments should put in place overarching targets (similar to the ones in the Paris Agreement) and then show how they plan to reach these targets through sub-targets for reductions in greenhouse gas emissions across a range of important industries in that country. This needs to be a well-defined co-ordinated plan that is publicly accountable, such that should participants fail to meet their targets they will be publicly named and there should be financial disincentives should participants fail to meet targets several times.