We the peoples of the United Nations determined … to promote social progress and better standards of life in larger freedom

From Preamble to the United Nations Charter, 1945

8.1 Progress

We humans appear to have somewhat ambivalent attitudes to progress. In a number of aspects of life, winning is all. In others, drawing on a line of Grantland Rice's poetry, it matters not whether you win or lose, but how you play the game. This echoes the ancient Greek idea of good strife and bad strife: good strife, what we might nowadays call good competition, should spur us to reach greater achievements. Bad strife is all the rest. Is there a natural human competitiveness in everything we do, not just when we are playing a game?

Some people talk of ‘moving on’ and ‘putting the past behind us’, in relationships and in life more generally, while others are ‘comfortable in the place they are’. Some political parties and movements are described as ‘progressive’, meaning that they want to change the world, while others are more conservative, reluctant to change or even striving to re-create the values, conditions and mores of an earlier time. Advertisements for financial services invite comparisons between relentless economic growth and growth in the natural world, without appearing to reflect on the cycle of natural growth. Yes, sunflowers can grow tall, for example, but they are also harvested and then die back. In his seminal work on the collapse of complex societies, Joseph Tainter (1988) shows that collapse of civilisations is recurrent. He describes how progress is associated with increasing specialisation, intrinsically nonproductive interfaces between the specialists, increased regulation and costs which increase at a faster rate than the output. In short, a greater proportion of an organisation's effort is spent on simply running it, instead of on its primary aim – with consequences which manifest in the law of diminishing returns, ultimately overwhelming societies. There is an analogy with the Laffer curve, where increasing rates of tax ultimately result in decreasing revenue for the state. ‘Progress’ is not a straightforward notion.

We should also not confuse growth with evolution. Evolution is a process of adaptation and change. We, as humans, have certainly evolved to the extent where we can invent and manufacture products, and make scientific discoveries, some of which make the world a safer place. But there are inevitable concomitant downsides, such as the way in which we can destroy other humans in warfare and use up natural resources more quickly than they can be replaced. Something which may represent progress and be good for one group may be bad for another. Rising house prices are good for property owners, but bad for those hoping to buy their first home. Fast new railways may be good for travellers, but will have damaging wellbeing implications for those living near to the track. Studies of the impact of noise from airport flight paths on psychological wellbeing and on cardiac health are a similar illustration, as are studies of the impact of particulate pollution on those living near roads with heavy traffic.

Progress comes in various flavours, and much of it is driven by technological advances. Sporting records seem regularly to fall, as athletes jump higher, run faster, and throw further, much of which is attributable to advances in training methods, in footwear and in diet. Progress in standard of living is also heavily driven by technological advance. Think of the impact on society of the successive waves of communications technologies: the telegraph, landline telephones and mobile phones. Think of the all-pervasive impact of computers, and imagine managing without the internet for a week. Carr (2010) has gone further, documenting ‘how the internet is changing the way we think, read and remember’.

Cukier and Mayer-Schöenberger (2013) make a similar claim for a new technological front which appears to be opening – that of ‘big data’. A McKinsey report on this subject claimed, ‘we are on the cusp of a tremendous wave of innovation, productivity, and growth, as well as new modes of competition and value capture – all driven by big data as consumers, companies, and economic sectors exploit its potential’ (Manyika et al., 2011). Stephan Shakespeare's review of the use of public sector information in the United Kingdom, in the context of ‘open data’, commented that, ‘from data we will get the cure for cancer as well as better hospitals; schools that adapt to children's needs making them happier and smarter; better policing and safer homes; and of course jobs. Data allows us to adapt and improve public services and businesses and enhance our whole way of life, bringing economic growth, wide-ranging social benefits and improvements in how government works … the new world of data is good for government, good for business, and above all good for citizens’ (Shakespeare, 2013).

On the other hand, a French epigram from the middle of the nineteenth century has become something of a proverb that may describe a familiar feeling. Plus ça change, plus c'est la même chose can be understood as ‘the more things change, the more they stay the same’. This points, perhaps in a slightly world-weary or even cynical way, to change in some sense being an illusion, for we are always living in a world which is as good as it can be at the time.

The early hopes that television would become a wonderful driver of mass education seem to have fallen beneath populist cultures of game shows, reality shows and celebrity culture. Technological advance does not necessarily imply progress. And progress, however defined, does not necessarily increase wellbeing: we are increasingly searching for new models of progress, including what else, in addition to economic growth, ‘can increase the well-being of our societies’ (Anderson et al., 2012, p. 3).

There is also a feeling that technological change appears to be happening at an increasing rate. And when we think of modern computer-related technologies, it is difficult to argue that this is not the case. There may also be synergistic effects, accelerating this increasing rate: search engines permitting instant access to knowledge resources which would previously have required days of search, increased connectivity via social networks, enhanced online access to goods, resources, expertise and so on. These aspects of the gradual shift from material wealth to information wealth cast yet further doubt on the adequacy of GDP as a measure of progress.

Making a considerable simplification, we can see that social change has often been, and continues to be, studied in two broad contexts. First are the sociological studies of what is happening within a country, for example, as a result of increasing industrialisation or as a consequence of economic downturn with rising unemployment and poverty (e.g. Silbereisen and Chen, 2010). The second approach studies the process of international development. One reading of international development is of countries in the North encouraging countries in the South to become self-governing states and full participants in the global market, with the System of National Accounts and especially GNP as ‘a universal quantifiable measure of development’ (McMichael, 2012, p. 4).

Both ways of examining social change involve the development of economies as envisaged by Adam Smith onwards. But we also appear to have reached a place – really more a period of reflection than a precise point – where the key issue is ‘increasingly about how we survive the future rather than how we improve on the past’ (McMichael, 2012, p. 1). Back in 1999, Robert Gordon was examining changing patterns of US productivity and asking ‘why did the fundamental determinants of American economic growth create such a surge between 1913 and 1972, but neither before nor after?’ He predicts this ‘will not be replicated in the lifetimes of our generation or that which follows us’ (Gordon, 1999, p. 127) and continues to hold that view, raising basic questions about the process of economic growth (Gordon, 2012).

As we saw in Chapter 2, there is a long tradition of collecting, publishing and analysing statistics to describe different aspects of a country's economy and society. Data such as that collected in censuses of the population of England and Wales, held every 10 years from 1841 apart from in 1941, continue to be exploited. Barrett (2013), for example, describes how the industries people work in have changed over 170 years, including a marked shift from working on the land in agriculture to working in services in towns and cities. Social theorists and sociologists have also kept a close eye on how societies have been changing, adding their descriptions of what was going on, for example, during depressing times in many countries in the 1920s and 1930s. However, it now seems that the system of national accounts, especially the measurement of gross national product and gross domestic product, was the only real contender as a measure of progress. Anderson (1991, p. 17) notes how political arithmetic evolved into economics, with national income accounting ‘seen by its advocates as primarily a matter of being simply more efficient and systematic about collecting statistical information’.

Anderson concluded that economic progress had emerged as a way of assessing social progress during the eighteenth and nineteenth centuries and that in the first half of the twentieth century ‘for economics as a developing quantitative science, gross national product statistics appeared to offer a much more precise way of talking about economic progress’ (Anderson 1991, p. 45). Stiglitz et al. (2010, p. 61) explain why it has taken so long for other measures to appear: ‘While a long tradition of philosophical thought has addressed the issues of what gives life its quality, recent advances in research have led to measures that are both new and credible … These measures, while not replacing conventional economic indicators, provide an opportunity to enrich policy discussions and to inform people's view of the conditions of the communities where they live’. Stiglitz, Sen and Fitoussi see these measures as applicable to industrialised countries as well as to developing countries and ‘more importantly, the new measures now have the potential to move from research to standard statistical practice’. In particular, we have started to see these measures being taken up by national statistical offices, with support and encouragement from international agencies.

Many economists see the natural state of economies as inevitably growing: Will Hutton (2013) has described economies as having an ‘inbuilt upward momentum driven by productivity and population growth’. While productivity is perhaps a simpler concept than wellbeing, it is not an entirely objective concept, because it assumes that demand is absolute. Population growth can add to demand, for example, for food and housing, but can also be taken account of in a relatively simple way, by producing statistics such as GDP per head, rather than total GDP. Dorling (2013, Figure 2.2) has analysed how the rise in the world's population began to slow down in the early 1970s and has continued to slow down, more or less, since then. (That is, the total population number continues to rise but the rate of annual growth shows a downward trend.) There is a fine line between seeing economic growth as inevitable and seeing it as necessary in order to maintain markets and capitalism. Perhaps it is time to differentiate, if we can, between different types of growth. This seems to be the notion behind the index of sustainable economic welfare and the identification of ‘green growth’. Otherwise, we might be trapped into thinking that economies, as conventionally defined, will always recover from a downturn.

Companies seem to define progress as producing new products and services in response to consumer demand. Quite how this demand is identified before new brands, functionality or features are launched may be less clear, and for the most part the ‘demand’ is realised by the purchase of goods and services as they are advertised, recommended by friends or spotted in stores or online. There is a fine line here between what people want and what they need.

A further complication is the homeostatic effect discussed earlier. We quickly get used to ‘better’ products and services. This happens at the level of the individual: many of those reading this book will have grown up before the age of the internet, but would now find life difficult without it. And think of life before mobile phones! But it also happens at the community level, as the proportion of a population adopting a new technology gradually increases. The eminent physicist Max Planck had an elegant way of putting this community effect in the context of science, saying, ‘a new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it’. Individuals may not progress here, but the group does. Of course, science as a whole progresses by developing new theories which explain more empirical observations or which explain existing data better, but the meaning of that sort of ‘progress’ is relatively straightforward.

A corollary question is whether, once we have got used to new things, we then feel an urge to move on to further new things. Fashion would seem to be a primary example of this – though we have to be aware of the additional commercial driver here: persuading people that they need a new coat every year, even if the old one is barely used, owes little to ‘progress’.

Economists can track changes in the characteristics and qualities of goods and services, using hedonic methods, but it is more difficult to do this for our ‘quality time’. If we were to travel back in time – as some TV documentaries attempt to do, with participants living as our ancestors did – then it looks as if we would consider that wellbeing has improved. We can also make a personal judgement – the English actor Sir Cedric Hardwicke was born in 1893, close to the end of the reign of Queen Victoria. He was reported (Lyons, 1964) to have said that he would liked to have lived in the Victorian Age, but with penicillin. But such retrospective imaginings are fraught with difficulties: few if any technological advances exist in isolation, and most require an infrastructure. Manufacture of penicillin on a commercial scale would necessarily imply other differences. An iPad is built on a very extensive foundation of technical progress. There is also an inevitable whiggish tendency to look backwards and see changes as steps inevitably leading towards the present, rather than as a sequence of events which could have had other outcomes.

Similar caveats apply when we look forward, contemplating future progress – imagining, for example, a time when we have a cure for all cancers or more leisure time (that last being a particular sign of progress which seems to advance at the same rate as we move forward). Again we caution that such changes occur in the context of other changes, and it is not necessarily obvious that things which appear to be progressive will constitute progress when taken along with the concomitant changes of their context. In particular, it is not inevitable that they will increase human happiness and wellbeing.

Governments provide the necessary framework within which society functions – and this includes regulatory restrictions without which, for example, a free-market economy would run amok. But this also implies that they impede or moderate progress. Analogies are speed limits on roads and traffic-calming measures in built-up areas, which slow the progress of vehicles but lead to smoother running at a higher level. A more subtle example has arisen in agriculture. Agricultural intensification, monocultures, housing and tree-planting have had the effect of drastically reducing the amount of species-rich meadows and pastures in parts of Britain. Conservation groups have formed to help landowners re-introduce meadows, including through grants from public funds towards more traditional land management methods.

Progress, then, is multifaceted. But we should not underestimate the extent to which the story continues to be told purely in terms of economic wellbeing, and GDP in particular. Peston notes that the GDP model is played out with different attitudes and values between countries. Germany's ‘shocking and traumatic [20th century] history persuaded the Germans that a stable economy and steadily rising prosperity are the sine qua nons of a healthy democracy’ (Peston, 2012, p. 135). Peston also observes that for most people in Japan (and one might add, presumably for most people everywhere), ‘it's the income they actually enjoy and the quality of the life they lead, rather than the aggregate GDP of the economy, which matters’. Drawing on the Japanese experience, he suggests that ‘at the very least [this] leads us to re-examine our basic presumption that low aggregate GDP growth is necessarily a bad thing. What matters at least as much as the rate of increase in GDP is how that GDP is shared’ (Peston, 2012, p. 139). Observing that China's overriding target is GDP growth, Peston concludes that China has learned that ‘not all contributions to GDP growth are of the same quality’, citing particularly examples of economic activity that may be doing long-term harm to the health of people and to the environment, although he concedes that Chinese people also tell him they can ‘barely believe the astonishing economic progress of their lifetimes’ (Peston, 2012, p. 272).

Despite two waves in which potential alternatives to GDP were proposed, as we saw in Chapters 2 and 3, the progress of a nation (perhaps bar the cases of Bhutan and Colombia) still typically comes down to economic performance, measured through system of national accounts (SNA) and headline measures in particular. But even within the narrow confines of the SNA, opinions differ on what is meant by progress. As we observed in Section 3.4, The Economist magazine recently commented on the ‘paltry’ GDP growth of Canada, referring to an annual increase of 1.6%, since this is below the long-run, post-war average for GDP growth. However, according to figures published by Statistics Canada (Baldwin and Macdonald, 2011), Canada's real GDP per head increased between 1945 and 2010 by a factor of 3.37, equivalent to an annual compound rate of increase of 1.9%. Within this 65-year period, the highest annual increase in real GDP per capita was 6.6% and the lowest annual change was a decrease of 4%. The recent figure quoted by the magazine may be lower than the long-run average, but does it really count as ‘not worth considering’ – which is the dictionary definition of paltry?

Looking at the bigger picture, we should perhaps also ask whether sustainable development is an oxymoron, a contradiction in terms, as Sir David Attenborough once suggested.

To us it seems that national wellbeing, progress and sustainable development go hand-in-hand. While progress might be judged from how wellbeing is changing, for some people the assessment of progress and sustainability is part of understanding current wellbeing.

If wellbeing is to be used as a national indicator, at the level of GDP, it will also be reported in the national news media. People seem to accept GDP (though we suspect that few readers could say how it is constructed), but the acceptance of the concept of wellbeing is often confused with the concept of happiness: formal technical definitions distinguishing between the two are all very well, but lay usage is a different matter (and in any case, some researchers regard wellbeing and happiness as interchangeable – e.g. Easterlin, 2003).

It will doubtless be some time before we reach the tipping point, when national statistical offices worldwide routinely collect, analyse and publish wellbeing data, treating it as one of the portfolio of measures of progress within societies.

8.2 Measuring wellbeing

If we are going to use wellbeing as one indicator of the state of a nation, then we need to have some way of measuring it. The lay response to the very notion that wellbeing might be measurable and indeed be measured is often one of scepticism. It is interesting to note that nowadays there is not a similar scepticism to the notion that pain, depression or anxiety can be measured, although these are in some sense complementary to wellbeing.

This scepticism seems to have two primary aspects. One is the notion of whether it makes sense to speak of a numerical scale for wellbeing. This reservation is a familiar one in the history of measurement. Even physical concepts which we would nowadays regard as clear examples of things which permit numerical measurement scales, such as temperature, often had their early battles, as people gradually refined the concept (see, for example, Chang, 2004). It took a long time, and much deep thought by generations of philosophers and scientists, before heat and temperature were separated, and even longer before energy, thermodynamics and the surrounding theories were developed. Less physical concepts have taken even longer.

The second aspect of scepticism concerns how one can actually construct a measurement scale for the concept of wellbeing. This is intimately tied in with how one defines it. The way wellbeing is measured and its very definition are two sides of the same coin. Furthermore, as we have seen, the concept of wellbeing defies a simple and straightforward unique definition, with different perspectives being suited to different uses – wellbeing is near the pragmatic end of the representational/pragmatic measurement spectrum. And as if all that was not enough, things are complicated yet further by the fact that wellbeing is intrinsically multidimensional. At least temperature has the advantage of being unidimensional!

There is also a third complication: the fact that wellbeing necessarily has subjective aspects. Until relatively recently, it was not appreciated that subjective attributes could be effectively and reliably measured, and this suspicion lingers on among those not versed in modern measurement technology. But even when one accepts that such things can be measured, there remains the question of how to combine the very different aspects of wellbeing to yield a single index. This is why many have favoured an intrinsically multidimensional approach – a dashboard or profile showing the different components of wellbeing.

The subjective aspects of wellbeing describe individuals. Some researchers regard the wellbeing of a nation as necessarily the collective aggregate of the wellbeing of individuals. This perspective certainly has some appeal: it is straightforward and relatively clear. One example was the British social reformer Sir William Beveridge (later Lord Beveridge), who was for nearly 20 years the director of the London School of Economics prior to the Second World War. The school's department of social policy still quotes him on its website homepage as saying, ‘the object of government in peace and in war is not the glory of rulers or of races, but the happiness of the common man’.

National wellbeing, defined by aggregation of individual scores, has the singular merit of permitting its measurement for local areas and/or for population subgroups.

As we have seen, however, even what is meant by the wellbeing of an individual is far from agreed: regardless of the complications of how to go about the aggregation, there are different approaches to defining and measuring individual wellbeing. Different approaches have different merits, and further evaluation and development is needed, along with ways of analysing and presenting them, to be sure that they do the job(s) required of them. The OECD guidelines are helpful in making progress, both in detail and through a more general encouragement that this can be done, but they leave many questions.

Even if we take the restrictive view that national wellbeing is solely an aggregate of individual wellbeing, we have to think carefully about how that aggregation is to be achieved. A sum or average has its place, but one might argue that additional summary statistics are needed to capture other aspects – that, for example, national wellbeing also depends on how individual wellbeing is distributed, with less equal societies appearing to be less happy ones. Alternatively, some argue that individual wellbeing has to be the sole determinant of the wellbeing of the nation, and that if inequality influences individual wellbeing, then inequality is one possible explanation of the level of national wellbeing that we observe, not an additional aspect of it.

More generally still, many argue that we need a fuller picture of national wellbeing, beyond the simple aggregation of individual scores – for example, because some issues (such as natural resource sustainability) may have no impact on individuals currently measured, but do have a larger-scale national wellbeing implication. One of the ‘key messages’ in the Marmot review (on health inequalities in England) in 2010 (p. 15) was that ‘Economic growth is not the most important measure of our country's success. The fair distribution of health, well-being and sustainability are important social goals. Tackling social inequalities in health and tackling climate change must go together’. (Again we come back to the importance of inequality, as described by Wilkinson and Pickett, 2010.) The separation of ‘current’ wellbeing from ‘future’ wellbeing also worries us, even if these are presented as components of an overall framework for national wellbeing. We do not see how we can call it ‘progress’ if our current wellbeing is doing more harm than good for future generations. We were not being glib when we mentioned turkeys and Christmas at the start of this book!

All of this suggests a very large ‘big picture’ embracing individual subjective wellbeing, sustainability, inequalities and economic progress. Although, naturally enough, some have suggested that this might be hoping for too much, nevertheless, it does seem to us that such issues need to be explored if an effective measure of the wellbeing of nations is to be developed. A broadening of the system of national accounts to include social and environmental accounts might be an answer. It would summarise the state of all the capital stocks – ‘wealth’ in its widest sense – available to a nation/society.

An example of recommendations in this direction is the 2012 Royal Society report, People and the Planet, which looked at global population changes and consumption patterns, and identified three pressing challenges: to raise the world's 1.3 billion poorest people out of extreme poverty, to urgently reduce unsustainable consumption in the most developed and the emerging economies and to slow and stabilise global population growth (not by coercive means). The report reviewed measures of progress alternative to GDP, covering objective, subjective and economic measures, and noted that, while there is a growing body of work looking at alternative measures, there is ‘as yet, no consensus on a replacement for GDP, or if there should be one. What is clear is that very few measures of progress actually measure sustainability – a key element of development’ (Royal Society, 2012, p. 90).

When measuring sustainability, the Royal Society saw it as important ‘to measure a society's wealth, which means the value of its entire set of capital assets … Sustainable development means growth in (comprehensive) wealth per capita. Market prices are a misleading guide for valuing goods and services, and they under-value natural capital to such an extent that market signals encourage profligacy in its use’ (Royal Society, 2012, p. 89). The Royal Society recommended that national governments should accelerate the development of comprehensive wealth measures. This should include reforms to the system of national accounts and improvement in natural asset accounting (Royal Society, 2012, p. 105).

The call to adjust GDP to reflect the use of natural capital is not new. Martin called the focus on GDP ‘false accounting … a false view of our current balance sheet’. If natural capital was given some realistic non-zero value, then different business decisions are likely to ensue and be more geared to ‘planetary well-being’ (Martin, 2007, pp. 56–58).

The idea of identifying, restoring and maintaining natural assets is being taken up by increasing numbers of local authorities and amenity groups. Botanical and wildlife surveys help to quantify the state of the natural assets. What is proving more difficult is to value the assets, although we note this does not deter projects with aspirations to add value to local wildlife sites, for example.

Again we stress that we are not ignoring the measurement of individual wellbeing in all of this – but merely that, if a dashboard of measures of the state of a nation is to be used, then (aggregate) individual wellbeing is but one indicator on that dashboard of measures. It is just that we are not convinced that (aggregate) individual wellbeing should be the single or overall measure of national wellbeing.

Overall, the system of national accounts has a rigour which it is important to preserve, and which should be applied across the big picture, not just within the production boundary as defined in the SNA.

It is perhaps also worth asking to what extent is it necessary to resolve the significant conceptual uncertainties surrounding wellbeing, before actually using some such measure. Again we recall the example of temperature – where people found temperature measurement of great value long before the conceptual basis of temperature was properly understood – and the same is true in other areas. (Ancient Egyptians built the pyramids and ancient Britons built Stonehenge long before a formal representational theory of length measurement was developed.) More recently, measures of concepts such as intelligence and depression continue to undergo development and refinement – but this state of flux does not mean existing measures are not of great value. Recall Voltaire's adage that ‘the best is the enemy of the good’.

8.3 New technologies, new data?

We live in a changing world. The very fact that we are contemplating extending and supplementing the standard economic measures of progress illustrates that. But it is not merely the high-level things that change. In particular, low-level data and also strategies for capturing those data are also evolving. In large part, this is driven by progress in electronic and computer technology. Increasingly, data is automatically added to a database, without requiring human effort. For example, medical prescription records, ticket purchases and travel details go into databases, which can subsequently be analysed (or ‘mined’) for valuable information about human behaviour and its condition. There is no practical limit to the size of such databases which can now be stored, since computer memory is so cheap. And neither does their size pose any practical restrictions on analysis (though there are often interesting inferential questions which arise when one has an overabundance of data). We are entering the world of ‘big data’, mentioned in Section 8.1.

The New York Times described big data as ‘the tool du jour for tech-savvy’ companies and city governments who have ‘realized that lurking in the vast pools of unprocessed information in their networks are solutions to some of today's most pressing and convoluted problems’. Going hand-in-hand with big data is open data – access to data by all. In the United Kingdom, one example is the HM Revenue and Customs Datalab, which was launched in 2011 to allow approved academics (so not quite ‘anyone’) to access anonymised tax data in a secure environment for research purposes.

Such things open up interesting new possibilities for measuring wellbeing. The traditional approach of survey sampling is now not the only source of relevant data – it might be supplemented by, or even replaced by, information coming from administrative databases. In 2013, the United Kingdom's Economic and Social Research Council announced the launch of a £64 million initiative in big data, the first phase of which is a £34 million network of four research centres tasked with facilitating research projects using administrative data from government departments. The UK's Beyond 2011 project is exploring ways in which the decennial UK census, next due to take place in 2021, might be replaced by alternative approaches, including using administrative data originally collected for other purposes.

It is clear that such alternative sources could be immensely valuable when measuring any ‘national’ indicator. We have repeatedly mentioned the relevance of health, education and income to the measurement of wellbeing, and the ability to extract data relating to those from existing databases covering the whole of the population can only lead to better measures.

These alternative sources of relevant data hold great promise for enhancing measures of wellbeing – though they do not help resolve the deep conceptual issues about wellbeing and its measurement discussed in this book. However, very little in life is an unqualified benefit, and big data and open data have other potential problems which we should be aware of (see, for example, Hand, 2013). Perhaps the most important of these are uncertainty and data quality issues.

Uncertainty in estimates arising from sampling fluctuation is well understood. Such sources of uncertainty have been studied for over half a century, and highly sophisticated methods for estimating and reducing that uncertainty have been developed in the context of survey samples drawn by formal probabilistic methods. Uncertainty in estimates based on administrative databases is more of an unknown. It will have various aspects, including uncertainty about coverage – because, although in principle such databases might be intended to be complete, they rarely are. Since the sample is not drawn in a random way, any deficiencies in coverage cannot be tackled by traditional statistical means. Essentially such deficiencies are likely to introduce systematic bias rather than variance into the estimates – and bias is more difficult to handle. The question is whether that bias is large enough to matter.

Coverage is one aspect of a broader issue – that of data quality. Errors creep into data in all sorts of ways, many known about (e.g. digit transposition, unfortunate rounding, misplaced decimal points, incorrect units and so on), but sometimes unexpected (such as the time when one of our printers failed to print the most significant digit of a column of numbers we had prepared for a student exercise). William Kruskal wrote that ‘almost all – perhaps all – sizable collections of statistical material have prima facie strange contents’ (Kruskal, 1981). Since wellbeing measures are condensation of large collections of data, we should be aware of the risks.

Administrative data will have been collected for a particular purpose, rather different from our aim of measuring wellbeing. For example, medical prescriptions are written with a view to give the patient the right medicine, not with a view to subsequently use the data as a possible input to a wellbeing measure. This can mean that the definitions are not ideal for our purposes. Is the definition of unemployment, as used for economic measurement, the same as the definition we would ideally like to use if using it as an input to a wellbeing measure?

Furthermore, administrative data definitions can change over time, for reasons completely unlinked to wellbeing. Unless such changes are allowed for, they could induce an apparent step change in wellbeing.

8.4 Beyond the economy

Economic policies are seen collectively as about re-shaping the political economy of the country, and not merely about re-distributing its proceeds. But economics per se is, nevertheless, very one-sided, at least for our purposes. For wellbeing, we need also to consider the environment, and, more generally, other social aspects of the human condition – the sorts of issues discussed throughout this book. One might say that it is time for society to come out of the economic shadow. In any case, new economic theories and case studies are challenging the established idea that economic growth, social progress and the environment are inevitable enemies.

It is true that, to a large extent, the fate of governments depends on the performance of the economy under their stewardship. But, even so, current indicators – GDP, for example – even fail to pick up on aspects of the economy which are relevant to national wellbeing, let alone noneconomic aspects. Economic equality is an obvious example. The need to see wealth widely shared, as well as created, is as likely to be a social priority of a neoclassical economic government as it is of a government of a more progressive or communitarian hue.

The choice of direction to take is a political one, and even in the same political movement there will be many different motives, opinions and approaches to the concept of progress and the wealth of the nation. Even with hindsight, it can be difficult to agree on whether or not wellbeing has been attained and progress made. Neoclassical economic policies in the 1980s may have reversed long-term economic decline and led to a 16-year boom in the United Kingdom between 1992 and 2008, but it is not so clear that wellbeing was advanced. Even economists disagree about whether or not Britain was able to pave its way in the world. And, again more generally, to others the sense of community has evaporated. One might ask if wealth was shared or if materialistic individualism was the driver of national ‘success’ – with anything being justified as long as it made money.

In the context of sustainability, Scott (2012, p. 62) argues that ‘process is as important as product’ in developing local indicators of wellbeing and sustainability. Recognising, as we have done in this book, that ‘wellbeing is a complex human phenomenon and a political construct’, she urges policymakers to generate ‘a democratically derived account of wellbeing through working closely with the public and different interest and community groups’, based on a wide range of evidence (Scott 2012, p. 169). But even process and product are not all that is needed. To be successful, measures must also be widely used.

In Junjie Zhang's analysis of China's economic, social and environmental positions (Zhang, 2012, p. 10), he discusses problems with its claim to be one of the first developing countries to implement a national strategy for sustainable development. Some inadequacies are due to ‘universal shortcomings of the sustainable development concept’. Zhang notes that the final document of the 2012 Rio+20 Conference allows that ‘any action that a country performs to improve social welfare can be counted toward sustainable development. However, the trade-offs among the economic, environmental, and social pillars are often ignored. For example, if poverty eradication through economic growth is accompanied by environmental degradation, is this development pattern sustainable? At the core of the issue is that there is no agreed-upon way to measure the overall state of sustainable development’. We might also ask how the sustainability of huge investment programmes, say to establish more urban centres with associated construction, transport and supporting infrastructure, can be assessed. Economic growth might be generated by such activities, but at what cost to the environment and to society?

The universal numeraire that is used (by economists) as a common currency is money. Lord O'Donnell has commented on this: ‘At the moment we tend to regard the impact of GDP as a success measure. This is rarely a very sensible measure but it is particularly inappropriate for many public sector projects. Take the case of a policy designed to reduce prisoner re-offending. We want to do this because it will raise the wellbeing of individuals who will avoid being victims of crimes, it will raise the prisoner's wellbeing by leading him or her away from a life spent largely in prison and there are all sorts of gains in wellbeing for the families concerned. The reduced strain on the resources of the criminal justice system will raise wellbeing for many groups, not least the taxpayers who will not need to pay for so many prison places. So how should we add up all the gains? At the moment we attempt to translate them all into money and to come up with an overall figure of x% GDP as a saving and then compare this to the cost of the policy. But if we could measure each step in wellbeing units we could end up with the question “is x units of wellbeing worth y units of money?” In the end we have to find a way of answering this question if we are ever to make progress in using wellbeing as a “numeraire”' (O'Donnell, 2013).

A higher-level generalisation from simply monetary value was described by John Maynard Keynes, over 80 years ago. He saw ‘the modern age’ as reaching a time when ‘We shall once more value ends above means and prefer the good to the useful’ (Keynes, 1930/1963, p. 7). He envisaged that time as a hundred years on from when he was writing (i.e. less than 20 years from when we are writing). By then, he said, we would have ‘down-sized’ (to use current jargon) with increased leisure time enhancing the quality of life for all. We have already commented that increased leisure time seems to be as far off as it ever was. Email, instead of leading to more efficient, and hence less extensive, correspondence, seems to have had the opposite effect – who, now, does not have a full email inbox? On the other hand, it is certainly true that the internet and World Wide Web has enhanced individual opportunities. Long gone are the days of shared cultural experience when we all watched the same television shows on the same nights. Likewise, in terms of products, Chris Anderson has argued in his book The Long Tail that modern technology means that mass sales of identical items is being replaced by sales of large numbers of individually customised goods (Anderson, 2006).

However, the bottom line is that wellbeing measures will not have an effect until governments and policy makers embrace them and incorporate them into the administrative and legislative machinery. The levers available to governments and policy makers include statutory regulation (which needs enforcement) and systems of incentives, which have also traditionally been provided through statutory provision. Latterly some governments have also been increasingly interested in ‘nudging’ their citizens and companies to act differently, for example, by requiring opt out from the preferred direction, rather than opting in: make it more costly to take action A than B, and people will prefer the latter.

Change will not happen overnight, nor as the result of a single, or even a succession of well-argued, reports. As architect Richard Rogers believes, and has led by example, ‘To bring about change you need to campaign constantly. Demonstrations, Parliamentary speeches or the way you run your life and business could all be means at our disposal. It is equally important to campaign for the planting of a tree as for a just National Planning Policy’ (Royal Academy of Arts, 2013, p. 2).

How far should governments reflect the preferences of their citizens? Even in a democracy, we tend to rely on the outcome of occasional elections, rather than through referenda or voting on specific issues. On the other hand, statistical opinion polls have long captured what the public reports are its preferences and a handful of national statistical offices have asked the public ‘what matters’ to them in the design of measures of national wellbeing and progress. Modern Web technology has increased the possibilities for a closer link between representatives and those they represent.

Recall the comment made by Joseph Stiglitz, in Vanity Fair in 2011, when he said that most US political representatives ‘are members of the top 1 per cent [of society by personal wealth] when they arrive, are kept in office by money from the top 1 per cent, and know that if they serve the top 1 per cent well they will be rewarded by the top 1 per cent when they leave office’ (Stiglitz, 2011). There is evidence of growing awareness of the opportunities here, with increasing engagement with academia, business and civil society. For example, Professor John Harries, Chief Scientific Adviser for Wales, says ‘Social Sciences are important to many research areas and to policy-making. For example, we are placing increasing focus on behavioural research, in fields such as energy. A related area where we are very active is the better availability and application of data, to address links and causality across economic performance and social, health and environmental well-being. Research on people's attitudes to, and adoption of new energy sources and technologies is one example of social science work that can inform natural science research activity and policy-making’ (Harries, 2012, p. 7). (On the other hand – two steps forward and one back – at the time of writing the UK government is currently without a chief social scientist.)

International organisations, whether working directly with national governments or more independently, are identifying the scale and the breadth of the challenge. According to its website, the OECD's mission, ‘Better Policies for Better Lives’, promotes ‘policies that will improve the economic and social well-being of people around the world’. And to avoid thinking that the environment does not count, the OECD provides a unique forum in which governments work together to share experiences on what drives economic, social and environmental change, seeking solutions to common problems. The World Economic Forum has a similar mission, committed to ‘improving the state of the world’.

Only the fullest understanding of popular sentiment – that is, of society as it is, rather than as we would wish it to be – can provide the firm basis for government. It is for these sorts of reasons that it is so important that official statistics should be produced independently of government: the measuring instrument must not be susceptible to distortion according to the desirability of the results. Even further, official statistics must also be seen to be independent. In a nutshell, they have to be both trustworthy and trusted. This is enshrined in the UN's Fundamental Principles for Official Statistics, and the United Kingdom has achieved it through its Statistics Authority, which reports directly to parliament, and not via the government.

Of course, this does not answer the question of whether such an independent but official body is sufficient for assessing national wellbeing. Many wellbeing measures are being produced outside official statistics – all with slightly different objectives and all defined in slightly different ways, as described earlier in this book. That is, we have a ‘mixed economy’ of public sector, academic, civic society and commercial providers all owning products relevant to measuring national wellbeing.

One consequence is that there is certainly the opportunity for confusion. After all, think how much confusion has been generated in the UK media over the various official price indices, such as RPI, CPI, RPIJ and so on, despite guidance from the Office for National Statistics. The question of how to present, or to bring, the different measures together for the benefit of citizens is a real one.

Sainsbury (2013) has argued for a better ‘knowledge infrastructure’ as one way of reforming capitalism, ‘to achieve economic growth, liberty and social justice’. This infrastructure would facilitate growth by making the market potential of basic scientific and technological research clearer to companies, especially venture capitalists, as well as seeking to improve human capital through education and training more geared to market needs. We suggest that the knowledge infrastructure of future societies also needs to cover the production, analysis and use of better statistics on economic performance, social progress and environmental sustainability. The transparency agenda is a critical part of this. Note that integral to Sainsbury's proposals for progressive capitalism is competent and active government, standing for economic growth and the quality of people's lives (including the environment). The role of such governments should be to define and uphold the public interest, and to do this by supporting and enabling, not directing or controlling, markets and other human endeavours.

These are not easy issues and we should avoid thinking that there is a single ‘right’ answer to many public policy, commercial and personal decisions. The call for more evidence means bringing in more scientific evidence, including on the natural environment, and more social science evidence, covering quality of life as well as economics. Evidence can only inform decision-making. People take decisions not only on the evidence but also within the context of their political, ethical and religious values.

If we set national wellbeing at the heart of things, it will obviously need to be surrounded by the policy areas that governments, businesses, civic society and individuals can affect. Each of these areas will need suitable measures, to complement the overall measure of national wellbeing.

8.5 The future

We have almost reached the end of our book, but the story mostly starts from here. Our first overall conclusion is that it is far too early to draw definitive conclusions. There have been approaches to measuring the topic we call national wellbeing for over 40 years, counting Bache's ‘first wave’ – the social indicators movement – as well as the more recent, ‘second wave’ of the Stiglitz, Sen and Fitoussi commission and wider interest in measuring subjective wellbeing. However, we still feel a long way from a world in which looking at the wellbeing of nations will be more than looking at economic welfare, as measured by GDP, not least because for many nations it is improving economic performance that is paramount.

The second wave is still in play. The High Level Expert Group attached to the OECD that is to continue the work of the Stiglitz et al. commission will have a work programme reaching to 2016. There will also be many international discussions over a similar timescale to put in place successors to the Millennium Development Goals, with the aim of measuring wellbeing and sustainable development in all countries, and in support of the core aim of reducing or eliminating poverty.

It is tempting to say that the second wave is a time of experimentation, of consolidation and of placing measures on a more rigorous footing. Many measures of national wellbeing and progress have already been proposed, and we see early moves towards international standards and the sharing of good practice. But, we have not actually found a lot of real experiments, exploring which measures work best and which capture the most relevant information. There has been some evaluation of different subjective wellbeing scales, some testing of specific subjective wellbeing questions, and policy areas that should benefit from the use of subjective wellbeing measurements have also been proposed. Beyond that, however, we are not aware of efforts to assess how measures of national wellbeing and progress are being used, nor how they could be used. And this last is, after all, the ultimate aim. Without this, the entire exercise is rather pointless.

Going beyond GDP in how we assess wellbeing and progress requires a paradigm shift – for governments, businesses and individuals to switch to thinking about wellbeing and progress in terms of the kinds of areas suggested in Chapter 6, rather than just the financial bottom line, GDP and a monetary return on investment. It is not clear how such a shift will be effected: there is no real precedent. We understand that GDP and the national accounts evolved with the need to monitor and affect the economy. Until we have widespread political willingness to take the broader view, it seems to us unlikely that wider measures will gain much traction.

So our second overall conclusion is that processes to explore measures wider than GDP and, crucially, how these will be used, must continue. These processes should be as inclusive as possible. We see the prospect of a new set of development goals, to follow on from the Millennium Development Goals when they expire in 2015, as a good way to advance the measurement of wellbeing, progress and sustainable development within a coherent framework, involving all nations. It would be good to make as much use as possible of existing statistics, as the basis for new system of economic, social and environmental accounts.

At the start of Chapter 1, we listed some of the questions about the measurement of national wellbeing, so that we can all better understand how a country is doing these days, and how sustainable are its current lifestyles. We have found much work going on around the world to help us answer our questions about the meaning of national wellbeing, the motive for measuring it and how it should be measured. However, we have not found full, clear or widely accepted answers. There is much more to be done, and we do not underestimate the hurdles ahead. They are probably best tackled through incremental steps. Here are a few suggestions to start along the way:

• More joining up of GDP and wellbeing measures from national and regional statistical offices. This is needed not only in countries like the United Kingdom, where the Office for National Statistics now publishes on both fronts, but also in countries like Canada, where Statistics Canada publishes GDP while academics publish the Canadian Index of Wellbeing.
• More companies reporting on a wellbeing bottom line, not just on profits made.
• More probing of value for money. When, for example, a business leader says of a major infrastructure investment, ‘The case for judging this absolutely has to be value for money. At what point does it cease to be value for money?’ then we should ask whether or not this is a judgement solely on the financial cost of the investment and the financial return on that investment. Do things look different if we include the environment and social costs and benefits? ‘Value’ should be interpreted more broadly than the purely financial.
• Widen the System of National Accounts development programme to become a System of National Wellbeing Accounts programme, all under wing of the UN Statistics Division – working, of course, with the plethora of organisations and developers who already have a stake in all of this.

After all, if we do not come up with better measures for how countries are doing, it is difficult to see how we can understand what progress we are making, and what sort of world we are handing over to future generations.

References

1. Anderson C. (2006) The Long Tail: How Endless Choice Is Creating Unlimited Demand. Random House Business Books, London.
2. Anderson P., Cooper C., Layard R., Litchfield P. and Jane-Liopis E. (2012) Well-being and Global Success. Report prepared by the World Economic Forum Global Agenda Council on Health and Well-being for the World Economic Forum Annual Meeting, January 2010. World Economic Forum, Switzerland. http://www.weforum.org/reports/well-being-and-global-success (accessed 20 June 2013).
3. Anderson V. (1991) Alternative Economic Indicators. Routledge, London.
4. Baldwin J. and Macdonald R. (2011) Natural Resources, the Terms of Trade, and Real Income Growth in Canada: 1870 to 2010. Economic Analysis research paper series. No. 079. Statistics Canada catalogue number 11F0027M. Ottawa, Canada. Data in CANSIM Table 383-0027 at http://www5.statcan.gc.ca/cansim/home-accueil?lang=eng&p2=49&MM (accessed 14 August 2013).
5. Barrett R. (2013) 2011 Census Analysis, 170 Years of Industry. UK Office for National Statistics, http://www.ons.gov.uk/ons/rel/census/2011-census-analysis/170-years-of-industry/index.html (accessed 28 October 2013).
6. Carr N. (2010) The Shallows: How the Internet Is Changing the Way We Think, Read and Remember. Atlantic Books, London.
7. Chang H. (2004) Inventing Temperature: Measurement and Scientific Progress. Oxford University Press, Oxford.
8. Cukier K. and Mayer-Schöenberger V. (2013) Big Data: A Revolution That Will Transform How We Live, Work and Think. Houghton Mifflin Harcourt, New York.
9. Dorling D. (2013) Population 10 Billion. Constable, London.
10. Easterlin R.A. (2003) Building a better theory of well-being. Discussion Paper No. 742, Institute for the Study of Labour, Bonn.
11. Gordon R.J. (1999) U.S. economic growth since 1870: one big wave? The American Economic Review, 89(2), 123–128.
12. Gordon R.J. (2012) Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds. NBER Working Paper No. 18315, http://www.nber.org/papers/w18315 (accessed 11 December 2013).
13. Hand D.J. (2013) Data not dogma: big data, open data, and the opportunities ahead. In Advances in Intelligent Data Analysis, XII, 12th International Symposium, LNCS 8207, Springer, Berlin, pp. 1–12.
14. Harries J. (2012) Strengthening Science in Wales, Momentum (Research news from Swansea University), Issue 8, December 2012, pp. 6–7.
15. Hutton W. (2013) Ignore the hype: Britain's ‘recovery’ is a fantasy that hides our weakness. http://www.guardian.co.uk/commentisfree/2013/jul/21/british-economy-still-in-bad-position (accessed 23 July 2013).
16. Keynes J.M. (1930/1963) Economic possibilities for our grandchildren. In: J.M. Keynes (ed.) Essays in Persuasion (1963 ed.). Norton & Co., New York. http://www.econ.yale.edu/smith/econ116a/keynes1.pdf (accessed 27 June 2013).
17. Kruskal W. (1981) Statistics in society: problems unsolved and unformulated. Journal of the American Statistical Association, 76, 505–515.
18. Lyons L. (1964) Cedric Hardwicke Didn't Care That the Sand of Time Ran Out, Lawrence Daily Journal-World. http://news.google.com/newspapers?nid=2199&dat=19640813&id=FocyAAAAIBAJ&sjid=G-YFAAAAIBAJ&pg=3309,3693400 (accessed 24 May 2013).
19. Manyika, J., Chui, M., Brown, B. et al. (2011) Big data: the next frontier for innovation, competition, and productivity, http://www.mckinsey.com/insights/businesstechnology/big data the next frontier for innovation (accessed 30 December 2013).
20. Marmot M. (Chair) (2010) Fair Society, Healthy Lives: Strategic Review of Health Inequalities in England post-2010. The Marmot Review, University College London, London. http://www.ucl.ac.uk/whitehallII/pdf/FairSocietyHealthyLives.pdf (accessed 11 December 2013).
21. Martin J. (2007) The Meaning of the 21st Century: A Vital Blueprint for Ensuring Our Future. Riverhead Books, New York.
22. McMichael P. (2012) Development and Social Change: A Global Perspective (5th ed.) SAGE Publications, Thousand Oaks.
23. O'Donnell G (2013) Inaugural Lecture: Building a Better Government. University College, London.
24. Peston R. (2012) How Do We Fix This Mess? The Economic Price of Having It All, and the Route to Lasting Prosperity. Hodder & Stoughton, London.
25. Royal Academy of Arts (2013) Richard Rogers RA, Inside Out, Gallery Guide, Royal Academy of Arts, London.
26. Royal Society (2012) People and the planet. The Royal Society Science Policy Centre report 01/12, London.
27. Sainsbury D. (2013) Progressive Capitalism: How to Achieve Economic Growth, Liberty and Social Justice. Biteback Publishing, London.
28. Scott K. (2012) Measuring Wellbeing: Towards Sustainability? Routledge, Abingdon.
29. Shakespeare, S. (2013) Shakespeare Review: An independent review of public sector information, https://www.gov.uk/government/publications/shakespeare-review-of-public-sector-information (accessed 11 December 2013).
30. Silbereisen R.K. and Chen X. (2010) Social Change and Human Development: Concept and Results. SAGE Publications, London.
31. Stiglitz J.E. (2011) Of the 1%, by the 1%, for the 1%. Vanity Fair, May 2011, http://www.vanityfair.com/society/features/2011/05/top-one-percent-201105 (accessed 28 May 2014).
32. Stiglitz J.E., Sen S. and Fitoussi J-P. (2010) Mismeasuring Our Lives: Why GDP Doesn't Add Up. The New Press, New York.
33. Tainter J.A. (1988) The Collapse of Complex Societies. Cambridge, Cambridge University Press.
34. Wilkinson R. and Pickett K. (2010) The Spirit Level: Why Equality Is Better for Everyone. Penguin Books, London.
35. Zhang J. (2012) Delivering Environmentally Sustainable Economic Growth: The Case of China. On Asia Society website, http://asiasociety.org/policy/environmentally-sustainable-economic-growth-possible-china (accessed 9 May 2013).