An interview with Carol Graham author of Happiness for All? Unequal Hopes and Lives in Pursuit of the American Dream
Why did you decide to write a book on unhappiness in the U.S.?
This was a first for me, as I have spent much of my career exploring and writing about the causes and potential solutions to poverty and inequality challenges in developing countries. I took a modest change in direction about a decade ago and began to explore the determinants of happiness in countries and cultures around the world. This turn was driven by my findings of deep frustration among upwardly mobile low-income respondents in emerging market economies. What was most notable was the remarkably consistent patterns in the correlates of happiness across countries of all levels of development. I then found that happier people tended to have happier and more productive lives, and wrote one of the early papers on what happiness ’causes.’ Those findings have since been confirmed by several subsequent studies. Meanwhile, despite (or because of?) my grounding in development economics and origins in Peru, I have been increasingly concerned by the very large gaps between the incomes, opportunities, and lives of the rich and poor in the U.S. – a country with a reputation as the land of opportunity. As such, I decided to explore if and how those gaps were mirrored by differences in well-being and ill-being across the same groups in this book.
What is different about this book from the many recent studies of rising inequality of incomes and opportunities in the U.S.?
While many economists, including me, have been discussing and writing about the downsides of increasing inequality in the U.S., interest in the topic was largely confined to academic audiences until very recently. And while the debate surrounding the 2016 elections brought inequality to the public’s attention, public understanding of actual trends in inequality and their implications remains very limited, in large part because of the complexity of the metrics used to measure it, such as Gini coefficients and 90/10 ratios. In the book I try and tell the same story from the perspective of well-being metrics, in the hopes that it might be a better way to explain the implications of inequality for economists and non-economists alike. One of the little known channels that I highlight is a beliefs and behaviors channel via which high levels of inequality – and large differences between those at the top of the distribution and the rest of the population – can act as a disincentive to investments in the future. This is because ‘success,’ as defined by the lives of those at the top, seems (and often is) out of reach for those at the bottom, making them less likely to make the difficult trade-offs to forego current consumption for the ‘promise’ of future outcomes.
What are your key findings for the land of the American Dream?
Most markers of well and ill-being, ranging from life satisfaction to stress, are more unequally shared across the rich and the poor in the U.S. than they are in Latin America, a region long known for high levels of inequality. The most remarkable finding is that the belief that hard work can get you ahead in the future – a classic American dream question – is the most unequally shared metric. The poor in Latin America are almost four times as likely to believe that hard work will get them ahead than are the poor in the U.S. In contrast, the rich in the U.S. are more likely to believe that hard work will get them ahead than the rich in Latin America. Meanwhile, stress, a marker of ill-being, is significantly higher among the poor in the U.S. than the poor in Latin America. The stress which is typically experienced by the poor is related to constant negative shocks which are beyond individuals’ control. This kind of stress makes it hard to plan ahead, much less invest in the future, and is distinct from stress that is associated with goal achievement – which is more common among those with more means and control over their lives. These findings highlight very different incentives – and capabilities – for making investments in the future across the rich and the poor in the U.S.
Were there any other surprises?
The most surprising of the findings were large gaps in optimism across racial cohorts, which did not run in the expected direction. In the fall of 2015 – about the same time as the riots against police violence against blacks in cities such as Ferguson and Baltimore – I found that the most optimistic group among the poor were poor blacks, followed by poor Hispanics. In contrast, poor whites showed signs of deep desperation. At roughly the same time, Anne Case and Angus Deaton published a study highlighting rising U.S. mortality rates driven by preventable deaths among uneducated middle aged whites. Since then, I have matched my desperation data/lack of optimism data with the mortality rate trends – by race and place – and find that the markers correspond quite closely. The most desperate people and places are poor and vulnerable middle class whites in the rust belt, where available jobs are shrinking due to the hollowing out of manufacturing and people are extremely isolated by distance and climate. In contrast, cities, which are more racially diverse, are healthier, more hopeful, and happier. These trends help explain some of the anger and desperation that drove the 2016 election results in the U.S. and also mirror those which influenced the U.K.’s Brexit referendum and an unexpected (and economically costly) decision to leave the European Union.
What are the potential solutions?
There is no magic bullet to the narrowing the gaps between the lives – and well-being – of the rich and the poor in the U.S. And while desperation among poor and downwardly mobile whites is clearly a concern, there are still momentous challenges facing poor – if more optimistic – minorities. In the book I highlight a range of policies – from better vocational training, to more widely available pre-school and quality public education, to improving our safety net so that it does not stigmatize recipients and at the same time leave the non-working poor behind. I also provide examples – from novel experimental data – of interventions which raise aspirations and hope among the poor and disadvantaged, thereby encouraging investments in the future. I conclude by highlighting the important role that well-being metrics can and should play in official statistics, by tracking the health and well-being of our society, as the U.K. is already doing. The metrics can, for example, identify pockets of desperation before mortality rates increase, and highlight community level practices which increase well-being among the vulnerable, among many other things.