Happiness Trends

Interdisciplinary research can take you to some unexpected places. You may have heard about a paper that Betsey Stevenson and I wrote a while back, documenting that the average level of happiness among women has trended downward relative to that of men. It’s an interesting fact, and we aren’t quite sure whether it tells us about the reliability of happiness data, the women’s movement, or other changes in men’s and women’s lives.

It is also a fact that seems to capture the public’s imagination — perhaps more than anything else I’ve worked on. The recent publication of the paper led to another round of discussion. First it was Maureen Dowd, then Newsweek, NPR, and now it turns out that self-help guru Marcus Buckingham has used this research as the basis for a book telling women how to live their strongest lives. (Don’t ask me; I really don’t know!)

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I certainly never expected a career in economics to lead me to share a green room with singer Harry Connick Jr. or actor Derek Luke, or even to meet a motivational speaker. And while that was it from me, Betsey had an even busier week, as CNN devoted an hour to discussing the paper.

And despite all the discussion, I’ve got to admit, we are still quite puzzled about just what lies behind “The Paradox of Declining Female Happiness.” But if you have an idea, we’ve posted all of our data, and you can test hypotheses to your heart’s content.

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Is Ignorance Bliss?

A regular blog reader, Mitch Kosowski, sent along an interesting question: “Is ignorance truly bliss? Are people with lower intelligence happier than those with higher intelligence?”

Let’s start with a quick literature review. Here are the findings reported by Simpson, L. (2001):

Lisa Simpson: “As intelligence goes up, happiness goes down. See, I made a graph. I make lots of graphs.” [The Simpsons, episode 257]

Despite her formidable unhappiness, I don’t think Lisa is right on this one. My reasoning is simple: more intelligent people tend to earn higher incomes, and we know that people with higher incomes are more likely to be happy.

But that’s theory; let’s crunch some numbers.

The General Social Survey asks about happiness and also contains a simple vocabulary test, which we’ll use as a proxy for intelligence. While this is a pretty rough proxy, I’ll rely on the Rumsfeld defense, analyzing the data we’ve got, rather than the data we want. I simply divided people into the top, middle, and bottom thirds of the population, in terms of their vocabulary scores:

There’s also a small reasoning-based test:

Armed with these data, Lisa can make more graphs, and she’ll discover that those with stronger vocabularies or stronger analytic reasoning skills are more likely to be very happy, and less likely to be unhappy.

These differences were also statistically significant. By contrast, much of the existing literature finds no statistically significant relationship between individual happiness and intelligence. But the failure of small-scale studies to find statistically significant results likely reflects the fact that small-scale studies can’t verify much. (My analysis includes over 14,000 people; existing studies range from analyzing a couple of dozen to a couple of thousand people.)

Even so, these happiness differences look small. But I don’t immediately conclude that the happiness-intelligence link is weak; instead, these weak(ish) results may reflect a weak link between actual and measured intelligence. The coarseness of my intelligence measures means that there are likely some very intelligent and very happy people mis-categorized as moderately intelligent and very happy. If we could sort these people out, I think it’s pretty likely that we would find that there is an even stronger relationship between intelligence and happiness. (Hint for econ students: there’s an interesting paper waiting to be written on this.)

But this doesn’t answer the harder question: What creates a relationship between (measured) intelligence and (measured) happiness? Are those who are lucky enough to be born intelligent also lucky enough to be born happier? Do happy folks elicit greater attention from their teachers? Or does the sort of intelligence that is created by education also enable us to successfully pursue happiness? If it’s the latter, then perhaps these data point to yet another reason to invest in education.

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An Unhappy Year

In a New York Times Op-Ed on Saturday, Sonja Lyubomirsky wrote that subjective well-being has remained high during the recession. But she’s dead wrong.

Here’s the gist of her piece, titled “Why We’re Still Happy” :

Research in psychology and economics suggests that when only your salary is cut, or when only you make a foolish investment, or when only you lose your job, you become considerably less satisfied with your life. But when everyone from autoworkers to Wall Street financiers becomes worse off, your life satisfaction remains pretty much the same …

So in a world in which just about all of us have seen our retirement savings and home values plummet, it’s no wonder that we all feel surprisingly O.K.

Unfortunately the claim she’s making — that we’re all O.K., thank you very much — isn’t one for theory, it is a factual claim. Let’s see how it checks out, updating my earlier analysis of daily data on life satisfaction through 2008, courtesy of the Gallup-Healthways Well-Being Index (and see that earlier post for the details on this chart):

We’re still happy? No way. Life satisfaction has plummeted during the recession. Of course there remain important issues about how best to measure well-being. So here’s my challenge to Lyubomirsky: Find a single indicator of subjective well-being that hasn’t gotten worse through 2008. I’ll be happy to write about it, if she finds one.

Not only has happiness declined during this recession, it has declined through every U.S. recession for which we have data. Here’s a chart from a paper of mine (with Betsey Stevenson), documenting the clear correlation between the U.S. business and happiness cycles:

I’m optimistic that research into subjective well-being can be useful. But careful science is about replacing conjecture with facts, and right now, happiness research could use a bit more empirical rigor.

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Delving into Subjective Well Being

What good is G.D.P., anyway? While my postings this week have shown that it is correlated with happiness, I have not spent much time asking just precisely what it is about our subjective experiences that is correlated with higher G.D.P.

In fact, the analysis in my previous posts, focused almost exclusively on simple responses to surveys asking people how happy they are, how satisfied they are with their lives, or where they think they are on a satisfaction ladder.

But we can do a lot better.

The Gallup World Poll asks an amazing battery of questions about the subjectively-experienced lives of people across the globe, and hence offers an unparalleled opportunity to contrast the subjectively-experienced lives of those in rich and poor countries.

This chart is my personal favorite, showing the proportion of people in each country who report having smiled or laughed a lot the previous day. Higher levels of economic development are clearly associated with more smiles and laughter. But equally, there are a lot of exceptions to this rule, and plenty of puzzles.

Laotians are more likely to smile than anyone else, and the Irish appear to have earned their national reputation as jolly japesters. My own country, Australia, comes in as the 29th of the 131 countries in the Smile Stakes, while the U.S. is a disappointing 45th.

This survey also asks about a range of feelings that might have been experienced the previous day. It is clear that G.D.P. is correlated with more people reporting enjoyment, while those in richer countries are less likely to report experiencing physical pain, depression, boredom, and anger.

Interestingly, G.D.P. appears uncorrelated with feelings of worry.

And as I mentioned last Valentine’s Day, love is very democratic; it is as likely to be experienced in rich as poor countries.

It is also interesting to note some of the experiences that were reported in rich and poor countries.

Perhaps it is unsurprising that those in rich countries are more likely to report having eaten tasty food. But I was also interested to learn that people in rich countries are more likely to report having been treated with respect, or having autonomy about how to choose their time. Equally, many of these reports — including things like feeling well-rested, or having pride in one’s recent achievements — are surprisingly unrelated to economic development.

My recent research paper with Betsey Stevenson only scratches the surface of what we can learn from these data. But I am confident that over the next few years, the social science community is going to learn a lot more about the relationship between our current objective (and primarily economic) measures of living conditions, and the subjectively-experienced lives of people all around the world.

Let the interdisciplinary research teams loose: there’s a lot here for economists, psychologists, sociologists, anthropologists, and political scientists to better understand.

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Raise the Incomes of All?

In a famous 1995 paper, Richard Easterlin asked: “Will raising the incomes of all increase the happiness of all?” His analysis involved studying the evolution of happiness through time in Japan, the U.S. and Europe. His answer? “No.”

Betsey Stevenson and I recently returned to examining the evolution of happiness in these three important regions, and we conclude that the evidence is not so clear cut.

First, Europe. The Eurobarometer Survey allows us to track average levels of life satisfaction since 1973, in the same nine nations that Easterlin analyzed. The relationship between happiness and G.D.P. in these countries is shown below:

A few observations:

1) In eight of these nine nations, satisfaction grew as G.D.P. grew, and in six of these cases, the relationship is statistically significant.

2) But there are some pretty interesting exceptions. For instance, why has happiness fallen in Belgium, even as G.D.P. has grown? And why did happiness take so long to grow in Ireland, even as the “Irish miracle” led to tremendous economic growth?

3) While the pattern varies across countries, in most cases, the time series data suggest a satisfaction-G.D.P. gradient of about 0.2, with some larger, and some smaller.

4) This pattern of satisfaction growing with G.D.P. is less clearly evident if one analyzes only the early data (solid dots). This partly explains how we are able to make stronger inferences than earlier researchers.

5) In subsequent years, this survey (and indeed, Europe) has expanded to include more countries. We have analyzed this broader sample of countries, finding roughly similar conclusions.

Now, let’s turn to Japan, which is arguably the most interesting case study, because it went from a quite poor country after the war, to become one of the world’s economic powerhouses by the late 1980’s. Moreover, Japan is unusual because the government has collected life satisfaction data since 1958. Previous researchers had interpreted those data as suggesting that this incredible economic growth had yielded no gains in happiness.

Puzzled by this finding, we had the Japanese survey questions re-translated. It turns out that there was not one continuous question yielding a flat trend in well-being, but instead four separate questions asked in four separate periods. And during each of the first three periods — when economic growth was rapid — it was matched by commensurate growth in life satisfaction. The fourth question began in 1992 and satisfaction declined as per capita economic growth was anemic (0.9 percent) and unemployment became a problem.

Looked at this way, the dramatic growth in Japanese G.D.P. from 1958 to 1991 was matched by rapid growth in life satisfaction. The decline in satisfaction since 1992 is both worrying, and worth much more study.

Finally, we turn to the United States. Happiness data from the General Social Survey show virtually no trend since 1972, despite G.D.P. having doubled over this period. We find this puzzling, and we really don’t have an airtight understanding of what is happening in the U.S. Equally the “happiness shortfall” isn’t that large — by 2006 perhaps another 8 percent of the population should be “very happy”, and the proportions “not too happy” or “fairly happy” should each be about 4 percent lower.

One possibility is that inequality may play a role.

Yesterday I showed that happiness seems to be related to the log of a person’s income level. If this is right, then average levels of happiness would rise with average log income, whereas our usual income numbers (shown in the second panel, below) focus on the log of average income.

Instead, the bottom panel shows rather anemic growth in average log income. Thus, given that the income gains over the past few decades went mostly to those who are well off, and given that these folks get somewhat less happiness per extra dollar, then perhaps it seems reasonable not to expect much of a rise in happiness. And indeed, average happiness for those at the top of the income distribution has grown through this period.

Our research paper contains a lot more about comparisons of happiness and income through time. The broader datasets follow the contours of the discussion above: the experience of some countries points strongly to a happiness-income link, there are definitely cases that point against it, and others leave you scratching your head.

All told, there are probably more time series suggesting that growing G.D.P. is related to growing happiness than there are suggesting the opposite. Thus we conclude that the time series evidence is both weakly supportive of a happiness-income link, and also fragile.

And even if these data don’t convince you that there is a strong connection between G.D.P. and happiness, they also shouldn’t convince you that they are unrelated.

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Are the Rich happier than the Poor?

Continuing on the theme of the relationship between income and happiness (previous posts: 1, 2 , and 3), let me show you what Betsey Stevenson and I learned when comparing the happiness of rich and poor people.

Let’s begin with the most recent data from the 2006 General Social Survey, which asked: “Taken all together, how would you say things are these days?”

It sure seems like the rich are more likely to be “very happy” than the rest of us. Is this a big effect? In 2005, Robert Frank argued:

When we plot average happiness versus income for clusters of people in a given country at a given time, we see that rich people are in fact much happier than poor people.

It’s actually an astonishingly large difference. There’s no one single change you can imagine that would make your life improve on the happiness scale as much as to move from the bottom 5 percent on the income scale to the top 5 percent.

Let’s go ahead and draw the plot that Frank envisions, using all of the data from the 2006 survey:

Here’s the key point:

By comparing rich and poor people, we estimate a happiness-income gradient that has a slope that is similar to what we saw when we compared rich and poor countries.

OK, that’s the United States, what about other countries? We estimated the well-being-income gradient for over 100 countries in the Gallup World Poll. Rather than show you dozens of separate coefficients, we’ll let a picture tell the story (and let me admit, I love this graph).

The arrows in this figure show the slope of the well-being-income gradient for each country, while the dots show the average level of happiness and G.D.P. for each country. The dashed line shows the best fit through these dots.

The fact that the arrows all have a similar slope to the dashed line suggests that comparisons of rich and poor people yield very similar conclusions to comparisons of rich and poor countries. In the full paper, we document that this finding holds for many different datasets.

Why do we emphasize this finding?

Because it stands directly at odds with a key claim of Easterlin (see p.106 to 107):

… the happiness difference between rich and poor countries that one might expect on the basis of the within-country differences by economic status are not borne out by the international data.

Economics of Happiness - the evidence

Yesterday I noted that there is powerful evidence from the recent Gallup World Poll that rich countries are happier than poor countries. Today, I want to show you how this fact remained hidden in the data for several decades. (And I don’t mean to suggest that we are the first to discover this, but rather that those who noted this were somewhat outside the mainstream.)

In our recent paper, Betsey Stevenson and I went back and re-analyzed all of the early international surveys of happiness, and we now have data from 1946 to 2006.

The figure below shows the results from five early international comparisons of happiness and G.D.P.

The G.D.P. data on the x-axis are self-explanatory. The happiness data on the y-axis are also easy to understand — although the units we use for analyzing them may be less so.

The difficulty we face is that some surveys ask about well-being on a 0 to 10 scale, some ask if you are “very happy, fairly happy, or not very happy”, and others ask about happiness on a 4, 5, and sometimes even 7-point scale.

These differences make it difficult to make comparisons across surveys. We estimate average happiness scores by country by running an ordered probit regression of happiness on country fixed effects, and this is what you see plotted above.

Yes, there is too much jargon in that sentence, so let me try to give an intuitive explanation:

Essentially, this technique assigns each person a happiness “z-score,” by taking their response, dividing it by the standard deviation, and subtracting the mean. We also need to sort out the extent to which “very happy” differs from “fairly happy” or “not very happy,” and the ordered probit does this by analyzing the proportion of the population giving each response.

If, say, only a tiny fraction of people ever respond that they are “not very happy”, then we could infer that this is a pretty bad state to be in. All told, the coefficients can be interpreted as average levels of happiness, measured in units that correspond to the pooled within-country standard deviation of happiness.

If this seems overly complex, the main point is that we try to make these estimates comparable.

To the eye, this figure seems not to show much of a relationship between income and happiness, and early observers simply noted that most of the data was inside the shaded band. But looking more closely, in three of the five cases we get statistically significant effects, and in no case can we reject the hypothesis that the happiness-G.D.P. gradient is 0.3. This is pretty important, as we shall see below.

Next we show the data from succeeding waves of the World Values Survey, which began in the early 1980’s.

While there is still some doubt about the link between well-being and G.D.P., in the early 1980’s (as more data accumulated) it became increasingly clear that there is a close link between the two. Indeed, by the latest wave of the survey, we see a wellbeing-income gradient of 0.35, and a correlation of 0.7.

Here are some more supportive data from the 2002 Pew Global Attitudes Survey, covering 44 countries:

Finally, we get to the 2006 Gallup World Poll:

Yes, this is the same graph I showed yesterday, but this time I’ve put the y-axis in comparable units to the other surveys. And the wellbeing-income gradient is about 0.4.

The key point is that across all of these surveys, the estimated wellbeing-income gradient is around 0.2 to 0.4. Moreover, this holds across each of the many datasets that have accumulated over the past sixty years. In the early years, this relationship was not always statistically significant, but this did not mean that there was no such relationship.

Three more observations about what we can learn from this history:

1) The income-well-being relationship has appeared just about as strongly in surveys probing happiness as in surveys asking about life satisfaction. (There are exceptions.)

2) One interpretation of the 2006 Gallup data is that it is still all about relative income comparisons: In today’s global village, folks in Jamaica may be comparing their lot in life to the greater prosperity they observe when watching U.S. television shows. Countering this, it looks, to my eye, as though the income-happiness link appears about as strong in countries that are truly plugged in to the global village, as those that are less engaged.

3) Moreover, the relationship between income and happiness is about as strong today as it was in the very first surveys, which were taken sixty years ago, when the world was less integrated.

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Are rich countries happier than poor countries?

Following yesterday’s post, I promised to describe the new evidence that rich countries are happier than poor countries.

The simplest way to make this point is with a chart, using data from the Gallup World Poll. This amazing new dataset contains detailed data on subjective well-being for 132 countries in 2006. (Amazingly, Gallup plans to continue to field this poll every year.)

The key question asks:

“Please imagine a ladder/mountain with steps numbered from 0 at the bottom to 10 at the top. Suppose we say that the top of the ladder/mountain represents the best possible life for you and the bottom of the ladder/mountain represents the worst possible life for you. If the top step is 10 and the bottom step is 0, on which step of the ladder/mountain do you feel you personally stand at the present time?”

The following chart simply takes the average levels of satisfaction on this 0-10 scale, and plots it against G.D.P. per capita (note the log scale):

There is an incredibly high correlation between average levels of happiness and average incomes — greater than 0.8. Angus Deaton actually beat us to this finding, and his analysis of these data is worth a close reading, (here).

There’s another striking finding in this graph: the relationship between happiness and log income appears nearly linear.

Thus, a 10 percent rise in income in the United States appears to increase happiness by about as much as a 10 perecent rise in income in Burundi.

Let me add two further comments here:

1. This is an interesting finding, because many had argued that there is a “satiation point” beyond which you just don’t benefit from greater income. Indeed, Richard Layard has argued that “there is no evidence that richer countries are happier than poorer ones — so long as we confine ourselves to countries with incomes over $15,000 per head.”

In fact, the slope appears to get steeper above $15,000!

2. Even so, it is worth noting that a 10 percent rise in income in Burundi requires one-sixtieth as much income as a 10 percent rise in income in the U.S. Thus, even if the slope is three times as steep for rich countries as poor countries (as we estimate), this still means than an extra $100 has about a twenty-times-greater effect on happiness in Burundi than it would in the United States.

Comparisons like this make you think that foreign aid may not be such a bad idea.

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The Easterlin Paradox

Arguably the most important finding from the emerging economics of happiness has been the Easterlin Paradox.

What is this paradox? It is the juxtaposition of three observations:

1) Within a society, rich people tend to be much happier than poor people.
2) But, rich societies tend not to be happier than poor societies (or not by much).
3) As countries get richer, they do not get happier.

Easterlin offered an appealing resolution to his paradox, arguing that only relative income matters to happiness. Other explanations suggest a “hedonic treadmill,” in which we must keep consuming more just to stay at the same level of happiness.

Either way, the policy implications of the Paradox are huge, as they suggest that economic growth may not raise well-being by much.

Given the stakes in this debate, Betsey Stevenson and I thought it worth reassessing the evidence.

We have re-analyzed all of the relevant post-war data, and also analyzed the particularly interesting new data from the Gallup World Poll.

Last Thursday we presented our research at the latest Brookings Panel on Economic Activity, and we have arrived at a rather surprising conclusion:

There is no Easterlin Paradox.

The facts about income and happiness turn out to be much simpler than first realized:

1) Rich people are happier than poor people.
2) Richer countries are happier than poorer countries.
3) As countries get richer, they tend to get happier.

Moreover, each of these facts seems to suggest a roughly similar relationship between income and happiness.

What explains these new findings? The key turns out to be an accumulation of data over recent decades. Thirty years ago it was difficult to make convincing international comparisons because there were few datasets comparing rich and poor countries. Instead, researchers were forced to make comparisons based on a handful of moderately-rich and very-rich countries. These data just didn’t lend themselves to strong conclusions.

Moreover, repeated happiness surveys around the world have allowed us to observe the evolution of G.D.P. and happiness through time — both over a longer period, and for more countries. On balance, G.D.P. and happiness have tended to move together.

There is a second issue here that has led to mistaken inferences: a tendency to confuse absence of evidence for a proposition as evidence of its absence. Thus, when early researchers could not isolate a statistically reliable association between G.D.P. and happiness, they inferred that this meant the two were unrelated, and a paradox was born.

Our complete analysis is available here. An excellent summary is available in today’s New York Times, here, with a very cool graphic, and readers’ comments. Other commentary is available in the F.T. (here and here), and Time Magazine.

Given the broad interest in this topic, I thought that I would spend the next couple of days blogging about our new findings on the links between income and happiness. Tomorrow, I’ll describe comparisons of rich countries and poor countries. I’ll follow that up with separate posts describing comparisons of rich and poor people, and then assessing how happiness changes as countries get richer or poorer.

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Economics of Happiness

Is our government making us happier?

• How many Americans are taking antidepressants or using alcohol or other forms of addictions as a way to cope with the pressures of the current socioeconomic system? Is the number declining or on the rise?

• How many people do you know whose lifestyle is causing severe pressures on their psychological, emotional and relationship health?

• How many people do you know suffer from chronic workplace stress, anxiety, low self-esteem, or some form of depression?

• Are the rates of divorce, crime and lawsuits declining or on the rise?

A) Government

The role of government should shift from managing economic growth to socioeconomic development. American public policy should shift its focus from:

• The standard of living to the quality of life
• Material possessions to well-being (physical, mental, and material)
• Unsustainable economic development to sustainable environmental development
• Consumerism to investment
• Economic-driven education to socioeconomic-driven education

Government can also make substantial improvements by implementing the following recommendations:

• Simplify people’s lives through reformed civil laws and taxes.
• Establish new tax and budget policies in line with public mental, emotional and physical wellness goals. For example, provide funding for the promotion of positive psychology and cultural education in schools, workplaces and public media.
• Shift policy priority from waging wars - a major source of socioeconomic stress and long-term liability - to local socioeconomic development and foreign collaboration.

It is important to note that the success or failure of any new initiative is dependent on the sponsorship of the power centers within the socioeconomic system. The public must drive Congress to provide additional reforms to ensure honest representation by elected officials and by instituting controls on the abuse of power such as the promotion of private interests on the expense of public good which is a major source of socioeconomic stress.

B) Economics

In 1972, Bhutan's King Jigme Wangchuck coined the term Gross National Happiness (GNH) to emphasize the holistic values of economic development policies. While there has been no independent study to validate the success of Bhutan’s national policies, Wangchuck correctly asserts that economic growth does not necessarily lead to contentment. His government instead focuses on the four pillars of Gross National Happiness: economic self-reliance, a pristine environment, the promotion of culture, and good governance in the form of a democracy. Regardless of the King’s future success in formulating and executing his national policies, the concept remains a new and innovative way to look at modern socioeconomic development.

According to Nadia Mustapha’s article in Time magazine dated January 10, 2005, "The independent London-based think tank New Economics Foundation (NEF) is pushing for the implementation of a set of national well-being accounts that would tote up life satisfaction and personal development, as well as issues such as trust and engagement. The accounts would also include liabilities, such as stress and depression. In 2002, the Strategy Unit, an internal government think tank that reports to Prime Minister Tony Blair, conducted a seminar on life satisfaction and its public policy implications." Germany, Italy and France are also considering such studies.

There is a need for a new integrated qualitative and quantitative approach, as opposed to current subjective measures, to assist in the creation of a new socioeconomic development metric to measure and monitor the development of the nation's most important asset - its people.

A second generation GNH concept, treating happiness as a socioeconomic development metric, is proposed by International Institute of Management. IIM proposes to call it Gross National Wellness (GNW) or second generation Gross National Happiness (GNH). The metric measures socioeconomic development by tracking 7 development area including the nation's mental and emotional health. GNH/GNW value is proposed to be an index function of the total average per capita of the following measures:

1. Economic Wellness: Indicated via direct survey and statistical measurement of economic metrics such as consumer debt, average income to consumer price index ratio and income distribution

2. Environmental Wellness: Indicated via direct survey and statistical measurement of environmental metrics such as pollution, noise and traffic

3. Physical Wellness: Indicated via statistical measurement of physical health metrics such as severe illnesses, overweight, etc.

4. Mental Wellness: Indicated via direct survey and statistical measurement of mental health metrics such as usage of antidepressants and rise or decline of psychotherapy patients

5. Workplace Wellness: Indicated via direct survey and statistical measurement of labor metrics such as jobless claims, job change, workplace complaints and lawsuits

6. Social Wellness: Indicated via direct survey and statistical measurement of social metrics such as discrimination, safety ,divorce rates, complaints of domestic conflicts and family lawsuits, public lawsuits, crime rates

7. Political Wellness: Indicated via direct survey and statistical measurement of political metrics such as the quality of local democracy, individual freedom, and foreign conflicts.

The above 7 metrics were incorporated into the first Global GNH Survey

While the proposed new GNW or GNH metric may not be all-inclusive or provide a perfect measure, the consideration of the above parameters is a good start when creating a new metric for the measurement of socioeconomic development and policy management.

C) Work

Equal opportunity is not truly equal until all U.S. populations have equal access to the same quality of education and equitable development programs.

Government can institute new employment laws to promote life and work balance and to guarantee a healthy (mental and physical) work environment. Contrary to what some managers think, this recommendation does not have to incur additional costs or liabilities to their businesses, instead it will improve working relationships and productivity and reduce employee turnover. A smart corporate policy will ensure the development of its management team to transform an alpha-dominating/intimidating leadership style into a coaching leadership style with better work and relationship ethics.

D) Media:

Without controlling free speech and the commercial rights of media owners, government can fund public broadcasting to produce more educational and awareness programs to promote mental and emotional well-being, life management skills and social bonding. That will help change the public taste and demand for the type of information and commercial media programs.

E) Education:

If you google “antidepressants” you will get more then six million pages. If you do the same for "depression prevention" you will get less than 50 thousand. If you google "happiness education" you will get less than 500! Even when using different search phrases, the results are more focused on treatment than prevention. Many mild to moderate depression cases can be eliminated or at least greatly helped with personal life management and happiness education

Start in high schools by providing basic social education in applied formats to personal and relationship management including basic psychology, self-awareness, leadership development, communication skills, conflict resolution, and basic sociology (social contracts and civil duties).

F) Environment

Institute and enforce better policies to promote a cleaner and safer environment (city planning, art, spaces, reduced pollution, noise, traffic, health, and so on.)

Original source

There's an election coming in the UK - what is the UK government doing to help us be happy?