Does Income Bring Happiness?

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Back in 1974, Richard Easterlin published a paper called "Does Economic Growth Improve the Human Lot? Some Empirical Evidence" (available here and here, for example). Easterlin raised the possibility that what really matters to most people is not their absolute level of income, but their income level relative to others in society. If relative income is what matters, then an overall rise in incomes doesn't make me any better off relative to others, and so my happiness does not increase. Income becomes a sort of arms race: even as we all race to get more, it doesn't actually make us any happier.

Since then, the question of whether income brings happiness has been much-debated by economist and other social scientists. In "The New Stylized Facts about Income and Subjective Well-Being," Daniel W. Sacks, Betsey Stevenson, and Justin Wolfers offer a compact and readable summary of the evidence (much of which they generated in earlier research) that income is not just relative--and so more income does increase happiness. The paper is available as IZA Discussion Paper No. 7105, released in December.

At a basic level, this research looks at economic data on levels of income and compares it with survey data on on life satisfaction. For example, the Gallup World Poll provides data from 122 countries on the question: “Please imagine a ladder with steps numbered from zero at the bottom to ten at the
top. Suppose we say that the top of the ladder represents the best possible life for you, and the
bottom of the ladder represents the worst possible life for you. On which step of the ladder would
you say you personally feel you stand at this time?”

As a starting point, let's compare countries across the world in terms of real per capita GPD, along with their answers to this question on a scale from 0-10. The horizontal axis of the graph is a logarithmic scale: that is, rather than rising by a fixed amount between each tic mark, it rises by a fixed proportion (in this case, doubling) between each tic mark.

The general pattern is clear those in higher-income countries tend to report more life satisfaction. The best-fit straight line is drawn through the data. The much lighter dotted line is a "non-parametric" line which is a best-fit line that isn't required to be straight,and thus flattens out near the bottom and curves more steeply at the top than a straight line. Broadly speaking, it seems as if each doubling of income does lead to a distinct rise in the happiness scale, both for low-income and for high-income countries.

Of course, this result by itself doesn't prove the case either way. It could be that people in high-income countries are happier because they perceive that they are not in low-income countries, and so the happiness from their income is relative, rather than absolute. Thus, a second test is to look within individual countries at the happiness level of those with different income levels. If happiness from income is a relative concept, one might expect that, say, the rise in income from being a low-income person in the U.S to being a high-income person in the U.S. would bring more happiness, but the rise in happiness should be much less within a country than it would be across countries. However, the rise in happiness as a result of higher incomes within a country ends up looking very much like the relationship between countries.

Yet another test is to look at comparisons over time: that is, as economic growth gradually raises income levels, do people on average within a given country report a higher level of  happiness. The data here is harder to interpret, because long-run data on happiness measures isn't available for many countries, and the wording of the survey questions about life satisfaction often changes over time. While acknowledging that the existing evidence is messy and difficult to interpret firmly, the authors argue that it is at least consistent with the same finding: that is, higher income levels over time are correlated with higher reported life satisfaction.

But not for the United States! Sacks, Stevenson, and Wolfers write: "The US, however, remains a paradoxical counter-example: GDP has approximately doubled since 1972 and well-being, as measured by the General Social Survey, has decreased slightly." The authors point out that any individual country may have specific social changes that alter the reported "life satisfaction." In particular, they point out that inequality of income started rising in the U.S. economy in the 1970s, which may explain why the typical or median person in the economy isn't feeling much better off. They write: "We suggest that the US is more of an interesting outlier than a key example."

Those who want to sort through why Sacks, Stevenson, and Wolfers reach different conclusion from Easterlin can dig into the paper itself: a lot of the difference, they argue, is just that more and better data is available now.

For my own part, I confess that I find happiness surveys both intriguing and dubious. It seems to me that higher levels of income are typically correlated with more health, education, travel, consumption, and a higher quality of recreation, so it's not a surprise to me it seems to me that happiness rises iwth income. On the other side, it does seem to me that survey questions about life satisfaction are answered in the context of a particular place and time. If a person says that their life satisfaction was a 7 in 1960 on a scale of 0-10, and another person says that their life satisfaction is a 7 in 2013, are those two people really equally satisfied? To put it another way, if the person from 2013 was transported by a time machine back to live in 1960, with all their memories and knowledge of the technologies, medicines, foods, education, and travel available in 2013, would that time traveller really be equally happy in either time period? I suspect that when most people are asked to rank happiness on a scale of 0-10, they don't say to themselves: "Well, people living 100 years from now might have extraordinarily high levels of income and technology, so compared with them, I'm really no more than a 2." At best, survey questions on a scale of 0-10 seem like an extremely rough-and-ready way of measuring life satisfaction across very different countries or across substantial periods of time.

Plaudits for "The Instant Economist"

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Early in 2012, my book The Instant Economist: Everything You Need to Know About How the Economy Works, was published by Penguin Plume. Here's the Amazon link; here's the Barnes & Noble link. At the tail end of the year, the book was named an "Outstanding Academic Title" by Choice magazine, which is published by the American Library Association. It was also listed as one of the Best Books for 2012 in the "Business" category by Library Journal, another prominent trade publication for librarians. 

Here's the review from the August 2012 issue of Choice:

"Currently The Instant Economist is the most readable and up-to-date summary of a typical US college principles of economics course. Following the traditional table of contents--from microeconomics through macroeconomics and international topics--and using original, helpful metaphors (and only two graphs), Taylor (managing editor, Journal of Economic Perspectives) takes the reader through the terminology, key concepts, and controversies dominant in today's economics profession. Noteworthy additions to the standard textbook canon are a chapter on personal investing and detailed accounts of the minimum wage, corporate merger, and inequality debates, introducing readers to the data issues that lie behind these controversies. The 36 short chapters reflect the book's origin in the author's Teaching Company recording, Economics; however, the book is a valuable stand-alone option. For supplementary coverage of the history of
economic thought and more complete institutional context, see Robert Heilbroner and Lester Thurow's Economics Explained (4th ed., 1998; 1st ed., CH, Oct'82). Summing Up: Highly recommended. All levels of undergraduate students as well as general readers wanting a readable introduction to economics. -- M. H. Maier, Glendale Community College

And here's the review from the Library Journal:

"Taylor’s (managing editor, Journal of Economic Perspectives) volume can help conversationalists looking to raise the bar for their watercooler chats and casual readers who want to understand better the current economic condition of the United States. Taylor uses simple language with field-specific vocabulary to explain economic concepts, and each concept is successfully reinforced with a real-life—and usually entertaining—example. He hits all the subjects that might interest a layperson, such as division of labor, supply and demand, wages, competition and monopoly, inflation, banking, and trade, for a total of 36 petite chapters—just enough information to give the reader a basic but well-rounded understanding of the subject. VERDICT This highly readable, nonpoliticized look at some of the economic principles that shape our society, presented in an engaging, anecdotal fashion, is highly recommended for armchair economists and anyone with a general interest in the state of our economy. —Poppy Johnson-Renvall, Central New Mexico Community Coll. Lib., Albuquerque

As these reviews emphasize, the book is written for the general non-economist reader who would like to gain some insight into the terminology and structure of economic thinking. Those who are interested in knowing a bit more about the genesis of the book might check here.
As one of the reviews notes, this book was rooted in a course I several years ago for the Teaching Company, which is available here. Or if you are teaching or taking an introductory college-level course in economics, I of course recommend my Principles of Economics textbook, available here.

Over 65 and Working

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The proportion of U.S. adults who are "in the labor force"--that is, who either have jobs or are unemployed and looking for a job--has been falling for a decade, as I explored in an April 26, 2012, post on "Falling Labor Force Participation." But for one demographic group, the elderly, labor force participation is rising substantially.


Braedyn Kromer and David Howard of the U.S. Census Bureau offer some snapshots of the data in their just-released survey brief, "Labor Force Participation and Work Status of People 65 Years and Older." For example, here are some comparisons for the labor force participation of men and women, for those over 65 and for some age subgroups. While labor force participation is down a bit for the 75+ age group, it is noticeably higher since 1990 for the 65-69 and 70-74 age group. 


From a slightly longer-run perspective, 1990 was roughly the time period when labor force participation rates among the elderly were at their lowest. Here are a couple of figures from "The Increasing Labor Force Participation of Older Workers and its Effect on the Income of the Aged," by Michael V. Leonesio, Benjamin Bridges, Robert Gesumaria, and Linda Del Bene, which appeared in the Social Security Bulletin earlier in 2012. The figures show that for men over age 62, rates of labor force participation were falling through the 1980s, bottomed out around 1990, and have been rising since then. For women, the pattern is a little different, because a much greater proportion of women entered the paid workforce in the 1970s and 1980s, and so compared with earlier generations, a larger share of women continued working into their 60s and 70s, too.




The rising labor force participation of the elderly in the last two decades represents a remarkable social change. Here's a figure created with the ever-useful FRED website at the Federal Reserve Bank of St. Louis, showing the labor force participation rate of those over age 55, going back to the late 1940s.Through the 1950s, 1960s, and 1970s, the notion that more and more people would retire earlier and earlier seemed like an inexorable social trend. But the patterns have changed--and they changed long before the Great Recession.


When I was starting off as a young adult in the paid workforce in the 1980s, I remember looking at this kind of data and thinking about how I might be retire--like many other people!--in my mid-50s. But that's clearly not going to happen for me; instead, my current expectation is to be working well into my late 60s or 70s. A steadily rising average age of retirement has become the new normal. But then, a pattern of "keep living more years while working fewer years" was never a viable long-term option.

Checkerboard Puzzle, Moore's Law, and Growth Prospects

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My father the mathematician first posed the checkerboard puzzle to me back in grade-school, perhaps on some rainy Saturday. His version of the story went something like this:

The jester performs a great deed, and the king asks him how he would like to be rewarded. The jester is aware that the king is a highly volatile individual, and if the jester asks for too much, the king might just kill him then and there. The jester also knows that the king views his promise as sacred, so if the king says "yes" to the jester's proposal, then the king will honor that promise. So in a way, the jester's problem is how to ask for a lot, but have the king at least initially think it's not very much, so that the king will give his consent.

So the jester clowns around a bit and then says: "Here's all I want. Take this checkerboard. On the first square, but one piece of gold. On the second square, two pieces. On the third square, four pieces, and on the fourth square, 8 pieces. Double the amount on each square until you reach the end of the checkerboard."

In the story, the king laughs at this comic proposal and says,  "Your great deed was so wonderful, I would have happily done much more than this! I grant your request!"

But of course, when the king starts hauling up gold pieces from the treasury, he will discover that 2 raised to the 63rd power, the final spot on the checkerboard requires about 9 quintillion gold pieces (that is, 9 followed by 18 zeros). 

I've had some sense of the power of exponential growth ever since.  But what I hadn't thought about is the interaction of Moore's Law and economic growth. Moore's Law is of course named for Gordon Moore, one of the founders of Intel, who noticed this pattern back in 1965. Back in the 1970s, he wrote a paper that contained the following graph showing how much it cost to produce a computer chip with a certain number of components. Here's his figure. Notice that the numbers of component on the horizontal axis and the cost figures on the vertical axis are both graphed as logarithm (specifically, each step up the axis is a change by a factor of 10). The key takeaway was that the number of transistors ("components") on an integrated circuit was doubling about every two years, making computing power much cheaper and faster.


Ever since I started reading up on Moore's law in the early 1980s, there have been predictions in the trade press that it will soon reach technological limits and come to and end. But Moore's law marches on: indeed, the research and innovation targets at Intel and other chip-makers are defined in terms of making sure that Moore's law continues to hold for at least awhile longer. Stephen Shankland offers a nice accessible overview of the current situation in an October 15, 2012, essay on CNET: ""Moore's Law: The rule that really matters in tech"  (The Gordon Moore graph above is copied from Shankland's essay.)

As Shankland writes: "To keep up with Moore's Law, engineers must keep shrinking the size of transistors. Intel, the leader in the race, currently uses a manufacturing process with 22-nanometer features. That's 22 billionths of a meter, or roughly a 4,000th the width of a human hair." He cites a variety of industry and research experts to the effect that Moore's law has at least another decade to run--and remember, a decade of doubling every two years means five more doublings!

It's hard to wrap one's mind around what it means to say that the power of microchipo technology will increase by a factor of 32 (doubling five times) in the next 10 years. A characteristically intriguing survey essay  from the January 10 issue of the Economist on the future of innovation uses the checkerboard analogy to think about the potential effects of Moore's law. Here's a comment from the Economist essay:

Ray Kurzweil, a pioneer of computer science and a devotee of exponential technological extrapolation, likes to talk of “the second half of the chess board”. There is an old fable in which a gullible king is tricked into paying an obligation in grains of rice, one on the first square of a chessboard, two on the second, four on the third, the payment doubling with every square. Along the first row, the obligation is minuscule. With half the chessboard covered, the king is out only about 100 tonnes of rice. But a square before reaching the end of the seventh row he has laid out 500m tonnes in total—the whole world’s annual rice production. He will have to put more or less the same amount again on the next square. And there will still be a row to go.

Erik Brynjolfsson and Andrew McAfee of MIT make use of this image in their e-book “Race Against the Machine”. By the measure known as Moore’s law, the ability to get calculations out of a piece of silicon doubles every 18 months. That growth rate will not last for ever; but other aspects of computation, such as the capacity of algorithms to handle data, are also growing exponentially. When such a capacity is low, that doubling does not matter. As soon as it matters at all, though, it can quickly start to matter a lot. On the second half of the chessboard not only has the cumulative effect of innovations become large, but each new iteration of innovation delivers a technological jolt as powerful as all previous rounds combined."

Now, it's of course true that doubling the capacity of computer chips doesn't translate in a direct way into a higher standard of living: there are many steps from one to the other. But my point here is to note that many of us (myself included) have been thinking about the changes in electronics technology a little too much like the king in the checkerboard story: that is, we think of something doubling a few times, even 10 or 20 times, and we know it's a big change, but it somehow seems within our range of comprehension.

But when something has already been doubling every 18 months or two years for a half-century--it is continuing to double!--the absolute size of each additional doubling is starting to get very large. I lack the imagination to conceive of what will be done with all this cheap computing power in terms of health care, education, industrial process, communication, transportation, entertainment, food, travel, design, and more. But I suspect that these enormous repeated doublings, as Moore's law marches forward in the next decade and drives computing speeds up and prices down, will transform lives and industries in ways that we are only just starting to imagine.

Reusable Grocery Bags Can Kill (Unless Washed)

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One recent local environmental cause, especially popular in California, has been to ban or tax plastic grocery bags. The expressed hope is that shoppers will instead carry reusable grocery bags back and forth to the grocery store, and that plastic bags will be less likely to end up in landfills, or blowing across hillsides, or floating in water. The problem is that almost no one ever washes their reusable grocery bags. Reusuable grocery bags often carry raw meat, unseparated from other foods, and are often stored for convenience in the trunk of cars that sit outside in the sun. In short, reusuable grocery bags can be a friendly breeding environment for E. coli bacteria, which can cause severe illness and even death.

Jonathan Klick and Joshua D. Wright tell this story in "Grocery Bag Bans and Foodborne Illness," published as a research paper by the Institute for Law and Economics at the University of Pennsylvania Law School. As their primary example, they look at E. coli infections in the San Francisco County after it adopted an ordinance severely limiting the use of plastic bags by grocery stores.

As one piece of evidence, here's a figure showing the number of emergency room visits in San Francisco County related to E. coli for the 10 quarters before and after the enactment of the ordinance, where zero on the horizontal axis is the date the ordinance went into effect. (The shaded area around the line is a 95% statistical confidence interval.)  Clearly, there is a discontinuous jump in the number of emergency room visits.

For comparison, here's the same measure of emergency room visits related to E. coli infections for the other counties in the San Francisco Bay Area in the 10 quarters before and after the ordinance was enacted. These counties don't see a jump.

Klick and Wright flesh out this finding in a variety of ways. They look at other measures of foodborne illness, like salmonella and campylobacter, and also find a rise associated with the ordinance limiting plastic bags. They look at other cities in California that have enacted such bans, and although it is harder for them to track health effects for individual cities--because the health statistics are collected at the county level--they find negative health effects as well. (The city of San Francisco is consolidated with the county of San Francisco.)

Overall, they find that San Francisco typically experiences about 12 deaths per year from intestinal infections, and that the restrictions on plastic bags probably let to another 5-6 deaths per year in that city--plus, of course, the personal and social costs of some dozens of additional hospitalizations. With these costs taken into account, restrictions on plastic bags stop looking like a good idea.

Of course, a possible response to this problem is to launch a public information campaign to encourage people to wash their reusable grocery bags. But that response then leads to two other issues.  First, if public information campaigns can be effective on the grocery bag issue, the campaign could simply focus on the need to dispose of plastic bags properly and recycle them where possible--without a need to ban them. The argument for an ordinance sharply limiting the use of plastic grocery bags is, in effect, based on an implicit assumption that public information campaigns about grocery bags don't work well.  Second, if reusable grocery bags are washed after each use, then any cost-benefit analysis of their use would have to take into account the costs of water and detergent use. I have no idea if these costs alone would outweigh the benefits of reusable grocery bags, but it might be a near thing.

 Like most economists, I have a mental file drawer of "good intentions aren't enough" stories. The push to ban plastic grocery bags is one more example.

A Dose of Reality for Energy Policy

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Bruce Everett  of the Fletcher School at Tufts University offers a healthy double-helping of reality in his essay entitled "Back to Basics on Energy Policy: For the past 40 years, political leaders have promised that government can plan and engineer a fundamental transformation of our energy industry They were wrong." It appears in the Fall 2012 edition of Issues in Science and Technology. He begins:

"In June 1973, President Richard Nixon addressed the emerging energy crisis, saying that “the answer to our long-term needs lies in developing new forms of energy.” He asked Congress for a five-year, $10 billion budget to “ensure the development of technologies vital to meeting our future energy needs.” With this speech, the federal government set out to engineer a fundamental transformation of our energy supply. All seven subsequent presidents have endorsed Nixon’s goal, and during the past 40 years, the federal government has spent about $150 billion (in 2012 dollars) on energy R&D, offered $35 billion in loan guarantees, and imposed numerous expensive energy mandates in an effort to develop new energy sources. During this time, many talented and dedicated people have worked hard, done some excellent science, and learned a great deal. Yet federal energy technology policy has failed to reshape the U.S. energy market in any meaningful way."

For example, about 30% of that energy R&D spending went to nuclear power, with President Nixon forecasting 40 years ago that nuclear would provide half of the nation's electricity supply by 2000. But nuclear power plateaued at 20% of the electricity supply in 1991, and given the lack of new plants and the gradual retirement of older ones, it seems certain to be a declining contributor in the next few decades. 
Over the last 40 years, the U.S. government has backed a number of renewable energy technologies: hydro-power, solar, wind, solar, geothermal, synthetic fuels including ethanol, burning municipal  waste, and others. Over that time, the share of all these renewables in energy consumption went from 6% in 1973 to 8% at present. Hydropower and corn ethanol comprise more than half that total. Current projections from the Energy Information Administration hold that solar power will quadruple by 2035--at which point it will still be less than 0.5% of U.S. energy consumption.
The fundamental problem, Everett argues, is that showing something is possible at high cost is one thing, but commercializing it at low costs is quite another. He writes: "The mantra of the energy R&D program has always been, “If we can put a man on the Moon, we can do anything,” but this comparison is wrong. Apollo was a conceptual and technical triumph with no commercial aspirations. Between 1969 and 1972, the United States landed 12 astronauts on the Moon at a cost of $12.5 billion (in 2012 dollars) per astronaut. The purpose of the program was to accomplish a technically difficult feat a few times despite the enormous cost. Civilian technology requires the exact opposite: the ability to do something on a large scale at a low cost."
 As a matter of public policy, Everett argues, the government has shown a pattern of trying to force-feed commercialization before it is actually ready to happen, through subsidies to nuclear power, or synthetic fuels, or wind, or battery-powered cars. It's always politically enticing to promise that a few temporary subsidies will jump-start large industries with many new jobs, but the record in energy is that the subsidies are often long-lasting and large, while the subsidized companies are short-lived. Managers get their bonuses, but sustainable jobs aren't created. (And for those who argue that fossil fuels are subsidized as well, Everett points out that the taxes collected on oil use are vastly higher than any public support received by the oil industry.)
Everett doesn't emphasize the point, but the newfound ability of U.S. energy producers to access vast reserves of natural gas will reshape energy markets in manifold ways. I've posted in the past about "Unconventional Natural Gas and Environmental Issues" and also about my own preference for "The Drill-Baby Carbon Tax," which would be a policy of moving ahead with all deliberate speed in developing U.S. fossil fuel resources while also imposing a carbon tax and addressing the costs of other environment issues as well.
But after 40 years of watching the U.S. government try to force energy markets on to a different path, it's time for an alternative approach. The U.S. government should stop subsidizing commercial energy firms, and instead put that money into a dramatic increase in energy research and development.

Head Start is Failing Its Test

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I'll just admit up front that the vast inequities that exist even before children start school bother me, and that I am predisposed to favor programs that would help disadvantaged children early in life. Thus, I was delighted when Head Start announced some years back that it was going to carry out a randomized control trial--that is, to assign some preschool children randomly to Head Start and others not--so that it would be possible to do a statistically meaningful test of how well Head Start worked.  I presumed that the test would provide ammunition for my pre-existing views.

But as the evidence has built up, Head Start is failing its test. The latest evidence appears in the "Third Grade Follow-up to the Head Start Impact Study: Final Report," which was released in December. The report was carried out by a company called Westat and published by the Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. Basically, the report shows that Head Start provides short-term gains to preschool children, but those gains have faded to essentially nothing by third grade.

To appreciate how depressing this conclusion is, you need to appreciate the high quality of the study. It's based on a nationally representative sample of more than 5,000 3 and 4 year-olds from low-income families who were eligible for Head Start. These children were randomly either assigned to Head Start, or not. Data collection started in 2002, and so by 2008, data was available on how the children were performing in third grade. The study didn't just look at test scores: it considered a range of data on how Head Start might affect aspects of cognitive development, social-emotional development, health status and services, and even parenting practices.

The findings are summarized in this way:  "In summary, there were initial positive impacts from having access to Head Start, but by the end of 3rd grade there were very few impacts found for either cohort in any of the four domains of cognitive, social-emotional, health and parenting practices. The few impacts that were found did not show a clear pattern of favorable or unfavorable impacts for children."

Of course, because I am predisposed to favor these kinds of programs, I look for silver linings. Perhaps for certain specific subgroups such preschool programs can be useful? Perhaps certain kinds of curriculum are more likely to make a lasting difference?  Perhaps helping children from low-income families catch up before they start school is insufficient, but a sustained set of interventions continuing through elementary school would show lasting results? Sometimes studies of early preschool interventions have found little gain in measured outcomes a few years into school, but later gains like greater rates of high school completion or reductions in certain risky behaviors in adolescence. Maybe as the Head Start study continues, these sorts of longer-term gains will emerge?

I don't have an answer  here. Some years ago, I edited a paper in a special issue of the  Future of Children about the enormous gaps in school readiness for preschool children. Equal opportunity is an important goal of public policy, and as a society, we are clearly not providing equal opportunity to many children--who are already well behind before their first day of school. If the Head Start study had positive results about the long-run efficacy of preschool programs, I'd trumpet it to the hills. But the unfolding evidence isn't backing up the conclusion I would prefer.