If the past is any indication of the future, then at least one commenter will write something to the effect of: “Huh? What are these drawings doing on the Freakonomics blog? They don’t belong here. Because Freakonomics is about [fill in the blank], and not about [fill in the blank]. Get rid of these!”
And then someone else will write something like: “Shut up. Jessica Hagy is brilliant, and if you weren’t such a numbskull you would know that.”
And the rest of us will sit back and be nearly as entertained by the comments as by Hagy’s work.
A few weeks back, just as I finished up my stint as a journal editor, I asked a former University of Chicago economics professor to serve as an anonymous referee on a paper.
Usually I wouldn’t ask someone in his eighties to be a referee, but the last time I used this fellow (when he was just a young turk in his late seventies), he wrote one of the most insightful referee reports I ever received. He took a paper that I had a hard time understanding, distilled it, and then explained how it could be redone much more simply to accomplish the same goal. I made the authors redo the paper exactly along the lines the referee recommended.
In fairness, the referee should have been a co-author.
Anyway, when I asked the octogenarian economist if he could referee a paper for me, here is the response I received:
Much as I would like to do a review of this paper, my schedule looking ahead for as much as a year is just too crowded. Maybe next time!!
I hope when I am in my eighties “too busy” is the reason I am turning things down!
When I was a kid, I loved baseball more than anything, and I’m afraid I mean that literally — more than my family, my friends, even more than my dog. If given the opportunity, I would have played baseball 24 hours a day. And when I couldn’t play it, I would watch it on T.V.
Now I can barely sit through a whole inning of a game on T.V.
Judging from the World Series T.V. ratings for the past 40 years — they’ve slipped from a 22.8 rating/57 share in 1968 to 10.6 rating/18 share in 2007 — I am not alone.
Why? Maybe I and a lot of people have adult-onset A.D.D. and need more stimulation than baseball can offer. Maybe there are just too many other forms of entertainment. Or maybe the game is just too boring.
No, but it hasn’t changed much since then either. If you are a traditionalist, which I am in many ways, this could be good news. But since sport is entertainment, you have to keep in mind that people get bored watching the same game play out every day.
Football and basketball may be more innately exciting than baseball, but just as important, they’ve also changed a lot over the past 40 years. They are full of innovation.
What is baseball’s biggest innovation of the past 40 years? Steroids maybe. Or the specialization of the pitching staff (yawn).
You may not like all the changes in other sports, but it does keep things interesting. Baseball, meanwhile — well, if you watched enough of it, you know exactly what’s coming at just about any point in the game. You can predict what the manager will do in a given situation. You can predict what the commentators will say after the play.
Darren Everson has written a nice piece in the Wall Street Journal about how a few baseball managers are trying some new things, however marginal. Here are a few examples from Everson’s piece:
1) Having a relief pitcher play the outfield for a batter or two and then come back in and pitch; this gets around the archaic substitution rules — you can’t take a pitcher out of the game and bring him back in — while still letting you practice situational pitching.
2) Putting an infield shift even on a right-handed batter like Vladimir Guerrero, which means asking any of the three infielders who might field the ball to make a long throw to first.
3) If bad weather is forecast, don’t waste your starting pitcher; instead, start a bullpen pitcher. More broadly, use relievers to start the game but have them pitch only a few innings, bringing in your “starter” to finish the game off, including innings eight and nine.
4. Have your pitcher bat eighth instead of ninth so your ninth-place hitter can set things up for the top of the lineup.
I particularly like what Bill James had to say in Everson’s article about why most managers do the same thing in baseball:
“A blunder by a manager is a move that is A) unconventional, B) doesn’t work, and C) occurs at a moment of focus in the game,” says Bill James, senior baseball-operations adviser with the Boston Red Sox. “If you put those three things together, you have a blunder. As long as you do what’s conventional, you won’t be accused of a blunder.”
While none of the above examples are earth-shattering, they’d certainly make the game a bit more fluid and fun to watch. I am guessing that you all can come up with at least a few dozen other potential changes, including rule changes, that would make baseball better without damaging its great tradition.
A lot of these changes might not have to do with how the game is played but rather how it is presented on T.V.; the long commercial break between each half-inning, for instance, is a gilded invitation to go watch something else.
I understand that the game is the game and that you don’t want to start installing trampolines in the outfield, for instance. But aren’t there some things that could be done to make people like me who used to love the game want to watch it again?
With more than $110 billion in tax rebates set to flow into taxpayer pockets starting today, everyone from big-box retailers to restaurants to debt-collection agencies is vying for a piece of the action. But what’s the smartest way to spend your rebate — for yourself and for the larger economy?
Now that we’ve considered that, how are you really going to spend it? And will it make you happier?
As Dubner has shown in the past, a quick snapshot — of a congestion-pricing poster in this case — can spark a lot of discussion.
So send us your photo or snapshot (here) — and be sure to tell us where it was taken, who took it, and what makes it Freak-worthy.
We’ll publish our favorites on the blog.
They don’t have to be artwork (or even photos of art):
No self-portraits or publicity materials please — Levitt has already covered that:
(Dubner’s the one on the far right.)
There’s one theme that we’ve touched on repeatedly in our Times columns and on this blog, and which we’ll devote considerable space to in SuperFreakonomics: how technological innovation and robust markets tend to fix a lot of problems that seem unsolvable.
In the business community, “innovation” is a buzzword of the highest order (so high, in fact, that some people run screaming the moment they hear it mentioned). See, for instance, Fortune’s innovation blog.
For all the talk, however, there remains the murky issue of how to properly measure innovation. The Department of Commerce, which has begun addressing this challenge, has this to say:
The United States today is more than 75 percent wealthier in terms of real G.D.P. per capita than it was 30 years ago, which is largely attributable to productivity gains driven, in large part, by innovation.
We gathered up a group of people who think about this issue — Ashish Arora, John Seely Brown, Seth Godin, Bill Hildebolt, Daphne Kwon, and Mark Turrell — and asked them directly:
How can a company measure innovation?
Here are their answers. Many thanks for their participation and insights.
If the question is, “How can a company quantify and measure innovation?” — then it’s certain the company is asking the wrong question.
Innovation happens long before the benefit is realized. And, by definition, each innovation is different than the one before it. As a result, you can watch an innovation become profitable and then say, “Wow that was great, let’s buy some more of that.”
Great organizations have faith in their future, and part of that belief is that innovation pays, even when it doesn’t. It pays because the next innovation — the one after this one — will pay.
And if we embrace the process, not the event, we win.
John Seely Brown, co-chairman of the Deloitte Center for Edge Innovation, former chief scientist of Xerox Corporation and director of its Palo Alto Research Center (P.A.R.C.).
“Metrics for such innovations are tricky, since social practices evolve slowly and surround us continuously, and thus become our frame of reference. It is not until we are abruptly forced to put them aside that we become aware of how much they have been shaping our lives.”
Ask how to measure innovation and you will get a barrage of answers. To help get some purchase on this question, let me suggest we consider three different kinds of innovation, each with its own metrics.
Incremental innovation might be best captured by the saying, “cheaper, thinner, faster and, of course, more features.”
For example, just look at the parade of L.C.D. televisions over the last few years, or digital cameras or cell phones. Incremental innovation is the mainstay of consumer electronics and many other consumer goods. It can be easily measured by looking at how much revenue each year is produced by new products versus legacy products.
These kinds of innovations are both predictable and are important for our economy. Although it is easy to measure the consequence of an incremental innovation, the progenitors behind them are often hard to determine — they can be suppliers, customers, or the company’s own internal R&D.
Architectural innovations are often deeper and more surprising than the incremental kind since they involve a restructuring of the very building blocks of a product family, industry, or infrastructure.
Consider, for example, voice over I.P. (V.O.I.P.) such as is being used by Skype, or the most recent announcement from I.B.M. on their new memory system called racetrack, or Google’s cloud computing. Each of these is changing the game and can be measured by the degree they transform the core competencies required to make, service, and deliver them and the degree they disrupt current business models. Perhaps V.O.I.P. is the clearest example of such.
Disruptive innovations are perhaps the most interesting, at least from a societal point of view. Many students of innovation question if something can even be called a real innovation if it doesn’t end up altering social practices.
Consider, for example, how the cell phone, digital camera or the personal computer, as products — or the world wide web, as a service — have slowly but surely transformed how we live, work, learn, and socialize. These innovations cause us to see and interact with the world differently.
Metrics for such innovations are tricky, since social practices evolve slowly and surround us continuously, and thus become our frame of reference. It is not until we are abruptly forced to put them aside that we become aware of how much they have been shaping our lives.
But the types of innovation we have mentioned thus far miss perhaps the most fundamental kind and the least appreciated kind of innovation — perhaps precisely because these innovations are so fundamental.
Let’s call these institutional innovations, because they actually enable society to function.
In periods of stability they are barely noticed since they are simply considered the way things are. Ask yourself this question:
What innovation over the last several hundred years has led to the most wealth creation?
I was once asked this by a group that was hoping I would say it was the microprocessor. But no, my guess was that it was the creation of the modern corporation (Ltd. in the U.K., Inc. in the U.S.).
The great innovation in the modern corporation was ownership without liability. This allowed shares to be sold on an open market and, unlike other forms of ownership, limited a shareholder’s liability to the price paid for the shares and nothing more. This made it possible for ordinary people to become investors.
My goal here is not to argue that I was right, but rather to suggest that institutional innovations tend to have pervasive and subtle influences on our lives. And in periods of great change, like now, they may well have more impact on us than any other kind.
For example, consider the impact that open source software license B.S.D. used for Linux is having, or the copyleft (institution) used by Wikipedia, or the creative commons licensing regimes, or the global process networks of Li & Fung’s apparel operations around the globe.
These institutional innovations are just the tip of the iceberg of what we will see and need in our age of accelerating change.
Ashish Arora, professor of economics and public policy at the Heinz School, Carnegie Mellon University.
“I can only quote Joseph Schumpeter … and say that ‘the wish was not father to the thought.’”
The creation and application of knowledge is at the core of innovation.
This knowledge need not always be new; Nathan Rosenberg and David Mowery recount how Henry Clay Frick used his knowledge of basic organic chemistry to understand which types of coal were best suited to make steel. Other steel producers at the time relied upon tradition and intuition to select their raw materials, providing Andrew Carnegie (Frick’s partner) with a decisive advantage.
In the twentieth century, American firms in a wide range of industries invested in reducing costs, improving the quality of their products, and in developing entirely new and useful products. As they did so, they also tried to measure what they were getting for their investments.
At one level, therefore, measuring innovation is straightforward.
Innovation can be measured by the additional profit it generates and expressed as a return on the investments made for that purpose. At the level of the industry or even economy as a whole, economists use the concept of “total factor productivity,” which captures a similar idea.
But this is a cop out.
The profits from an innovation can be a long time coming and depend upon many factors — some outside the innovator’s control. An innovation may be ahead of its time (as Charles Babbage’s mechanical computer perhaps was), may require extensive development, or may require extensive investments in infrastructure (as any clean fuel, such as hydrogen, certainly will).
So, if the reason for measuring innovation is so that a firm can reward its employees, attract investors, and persuade potential customers, we need to measure innovation — rather than the impact of innovation (as captured by return on investment or total factor productivity growth).
Therein lies the problem, for an innovation may be little more than a new business model to satisfy an existing customer need in a new way (McDonald’s, Starbucks, Barnes and Nobel, PepBoys, etc.).
The measurement problem is obvious. But in the spirit of, “It is better to light a candle than to curse the darkness,” firms use a variety of measures.
Some measure the number of new products and services they have introduced, or the share of their revenues linked to these new products and services. This is the measure that the government statistical agencies in Europe use as well in their Community Innovation Surveys (C.I.S.).
This seems sensible, but problems remain. In some cases, the product may be new only to the firm; another firm may have already introduced it. This may be an innovation for the firm, but not for the market. In other cases, the product may be have been developed by another firm, perhaps in another country.
But even more to the point, who is to say what is new, and what is merely old wine in a new bottle, or the same car with a new tail-fin?
Defining innovation using this measure comes down to each firm applying a version of Justice Potter’s famous test for pornography — “I know it when I see it.” As long as a firm applies the same standard, the number of new goods introduced may be a good way to track whether the firm has become more or less innovative over time.
However, it is not a good way to compare across firms or countries. For instance, the C.I.S. surveys imply that Spain and Portugal are more innovative than Germany, France, and the U.K.
For innovations of a technical nature, industry or government standards can provide another measure:
Indian software outsourcing firms worked to achieve CMM-level 5 certification as a way of signaling the high quality of their software development skills — these standards do not always mean what one might imagine.
Oracle Corporation widely advertised that its database products satisfied the highest level of security standards (popularly known as the Common Criteria) only for hackers to announce, days afterwards, that they had found ways to hack into the product.
Patents are another widely used measure. Typically, patents were thought to apply mainly to technical inventions, and in most of the world, they still do. However, in the United States, one can even patent innovations relating to new ways of doing businesses, as Amazon’s infamous “one-click” payment patent, or State Street’s patent on how to assemble a financial portfolio showed.
In other words, patents may represent land grabs in the intellectual space, rather than innovation, and many researchers are convinced that the patent system has gone too far. It is also true that many — perhaps even most — patents turn out to be of little value, so that the distribution of patent values is highly skewed.
That said, recent research suggests that patents are valuable. Research by Dietmar Harhoff and Alfonso Gambardella and their colleagues, based on a survey of inventors of patents, reveals that the typical (modal) patent was worth $9,000. However, a full 50 percent of the patents were worth at least $450,000!
Other research reveals a somewhat lower range of values, but on the whole, patents are a useful, though imperfect, measure of innovation.
However, for a firm, the problem with using patents to measure innovation remains: is a particular patent a blockbuster or a bust?
The way forward may lie in changing the viewpoint — treating the portfolio of patents as finance firms treat portfolios of assets of uncertain value. Some of the assets will pay off while others will not, and it is difficult, if not impossible to be more certain.
However, one can be more certain about the value of the portfolio. Similarly, firms may be able to borrow techniques from the world of finance.
A promising possibility may lie in the not-too-far-off future:
Innovations and new knowledge are increasingly being traded on the market, via licensing deals. My own research, with Alfonso Gambardella and Andrea Fosfuri, indicates that the value of the deals in the market for technology ranged between $30 billion and $45 billion in the mid 1990’s. More authoritative estimates, produced by Carol Robins of the Department of Commerce, imply that the value of such deals was about $60 billion in 2002.
The idea is to use these payments to estimate the value of a patent portfolio, much as one might use rental payments to estimate the value of a portfolio of real property.
In the end, however, all measures fall well short. This was also the conclusion a recent advisory government committee charged with recommending measures of innovation reached.
Innovation is simply too complex for a single summary measure. If this is too gloomy a conclusion, I can only quote Joseph Schumpeter (to whom we owe the immortal phrase, “creative destruction”), and say that “the wish was not father to the thought.”
“Embracing failure … brings you dangerously close to failure’s more deadly cousin, flailing.”
“It’s such a fine line between stupid and clever,” said David St. Hubbins (of Spinal Tap fame).
As a start-up company trying to pioneer a new industry, measuring innovation poses an especially tough challenge. Success by traditional metrics — revenue and profits — only becomes evident after you’ve become successful. In fact, early innovation often looks like idiocy and idiocy can masquerade as innovation.
Why is this?
According to Clayton Christensen in The Innovator’s Solution, truly disruptive technologies are generally worse than existing incumbent products at launch.
When the first digital cameras were made available to the public, their picture quality was far inferior to film cameras. Today it seems obvious that digital cameras were destined to vanquish film, but in the moment, it was hard to measure the true innovation that was occurring.
Our company’s focus, video product reviews, fares poorly against the incumbent — the ubiquitous written product review — in quality and quantity. But we have a vision that marrying the power of video storytelling with authentic consumer experiences can unleash word-of-mouth influence beyond anything available today.
While we track traditional industry metrics such as number of reviews, breadth of catalog, and quality of information, we’ve added new metrics that help define the goals of consumer word-of-mouth. Defining these new benchmarks helps us select new risk-taking projects that can speed us along our path to success.
How can our experience measuring innovation in the moment (rather than just looking backwards) be generalized for other entrepreneurs and managers?
We’re going to go on record and say that it is all about looking for and then celebrating the unique “failure metrics” in your business:
1) The rate of failure. As noted, innovation’s first steps are likely to be tentative and wrong. In a society that shuns failure, management needs to make a conscious effort to identify and embrace risk-taking. Failures can be turned into learning opportunities, but need to be meticulously constructed to do so.
Postmortem meetings reviewing projects that failed to meet their goals must be designed to be free of finger-pointing and dis-ownership. Instead, management should very purposefully uncover what was learned about its customers or partners through the effort. New projects should be born from those learnings immediately. Iteration is critical.
Most importantly, employees who were daring enough to experiment should be recognized and further empowered to pursue their initial hypothesis in a more informed way.
2) Failing along the right path. Embracing failure, however, brings you dangerously close to failure’s more deadly cousin, flailing.
Every entrepreneur will tell you that their first business plan was not where the company ended up. Every definition of innovation focuses on the fact that change is the critical element. However, empowering any idea for change can clog up precious resources and prevent truly innovative projects from seeing the light of day.
The critical ability of management to separate the wheat from the chaff is based largely on the strength of the company’s vision. Ensuring that management is in vision lock on the larger company mission will allow executives to have a positive, healthy debate about which ideas are likely to make the greatest impact on the company’s success.
3) The source of failures. Another measure we use to determine if our company is embracing failures is whether new strategic ideas are coming from all levels of the company.
Are only executives contributing to new projects, or are they bubbling up from the tech developers, customer service staf, and sales team? First, broad participation can indicate that you’ve been successful in creating a culture of risk-taking. Second, if most of the new ideas are strategic in nature, it can mean that you are effectively diffusing the broad vision of the company to all levels.
We review our board presentations with our entire staff to ensure that they are as aware of the discussions occurring behind closed doors as they are of those with their own managers. Knowledge is power in any organization and diffusing knowledge is essential to releasing creativity at all levels.
Failure must, of course, give way to success in order for customers, not to mention your staff and investors, to benefit. How entrepreneurs maintain the balance between pushing for success and embracing “failure” will be a key determinant in how quickly their start-ups can innovate new industries.
“Some of the largest R&D spenders live in a happy world where the number of patents goes up, whilst the returns slope downwards.”
The question of how to measure innovation is linked to, “Why measure innovation?” This differs depending on your viewpoint.
As an investor, you might wish to know that the company is innovating to justify a higher share price — set by market expectations of future growth — itself driven in part by innovation. Deloitte has published reports on the Innovation Premium that measures the contribution innovation makes to a company’s share price.
As an executive, you may need to use an innovation measure as a surrogate of future growth, both in terms of potential and pipeline deliverables.
As a functional director, you may be tasked with measuring innovation at group level, to support overall company objectives, and to assess the growth potential of your own areas.
And finally, back to the macro level and beyond, governments wish to measure innovation to determine the right levels of investment in education, R&D, and sponsoring champions to grow their economies and the economic well-being of their people.
Now, rather than giving the cop out answer of “it depends,” I’d like to try a different, more controversial tack — just to wake people up a bit:
Let’s start with a few commonly used measures of innovation — the number of patents and percentage of revenue from new products — and do a deep dive into them to see if they live up to their expectations.
Number of Patents
The theory of tracking number of patents, I hazard a guess, is that they are one of the few tangible measures of output from an R&D process. The granting of a patent is a milestone in the public domain, and has the added advantage that the granting takes place via a third party, not an executive committee that may be open to internal bias.
The theory would then have it that more patents are better than fewer new patents.
Unfortunately the theory is largely hokum, a fact acknowledged at least tacitly in the bars adjoining R&D conference venues, if not in public.
I recall a Motorola researcher commenting in a recent article that he was effectively coerced into filing multiple patents on trivial components, such as battery catches — an act that yielded zero business value but served to boost the patent numbers. Several leading companies have trawled through their patent portfolios to work out which patents actually drive business value, and are frequently shocked to discover that less than 10 percent of the patents drive 90 percent of the value.
R&D resources, already woeful in their returns (according to studies, 70 percent plus in R&D dollars are wasted), are directed to delivering patents instead of developing high-impact solutions that add value to customers and deliver positive financial returns. And some of the largest R&D spenders live in a happy world where the number of patents goes up, whilst the returns slope downwards.
Percentage of Revenue from Products Less Than 3 to 5 Years Old
This is one of the most commonly used measures of innovation for public companies. It is also highly dangerous, creating systematic distortions in behavior that can destroy business value and any semblance of an innovation culture.
It is supposed to work by calculating the revenue generated from recently introduced product lines, and measuring that revenue as a percentage of overall revenue. It is intended as a form of freshness indicator for the business, and has the benefit in that it measures realized outputs rather than expected benefit.
As a practitioner with ten years experience, and a personal leitmotif of “I break things”, I like to look at measures like this with a view to breaking them.
As a thought experiment, I set out four years ago to work out how a firm or group of people could cheat the metric. I then had the good fortune to meet folks working in the best companies in the world, and ask them whether they had witnessed dysfunctional behavior in their own careers (obviously, not them themselves, of course not, no, not never).
What emerged was shocking. One globally renowned corporate inventor referenced to his company’s practice of S.K.U. Innovation. (An S.K.U. is a shop keeping unit, a code used to track products.) When the company was faced with a shortfall in genuine new revenue from new products, certain groups just added new S.K.U. codes to the accounting system, thereby creating an artificial stream of “new” products.
Another executive in a sporting goods company commented that new products rarely reach anything like peak revenue in three years from initial launch, and so the top marketing executives would time their entry and exit into products based on the target and time line (sound familiar?).
Yet another executive in a manufactured goods company complained that the target could be hit by introducing new products that cannibalized existing revenue streams with worse margins — destroying the profitability of the business.
There is hope, however, of a more enlightened approach to this specific metric. Statements in annual reports have a Sarbanes-Oxley dimension to them, which means that auditors need to be comfortable that these are true statements. Whirlpool, one of the pioneers in this area, took this as an opportunity a few years ago to apply significantly more rigor to their measurement and reporting of new revenue. To save you wondering what they did for too long, the basic model they adopted was as follows:
- Introduce a strict definition for “innovative revenue” that precludes things like S.K.U. innovation.
- Allow new revenue streams to be counted as “innovation” for as long as the stream is growing at more than 10 percent per year (i.e. a growing product could be 20 years old, and providing that it is still growing, the group would still get credit).
- Force new products to have margins at least as good as existing margins in the category.
The two examples above highlight some of the challenges faced by organizations in measuring innovation. These common metrics both have significant negative implications to the efficient running of an innovative business.
There are frameworks that allow firms to better measure innovation. My firm, Imaginatik, has worked on innovation metrics for several firms. Our model is based around three areas of innovation metric:
1. Realized Benefits – a measure of outputs from the innovation process, using the Whirlpool definitions as a reference point.
2. Expected Benefits – a measure of pipeline value of project candidates.
3. Process & Engagement Metrics – a set of measures that describe how the front-end of the innovation process is working, including the level of employee engagement, the number of quality ideas generated, and the scope of the innovation initiative across a wide range of business activities.
Ultimately companies need to craft their own metrics, based on simple models as described above.
One final thought on metrics:
Metrics lose their value quickly if there are no targets associated with them. Measuring for measuring sake is a good way to tie up consultants for a few months, but it does not drive behavior and results. Targets are essential to help drive behavior, and target setting is a critical task for senior management. The absence of targets leads to uncertainty and an inconsistent application of any improvement activities.
Times columnist Nick Kristof recently highlighted economic research showing that climate change may be driving up the rate of executions of suspected witches in East Africa.
Tough times in the Congo may have been behind the recent witchcraft panic there, where police arrested 13 people accused of using black magic to shrink men’s penises.
University of Chicago economist Emily Oster also found a surge in witch hunts during Europe’s “little ice age,” from the 1500’s to late 1700’s.
Dubner and Levitt also wrote of some other surprising climate results over the ages, ranging from property crime, to life expectancy, to civil war.
What other unexpected consequences, whether economic, social, political, or otherwise, should we expect to see from climate change?
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.
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.
Back when I worked as an editor at the Times Magazine, we held weekly or twice-weekly editorial meetings at which you’d go around the table and suggest story ideas. There were many varieties of ideas, including: Dutiful but Dull; Dutiful and Worthwhile; Sexy but Substance-Free; Just Not Interesting; and everyone’s favorite: Interesting — if True.
Into this final category falls a report that a federal judge in Detroit has taken away from African-American mothers the right to name their babies:
[A] federal judge ruled today that black women no longer have independent naming rights for their children. Too many black children — and many adults — bear names that border on not even being words, he said. “I am simply tired of these ridiculous names black women are giving their children,” said U.S. Federal Judge Ryan Cabrera before rendering his decision. “Someone had to put a stop to it.”
Interesting — but true? Not even close, as the folks at Snopes.com explain. Which means, if nothing else, that our chapter in Freakonomics called “Would a Roshanda by Any Other Name Smell as Sweet?” isn’t headed for obsolescence just yet.
(Hat tip: Fred Telegdy.)
Michael and I looked over the 500 plus comments and suggestions that were generously offered regarding his upcoming dilemma:
How should I give away $70 million?
We were joined by his sister, Cathy, who also has a “small sum of money” (her words) that she needs to donate in the coming decade. Apparently, she will have to give away “only” about $45 million.
The three of us were overwhelmed at the number of thoughtful responses. Michael and Cathy’s specific reactions are presented below. We all agreed that the discussion should be continued.
Most of their friends won’t receive their trust-related disbursement for a few years, so I offered to bring together other privileged twenty- and thirty-somethings who might be looking to give away large sums of money to charity. If any aristocrats in the blogosphere would like to join me for a discussion, I invite you to e-mail me and come to N.Y.C. Don’t worry, I’ll pick up the tab for coffee and lunch.
I also shared with them the suggestions of “The Thugz,” the group of ex-street hustlers/gang members with whom I watched season five of The Wire. Shine and the others laughed when I asked them, “How can Michael use his charitable dollars most effectively.” They all wished they had this problem. Their replies echoed some of their earlier thoughts on the state of modern society:
SHINE: Like we always tell you, Sudhir — a man wakes up in the morning in most poor places, and his first problem is, “What am I going to eat?” He has to feed his family. Lots of people don’t realize that if you can’t eat, your whole day gets messed up.
I can’t tell you how many n– -s do stupid shit because they couldn’t get no food. Lot of people rob and steal to put some food in their belly. Make sure people got food. A man stops feeling angry against the world when his belly is full. That’s what I’d tell the brother to do with his money. And, make sure the older folks got food, not just the kids.
ORLANDO: Get them guns off the street. And, I don’t mean just around here (New York City). I mean go where them white folks live — New Jersey, and places like that.
If brothers want to fight, they should do like they did in the old days: with their hands. You get guns off the street, you’ll get rid of a lot of problems. I agree with Shine, people have to eat. But, there’s always going to be angry folks. The problem is when they start shooting each other.
TONY-T: The suburbs. My cousin grew up there. Went to college. Ain’t learned a thing. Tell Michael he should pay these kids to go do something so they can really learn what life is like.
Instead of going to college, pay them to go fix a house, or hang out with hustlers who struggle out here. I’ve been to the suburbs. You got some seriously ignorant people out there who need help.
KOOl-J: You want the truth? I’d make it a law that if people get money when their parents die, they have to spend ten years doing some kind of free work. You know, like what I had to do after jail: clean up the streets, paint buildings.
I sell a lot of dope to the rich kids, so I know what they’re like. They got a lot of time, and they don’t do nothing! That’s a crime. Make it so they can’t sit around all day, snorting coke. If they want their money, they have to get up off their a–. Like Michael is doing.
Michael and Cathy both admitted that their peers had relatively little pressure to make a “positive societal contribution.”
You grow up like I did, and it’s all so easy,” said Michael. “And, your parents really don’t think a lot about what you need. I mean, every time I had a problem, my mom wrote a check. My dad was never around.
“Right, and when Dad wasn’t around, his secretary wrote us the checks!” laughed Cathy.
So, I spent six years getting high, doing coke and feeling horrible about myself. Kool-J is absolutely right. There’s no one who teaches us what our responsibility is. And, now, I have to give this money away. But, how?! I really struggle to figure out where to begin.
I mentioned several options, including giving money to an established foundation and making a career out of philanthropy, as opposed to simply writing checks. Or, why don’t they draw on experts who help the rich give their money away?
Honestly, when you work with consultants, the first thing they do is make sure you don’t see what is really going on. If I have to see another brochure about a kid who beat the odds, or attend another party where my friends get applauded … It’s sickening, I don’t want consultants to protect me from the outside world. My parents already accomplished that.
Cathy continued by turning the lens inward. She pointed to GiveWell, an organization that she felt understood one of the central problems for her generation.
I’d like to help other people I grew up with first. I know that sounds crazy. If I tell you I’ve got hardships, you’ll laugh, right? I mean who really believes we have a hard life? The problem is that we have resources, but no direction. My friends like this group called GiveWell because they sort of get how we think, they understand where we are coming from. I would like to get to my friends just after they graduate, right when they start having problems — drugs, depression, getting bored. That’s the time I think I could help them. But, I still don’t know how, exactly, to do that.
“I know what I don’t want to do,” shouted Michael, spilling his coffee on his lap. And, at this point, the conversation turned to the comments of Freakonomics.com readers:
I will never act like I know better how people should spend their money. The one thing I can’t stand is when my friends give away money and then write a report card. At some point, I think you just have to trust that the money is doing good.
My friends give away millions, and all they do is b–ch and moan that they didn’t get the results they wanted. What did they expect? To end poverty overnight? They all want this oversight, but frankly it’s all armchair complaining.
Michael liked the suggestions regarding assistance to hospitals and medical clinics. He felt passionate about making sure people had access to good medical care: “I agree (with johnjac, #60). People shouldn’t die because they couldn’t get to a hospital.”
He wanted to combine health-related philanthropy with an approach to solving hunger in America.
I think that Debra (comment #380) is thinking like I am. I’d like to create a place where you come in, get a meal, get checked out, and get medical care. One stop. I’d also like to make sure we end hunger in this country. I think Shine is right: you can’t function if you’re hungry.
But, he quickly made the point that U.S. needs deserve priority over international charity — a point contested with great passion by many Freakonomics.com readers.
I can’t believe all these people think we should first give outside America! That’s exactly the problem.
I go to the Hamptons, and they have these stupid fund raisers for things going on that are thousands of miles away. And, then you go back to 5th Ave (on Manhattan’s Upper East Side), and you tell your doorman to make sure no homeless people ask you for money on the block. It’s sick.
Michael suggested that the government force rich, new philanthropists to give only in their own town or city. “Give locally. That way you’ll be forced to see the pain close up. And, you’ll see you can’t fix it overnight.”
“So, you’ll be giving to whom exactly? The poor child at 84th and Park?” I said with just a hint of sarcasm.
“No, but maybe I could give to their maid or nanny,” he quickly retorted. “She is getting $5 per hour, and is probably getting treated like crap!”
Cathy chimed in.
A lot of people (on the blog) talked up the idea that we should be social “entrepreneurs.” I disagree. I don’t like it when people like me give money away to get a return on their investment. That’s disgusting. I didn’t do anything to get rich, so why should I deserve to get anything back? And, I think that the micro-lending people also do the same thing. Give a dollar, get back 30 cents. Wow, that’s not charity, that’s selfish.
Michael felt similarly, but moved the conversation in a different direction — along the lines suggested by comment #299.
I like the idea of having people do things like building roads, or teaching the poor. But, I don’t like the Teach for America program. Two years, and then you go and work for Merrill, feeling good that at least you tried to save the world.
For God sakes, do it for longer. And, I think that people should do it differently. Maybe they have to teach for a year, go to work at Merrill, and then come back after five years. Then go back to being an I-banker, and then teach again. This way, you have to reconnect, and feel the pain of the world around you.
Michael kept saying “feel the pain” throughout the conversation, so I asked him what his next steps would be to get out of his insular world.
He said that he’d like to take a car and drive around the country and talk to people for a year. “I know I would prioritize hunger and hospitals and things like that. But, maybe I should get to know what’s out there. For a year, I’d like to feel my way around.”
Happy trails. Stay tuned.
… The amount of time auto-rickshaws are striking.
… How long it took to crack the iPhone root password.
… The length of the papal visit to New York.
… How long a man played online games before dying.
… How long a cow-human cross embryo lived.
The past few weeks I have been blegging for information about famous computer quotations to help with future editions of the recently published Yale Book of Quotations.
Another questionable quote is, “There is no reason for any individual to have a computer in their home.” This is attributed to Kenneth Olsen, the founder of Digital Equipment Corporation. Mr. Olsen is frequently quoted as having said it in a speech to the Convention of the World Future Society in 1977, but I have been unable to find contemporaneous documentation of the utterance.
The earliest version I have found was printed in the Arkansas Democrat-Gazette, October 30, 1984. Can anyone point me to evidence of earlier usage than that?
Also, some of the apocryphal or true “bad prediction” quotes are prognostications about business or the economy, not having to do with technology.
Irving Fisher saying, “Stock prices have reached what looks like a permanently high plateau,” in October 1929 (posted in a comment here last week) is an example. Can anyone suggest other celebrated business or economic bad predictions?
The actor Ed Begley Jr. has a widely-circulated OpEd piece touting his eco-friendly activities, featuring a proud announcement that his exercise on his stationary bicycle generates the electricity he uses to toast two pieces of bread.
Now those two pieces give him 200 calories, but he burns at least 100 calories on the bike. So half of his eco-friendly exercise is lost because he needs to obtain additional food from elsewhere to maintain his weight — food whose growth and distribution have environmental consequences too, as does the manufacture of his bicycle.
This illustrates the general equilibrium difficulties of so many pro-environmental activities about which the rich and famous boast.
Saving the environment in one market generates consequences in others. Perhaps the best illustration is the misguided effort to generate ethanol from corn by subsidizing farmers to switch to corn production. Fine for gasoline users, and fine in reducing environmental damage from gasoline; but corn uses lots of water (environmental depletion) and, moreover, the subsidies have helped fuel the spurt of inflation in food prices worldwide.
There should be a rule: before helping the environment in one market, we should be required to think through the impacts on other markets.
In 2006, a Rhode Island jury found three major paint makers liable for the toxic effects of lead paint on children.
One of those effects may have been a rise in the crime rate — and the removal of lead from house paint has been linked to the crime drop of the 1990’s (as Levitt blogged about here).
Now the paint manufacturers are appealing the landmark ruling before Rhode Island’s Supreme Court, with opening arguments scheduled for May 15.
Freakonomics readers may want to mark their calendars: due to the extraordinary level of interest in the case, oral arguments will be Webcast live.
(Hat Tip: Jon Pincince)
Arthur Brooks, the Louis A. Bantle Professor at Syracuse University’s Maxwell School of Public Affairs and a visiting scholar at the American Enterprise Institute, made his first appearance on this blog when he found that religious conservatives are more philanthropic than secular liberals. He has appeared a few more times since then. He has just published a new book, Gross National Happiness, and has agreed to blog here periodically on the subject. We are very pleased to have him.
Readers of this blog have been seeing quite a bit lately on the subject of happiness, which has become a fairly popular research topic for economists of late. Justin Wolfers has been publishing an elegant series of posts about whether money buys happiness.
But what about politics? Who’s happier, on average — conservatives or liberals? This is a major theme in my new book, and I’m going to post on this question here for a few weeks.
Several years ago I would have told you that liberals have the happiness edge. Regardless of our personal political views, when most academics like me think of an “average conservative,” I have found we tend to conjure up an image of something like the American Gothic: grim, puritanical, and humorless.
Until relatively recently it seemed that the evidence more or less backed up this impression. For example, in one study in the Journal of Research in Personality, Berkeley researchers traced the political ideology and world view of people in their early twenties back to the personalities they had exhibited as toddlers — recorded by their preschool two decades earlier.
The “liberal” young men had these principal traits as babies: resourcefulness in initiating activities, independence and autonomy, and pride in accomplishments. Liberal young women had similarly happy characteristics. In contrast, as babies the conservatives had been easily offended, immobilized under stress, brooding and worried, and suspicious of others. Conservative young women had cried the most easily.
There are a few reasons one might take issue with the study’s conclusions:
All of the study participants, for instance, lived in the San Francisco Bay Area (which by itself would make a conservative of any age emotionally rigid and prone to weeping). But this study reinforced the stereotype that conservatives are naturally less happy than liberals.
What the actual data on self-assessed happiness show, however, is that conservatives have a substantial happiness edge, at least by the time they grow up.
For three decades, the General Social Survey has asked a nationwide sample of adults, “Taken all together, how happy would you say you are these days? Would you say that you are very happy, pretty happy, or not too happy?” Here is a representative sample of the results:
• In 2004, 44 percent of respondents who said they were “conservative” or “very conservative” said they were “very happy,” versus just 25 percent of people who called themselves “liberal” or “very liberal.” (Note that this comparison uses unweighted data — when the data are weighted, the gap is 46 percent to 28 percent.)
• Adults on the political right are only half as likely as those on the left to say, “At times, I think I am no good at all.” They are also less likely to say they are dissatisfied with themselves, that they are inclined to feel like a failure, or to be pessimistic about their futures.
• It doesn’t matter who holds political power. The happiness gap between conservatives and liberals has persisted for at least 30 years. Indeed, the difference was greater some years under Bill Clinton than it was under George W. Bush. Democrats may very well win the presidency in 2008, and no doubt many liberals will enjoy seeing conservatives grieving out about that — but the data say that conservatives will still be happier people than liberals.
Lots of other data sources tell the same story as the G.S.S. Furthermore, there are many related findings, such as the fact that gun owners are happier than non-gun-owners, on average.
Now, before any conservatives get out their big foam fingers and liberals flame me to within an inch of my life, let me stress what these data are not saying.
• The data don’t say that all conservatives are happy, that all liberals are unhappy, or that all conservatives are happier than all liberals. Such claims would be absurd and wrong.
• The happiness differences here do not indicate that conservatives are better than liberals, righter than liberals, or even that they deserve to be happier. In fact, a major criticism of conservatives by liberals is that they have no right to be so happy—that they really should feel worse because they are misguided, or even malevolent. I’m not claiming here that the right wing merits their relative happiness. You can be the judge of that.
• The differences here mask all sorts of variations between different flavors of conservatives and liberals. Are right-wing libertarians as happy as religious conservatives? Are economic lefties more or less depressed than social liberals? We don’t know, because the data are too limited to get into that kind of detail.
In a post next week, I’ll dig into why conservatives have the happiness edge, hypotheses about world view and psychological differences, as well as some important lifestyle distinctions between right and left. After that, I’ll write about the happiness differences between people with moderate and extreme political views.
In the mean time, I welcome your thoughts.
How do you score a bruising fight like the Pennsylvania primary? In politics, it seems, expectations are everything. And regular readers will not be surprised to hear that I would argue that political prediction markets can help us understand which candidates actually exceeded pre-poll expectations.
Some simple observations:
• Clinton’s 9.5 point victory margin was roughly what one might expect from a candidate who had been rated as having a nine-in-ten chance to win the primary.
• Consistent with this, the electoral math appears roughly unchanged by last night’s result. Over recent weeks, markets have consistently assessed Obama’s chances of winning the Democratic nomination at about four-in-five, and early trading this morning suggests this assessment remains unchanged.
• If one simply relied on newspapers to track the race, one might be overwhelmed by the flow of bad news (or at least intense scrutiny) of Obama since the Texas and Ohio primaries. In fact, markets rate Clinton the real loser from the six week campaign in Pennsylvania: her chances of winning the nomination were as high as 29 percent following those earlier victories; today they are down to 18 percent.
• Looking forward, prediction markets suggest that Obama and Clinton are likely to trade victories over coming weeks. Currently Obama is favored in North Carolina, Oregon, and Montana, while Clinton is favored to win Indiana, West Virginia, and Kentucky. My full W.S.J. column analyzing recent movements in political prediction markets (written jointly with my Ph.D. student, David Rothschild, at 1 a.m. last night) is available here.
I walked into a Starbucks in Manhattan the other day and noticed that the food in the glass display case now lists three key facts: the name of the item, the price, and the calories. This last fact is new. It is the result of a recent New York City regulation that requires chain restaurants — those with 15 or more outlets in the city — to list caloric information.
Starbucks had a nice-looking (and huge!) apple fritter in the glass case that went for 490 calories. A slice of pound cake was just a bit less; I think the bagel cost 220 calories. When I asked the clerk about the new calorie info, she told me the signs had just gone up a few days earlier. I asked if she’d seen any changes. She wasn’t sure, she said, but she thought there was a bit less demand on the high-calorie items. A few days later, the Times published an article on the subject.
It struck me that this new regulation presents a great opportunity for obesity researchers. If you could get good data, I’m guessing we could learn a lot about how a posted calorie count affects eating behavior, with all sorts of wrinkles:
+ How calorie-sensitive are people in general, and are they more so during different times of day, days of the week, or types of days (holiday vs. workday, bad weather vs. good, etc.)?
+ If a posted calorie count does shock people into buying/eating differently, how long does that shock last?
+ There’s also a lot of experimentation to be done, including: altering the size of the calorie count on the signs and/or perhaps using different icons (smiley faces?) to differentiate between high-, medium-, and low-calorie foods. You could, of course, also experiment with using images like an obese person vs. a skinny person, or perhaps just a blob of fake fat to represent high-cal., but since we are talking about companies that sell food, I doubt they’d be interested. Maybe Brian Wansink would be, however.
It would also be interesting to see how calorie signs affect demand for lower-calorie foods. While on the surface, the New York City regulation might seem like bad news for restaurants, I could imagine it turning out to be good news if it stokes such demand.
Imagine that Starbucks figures out that most customers don’t want to buy any single piece of food that has more than 250 calories. No one is buying that delicious 490-calorie apple fritter any more (which, for the sake of argument, we’ll say costs $3). What if Starbucks cuts the portion size by 50 percent but sells the new fritter for 80 percent of the original price — i.e., a 245-cal. fritter for $2.40.
That means Starbucks is taking in $4.80 for every 500 calories of apple fritter it sells, versus just $3 in the old days. You might think that $2.40 is a lot for a half-size fritter — but if people turn out to be more calorie-sensitive than they are price-sensitive, Starbucks and a lot of other restaurants may be end up celebrating the day that New York City tried to rein them in.
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.
Tomorrow, we’ll turn to asking in a bit more detail just what these happiness data are measuring.
In some cases, both rely on the honor system to collect their revenue.
During tax season, New York State asks its citizens to voluntarily pay sales tax on any untaxed internet purchases they have made over last year. The plea has been pretty effective — New Yorkers handed over $45 million in internet sales tax last year alone. Still, that’s less than half of what the government thinks it’s owed.
So, starting in June, 2008, New York will require the largest online retailers to collect sales tax on purchases shipped to the Empire State.
Japanese farmers have had somewhat better luck with the honor system, which they employ in thousands of unmanned produce stands across the country. Many of the stands see payment rates approaching 90 percent. But in Japan, as in New York, the free ride may be coming to an end, the Yomiuri Shimbun reports, as farmers start to insist on being paid in full.
We’ve written about honor payment systems in unexpected places before.
Where haven’t we looked?
Reich has served in three national administrations, and implemented the Family and Medical Leave Act while he was labor secretary. He was awarded the Vaclev Havel Foundation Prize for his work in economic and social thought. He is currently professor of public policy at the Goldman School of Public Policy at the University of California and has written eleven books, the most recent of which is Supercapitalism.
We are very happy he has agreed to field questions from Freakonomics readers. Please fire away in the comments section below and, as with past Q&A’s, Reich will provide the answers in short course.