by Robert Litan
Whatsyourprice.com is an extreme example of where prices can be used in a setting that most people would never consider to be a traditional market. Instead, the trend with the majority of dating sites has been to introduce algorithms designed to create efficient and stable matches. For example, the psychologists at eHarmony claim that the algorithm at this well-known dating site has the ability to identify the key traits that contribute most to stable matches and enduring relationships. Much like the labor market sites devoted to identifying the real characteristics that yield successful relationships in the workplace, eHarmony asserts that the traditional traits that lead to many relationships, like physical attraction, are in fact poor predictors of stable matches. The site instead arranges matches by using the results of long questionnaires that its customers fill out. The company doesn’t let customers search for partners on their own, a method the company thinks is inferior compared with its advanced algorithm.38
Over the years, other dating sites, which include match.com, chemistry.com, and okcupid.com to name a few, also have claimed that their algorithms produce better matches and longer-lasting marriages compared with alternative methods. However, many of these online sites preserve their intellectual property—their algorithms—as trade secrets, thereby making it virtually impossible to confirm with any degree of certainty whether their claims are valid.
It is nonetheless conceivable that the operators of one or more of these sites one day will develop sufficient confidence in the reliability of their algorithms to open up these databases for independent researchers to study. Indeed, it may only take one to get the ball rolling. If one site’s methodology is verified by highly respected researchers, other sites may be compelled by market pressures to open up their databases as well to other researchers. But even if none of this happens, eventually the good sites will drive out the bad or not-so-good ones or, hold your breath, a government agency like the Federal Trade Commission may compel the sites to publish their marriage rates and other indicators of dating success (such as length of marriages) as the sites mature.
As for the business opportunities associated with online matchmaking, the title of a recent book on the subject—Love in the Time of Algorithms—makes it clear that dating sites are here to stay. Indeed, with an estimated $2 billion in annual revenues in North America alone, third-party, for-profit matchmaking is a booming industry.39 Techniques used to make matches will surely improve over time, as will the design of the markets themselves, with likely better and more stable marriages the result. Let’s hope.
The Bottom Line
As important as prices are in clearing most markets, they are not the deciding factor in some markets where buyers and sellers, or those on each side of the market, are looking to match specific non-price characteristics. Just as the house in gambling establishments always collects the “vig,” matchmaking businesses in an expanding array of both traditional and nontraditional markets are likely to grow by earning fees from the matches they arrange. Hopefully this chapter has explained how and why economists may help them and their customers along the way.
Notes
1. Jonathan Gruber, Public Finance and Public Policy (New York: Worth Publishers, 2005), 3.
2. The Royal Swedish Academy of Sciences, “The Prize in Economic Sciences 2012: Stable Matching: Theory, Evidence, and Practical Design,” www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2012/popular-economicsciences2012.pdf.
3. Leon Neyfakh, “The Matchmaker,” Boston Globe, www.boston.com/bostonglobe/ideas/articles/2011/04/03/the_matchmaker/.
4. Alvin Roth, “The Art of Designing Markets,” Harvard Business Review, http://hbr.org/2007/10/the-art-of-designing-markets/ar/1.
5. Ibid., 1.
6. Hal Varian, “Avoiding the Pitfalls When Economics Shifts,” New York Times, www.nytimes.com/2002/08/29/business/economic-scene-avoiding-pitfalls-when-economics-shifts-science-engineering.html.
7. Muriel Niederle, Alvin E. Roth, and Tayfun Sonmez, “Matching and Market Design,” In The New Palgrave Dictionary of Economics, 2nd ed., ed. Steven Derlauf and Larry Blume (Hampshire, UK: Palgrave Macmillan, 2008).
8. Ibid.
9. Ibid.
10. Ibid.
11. Quote from his biography at the time of his winning the Nobel, which is a major source for this profile. Cynthia Lee and Judy Lin, “Colleagues Applaud Lloyd Shapley’s Nobel,” UCLA Today, http://today.ucla.edu/portal/ut/colleagues-at-ucla-applaud-lloyd-239730.aspx.
12. The American Economic Association, “Lloyd Shapley,” www.aeaweb.org/PDF_files/Bios/Shapley_bio.pdf.
13. The Royal Swedish Academy of Sciences, “The Prize in Economic Sciences 2012: Stable Matching: Theory, Evidence, and Practical Design,” October 2012, www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2012/popular-economicsciences2012.pdf.
14. Alvin Roth, “The Art of Designing Markets,” Harvard Business Review, 3, http://hbr.org/2007/10/the-art-of-designing-markets/ar/1.
15. Interview with Clayton Featherstone, October 18, 2013. I am grateful to Featherstone for discussing many of the insights of market design and matching theory described in this chapter.
16. Roth, “The Art of Designing Markets,” 2.
17. Ibid.
18. I appreciate the help that Clayton Featherstone provided in making the point in this paragraph.
19. Alvin E. Roth, Tayfun Sonmez, and M. Utku Unver, “Kidney Exchange,” Quarterly Journal of Economics 119, no. 2 (2004): 457–488.
20. Economic Report of the President (2013): 171.
21. Susan Adams, “Unfreakonomics,” Forbes, www.forbes.com/forbes/2010/0809/opinions-harvard-alvin-roth-freakonomics-ideas-opinions.html.
22. The Royal Swedish Academy of Sciences, “The Prize in Economic Sciences 2012.”
23. Ibid.
24. David Zax, “Falling for the Job,” Time, http://content.time.com/time/magazine/article/0,9171,2151168,00.html.
25. Aki Ito, “Algorithms Play Matchmaker to Fight 7.7% U.S. Unemployment: Jobs,” Bloomberg News, www.bloomberg.com/news/2013-04-03/algorithms-play-matchmaker-to-fight-7-7-u-s-unemployment-jobs.html.
26. George Anders, “Who Should You Hire? LinkedIn Says: Try Our Algorithm,” Forbes, www.forbes.com/sites/georgeanders/2013/04/10/who-should-you-hire-linkedin-says-try-our-algorithm/.
27. Ibid.
28. Zax, “Falling for the Job.”
29. Ito, “Algorithms Play Matchmaker.”
30. Zax, “Falling for the Job,” 4.
31. Ibid.
32. Ibid.
33. Ibid., 2.
34. The Economist, “The Modern Matchmakers,” www.economist.com/node/21547217.
35. Ito, “Algorithms Play Matchmaker.”
36. Mark Whitehouse, “Job-hunting Takes a Line from Dating,” Wall Street Journal, www.stanford.edu/~niederle/WSJ.Matching.htm.
37. Ibid.
38. Zax, “Falling for the Job,” 4.
39. Seth Stevenson, “Love Bytes,” Slate, www.slate.com/articles/technology/books/2013/02/dan_slater_s_love_in_the_time_of_algorithms_reviewed.html.
Chapter 8
Economists and Mostly Good Financial Engineering
We now come to the chapter about economists and finance. Given the bad reputation that the subject has earned in the wake of the financial crisis, I purposely delayed discussing it until I’ve put you in a better mood.
Seriously, economists, or actually financial economists, have made major contributions to our understanding of the way not only how the financial sector works, but also how the overall economy operates. Modern economies would not exist without modern financial sectors and systems, for finance is the lifeblood of all economies. When it works as it is supposed to, financial institutions and markets are not just abstract middlemen, but essential institutions that enable people and firms to save and diversify their wealth. Just as clogged arteries and malfunctioning hearts can debilitate or kill people, finance gone wrong can do the same to economies. That is wh
y financial engineering, in some quarters, no longer has the desirable connotations it once did. As an aside, most of those innovations that turned out wrong were not invented by economists, although many economists, including some famous and important ones, were late in realizing precisely how wrong they turned out to be.
In Chapter 12, I discuss a few ways in which economists have contributed to policy measures that have provided the platforms that have enabled or encouraged certain financial innovations or practices which I believe have had positive economic effects.
This chapter is not about policy, however, but about financially related economic ideas that collectively have had major business implications. I will concentrate on three of the most important ones, as well as on the economists who thought them up, and a few of the business visionaries who put them to profitable, socially productive uses.
Not Putting Your Eggs in One Basket: The Rise of Index Investing
If there is one adage that many investors have been told by their financial advisers, or by many books on investing, it is “Don’t put all your eggs into one basket.” In other words, do your best to diversify. True, this won’t make you a killing, unless you make a lot of money from some other endeavor, save a lot of it, and then put that money into a diversified portfolio of stocks, bonds, and some alternative assets (like real estate, or even gold). Then the laws of compound interest will take over, and if you live long enough, your wealth will be substantial.
There is a competing investment philosophy that is diametrically opposed to this bit of conventional wisdom. Attributed to a wide number of people, one of whom was Andrew Carnegie, the founder of U.S. Steel (once a mighty industrial powerhouse), this notion is to concentrate on only one investment, and then watch that particular “basket” very carefully. I have heard this quote from some businessmen before, and frankly, it strikes me as much better advice for people engaged in business than those deciding how to invest someone’s money.
Business calls for single-minded focus on what a firm and its employees do best. The national analogue to this notion is the principle of comparative advantage, probably one of the least understood and yet most important insights from economics. This principle says that nations (or firms or people) are best off if they concentrate on what they do best compared to others, even if they are absolutely better at doing a lot of things better than others. The principle implies that businesses are thus better off if they are focused on just one or a few things.
Investing is different. One can earn more and take less risk overall by diversifying. But what is the optimal amount of diversification? That was a question that Harry Markowitz asked in the early 1950s. His answer, roughly 20 to 30 stocks, and the methodology he used to derive it, earned him a Nobel Prize in 1990. Several years earlier, in 1981, Yale economist James Tobin (one of my graduate school mentors and favorite teachers and people) also won the Nobel Prize for related work.
Some ideas win Nobel Prizes while others become popularized, either by journalists or other economists. The notion that portfolio diversification is the best way to invest in the market provides such an example. When investors think of the concept, the individual who most often comes to mind is neither Markowitz nor Tobin, but long-time Princeton economics professor and frequent op-ed columnist Burton Malkiel, who penned one of the most famous popular books about investing, A Random Walk Down Wall Street. Originally published in 1973, the book has since had 10 editions.1
Ideas can have real-world commercial impacts in many different ways. Sometimes, entrepreneurs and executives at established firms read a book or an article with a clever idea and they proceed to make it operational. Others get commercial ideas from economists they hire as consultants. And frequently, as you will see in this book, entrepreneurs are motivated by an economic idea they learn while attending school.
John “Jack” Bogle, the founder of the Vanguard family of mutual funds, is a prime example of the last way economists have had an impact. Bogle reports that he was heavily influenced by both Malkiel and Paul Samuelson (profiled in Chapter 2), two of the champions of indexing and critics of active money management, especially by individual investors, both in writing his senior thesis at Princeton on the idea of index funds and then actually implementing that idea at Vanguard.2 In 1976, the firm launched its S&P index fund, shortly after Malkiel published his first edition of A Random Walk Down Wall Street.
The rest, as they say, is history. Not only did Vanguard go on to sponsor funds based on other indices, but other funds copied Vanguard’s model and did the same and then some. Eventually, numerous mutual funds offered all kinds of sector-specific funds, each with its own index.
It is difficult to overstate the importance of the indexing revolution in the mutual fund business, which up to Bogle’s time operated entirely through funds that were actively managed by stock pickers, and accordingly charged comparatively larger management fees (typically 1 percent or more of the assets of the fund each year) than index funds (where the fees tend to fall in the range of 10 to 20 basis points, or 0.1 to 0.2 percent of assets). Bogle has shown in his extensive writings how this difference in fees mounts up over time, especially for long-term investors, taking away half or more of their total returns.3 Furthermore, economic research has consistently documented that indexed funds have generally generated better returns for investors than actively managed funds. Investors have noticed, moving more of their money over time to indexed products: The share of all equity mutual funds that are indexed more than doubled from 1998 to 2012 (8.7 percent to 17.4 percent).4 If one adds in the newer exchange-traded funds discussed next, indexed products accounted for fully one-third of both stock mutual funds and ETFs in 2013.5
There is one downside to indexing, however: Index funds or their shareholders have no incentive to monitor the managers of the companies that make up the index, or to exercise voice rather than exit, to use Hirschman’s terminology. But there are still many investors who can and do perform this monitoring function, so it is not clear how much of a loss of oversight the trend toward indexing has actually caused.
In the past two decades or so, the exchange-traded fund (ETF) was developed by other financial entrepreneurs; it was modeled on the index approach that Bogle had pioneered. An index-based ETF essentially holds a fixed basket of stocks and trades like a stock throughout the day, unlike a mutual fund, which reprices only at the end of each trading day. In addition, an ETF has tax advantages over a mutual fund, which passes through its gains and losses on a pro rata basis to shareholders, with the decision to sell or buy being made by the fund manager. In an ETF, that decision is made by the ETF holder, who controls his or her own tax consequences.6
The ETF has made inroads into the institutional investment world for the above reasons, so much so that many mutual fund companies now offer ETF products themselves. Moreover, some innovators have designed ETFs whose stock holdings are actively managed. Still, as of 2012, assets held in ETFs accounted for only 9 percent of all assets managed by investment companies.7
What started then as a simple, but important economic insight from Harry Markowitz, elaborated by Samuelson, and popularized by Malkiel—that one gains superior returns given any level risk by diversifying an equity portfolio—eventually transformed the investment world.
Efficient Markets and Their Implications
It took an economist following an unlikely route to this subject to take the logic of index investing to the next theoretical level: If it makes sense to diversify, that must be because it is rare (see Warren Buffett), if impossible, to consistently outperform the market as a whole.
Eugene Fama was that individual, and for his research work he was awarded the Nobel Prize in Economics in 2013 (see following box). Fama won the prize for his development of the efficient markets hypothesis (EMH), which is one of the most cited, contentious, and often misunderstood propositions in economics. Nate Silver, the statistician and political forecaster (among other things), has done one of the
best jobs I have seen translating the hypothesis into plain English and I will summarize his description here.8
EMH has a number of versions, each stronger then the next. In its weakest form, EMH postulates the findings just stated: Future stock price movements cannot be predicted from past statistical patterns.
The second, semi-strong version of EMH, is that trying to pick stocks that are undervalued—the kind of thing that Warren Buffett does remarkably well—is a sucker’s game. All relevant information about the fundamental value of a company is instantaneously reflected in its stock price, so there is no room for investors or traders to consistently make money trying to guess which stocks will outperform the average, or won’t.
How then can one explain Buffett’s success (and that of a few others, like Peter Lynch, the famed investor who managed Fidelity’s Magellan Fund in its early years for roughly two decades)? Fama’s answer, like that of other EMH defenders, is luck. In any large number of coin-flippers there inevitably will be a few who consistently pick which side of the coin comes out on top. But the winners clearly have no special insight into coin flipping.
Buffett had a rejoinder to that answer, which he supplied in a famous debate he had at Columbia University in 1984 with another EMH defender, Harvard Business School professor (emeritus) Michael Jensen. The event celebrated the fiftieth anniversary of the publication of the bible of value investing, Graham and Dodd’s The Intelligent Investor, which advocates an investment style that is the very antithesis of EMH. After Jensen presented the coin-flipper analogy, Buffett replied by identifying nine other money managers who managed very different portfolios and yet had outstanding investment records. This result, he argued, could not be the result of random flips of the coin.