If the rich could hire other people to die for them, the poor could make a wonderful living.
— Yiddish Proverb
Just like Jesus said, “The poor will always be with us.” There is a group of people [the poor] that just don’t want health care and aren’t going to take care of themselves Morally, spiritually, socially, [the poor, including the homeless,] just don’t wan’t healthcare.
— Rep. Roger Marshall, Republican of Kansas, NPR caption above.
In The Great Escape, published in 2013, one of us told a positive story about human progress over the last two hundred and fifty years. The story there was one of previously unimaginable material progress, a decline in poverty and deprivation, and extensions in the length of human life. The generation and application of useful knowledge made this progress possible. A star of the show was capitalism, which freed millions from dire poverty, supported by the positive forces of globalization. Democracy spread around the planet, allowing more and more people to participate in shaping their communities and societies. (Case and Deaton 2020, Preface)
This book is much less upbeat. It documents despair and death, it critiques aspects of capitalism, and it questions how globalization and technical change are working in America today. Yet we remain optimistic. We believe in capitalism, and we continue to believe that globalization and technical change can be managed to the general benefit. Capitalism does not have to work as it does in America today. It does not need to be abolished, but it should be redirected to work in the public interest. Free market competition can do many things, but there are also many areas where it cannot work well, including in the provision of healthcare, the exorbitant cost of which is doing immense harm to the health and wellbeing of America. If governments are unwilling to exercise compulsion over health insurance and to take the power to control costs—as other rich countries have done—tragedies are inevitable. Deaths of despair have much to do with the failure—the unique failure—of America to learn this lesson. (Case and Deaton 2020, Preface)
There have been previous periods when capitalism failed most people, as the Industrial Revolution got under way at the beginning of the nineteenth century, and again after the Great Depression. But the beast was tamed, not slain, and it brought the great benefits laid out in The Great Escape. If we can get the policies right, we can ensure that what is happening today is not a prelude to another great disaster but rather a temporary setback from which we can return to rising prosperity and better health. We hope this book, while not as heartening as The Great Escape, will help put us back on track to make the progress in this century that we have generally made in the past. The future of capitalism should be a future of hope and not of despair. (Case and Deaton 2020, Preface)
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Rep. Roger Marshall (R-Kan.), a member of the GOP Doctors Caucus (comments made in interview with Stat News). He further said, “The Medicaid population, which is a free credit card as a group, do probably the least preventative medicine and taking care of themselves and eating healthy and exercising. And I’m not judging; I’m just saying socially that’s where they are,” he told Stat News, a website focused on healthcare coverage. “So, there’s a group of people that even with unlimited access to healthcare are only going to use the emergency room when their arm is chopped off or when their pneumonia is so bad they get brought to the ER.”
The poor; when will they every learn! Going to the ER when you chop-off your arm! Sheesh, put a band-aid on it and take an aspirin — such little faith! It will get better soon like a miracle. Of course, the real solution is education and early and easy and affordable access to preventative healthcare. What the GOP and ilk like Roger Marshall are doing is scapegoating the poor while ignoring the bigger issues in American healthcare, such as insurance companies seeking to deny coverage based upon pre-existing conditions or drug companies charging predatory prices for life saving drugs.
In reality, this is the twisted anti-gospel of the GOP’s evangelical fundamentalist idolatry — libertarian unprincipled conservatism and its worship of wealth qua the prosperity gospel qua the gospel of greed— the monstrous abomination of a hybrid twisted gospel of evangelical fundamentalism and market fundamentalism, to wit:
Of course, anyone who knows THE ONE TRUEBiblicist gospel, Jesus instructed the poor to feed the rich, for the poor shall fill their empty bellies with good tidings preached to them by the rich — they don’t need (or want) good healthcare —for their treasures are in heaven. Have you not heard, “Happy are the poor and sick, for their treasures are in heaven waiting for them, and the sooner they get there the better for the rich.” Jesus had a firm sense of justice for the poor, but it was always Trumped by fiscal conservatism and his love for his favorite apostle Ayan Rand. The elderly, widowed, and disabled poor who would receive Medicaid must work or die quickly! What do they expect, mercy? Where do they think they are, heaven on earth? Have they not read, “Whoso stops his ear to the cry of the rich, he also will someday cry for help and no one will hear him.” Jesus also said to the rich man who invited him to dinner, “When you give a dinner or banquet serve caviar and champagne; invite your friends, your GOP fellows and political allies, all your rich republican neighbors, for they also will invite you in return and you’ll be repaid. But when you give a feast, leave some for the poor birds, and you’ll be blessed, for they cannot repay you — they are, after all, just sparrows. But not one of these little birdies falls to the ground without the Father knowing. Just don’t leave anything outside the gated community for the poor, the crippled, the lame, the blind and sick human beings— or they’ll start dumpster diving — and then their goes the neighborhood!
I suppose this book started when I first heard the story of Sergey Aleynikov, the Russian computer programmer who had worked for Goldman Sachs and then, in the summer of 2009, after he’d quit his job, was arrested by the FBI and charged by the United States government with stealing Goldman Sachs’s computer code. I’d thought it strange, after the financial crisis, in which Goldman had played such an important role, that the only Goldman Sachs employee who had been charged with any sort of crime was the employee who had taken something from Goldman Sachs. I’d thought it even stranger that government prosecutors had argued that the Russian shouldn’t be freed on bail because the Goldman Sachs computer code, in the wrong hands, could be used to “manipulate markets in unfair ways.” (Goldman’s were the right hands? If Goldman Sachs was able to manipulate markets, could other banks do it, too?) But maybe the strangest aspect of the case was how difficult it appeared to be—for the few who attempted—to explain what the Russian had done. I don’t mean only what he had done wrong: I mean what he had done. His job. He was usually described as a “high-frequency trading programmer,” but that wasn’t an explanation. That was a term of art that, in the summer of 2009, most people, even on Wall Street, had never before heard. What was high-frequency trading? Why was the code that enabled Goldman Sachs to do it so important that, when it was discovered to have been copied by some employee, Goldman Sachs needed to call the FBI? If this code was at once so incredibly valuable and so dangerous to financial markets, how did a Russian who had worked for Goldman Sachs for a mere two years get his hands on it? (Lewis 2014, 40-53)
[I]n a room looking out at the World Trade Center site, at One Liberty Plaza … gathered a small army of shockingly well-informed people from every corner of Wall Street—big banks, the major stock exchanges, and high-frequency trading firms. Many of them had left high-paying jobs to declare war on Wall Street, which meant, among other things, attacking the very problem that the Russian computer programmer had been hired by Goldman Sachs to create. (Lewis 2014, 53-56)
(….) One moment all is well; the next, the value of the entire U.S. stock market has fallen 22.61 percent, and no one knows why. During the crash, some Wall Street brokers, to avoid the orders their customers wanted to place to sell stocks, simply declined to pick up their phones. It wasn’t the first time that Wall Street people had discredited themselves, but this time the authorities responded by changing the rules—making it easier for computers to do the jobs done by those imperfect people. The 1987 stock market crash set in motion a process—weak at first, stronger over the years—that has ended with computers entirely replacing the people. (Lewis 2014, 62-67)
Over the past decade, the financial markets have changed too rapidly for our mental picture of them to remain true to life. (Lewis 2014, 67)
(….) The U.S. stock market now trades inside black boxes, in heavily guarded buildings in New Jersey and Chicago. What goes on inside those black boxes is hard to say—the ticker tape that runs across the bottom of cable TV screens captures only the tiniest fraction of what occurs in the stock markets. The public reports of what happens inside the black boxes are fuzzy and unreliable—even an expert cannot say what exactly happens inside them, or when it happens, or why. The average investor has no hope of knowing, of course, even the little he needs to know. He logs onto his TD Ameritrade or E*Trade or Schwab account, enters a ticker symbol of some stock, and clicks an icon that says “Buy”: Then what? He may think he knows what happens after he presses the key on his computer keyboard, but, trust me, he does not. If he did, he’d think twice before he pressed it. (Lewis 2014, 72-78)
The world clings to its old mental picture of the stock market because it’s comforting; because it’s so hard to draw a picture of what has replaced it; and because the few people able to draw it for you have no [economic] interest in doing so. (Lewis 2014, 78-80)
In April 1998, I traveled from London to the United States to interview several economics and finance professors. It was during this trip that I learned how derivatives had broken down the wall of skepticism between Wall Street and academia. My trip started at the University of Chicago, whose economists had become famous for their theories about market rationality. They argued that markets were supposed to reach equilibrium, which means that everyone makes an informed judgment about the risk associated with different assets, and the market adjusts so that the risk is correctly compensated for by returns. Also, markets are supposed to be efficient—all pertinent information about a security, such as a stock, is already factored into its price. In April 1998, I traveled from London to the United States to interview several economics and finance professors. It was during this trip that I learned how derivatives had broken down the wall of skepticism between Wall Street and academia. My trip started at the University of Chicago, whose economists had become famous for their theories about market rationality. They argued that markets were supposed to reach equilibrium, which means that everyone makes an informed judgment about the risk associated with different assets, and the market adjusts so that the risk is correctly compensated for by returns. Also, markets are supposed to be efficient—all pertinent information about a security, such as a stock, is already factored into its price. (Dunbar 2011, 36-37)
At the university’s Quadrangle Club, I enjoyed a pleasant lunch with Merton Miller, a professor whose work with Franco Modigliani in the 1950s had won him a Nobel Prize for showing that companies could not create value by changing their mix of debt and equity. A key aspect of Miller-Modigliani (as economists call the theory) was that if a change in the debt-equity mix did influence stock prices, traders could build a money machine by buying and shorting (borrowing a stock or bond to sell it and then buying it back later) in order to gain a free lunch. Although the theory was plagued with unrealistic assumptions, the idea that traders might build a mechanism like this was prescient. (Dunbar 2011, 37)
Miller had a profound impact on the current financial world in three ways. He:
Mentored academics who further developed his theoretical mechanism, called arbitrage.
Created the tools that made the mechanism feasible.
Trained many of the people who went to Wall Street and implemented it.
One of the MBA students who studied under Miller in the 1970s was John Meriwether, who went to work for the Wall Street firm Salomon Brothers. By the end of that decade, he had put into practice what Miller only theorized about, creating a trading desk at Salomon specifically aimed at profiting from arbitrage opportunities in the bond markets. Meriwether and his Salomon traders, together with a handful of other market-making firms, used the new futures contracts to find a mattress in securities markets that otherwise would have been too dangerous to trade in. Meanwhile, Miller and other academics associated with the University of Chicago had been advising that city’s long-established futures exchanges on creating new contracts linked to interest rates, stock market indexes, and foreign exchange markets. (Dunbar 2011, 37)
The idea of arbitrage is an old one, dating back to the nineteenth century, when disparities in the price of gold in different cities motivated some speculators (including Nathan Rothschild, founder of the Rothschild financial dynasty) to buy it where it was cheap and then ship it and sell it where it was more expensive. But in the volatile markets of the late 1970s, futures seemed to provide something genuinely different and exciting, bringing together temporally and geographically disparate aspects of buying and selling into bundles of transactions. Buy a basket of stocks reflecting an index, and sell an index future. Buy a Treasury bond, and sell a Treasury bond future. It was only the difference between the fundamental asset (called an underlying asset) and its derivative that mattered, not the statistics or economic theories that supposedly provided a benchmark for market prices. (Dunbar 2011, 38)
In the world Merton Miller lived in, the world of the futures exchanges (he was chairman emeritus of the Chicago Mercantile Exchange when I met him), they knew they needed speculators like Meriwether. Spotting arbitrage opportunities between underlying markets and derivatives enticed the likes of Salomon to come in and trade on that exchange. That provided liquidity to risk-averse people who wanted to use the exchange for hedging purposes. And if markets were efficient—in other words, if people like Meriwether did their job—then the prices of futures contracts should be mathematically related to the underlying asset using “no-arbitrage” principles. (Dunbar 2011, 38)
Bending Reality to Match the Textbook
The next leg of my U.S. trip took me to Boston and Connecticut. There I met two more Nobel-winning finance professors—Robert Merton and Myron Scholes—who took Miller’s idea to its logical conclusion at a hedge fund called Long-Term Capital Management (LTCM). Scholes had benefited directly from Miller’s mentorship as a University of Chicago PhD candidate, while Merton had studied under Paul Samuelson at MIT. What made Merton and Scholes famous (with the late Fischer Black) was their contemporaneous discovery of a formula for pricing options on stocks and other securities. (Dunbar 2011, 38)
Again, the key idea was based on arbitrage, but this time the formula was much more complicated. The premise: A future or forward contract is very similar (although not identical) to the underlying security, which is why one can be used to synthesize exposure to the other. An option contract, on the other hand, is asymmetrical. It lops off the upside or downside of the security’s performance—it is “nonlinear” in mathematical terms. Think about selling options in the same way as manufacturing a product, like a car. How many components do you need? To manufacture a stock option using a single purchase of underlying stock is impossible because the linearity of the latter can’t keep up with the nonlinearity of the former. Finding the answer to the manufacturing problem meant breaking up the lifetime of an option into lots of little bits, in the same way that calculus helps people work out the trajectory of a tennis ball in flight. The difference is that stock prices zigzag in a way that looks random, requiring a special kind of calculus that Merton was particularly good at. The math gave a recipe for smoothly tracking the option by buying and selling varying amounts of the underlying stock over time. Because the replication recipe played catch-up with the moves in the underlying market (Black, Scholes, and Merton didn’t claim to be fortune-tellers), it cost money to execute. In other words you can safely manufacture this nonlinear financial product called an option, but you have to spend a certain amount of money trading in the market in order to do so. But why believe the math? (Dunbar 2011, 38-39)
The breakthrough came next. Imagine that the option factory is up and running and selling its products in the market. By assuming that smart, aggressive traders like Meriwether would snap up any mispriced options and build their own factory to pick them apart again using the mathematical recipe, Black, Scholes, and Merton followed in Miller’s footsteps with a no-arbitrage rule. In other words, you’d better believe the math because, otherwise, traders will use it against you. That was how the famous Black-Scholes formula entered finance. (Dunbar 2011, 39, emphasis added)
When the formula was first published in the Journal of Political Economy in 1973, it was far from obvious that anyone would actually try to use its hedging recipe to extract money from arbitrage, although the Chicago Board Options Exchange (CBOE) did start offering equity option contracts that year. However, there was now an added incentive to play the arbitrage game because Black, Scholes, and Merton had shown that (subject to some assumptions) their formula exorcised the uncertainty in the returns on underlying assets. (Dunbar 2011, 39)
Over the following twenty-five years, the outside world would catch up with the eggheads in the ivory tower. Finance academics who had clustered around Merton at MIT (and elsewhere) moved to Wall Street. Trained to spot and replicate mispriced options across all financial markets, they became trading superstars. By the time Meriwether left Salomon in 1992, its proprietary trading group was bringing in revenues of over $1 billion a year. He set up his own highly lucrative hedge fund, LTCM, which made $5 billion from 1994 to 1997, earning annual returns of over 40 percent. By April 1998, Merton and Scholes were partners at LTCM and making millions of dollars per year, a nice bump from a professor’s salary. (Dunbar 2011, 40)
(….) It is hard to overemphasize the impact of this financial revolution. The neoclassical economic paradigm of equilibrium, efficiency, and rational expectations may have reeled under the weight of unrealistic assumptions and assaults of behavioral economics. But here was the classic “show me the money” riposte. A race of superhumans had emerged at hedge funds and investment banks whose rational self-interest made the theory come true and earned them billions in the process. (Dunbar 2011, 40)
If there was a high priest behind this, it had to be Merton, who in a 1990 speech talked about “blueprints” and “production technologies” that could be used for “synthesizing an otherwise nonexistent derivative security.” He wrote of a “spiral of innovation,” wherein the existence of markets in simpler derivatives would serve as a platform for the invention of new ones. As he saw his prescience validated, Merton would increasingly adopt a utopian tone, arguing that derivatives contracts created by large financial institutions could solve the risk management needs of both families and emerging market nations. To see the spiral in action, consider an over-the-counter derivative offered by investment banks from 2005 onward: an option on the VIX index. If for some reason you were financially exposed to the fear gauge, such a contract would protect you against it. The new option would be dynamically hedged by the bank, using VIX futures, providing liquidity to the CBOE contract. In turn, that would prompt arbitrage between the VIX and the S&P 500 options used to calculate it, ultimately leading to trading in the S&P 500 index itself. (Dunbar 2011, 40-41)
As this example demonstrates, Merton’s spiral was profitable in the sense that every time a new derivative product was created, an attendant retinue of simpler derivatives or underlying securities needed to be traded in order to replicate it. Remember, for market makers, volume normally equates to profit. For the people whose job it was to trade the simpler building blocks—the “flow” derivatives or cash products used to manufacture more complex products—this amounted to a safe opportunity to make money—or in other words, a mattress. In some markets, the replication recipe book would create more volume than the fundamental sources of supply and demand in that market. (Dunbar 2011, 41)
The banks started aggressively recruiting talent that could handle the arcane, complicated mathematical formulas needed to identify and evaluate these financial replication opportunities. Many of these quantitative analysts—quants—were refugees from academic physics. During the 1990s, research in fundamental physics was beset by cutbacks in government funding and a feeling that after the heroic age of unified theories and successful particle experiments, the field was entering a barren period. Wall Street and its remunerative rewards were just too tempting to pass up. Because the real-world uncertainty was supposedly eliminated by replication, quants did not need to make the qualitative judgments required of traditional securities analysts. What they were paid to get right was the industrial problem of derivative production: working out the optimal replication recipe that would pass the no-arbitrage test. Solving these problems was an ample test of PhD-level math skills. (Dunbar 2011, 41)
On the final leg of my trip in April 1998, I went to New York, where I had brunch with Nassim Taleb, an option trader at the French bank Paribas (now part of BNP Paribas). Not yet the fiery, best-selling intellectual he subsequently became (author of 2007’s The Black Swan), Taleb had already attacked VAR in a 1997 magazine interview as “charlatanism,” but he was in no doubt about how options theory had changed the world. “Merton had the premonition,” Taleb said admiringly. “One needs arbitrageurs to make markets efficient, and option markets provide attractive opportunities for replicators. We are indeed lucky . . . the world of finance has agreed to resemble the textbook, in order to operate better.” (Dunbar 2011, 42)
Although Taleb would subsequently change his views about how well the world matched up with Merton’s textbook, the tidal wave of money churned up by derivatives in free market economics carried most people along in its wake.9 People in the regulatory community found it hard to resist this intellectual juggernaut. After all, many of them had studied economics or business, where equilibrium and efficiency were at the heart of the syllabus. Confronted with the evidence of derivatives market efficiency and informational advantages, why should they stand in the way? (Dunbar 2011, 42)
Arrangers as Market Makers
It is easy to view investment banks and other arrangers as mechanics who simply operated the machinery that linked lenders to capital markets. In reality, arrangers orchestrated subprime lending behind the scenes. Drawing on his experience as a former derivatives trader, Frank Partnoy wrote, “The driving force behind the explosion of subprime mortgage lending in the U.S. was neither lenders nor borrowers. It was the arrangers of CDOs. They were the ones supplying the cocaine. The lenders and borrowers were just mice pushing the button.”
Behind the scenes, arrangers were the real ones pulling the strings of subprime lending, but their role received scant attention. One explanation for this omission is that the relationships between arrangers and lenders were opaque and difficult to dissect. Furthermore, many of the lenders who could have “talked” went out of business. On the investment banking side, the threat of personal liability may well have discouraged people from coming forward with information.
The evidence that does exist comes from public documents and the few people who chose to spill the beans. One of these is William Dallas, the founder and former chief executive officer of a lender, Ownit. According to the New York Times, Dallas said that investment banks pressured his firm to make questionable loans for packaging into securities. Merrill Lynch explicitly told Dallas to increase the number of stated-income loans Ownit was producing. The message, Dallas said, was obvious: “You are leaving money on the table—do more [low-doc loans].”
Publicly available documents echo this depiction. An annual report from Fremont General portrayed how Fremont changed its mix of loan products to satisfy demand from Wall Street:
The company [sought] to maximize the premiums on whole loan sales and securitizations by closely monitoring the requirements of the various institutional purchasers, investors and rating agencies, and focusing on originating the types of loans that met their criteria and for which higher premiums were more likely to be realized. (The Subprime Virus: Reckless Credit, Regulatory Failure, and Next Steps by Kathleen C. Engel, Patricia A. McCoy, 2011, 56-57)