adverse selection

Trading and Exchanges: Market Microstructure for Practitioners
by Larry Harris
Published 2 Jan 2003

However expressed, adverse selection is the most important determinant of dealer profitability. The remainder of this chapter discusses how dealers respond to adverse selection from informed traders. We focus closely on adverse selection because informed trading is the most important—and most dangerous—cause of one-sided order flows. Dealers must have a thorough understanding of informed trading to best discover market values and avoid substantial losses. Dealers generally discover fundamental values as a by-product of their search for market values. 13.8 DEALER RESPONSES TO ADVERSE SELECTION Successful dealers must confront the informed trader problem continuously.

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This additional widening of the spread is the adverse selection spread component. It allows dealers to recoup from uninformed traders what they lose to informed traders. By widening the spread, it also decreases dealer losses to informed traders by ensuring that informed traders trade at less attractive prices. Economists also call the adverse selection spread component the permanent spread component. Price changes due to the adverse selection spread component are permanent in the sense that they do not systematically reverse. Subsequent price increases and decreases are equally likely. Price changes due to the adverse selection spread component reflect changes in dealers’ estimates of instrument values.

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On average, limit order strategies will execute at slightly better prices than market orders strategies because market order traders must compensate limit order traders for the additional management time, price risk, and timing options associated with limit order strategies. Adverse selection helps us understand why uninformed traders lose whether they submit limit or market orders. If they use limit orders, they suffer adverse selection. When they compete with informed traders, their limit orders do not fill, and they subsequently wish they had traded. When they offer liquidity to informed traders, their limit orders quickly fill, and they subsequently wish that they had not traded. If they use market orders, they avoid direct adverse selection, but they still suffer its indirect effects because they must pay dealers the adverse selection spread. The adverse selection spread is effectively a fee dealers charge uninformed traders for bearing their adverse selection risk.

Big Data and the Welfare State: How the Information Revolution Threatens Social Solidarity
by Torben Iversen and Philipp Rehm
Published 18 May 2022

This fragmentation has been magnified by the growing segmentation of labor markets into low- and high-skilled occupations, which has left many of the former uninsured – a trend only recently counteracted by the ACA. 3 Gottlieb (2007) claims that MASs providing sickness insurance did not face an adverse selection problem. But the evidence is not entirely persuasive. He essentially tests whether members (compared to nonmembers) were more likely to be sick (or suffer an accident). According to his data, this does not appear to be the case, but membership composition already reflects efforts to deal with adverse selection. In our view, the adverse selection was in fact a serious problem for MASs. https://doi.org/10.1017/9781009151405.003 Published online by Cambridge University Press Before the Welfare State 51 insurance areas – unemployment, health, and pensions – were grossly under-provided.

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The previously mentioned event would have been impossible to predict ex ante, but information often allows those in bad health to buy good plans, which drives up prices and pushes out good risks and that, in turn, increases prices even further in a spiraling logic. In the insurance literature, this is called adverse selection. Adverse selection is not the only 1 https://doi.org/10.1017/9781009151405.001 Published online by Cambridge University Press 2 Introduction reason insurance markets break down, but it is an important one and it helps explain why, inter alia, medical insurance in most rich democracies is public.

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Gottlieb notes that “intrusive monitoring and social pressure may have been an effective way of mitigating moral hazard” (2007, 278), and such monitoring can be seen as an extension of MASs “fraternizing” function (which sometimes turned abusive). In this respect, MASs had a real advantage over commercial insurance, which was anonymous and arm’s length. Nevertheless, it was hard to avoid adverse selection in the case of sickness pay, and the time-inconsistency problem was never far behind because older workers were more likely to fall sick or have accidents. Unlike the case of burial insurance, rising life expectancy made the adverse selection problem worse (Beito 1990, 725), and the implied direct transfer between younger and older generations was severe enough that it has been likened to a Ponzi scheme (Kaufman 2002, 47).

The Wisdom of Finance: Discovering Humanity in the World of Risk and Return
by Mihir Desai
Published 22 May 2017

Given the importance of adverse selection and moral hazard, what are the best mechanisms for dealing with them? Ensuring that insurance pools aren’t susceptible to people advantageously selecting into policies is what national mandates to buy insurance and employer-provided insurance are all about. Similarly, deductibles make sure that individuals aren’t overusing healthcare because they’re insured. But what organization is best suited to pool risk and counter the effects of moral hazard and adverse selection? It should be one where membership isn’t a choice, so that adverse selection isn’t operating, and one where you can closely monitor each other’s behavior to make sure moral hazard doesn’t work against you.

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Even if the French had annuity rates that differed by age, as they clearly should have, the adverse selection problem would have persisted. Individuals who know they’re healthy enough to outlive their expected longevity will buy these annuities, while those knowing that they have histories which would indicate earlier mortality would never invest. In fact, economists Amy Finkelstein and James Poterba have shown that the United Kingdom’s large annuity market still demonstrates this same tendency: people buying annuities live longer than people who don’t. That means pricing of the annuities has to try to anticipate how much adverse selection there will be—and that’s not easy.

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The discussion of the IOOF draws on Emery, George Neil, and John Charles Herbert Emery. A Young Man’s Benefit: The Independent Order of Odd Fellows and Sickness Insurance in the United States and Canada, 1860–1929. Montreal: McGill-Queen’s University Press, 1999. Evidence of adverse selection in the British annuities markets is from Finkelstein, Amy, and James Poterba. “Adverse Selection in Insurance Markets: Policyholder Evidence from the U.K. Annuity Market.” Journal of Political Economy 112, no. 1 (2004): 183–208. Evidence on the effects of pensions on household formation is from Costa, Dora L. “Displacing the Family: Union Army Pensions and Elderly Living Arrangements.”

Culture and Prosperity: The Truth About Markets - Why Some Nations Are Rich but Most Remain Poor
by John Kay
Published 24 May 2004

Inexpensive and noninvasive tests of height, weight, and blood pressure can give the insurer equivalent knowledge about the prospective policyholder's health. Even so, adverse selection is a problem. Medical insurance is cheaper when bought by an employer for a group of workers. This is not primarily because of the employer's greater bargaining power. The insurer insists that the employer provide cover for all employees and so reduces or eliminates the adverse-selection issue. Private individuals seeking medical insurance are more than averagely likely to be sick, or to be hypochondriacs. Markets for life and medical insurance are possible because medical knowledge is still rudimentary.

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The combination proved irresistible to fools and crooks. 16 The government met losses that ultimately ran to the tens of billions of dollars while the savings and loans, and their execu- Culture and Prosperity { 241} tives, kept the gains. When those you insure can influence the risks you cover, you must supervise them. Social Insurance of Personal Risks ••••••••••••••••••••••••••••••••••••• When people can opt out, adverse selection is a problem. If you can't easily watch what they're doing, moral hazard is a problem. The combination of adverse selection and moral hazard means that risks are best managed by groups that have other common bonds: typically families, communities, workplaces, and nations. The management of everyday risk is best and principally undertaken through social institutions.

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A single failure jeopardized the entire Lloyd's insurance market (in one case) and the American securities market (in the other). Far from spreading risks and reducing their costs, markets in risk concentrated them and made them threatening, even fatal, to the solvency of participants. { 238} John Kay Asymmetric Information and Adverse Selection * ••••••••• * ••••••••••••••••••••••••• * The risk that Seabiscuit will not come in first in the 1940 Santa Anita handicap. The risk that the Federal Reserve will unexpectedly lower interest rates. The risk that a hurricane will hit the South Carolina coast. These risks are the currency of specialist risk markets in modern market economies.

The Middleman Economy: How Brokers, Agents, Dealers, and Everyday Matchmakers Create Value and Profit
by Marina Krakovsky
Published 14 Sep 2015

As a result, honest sellers (unable to show that they are honest) would have trouble getting a good price for their goods, driving some of them out of the market—a decision that leaves the market overpopulated with dishonest sellers, which further erodes buyers’ trust and prices and so on in a vicious cycle called “adverse selection.”26 The original paper about adverse selection, “The Market for Lemons,” dealt with the case of used cars, but the phenomenon is so pervasive, rearing its head in important markets like those for insurance, that the economist behind the lemons model, George Akerlof, eventually earned a Nobel Prize for this insight.27 The lemons problem explains why middlemen so often appear in markets for used goods: they not only have the expertise to judge quality, but they can vouch for it with their reputation.

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And yet, as the chapters on Certifiers and Enforcers showed, middlemen must be discriminating to avoid adverse selection and moral hazard. Therefore, to profit from risk, middlemen, like successful insurers, must be astute at teasing apart these two types of risk: •Internal risk. This is my term for what finance scholars call counterparty risk, or risk due to the characteristics or actions of a trading partner. In other words, internal risks are risks caused by asymmetric information (adverse selection and moral hazard). Risk-bearing middlemen should avoid internal risk because it can only harm them and their partners on the other side.

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The middleman who is able to bear risk can profit from doing so by charging a risk premium, while the more risk-averse party doesn’t mind paying the risk premium to reduce risk. So why don’t we see middlemen bearing most of the risk? The answer to this risk-sharing question goes back to the old problems of adverse selection and moral hazard. Most economic outcomes in the world are some combination of effort and chance (or skill and luck). How many widgets a sales rep sells, for example, depends on how hard the rep works, how good the rep is at sales to begin with, and factors completely outside the rep’s control, from the quality of the widget to the state of the economy.

Advances in Financial Machine Learning
by Marcos Lopez de Prado
Published 2 Feb 2018

See Chapter 19 for further details on this microstructural theory. Persistent order flow imbalance is a necessary, non-sufficient condition for adverse selection. For market makers to provide liquidity to informed traders, that order flow imbalance |OIτ| must also have been relatively unpredictable. In other words, market makers are not adversely selected when their prediction of order flow imbalance is accurate, even if |OIτ| ≫ 0. In order to determine the probability of adverse selection, we must determine how unpredictable the order flow imbalance is. We can determine this by applying information theory. Consider a long sequence of symbols.

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Entropy characterizes the redundancy of a source, hence its Kolmogorov complexity and its predictability. We can use this connection between the redundancy of a sequence and its unpredictability (by market makers) to derive the probability of adverse selection. Here we will discuss one particular procedure that derives the probability of adverse selection as a function of the complexity ingrained in the order flow imbalance. First, given a sequence of volume bars indexed by τ = 1, …, N, each bar of size V, we determine the portion of volume classified as buy, vBτ ∈ [0, 1]. Second, we compute the q-quantiles on {vBτ} that define a set K of q disjoint subsets, K = {K1, …, Kq}.

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This results in a translation of the set of order imbalances {vBτ} into a quantized message X = [f[vB1], f[v2B], …, f[vBN]]. Fifth, we estimate the entropy H[X] using Kontoyiannis’ Lempel-Ziv algorithm. Sixth, we derive the cumulative distribution function, F[H[X]], and use the time series of {F[H[Xτ]]}τ = 1, …, N as a feature to predict adverse selection. Exercises Form dollar bars on E-mini S&P 500 futures: Quantize the returns series using the binary method. Quantize the returns series using the quantile encoding, using 10 letters. Quantize the returns series using the sigma encoding, where σ is the standard deviation of all bar returns.

The Economics of Inequality
by Thomas Piketty and Arthur Goldhammer
Published 7 Jan 2015

The government’s advantage in this respect is that, over time, it has acquired the legal and administrative capacity to monitor what employers actually pay workers and thus to establish each worker’s claim to unemployment insurance. Adverse selection is also an important factor. Companies have an interest in attracting low-risk clients, but the worker is better informed than the company about his level of risk. Companies will therefore tend to offer policies designed to separate low-risk workers from high-risk ones. Such policies will be inefficient. For instance, they may propose high deductibles or cover only minor risks. Adverse selection can be particularly problematic in the health insurance market, where individuals often have a good deal of private information about their risks.

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The lender will also want to make sure that the borrower has sufficient incentives to do what needs to be done over a long period of time even though some of the gains will go to the lender. Finally, the lender needs to assure himself that the borrower will not simply disappear with the profits. Investment thus raises a series of problems that economists have classified as problems of “adverse selection” and “moral hazard.” Such problems arise wherever there is an “intertemporal” market, that is, a market in which exchanges occur in different time periods. Credit markets are intertemporal markets, as are social insurance markets, which we will encounter in Chapter 4. These problems are particularly difficult in international markets, because the information available about potential borrowers and investment projects in another country may be of low quality.

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This argument is often used to explain why health care costs are so high in countries where private health insurance predominates, such as the United States, and to justify government regulation of health-care expenditure in public health-care systems. The imperfection of intertemporal markets may also justify public pension systems. Adverse selection exists, since a pension is also a kind of “survival insurance.” Indeed, the market for converting savings into lifetime annuities is far from perfect. Still, the problem of private information about one’s own life expectancy is surely less important in regard to pensions than in regard to unemployment and health risks.

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better
by Andrew Palmer
Published 13 Apr 2015

It was perfectly permissible in those days for people to buy annuities on the lives of third parties, so the obvious thing to do was buy annuities on the lives of children who had gotten through the dangerous years of infancy but were still very young and had many more years of payments ahead of them. The amount of money that the French state was paying out on nominees aged between five and fifteen far exceeded the payments for any other age. The tendency for a product or market to attract higher-risk customers is known as “adverse selection,” and on this occasion adverse selection was working to the detriment of the French. The ideal annuitants would have been those with the fewest years left on the planet; instead, the French were committed to doling out money to those with the longest to live. The ones who moved most aggressively to take advantage of this opportunity were bankers from Geneva.

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The information asymmetry that all markets must grapple with is particularly great when it comes to investing in people: no investor can hope to understand the aspirations, integrity, and self-discipline of a young person like the young person himself. With a traditional loan, the asymmetry still exists, but the obligation to repay at least offers greater protection to the interests of the investor. Information asymmetry goes hand in hand with a problem known as “adverse selection.” Imagine that the year is 2003, and an investor decides to put her money into a promising young Harvard undergraduate named Mark Zuckerberg. As the years roll on, it becomes clear that the investor has made a spectacularly good decision: Zuckerberg’s social-networking site, Facebook, is steaming toward a public listing, and a small share of his annual income is still a big amount of money.

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His logic is that wages are a much less volatile asset than they first appear. About 40 percent of start-up companies fail within three years, and that number rises to 65 percent by year ten. The chances of an individual failing to earn their expected income is lower.18 What about the issue of adverse selection? A cap on the total absolute amount of income that can be given away is one answer to the Zuckerberg problem—Upstart used to set a limit of five times the amount raised, for example. But Gu’s model was also designed to do away with this problem by enabling people with higher income potential (based on where and what they studied, for example, or how well they did in college) to raise more money for every percentage point of income shared than those with lower income potential.

High-Frequency Trading
by David Easley , Marcos López de Prado and Maureen O'Hara
Published 28 Sep 2013

The upshot of this new paradigm is clear: even if connectivity speed ceased to be a significant edge, HFT would still exist. MORE THAN SPEED Easley et al (1996) linked liquidity to informational asymmetry by identifying how market makers adjust their bid–ask spreads to the probability of informed trading (PIN). Because informed traders monetise their superior knowledge of a security’s future price by adversely selecting uninformed traders, market makers must update their quoted levels and sizes in real time in a manner that reflects their estimate of PIN. HF traders react to information leaked by LF traders in order to anticipate their actions. Direct market access (DMA) allows the deployment of this kind of strategic sequential trading logic to market venues. 7 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 8 — #28 i i HIGH-FREQUENCY TRADING To be clear, strategic sequential trading is not particular to HFT.

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New algorithms by the more sophisticated brokers use volume patterns, dark executions and the like to reduce their trading footprint (see Easley et al (2013) for an example). Choice #5: trade in exchanges that incorporate technology to monitor order flow toxicity Toxic order flow disrupts the liquidity provision process by adversely selecting market makers. An exchange that prevents such disruptions will attract further liquidity, which in turn increases the corporate value of its products. One way to avoid disruptions is to make it harder for predators to operate in that exchange. Exchanges have been changing their trading systems to cater to HF traders (and the resulting liquidity they provide).

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Hendershott and Riordan (2011) examine the impact AT has on the market quality of NYSE listed stocks. Using a normalised measure of NYSE message traffic surrounding the NYSE’s implementation of automatic quote dissemination in 74 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 75 — #95 i i HIGH-FREQUENCY TRADING IN FX MARKETS 2003, they find AT narrows spreads, reduces adverse selection and increases the informativeness of quotes, especially for larger stocks. Hasbrouck and Saar (2012) measure HFT activity by identifying “strategic runs” of submission, cancellations and executions in the Nasdaq order book. They find that HFT improves market quality by reducing short-term volatility, spreads and depth of the order book.

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
by Irene Aldridge
Published 1 Dec 2009

Brennan and Subrahmanyam (1996) specify the following vector autoregressive (VAR) model for estimation of the information-based impact measure, λ: Vi,t = θi,0 + K
k=1 βi,k Pi,t−k + M
γi,mVi,t−m + τi,t (11.1) m=1 Pi,t = φi,0 + φi,1 sign(Pi,t ) + λi τi,t + εi,t (11.2) where Pi,t is the change in price of security i from time t − 1 to time t, Vi,t = sign(Pi,t ) · vi,t , and vi,t is the volume recorded in trading the security i from time t − 1 to time t. Brennan and Subrahmanyam (1996) propose five lags in estimation of equation (1): K = M = 5. Adverse Selection Components of the Bid-Ask Spread The adverse selection components of the bid-ask spread is attributable to Glosten and Harris (1988). The model separates the bid-ask spread into the following three components: r Adverse selection risk r Order-processing costs r Inventory risk Models in a similar spirit were proposed by Roll (1984); Stoll (1989); and George, Kaul, and Nimalendran (1991). The version of the Glosten and Harris (1988) model popularized by Huang and Stoll (1997) aggregates inventory risk and order-processing costs and is specified as follows: Pi,t = (1 − λi ) Si,t Si,t sign(Pi,t ) + λi sign(Pi,t ) · vi,t + εi,t 2 2 (11.3) where Pi,t is the change in price of security i from time t − 1 to time t, Vi,t = sign(Pi,t ) · vi,t , vi,t is the volume recorded in trading the security i 148 HIGH-FREQUENCY TRADING from time t-1 to time t, Si,t is the effective bid-ask spread as defined previously, and λi is the fraction of the traded spread due to adverse selection.

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This chapter describes information-based microstructure trading strategies. MEASURES OF ASYMMETRIC INFORMATION Asymmetric information present in the markets leads to adverse selection, or the ability of informed traders to “pick off” uninformed market participants. According to Dennis and Weston (2001) and Odders-White and Ready (2006), the following measures of asymmetric information have been proposed over the years: r r r r r Quoted bid-ask spread Effective bid-ask spread Information-based impact Adverse-selection components of the bid-ask spread Probability of informed trading Quoted Bid-Ask Spread The quoted bid-ask spread is the crudest, yet most readily observable measure of asymmetric information.

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Mende, Menkhoff, and Osler (2006) note that the process of embedding information into foreign exchange prices differs from the process of other asset classes, say equities. Traditional microstructure theory observes four components contributing to the bid-ask spread: adverse selection, inventory risk, operating costs, and occasional monopoly power. Foreign exchange literature often excludes the possibility of monopolistic pricing in the foreign exchange markets due to decentralization of competitive foreign exchange dealers. Some literature suggests that most bid-ask spreads arise as a function of adverse selection; dealers charge the bid-ask spread to neutralize the effects of losing trades in which the counterparties are better informed than the dealer himself.

The Inner Lives of Markets: How People Shape Them—And They Shape Us
by Tim Sullivan
Published 6 Jun 2016

Today, reputation scores let a buyer on eBay distinguish, to some degree, high-quality sellers from lemons, and a seller can avoid deadbeat customers by taking payment through PayPal before mailing off the goods. As Omidyar and Skoll were getting started, though, eBay transactions involved a bigger leap of faith, and it’s easy to see how adverse selection might have killed the market early on. According to Podolny, eBay’s founders took it as a testament to the fundamental goodness of human nature that eBay survived: buyers and sellers didn’t cheat their customers despite the economic benefits of doing so. But consumers’ failure to grasp the nuances of adverse selection may have been crucial to generating the volume of traffic required to get the site off the ground. If they’d thought hard about the lemons problem, maybe they would have found their collectibles or Tiffany earrings somewhere else.

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(It wasn’t Akerlof’s last word on why the labor market falls so far short of the Arrow-Debreu ideal, but it was at least a model that he found to be a lot more satisfying than anything that preceded it.). Even if the market for unemployed workers doesn’t quite collapse under the weight of “adverse selection” (the absence of higher-quality items from the market because their owners keep them), it’s possible to see the connection between the markets for used cars and “used” workers: if a job applicant’s previous employer didn’t want to keep him on the payroll, it’s worth asking why not. You can also imagine that the problem deepens the longer you’ve been out of work: Why on earth hasn’t she found someone willing to give her a job, and what are other prospective employers seeing that I don’t?

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(The paper’s main insight is, in a sense, a warning for all businesses where information is of paramount importance: when the seller knows more about the quality of her wares than the buyer does, the market is prone to collapse.) And all this can be traced back, in some small way, to young George Akerlof choosing to sit in on a topology class his first year at Harvard. Adverse Selection on eBay Despite his early doubts, Jeff Skoll did ultimately end up running eBay, which (along with other e-tailers like Amazon) has succeeded in selling on the internet only because of the enormous resources it devotes to keeping customers from getting screwed.8 As one eBay economist put it to us, in academic parlance, “Our job is to reduce asymmetric information on eBay.”

Other People's Money: Masters of the Universe or Servants of the People?
by John Kay
Published 2 Sep 2015

Market institutions cannot manage these risks, except at the margin. The reasons come under the headings of asymmetric information, adverse selection and moral hazard. You cannot insure against divorce because couples know more about the state of their relationship than any insurer. Happily married couples will not seek divorce insurance: the unhappily married will. The premiums will reflect this dichotomy, with the result that such insurance will seem attractive only to those whose marriage is already on the rocks. Asymmetry of information and adverse selection are so pervasive that no divorce insurance market can exist. And since fear of the financial consequences of separation is one of the factors that keep unhappy couples together, the incidence of divorce would rise if such insurance existed.

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Roosevelt, US presidential campaign address, Chicago, 14 October 1936 Contents Prologue: The parable of the ox Introduction: Far too much of a good thing PART I: FINANCIALISATION 1 History The road to Pottersville The rise of the trader New markets, new businesses From crisis to crisis The robber barons We are the 1 per cent 2 Risk Cows, coffee and credit default swaps Chasing the dream Adverse selection and moral hazard 3 Intermediation The role of the middleman Liquidity Diversification Leverage 4 Profits Smarter people Competition The Edge Regulatory arbitrage I’ll be gone, you’ll be gone How profitable is the finance sector? PART II: THE FUNCTIONS OF FINANCE 5 Capital allocation Physical assets Housing Property and infrastructure Large companies Financing small and medium-size enterprises 6 The deposit channel Household wealth The payment system The activities of the deposit channel 7 The investment channel Stewardship A bias to action The role of the asset manager PART III: POLICY 8 Regulation The origins of financial regulation The Basel agreements Securities regulation The regulation industry What went wrong 9 Economic policy Maestro Financial markets and economic policy Pensions and inter-generational equity Consumer protection The British dilemma 10 Reform Principles of reform Robust systems and complex structures Other people’s money The reform of structure Personal responsibility 11 The future of finance Epilogue; The emperor’s guard’s new clothes Acknowledgements Notes Bibliography Index PROLOGUE The parable of the ox1 In 1906 the great statistician Francis Galton observed a competition to guess the weight of an ox at a country fair.

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And most importantly of all, to proscribe gambling with other people’s money. These key insights were discarded as financialisation exalted the role of the trader and the overseers of the financial world assured each other that activities which in reality represented irresponsible gambling constituted a new era of sophisticated risk management. Adverse selection and moral hazard Regrets, I’ve had a few But then again, too few to mention … Frank Sinatra, ‘My Way’, lyrics by Paul Anka, 1968 I wake up every single night thinking what could I have done differently. And this has been going on, what could I have done differently, certain conversations, what could I have said, what should I have done?

Naked Economics: Undressing the Dismal Science (Fully Revised and Updated)
by Charles Wheelan
Published 18 Apr 2010

Once again the pool changes and now even $1,800 does not cover the cost of insuring the men who sign up for the program. In theory, this adverse selection could go on until the market for health insurance fails entirely. That does not actually happen. Insurance companies usually insure large groups whose individuals are not allowed to select in or out. If Aetna writes policies for all General Motors employees, for example, then there will be no adverse selection. The policy comes with the job, and all workers, healthy and unhealthy, are covered. They have no choice. Aetna can calculate the average cost of care for this large pool of men and women and then charge a premium sufficient to make a profit.

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Why do we stop at McDonald’s along a highway even though many other establishments may make better hamburgers? Why do so many people apply to “prestige” colleges even though many other institutions offer just as good an education at far lower prices? Have you ever wondered what such common terms as “adverse selection,” “public goods,” and “the prisoner’s dilemma” have to do with everyday life? These are among the subjects treated in this delightful book. It’s often said that if you ask ten economists the same question you will get ten different answers. But I’ll wager that if you asked ten economists why there is a shortage of cabs and apartments in New York City, all ten would tell you that limitations on the number of taxi medallions and rent control are what restrict the supply of these goods and services.

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Instead, salaries in nearly every public school district in the country are determined by a rigid formula based on experience and years of schooling, factors that researchers have found to be generally unrelated to performance in the classroom. This uniform pay scale creates a set of incentives that economists refer to as adverse selection. Since the most talented teachers are also likely to be good at other professions, they have a strong incentive to leave education for jobs in which pay is more closely linked to productivity. For the least talented, the incentives are just the opposite. The theory is interesting; the data are amazing.

The Best Way to Rob a Bank Is to Own One: How Corporate Executives and Politicians Looted the S&L Industry
by William K. Black
Published 31 Mar 2005

The control frauds had an elegant means of finding bad real estate developers. They maximized “adverse selection.” Economists first identified adverse selection in the insurance context. A company offering insurance against lung cancer faces the risk that the people most likely to buy coverage are the ones most likely to develop lung cancer. Insurance theory and practice have developed means of reducing adverse selection. Control frauds took the opposite steps. The best way to reduce adverse selection in lending is to ensure that the borrower will suffer financially should the loan default and to conduct superior underwriting of the borrower and the real estate project pledged as security for the loan.

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This maximized the fraudulent S&Ls’ leverage over them.7 Everyone agrees that underwriting by the S&L high fliers was pervasively horrific (Patriarca 1987, 3–5; GAO Thrift Failures 1989, 31–38). They frequently made massive ADC loans to individuals without conducting credit checks or appraising the value of the real estate. This maximized adverse selection (and losses). It was a perversely rational practice for a control fraud precisely because it maximized adverse selection. Moreover, if the initial appraisal would have shown a large loss (or the credit check would have shown the developer to be uncredit-worthy), it was better to make the loan without the damning appraisal or credit check in the file, where the Bank Board examiners could find it and use it to prove that the loans were unsafe and unsound.

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The pattern of failures shows that the high fliers were control frauds. They invariably reported high initial profits, and they all failed. Honest gambling cannot explain any aspect of the pattern (Black, Calavita, and Pontell 1995). Finally, the high fliers invested in a manner (particularly by embracing adverse selection and consistently underwriting incompetently) that would have been irrational for honest gamblers (ibid.). THE MANY FRONTS IN GRAY’S WAR AGAINST THE CONTROL FRAUDS The great controversies during the S&L debacle almost universally involved control frauds. There was no real controversy about how to deal with the 1979–1982 crisis in interest-rate risk.

Economists and the Powerful
by Norbert Haring , Norbert H. Ring and Niall Douglas
Published 30 Sep 2012

They consider it as a breach of trust if a firm wants to cut pay simply because a larger pool of job seekers allows them to (Fehr, Goette and Zehnder 2009). Campbell and Kamlani (1997) conducted a survey of 184 firms to investigate the reasons for downward wage rigidity. The strongest explanation, according to the answers of the managers, lies in the negative effect of wage cuts on effort and in adverse selection in talent retention. Adverse selection here means that the companies are concerned that the best employees will leave if they cut wages. Bewley (1995) summarizes the answers he received in many interviews with highranking personnel managers: “Workers have many opportunities to take advantage of employers so that it is not wise to depend on coercion and financial incentives alone as motivators… Employers believe that other motivators are necessary, which are best thought of as having to do with generosity.”

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If they mandate minimum standards for issues sensitive to adverse selection or signaling problems, they can prevent a race towards the bottom (Kaufman 2009). Alternatively, unions can negotiate such issues for large groups of workers. A union, which negotiates minimum leave times, can truthfully represent their constituencies’ average preferences. If the union negotiates with individual employers, this can take care of the signaling problem. If they negotiate with an employer organization over standards for the whole industry, this will also take care of the adverse selection problem for companies who are willing to satisfy union demands.

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Indeed, just being denied a loan in itself can damage a person’s centralized credit rating according to any of the “Big Three” international centralized credit bureaus (Experian, Equifax and TransUnion/Callcredit), as can applying for more than one new credit source in “too short” a time period. The main reason that the credit market does not clear is the potential for adverse selection. Ideally, banks charge a low interest rate for loans to finance low-risk projects and a high interest rate to finance high-risk projects. If they could reliably tell them apart, they would finance every project at an interest rate commensurate with the risk. However, the bankers can only make an educated guess about the riskiness of a project and the trustworthiness of a borrower.

Capitalism, Alone: The Future of the System That Rules the World
by Branko Milanovic
Published 23 Sep 2019

The reverse, as we saw, holds for pessimistic or low-skilled migrants who expect to be placed low in the recipient country’s distribution: they will tend to choose more equal countries. For that reason, there may be adverse selection of pessimistic migrants moving to countries with more developed social safety nets. If more pessimistic migrants are indeed also effectively less ambitious or less skilled, rich countries with extensive social welfare systems will tend to attract the “wrong” kinds of migrants.47 The existence of such an adverse selection dynamic is documented by Akcigit, Baslandze, and Stantcheva (2015), who show that inventors (who may be supposed to be highly skilled or highly ambitious) tend to migrate from high-tax to low-tax jurisdictions, that is, to places with a less-developed welfare state.

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At the same time, the failure to be accepted as an equal member of the community will be seen by the migrants as confirmation of natives’ anti-migrant prejudices, or, even worse, as religious or ethnic discrimination. Thus, large welfare states face two types of adverse selection, which are mutually reinforcing. On the domestic side, polarization between the poor and the rich encourages the private provision of social services and leads the rich to opt out of government-provided services. This leaves in the system only those whose premiums may be unaffordably high, and many of them may leave the system altogether. On the international side, adverse selection works by bringing in low-skilled migrants—a process that leads to the opting out of the native-born.

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It is no accident that the prototypical welfare state, born in the homogeneous world of 1930s Sweden, had many elements of national socialism (not used here in a pejorative sense). In addition to depending on common behavior and experiences, the welfare state, in order to be sustainable, requires mass participation. Social insurance cannot be applied to only small parts of the workforce because it then naturally leads to adverse selection, a point well illustrated by the endless wrangles over health care coverage in the United States. If it is possible to opt out, anyone who thinks they may not require the insurance (for example, the rich, those unlikely to be unemployed, or healthy people) will do so, since they do not want to subsidize the “others.”

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation
by Richard Bookstaber
Published 5 Apr 2007

The person on the other side of the trade might have insider information on the company, or he might know that there is a much larger overhang of potential selling, the demand the buyer sees being a first trickle in what will emerge as a flood of selling. Even beyond the problem of adverse selection, if somebody waves a white flag and tries to overcome the adverse selection bias by announcing who they are—confirming to everyone’s satisfaction that they are trading strictly because of a liquidity need and have no special information or view of the market and are willing to discount the price an extra point to get someone to take the position off their hands—the trader who buys the position still faces a risk because there is no guarantee the price will not fall further between the time the trader takes on the position and the time he seeks to resell it.

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The discrepancy could be caused by information or even manipulation. This possibility leads to uncertainty about the quality of the security, will lead prices to move further than they would otherwise, and will also make the market less liquid. Both stat arb traders and market makers share a problem called adverse selection. They don’t know what they don’t know, which is easily described in the context of used cars. When you’re buying a new car it is difficult to know its relative quality, but once you’ve driven it for a while you can assess if it is a good car or a lemon. You now have information that no one else does.

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Even beyond the problem of adverse selection, if somebody waves a white flag and tries to overcome the adverse selection bias by announcing who they are—confirming to everyone’s satisfaction that they are trading strictly because of a liquidity need and have no special information or view of the market and are willing to discount the price an extra point to get someone to take the position off their hands—the trader who buys the position still faces a risk because there is no guarantee the price will not fall further between the time the trader takes on the position and the time he seeks to resell it. There may be many other liquidity-driven sellers behind this sale, or there may be a surprise economic announcement that affects the market. The adverse selection problem is especially troublesome for market makers, and particularly for market makers in specialized arenas, such as corporate bonds, mortgage securities, and emerging markets. Their longterm business depends on standing ready to meet transaction demand. A bank’s emerging market trading desk might like nothing better than to duck for cover when a crisis occurs, but it has to be ready to make trades regardless of the situation.

The Healing of America: A Global Quest for Better, Cheaper, and Fairer Health Care
by T. R. Reid
Published 15 Aug 2009

The American insurers point out—and they’re right—that they have to pick and choose their customers to avoid a problem known as “adverse selection.” That term refers to people who refuse to buy health insurance when they’re healthy but go shopping for a plan after they’ve been diagnosed with a serious disease. If an insurance company had to sell coverage to all those people, it would quickly face claims in excess of the premiums it took in. The solution to adverse selection is to mandate that everybody pay for health insurance, through either a private company or a government program. That requirement is known as the “individual mandate,” and it is a necessary corollary to “guaranteed issue.”

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-style, profit-making health insurance, but the Swiss dropped that system on the theory that health insurance has to be nonprofit in order to do its job. Switzerland still has private health insurance companies; but the firms can’t make a profit on the basic coverage package, and they have to cover everybody, regardless of “adverse selection” concerns.13 The second major anomaly of the U.S. system—the flaw that forces us to spend more than any other country on health—is sheer complexity. We have developed, more or less by accident, the most fragmented health care system in the developed world, with “providers” sending bills to a vast array of different payers.

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Honda Hong Kong Hôpital Saint-Louis Hospital Corporation of America hospitals “dumping” of uninsured by emergency rooms in privately owned as run by charities see also specific hospitals House of Commons, British Hsiao,William hypertension Ikegami Naoki Index of Quality Indicators India Indian Health Service, U.S. infant mortality Institute of Medicine insurance, health administrative costs in adverse selection in Americans lacking in choice in claims denied by Clinton administration’s proposed reform of co-payments in deductibles in French government-run individual mandate and marketing of “medical loss” in “Medi-gap” insurance nonprofit preexisting conditions and denial of premiums for private profits in as provided by employers rescission in insurance, malpractice Israel Italy, health care in IUDs Iwasaki Yataro Japan, health care in as based on Bismarck Model cost of fees and co-pays in German health care vs.

Super Thinking: The Big Book of Mental Models
by Gabriel Weinberg and Lauren McCann
Published 17 Jun 2019

This is often the case with insurance products, where the person or company applying for insurance usually knows more about their own risk profile than the insurance company does. When parties select transactions that they think will benefit them, based at least partially on their own private information, that’s called adverse selection. People who know they are going to need dental work are more likely to seek out dental insurance. This unfortunately drives up the price for everyone. Two ways to mitigate adverse selection in the insurance market are to mandate participation, as many localities do for car insurance, and to distinguish subpopulations based on their risk profiles, as life insurers do for smokers. Like crossing a herd immunity threshold, rampant and persistent asymmetric information in a market can lead to its collapse.

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Sellers who know their cars are peaches, however, will not want to sell them in this market because they know their cars are worth more than the average price. As they pull their peaches out of the market, the average quality drops and, in turn, the price of the used cars left in the market keeps dropping. The sellers of lemons free-ride on the market until it collapses into just a market of lemons. Adverse selection was an early concern with the state health insurance exchanges as part of the Affordable Care Act (ACA) in the United States. Extending the metaphor, the lemons are sick people applying to the exchanges, and the peaches are healthy people applying. There was an individual mandate requiring health insurance, but the penalties for not complying were low, so the concern was that many healthy people would just opt to pay the fine rather than participate.

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This would, in turn, eject from the market more healthy participants not willing to pay these higher premiums, further raising prices. This situation is still unfolding, with those invested in the success of the ACA trying to ensure that it doesn’t spiral out of control. The “Death Spiral” of Adverse Selection Sometimes there are ways to break the cycle. In the case of the used car market, services like Carfax try to restore symmetric information. This arrangement allows buyers to distinguish between lemons and peaches, and it eventually pushes lemons out of the market. In contrast, one of the goals of the ACA was to make sure that people with preexisting conditions were not pushed out of the market.

Broken Markets: How High Frequency Trading and Predatory Practices on Wall Street Are Destroying Investor Confidence and Your Portfolio
by Sal Arnuk and Joseph Saluzzi
Published 21 May 2012

A Guide to Preventing Information Leakage”5 and its 2009 report “Understanding and Avoiding Adverse Selection in Dark Pools.”6 The reports break down the dark pool industry into five groups: • Public crossing networks, such as Instinet, Liquidnet, and POSIT • Internalization pools, such as Goldman’s SigmaX and Credit Suisse’s Crossfinder • Ping destinations, such as dark pools operated by GETCO and Citadel (these orders do not rest in the pool but give the prop-trading owners of the pool the option to trade with you) • Exchange-based pools, such as ARCA Hidden and BATS Hidden • Consortium-based pools, such as BIDS ITG highlights how adverse selection in these pools varies greatly.

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Typically, dark pool fees are lower to attract more flow. Many dark pools, however, are filled with predatory traders, who are electronically hiding out so that they can watch for institutional algo footprints, to take advantage of these orders. See Chapter 8, “Heart of Darkness,” for more about adverse selection issues with dark pools. Institutional investors may think they are lowering their transaction costs because their brokers are supplying algos at a commission rate of a fraction of a penny per share. The real cost of a trade, however, is what you don’t see. In our Instinet days, we referred to this as the transaction iceberg.

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Nina Mehta, “Morgan Stanley Changing Dark Pool to Attract Bigger Orders” (Sept. 21, 2011), Businessweek website, http://www.businessweek.com/news/2011-09-21/morgan-stanley-changing-dark-pool-to-attract-bigger-orders.html. 5. Hitesh Mittal, “Are You Playing in a Toxic Dark Pool? A Guide to Preventing Information Leakage” (June 2008), Investment Technology Group website, http://www.itg.com/news_events/papers/ITGResearch_Toxic_Dark_Pool_070208.pdf. 6. Nigam Saralya and Hitesh Mittal, “Understanding and Avoiding Adverse Selection in Dark Pools” (Nov. 2009), Investment Technology Group website, http://www.itg.com/news_events/papers/AdverseSelectionDarkPools_113009F.pdf. 7. Dennis Dick, “Undisplayed Trading Centers Compromising the NBBO” (April 8, 2010), Zero Hedge website, http://www.zerohedge.com/sites/default/files/SubPennying%20Summary%20Prez.pdf. 8.

The Economics Anti-Textbook: A Critical Thinker's Guide to Microeconomics
by Rod Hill and Anthony Myatt
Published 15 Mar 2010

Second, it contributes to ‘moral hazard’, where incentives are changed by certain kinds of contracts. (For example, individuals may have less incentive to prevent fires after buying fire insurance, and asymmetric information means that we can’t easily monitor this changed behaviour.) Third, it contributes to ‘adverse selection’, where particular contracts disproportionately attract undesirable customers. Competitive markets cannot function efficiently when these problems are present: government regulation may be required. Prasch believes the failure to distinguish between inspection-goods and experience-goods, or between spot markets and relational contracts, explains the ‘largely fatuous’ dichotomy between government regulation and the free market that has become a staple of American political discourse.

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Akerlof and Shiller say (2009: 173): 244 While endorsing the importance of animal spirits and limited rationality, we do not agree with Akerlof and Shiller that if individuals were rational and had only economic motives then there would be little role for the government in regulating financial markets. Problems of imperfect and asymmetric information are pervasive and are particularly important in financial markets. They give rise to principal-agent problems, moral hazard problems and adverse selection. This suggests a key role for the government in regulating many markets, in­ cluding financial markets. The goals of equity and efficiency Textbooks emphasize the importance of efficiency and downplay the importance of equity. In textbook treatments, the equity goal is always subservient to the efficiency goal.

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Nor can depositors and shareholders know everything about the solvency and risk profile of any given bank; nor (it turns out) can borrowers know everything about how honestly the terms, conditions and fees associated with loans may be presented. We noted in Chapter 6 that asymmetric information gives rise to a cluster of well-known problems: the principal-agent problem, the moral hazard problem and the adverse selection problem. Competitive markets cannot function effi­ ciently when these problems are present: government regulation is required. So, how do these problems manifest themselves in credit markets? 256 The role of externalities The temptation of high returns might lull a bank into ignoring the increasing riskiness of loans as interest rates rise.

The Undercover Economist: Exposing Why the Rich Are Rich, the Poor Are Poor, and Why You Can Never Buy a Decent Used Car
by Tim Harford
Published 15 Mar 2006

Nevertheless, it is striking that partial coverage, inefficiency, and high costs are not only the defining characteristics of private health insurance, they are also exactly what we would have predicted armed only with the theoretical models of Akerlof, Spence, and Stiglitz. Imperfect information— the whole story The lemons problem (“adverse selection” in the economists’ jargon), when inside information guts a market because ignorant buyers are unwilling to pay for quality they cannot observe, is one example of the broader problem of inside information (“asymmetric information” in the jargon). Inside information also produces an obstacle called “moral hazard.”

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Because the government cannot monitor people’s job searches perfectly, it pays out only meager unemployment benefits. Yet if the government could really tell how hard unem- • 124 • T H E I N S I D E S T O R Y ployed people were looking for jobs, then it would be possible to pay more generous benefits to genuinely deserving recipients. The problems of imperfect information include adverse selection (lemons) and moral hazard, but there are other, broader, and vaguer issues. For example, my boss would like to pay me extra if I try harder to do a good job, but because he has only a vague idea how hard I am trying, my performance bonus is only a small part of my salary. If my boss could observe my skill and effort perfectly, he could make my entire salary performance-related.

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The savings are no problem either: simply reduce each person’s tax bill by, • 132 • T H E I N S I D E S T O R Y say $1,500 a year—this is very roughly the cost, in taxes, of both the UK and the US public health systems—and make them put the money in a savings account. For people who pay less than $1,500 in tax a year, the government would contribute money to make up the shortfall. Since the system is compulsory, no adverse selection takes place. If you participated in such a program, how would it work for you? Your health-care savings would automatically go into a high-interest bank account. They would build up gradually throughout your life. For most people, medical bills are low in their younger years. So you could expect to have thirty thousand dollars in your account when you turn forty; more, if you’ve managed to keep your spending low and watched the money earn interest.

Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty
by Abhijit Banerjee and Esther Duflo
Published 25 Apr 2011

It seems that everything pushes in the same direction: Patients want to see action, so they tend to prefer doctors who are prescription happy, and the doctors often make more money if they prescribe more. Offering reimbursement-based health insurance for outpatient care in a country where health care is at best weakly regulated, and where anybody can set up shop as a “doctor,” seems like the first step toward bankruptcy. Another issue is “adverse selection.” If insurance is not mandatory, those who know that they are likely to have a problem in the future may be more likely to get insurance. This would be fine as long as the insurer also knows that, because it could be factored into the premium. But if the insurance company is unable to identify those who are joining because they want care now, all they can do is raise the premium on everyone.

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Nobody wants to have surgery or chemotherapy just for the heck of it, and the treatment is easily verified. The danger of overtreatment remains, but the insurer can cap what it will pay for each treatment. The big issue that remains is selection: The insurance company does not want only sick people signing up. To avoid adverse selection, the trick is to start from a large pool of people who came together for some other reason than health—employees of a large firm, microcredit clients, card-carrying Communists . . . and try to insure all of them. This is why many microfinance institutions (MFIs) thought of offering health insurance.

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Moreover, it would be easy to collect premiums from the clients, since loan officers already meet with them every week—in effect, they could just fold the premium into the loan. In 2007, SKS Microfinance, then the largest microfinance institution in India, introduced “Swayam Shakti,” a pilot health-insurance program offering maternity, hospitalization, and accident benefits. It was made mandatory for the groups to which it was offered to avoid adverse selection. To deal with the potential for fraud, benefits were capped and clients were strongly encouraged to use those hospitals with which SKS had a long-term networking arrangement. To sweeten the deal, clients who went to these hospitals were offered a “cashless facility”: They would not need to pay anything as long as their treatment was for a covered illness—SKS would pay the hospitals directly.

Modernising Money: Why Our Monetary System Is Broken and How It Can Be Fixed
by Andrew Jackson (economist) and Ben Dyson (economist)
Published 15 Nov 2012

First: “among those who are most likely to bid high interest rates are risk lovers (who are willing to undertake very risky projects, with a small probability of success, but high returns if successful); optimists (who overestimate the probability of projects succeeding and the return if successful); and crooks (who, because they do not plan to pay back the money anyway, are virtually indifferent to the interest rate which they promise). “As a consequence, as the bank raises the rate of interest, there is an adverse selection effect; the mix of loan applicants changes adversely, so much so that the expected return from those receiving loans may actually decrease as the interest rate charged increased.” The problem of adverse selection has long been known – Adam Smith noted in the Wealth of Nations that when interest rates are high the only people wishing to borrow would be “prodigals and projectors”: “Sober people, who will give for the use of money no more than a part of what they are likely to make by the use of it, would not venture into the competition.

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What effect dominates will be hard to say - all that can be said with certainty is the wealth and imperfect information channels of monetary policy (as outlined above) are difficult to predict. 12. In addition, in their model banks cannot overcome the problem of imperfect information by increasing their collateral requirements on borrowers, due to adverse selection issues. 13. The NINJA mortgages made in the run up to the financial crisis are an example of such lending in action (so called because they were made to individuals with No Income, No Job or Assets, who were unlikely to be able to repay). 14. ‘Business services’ account for a tiny proportion of this 15% figure. 15.

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However, increases in wealth may also increase the total amount of credit available to individuals (this is known as the financial accelerator; see Box 4.D for more details). To briefly sum up, because of asymmetric information between borrowers and lenders, financial markets suffer from moral hazard and adverse selection problems. As such lending to households is largely determined by the amount of collateral they can offer – increases in the price of housing (which can be used as collateral) increase the quantity of credit available and decrease its price (Goodhart & Hofmann, 2007).6 Furthermore, to the extent that a bank’s loans are secured on property, increases in house prices may lower the amount of capital banks feel it is prudential to hold against these types of loans, and so increase their lending capacity.

The Great Reversal: How America Gave Up on Free Markets
by Thomas Philippon
Published 29 Oct 2019

It is a complex and controversial idea, and its definition differs across jurisdictions. US regulators prefer to talk about monopolization. adverse selection: A situation in which some market participants take advantage of private information that other participants do not have. The information can be about the true quality of a good (such as used cars), the true risk of an activity, or the true value of an asset. For instance, informed traders will try to sell their shares when they learn before anyone else that a company is in trouble. Markets can collapse when adverse selection is strong because everyone mistrusts the trading motives of everyone else. anti-steering: A contractual arrangement that prevents firms from directing their clients toward some products.

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In addition, these loans are fundamentally risky: good borrowers can be unlucky and lose their jobs or their customers, and bad borrowers can pretend to be good. Savers, on the other hand, want less risk and more liquidity. They don’t want to buy rotten eggs, they don’t want to put all their eggs in the same basket, and they want to be able to sell their eggs if they need to. These issues have names in economics: rotten eggs are moral hazard and adverse selection; placing one’s eggs in different baskets is called diversification; eggs that can be sold are called liquid assets. The trouble—and the opportunity for financiers—is that borrowers and savers have conflicting demands. This creates the need for financial intermediaries. Without intermediaries, information costs would make it difficult for households to screen and monitor corporations and for corporations to pool household funds to raise sufficient capital.

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The US government insures trillions of dollars of mortgages via inefficient and badly run companies (Fannie Mae, Freddie Mac). Now ask yourself: which market is more likely to experience market failures that justify government involvement? Health care or mortgages? Yes, this is almost a rhetorical question because the answer is obvious. The health-care market is “Exhibit A” for externalities, adverse selection, and market failures. This should be obvious to everyone. In fact, it is obvious to everyone outside the US, and that is why all governments around the world are involved in some way in health care. On the other hand, most countries have a private mortgage market. Denmark has a liquid, efficient private mortgage market, and a state-run, efficient health-care system, not the other way around.

India's Long Road
by Vijay Joshi
Published 21 Feb 2017

There is also a more general ‘efficiency’ case for state intervention for the following reason. The combination of the uncertain need for care, and its high expense, makes major health events natural candidates for risk-​sharing via health insurance. But unregulated markets in health insurance are notoriously subject to market failure. One of the causes is so-​called ‘adverse selection’. There is a tendency for unhealthy people to demand more health insurance relative to healthy people, which bids up the average premium. This reinforces the tendency for less healthy people to stay in the market and healthier people to quit, which pushes up the insurance premium still further, and so on, in a vicious cycle that can, in the extreme, cause the market to break down altogether.

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This reinforces the tendency for less healthy people to stay in the market and healthier people to quit, which pushes up the insurance premium still further, and so on, in a vicious cycle that can, in the extreme, cause the market to break down altogether. Insurance companies tend to respond to this by excluding people with a prior history of health trouble or excluding certain services from coverage, with the consequence that many people are left uncovered by health insurance. In the presence of ‘adverse selection’, the government can improve overall welfare by universal compulsory health insurance. (Equity considerations can be handled by state subsidies to pay the insurance premiums of poor people.) Another cause of the failure of insurance markets is ‘moral hazard’, the tendency of insurance to change the behaviour of the insured in ways that are hard to monitor.

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(However, the incidence of this problem can be exaggerated in the field of secondary care since many of the conditions that are insured against are unpleasant enough to offset the moral hazard effect.) More importantly, since insurance is paid by a third party, there is a tendency for patients to demand, and health providers to supply, unnecessary care and more expensive care, which leads to cost and price escalation. Moral hazard cannot be addressed by state intervention. But adverse selection constitutes by itself a sufficient ground for the state to step in and regulate the insurance market. Countries differ in their response to market failures in health care. The UK and Southern European countries have mostly chosen to deliver health services through a national health service. This is, in effect, a combination of in-​kind universal state insurance with state provision of care; private health insurance and provision are only voluntary add-​ons.

Corporate Warriors: The Rise of the Privatized Military Industry
by Peter Warren Singer
Published 1 Jan 2003

Or even their customers, who bought their gas that helped pay for the firm that directed the killings? Obviously, although it is murky exactly where the lines of responsibility stop, it is very clear that privatizing security actions only complicates the issue. ADVERSE SELECTION, PMF-STYLE The next moral area of concern is that of adverse selection. Although certain military firms may strive toward respectability, the very nature of provider sector activity also means that there may be a mechanism that draws in disreputable players looking for the cover of legitimacy. Specifically, the privatized military industry provides an employment opportunity for those previously drawn toward mercenary work or who have been forced out of public military activities for past misdeeds.2** On the executive side, it should not be reassuring that many of the major actors in the Iran-Contra and BCCI scandals are now associated with the 222 IMPLICATIONS industry.20 On the employee side, firms are not always looking for the most congenial workforce, but instead recruit those operators known for their effectiveness.

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In the past, these individuals acted without concern for human rights and certainly could do so again. Doug Brooks, a leading industry proponent who heads a PMF lobby group, puts it even more bluntly. The firm's best employees are often ". . . not nice guys. You wouldn't want them to marry your sister."27 This issue of adverse selection becomes particularly worrisome when placed in the context of the industry, with its layers of moral hazard and diffused responsibilities. Thus, even if PMFs are scrupulous in screening out their hires for human rights violations (which is difficult for a firm to accomplish, given that most of its prospective employee's resumes do not have an "atrocities committed" section), it is still difficult for them to monitor their troops in the field completely.

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When their private commercial aspirations are aligned with the public interest, they hold the capacity for better moral outcomes than what would occur otherwise. The issue is not so simple, however. The firms are not altruistic by any measure. When the means of security are privatized, certain mechanisms of moral hazard and adverse selection might lead firms astray. Just as in the rest of commerce, war is business where nice firms do not always finish first. Aspirations of corporate responsibility and a positive public image may be overridden bv the need to fulfill a contract or be seen as an effective firm 'that gets things done.'

Radical Uncertainty: Decision-Making for an Unknowable Future
by Mervyn King and John Kay
Published 5 Mar 2020

That leads owners of better-quality cars to drop out of the market, and only cars of even lower quality are on sale, a process known as adverse selection. As this process continues, the market may collapse altogether. The difference in information between buyers and sellers means that no price can bring about a balance between supply and demand. Adverse selection may arise in many markets. Health insurance depends on pooling risks, but the healthy will seek to drop out and the less healthy will be anxious to obtain coverage. In practice, health insurance works well only when there is some compulsion to join. Like many good ideas, the problem of adverse selection may seem obvious when explained but the idea has proved immensely helpful in understanding a range of markets, and explaining why some of these markets do not function well.

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Young men with sports cars will pay much higher premiums than elderly ladies with decades of unblemished motoring records. But within each class of risk, the question of which young men and which elderly ladies experience accidents is unknown. And this information is not known either by the insured or the insurer, otherwise the problem of adverse selection – only higher-risk individuals would seek insurance and only lower-risk individuals would be offered it – would prevent the emergence of an insurance market. Insurance is possible only when ignorance of specific future outcomes is considerable, and that ignorance is common to both insurer and insured.

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INDEX 10 (film, 1979), 97 737 Max aircraft, 228 9/11 terror attacks, 7 , 74–6 , 202 , 230 Abbottabad raid (2011), 9–10 , 20 , 26 , 44 , 71 , 102 , 118–19 , 120 , 174–5 ; reference narrative of, 122–3 , 277 , 298 ; role of luck in, 262–3 ; and unhelpful probabilities, 8–19 , 326 abductive reasoning, 138 , 147 , 211 , 388 , 398 ABN AMRO, 257 Abraham (biblical character), 206 Abrahams, Harold, 273 Abramovich, Roman, 265 accountancy, 409 aeronautics, 227–8 , 352–6 , 383 Agdestein, Simen, 273 AIDS, 57 , 230 , 375–6 Airbus A380, 40 , 274–6 , 408 Akerlof, George, 250–1 , 252 , 253 , 254 , 382 Alchian, Armen, 158 alien invasion narratives, 295–6 Allais, Maurice, 134–5 , 136 , 137 , 437 , 440–3 Allen, Bill, 227–8 Allen, Paul, 28 , 29 Altair desktop, 28 Amazon, 289 , 309 Anderson, Roy, 375 ant colonies, 173 anthropology, 160 , 189–91 , 193–4 , 215–16 antibiotics, 40 , 45 , 284 , 429 Antz (film, 1998), 274 apocalyptic narratives, 331–2 , 335 , 358–62 Appiah, Anthony, 117–18 Apple, 29–30 , 31 , 169 , 309 Applegarth, Adam, 311 arbitrage, 308 Archilochus (Greek poet), 222 Aristotle, 137 , 147 , 303 Arrow, Kenneth, 254 , 343–5 , 440 artificial intelligence (AI), xvi , 39 , 135 , 150 , 173–4 , 175–6 , 185–6 , 387 ; the ‘singularity’, 176–7 Ashtabula rail bridge disaster (1876), 33 Asimov, Isaac, 303 asteroid strikes, 32 , 71–2 , 238 , 402 astrology, 394 astronomical laws, 18–19 , 35 , 70 , 373–4 , 388 , 389 , 391–2 , 394 AT&T, 28 auction theory, 255–7 Austen, Jane, 217 , 224–5 , 383 autism, 394 , 411 aviation, commercial, 23–4 , 40 , 227–8 , 274–6 , 315 , 383 , 414 axiomatic rationality: Allais disputes theory, 134–5 , 136 , 137 ; Arrow– Debreu world, 343–5 ; assumption of transitivity, 437 ; and Becker, 114 , 381–2 ; and behavioural economics, 116 , 135–6 , 141–9 , 154–5 , 167–8 , 386–7 , 401 ; capital asset pricing model (CAPM), 307–8 , 309 , 320 , 332 ; completeness axiom, 437–8 ; consistency of choice axiom, 108–9 , 110–11 ; continuity axiom, 438–40 ; definition of rationality, 133–4 , 137 , 436 ; definition of risk, 305 , 307 , 334 , 420–1 ; efficient market hypothesis, 252 , 254 , 308–9 , 318 , 320 , 332 , 336–7 ; efficient portfolio model, 307–8 , 309 , 318 , 320 , 332–4 , 366 ; and evolutionary rationality, 16 , 152–3 , 154–5 , 157 , 158 , 166–7 , 171–2 , 386–7 , 407 ; and ‘expectations’ concept, 97–8 , 102–3 , 121–2 , 341–2 ; extended to decision-making under uncertainty, xv , 40–2 , 110–14 , 133–7 , 257–9 , 420–1 ; and Friedman, 73–4 , 111–12 , 113–14 , 125 , 257–9 , 307 , 399–400 , 420 , 437 ; hegemony of over radical uncertainty, 40–2 , 110–14 ; implausibility of assumptions, xiv–xv , 16 , 41–4 , 47 , 74–84 , 85–105 , 107–9 , 111 , 116–22 , 344–9 , 435–44 ; independence axiom, 440–4 ; as limited to small worlds, 170 , 309–10 , 320–1 , 342–9 , 382 , 400 , 421 ; and Lucas, 36 , 92 , 93 , 338–9 , 341 , 345 , 346 ; and Markowitz, 307 , 308 , 309–10 , 318 , 322 , 333 ; maximising behaviour, 310 ; ‘pignistic probability’, 78–84 , 438 ; and Popperian falsificationism, 259–60 ; Prescott’s comparison with engineering, 352–6 ; ‘rational expectations theory, 342–5 , 346–50 ; and Samuelson, xv , 42 , 110–11 , 436 ; and Savage, 111–14 , 125 , 257–9 , 309 , 345 , 400 , 435 , 437 , 442–3 ; shocks and shifts discourse, 42 , 346 , 347 , 348 , 406–7 ; Simon’s work on, 134 , 136 , 149–53 ; triumph of probabilistic reasoning, 15–16 , 20 , 72–84 , 110–14 ; Value at risk models (VaR), 366–8 , 405 , 424 ; von Neumann–Morgenstern axioms, 111 , 133 , 435–44 ; see also maximising behaviour Ballmer, Steve, 30 , 227 Bank of England, xiii , 45 , 103–5 , 286 , 311 Barclays Bank, 257 Barings Bank, 411 Basel regulations, 310 , 311 Bay of Pigs fiasco (1961), 278–9 Bayes, Reverend Thomas, 60–3 , 66–7 , 70 , 71 , 358 , 431 Beane, Billy, 273 Bear Stearns, 158–9 Becker, Gary, 114 , 381–2 Beckham, David, 267–8 , 269 , 270 , 272–3 , 414 behavioural economics, 116 , 145–8 , 154 , 386–7 ; and Allais paradox, 442 ; ‘availability heuristic’, 144–5 ; biases in human behaviour, 16 , 136 , 141–8 , 154 , 162 , 165 , 167–8 , 170–1 , 175–6 , 184 , 401 ; and evolutionary science, 154–5 , 165 ; Kahneman’s dual systems, 170–1 , 172 , 271 ; Kahneman–Tversky experiments, 141–7 , 152 , 215 ; ‘noise’ (randomness), 175–6 ; nudge theory, 148–9 Bentham, Jeremy, 110 Berkshire Hathaway, 153 , 319 , 324 , 325–6 Berlin, Isaiah, 222 Bernoulli, Daniel, 114–16 , 199 Bernoulli, Nicolaus, 199 , 442 Bertrand, Joseph, 70 Bezos, Jeff, 289 big data, 208 , 327 , 388–90 billiard players, 257–8 bin Laden, Osama, 7 , 8–10 , 21 , 44 , 71 , 118–19 , 120 , 122–3 , 262–3 , 326 Bismarck, Otto von, 161 Bitcoin, 96 , 316 Black Death, 32 , 39–40 BlackBerry, 30 , 31 blackjack, 38 Blackstone, Sir William, 213 BNP Paribas, 5 , 6 BOAC, 23–4 Boas, Franz, 193 Boeing, 24 , 227–8 Boer War, 168 Bolt, Usain, 273 bonobos, 161–2 , 178 Borges, Jorge Luis, 391 Borodino, battle of (1812), 3–4 , 433 Bortkiewicz, Ladislaus, 235–6 Bower, Tom, 169–70 Bowral cricket team, New South Wales, 264 Box, George, 393 Boycott, Geoffrey, 264–5 Bradman, Don, 237 , 264 Brahe, Tycho, 388–9 Brånemark, Per-Ingvar, 387 , 388 Branson, Richard, 169–70 Brearley, Michael, 140–1 , 264–5 Breslau (now Wrocław), 56 Brexit referendum (June 2016), 241–2 ; lies told during, 404 bridge collapses, 33 , 341 Brownian motion, 37 Brunelleschi, Filippo, 143 , 147 Buffett, Warren, 83 , 152 , 179 , 319–20 , 324 , 335 , 336–7 Burns, Robert, 253 Bush, George W., 295 , 407 , 412 business cycles, 347 business history (academic discipline), 286 business schools, 318 business strategy: approach in 1970s, 183 ; approach in 1980s, 181–2 ; aspirations confused with, 181–2 , 183–4 ; business plans, 223–4 , 228 ; collections of capabilities, 274–7 ; and the computer industry, 27–31 ; corporate takeovers, 256–7 ; Lampert at Sears, 287–9 , 292 ; Henry Mintzberg on, 296 , 410 ; motivational proselytisation, 182–3 , 184 ; quantification mistaken for understanding, 180–1 , 183 ; and reference narratives, 286–90 , 296–7 ; risk maps, 297 ; Rumelt’s MBA classes, 10 , 178–80 ; Shell’s scenario planning, 223 , 295 ; Sloan at General Motors, 286–7 ; strategy weekends, 180–3 , 194 , 296 , 407 ; three common errors, 183–4 ; vision or mission statements, 181–2 , 184 Buxton, Jedediah, 225 Calas, Jean, 199 California, 48–9 Cambridge Growth Project, 340 Canadian fishing industry, 368–9 , 370 , 423 , 424 cancer, screening for, 66–7 Candler, Graham, 352 , 353–6 , 399 Cardiff City Football Club, 265 Carlsen, Magnus, 175 , 273 Carnegie, Andrew, 427 Carnegie Mellon University, 135 Carré, Dr Matt, 267–8 Carroll, Lewis, Through the Looking-Glass , 93–4 , 218 , 344 , 346 ; ‘Jabberwocky’, 91–2 , 94 , 217 Carron works (near Falkirk), 253 Carter, Jimmy, 8 , 119 , 120 , 123 , 262–3 cartography, 391 Casio, 27 , 31 Castro, Fidel, 278–9 cave paintings, 216 central banks, 5 , 7 , 95 , 96 , 103–5 , 285–6 , 348–9 , 350 , 351 , 356–7 Central Pacific Railroad, 48 Centre for the Study of Existential Risk, 39 Chabris, Christopher, 140 Challenger disaster (1986), 373 , 374 Chamberlain, Neville, 24–5 Chandler, Alfred, Strategy and Structure , 286 Chariots of Fire (film, 1981), 273 Charles II, King, 383 Chelsea Football Club, 265 chess, 173 , 174 , 175 , 266 , 273 , 346 Chicago economists, 36 , 72–4 , 86 , 92 , 111–14 , 133–7 , 158 , 257–8 , 307 , 342–3 , 381–2 Chicago Mercantile Exchange, 423 chimpanzees, 161–2 , 178 , 274 China, 4–5 , 419–20 , 430 cholera, 283 Churchill, Winston: character of, 25–6 , 168 , 169 , 170 ; fondness for gambling, 81 , 168 ; as hedgehog not fox, 222 ; on Montgomery, 293 ; restores gold standard (1925), 25–6 , 269 ; The Second World War , 187 ; Second World War leadership, 24–5 , 26 , 119 , 167 , 168–9 , 170 , 184 , 187 , 266 , 269 Citibank, 255 Civil War, American, 188 , 266 , 290 Clapham, John, 253 Clark, Sally, 197–8 , 200 , 202 , 204 , 206 Clausewitz, Carl von, On War , 433 climate systems, 101–2 Club of Rome, 361 , 362 Coase, Ronald, 286 , 342 Cochran, Johnnie, 198 , 217 Cochrane, John, 93 coffee houses, 55–6 cognitive illusions, 141–2 Cohen, Jonathan, 206–7 Colbert, Jean-Baptiste, 411 Cold War, 293–4 , 306–7 Collier, Paul, 276–7 Columbia disaster (2003), 373 Columbia University, 117 , 118 , 120 Columbus, Christopher, 4 , 21 Colyvan, Mark, 225 Comet aircraft, 23–4 , 228 communication: communicative rationality, 172 , 267–77 , 279–82 , 412 , 414–16 ; and decision-making, 17 , 231 , 272–7 , 279–82 , 398–9 , 408 , 412 , 413–17 , 432 ; eusociality, 172–3 , 274 ; and good doctors, 185 , 398–9 ; human capacity for, 159 , 161 , 162 , 172–3 , 216 , 272–7 , 408 ; and ill-defined concepts, 98–9 ; and intelligibility, 98 ; language, 98 , 99–100 , 159 , 162 , 173 , 226 ; linguistic ambiguity, 98–100 ; and reasoning, 265–8 , 269–77 ; and the smartphone, 30 ; the ‘wisdom of crowds’, 47 , 413–14 Community Reinvestment Act (USA, 1977), 207 comparative advantage model, 249–50 , 251–2 , 253 computer technologies, 27–31 , 173–4 , 175–7 , 185–6 , 227 , 411 ; big data, 208 , 327 , 388–90 ; CAPTCHA text, 387 ; dotcom boom, 228 ; and economic models, 339–40 ; machine learning, 208 Condit, Phil, 228 Condorcet, Nicolas de, 199–200 consumer price index, 330 , 331 conviction narrative theory, 227–30 Corinthians (New Testament), 402 corporate takeovers, 256–7 corporations, large, 27–31 , 122 , 123 , 286–90 , 408–10 , 412 , 415 Cosmides, Leda, 165 Cretaceous–Paleogene extinction, 32 , 39 , 71–2 Crick, Francis, 156 cricket, 140–1 , 237 , 263–5 crime novels, classic, 218 crosswords, 218 crypto-currencies, 96 , 316 Csikszentmihalyi, Mihaly, 140 , 264 Cuba, 278–80 ; Cuban Missile Crisis, 279–81 , 299 , 412 Custer, George, 293 Cutty Sark (whisky producer), 325 Daily Express , 242–3 , 244 Damasio, Antonio, 171 Dardanelles expedition (1915), 25 Darwin, Charles, 156 , 157 Davenport, Thomas, 374 Dawkins, Richard, 156 de Havilland company, 23–4 Debreu, Gerard, 254 , 343–4 decision theory, xvi ; critiques of ‘American school’, 133–7 ; definition of rationality, 133–4 ; derived from deductive reasoning, 138 ; Ellsberg’s ‘ambiguity aversion’, 135 ; expected utility , 111–14 , 115–18 , 124–5 , 127 , 128 – 30 , 135 , 400 , 435–44 ; hegemony of optimisation, 40–2 , 110–14 ; as unable to solve mysteries, 34 , 44 , 47 ; and work of Savage, 442–3 decision-making under uncertainty: and adaptation, 102 , 401 ; Allais paradox, 133–7 , 437 , 440–3 ; axiomatic approach extended to, xv , 40–2 , 110–14 , 133–7 , 257–9 , 420–1 ; ‘bounded rationality concept, 149–53 ; as collaborative process, 17 , 155 , 162 , 176 , 411–15 , 431–2 ; and communication, 17 , 231 , 272–7 , 279–82 , 398–9 , 408 , 412 , 413–17 , 432 ; communicative rationality, 172 , 267–77 , 279–82 , 412 , 414–16 ; completeness axiom, 437–8 ; continuity axiom, 438–40 ; Cuban Missile Crisis, 279–81 , 299 , 412 ; ‘decision weights’ concept, 121 ; disasters attributed to chance, 266–7 ; doctors, 184–6 , 194 , 398–9 ; and emotions, 227–9 , 411 ; ‘evidence-based policy’, 404 , 405 ; excessive attention to prior probabilities, 184–5 , 210 ; expected utility , 111–14 , 115–18 , 124–5 , 127 , 128–30 , 135 , 400 , 435–44 ; first-rate decision-makers, 285 ; framing of problems, 261 , 362 , 398–400 ; good strategies for radical uncertainty, 423–5 ; and hindsight, 263 ; independence axiom, 440–4 ; judgement as unavoidable, 176 ; Klein’s ‘primed recognition decision-making’, 399 ; Gary Klein’s work on, 151–2 , 167 ; and luck, 263–6 ; practical decision-making, 22–6 , 46–7 , 48–9 , 81–2 , 151 , 171–2 , 176–7 , 255 , 332 , 383 , 395–6 , 398–9 ; and practical knowledge, 22–6 , 195 , 255 , 352 , 382–8 , 395–6 , 405 , 414–15 , 431 ; and prior opinions, 179–80 , 184–5 , 210 ; ‘prospect theory’, 121 ; public sector processes, 183 , 355 , 415 ; puzzle– mystery distinction, 20–4 , 32–4 , 48–9 , 64–8 , 100 , 155 , 173–7 , 218 , 249 , 398 , 400–1 ; qualities needed for success, 179–80 ; reasoning as not decision-making, 268–71 ; and ‘resulting’, 265–7 ; ‘risk as feelings’ perspective, 128–9 , 310 ; robustness and resilience, 123 , 294–8 , 332 , 335 , 374 , 423–5 ; and role of economists, 397–401 ; Rumelt’s ‘diagnosis’, 184–5 , 194–5 ; ‘satisficing’ (’good enough’ outcomes), 150 , 167 , 175 , 415 , 416 ; search for a workable solution, 151–2 , 167 ; by securities traders, 268–9 ; ‘shock’ and ‘shift’ labels, 42 , 346 , 347 , 348 , 406–7 ; simple heuristics, rules of thumb, 152 ; and statistical discrimination, 207–9 , 415 ; triumph of probabilistic reasoning, 20 , 40–2 , 72–84 , 110–14 ; von Neumann– Morgenstern axioms, 111 , 133 , 435–44 ; see also business strategy deductive reasoning, 137–8 , 147 , 235 , 388 , 389 , 398 Deep Blue, 175 DeepMind, 173–4 The Deer Hunter (film, 1978), 438 democracy, representative, 292 , 319 , 414 demographic issues, 253 , 358–61 , 362–3 ; EU migration models, 369–70 , 372 Denmark, 426 , 427 , 428 , 430 dentistry, 387–8 , 394 Derek, Bo, 97 dermatologists, 88–9 Digital Equipment Corporation (DEC), 27 , 31 dinosaurs, extinction of, 32 , 39 , 71–2 , 383 , 402 division of labour, 161 , 162 , 172–3 , 216 , 249 DNA, 156 , 198 , 201 , 204 ‘domino theory’, 281 Donoghue, Denis, 226 dotcom boom, 316 , 402 Doyle, Arthur Conan, 34 , 224–5 , 253 Drapers Company, 328 Drescher, Melvin, 248–9 Drucker, Peter, Concept of the Corporation (1946), 286 , 287 Duhem–Quine hypothesis, 259–60 Duke, Annie, 263 , 268 , 273 Dulles, John Foster, 293 Dutch tulip craze (1630s), 315 Dyson, Frank, 259 earthquakes, 237–8 , 239 Eco, Umberto, The Name of the Rose , 204 Econometrica , 134 econometrics, 134 , 340–1 , 346 , 356 economic models: of 1950s and 1960s, 339–40 ; Akerlof model, 250–1 , 252 , 253 , 254 ; ‘analogue economies’ of Lucas, 345 , 346 ; artificial/complex, xiv–xv , 21 , 92–3 , 94 ; ‘asymmetric information’ model, 250–1 , 254–5 ; capital asset pricing model (CAPM), 307–8 , 309 , 320 , 332 ; comparative advantage model, 249–50 , 251–2 , 253 ; cost-benefit analysis obsession, 404 ; diversification of risk, 304–5 , 307–9 , 317–18 , 334–7 ; econometric models, 340–1 , 346 , 356 ; economic rent model, 253–4 ; efficient market hypothesis, 252 , 254 , 308–9 , 318 , 320 , 332 , 336–7 ; efficient portfolio model, 307–8 , 309 , 318 , 320 , 332–4 , 366 ; failure over 2007–08 crisis, xv , 6–7 , 260 , 311–12 , 319 , 339 , 349–50 , 357 , 367–8 , 399 , 407 , 423–4 ; falsificationist argument, 259–60 ; forecasting models, 7 , 15–16 , 68 , 96 , 102–5 , 347–50 , 403–4 ; Goldman Sachs risk models, 6–7 , 9 , 68 , 202 , 246–7 ; ‘grand auction’ of Arrow and Debreu, 343–5 ; inadequacy of forecasting models, 347–50 , 353–4 , 403–4 ; invented numbers in, 312–13 , 320 , 363–4 , 365 , 371 , 373 , 404 , 405 , 423 ; Keynesian, 339–40 ; Lucas critique, 341 , 348 , 354 ; Malthus’ population growth model, 253 , 358–61 , 362–3 ; misuse/abuse of, 312–13 , 320 , 371–4 , 405 ; need for, 404–5 ; need for pluralism of, 276–7 ; pension models, 312–13 , 328–9 , 405 , 423 , 424 ; pre-crisis risk models, 6–7 , 9 , 68 , 202 , 246–7 , 260 , 311–12 , 319 , 320–1 , 339 ; purpose of, 346 ; quest for large-world model, 392 ; ‘rational expectations theory, 342–5 , 346–50 ; real business cycle theory, 348 , 352–4 ; role of incentives, 408–9 ; ‘shift’ label, 406–7 ; ‘shock’ label, 346–7 , 348 , 406–7 ; ‘training base’ (historical data series), 406 ; Value at risk models (VaR), 366–8 , 405 , 424 ; Viniar problem (problem of model failure), 6–7 , 58 , 68 , 109 , 150 , 176 , 202 , 241 , 242 , 246–7 , 331 , 366–8 ; ‘wind tunnel’ models, 309 , 339 , 392 ; winner’s curse model, 256–7 ; World Economic Outlook, 349 ; see also axiomatic rationality; maximising behaviour; optimising behaviour; small world models Economic Policy Symposium, Jackson Hole, 317–18 economics: adverse selection process, 250–1 , 327 ; aggregate output and GDP, 95 ; ambiguity of variables/concepts, 95–6 , 99–100 ; appeal of probability theory, 42–3 ; ‘bubbles’, 315–16 ; business cycles, 45–6 , 347 ; Chicago School, 36 , 72–4 , 86 , 92 , 111–14 , 133–7 , 158 , 257–8 , 307 , 342–3 , 381–2 ; data as essential, 388–90 ; division of labour, 161 , 162 , 172–3 , 216 , 249 ; and evolutionary mechanisms, 158–9 ; ‘expectations’ concept, 97–8 , 102–3 , 121–2 , 341–2 ; forecasts and future planning as necessary, 103 ; framing of problems, 261 , 362 , 398–400 ; ‘grand auction’ of Arrow and Debreu, 343–5 ; hegemony of optimisation, 40–2 , 110 – 14 ; Hicks–Samuelson axioms, 435–6 ; market fundamentalism, 220 ; market price equilibrium, 254 , 343–4 , 381–2 ; markets as necessarily incomplete, 344 , 345 , 349 ; Marshall’s definition of, 381 , 382 ; as ‘non-stationary’, 16 , 35–6 , 45–6 , 102 , 236 , 339–41 , 349 , 350 , 394–6 ; oil shock (1973), 223 ; Phillips curve, 340 ; and ‘physics envy’, 387 , 388 ; and power laws, 238–9 ; as practical knowledge, 381 , 382–3 , 385–8 , 398 , 399 , 405 ; public role of the social scientist, 397–401 ; reciprocity in a modern economy, 191–2 , 328–9 ; and reflexivity, 35–6 , 309 , 394 ; risk and volatility, 124–5 , 310 , 333 , 335–6 , 421–3 ; Romer’s ‘mathiness’, 93–4 , 95 ; shift or structural break, 236 ; Adam Smith’s ‘invisible hand’, 163 , 254 , 343 ; social context of, 17 ; sources of data, 389 , 390 ; surge in national income since 1800, 161 ; systems as non-linear, 102 ; teaching’s emphasis on quantitative methods, 389 ; validity of research findings, 245 ‘Economists Free Ride, Does Anyone Else?’

Empirical Market Microstructure: The Institutions, Economics and Econometrics of Securities Trading
by Joel Hasbrouck
Published 4 Jan 2007

The trade is at the ask if qt = +1, and at the bid if qt = −1, which imply that the ask and bid are mt−1 + c + λ + ut and mt−1 − c − λ + ut . Thus, the bid and ask are set symmetrically about mt−1 + ut . The spread is 2(c + λ), where c reflects the noninformational fixed costs of the trade (clearing costs, clerical costs, etc.) and λ reflects the adverse selection cost. In the spirit of the asymmetric information models, λ is the price impact necessary to balance expected gains from trading against uninformed agents with expected losses to informed agents. These conventions suggest the following timing. Immediately after the trade at t − 1, the efficient price is mt−1 .

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Merton, Robert, 1980, On estimating the expected rate of return on the market, Journal of Financial Economics 8, 323–62. Milgrom, Paul, 2004, Putting Auction Theory to Work (Cambridge University Press, Cambridge). Morse, Andrew, 2005, Tokyo Exchange chief quits; Move follows technology blunders, may slow pace of reforms, Wall Street Journal, December 21, C, p. 14. Neal, Robert, and Simon M. Wheatley, 1998, Adverse selection and bidask spreads: Evidence from closed-end funds, Journal of Financial Markets 1, 121–49. New York Stock Exchange, 2005, Constitution and Rules. Niederhoffer, Victor, and M. F. M. Osborne, 1966, Market making and reversal on the stock exchange, Journal of the American Statistical Association 61, 897–916.

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Saar, Gideon, 1998, Information and the pricing of assets when orders arrive one at a time (Johnson School, Cornell University). Saar, Gideon, and Lei Yu, 2002. Information asymmetry about the firm and the permanent price impact of trades: Is there a connection? (Finance Department, Stern School, NYU). Sandas, Patrik, 2001, Adverse selection and competitive market making: evidence from a pure limit order book, Review of Financial Studies 14, 705–34. Sargent, Thomas J., 1979, Macroeconomic Theory (Academic Press, New York). Seppi, Duane J., 1990, Equilibrium block trading and asymmetric information, Journal of Finance 45, 73–94. Seppi, Duane J., 1997, Liquidity provision with limit orders and a strategic specialist, Review of Financial Studies 10, 103–50.

Information: A Very Short Introduction
by Luciano Floridi
Published 25 Feb 2010

We know that John is very absent-minded (he tends to forget to switch off the lights of his car) and not entirely trustworthy (he tends to lie and likes to blame his wife for his mistakes). Mark, however, does not have all this information about John. So this is a case of asymmetric information: one player has relevant information that the other player misses. Mark is underinformed, and this can lead to two well-known types of problems: moral hazard and adverse selection. An adverse selection scenario is one in which an absent-minded player like John is more likely to buy an insurance for his car battery because the underinformed player, like Mark, cannot adjust his response to him (e.g. by negotiating a higher premium) due to his lack of information (this is the relevant point here; Mark might also be bound by legal reasons even if he had enough information).

Unelected Power: The Quest for Legitimacy in Central Banking and the Regulatory State
by Paul Tucker
Published 21 Apr 2018

Trustees Are Still Agents: Pathologies, Incentives, and Design Whatever their formal status, political scientists have long argued that even if not captured by sectional interests, agency officials are liable to pursue their own interests—whether leisure or power—or their own conception of the public good (or welfare) at the expense of pursuing the public purpose as framed and intended by legislators.23 That is no less true of trustee agents than regular agents, but standard P-A analysis applies in slightly special ways. As economists have documented, any principal-agent problem has three components: incomplete contracts, adverse selection, and moral hazard. Most elementally, a principal cannot write a fully state-contingent contract that determines what should be done in every possible circumstance. They are destined to delegate via incomplete contracts.24 Indeed, for trustee agencies the whole point is to delegate some policy discretion: the contract is incomplete by design.

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First, in the usual way, candidates to take on the role of trustee/policy maker might pose as something they are not in order to get the trappings and/or power of the job. Second, the principal making the appointment has incentives to appoint an ally whose loyalty is to them, not to the mandate. The two hazards are linked, potentially deterring well-qualified candidates from applying at all, in an appointments-process manifestation of what is known as adverse selection.25 Even where personnel choices are made in good faith and wisely ex ante, they may prove badly flawed ex post because, once again as in a simple P-A arrangement, the principal and the wider public might not be able to observe whether the trustee has walked off the ranch when implementing policy; there might be long lags in detection.

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While that seems obvious, it means that delegation to insulated officials should occur only where society recognizes that there is a body of professional, technical knowledge, imperfect though it inevitably will prove, relevant to delivering the regime’s purposes. That would rule out some fields, either because there is no recognized body of expertise or because experts are so few that there is not a professional community. Furthermore, formally requiring recognized expertise can reduce the adverse selection problems facing politicians and also constrain the politicians from appointing inexpert allies, since an expert will tend to have a professional reputation already. Third, the appointed policy makers would desirably also have a reputation for truly believing in what they are being asked to do (intrinsic motivation).

A Little History of Economics
by Niall Kishtainy
Published 15 Jan 2017

One editor said that the idea was trivial. Another said that if it was true, economics would have to change. Eventually Akerlof’s article was published and economics did change. It helped start off the new field of ‘information economics’. Economists had a technical name for the lemons problem – ‘adverse selection’ – and found it cropping up all over the place. Take health insurance. When you buy health insurance you pay a company a monthly amount (a premium) and the company promises to pay your medical bills if you get ill. In insurance markets it’s the buyers – the people who want to get insured – who know more than the sellers, the insurance company.

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Hence, the unhealthy drive out the healthy. The insurance company then has to raise its premiums sky high to cover the increased costs from having to pay the medical bills of the many unhealthy people who buy health insurance from it. Eventually only the sickest people are willing to buy the expensive insurance on offer. Adverse selection happens when important characteristics are unknown by buyers or sellers, such as when a buyer doesn’t know how good a car is, or a seller of insurance knows little about the health of a potential customer. Markets also get disrupted when people’s actions are unknown. Economists call it ‘moral hazard’.

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What makes them truly thrive? That’s where economics started and, after all the arguments and disagreements, it’s where it must begin from again. Index Page numbers in bold are where definitions of terms and concepts can be found. absolute poverty (i) acid rain (i) adaptive expectations (i) adverse selection (i) advertising (i) agriculture (i), (ii), (iii) aid (i) Akerlof, George (i) alienation (i) Ambrose, St (i) animal spirits (i), (ii), (iii) antitrust policies (i) Apple (i) Aquinas, St Thomas (i), (ii) Aristotle (i) Arrow, Kenneth (i) ascending auction (i) Asian Tigers (i), (ii) Atkinson, Anthony (i), (ii) auction theory (i) auctions (i) Augustine of Hippo, St (i) austerity (i) balance of trade (i) banks and entrepreneurs (i) and interest rates (i) and loans (i) and monopoly capitalism (i), (ii) and speculation (i) see also Britain, Bank of England; central banks; independent central banks; World Bank battle of the methods (i) Becker, Gary (i) behavioural economics (i) benevolent patriarch (i) Beveridge, William (i) big push (i) Black Wednesday (i) bonds (i) bourgeoisie (i), (ii), (iii) brand image (i) Britain Bank of England (i) inflation (i) pegged currency (i) Second World War (i) war with China (i) war with South Africa (i) bubbles (i), (ii) Buchanan, James (i) budget deficit (i) Burke, Edmund (i) capabilities (i) capital (i) and growth (i) Marx on (i) Capital (Marx) (i) Capital in the Twenty-First Century (Piketty) (i) capitalism (i), (ii), (iii) and entrepreneurs (i) and governments (i) and the Great Depression (i) and the Great Recession (i) historical law of (i) Marx on (i) world (i) see also communism Capitalism and Freedom (Friedman) (i) Capitalism, Socialism and Democracy (Schumpeter) (i) capitalists (i), (ii), (iii), (iv) and imperialism (i), (ii), (iii) Marx on (i), (ii), (iii), (iv), (v) carbon tax (i) carbon trading permits (i) Carlyle, Thomas (i), (ii) Castro, Fidel (i), (ii) central banks (i), (ii), (iii), (iv), (v) central planning (i), (ii) chaebols (i) chain of being (i), (ii) Chamberlin, Edward (i) Chaplin, Charlie (i) Chicago Boys (i) Chicago school (i), (ii), (iii), (iv) China, war with Britain (i) Christianity, views on money (i) Churchill, Winston (i) classical dichotomy (i) classical economics (i), (ii), (iii), (iv), (v) coins (i), (ii) Colbert, Jean-Baptiste (i) colonies/colonialism (i), (ii), (iii), (iv) American (i) Ghana (i), (ii) commerce (i), (ii), (iii), (iv) communism (i) and the Soviet Union (i) Communist Manifesto, The (Engels and Marx) (i), (ii) comparative advantage (i), (ii) competition (i), (ii), (iii), (iv) Condorcet, Marquis de (i) Confessions of an Economic Heretic (Hobson) (i) conspicuous consumption (i) constitution (rules) (i) consumers (i), (ii), (iii), (iv) contagion, economic (i) core (i) Corn Laws (i), (ii) Cortés, Hernan (i) cost (i) creative destruction (i) Credit Crunch (i) crime, economic theory of (i) Cuba (i) currency (i), (ii) see also coins currency markets (i), (ii) currency reserves (i) Debreu, Gérard (i) demand law of (i) see also supply and demand demand curve (i) democracy (i), (ii) Democratic Republic of the Congo (i) dependency theory (i) Depression (Great) (i), (ii), (iii), (iv), (v), (vi), (vii) and economic growth (i) and the US central bank (i) descending auction (i) developing/underdeveloped countries (i), (ii) development economics (i) Development of Underdevelopment, The (Frank) (i) diminishing marginal utility (i), (ii) diminishing return to capital (i) discretion (i) discrimination coefficient (i) distribution of income (i), (ii) diversification (i), (ii) dividends (i) division of labour (i) doomsday machines (i) Drake, Sir Francis (i) Drew, Daniel (i) dual economy (i) economic value (i), (ii), (iii), (iv) economics defined (i) normative (i) Economics of Imperfect Competition (Robinson) (i) economies of scale (i) economists (i), (ii), (iii) efficient markets hypothesis (i), (ii), (iii), (iv) efficient/inefficient economic outcome (i) see also pareto efficiency; pareto improvement Elizabeth I (i) Elizabeth II (i) employment, full (i) Engels, Friedrich (i) England’s Treasure by Forraign Trade (Mun) (i) entitlement (i), (ii) entrepreneurs (i), (ii) equilibrium (i), (ii), (iii), (iv), (v) exchange of goods (i), (ii) exchange rates (i) expectations, adaptive/rational (i), (ii), (iii), (iv) exploitation (i), (ii), (iii), (iv), (v) exports (i) and poor countries (i), (ii), (iii) externalities (i), (ii), (iii), (iv) Extraordinary Popular Delusions and the Madness of Crowds (MacKay) (i) failure, market (i), (ii), (iii), (iv) Fama, Eugene (i) famine (i), (ii), (iii), (iv) feminist economics (i) feudalism (i), (ii), (iii), (iv) financial systems (i), (ii) Finer, Herman (i) first price auction (i), (ii) First Welfare Theorem (i), (ii) First World War (i) fiscal policy (i), (ii) floating exchange rate (i) Florence (i) Folbre, Nancy (i) Fourier, Charles (i) framing (i), (ii) France agriculture (i) economic models (i), (ii) revolution (i), (ii), (iii), (iv) and taxation (i) Frank, Andre Gunder (i) free choice (i), (ii) free-market economics (i), (ii), (iii), (iv) free trade (i), (ii), (iii) Friedman, Milton (i), (ii), (iii) full employment (i) game theory (i), (ii), (iii) general equilibrium (i), (ii), (iii), (iv) General Theory of Employment, Interest and Money, The (Keynes) (i) Germany, infant industries (i) Ghana (i), (ii) Gilded Age (i) Global Financial Crisis (i), (ii) global warming (i) Goethe, Johann Wolfgang (i) gold (i), (ii) Golden Age (i) goods and services (i) government, and economies (i), (ii), (iii), (iv), (v), (vi), (vii) Great Moderation (i), (ii) Great Recession (i) Greece (i), (ii), (iii) gross domestic product (i) growth (i) and dependency theory (i) of government (i) and the Great Moderation (i) and Pakistan (i) and population (i) theory (i) Guevara, Ernesto ‘Che’ (i), (ii) guilds (i) Hamilton, Alexander (i) Hansen, Alvin (i) harmony, system of (i) Hayek, Friedrich (i), (ii) hedge funds (i) herds (i) Hicks, John (i) historical law of capitalism (i) HIV/AIDS (i) Hobson, John (i) Homobonus, St (i) human capital (i) human development (i), (ii) Human Development Index (i) imperfect competition (i), (ii) imperialism (i) Imperialism: The Highest Stage of Capitalism (Lenin) (i) imports (i), (ii), (iii) income (i), (ii) and bank loans (i) and capitalism (i) and communism (i) distribution of (i), (ii) and growth (i), (ii) national (i), (ii), (iii), (iv), (v) income per person (i), (ii) independent central banks (i) Industrial Revolution (i), (ii), (iii), (iv), (v) inequality (i), (ii) infant industries (i) inflation (i), (ii), (iii), (iv), (v) information economics (i), (ii), (iii) injection of spending (i) innovations (i), (ii) insurance (i), (ii) interest rates (i) British (i) and monetary policy (i) and recession (i) and usury (i) International Monetary Fund (i) investment (i) and the big push (i) and recession (i), (ii) invisible hand (i), (ii), (iii), (iv), (v) iron law of wages (i) Irrational Exuberance (Shiller) (i) Jefferson, Thomas (i) Jevons, William (i) just price (i) Kahneman, Daniel (i), (ii) Kennedy, John F.

How Markets Fail: The Logic of Economic Calamities
by John Cassidy
Published 10 Nov 2009

Akerlof believed that “a major reason as to why people preferred to purchase new cars rather than used cars was their suspicion of the motives of the sellers of used cars.” Horse traders and other dealers in secondhand goods of questionable quality have been dealing with this type of dilemma for centuries. Economists now refer to it as the problem of “adverse selection,” but “hidden information” is equally accurate and less off-putting. Within a year or so of arriving in Berkeley, Akerlof had written a paper showing how in some circumstances the presence of “lemons” in the used car market could drive out sellers of higher-quality vehicles, even though there are some customers willing to pay a premium for reliability.

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All they know is that those who have been hardest hit by the downturn will be those most eager to take out more credit. This creates a serious lemons problem. Fearing that new borrowers will be more likely to default, banks have strong incentive to curtail lending. But if they do this, businesses will be deprived of credit; the economic downturn and the problem of adverse selection will only get more acute. In extreme circumstances, the entire lending market might freeze up. In solving one set of information problems, banks create others, of which the possibility of a credit crunch is but one example. Since banks don’t publish a list of all the loans they have made, the typical bank customer doesn’t really know if his bank is sound.

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“The older market failures were, for the most part, easily identified and limited in scope, requiring well-defined government interventions,” Stiglitz wrote in his 1994 book, Whither Socialism? in which he discusses the consequences of communism’s collapse. “Because . . . information is always imperfect—moral hazard and adverse selection problems are endemic to all market situations—the market failures are pervasive in the economy.” Stiglitz is, of course, a well-known liberal Democrat. By today’s standards, he might even be called left-wing. As Milton Friedman’s ghost would surely point out, the fact that markets are imperfect doesn’t mean that governments can do a better job, or that all markets need close government oversight.

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism
by Arun Sundararajan
Published 12 May 2016

These and other forms of information asymmetry can lead to a lower level of economic activity than society might find desirable. Part of this could be due to uncertainty about quality—I’m not going to get into a taxi unless I’m sure the driver is reliable and won’t rip me off. Or information asymmetry can lead to the situation of “adverse selection”: if there’s no good way of distinguishing between lower and higher quality providers, then a customer is likely to be willing to pay, on average, a price commensurate with the value they’d get from an average quality provider. Noticing this, the higher quality providers will be reluctant to transact, since they’re not getting a fair price for the higher value they deliver.

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As I defined and discussed in chapter 6, sharing economy platforms can reduce many forms of information asymmetry. The predictions of economic theory are that such reductions will increase, rather than reduce, wages over time. Let me explain the consequences of information asymmetry, and in particular, the effect of “adverse selection” further by appealing to the example of used car markets that George Akerlof famously used in his Nobel Prize–winning work. In Akerlof’s model, there are two kinds of used cars—those of high quality, and those of low quality (the “lemons”). Suppose that prospective buyers have no way of determining the true quality of a used car prior to purchasing it.

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Index Abrams, Jen, 43 Access without ownership, 14–16 Accommodation platforms, 38–43, 45. See also Airbnb; Couchsurfing increased variety and consumption with, 121 rental market analysis, 125–130 Acemoglu, Daron, 144 Achamore House, 105 Additive manufacturing, 57–58 Adomavicius, Gedas, 112 Adverse selection, 139 Aggarwal, Bhavish, 116 Airbnb, 2, 3, 6, 29, 45, 48, 106, 139, 159, 197, 203. See also Accommodation platforms blurring of boundaries and, 141–142 convenience of, 128 ease of using, 124 entrepreneurial nature of, 194 externalities, 140 financing of, 25 founding and growth of, 7–9, 131 gift aspect of, 39–40 gift economy aspects, 35 hotel taxes and, 186 impact on hotel industry, 121–122, 129, 216–217n11, 219n3 increased variety and consumption with, 121 local network effects, 120 as microentrepreneurship, 125 as micro-outsourcing, 77 peer regulation and, 151–152 pricing, supply, and merchandising, 194–195 regulation and, 131–136, 154, 155 search capability, 97 shared redistribution, 82 trust and, 61, 62, 64, 65, 98, 145, 147 Alaska Permanent Fund, 190 Alibaba, 48, 97, 99 Alone Together (Turkle), 45 Altavista, 96 Amazon, 37, 47, 54, 57, 91, 203 logistics, 99 market value, 96 price search comparisons and product offerings, 112 search capability, 97 user-generated reviews, 147 Walmart and, 98–99 American Hotel and Lodging Association (AHLA), 134–135 American Medical Association, 153, 192 Amtrak, 12 Andreessen, Marc, 59–60, 87 Andreessen Horowitz, 25, 87 AngelList, 42–43 Apple, 2, 55, 203 iTunes, 54, 56, 57, 91, 93 Apple Core Hotels, 121 Arthurs, H.

Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe
by Greg Ip
Published 12 Oct 2015

Second, how correlated are those risks: If he dies, does this make it more likely that his neighbor will die? If his house burns down, does it mean that others are more likely to burn down, too? Beyond the arithmetic, insurers must also consider several aspects of human behavior. The first is adverse selection: people who buy insurance may be more likely to need it. For example, someone with terminal cancer is more likely to want life insurance, but this is a poor risk for an insurer to cover. The other is moral hazard: the tendency of someone to be more careless about the risks he has insured against.

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References to insurance have been found as far back as Hammurabi’s Code, written around 1790 BC, which stipulates that a man whose crops are destroyed by flood or drought “shall not pay corn to his creditor. He shall dip his tablet in water, and the interest of that year he shall not pay.” The earliest known commercial contracts date from the 1300s. Incorporating human behavior such as moral hazard and adverse selection into insurance policies took longer. The process was hampered both by lack of statistical tools and theological objections; since accidents, disasters, and hazards were seen as acts of divine will, humans had little ability to affect their occurrence. In the 1800s, with better statistical tools, insurers began to differentiate risks, for example, requiring medical exams for life insurance.

…

Part of the challenge is that insurance is supposed to enable people to do things they otherwise might not. Sometimes, this is by law: you can’t drive without liability insurance. And sometimes this is by choice: financial innovation has enabled many to take risks they otherwise would not. The insurance industry has come up with many ways to deal with both moral hazard and adverse selection. The use of deductibles, copays, and insured maximums ensure that customers bear some of the cost of a peril. Customers are screened for characteristics likely to lead to higher claims—serious illness, for example, in the case of life insurance, or previous traffic offenses in the case of automobile insurance.

Going Infinite: The Rise and Fall of a New Tycoon
by Michael Lewis
Published 2 Oct 2023

“Part of me is like, Jesus Christ, Sam, why do you care why he cares what sweaters he’s wearing?” A bigger part of him cared. And Asher had approached him. In the conference room, one morning. Before Jane Street’s intern class. Let’s make a bet, Asher had said. On what? On how much any one intern will lose gambling today. Sam’s first thought was about adverse selection. Adverse selection was a favorite topic at Jane Street. In this context it meant that the person most eager to make a bet with you is the person you should be most worried about betting against. When people wanted to bet—­or trade—­with you, there was usually a reason: they knew something you did not.

…

Sam hired Natalie Tien, who had little experience with media or marketing, and made her head of corporate public relations, for instance. He hired a young saleswoman from the Huobi exchange named Constance Wang and made her the company’s chief operating officer. Faced with a necessity, Sam turned it into a virtue. “It’s a moderately bad sign if you are having someone do the same thing they’ve done before,” he said. “It’s adverse selection of a weird sort. Because: why are they coming to you?” The funny thing about Ramnik Arora was that all he’d really been looking for was a chance to walk to work. He’d grown up in India, completed a master’s in computer science at Stanford, done a stint at Goldman Sachs, and was now married and settled in the East Bay.

Flash Boys: Not So Fast: An Insider's Perspective on High-Frequency Trading
by Peter Kovac
Published 10 Dec 2014

Lewis faces a dilemma: how can you argue that volatility – the unpredictability of a stock’s price – somehow benefits high-frequency traders, whom he has been arguing make all their money by predicting market moves? It seems that unpredictability would ruin whatever scam they have going. It’s a very difficult argument to make, even more so given the principle of “adverse selection.” Adverse selection is the fancy economic term that means that a market-maker who sticks his neck out is the first one to get stuck with a losing position when the market drops. The more volatile the markets, the more likely he gets stuck with losing positions. Lewis’ own volatility example above illustrates this: the market-maker bids to buy Microsoft at $30.00, you sell shares to him at that price, and the market begins to fall.

Fault Lines: How Hidden Fractures Still Threaten the World Economy
by Raghuram Rajan
Published 24 May 2010

The debate about universal health care and health care costs is far from settled, and it will be with us for many years to come; hence a closer look at the key issues is useful. Universal Health Care There is little appetite in the United States for a radical overhaul of the largely private health care system. The key to universal health care, then, is to deal with the adverse-selection problem. If an insurance plan attracts a disproportionate number of those with preexisting health problems, which make them higher insurance risks, while attracting too few of the young and healthy whose premiums are necessary to subsidize the less healthy, the economics supporting insurance breaks down, and it becomes uneconomic.

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The reduction in anxiety among the population in downturns, and the associated reduction in the need for expansionary macroeconomic policies, will make the United States better able to calibrate fiscal and monetary policy to its actual needs, while serving notice on policy makers in the rest of the world that they need to become more expansionary. The major problem in expanding coverage, once the adverse-selection problem is dealt with, is that U.S. health care does not seem cost-effective. The United States spent 15 percent of GDP on health care in 2006, compared to 11 percent in France and Germany, 10 percent in Canada, and 8 percent in the United Kingdom and Japan.25 On a per capita basis, the United States spent $6,347, while Japan spent $2,474.

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See economic growth; export-led growth strategies GSEs (government-sponsored enterprises). See Fannie Mae; Freddie Mac; Ginnie Mae Haitian earthquake Hart, Robert M. Hayek, Friedrich von Head Start health care: cost-efficiency of in developing countries medical tourism health insurance: adverse-selection problem of costs of employment-based, in Europe reform act (2010)required subsidies for universal U.S. system of Heckman, James hedge funds Henry VII, King Heymath higher education: business schools costs of enrollment assistance for future of graduation rates of relationship to incomes high school graduation rates, See also education Hillery, Ruthie HOLC.

The Irrational Economist: Making Decisions in a Dangerous World
by Erwann Michel-Kerjan and Paul Slovic
Published 5 Jan 2010

Group insurance tends to charge explicit premiums that are independent of risk (though with much lower than expected benefits) and thus seems to discriminate against lower risks, sometimes creating a situation where lower-risk employed people are less likely to take coverage than the higher-risk employed. (It probably helps the risk pool that a person must at least be able to work to get group insurance, such that the possibility of severe adverse selection is reduced.) A low-risk person will face the same explicit premium as a high-risk person working in the same firm, but the options available in firms employing mostly lower-risk people and the existence of a lower wage offset for coverage cause premiums to be somewhat reflective of risk. Here, the best outcome is probably a compromise.

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It is clear and reasonable that different individuals have access to different information; they have varying life experiences and varying opportunities to make observations. A number of economists came to stress this concept from varying points of view; I myself came to it by considering the economics of medical care (Arrow, 1963).4 Insurance companies had long understood the consequences of asymmetry of information under such headings as moral hazard and adverse selection. It is not always recognized that the most neoclassical approaches in economics also assume asymmetry of information. It is a standard claim for the usefulness of a system of markets that it requires an individual to know only his or her own utility function and production possibilities. The only information about the rest of the world is contained in the prices.

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Professor Doherty has written three books in this area—Corporate Risk Management: A Financial Exposition (McGraw Hill, 1985), The Financial Theory of Insurance Pricing, with S. D’Arcy (1987), and Integrated Risk Management (McGraw Hill, 2000)—as well as several recent papers. His other areas of interest include the economics of risk and information, adverse selection, the value of information, and the design of insurance contracts with imperfect information and related issues. Baruch Fischhoff, Carnegie Mellon University Baruch Fischhoff is Howard Heinz University Professor in the Department of Social and Decision Sciences and the Department of Engineering and Public Policy at Carnegie Mellon University, where he heads the Decision Sciences Major.

The Bottom Billion: Why the Poorest Countries Are Failing and What Can Be Done About It
by Paul Collier
Published 26 Apr 2007

Not all companies are concerned about the risk to their reputation because not all companies have good reputations to protect. However, this gives rise to what is known technically as an “adverse selection problem”: the companies attracted to the risky environments are those that are not concerned about poor governance and so have no interest in helping to avoid the problems of the resource trap. This adverse selection is now extending to the governments behind many resource extraction companies. In 2006 the vice president of China toured Africa with the revealing refrain “We won’t ask questions.” Strategy 8: Rural Development Because landlocked countries do not have the option of rapid industrialization, the bulk of their populations will continue to be rural for a long time.

Global Governance and Financial Crises
by Meghnad Desai and Yahia Said
Published 12 Nov 2003

Therefore, contracts explicitly contingent on this characteristic are not feasible. The role of banks is to make investments on behalf of consumers. We assume that only banks can distinguish the genuine risky assets from assets that have no value. Any consumer who tries to purchase the risky asset faces an extreme adverse selection problem, so in practice only banks will hold the risky asset. This gives the bank an advantage over consumers in two respects. First, the banks can hold a portfolio consisting of both types of assets, which will typically be preferred to a portfolio consisting of the safe asset alone. Second, by pooling the assets of a large number of consumers, the bank can offer insurance to consumers against their uncertain liquidity demands, giving the early consumers some of the benefits of the high-yielding risky asset without subjecting them to the volatility of the asset market.

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United Nations (2000) Comtrade Database. Valdés-Prieto, S. and Soto, M. (1998) ‘The effectiveness of capital controls: theory and evidence from Chile’, Empirica, 25, 133–164. World Bank (2000a) World Development Indicators CD-ROM. World Bank (2000b) Global Development Finance CD-ROM. Index adverse selection 32 ageing population 67 agency problems 21–9, 41 Akyüz, Y. 99 Allen, F. 20–2, 29 Argentina 11–12, 61 Asian financial crisis 1, 4, 6, 64, 74–5, 79, 83–5, 120; IMF role in 91–4; recovery from 94–7, 101–2 Austrian school of economists 75–6, 81 corporate governance 101–5 cosmopolitan order, concept of 74–5, 79 Cox, R. 77 crashes 11–12 crises, financial 30; definition of 7–8; history of 11–16, 67; management of 57–9, 64–6; three routes to 122–40 crony capitalism 83, 121, 152 currency, international 52–3, 57, 66–7 currency unions 80 Baker, J. 48 Bank of England 2, 11–13, 29 Bank for International Settlements (BIS) 4, 78, 88, 93, 100 bank runs 30, 36–40 Baring Brothers 11–12 Basle Committee 61 Brazil 57, 120, 128–9, 133 Bretton Woods system 13, 15, 43–6, 50–1, 57 bubbles 3–4, 6, 19–24, 28, 70, 84, 129–30, 136–8, 144–8; negative 20–1, 31, 39, 41 business cycles, theory of 1, 6, 9, 13, 15, 30–1 debt, external 87–90 default 28–9 deregulation 70, 72, 103 devaluation, competitive 48 developing countries 54 Diamond, D. 30, 35–6, 39 Dybvig, P. 30, 35–6, 39 Calomiris, C. 31 capital flight 91, 96–7 capital flows 84–5, 89–90, 97–8, 104, 122, 127, 140; controls on 5, 45, 144–50 capitalism 76–7; alternative models of 79–81 Cardoso, Henrique 138 central banks, role of 39–41 Chile 122, 129, 140–6 conditionality 47, 55–6, 99, 104 contagion 57, 89, 91, 104, 137 contingent credit lines 57 convertibility of currencies 13 Federal Reserve 2, 6, 12–15, 30, 94–5 Financial Stability Forum 15–16, 61–2 Finland 19–20 foreign direct investment (FDI) 87, 89 Friedman, Milton 12 “fundamentals” (in asset pricing) 22–4, 28, 41 Furman, J. 92 early warning system, financial 62 Eatwell, J. 15–16 emerging markets 54, 61 Enron 6 euro (currency) 66 European integration 52, 72, 80 exchange rates, fixed 13–14 G5 meetings 15 G7 meetings 15, 66–7 Gale, D. 20–2, 29 General Agreement to Borrow (GAB) 50–1 160 Index General Agreement on Trade in Services (GATS) 100 Germany 53 globalisation 4; alternative views of 70–2 Goldsmith, Raymond 8, 10–11 gold standard 12, 49, 73 Goodhart, C. 64 Gorton, G. 12, 31 Great Depression 2, 12–14 Hamilton, Alexander 29 Hamilton-Hart, N. 103 Hayek, F.A. 2, 9–10, 15, 75 hedging, dynamic 62 hegemony 13, 43, 72, 77–81; collective 77 incentive compatibility 33, 37 Indonesia 92, 94, 115, 117 International Monetary Fund (IMF) 2–5, 13–15, 43–67, 77, 80, 84, 98–105; Articles of Agreement 65; mandate of 58; role in Asian financial crisis 91–4 ISLM model 10 Jackson, Andrew 29 Jamaica Accord 46–7 Japan 19–20, 72 Juglar cycles 9–10 Kahn, J. 12 Keohane, R. 77 Keynes, J.M. 2, 10, 44, 68, 120, 127, 140 Keynesian policies 94, 97, 102, 105 Kindleberger, C.P. 2–3, 7, 11, 19, 30, 77, 122, 127 Kitchin cycles 9–10 Kondratieff cycles 9–10 Korea see South Korea Krueger, Anne 65 Kusnetz cycle 132, 150 lender of last resort (LOLR) 2–4, 49, 57–9, 63–7 liberalisation, financial 48–9, 56, 59, 83–5, 90, 101–2, 120–2 Lindgren, C.J. 30 Long-Term Capital Management (LTCM) 6, 94, 97, 124, 151 McKinnon, R. 128 Malaysia 74, 84, 87, 90–1, 94–5, 102–5, 116, 119, 122, 130, 133, 139, 147–51 Malthus, Thomas 8 market failure 121 Marxism 76, 79, 81 Marx, Karl 2, 9–10 Meltzer Commission and Report 16, 64 Mexico 20, 48–9, 56, 64, 93, 130 Mill, James 8 Minsky, H.P. 2, 10–11, 127, 137 Mises, Ludwig von 75 Mishkin, F. 20 Mitchell, W. 30 monetarism 47 moral hazard 1, 49, 59, 64, 95, 121, 128, 152 nation-states, role of 70–5, 78–9 neo-liberalism 75–81, 104 New Agreement to Borrow (NAB) 57 Nixon, Richard 46 North American Free Trade Agreement (NAFTA) 30, 72, 93 Norway 19 oil prices 13 Organisation for Economic Co-operation and Development (OECD) 83 Overend, Gurney and Company 11, 29 panics 11–12, 29–32, 92 Perez, C. 127 Philippines, the 91 Pill, H. 128 Plaza Accord 15 protectionism 73–5, 78 prudential supervision 60, 100, 103 quantitative controls 147–50 reform programmes 84, 99–105 regionalism 71–2 regulation of the global economy 71–81; see also prudential supervision reserve requirements 25 Ricardo, David 8 Rio de Janeiro agreement (1967) 53 risk shifting 20–5, 28; optimal 32–6 Say, J.B. 8 Say’s Law 126 Schumpeter, J. 2, 9–10 September 11th 2001, events of 6 Shin, J.

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined
by Lasse Heje Pedersen
Published 12 Apr 2015

Simultaneously, liquidity-providing HFTs immediately try to cancel their stale orders. HFTs engage in an “arms race” against each other where being fast is not important per se but being faster is very important. Indeed, there are only so many stale limit orders, so only the fastest HFTs get to hit them. On the flip side, to reduce the risk of being exposed to adverse selection, an HFT needs to be able to cancel its own limit orders before they become stale and are hit by other HFTs. Some HFTs may also try to identify and exploit large orders that are broken up into smaller trades and traded over hours or days. For example, if you are seeking to buy a large stock position, try to submit a limit order to buy the same number of shares each minute, right at the minute, and see what happens to your execution (relative to an execution where you split up the order more finely and more randomly and execute at more random times).

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In this case, the convertible bonds can only be traded among qualified institutional buyers (QIBs), so they are especially illiquid until they are registered. When the bonds get registered (often after 3 to 6 months), then they can be sold in the public market. Because of a liquidity risk premium and adverse selection, convertible bonds are reportedly sold at an initial average discount (similar to the average initial public offering (IPO) underpricing of equities). Hence, part of the profit from convertible bond arbitrage comes from participating in the primary market and being active enough to secure allocations of bonds in oversubscribed issues. 15.2.

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More broadly, when a firm buys back shares or retires debt, this often signals management confidence. On the other hand, issuance of securities, especially stocks, can signal that the securities are overvalued or that there are agency problems in the firm. However, participating in a security offering can be profitable if there is an average underpricing and if the event manager can avoid adverse selection in terms of allocation of shares—e.g., if the event manager is allocated shares even in the most oversubscribed offerings. Furthermore, the market for rights offerings sometimes involves arbitrage opportunities, as do when-issued markets. Special Security Structures and Market Dislocations Event managers also find opportunity in special security structures, such as ETFs and closed-end funds.

Mastering Private Equity
by Zeisberger, Claudia,Prahl, Michael,White, Bowen , Michael Prahl and Bowen White
Published 15 Jun 2017

Exhibit 21.3 LP’s Perceived Benefits of Co-investing Source: Preqin Risks of Co-investing Despite the attractions of co-investing, the main way in which institutional investors implement co-investment programs, namely, through a passive co-investment approach (syndication), introduces either increased risk or significant cost. The syndication process exposes investors to the effects of adverse selection from both the GP and LP sides, may lead to poorly understood investments and offers little differentiated value to GPs. The challenges can be grouped into two main categories: selection issues (choosing the deal) and positioning (getting the deal) especially in an increasingly crowded co-investment space. Selection Issues When LPs choose in which deals to co-invest, they typically suffer from two distinct risks: (1) adverse selection by GPs and (2) selection problems by LPs. GP SELECTION: We start with the hypothesis that GPs might offer LPs marginally less attractive deals for co-investment either intentionally or unintentionally through the kind of deals they select for co-investments.

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While the relatively small number of these investments does not allow for meaningful statistical analysis, the negative impact on individual LPs has certainly been significant in some cases. LP SELECTION: Even if a GP offered all potential deals to an LP for co-investment, thereby eliminating any adverse selection problems on his side, the LP would still have to make the decision where to invest. By picking investments (and therefore moving away from “buying the market” represented by all deals it has access to) LPs introduce biases into the selection process. Unsurprisingly, investors in PE are influenced by the full range of biases identified by behavioral finance research, e.g., overconfidence, confirmation bias, availability of heuristics, trend chasing, etc.

Money Free and Unfree
by George A. Selgin
Published 14 Jun 2017

Rather than pretend to limit its exposure to the risk of a counterparty’s failure by severely limiting the number of counterparties it deals with, the Fed can achieve a genuine reduction in risk by doing just the opposite: diversifying its counterparties so as to greatly reduce its exposure to losses in the event of any single counterparty’s failure. A simple way to accomplish that end, while further limiting the Fed’s risk exposure and guarding against adverse selection, would be to open participation to any financial institution with a CAMEL score of 1 or 2.7 Such a broadening of Fed counterparties would, as Hoenig (2011: 9) observes, also “enable nearly all banks to play a role in the conduct of monetary policy,” leveling the credit-allocation playing field while simultaneously making the largest banks considerably less systematically important.

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The procedure I have in mind, if only in the crudest of outlines, involves simultaneous reverse (single price) auctions for a set of different securities.17 The Fed would first have to decide what security types are eligible, favoring those for which holdings are sufficiently dispersed to provide for competitive bidding, and (to further discourage adverse selection) indicating maximum values of total and individual security purchases that it is prepared to make from a single participant.18 The list of such securities could be compiled, and regularly updated, using reports regularly submitted by prospective counterparties as one requirement for eligibility.

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Second, and more importantly, it allows the composition of open market purchases to adjust automatically with changing market conditions, with few if any central bank purchases of relatively high-risk and long-maturity instruments taking place in normal times, and more such purchases—perhaps substantially more—occurring during times of financial distress. To assure this outcome and, thereby, make a single set of open market rules suffice to consistently conform to Bagehot’s rule—while still guarding against adverse selection—the Fed need only take care to set sufficiently low reference prices.19 These prescriptions, taken together, might be summarized by paraphrasing Bagehot as follows: the Fed should at all times be prepared to buy good securities freely, outright or subject to repurchase, at competitively determined prices that reflect, but are generally lower than, the values those securities would normally command in the private marketplace.

People, Power, and Profits: Progressive Capitalism for an Age of Discontent
by Joseph E. Stiglitz
Published 22 Apr 2019

Those in insurance markets are often related to asymmetries of information, problems of adverse selection (where there are important differences among individuals that firms, whether as employer, lender, or insurer, cannot easily ascertain), and moral hazard (where, for instance, the provision of insurance leads individuals to act in ways that expose the insurance company to more risk, but which the insurance firm cannot monitor and therefore cannot control). The government can avoid, for instance, some of the adverse selection problems because through Social Security it is insuring the entire population. 7.Private programs providing essentially the same services as Medicare have cost as much as 20 percent more.

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Remarkably, a year after the passage of the tax bill, and the enormous giveaway to corporations, not even the stock market was higher, and the CBO was estimating that growth will be slowing to 1.6 percent from 2020 through 2022. See Vox, “Republican Tax Cut Bill One Year Later: What It Did—and Didn’t—Do,” https://www.vox.com/policy-and . . . /tax-cuts-and-jobs-act-stock-market-economy. 17.In the modern literature, these are referred to as the adverse incentive and adverse selection effects of increasing interest rates. See, e.g., Joseph E. Stiglitz and Andrew Weiss, “Credit Rationing in Markets with Imperfect Information,” American Economic Review 71, no. 3 (1981): 393–410. 18.Though it had its origins back in the early 1990s. See Vitaly M. Bord and Joao A. C. Santos, “The Rise of the Originate-to-Distribute Model and the Role of Banks In Financial Intermediation,” Federal Reserve Bank of New York Policy Review, July 2012, 21–34, available at https://www.newyorkfed.org/medialibrary/media/research/epr/12v18n2/1207bord.pdf. 19.The role of reserves can be seen quite simply.

SuperFreakonomics
by Steven D. Levitt and Stephen J. Dubner
Published 19 Oct 2009

There was, for instance, the fellow back in Texas who still flew her in regularly and asked her to incorporate some devices he kept in a briefcase in a session most people wouldn’t even recognize as sex per se. But she categorically insists that her clients wear a condom. What if a client offered her $1 million to have sex without a condom? Allie pauses to consider this question. Then, exhibiting a keen understanding of what economists call adverse selection, she declares that she still wouldn’t do it—because any client crazy enough to offer $1 million for a single round of unprotected sex must be so crazy that he should be avoided at all costs. When she started out in Chicago, at $300 an hour, the demand was nearly overwhelming. She took on as many clients as she could physically accommodate, working roughly thirty hours a week.

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SEARCHABLE TERMS Note: Entries in this index, carried over verbatim from the print edition of this title, are unlikely to correspond to the pagination of any given e-book reader. However, entries in this index, and other terms, may be easily located by using the search feature of your e-book reader. Aab, Albert, 59 Abbott, Karen, 24 abortion, 4–5 accidental randomization, 79 Adams, John, 83 adverse selection, 53 Afghanistan, 65, 87 Africa, HIV and AIDS in, 208–9 Agricultural Revolution, 141–42 agriculture, and climate change, 166 air travel, and terrorism, 65–66 air bags, for automobiles, 150 Al-Ahd (The Oath) newsletter, 62 al Qaeda, 63 Allgemeine Krankenhaus (General Hospital), Vienna, 134–38, 203–4 Alliance for Climate Protection, 170 Allie (prostitute), xvi-xvii, 49–56 Almond, Douglas, 57, 58–59 altruism and anonymity, 109, 118 and charitable giving, 106–7 and climate externalities, 173 and economics, 105,106–23 effect of media coverage on, 107 experiments about, 106–23 games about, 108–11,113,115,117, 118–20 and Genovese murder, 97–100, 104–5,106,110,125–31 impure, 124–25 and incentives, 125, 131 List’s experiments about, 113–20, 121, 123, 125 and manipulation, 125 and monkey-monetary exchange experiment, 215 and people as innately altruistic, 110–11, 113 and taxes, 124 warm-glow, 124–25 Amalga program, 73–74 Ambrose, Stanley, 189 American Civil Liberties Union (ACLU), 101 Americans with Disabilities Act (ADA), 139 ammonium nitrate, 142, 160 An Inconvenient Truth (documentary), 170, 181 The Andy Griffith Show (TV), 104 aneurysms, repair of, 179–80 animals, emissions of, 166, 167–68 annuities, 82 antimicrobial shield, 207 apathy, and Genovese murder, 99–100, 125–31 Apni Beti, Apna Dhan (“My Daughter, My Pride”) project, 5–6 Arbogast, Jessie, 14, 15 Archimedes, 193 Army Air Forces, U.S., 147 Athabasca Oil Sands (Alberta, Canada), 195 athletes birthdays of, 59–60 women as, 22 automobiles air bags for, 150 and cheap and simple fixes, 146–58 children in, 150–58 crash-test data for, 153–55 as replacement for horse, 10–11 seat belts for, 148,149–58 stolen, 173–75 autopsies, 137–38,140, 203 Auvert, Bertran, 208 Azyxxi program, 73 baby boom, and crime, 102 banks, and terrorism, 90–96 Barres, Ben (aka Barbara Barres), 47–48 baseball, drug testing in, 92 baseball cards, experiment about, 115–17, 121 Baseball Hall of Fame, and life span, 82 Bastiat, Frédéric, 31 Bateson, Melissa, 122 Becker, Gary, 12–13, 105, 106, 113, 124 behavior Becker’s views about, 12 collective, 203 data for describing, 13–14 difficulty of changing, 148–49, 173, 203–9 of doctors, 203–8 influence of films on, 15 irrational, 214 predicting, 17 rational, 122–23, 213–14 for self-welfare, 208–9 typical, 13–14, 15–16 behavioral economics, 12–13, 113–23.

Profiting Without Producing: How Finance Exploits Us All
by Costas Lapavitsas
Published 14 Aug 2013

Consequently the relationship between borrower and lender takes the contractual form of the lender advancing money to the borrower for a given period of time in exchange for a proportionately fixed share of the proceeds from the project (interest).8 The lender must also practise information collection and monitoring of the borrower in order, first, to minimize the chances of the borrower undertaking fraudulent or careless action (moral hazard) and, second, to avoid attracting disproportionate numbers of poor quality borrowers (adverse selection). The outcome of moral hazard and adverse selection could be the rationing of credit actually provided by lenders, and hence the failure of credit markets to clear.9 In this light, banks and other financial institutions are providers of services that presumably improve the efficiency of the interaction between borrowers and lenders.

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Market-conforming regulation of finance has drawn ideological sustenance from the new microeconomics of finance stressing information-theoretic, principal–agent analysis of financial institutions, discussed in Chapter 5 and elsewhere in this book. Information asymmetries between lender and borrower could presumably lead to problems of adverse selection and moral hazard, thus resulting in suboptimal results in financial markets, including failure of markets to clear. Consequently, they provide grounds for market-conforming regulation of finance, advocated even by some who have been generally critical of financial liberalization.17 Contrary to the practices of the immediate post-war years, market-conforming regulation has not been based on the assumption that freely operating financial markets could be inimical to growth and accumulation.

The Fissured Workplace
by David Weil
Published 17 Feb 2014

First, it is costly for the principal to gather information about the agents in selecting across them: some agents may have qualities that might undermine the objectives of the principal. If the characteristics of the agent are particularly hard (costly) to see, the agents who approach the principal first might be the ones who in fact the principal wants to avoid. This issue, called adverse selection, can be alleviated the more the principal can make informed decisions about the agents it chooses.56 The second problem arises from the cost of observing the agent once hired. Many of the activities that the principal wants the agent to undertake are hard to observe directly (our discussion of employment picked up this problem in regard to setting wages).

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Cascom Inc. et al., Civil Action No. 3:09-cv-00257, U.S. District Court, Southern District of Ohio, Western Division at Dayton. 67. There is a theoretical literature on the optimal structure for subcontracting, where different organizational forms are employed by a principal in order to maximize profits while dealing with the problems of adverse selection and collusion among the potential agents. Mookherjee and Tsumagari (2004) show that the organizational form that best serves the principal’s interests is affected by the degree of collusion among the agents, the information possessed by the middleman, and the type of service provided by the agents (in particular, whether they are substitutes or complements). 6.

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I am deeply grateful for the assistance, comments, critiques, and insights from all of the above. But to return full circle to the loneliness of writing a book on your own, I am solely responsible for any errors that remain. Index ABM Industries, 56, 133 Abraham, Katherine, 90, 314n36 Accounting, and outsourcing, 52, 54–55 Adverse selection, 63 Aetna, 39 Affordable Care Act (2010), 309n3 Agriculture industry: and offshoring, 169; enforcement in, 217–219, 351n12; definition of establishment in, 218; competitive forces, 259–260; and labor standards, 260 Ahn, Sarah, 256 Airstream, 53 Akerson, Dan, 74 ALT Inc., 109–112 Americans with Disabilities Act, and notification about employee rights, 252 A&P, 28–30, 294n4 Apparel industry: and offshoring, 172; in Bangladesh, 176; enforcement in, 224–228; and lean retailing, 225–226; supply chain approach, 226–228; compliance with labor standards, 226, 228 Apple Inc., 7–8, 171–175, 234, 302n27; and core competencies, 50–51; and Foxconn, 174–175 Asian American Hotel Operators Association (AAHOA), 257–258, 363n28 A.

The Case Against Education: Why the Education System Is a Waste of Time and Money
by Bryan Caplan
Published 16 Jan 2018

It wants outstanding conformists.2 ALAN: Adverse selection, eh? If you were right, labor markets would have sorted out this problem ages ago. BRYAN: Really? Last time I checked, you still believed ten million able-bodied workers were involuntarily unemployed. Have labor markets suddenly sorted out the problem of mass joblessness? ALAN: [sigh] Even well-qualified unemployed workers have a devil of a time convincing employers they’re worth hiring. BRYAN: Now you’re appealing to adverse selection . . . not that there’s anything wrong with that. If adverse selection can prevent able-bodied workers from getting a job at all, why can’t it prevent talented workers from getting good jobs without impressive credentials?

Rethinking the Economics of Land and Housing
by Josh Ryan-Collins , Toby Lloyd and Laurie Macfarlane
Published 28 Feb 2017

Under such circumstances, it becomes difficult for the bank to estimate an interest rate that comfortably reflects the (unknowable) risk associated with the loan. An interest rate that covers this type of risk is likely to be very high and may lead to many reliable borrowers being priced out and only people with very high risk tolerance – ‘gamblers’ – choosing to take out loans. This problem is known as ‘adverse selection’ in the economics literature (Akerlof, 1970). Instead of using interest rates to determine borrowing decisions, the evidence suggests banks simply ration their lending quantitatively according to other criteria (Werner, 2005, pp. 194–196). The decision to extend a loan for house purchase then becomes subject to a number of more idiosyncratic variables not related to the price of credit but often related to the borrower’s circumstances.

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Financial Times, 9 September. World Bank. 1993. The East Asian Miracle, Economic Growth and Public Policy. Oxford: Oxford University Press. INDEX Note: Page numbers followed by n indicate a footnote with relevant number; page numbers in italic refer to figures and those in bold to tables. Addison Act (1919), 78 adverse selection, 127 affordable housing: capital grants, 34; housing investment bank proposal, 209–10; need for public investment, 222–3; planning permission conditionalities, 33, 93–6, 216; public corporations’ investment levels, 220–1; see also social housing age, and net property wealth, 181–2, 181 agricultural land, 9, 61, 68, 69, 122–3 agricultural tariffs, 43 agriculture: common agricultural policy, 33, 122–3; increase in productivity, 68 Alliance and Leicester, 139 Aquinas, Thomas, 16 Arkwright, Richard, 71 armed forces, demobilisation, 78, 79 Association of Residential Letting Agents (ARLA), 134 Assured Shorthold Tenancy, 89 Australia: house price to income ratio, 112, 114; land value taxes, 204–5; mortgage market structure, 156 Bank of England, 210 banks/banking: alternatives to bank debt financing, 211–12; business relationship banking, 208–9; credit and money creation, 115, 206–7; housing investment bank proposal, 209–10; incentives for non-property lending, 206–8; income from mortgage interest, 61; international regulation, 135; land as lending collateral, 7, 55, 127–8; land-related credit creation, 8, 114–19, 190–1, 222; lending by industry sector, 118–19, 118; lending relative to GDP, 117–18, 117; leverage, 184; macroprudential policy, 206; minimum deposit requirements (corset controls), 132, 155; money supply, 115; regulating property-related credit, 154–5; securitisation, 135–42, 156–7, 156; structural reform recommendations, 208–9; wholesale money markets, 131, 139 Basel Accord (Basel I), 135 basements, 57, 57n16 Bath, 71 Belgium, mortgage market structure, 156 Bradford and Bingley, 139 Bretton Woods system, 83 Brighton, 71 building societies: demutualisation, 134–5, 136; effect of mortgage funding deregulation, 132–3; emergence, 72, 128; favourable tax regime, 132; history, 129; interest rate cartel, 130, 132; mergers and acquisitions, 136; mortgage funding arrangements, 131; stability, 129–30, 132, 158 Building Societies Act (1986), 133 buy-to-let (BTL): increase, 7, 184; mortgages, 122, 134; overseas investors, 100, 160; tax relief, 62, 86, 160 Cadbury, George, 71 Canada, mortgage market structure, 156 capital: conflated with land, 48–52, 62; definition, 37–8; differences between land and capital, 51–7; differences between wealth and capital, 170–1; factor in production, 37–8 capital gains tax: for buy-to-let landlords, 62; definition, 85–6; exemption for primary residencies, 85–6, 104, 202 capital goods depreciation, 52–3 capital investment, 56 Capital Markets Union (CMU), 141 capitalism: Golden Age, 83; land as private property, 36; Primitive Accumulation concept, 18 Cerberus Capital Management, 136, 137 cholera, 70, 73 Churchill, Winston, 76–7, 189 Clark, John Bates, 48–51, 57–9 classical economics, 17, 38, 45, 48, 70 co-ownership housing, 72, 86 coal industry, 69 collateral: commercial real estate, 148; land as, 7, 20–1, 127–8, 160; see also home equity withdrawal collectivisation, 43 commercial real estate (CRE), 148–50; bank lending, 118–19, 118, 130, 148; credit bubbles and crises, 111, 148–9; data sets, 63; effect of UK vote to leave EU, 150; foreign investment, 149; investment returns, 148, 149–50; and Japanese crisis, 151–3; rating lists, 202; time-limited leases, 214 common agricultural policy, 33, 122–3 communications technology, 9 Community Land Trusts, 72, 198–9, 214, 221 commuting, 27 Competition, Credit and Control Act (1971), 130 compulsory purchase: ‘hope value’ court judgments, 88; housing construction, 80–1; infrastructure projects, 31, 73, 196–7, 222 conservation areas, 32 construction industry see housing construction industry consumption: affected by house deposit saving, 145; and asset-based wealth, 123–4; consumption-to-income ratio trends, 143–4, 144; equity release and consumer demand, 145–7, 146; and house prices, 147; and inequality, 185–7 cooperative housing, 72, 215 Corn Laws, 43, 69–70 corporate income tax, 168–9 council tax, 104, 201, 202 credit conditions index, 143–4, 144 credit controls, 132 credit liberalisation, 144 Crown Estate, 19, 31 Darrow, Charles, 47 de Soto, Hernando, 21 debt, public sector debt, 219–21 debt-to-income ratio, 115–16, 116, 139, 159, 186 defaults, mortgage lending, 141 deindustrialisation, 168 Denmark: land value taxes, 204; size of new-builds, 97 developing economies, and private property, 21–2 development charge, 82 digital economy, 9 Eastern Europe, serfdom, 23–4 Eccles, Marriner, 186–7 economic growth: dependence on land values, 190–1; and homeownership, 21–2 economic modelling, 50–1, 155, 218 economic rent: Crown Estate, 31; determined by collective rather than individual investment, 40; financial sector, 44, 184; infrastructure projects, 194–5, 196–7; and land, 39–44, 56–7; and land taxes, 34–5, 45–8, 76–7, 199, 222; and landownership, 10–13, 25; oil sector, 44; urban areas, 41–2, 73–4 economic theory: landownership, 16–18; marginal productivity theory, 49–50, 51, 56, 57–9, 165–7; shortcomings, 64–5, 191–2, 217; teaching reform proposals, 218 Edinburgh New Town, 66, 71, 80 eminent domain theory, 16 Enlightenment, 16 equity release see home equity withdrawal European Investment Bank, 210 European Union: Capital Markets Union (CMU), 141; common agricultural policy, 33, 122–3; full-recourse mortgage loans, 141–2; government debt, 220; UK decision to leave, 150, 160 Eurostat, 64, 219 factory workers, accommodation, 71 feudal system, 18, 19, 32 financial crisis (2007-8): causes, 153–4, 159–60, 186–7; effect on mortgages, 100; and house and land prices, 101, 140; Northern Rock, 136–7; payment defaults, 123; UK banking collapse, 139–40 financial instability, 152–3, 154–5, 185–7 Financial Policy Committee, 155, 206 financial sector: economic rent, 44, 184; profitability, 184; reform proposals, 205–12; see also banks/banking financialisation, 120; declining wage share in national income, 169; land, 14, 110–12; land and property, 160 First World War, 77 Fisher, Irving, 152 Florida, credit-driven bubbles, 111 foreign exchange controls, 132 France: feudal system, 32; Livrét A accounts, 210; mortgage market structure, 156; private tenancy, 32; residential property wealth, 9, 10 French Physiocrats, 38 Friedman, Milton, 87 Garden City movement, 72, 75–6 GDP: and bank lending by sector, 118–19, 118; and declining wage share, 169; and domestic mortgage lending, 118, 156–8, 156; and home equity withdrawal, 146; and household debt, 151; and outstanding credit loans, 117; and property wealth, 9–10, 10 George, Henry, 12, 25, 34, 45, 58, 60–1, 76, 87, 199; Progress and Poverty, 40–1, 46–7 Germany: business relationship banking, 208–9; credit controls, 207; economic success and low homeownership, 215; house price to income ratio, 112, 114; mortgage market structure and homeownership, 156, 157–8; private tenancy, 32 Gini coefficient, 163, 177, 178 globalisation, 167–8, 169 Great Depression, 186–7 Great Moderation, 154, 191 Grotius, Hugo, 16 Halifax Bank of Scotland (HBOS), 139 health problems, and inequality, 185 help-to-buy schemes, 122 Henry VIII, King, 20 high-rise buildings, 57 Hill, Octavia, 71 home equity withdrawal: contribution to consumer demand, 145–7, 146; and financial crisis, 187; and living standards, 180; and mortgage market structure, 156–7, 156; to finance consumer goods, 127, 133 homeownership: benefits, 101; difficulties in saving for, rent trap, 106; downward trend, 83, 103, 178; as financial asset, 63; housing costs, 179; increased unemployment and reduced labour mobility, 27–8, 215; interwar growth, 78; investment opportunity, 92; low-supply equilibrium, 102; and mortgage market structure, 156–8, 156; mutual co-ownership, 86; political and electoral dominance, 24–5, 92; Right to Buy policy, 89, 90–1, 103; rise in 1970s/80s, 86; second homes, 160; trends, 106–7, 107 Hong Kong, Mass Transit Railway, 195 house building see housing construction industry house prices: boom and bust, 88, 99; and consumer demand, 147; and credit availability, 116–18; financial crisis collapse, 140; and growing inequality, 177–8; house price-credit feedback cycle, 119–24; increase with buy-to-let mortgages, 134; low-supply equilibrium, 102; negative equity, 123, 133–4; price-to-income ratios, 99, 100, 112–14, 114, 139, 183, 183; and real disposable income, 115–16, 116; replacement cost vs market price, 6; rise due to insufficient supply, 63; volatility, 8, 8, 112–14, 114; volatility reduced by land taxes, 200 Housing Act (1924), 78 Housing Act (1980), 89 Housing Act (1988), 89 housing associations, 72, 82, 83, 93 housing benefit, 34, 96, 106 housing construction industry: barriers to entry, 97; building clubs, 72; compulsory land purchase, 80–1; concentration, 96–7; costs, 8, 95; development charge, 82; effect of financial crisis, 101; land banks (with planning permission), 96–7, 101; peak, 82; poor design quality, 97; private house building, 78; size trends, 97; speculative house building, 93, 94–5, 96; trends, 82–5, 82, 83 housing costs: by tenure type, 179; and inequality, 179–80 housing demand, 63, 114 Housing, Town Planning, &c.

The End of Accounting and the Path Forward for Investors and Managers (Wiley Finance)
by Feng Gu
Published 26 Jun 2016

Competition, particularly in the consumer segment of the business is fierce, evidenced by the substantial amount spent by insurance companies on advertising (Geico’s gecko, Progressive’s Flo). There are several large but not dominant firms in the industry (State Farm, Geico, Allstate). Insurers face two major issues: in the economists’ parlance, adverse selection and moral hazard. The former refers to the tendency of individuals or companies with high risk (e.g., seriously ill people) to obtain more coverage than low-risk persons, and the latter refers to the tendency of the insured to engage in riskier behavior (neglect house maintenance) relative to uninsured, and, at the extreme, to fake claims.

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Other strategic assets are brands (Allstate’s Esurance), intellectual property (patents on new products, like Snapshot, Progressive’s plugged-in-the-car device to track individual driving behavior and offer personalized premiums), and dedicated, productive agents. Back to customers. What are the “right” customers assuring sustained competitive advantage? These are persons with low adverse selection and moral hazard (defined earlier), namely, low-risk (safe drivers), and careful (property maintaining) customers. Successful strategy (referred to as book management) is aimed at targeting such customers (Hartford, for example, teamed Strategic Resources & Consequences Report: Case No. 2 149 up with AARP, the dominant retirees association, to market insurance to AARP members—older people are, on average, conscientious, low-mileage drivers, carefully maintaining their cars), and holding on to them as long as possible with attractive rates and good customer relations (claims management).

Principles of Corporate Finance
by Richard A. Brealey , Stewart C. Myers and Franklin Allen
Published 15 Feb 2014

For example, disputes about the liability for environmental damage can eat up millions of dollars in legal fees. Insurance companies need to recognize these costs when they set their premiums. • Reason 2: Adverse selection. Suppose that an insurer offers life insurance policies with “no medical exam needed, no questions asked.” There are no prizes for guessing who will be most tempted to buy this insurance. Our example is an extreme case of the problem of adverse selection. Unless the insurance company can distinguish between good and bad risks, the latter will always be most eager to take out insurance. Insurers increase premiums to compensate or require the owners to share any losses

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It repurchased the building one year later for £838 million. 2The market for used cars suffers from a “lemons” problem, since the seller typically knows more about the quality of the car than the would-be buyer. Because off-lease used cars are generally of above-average quality, leasing can help to alleviate this problem. Igal Hendel and Alessandro Lizzeri argue that this may help to explain the prevalence of car leasing. See I. Hendel and A. Lizzeri, “The Role of Leasing under Adverse Selection,” Journal of Political Economy 110 (February 2002), pp. 113–143. Thomas Gilligan uses a similar argument to analyze the market for aircraft leasing. See T. W. Gilligan, “Lemons and Leases in the Used Business Aircraft Market,” Journal of Political Economy 112 (2004), pp. 1157–1180. 3For evidence that leasing is relatively more common in such firms, see J.

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“Shh,” replied the other, “that’s tomorrow night.” The story is an example of another problem for insurers, known as moral hazard. Once a risk has been insured, the owner may be less careful to take proper precautions against damage. Insurance companies are aware of this and factor it into their pricing. The extreme forms of adverse selection and moral hazard (like the fire in the farmer’s barn) are rarely encountered in professional corporate finance. But these problems arise in more subtle ways. That oil platform may not be a “bad risk,” but the oil company knows more about the platform’s weaknesses than the insurance company does.

Radical Markets: Uprooting Capitalism and Democracy for a Just Society
by Eric Posner and E. Weyl
Published 14 May 2018

This is how George, Jevons, and Walras used the term, but contemporary usage in economics breaks the problem into many components. We highlighted one emphasized by Myerson and Satterthwaite, but other economists have given other reasons why assets are not passed on to their best use. As we will see, a COST alleviates all these problems simultaneously. One such problem is what economists call “signaling” or “adverse selection,” concepts for which economists George Akerlof and A. Michael Spence were awarded the Nobel Prize.51 The possessor of an asset, such as a used car, often knows the quality of the asset better than a potential purchaser. The possessor may thus demand a high price for the car not only because she guesses the buyer may be willing to pay it, but also because a high price signals she is reluctant to part with it, a ploy to convince the buyer the car must be valuable.

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Chad Syverson, Market Structure and Productivity: A Concrete Example, 112 Journal of Political Economy 1181 (2004); Syverson, Product Substitutability and Productivity Dispersion, 86 Review of Economics and Statistics 534 (2004); Syverson, What Determines Productivity, 49 Journal of Economic Literature 326 (2011). Not all of this misallocation is due to the monopoly problem in its simplest form. However, as we discuss below, many other problems that cause misallocation (adverse selection, endowment effects, and credit constraints) are also addressed by partial common property. We thus believe much of this misallocation can be addressed by a COST and related reforms. 8. Gareth Stedman Jones, Karl Marx—Greatness and Illusion (Belknap Press, 2016). 9. Michael Kremer, The O-Ring Theory of Economic Development, 108 Quarterly Journal of Economics 551 (1993), provides a definitive account of how large-scale enterprises typically must overcome monopoly problems. 10.

Basic Economics
by Thomas Sowell
Published 1 Jan 2000

Since the whole point of buying insurance is to reduce risk, the cost of the insurance has to be less than the cost of the uninsured risk. Therefore the cost of producing the insured product is less than the cost of producing the product without insurance, so that the price tends to be lower than it would be if the risk had to be guarded against by charging higher prices. “Moral Hazard” and “Adverse Selection” While insurance generally reduces risks as it transfers them, there are also risks created by the insurance itself. Someone who is insured may then engage in more risky behavior than if he or she were not insured. An insured motorist may park a car in a neighborhood where the risk of theft or vandalism would be too great to risk parking an uninsured vehicle.

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What if people who work in and around water are more likely to come down with this disease than people who work in dry, air-conditioned offices? Then fishermen, lifeguards and sailors are more likely to buy this insurance coverage than are secretaries, executives, or computer programmers. People living in Hawaii would be more likely to buy insurance coverage for this disease than people living in Arizona. This is known as “adverse selection” because statistics on the incidence of disease X in the population at large may seriously under-estimate its incidence among the kinds of people who are likely to buy insurance coverage for a disease that is more likely to strike people living or working near water. Although determining costs and probabilities for various kinds of insurance involve complex statistical calculations of risk, this can never be reduced to a pure science because of such unpredictable things as changes in behavior caused by the insurance itself as well as differences among people who choose or do not choose to be insured against a given risk.

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The power of government can be used to forbid some dangerous behavior, such as storing flammable liquids in schools or driving on tires with thin treads. This limits “moral hazard”—that is, how much additional risky behavior and its consequent damage may occur among people who are insured. Forcing everyone to have a given kind of insurance coverage, such as automobile insurance for all drivers, likewise eliminates the “adverse selection” problem. But government regulation of the insurance industry does not always bring net benefits, however, because there are other kinds of government regulation which increase risks and costs. During the Great Depression of the 1930s, for example, the federal government forced all banks to buy insurance that would reimburse depositors if their bank went bankrupt.

State-Building: Governance and World Order in the 21st Century
by Francis Fukuyama
Published 7 Apr 2004

The reason that hierarchical firms existed, according to Alchian and Demsetz, was because of the problem of monitoring joint output in which it was difficult to disentangle the relative contributions of a number of employees. Monitoring difficulties opened up the possibility for shirking and allowed organizational theory to incorporate the concept of adverse selection originally laid out by Akerlof (1970). That is, in a joint-output situation the individual worker has better information about his or her individual contribution than a third party, which could be manipulated to the worker’s advantage. Controlling this shirking behavior through monitoring and incentives was argued to be easier in a firm than in an arms-length contracting relationship.

Topics in Market Microstructure
by Ilija I. Zovko
Published 1 Nov 2008

They note that the number of orders placed up to five quotes away from the market decay monotonically but do not attempt to estimate the distribution or examine orders placed further then five best quotes. Our analysis looks at the price placement of limit orders across a much wider range of prices. Since placing orders out of the market carries execution and adverse selection risk, our work is relevant in understanding the fundamental dilemma of limit order placement: execution certainty vs. transaction costs (see, e.g., Cohen, et al. (1981); Harris (1997); Harris and Hasbrouck (1996); Holden and Chakravarty (1995); Kumar and Seppi (1992); Lo, et al. (2002)). In addition to the above, our work relates to the literature on clustered volatility.

Red-Blooded Risk: The Secret History of Wall Street
by Aaron Brown and Eric Kim
Published 10 Oct 2011

GNMAs were redeemed as homeowners repaid their mortgages (or defaulted on them, in which case the security holder was paid from proceeds of the foreclosure sale or by the government). Mortgages paid off on average in about seven years, one way or the other. Some people pay off their mortgages early because times are good, but most of the repayments occur when someone moves or refinances a home. The problem for the security holder was not just uncertainty. There was adverse selection. If interest rates went down, lots of people would refinance at the lower rates, and the security holders would get back money they had to reinvest at the new lower rates. But if interest rates went up, few people would refinance, and the security holders would get back less than the expected cash flows, at a time when they wanted to take advantage of the higher rates.

…

If you’re not familiar with that, it offers real money small bets on various issues like election results, weather, movie grosses, and so on. But I would allow students to bet play money at the mid of the bid and ask prices. This is a huge advantage; if you bet real money you either have to pay the ask or receive the bid, or else work your order, which opens you up to the possibility of adverse selection (that is, no one will hit your bid unless you set it too high). It’s not too hard to win playing this way. Students would have to double the play money by the end of the quarter, or start over the next quarter with a new play $1,000. One successful doubling and you’re done. But if you haven’t succeeded by graduation, no degree.

The Little Book of Common Sense Investing: The Only Way to Guarantee Your Fair Share of Stock Market Returns
by John C. Bogle
Published 1 Jan 2007

Yes, during the past 25 years, while the S&P 500 Index was providing an annual return of 9.1 percent and the average equity fund was earning an annual return of 7.8 percent, the average fund investor was earning only 6.3 percent a year. The dual penalties of costs and investor behavior. Compounded over the full period, the 1.5 percent annual penalty incurred by the average fund because of costs was huge. But the dual penalties of faulty timing and adverse selection made it even larger. Exhibit 7.1 shows that $10,000 invested in a low-cost S&P 500 index fund in 1991 earned a nominal (before-inflation) profit of $77,000. The average equity fund earned a profit of just $55,500—72 percent of what was there for the taking. The compound return earned by the average fund investor tumbled to $36,100, less than 50 percent of the $73,100 return earned by investors in the simple index fund.

On the Edge: The Art of Risking Everything
by Nate Silver
Published 12 Aug 2024

You’ll see a line that looks favorable, and you’d like to do some due diligence on it—maybe there’s an injury that you weren’t aware of? But a good line may go away after even five or ten seconds. And if the line is still available, it may not be such a great bet after all. This is what economists call “adverse selection”—if you’re being offered to buy a bet at a price that seems too good to be true, you have to ask why the sportsbook is willing to sell it to you. I hadn’t realized how much injuries—and other situations where you can get a leg up through inside information—can dominate other concerns. This issue is particularly important in basketball, a sport where star players have a disproportionate impact.

…

Action: A robust gambling term: (1) a lucrative or high-stakes but risky opportunity (“Where the action is”); (2) a synonym for loose, aggressive play (“He’s an action player”); (3) having a bet at stake (“She has action on the Bengals”); (4) when it’s your turn to act in poker (“The action’s on you, sir”). Advantage play: Being +EV at a casino game like slots that typically has a house edge. Adverse selection: An asymmetry in which one party to a transaction has more information and takes advantage of it. Or informally, getting more action from customers you don’t want, such as an all-you-can-eat sushi restaurant that sets up shop near a sumo wrestling tournament. Agency: As defined more completely in chapter ∞, being empowered to make robust, well-informed decisions; knowing which factors are inside one’s control.

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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z A abstraction, 23–24, 29, 30–31, 130, 477 academia, 26, 27, 28, 294–96 See also Village accelerationists, 31, 250, 411–13, 455–56, 477, 539n accelerators, 405–6, 477 action, 477 adaptability, 235–37, 264 addiction, 164–65, 166, 167, 168–69, 213–14, 321 Addiction by Design: Machine Gambling in Las Vegas (Schüll), 154–55 Adelson, Sheldon, 146 Adelstein, Garrett, 100, 102, 106 Robbi hand, 80–86, 89, 117, 123–29, 130, 444–45, 512n advantage play, 158–61, 478 adverse selection, 478 Aella, 375–77 Age of Em, The (Hanson), 379 agency, 453, 469–70, 478 agents, 478 aggressiveness, 120 AGI (artificial general intelligence), defined, 478 Aguiar, Jon, 199 AI (artificial intelligence) accelerationists, 31, 250, 411–13, 455–56, 477, 539n adaptability and, 236n agency and, 469–70 alignment and, 441–42, 478 Sam Altman and, 406 analogies for, 446, 541n bias and, 440n breakthrough in, 414–15 commercial applications, 452–53 culture wars and, 273 decels, 477 defined, 478 economic growth and, 407n, 463–64 effective altruism and, 21, 344, 348, 355, 359, 380 engineers and, 411–12 excitement about, 409–10 impartiality and, 359, 366 moral hazard and, 261 New York Times lawsuit, 27, 295 OpenAI founding, 406–7, 414 optimism and, 407–8, 413 poker and, 40, 46–48, 60–61, 430–33, 437, 439, 507n poor interpretability of, 433–34, 437, 479 prediction markets and, 369, 372 probabilistic thinking and, 439 randomization and, 438 rationalism and, 353, 355 regulation of, 270, 458, 541n religion and, 434 risk impact and, 91 risk tolerance and, 408 River-Village conflict and, 27 SBF and, 401, 402 sports betting and, 175–76 technological singularities and, 449–50, 497 transformers, 414–15, 434–41, 479, 499 Turing test and, 499 See also AI existential risk AI existential risk accelerationists and, 412–13, 455–56, 539n alignment and, 441 arguments against, 458–60 Bid-Ask spread and, 444–46 commercial applications and, 452–53 Cromwell’s law and, 415–16 determinism and, 297 effective altruism/rationalism and, 21, 355, 456 EV maximizing and, 457 excitement about AI and, 410 expert statement on, 409, 539n Hyper-Commodified Casino Capitalism and, 452–53 instrumental convergence and, 418 interpretability and, 433–34 Kelly criterion and, 408–9 models and, 446–48 Musk and, 406n, 416 optimism and, 413–14 orthogonality thesis and, 418 politics and, 458, 541n prisoner’s dilemma and, 417 reference classes and, 448, 450, 452, 457 societal institutions and, 250, 456–57 takeoff speed and, 418–19, 498 technological Richter scale and, 450–52, 451, 498 Yudkowsky on, 372, 415–19, 433, 442, 443, 446 Alexander, Scott, 353, 354, 355, 376–77, 378 algorithms, 47, 478 alignment (AI), 441–42, 478 all-in (poker), 478 alpha, 241–42, 478 AlphaGo, 176 Altman, Sam, 401 AI breakthrough and, 415 AI existential risk and, 419n, 451, 459 OpenAI founding and, 406–7 OpenAI’s attempt to fire, 408, 411, 452n optimism and, 407–8, 413, 414 Y Combinator and, 405–6 Always Coming Home (Le Guin), 454–55, 541n American odds, 477, 491 American Revolution, 461 analysis, 23, 24, 478 analytics casinos and, 153–54 defined, 23, 478 empathy and, 224 limitations of, 253–54, 259 politics and, 254 sports betting and, 171, 191 venture capital and, 249 anchoring bias, 222n, 478 Anderson, Dave, 219–20, 230, 231 Andreessen, Marc accelerationists and, 411 AI analogies and, 446, 541n AI existential risk and, 446 Adam Neumann and, 281–82 on patience, 260 politics and, 267–68 River-Village conflict and, 295 techno-optimism and, 249, 250–51, 270, 296, 498 VC profitability and, 293, 526n VC stickiness and, 290, 291–92 angles, 192–94, 235–36, 305, 478 angle-shooters, 478 ante (poker), 478 anti-authority attitude, 111–12, 118, 137 See also contrarianism apeing, 479 arbitrage (arb), 171, 172–74, 206, 478, 489, 516n, 517n Archilochus, 236, 263, 485 Archipelago, The, 22, 310, 478 arms race, 478 See also mutually assured destruction; nuclear existential risk art world, 329–30, 331n ASI (artificial superintelligence), 478 Asian Americans, 135–36, 513n See also race asymmetric odds, 248–49, 255, 259, 260–62, 276, 277 attack surfaces, 177, 187, 478 attention (AI), 479 attention to detail, 233–35 autism, 282–84, 363, 525n B back doors, 479 backtesting, 479 bad beats, 479 “bag of numbers,” 433, 479 bank bailouts, 261 Bankman, Joseph, 383–84 Bankman-Fried, Sam (SBF) AI and, 401, 402 angles and, 305 attitude toward risk, 334–35 bankruptcy and arrest of, 298–301, 373–74 cryptocurrency business model and, 308–9 cults of personality and, 31, 338–39 culture wars and, 341n as dangerous, 403–4 disagreeability and, 280 effective altruism and, 20, 340–42, 343, 374, 397–98, 401 as focal point, 334 fraud and, 124, 374 Kelly criterion and, 397–98 moral hazard and, 261 NOT INVESTMENT ADVICE and, 491 personas of, 302 politics and, 26, 341n, 342 public image of, 338 responses to bankruptcy and arrest, 303–5, 383–85, 386–88 risk tolerance and, 334–35, 397–403, 537–38n River and, 299 theories of, 388–96 trial of, 382–83, 385–86, 387, 403 utilitarianism and, 360, 400, 402–3, 471, 498 venture capital and, 337–39 warning signs, 374 bankrolls, 479 Baron-Cohen, Simon, 101n, 283, 284 Barzun, Jacques, 466 baseball, 58–59, 174 See also sports betting base rates, 479 basis points (bips), 479 basketball, 174 See also sports betting Bayesian reasoning, 237, 238, 353, 355, 478, 479, 493–94, 499 Bayes’ theorem, 479 beards, 207–8, 479 See also whales bednets, 479 Bennett, Chris, 177, 178 Bernoulli, Nicolaus, 498 Betancourt, Johnny, 332–33 bet sizing, 396, 479 Bezos, Jeff, 277, 410 Bid-ask spread, 444–46, 479 Biden, Joe, 269, 375 big data, 432–33, 479 Billions, 112 Bitcoin bubble in, 6, 306, 307, 307, 310, 312 creation of, 322–23, 496 vs.

The End of Loser Liberalism: Making Markets Progressive
by Dean Baker
Published 1 Jan 2011

This reduction in interest rates would be almost fully offset by an increase of approximately 8 percent in average home prices, leaving typical homeowners paying almost the same amount in their monthly mortgage payment. The analysis didn’t show the full economic effects of this subsidy, but higher home prices would be expected to lead to more consumption through the wealth effect, implying reduced investment and slower growth. [91] This is in addition to the payment reductions associated with adverse selection, where insurers reduce annual payments under the assumption that people who buy annuities have longer life expectancies than the population as a whole. [92] It can also be made a default option in which a portion of workers’ wages (e.g., 3 percent) is put into a savings fund every year, unless the worker opts out.

America's Bitter Pill: Money, Politics, Backroom Deals, and the Fight to Fix Our Broken Healthcare System
by Steven Brill
Published 5 Jan 2015

But to Gruber and most other economists, including some on Obama’s campaign team, as well as the entire insurance industry, the difference between a mandate and no mandate was crucial: If people didn’t have to buy insurance but could instead sign up when they became ill, the resulting wait-until-you-need-it dynamic, which the economists called adverse selection, would cripple the entire scheme. Insurers, faced with insuring a disproportionate number of people who knew they needed it while not collecting premiums from the young and others who thought they didn’t, would have to raise rates to cover the added risk. The inflated rates would, in turn, exacerbate the problem in a vicious downward spiral by discouraging all but the truly ill from signing on to pay the still-higher premiums.

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In states such as Mary Fowler’s Nevada, where insurers were allowed to reject applicants who had preexisting conditions or charge them high prices, people were increasingly going uninsured. Worse, a few states, like New York, had done what Obama was now proposing: force insurers not to discriminate but without an accompanying mandate that everyone had to buy insurance. As a result, insurers in New York—fearful of the adverse selection dynamic, in which only the sick would buy policies—had jacked up premiums to $15,000 to $25,000 a year for families of four. The prices were so out of reach that the market had dwindled almost to extinction. In New York, twenty-six thousand individual policies would be sold statewide in 2010.

Electronic and Algorithmic Trading Technology: The Complete Guide
by Kendall Kim
Published 31 May 2007

While investors may be wrong on the informational value of large block trades, there is also reason to believe that they will be right almost as often. The variables that determine the price impact of trading are the same variables driving the bid-ask spread. The price impact and the bid-ask spread are both a function of the liquidity of the market. The inventory costs and adverse selection problems are likely to be largest for stocks where small trades can move the market significantly. The difference between the price at which an investor can buy the asset and the price at which one can sell, at the same point in time, is a reflection of both the bid-ask spread and the expected price impact of the trade on the asset.

Tyler Cowen-Discover Your Inner Economist Use Incentives to Fall in Love, Survive Your Next Meeting, and Motivate Your Dentist-Plume (2008)
by Unknown
Published 20 Sep 2008

We might buy a warranty on our new kitchen stove to express loyalty to the idea of a secure home, immune from tragedy or catastrophe. Buying insurance is often about image. The data show that the worst drivers are the least likely to have insurance. These people are careless when it comes to driving and buying insurance because that is their self-image. This runs counter to the usual "adverse selection" hypothesis from economics, which predicts-incorrectly-that the best drivers are most likely to forgo insurance because they need it the least. My wife wants to make sure I am not one of these people with a careless or reckless self-image and therefore she expects me to buy lots of insurance.

Do More Faster: TechStars Lessons to Accelerate Your Startup
by Brad Feld and David Cohen
Published 18 Oct 2010

I quickly figured out that I could generate much more interesting deal flow by getting to know other real angel investors and by creating my own independent brand and visibility. It turns out that strong entrepreneurs are pretty good at finding people who actually make angel investments. And it seems to me that people who don't actually make angel investments, but tell the world they do, aren't really serious about it. Adverse selection was plainly evident to me in the angel group meetings I attended because the companies that were pitching typically had been unsuccessful at raising money from committed and professional angel investors. While there were a few exceptions, these companies already had some momentum with their financings and were looking for a few more investors to help them finish up their round.

Wars, Guns, and Votes: Democracy in Dangerous Places
by Paul Collier
Published 9 Feb 2010

If anyone can join Ethnic Politics 53 or leave the insurance group at any time, then it will be in perpetual deficit: people will declare themselves to be members of the community when they fall on hard times and declare themselves fancyfree when things are going well. This is known in economics as the problem of adverse selection: unless insurance companies take care, instead of getting a random selection of clients from the population, they get people who know that they are bad risks. That is why insurance companies use some device for restoring a random selection, such as offering much better terms for all the employees of a firm than they offer to individuals who turn up at the door.

Evil by Design: Interaction Design to Lead Us Into Temptation
by Chris Nodder
Published 4 Jun 2013

Composite graphic of trust logos: top line: eagleamerica.com; bottom line (L to R): thickquick.com, bbb.org, and dogstrainingbook.com. B.J. Fogg’s elements of website credibility: B.J. Fogg. Persuasive Technology. Massachusetts: Morgann Kaufmann, 2003. p. 130. Sites displaying certification are less trustworthy: Benjamin Edelman. Adverse selection in online trust certifications. Proceedings of the 11th International Conference on Electronic Commerce. ACM, 2009. McAfee 12 percent claim: McAfee SECURE Service page (mcafeesecure.com). Retrieved November 2012. Help people complete a set Codecademy coding challenge: codeyear.com/stats.

The Education of a Value Investor: My Transformative Quest for Wealth, Wisdom, and Enlightenment
by Guy Spier
Published 8 Sep 2014

Logically, perhaps, I should switch phone services or load up on their brilliant investment idea. But I just won’t do it. I may miss out in the short term. But over a lifetime I have no doubt that I’ll benefit much more by detaching myself from people with a self-interest in getting me to buy stuff. This is a simple application of “adverse selection.” As Charlie Munger has joked, “All I want to know is where I’m going to die so I’ll never go there.” For me, if an investment is being sold, that’s a place where I certainly want to avoid going. I even apply this rule if I’m at a cocktail party and someone starts telling me about a great stock they own or a private company in which they’d like me to invest.

Humans as a Service: The Promise and Perils of Work in the Gig Economy
by Jeremias Prassl
Published 7 May 2018

Ibid., 130–1. In their worked example of airbnb (a property rental business), they suggest: [delegating] regulatory responsibility relating to information asymmetry to plat- forms like Airbnb (whose interests are naturally aligned with the global aggregation of information and the mitigation of adverse selection and moral hazard), and let [local housing associations] play a key role in the regulation of local externalities, as the guest-noise and strangers-in-the-building externalities are typically local and primarily affect [the association’s] membership. * * * Notes 153 22. Sharing Economy UK, ‘Code of conduct’, http://www.sharingeconomyuk.

Brilliant, Crazy, Cocky: How the Top 1% of Entrepreneurs Profit From Global Chaos
by Sarah Lacy
Published 6 Jan 2011

They wanted to retain control and wanted to make the biggest share of the returns when they hit it big. Because the cost of starting a Web or software company had plummeted some 90 percent since the late 1990s, it was a lot easier to bootstrap something than in the past. So in essence, there was adverse selection, and VCs got stakes in the worst startups, the unproven kids, and the entrepreneurs looking for a flip or quick money acquisition. Similarly, there are a lot of reasons why it makes sense for a founder to take some capital off the table by cashing in shares. It makes the founder more likely to hold out for a big exit than to sel on the cheap early.

When to Rob a Bank: ...And 131 More Warped Suggestions and Well-Intended Rants
by Steven D. Levitt and Stephen J. Dubner
Published 4 May 2015

Another, more recent paper by Finan, Ernesto Dal Bó, and Martín Rossi finds that the quality of civil servants also improves when they are paid more, this time in Mexican cities: We find that higher wages attract more able applicants as measured by their IQ, personality, and proclivity toward public sector work—i.e., we find no evidence of adverse selection effects on motivation; higher wage offers also increased acceptance rates, implying a labor supply elasticity of around 2 and some degree of monopsony power. Distance and worse municipal characteristics strongly decrease acceptance rates but higher wages help bridge the recruitment gap in worse municipalities.

Finding Alphas: A Quantitative Approach to Building Trading Strategies
by Igor Tulchinsky
Published 30 Sep 2019

Because profits include liquidity, the riskiness of the 216 Finding Alphas latter also is included in the price: assets whose spread is highly sensitive to market liquidity shocks have higher risk and therefore yield an expected return premium over those with low sensitivity. Intraday patterns also can be used to estimate the microstructure of assets. Separating the pool of investors into subclasses with different behaviors allows us to detect informed trades and estimate the probability of adverse selection. Liquidity providers lose against informed traders, on average, and therefore require a premium to cover their expenses, which they include in their bid–ask spread quotes. Again, in line with the illiquidity premium, this is reflected in the expected returns of assets; hence, higher levels of informed trading expect excess returns.

Networks, Crowds, and Markets: Reasoning About a Highly Connected World
by David Easley and Jon Kleinberg
Published 15 Nov 2010

It is plausible that workers can affect their productivity by varying the amount of effort that they put into their job, but we will ignore this issue for the sake of the present formulation. Thus, the key issue is point (iv) above, which — as in the case of the used-car market — can be viewed as a problem of adverse selection. The firm cannot select for a population consisting only of high productivity workers; instead, if it hires any workers at all, the only thing it can be sure of is getting those with low productivity. It’s useful to work through the consequences of information asymmetry in the labor market through a simple example, whose structure closely parallels our used-car example.

…

Of course, whether this actually happens depends on the actual numbers: how much it costs to provide the insurance, and how much people value the insurance compared to their alternatives. But just as in our earlier examples, we see how socially undesirable outcomes can occur in the market when there are imbalances in information. The information asymmetry we have focused on in the market for health insurance leads, just as in case of used cars or employment, to a type of adverse selection. Insurance companies cannot select for a population consisting only of healthy individuals; rather, if anyone buys insurance at all, the only thing one can be sure of is that it will be bought by those who are less healthy. There is another type of information asymmetry that occurs in the market for health insurance that we have so far ignored in our discussion.

…

This ability to start over adds a severe moral-hazard feature to the on-line transaction problem, just like the ability of an individual to affect his health status adds a moral-hazard component to health insurance. This makes the problem of creating a reliable reputation system more difficult than it would be if there were only an adverse-selection problem. In addition, the design of a reputation system is further complicated by the potential for other kinds of misleading seller behavior. In particular, a seller can operate several identities simultaneously, and have the different identities engage in transactions with one another purely for the purpose of having them lavish positive feedback on each other.

Expected Returns: An Investor's Guide to Harvesting Market Rewards
by Antti Ilmanen
Published 4 Apr 2011

For example, high levels of disagreement and short-selling constraints together predict relatively low equity returns because overvalued stocks cannot be shorted and tend to be held by the most optimistic investors. Asymmetric information refers to situations in which one party is better informed than the other, leading to so-called principal–agent problems (including moral hazard, adverse selection, conflict of interest). Vayanos–Woolley (2010) show that delegated asset management can cause momentum patterns. As investors (principals) try to learn about a manager’s (agent’s) skill from his past performance and effectively chase returns, the resulting fund flows push prices away from fair values, inducing short-term momentum and long-term reversal patterns. 5.3 DETOUR: A BRIEF SURVEY OF THE EFFICIENT MARKETS HYPOTHESIS Before turning to behavioral finance, it is appropriate to briefly survey the efficient markets hypothesis (EMH).

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Investable HF indices are really portfolios of HFs that perhaps tried to take advantage of the marketing allure of the word “index”. Investable indices offered lower costs, better transparency, and better liquidity than non-index investments. However, top HFs had little incentive to participate, leading to adverse selection bias, and investable HF indices have consistently underperformed broader HF indices. After a brief detour I will return to other HF alternatives. Alphas, betas, alternative betas, and alpha–beta separation The demarcation line between alpha and beta is quite fuzzy. It is useful to think of the gray area between them as “alternative beta”, a catch-all term for all common factors beyond traditional equity, term, and credit premia.

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets
by Nassim Nicholas Taleb
Published 1 Jan 2001

An Interrupted Tennis Game It is not uncommon for someone watching a tennis game on television to be bombarded by advertisements for funds that did (until that minute) outperform others by some percentage over some period. But, again, why would anybody advertise if he didn’t happen to outperform the market? There is a high probability of the investment coming to you if its success is caused entirely by randomness. This phenomenon is what economists and insurance people call adverse selection. Judging an investment that comes to you requires more stringent standards than judging an investment you seek, owing to such selection bias. For example, by going to a cohort composed of 10,000 managers, I have 2/100 chances of finding a spurious survivor. By staying home and answering my doorbell, the chance of the soliciting party being a spurious survivor is closer to 100%.

The Devil's Derivatives: The Untold Story of the Slick Traders and Hapless Regulators Who Almost Blew Up Wall Street . . . And Are Ready to Do It Again
by Nicholas Dunbar
Published 11 Jul 2011

Morgan selected a “universe” of eligible credits for Mayu, using the criterion that their default swaps were liquid. But liquid meant heavily traded, which in WorldCom’s case was because unbeknownst to Vella, traders at J.P. Morgan and other banks were avidly buying default swaps to hedge their loan positions—an example of what economists call adverse selection. However, that default significantly eroded the cushion protecting Mayu’s investors from a loss on their triple-A-rated CDO—an unthinkable occurrence. (The Deutsche Bank REPON-16 product, with its five defaults, had been lower rated.) That’s why, behind the scenes, Vella organized a restructuring of Mayu in 2003, buying up defaulted or downgraded credits from the portfolio and replacing them with highly rated ones, including seven pieces of CDO on J.P.

The AI Economy: Work, Wealth and Welfare in the Robot Age
by Roger Bootle
Published 4 Sep 2019

Since the administration of this money-go-round is expensive, and since marginal tax rates have to be higher to fund the expenditure, this is massively wasteful. It is doubtful whether the state should be in the business of providing insurance. Even if some guarantees and top-up funding are required, arguably the insurance element is better provided by the private sector. (Admittedly, though, with regard to health insurance there is a problem of adverse selection. That is to say, the health insurance companies are reluctant to insure those most likely to need medical care. This requires state intervention in some form or other.) Moreover, state-provided services, in health and education, have a patchy record. Critics would argue that they have a tendency toward poor outcomes in regard to quality, consumer choice, and efficiency.

The Sense of Style: The Thinking Person's Guide to Writing in the 21st Century
by Steven Pinker
Published 1 Jan 2014

But many neologisms earn a place in the language by making it easy to express concepts that would otherwise require tedious circumlocutions. The fifth edition of the American Heritage Dictionary, published in 2011, added ten thousand words and senses to the edition published a decade before. Many of them express invaluable new concepts, including adverse selection, chaos (in the sense of the theory of nonlinear dynamics), comorbid, drama queen, false memory, parallel universe, perfect storm, probability cloud, reverse-engineering, short sell, sock puppet, and swiftboating. In a very real sense such neologisms make it easier to think. The philosopher James Flynn, who discovered that IQ scores rose by three points a decade throughout the twentieth century, attributes part of the rise to the trickling down of technical ideas from academia and technology into the everyday thinking of laypeople.37 The transfer was expedited by the dissemination of shorthand terms for abstract concepts such as causation, circular argument, control group, cost-benefit analysis, correlation, empirical, false positive, percentage, placebo, post hoc, proportional, statistical, tradeoff, and variability.

Confidence Game: How a Hedge Fund Manager Called Wall Street's Bluff
by Christine S. Richard
Published 26 Apr 2010

“We are at a loss to explain the enormous gap between dealer mid-market pricing, which shows the company with a $5.3 [billion] to $7.7 billion pre-tax loss, and the $35.5 million loss reported by the company.” MBIA was ballooning its exposure to CDOs—adding $30 billion of guarantees in nine months—and underestimating the risk, the report said. Bonds referenced in CDOs are more likely to suffer from adverse selection because banks may use CDOs to offload risk to credits they’re worried about, Ackman wrote. As a result, CDOs are more likely to be packed with higher-risk credits than a random portfolio of bonds, he explained. The credit-rating companies also were underestimating correlation risk, the report said.

Luxury Fever: Why Money Fails to Satisfy in an Era of Excess
by Robert H. Frank
Published 15 Jan 1999

“A Benz for the Wrist,” New York Times, March 8, 1998: sec. 9, pp. 1, 3. Land, Kenneth; P. McCall; and L. Cohen. “Structural Co-variates of Homicide Rates: Are There Any Invariances Across Time and Space?” American Journal of Sociology 95, 1990: 922-63. Landers, Renee M.; James B. Rebitzer; and Lowell J. Taylor. “Rate Race Redux: Adverse Selection in the Determination of Work Hours in Law Firms,” American Economic Review 86, June 1996: 329-48. Landers, Robert K. “America’s Vacation Gap,” Congressional Quarterly’s Editorial Research Reports 1, no. 23, 1988: 314-22. Lane, Robert E. The Market Experience, New York: Cambridge University Press, 1991.

Unconventional Success: A Fundamental Approach to Personal Investment
by David F. Swensen
Published 8 Aug 2005

Over reasonably long periods of time, aggregate venture returns more or less match marketable equity returns, indicating that providers of capital failed to receive compensation for the substantial risks inherent in startup investing. Aside from the dismal picture provided by historical experience, all but the most long-standing investors in venture partnerships face a problem in adverse selection. The highest-quality, top-tier venture firms generally refuse to accept new investors and ration capacity even among existing providers of funds. Venture firms willing and able to accept money from new sources may represent relatively unattractive, second-tier investment opportunities. Prior to the technology bubble of the late 1990s, investors in venture partnerships received returns inadequate to compensate for the risks incurred.

Cybersecurity: What Everyone Needs to Know
by P. W. Singer and Allan Friedman
Published 3 Jan 2014

unpatched vulnerabilities Lucian Constantin, “Over Half of Android Devices Have Unpatched Vulnerabilities, Report Says,” PC World, September 14, 2012, http://www.pcworld.com/article/262321/over_half_of_android_devices_have_unpatched_vulnerabilities_report_says.html. automated security tool Benjamin Edelman, “Adverse Selection in Online ‘Trust’ Certifications,” Electronic Commerce Research and Applications 10, no. 1 (2011): pp. 17–25, http://www.benedelman.org/publications/advsel-trust-draft.pdf. opt-in model Eric J. Johnson and Daniel Goldstein, “Do Defaults Save Lives,” Science 302, no. 5649 (November 2003): pp. 1338–1339, http://www.sciencemag.org/content/302/5649/1338.short.

The Future of Technology
by Tom Standage
Published 31 Aug 2005

Insecurity, he says, “is often due to perverse incentives, rather than to the lack of suitable technical protection mechanisms.” The person or company best placed to protect a system may, for example, be insufficiently motivated to do so, because the costs of failure fall on others. Such problems, Mr Anderson argues, are best examined using economic concepts, such as externalities, asymmetric information, adverse selection and moral hazard. A classic example is that of fraud involving cash dispensers (automated teller machines). Mr Anderson investigated a number of cases of “phantom withdrawals”, which customers said they never made, at British banks. He concluded that almost every time the security technology was working correctly, and that misconfiguration or mismanagement of the machines by the banks was to blame for the error.

The White Man's Burden: Why the West's Efforts to Aid the Rest Have Done So Much Ill and So Little Good
by William Easterly
Published 1 Mar 2006

Finally, formal statistical methods to control for possible reverse causality from crisis to treatment still found that structural adjustment lending has had a zero or negative effect on economic growth.12 Another influential recent study by Adam Przeworski of New York University and James Vreeland of Yale found that the effect of IMF programs on growth was negative, even when the study controlled for the adverse-selection effect. Another piece of evidence: as we see in a later chapter, African countries (even the “success stories”) couldn’t pay back zero-interest structural adjustment loans, and the World Bank and IMF had to forgive the debts. The White Man’s Burden was deployed in other ex-Communist countries of Eastern Europe and the former Soviet Union besides Russia.

Beyond the Random Walk: A Guide to Stock Market Anomalies and Low Risk Investing
by Vijay Singal
Published 15 Jun 2004

Investors who intended to sell for other reasons can benefit if they choose to sell several days before lockup expiration. References for Further Reading Aggarwal, Rajesh, Laurie Krigman, and Kent Womack. 2002. Strategic IPO Underpricing, Information Momentum, and Lockup Expiration Selling. Journal of Financial Economics 66, 105–37. Brau, James, and Grant McQueen. 2001. IPO Lockups: A Signaling Solution to an Adverse Selection Problem. Working paper, Department of Business Management, Brigham Young University. Fields, L.C., and G. Hanka. 2001. The Expiration of IPO Share Lockups. Journal of Finance 56, 471–500. Keasler, Terrill. 2001. Underwriter Lockup Releases, Initial Public Offerings and After-Market Performance.

Handbook of Modeling High-Frequency Data in Finance
by Frederi G. Viens , Maria C. Mariani and Ionut Florescu
Published 20 Dec 2011

Studies by Easley et al. (2011) and Kirilenko et al. (2011) provide evidence that UHFT orders did not cause of the crash, yet the algorithmic response to selling pressure wound up talking liquidity from the network market. Specifically, UHFTs either submitted large numbers of small-sized sell orders (Kirilenko et al.), or stopped trading in order to avoid adverse selection risk (Easley et al.), i.e. potential losses from trading with better-informed agents. These actions resulted in a ‘‘liquidity bottleneck’’ and raise concerns that UHFT may interfere with the self-correcting tendencies of financial markets. The microstructure model developed in this chapter offers insights on UHFT behavior, market liquidity and securities pricing in network markets.

After the Music Stopped: The Financial Crisis, the Response, and the Work Ahead
by Alan S. Blinder
Published 24 Jan 2013

—the IndyMac program quickly became the one to watch. But it was far from obvious that the IndyMac model was successful. Critics pointed to high redefault rates on modified mortgages at IndyMac—partly because the 38 percent DTI standard was too high. The Paulson Treasury worried about both adverse selection (lenders offering up their worst mortgages) and moral hazard (creating incentives that encouraged default). And then there was the “little” matter that the Bair plan would have bailed bad lenders and hedge funds out of losing positions. Undeterred, Bair sought to take the IndyMac model nationwide.

Investment: A History
by Norton Reamer and Jesse Downing
Published 19 Feb 2016

One of the staunchest opponents of this provision is the mutual fund industry.7 It presently enjoys the ability to advertise and is not pleased by the prospect of competition from hedge funds. Perhaps the most prominent concern regarding alternative investment advertising is the possibility for adverse selection. Many of the best funds may orient themselves primarily toward institutions given that, compared to individuals, institutions often have longer-dated capital and better underwriting and monitoring mechanisms by virtue of having full-time staff. As such, it is possible that there may be a disproportionate representation of lower-quality hedge funds that seek to advertise broadly because they have been less successful in raising money through traditional routes from sophisticated institutions.

More: The 10,000-Year Rise of the World Economy
by Philip Coggan
Published 6 Feb 2020

And there is an economic interest in ensuring that the population is healthy and able to work. But the public sector can struggle to meet the demand for healthcare, and the result is that services are rationed, meaning that patients can face a long wait for treatment. An insurance-based approach has problems too. Unless insurance is compulsory, there is a danger of adverse selection. Young healthy people will not buy policies but old, sick people will. This will drive up costs. In addition, there will always be a need to cover people who do not have insurance; no doctor wants to turn away a car-crash victim. The macro-economic impact The growth in government spending and taxation in the 20th century was about more than simply providing welfare, health and education.

Good Economics for Hard Times: Better Answers to Our Biggest Problems
by Abhijit V. Banerjee and Esther Duflo
Published 12 Nov 2019

That sets off the kind of self-confirming reasoning we saw in the case of newcomers to the labor market; the more suspicious buyers become of the old cars being sold, the less they will want to pay for them.50 The problem is the less they want to pay, the more the owners of good used cars will want to hold on to them (or sell their cars to friends who know and trust them). Only those who know their car is about to collapse will want to sell on the open market. This process by which only the worst cars or the worst employees end up on the market is called adverse selection.51 Connections are supposed to help people, but the fact that some have access to them and others do not may actually shut down a market that would function just fine if no one had connections. The playing field is level if there are no connections. Once some people have connections, the market can unravel, with the consequence that most people become unemployable.

Triumph of the Optimists: 101 Years of Global Investment Returns
by Elroy Dimson , Paul Marsh and Mike Staunton
Published 3 Feb 2002

The inflation index we use may not match the consumption pattern of investors in the market under consideration. Second, we are implicitly assuming that investors could invest globally throughout the twentieth century, yet markets were segmented for a significant part of this period. And third, as in our domestic comparisons, we are ignoring taxes, fees, or adverse selection costs, and this may matter more when the international comparison presumes transnational investing. We discuss the issue of the barriers to, and costs of, international investment in section 8.6 of the next chapter. With a common numeraire, we are nevertheless able to make comparisons across markets with added confidence.

The Bankers' New Clothes: What's Wrong With Banking and What to Do About It
by Anat Admati and Martin Hellwig
Published 15 Feb 2013

Oxford, England: Oxford University Press. Gorton, Gary, and Andrew Metrick. 2010. “Regulating the Shadow Banking System.” Brookings Papers on Economic Activity 41 (2): 261–312. Greenspan, Alan. 2010. “The Crisis.” Brookings Papers on Economic Activity, Spring, 201–246. Greenwald, Bruce C., and Robert R. Glasspiegel. 1983. “Adverse Selection in the Market for Slaves: New Orleans, 1830–1860.” Quarterly Journal of Economics 98 (3): 479–499. Grilli, Vittorio, Donato Masciandaro, and Guido Tabellini. 1991. “Institutions and Policies.” Economic Policy 6 (13): 341–392. Grossman, Gene M., and Elhanan Helpman. 1994. “Protection for Sale.”

The Third Pillar: How Markets and the State Leave the Community Behind
by Raghuram Rajan
Published 26 Feb 2019

What especially enraged the members of the Tea Party movement was the expansion in free health care for the poor, as well as the compulsion for all others to sign up for insurance plans. The proponents of Obamacare thought that compulsion would reduce overall health insurance premiums by reducing the extent of adverse selection (the phenomenon where the healthiest young people do not sign on because they least need health care). The angry Tea Party opponents instead felt they were subsidizing undeserving others through their own overly expensive premiums.42 Many among the Democratic leadership believed Tea Party members were protesting against their own interests, but they did not appreciate the extent to which the white majority had become angry about what they thought were the unfair privileges given to the clienteles of the Democratic Party, and the anxiety they had about their own slipping social status.

Stigum's Money Market, 4E
by Marcia Stigum and Anthony Crescenzi
Published 9 Feb 2007

For example, the quote spreads for 2-year notes averaged 0.8344 for GovPX quotes versus 0.2053 for the eSpeed ECN quotes, a reduction of 75%. For 5-year notes, the reduction was 0.8834 of a basis point, or 76%, and for 10-year notes the reduction was 1.7167 basis points, an 82% reduction. A combination of inventory and adverse selection costs explains the existence of spreads in the interdealer market. The inventory component is the cost of keeping a ready supply of securities for sale. The adverse selection component is caused by the risk that the dealer’s counterparty has private information about future price changes which could lead to losses for the dealer. The Brokers’ Screens In 1979, Garban became the first dealer to replace quotes over the phone with CRTs.

The Price of Time: The Real Story of Interest
by Edward Chancellor
Published 15 Aug 2022

Monte dei Paschi di Siena, Europe’s oldest bank – and Stefanel’s main lender – required a state bailout.26 Weighed down with old non-performing loans, European banks became reluctant to advance new loans. (The flattening of banks’ net interest margins by monetary policy exacerbated this problem.) A curious case of adverse selection appeared: more efficient firms in industries dominated by zombies were forced to pay more for their bank loans than those in other sectors.27 Another feature in common with Japan was how the ECB’s monetary balm removed the impetus for structural reforms in the Eurozone. Prior to Draghi’s arrival at the ECB around half of the OECD’s recommended growth initiatives were adopted across Europe.28 After the sovereign debt crisis was alleviated, politicians sat back.

City: Urbanism and Its End
by Douglas W. Rae
Published 15 Jan 2003

On the practical side, public housing often anchors people to places where attainable employment is scarce, tending to preserve the spatial mismatch from which lower-end urban economies suffer so severely.47 Other policies, having no direct relation to public housing, have exacerbated the mismatch—the decision to go for high-tech development in Science Park, next to Elm Haven, in the 1980s being an example. When major public housing projects dominate a neighborhood they tend to accelerate racial tipping and class tipping at the same time, so that most whites and many blacks decamp, leaving a more homogeneously impoverished population than before.48 From an economic viewpoint, this “adverse selection” process threatens to induce a death spiral, leaving projects and city blocks where having at least one adult family member with a regular job has become the exception and not the rule.49 Concentrating large numbers of low-income minority children in the neighborhood schools adjacent to major housing projects has in many instances helped to foment educational disaster.

Engineering Security
by Peter Gutmann

CA or security vendor-issued security seals are no better, with one security researcher pointing out that “almost every random example I picked where this [security vendor’s] logo had been used had basic security flaws” [618]. He then went on to replace the security seals on a major CA’s web site by ones announcing that they were from “Just Trust Me SSL”, powered by “Pixie Dust” [619]. The reason for this can be explained using a concept from economics called adverse selection. Reputable sites don’t need the seal while less reputable sites do in order to dupe (or at least attract) customers, with the result being that the less trustworthy sites are the ones most likely to have the seal. As with the case of SPF email signing being used far more by spammers than by legitimate senders, the cybercriminals were getting more out of the technology than the good guys.

…

[612] “ICANN’s TLD Plans Are Defined, Not Yet Refined”, Greg Goth, IEEE Internet Computing, Vol.12, No.5 (September 2008), p.10. [613] “The Good and the Bad of Top-Level Domains”, Barry Leiba, IEEE Internet Computing, Vol.13, No.1 (January/February 2009), p.66. [614] “New gTLD Draft Applicant Guidebook: Analysis of Public Comment”, Internet Corporation for Assigned Names and Numbers (ICANN), 18 February 2009, http://www.icann.org/en/topics/new-gtlds/agv1analysis-public-comments-18feb09-en.pdf. [615] “Generic TLDs Threaten Name Collisions, Information Leakage”, Robert Lemos, 11 July 2013, http://www.darkreading.com/advancedthreats/generic-tlds-threaten-name-collisions-in/240158075. [616] “Adverse Selection in Online “Trust” Certifications”, Benjamin Edelman, Proceedings of the 5th Workshop on the Economics of Information Security (WEIS’06), June 2006, http://weis2006.econinfosec.org/docs/10.pdf. [617] “Netscape 8’s ‘Trust Rating’ System”, Benjamin Edelman, 5 June 2005, http://www.benedelman.org/spyware/ns8/. [618] “Why I am the world’s greatest lover (and other worthless security claims)”, Troy Hunt, 6 May 2013, http://www.troyhunt.com/2013/05/why-i-amworlds-greatest-lover-and.html. [619] “Here’s why you can’t trust SSL logos on HTTP pages (even from SSL vendors)”, Troy Hunt, 8 May 2013, http://www.troyhunt.com/2013/05/heres-why-you-cant-trust-ssl-logos-on.html. [620] “User Perceptions of Privacy and Security on the Web”, Scott Flinn and Joanna Lumsden, Proceedings of the Third Annual Conference on Privacy, Security and Trust (PST’05), October 2005, http://www.lib.unb.ca/Texts/PST/2005/pdf/flinn.pdf. [621] “What Instills Trust?

The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite
by Daniel Markovits
Published 14 Sep 2019

averaged across four weeks: See Julia Szymczack et al., “To Leave or to Lie? Are Concerns About a Shift-Work Mentality and Eroding Professionalism as a Result of Duty-Hour Rules Justified?,” Milbank Quarterly 88, no. 3 (September 2010): 350–81. increased by nearly half: Renée M. Landers, James B. Rebitzer, and Lowell J. Taylor, “Rat Race Redux: Adverse Selection in the Determination of Work Hours in Law Firms,” American Economic Review 86, no. 3 (June 1996): 329–48, 330, citing American Bar Association, Young Lawyers Division, The State of the Legal Profession (American Bar Association, 1991), 22, Table 19. The ABA study reports that in 1984, 4 percent of lawyers worked more than 240 hours a month and 31 percent worked 200 to 239.

Corporate Finance: Theory and Practice
by Pierre Vernimmen , Pascal Quiry , Maurizio Dallocchio , Yann le Fur and Antonio Salvi
Published 16 Oct 2017

This is an insurance policy which guarantees the reimbursement of the unpaid debt by the credit insurer (Coface, Atradius, Euler Hermes, Zurich, SACE) in exchange for an insurance premium of between 0.10% and 2% of sales covered.8 It is rare that full compensation is paid out as the company will still have to pay the insurance excess, which will be between 10% and 30% of the amount of the debt. The insurance payout is made either when the purchaser of the company’s goods is declared insolvent or at the end of the waiting period before payment. In order to avoid carrying only the risks that the company knows are bad risks (adverse selection), insurance companies often insist on covering the whole of the company’s customer portfolio. Credit insurers provide three services: the prevention of receivables risk through solvency analyses and the provision of centralised commercial information which they update on an ongoing basis; recovery of unpaid invoices; compensation on guaranteed debts it has not been possible to recover.