Clever Geek Handbook
14 November 2025

Body Language in Business

Recommendation

Body language and other forms of nonverbal behavior are the subtext of all communication. Becoming fluent as a receiver and a sender is a necessary business skill. Authors Adrian Furnham and Evgeniya Petrova set out to debunk popular myths about body language, particularly any promises that you can learn to “read people like a book.” They examine different aspects of body language, such as facial expression, gesture, touch and eye contact. They also explain ways that body language provides cues and, in some cases, can mislead. Lastly, they offer practical strategies to consider in using your body language as well as decoding others’ signals. Furnham and Petrova broaden their examination of nonverbal communication to include other subjects, including feng shui, public speaking and bullying. Body language enthusiasts seeking detail will find this all-encompassing analysis insightful. For the less committed, the book’s aerial view of so many facets of this subject might muddy the waters. However, BooksInShort considers this an essential read for those wishing to sharpen their “soft” skills or raise their emotional intelligence.

Take-Aways

  • Nonverbal communication includes body language as well as statements made via appearance, behavior or possessions.
  • Nonverbal behaviors reinforce, emphasize, punctuate or even contradict the spoken word.
  • Understanding nonverbal behavior is a crucial business skill.
  • Body language includes looks, gestures, posture, touch, odor and expressions.
  • Character or culture influence some facial expressions, but others are innate.
  • The human smile is rich and varied, and communicates many different messages.
  • People accurately assess others within seconds based on a “thin slice of behavior.”
  • Some people are better than others at controlling and interpreting nonverbal messages.
  • Nonverbal behavior offers cues about whether someone is lying or telling the truth.
  • Fluency in body language is a valuable ability, especially when speaking in public, negotiating or selling.

Summary

What Is Nonverbal Communication?

A broad definition of nonverbal communication includes any kind of signal sent through the senses, as well as social statements made via dress, appearance or the possession of particular objects. Body language is nonverbal behavior that sends signals that communicate to the receiver, consciously or subconsciously. Body language can be subtle or overt, rehearsed and controlled, or spontaneous and physiologically revealing. It can be ideal for communicating and emphasizing a message.

“Bodily communication is communication without words: it is anything someone does to which someone else assigns meaning.”

Nonverbal behavior (NVB) serves to:

  • “Repeat, echo and emphasize what is being said.”
  • “Complement, modify and elaborate on verbal messages.”
  • “Contradict or confuse verbal messages to show ambivalence or cover up motives.”
  • “Substitute words.”
  • “Underline, accentuate, punctuate and moderate language.”
  • “Regulate and coordinate language.”
“Body language sends messages – messages about emotions, attitudes and personality.”

When people communicate verbally, they use the spoken or written word to convey messages. Visual cues include all NVB’s transmitted during face-to-face interactions, such as appearance, smell, age, dress and movement. Vocal cues can indicate the speaker’s emotional state, class, education or age.

“Nonverbal communication is a more primitive and often more powerful means of communications than verbal communication.”

In addition to what you say, how you say it has great meaning based on your tone, volume, speed, emphasis, pauses and more. However, experts who authoritatively announce that people send 70% of their messages nonverbally discount the power of language.

In most cases, words are the most accurate, precise way to communicate, particularly because people can’t control all their nonverbal signals. Many strong emotions “leak out.” For example, someone who is nervous might sweat or blush. Controlling your body language is not always possible, even when you can read it in others.

“We have an amazing ability to pinpoint other people accurately on a range of different personality and qualities scales without any deliberation or conscious thought on our part.”

Understanding nonverbal behavior can give you an advantage in negotiations, improve your work performance, boost your ability to manage people and enhance your communications. “Soft” skills, like reading body language, have come to carry more weight in business.

Body Language

Biologists began to study body language in the late 1800s. Charles Darwin published the first definitive book on the subject, The Expression of the Emotions in Man and Animals, in 1873. However, studying body language became popular many years later, in 1967, when Desmond Morris published The Naked Ape. Today scientists from various persuasions, from anthropology to psychology and even sexology, study and write about the topic. Though many people have published carefully researched data, a lot of gobbledygook also appears on this theme, particularly in the areas of “symbolism, power, and controllability” and the claim that “you can read people like a book.” For example, Freudians say that people who stand with their hands in their pockets are withdrawn, reclusive or secretive when actually they might just be cold.

“The face is a highly expressive region. It is ‘readout’ of emotions: immediate, spontaneous, honest and uncontrollable.”

Body language encompasses many physical signals such as looks, gestures, posture, touch, odor and expression. The eyes convey messages as plain as punctuation; for instance, glancing up at the end of a statement to gauge other people’s reactions. Eyes communicate complex emotions, like shame. Extended eye contact signals attention, cooperation and liking. The way people make and maintain eye contact varies among cultures. Outgoing people make more eye contact; introverts avoid an open gaze.

“Where, when and how we look are all part of the phenomenon of eye gaze, one of the most important and primitive ways of communication.”

Facial expressions are highly communicative. Many are innate to humans, such as looks of surprise, fear or pain. Cultural background influences how people use facial expressions in social situations. They compose their faces in one way at a funeral and another way at a wedding. Although people might try to mask their emotions by using a “poker face,” the more genuine the expression, the more authentically it reads – especially with smiles. Fake smiles don’t involve the eyes and recipients instinctively understand if a smile is real or counterfeit.

“Our ability to attribute other people’s states and attitudes relies on reading body language.”

Psychologist Paul Ekman studied smiles extensively and identified several types, including:

  • “The felt smile” – A genuine smile that conveys positive feeling.
  • “The fear smile or contempt smile” – A smile built on negative emotion.
  • “The dampened smile” – A smile someone tries to suppress.
  • “The miserable smile” – A smile someone uses to make the best of a situation.
  • “The flirtatious smile” – A come-hither signal.
  • “The Chaplin smile” – An exaggerated smile that is almost a parody of a smile.
  • “The qualifier smile” – A smile someone uses to convey unpleasant news.
  • “The coordinated smile” – A polite signal that shows, “I’m listening.”
“There is a skill in being a sender and a skill in being a receiver of nonverbal communication.”

Humans use gestures for many reasons including emphasis, indicating directions or drawing an imaginary picture. Some gestures are nearly universal, such as nodding to show agreement, clapping to indicate approval or rubbing your stomach to signal hunger. Yet gestures vary greatly from one country to another. For example, a circle created by your thumb and forefinger means “okay” in the US and “zero” in France, but in central Europe it is the equivalent of an obscenity.

“EQ is about emotional literacy, and emotional literacy is about reading the cues of nonverbal communication.”

Posture and body orientation send messages. Sitting at the head of a table signals power; standing over someone indicates dominance. How close you stand to someone – your body proximity – establishes territory. Cultures define personal space differently, but people generally establish four zones of body closeness: “intimate, personal, social and public.”

“When stakes are high and emotions intense, especially in business negotiations, body language is the source of information to be taken into account.”

Touch, odor and voice are integral elements of body language. Contact, from embracing to patting someone’s hand, stroking them or linking arms, is a powerful communicator. People use touch to persuade, sympathize, show affection or threaten. Many attach a spectrum of meaning to the way a person shakes hands. Animals communicate via odor and so do people, but this primitive system often operates beneath human consciousness.

What You See...

Ideally, people should evaluate each other based on individual character, but assuming that appearance doesn’t play a part is naive. Science proves that people assess others in seconds based on a “thin slice of behavior.” Moreover, this initial assessment is uncannily accurate. Height, weight, body shape, skin texture, symmetry of features and hair characteristics shape a person’s attractiveness. Furthermore, firms are likelier to hire and promote good-looking people, who generally have an easier time overall.

“Business people hope to detect the real, infallible truth and catch liars by carefully analyzing...body language.”

How you dress can indicate your social class, reveal your values, underscore your image or make an artistic statement. Many businesses dress their employees in uniforms to denote cleanliness, rank or professionalism. Color also plays a role since many colors have symbolic associations.

People express their emotions through body language, in part, because they can't help it. Blushing, perspiring, changes in breathing or pupil dilation are physical signs of emotions like anger, embarrassment or sexual excitement. As people mature, they learn to read other people’s emotions by watching their body language. Some of this skill is innate while some is culturally learned. Often, someone people describe as perceptive and intuitive is simply very adept at reading body language. However, some people send and interpret nonverbal messages better than others. Generally, women read body language better than men.

“Training and experience do help in the business of lie detection, but even then it is by no means simple or foolproof.”

People decode more proficiently as they mature, but the skill usually peaks in the mid-20s. Some evidence shows a relationship between intelligence and nonverbal skills. The smarter the child, the better he or she is at reading NVBs. Extroverts and optimists read people better than introverts or close-minded people do. Why do people act differently in various situations? The setting, social rules, relationships and reasons for an interaction all influence their behavior. Skilled people-watchers observe nuances in conduct that enrich their understanding. Such people usually rate high in Emotional Intelligence (EQ), the ability to “express emotion, regulate emotion in oneself and others, and utilize emotion in solving problems.” Your EQ depends on your ability to read body language with acuity.

Your Lips Say Yes, But Your Eyes Say...

Discerning between honesty and deception is a vital business skill, especially in negotiating. People lie for many reasons: to protect themselves from punishment, embarrassment or threat of violence; to win approval; to gain the upper hand; or to take credit. Lying takes three forms. The first is the commonly accepted “white lie,” told to avoid hurting another person’s feelings. The second is the kind of expedient lying associated with the stereotypical car salesman, or lying that misrepresents or excludes information to gain business. The third level of lying, falsifying facts or omitting data altogether, is the most insidious in business.

“Body language helps us quickly to sort out friends from foes, good from bad, and sincere from dishonest words.”

Many people rely on body language to deduce if someone is lying. Liars betray themselves via verbal and nonverbal cues. When dissembling, a person will hesitate between sentences or talk about himself or herself in the third person; speech cadence might vary from slow and uneven to quick and hurried. Liars often are uncomfortable with silences and may explain too much. Nonverbal cues include fidgeting, wriggling in a seat or making too much or too little eye contact. Liars may speak in a monotone to mask their emotions or use more “comfort gestures” such as touching their lips. To detect when someone is fibbing, look for variations outside his or her normal behavior. Consider discrepancies between verbal and nonverbal behaviors.

“Body Language in Business”

In many business situations, fluency in body language is a valuable ability, especially when speaking in public, negotiating or selling. Giving a speech is nerve-racking for most people. Because it is so intimidating, many speakers experience physical reactions: Their heart rate increases, they sweat and even tremble. Deep breathing helps counteract these symptoms.

Good speakers’ nonverbal behaviors include assuming an open body stance and suppressing distracting gestures like moving objects on the podium. Engaging orators inspire their audiences, impart information or persuade their listeners to consider a fresh viewpoint. They rehearse their nonverbal behaviors, such as gestures, eye contact and stage movements. Speaking in front of an audience of any size changes the dynamics of communication. The speaker offers a message, the audience reacts; the speaker receives their feedback and then changes in response.

During negotiations, nonverbal position and dominance clues signal who is in charge and making decisions, and who is the helper. Nonverbal behaviors are less binding than words during negotiations, yet they can suggest agreement, disagreement or the desire for a particular course of action. Nonverbal vehicles for relaying messages while negotiating include interpersonal distance, nodding and smiling, posture, mirroring and eye contact. In sales, nonverbal communication reinforces various methods of persuasion. In 2007, R. Cialdini outlined six methods of persuasion: “Commitment and consistency, reciprocation, social proof, authority, liking and scarcity.” Certain nonverbal behaviors reinforce each one. For example, a handshake can entice a buyer to enter a conversation. Motions that mirror a customer’s body language are signs of empathy and likability.

Body language will not reveal the depths of your soul, but people who read it well can gain accurate insights from very brief exposure. The main thing to remember is that “the power of body language lies in its subtlety, in its promise of an action rather than the action itself. Body language hints towards a certain disposition or behavior rather than identifies or determines it.”

About the Authors

Adrian Furnham, a psychology professor at London’s University College, has written more than 60 books and 800 articles. He contributes to the Financial Times and the BBC. Psychologist, researcher, ballet dancer and scholar Evgeniya Petrova has won several Russian literature prizes.

Read summary...
Body Language in Business

Book Body Language in Business

Decoding the Signals

Palgrave Macmillan,
 


14 November 2025

The Future of Decision Making

Recommendation

Education engineering experts Roger C. Schank, Dimitris Lyras and Elliot Soloway apply their knowledge of cognitive science, computer software and industry to a single purpose: helping you make better decisions. They directly challenge using logic and rationality as they argue for “case-based reasoning.” Their writing is exceptionally clear, which makes the book easy to follow. Its only weakness is that the authors are so positive you can improve your decision making through software that they sometimes make it sound easier than it might be. That aside, this first-rate book’s counsel applies to all fields. BooksInShort particularly recommends it to corporate leaders, software designers and those involved in knowledge management.

Take-Aways

  • Most people make bad decisions because they use the wrong decision-making models.
  • You’ve learned to make decisions logically and rationally, but decision making is an “unconscious process” based on your experiences.
  • Most organizations provide rules to guide decision making, but these work against you.
  • The best way to help employees make decisions is by letting them learn from experience, including failure. The second best way is by sharing expert stories.
  • Interview your veteran employees, as well as former staffers, outside experts, academics and consultants, to build a storehouse of useful stories.
  • The right knowledge management software can actively help you make better decisions by providing you with the right stories at the right time.
  • Good decision-making software is organized like the human mind.
  • You need software that is specific to your organization, industry and activities.
  • Truly useful software functions like a friend who knows you well, taking your character and emotional makeup into account.
  • Properly designed simulations can train people to make better decisions.

Summary

A New Model for Decision Making

Everyone in your organization wants to make good decisions, but many people make bad ones because they’ve learned the wrong model for decision making. They count on logic, data and “conventional wisdom.” That approach may work in simple situations where information is readily available, but in most instances, it works against you because “decision making is largely an unconscious process.”

“Many organizational employees make well-intentioned but poor choices. This is true for everyone from top executives to line workers.”

To begin to improve your decision making, discard the idea that you’re a rational decision maker. Like all human beings, you make your best assessments intuitively, using a feeling, a “gut instinct” or a hunch. Your best judgments are “based on accumulated experience.” When presented with an issue, your subconscious mind reviews related situations from your past, the choices you made and how those worked, and then it generates new options. The finest decisions “flow from goal conflict adjudication” – juggling several conflicting factors at once – rather than “half-baked logic.” For example, a captain at the helm of a freighter traveling through the Suez Canal knows it’s better to push through than to stop and deal with an onboard boiler fire. Why? The captain’s experience has shown that the expense and trouble of halting the ship, negotiating with local authorities to release it and missing delivery deadlines are greater than any potential fire damage. You learn to make better decisions by making decisions and learning from the results – both good and bad.

“Case-Based Reasoning”

In organizations, people may think they make decisions collaboratively, but what they’re really making is “a series of small individual decisions.” Even if they make choices as a team, they’re unlikely to involve the right people at the right time with the right experience. Companies often give their employees decision guidelines, but “rule-based logic” is of little help. Rules are well-intentioned, but they derive from past, static conditions, within known parameters and limited variables. But business is dynamic; situations change all the time, so generalizations based on the past often don’t apply to the present. Replace rigid rules with case-based reasoning, which is founded in individuals’ experiences, whose emotional power has greater impact on the psyche than abstract rules do. Case-based reasoning draws on a broad variety of experiences, both successful and not, and identifies which ones apply to current situations.

“Experience really is the best teacher. An experience is often emotional, and thus has a greater impact than a purely cognitive rule.”

In the maritime world, veteran sailors are called “old salts” because they’ve been through everything on the water and they know just what to do in an emergency. Call on your organization’s old salts to help in decision making. However, you can’t afford to hire people with only this level of expertise. Instead, capture their proficiency in story format through interviews. Stories are “the next best thing” to direct experience. Stories bypass your relatively inefficient logical mind and activate the wisdom of your unconscious. Your mind continually indexes your experiences, synthesizing events into patterns; case-based reasoning will allow you to tap these insights in ways that rules do not.

“Organizations loathe the idea of failure, but failure is integral to on-the-job learning.”

Applying case-based reasoning to corporate decision making “brings objectivity” to the process, discarding the “pet theories” that frequently cloud judgment. Case-based reasoning improves your hiring and retention process: In recognizing the value of experience, you’ll position your old salts where you can tap their know-how. Too often leaders have a lot of experience, but not the right kind for making “high-level decisions”; case-based reasoning can supplement this dimension. It will also help people master their responsibilities faster and take smarter risks. And making decisions this way has intangible benefits: People will feel better about their decisions.

Automating Decisions

Companies should transition gradually to case-based reasoning. The right decision-making software (which, in this context, can mean anything from information systems like email to structured applications like those for databases and purchasing) can help. But many times, generic software is complicated and not user-friendly. It can also be “object-based,” good at tracking budgets and files, but not at registering the activity-based, dynamic, decision-making variables specific to your field or company.

“Companies must develop industry-, organization- and process-specific software as well as capitalize on the common sense of the people with situation-specific experience.”

Software that incorporates the principles of cognitive science uses “indexing language” to organize expertise into useful, accessible forms. The indexing system that software uses should align with the four groups into which the human mind classifies information: “goals, plans, goal conflicts and conditions.”

“Expert stories are only worth as much as their ability to be delivered in a timely manner to the people who most need to hear them.”

As an example, consider the differences between the musical West Side Story and the play Romeo and Juliet. They take place in different centuries, places and situations. Yet they are indexed in your mind by “the same label: ‘Warring factions destroy lovers’ plans and lovers themselves’.” Similarly, one colleague’s complaint that his wife overcooked his steak last night triggered his friend’s recollection that he could never find a barber to cut his hair properly 30 years ago. The common label? “Extreme request.”

Stories Feed the System

Software can remember stories forever and objectively, without emotional bias. In addition, your software should remind you of the most appropriate stories at the most useful times, filter out excess data and connect your “decision makers with experts.”

“Some of the most interesting and instructive stories an expert can tell are related to mistakes he has made.”

Populate your decision-making software with stories from your old salts. Which veteran employees have been through it all? Ask them to discuss extreme experiences: the best and worst decisions they ever made, deals that looked great on paper but didn’t work out, big risks that had great payoffs, and so on. Request that they spell out the logic behind their decisions, what the negative results of their actions were, what they learned, and more. In all stories, push for specific details, and help arrange the material into a solid structure with a beginning, a middle and an end.

“Most of the email systems used in organizations are not as smart as even the slowest-witted, most inexperienced secretary.”

Then, collect expertise in specific areas: Who is the most proficient at cutting the budget, at fixing kinks in the supply chain, at innovation? These old salts won’t have “an unbroken string of successes” on their records; they’ve failed at times, but they learned from their mistakes. If you don’t have these expert employees in your company right now, fill the gaps with former staffers, academic experts and outside consultants.

“The difference between traditional and cognitive training is the difference between telling employees how to make good decisions and letting them practice making them.”

Once you’ve captured such knowledge, your software can begin to recognize it as similar to current challenges and link them together. The link might happen at a basic level, such as reminding you of past decisions related to the same subject matter, but software could also link saved stories and current situations at a more abstract level. For example, an HR officer relates her children’s desire to stay up late to the issue of her company laying off older workers. Underneath each is a hidden need – the kids want to watch a particular night’s TV program, while the employees want the respect their jobs afford them. This “cross-domain” thinking leads her to the right solution: The children can stay up late one night per week, and the older workers will be hired as part-time external consultants. In the same way, artificial intelligence can bring up seemingly disparate occurrences and find the commonalities in them to get to the right answer.

“Decision-Making Software”

Organizations often become buried in information, so your knowledge-management software should bring you exactly what you need, even things for which you didn’t think to search. This increased capacity should extend even into your email system. For example, your software could sort the organization’s messages by imposing a basic structure on the emails employees compose. Rather than writing emails as “free-form text,” structure them into “tasks, plans and goals” to make indexing easier. Just as personal assistants know their bosses’ likes and dislikes, so, too, can email act as a “prioritizing, reminding and coordinating” resource.

“Emotion can serve decision makers well.”

This greater functionality can apply to search engines as well. Right now, even the best programs search linguistically, generating many false hits (such as information on President Gerald Ford when you’re searching for Ford cars). Search engines, like other software, should index material based on how the mind works. Search functions should be “computer-intuitive,” too and generate searches based on whatever you’re doing on your computer.

“Computer users sense when software feels right. Something inside of them says that the software is asking them questions, reminding them of stories or providing other knowledge that is exactly what is required.”

Tough decisions stymie executives because choices often involve “underlying goal conflicts.” For example, a CEO must choose between cutting staff to save costs and to please investors, or retaining employees and investing in “the future of the company.” Well-designed software can help negotiate these clashes by providing information about similar divergences in the past that can aid present-day decision making. The software must allow for “modification” to incorporate new experiences as they happen. It must also track failures, so that you can gauge what went wrong and store those evaluations to help your corporate leaders in the future.

Implementation

A lot of software is functional: The screen is attractive, the icons are clear and the applications open smoothly. But that’s “level 1 usability,” where software functions as a tool, as in, for example, Microsoft Word. The goal is to produce “level 2 usability,” where software plays an active role in “facilitating the process of making a good decision.” For this sort of operability, the “visual metaphor” of the “desktop” takes software in the wrong direction: It organizes information like an office does, rather than like a mind does.

“Cognitive-based software is well-equipped to adjudicate through its communication capabilities. This is true whether or not decision makers are aware of these conflicts.”

Your decision-making software must customize itself to each user. It should guide you by offering “contextual knowledge,” examples, suggestions, guidelines and the like. Your software can function like a friend who knows you well, taking your character and emotional makeup into account. It should know your short- and long-term goals, how they conflict, what decisions you’ve made, and what obstacles you’re likely to encounter.

“Decision making isn’t about right and wrong. Training that attempts to convince people to follow decision-making rules won’t work.”

Truly useful software should provide interfaces in which graphics reflect how the mind actually functions. An interface should use “cognitive abstractions” for each activity mapped – that is, breaking down jobs that have different titles to expose underlying similarities. Likewise, it should demonstrate an “understanding of enterprise processes.” And it needs to winnow the results so it doesn’t bury users in data. Make your software respond to each “user’s role within the larger process” so that it interacts with experienced engineers differently than it does with new marketing hires. Software should put all interactions in context, yet be able to shift quickly from topic to topic. It should link all “related processes” and reflect how your organization functions.

Training in Decision Making

You can use the same software-design principles to help people learn to make better decisions. Recognize that you cannot teach people to decide better, however, you can give them practice so they can learn by doing. To do this, use software to provide “realistic decision-making simulations” in which learners can practice all aspects of decision making, including failing.

“Designing usable software for decision makers isn’t rocket science; it’s brain science.”

These simulations should include “expectation failure,” in which people make decisions that appear good but turn out badly, and “ambiguity,” to allow learners to practice realistically complicated decisions. These simulations should be “goal-based” for participants, yet fun enough to engage them.

As you develop software to train your employees, ask them which decisions frequently give them trouble. Solicit stories about bad decisions and their outcomes, about circumstances that have led employees to the wrong choices, and about the different kinds of judgments that most often cause problems. Determine what “employees need to know how to do to make good decisions.”

Expect obstacles and objections as you implement this training. You can’t design good training courses on making specific decisions, so those who want such classes will be frustrated. Instead, offer practice in decision making, feedback on the process, time to reflect and guidance. Set a brief series of “performance objectives,” and evaluate whether the training meets those goals. Finally, recognize that training is beneficial, especially in helping “employees change certain perceptions or habits,” but it can’t be a cure-all.

About the Authors

Roger C. Schank is a professor emeritus at Northwestern University. Dimitris Lyras founded Ulysses-Systems, a software consultancy. Elliot Soloway is a professor of engineering, information and education at the University of Michigan.

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The Future of Decision Making

Book The Future of Decision Making

How Revolutionary Software Can Improve the Ability to Decide

Palgrave Macmillan,
 


14 November 2025

Econned

Recommendation

Neoclassical economists contend that the economy naturally seeks equilibrium, an optimal point where the supply of goods and services equals the demand. This intellectual view has encouraged politicians to deregulate markets to make them more competitive and efficient. But deregulation of financial markets has been a failed experiment in freeing banks and investment firms, says financial writer Yves Smith. She argues, convincingly, that the global financial crisis that began in 2007 has provided ample justification for greater regulation of banks and other related institutions. This book went to press in late 2009, prior to the 2010 passage of the Dodd-Frank Act, a sweeping reform of the US financial services industry that embodies some of the author’s proposed changes. BooksInShort suggests Smith’s book to all those affected by the 2008 meltdown for its incisive description of the symptoms, causes of and cures for the financial crisis.

Take-Aways

  • Late 20th-century economic theories rested on flawed assumptions that led to the financial crisis beginning in 2007.
  • Once a social science, economics now uses mathematics and abstractions that conflict with real-world financial behavior.
  • Neoclassical economics professes that markets are better off unfettered by regulation.
  • Lawmakers liberalized real markets to make them resemble theoretical “free markets.”
  • An unregulated “shadow banking” system fed a global borrowing binge.
  • Securitizing mortgages allowed bankers to assume more – but less-creditworthy – loans.
  • Collateralized debt obligations and credit default swaps created secondary markets that offered opportunities to hedge against – or bet on – rising real estate values.
  • Private and public investors, as well as financial institutions, suffered massive losses amplified by leverage.
  • Lawmakers should restore the separation of commercial banks from investment firms.
  • Economists must become more “explicit and transparent” in their logic and ideas.

Summary

The “Self-Correcting” Economy

In his influential 1776 book, The Wealth of Nations, Adam Smith popularized the classical economic concept of market equilibrium. Smith is famous for comparing individual self-interest to an “invisible hand” that nudges each seller of goods and services to supply just enough to satisfy the needs and wants of buyers. His use of such an evocative metaphor was typical of the times; economics was a social science prior to the 20th century. Today, respected economists take a much more mathematical approach to their field.

“We need to implement economic policies that treat finance as the handmaiden of commerce, not its master.”

Since the 1940s, mathematical expressions of Smith’s ideas have made the economics discipline more accurate, in a narrow sense, but also more abstract and arguably less applicable to real problems. Neoclassical economics, the quantitative descendant of classical economics, developed formulas that identify theoretically optimal economic states – that is, mathematical points where the demand for a product equals its supply.

“Widespread acceptance of the phony precepts of financial economics and neoclassical economics helped bring about the financial crisis by endorsing policies and practices that allowed financial firms to exploit customers, shareholders and taxpayers on a scale heretofore seen only in banana republics.”

But disciples of the neoclassical school did more than just reduce the metaphor of the invisible hand to numbers. They embraced unrealistic assumptions about markets as they examined their use of mathematics to explain market phenomena. They misused Adam Smith’s concept of “free markets” by encouraging deregulation of financial markets for the sake of economic efficiency; and they professed that markets with less regulatory intrusion would work better and would reach equilibrium with greater ease.

“It is actually difficult to prove anything conclusively in economics. In fact, some fundamental constructs are taken on what amounts to faith.”

But this neoclassical belief is laden with debatable assumptions, which make the math simpler. Neoclassical economists assume, for the sake of analytical simplicity, that no one has more information than anyone else, that no one has enough sole purchasing power to affect prices, that transaction costs are nonexistent, and that markets remain open without interruption. This simplistic model of pure competition can serve as a guide for economic policy making, but many lawmakers have gone too far. They have embraced deregulation in the vain hope of being able to reshape financial markets to make them resemble the neoclassical model.

“Financial Economics” and Risk Management

The view of unbridled commerce as an equilibrium-seeking force seeded the growth of a branch of neoclassical economics known as financial economics. Its intellectual foundations emerged during the 1960s and 1970s and provided political justification for deregulation of the financial markets in the 1980s and 1990s. Paul Samuelson, the first American to win the Nobel Prize for economics, and Eugene Fama of the University of Chicago developed the “efficient markets hypothesis.” They proposed that prices of traded securities fully reflect all information about them. Economist Harry Markowitz introduced the concept of the “efficient portfolio.” He theorized that each investor seeks an optimal portfolio mix, balancing returns with risk.

“Despite economists’ attempts to position themselves as benign umpires, their role is profoundly political.”

But financial economics rests on illusory suppositions. Real markets sometimes stop functioning for one reason or another, so their continuous operation is never guaranteed. The assumption of perfect knowledge among all investors is equally unrealistic. In sales of assets, one party often knows more about the market than the other party.

“Economists love to twiddle with models to prove the existence of optima, but that begs the question of what is society trying to optimize?”

Markowitz’s theory of efficient portfolios suffers from dubious assumptions about risk management. Investors can adjust expected returns for risk only if they correctly measure that risk, but most modern tools for assessing investment risks have failed to predict the most serious threats. Modern models designed for financial risk management have consistently displayed three common weaknesses, even as their mathematical sophistication has grown. First, the designers of risk management tools such as the Value at Risk (VaR) model have relied too much on normal probability distributions, which consistently underestimate “tail risk” – that is, the probability of extreme events. Second, risk management tools have performed poorly because of built-in assumptions that markets will not halt and, third, that asset classes will not depreciate in unison.

Deregulation and “Shadow Banking”

The Great Depression of the 1930s led the US to tighten regulation of financial markets following an era of minimal regulatory interference that ended with the stock market crash of 1929. Subsequent to the crash, lawmakers mandated insurance for bank deposits, established the Securities and Exchange Commission (SEC) to regulate markets, and passed the Glass-Steagall Act to separate commercial banks from investment firms. But after about half a century of relative calm, financial markets became more dynamic during the deregulatory trend of the 1980s and 1990s.

“The United States tried unregulated securities markets and the result was periodic crashes, culminating in the spectacular 1929 meltdown.”

Financial market deregulation then became widespread because so many economic policy makers believed that reduced government regulation of financial markets would make the markets more efficient. One consequence of this school of thought was the US government’s deregulation of interest rates on bank deposits, a move which increased the competition between banks and securities firms that offered uninsured money market accounts. Federal lawmakers also gradually demolished the regulatory wall between commercial banks and securities firms, finally in 1999 repealing what remained of the Glass-Steagall Act. The SEC, which has focused more on crime prevention than prosecution, requires ongoing financial disclosures by public companies and prosecutes illegal insider trading and stock market manipulation. Yet budget limitations and other constraints have kept the SEC and Justice Department from pursuing complex civil and criminal litigation to deter financial fraud. They have been “sticking with easy-to-prove cases” instead.

“Effective risk management took a giant step backward with the creation of a widely used risk management tool, Value at Risk.”

Lax regulation contributed to the development of an unregulated shadow banking system comparable in size to the legal banking system. For example, securities repurchase agreements (“repos”) allow financial institutions to borrow increasing amounts of money by selling US Treasury securities or other types of collateral, including mortgage-backed securities. The institutions then repurchase the collateral at a higher price. The bank gains a bit of short-term liquidity and the markup is equivalent to loan interest.

“Risk management is often an exercise in providing cover for managers and directors, and thus serves as another tool to hide looting.”

Other forces drove the development of the shadow banking system. Market growth of repos reflected the inflated issuance of mortgage-based securities and insurance against losses on these securities. Trading in these instruments ballooned in a shadowy corner of the financial services industry that lacked effective regulatory oversight. Investment banking firms increasingly acquired, assembled and securitized large pools of mortgage loans, marketing them to investors as high-yield bonds. A breakdown in the relationship between mortgage lenders and borrowers was one of the counterproductive side effects of the shadow banking system.

“Financial deregulation spawned a shadow banking system, an unregulated sector that came to rival the traditional banking system in size.”

Mortgage-loan securitization, in particular, undermined lenders’ scrutiny of loan applicants. When housing prices were rising rapidly, especially from 2004 to 2007, securitization provided a vast secondary market for the originators of mortgage loans, allowing them to raise cash for additional lending by making new loans, collecting closing fees and selling the loans. But credit quality suffered, because so many lenders were originating mortgages primarily to sell them, not to hold them. By 2008, mortgage bonds were sinking under the weight of widespread defaults among borrowers.

Synthesis and Leverage: Piling More Paper on Mortgages

The collateralized debt obligation (CDO), a type of structured credit instrument, essentially provided a secondary market for financial institutions that wanted to cut their inventories of mortgage-backed bonds. Returns from the underlying pools of interest-bearing securities pass through to CDO investors. CDOs backed by mortgage bonds surged from 2004 to 2007.

“In banking, moral hazard results when devices to prevent bank failures encourage banks to take greater risks.”

Major banks and investment firms built many CDOs based on layers of mortgage bonds of uneven quality. Underwriting standards were stringent for some of the loans underlying mortgage bonds, but “subprime” standards applied to others, meaning the lenders permitted lenient loan terms or allowed loan applicants to qualify without proof of income. Like a butcher who can earn more money by selling pieces of an animal instead of the whole beast, financial institutions marketed mortgage-based CDOs in different slices with different credit ratings, descending from the top score of AAA and ending in unrated bottom layers, referred to as “equity” tranches.

“There is no economic theory of how the financial system interacts with the real economy.”

The leading CDO issuers, including Citigroup, Deutsche Bank, Merrill Lynch and UBS, retained approximately two-thirds of the tranches with the highest credit ratings in 2006 and 2007. The availability of insurance mitigated their difficulty in marketing the lower-rated tranches. Investors in these riskier CDO layers hedged against possible losses by purchasing credit default swaps, comparable to insurance policies. Sellers of credit default swaps collected premium payments from buyers and, in return, guaranteed to cover losses on CDOs arising from defaults on the underlying mortgage loans. These sellers basically bet that housing prices would keep rising and that the quality of mortgage credit would remain stable.

“Data do lend support to the notion that the shadow banking system was the main culprit in the meltdown.”

Synthetic borrowers and lenders deepened the black hole of mortgage finance that the shadow banking system had dug with the help of real borrowers and lenders. Credit default swaps became more than just hedges against losses; investors with nothing to hedge increasingly speculated by trading in credit default swaps. In this large and liquid market, Wall Street was thirsty for more.

“The dirty secret of the credit crisis is that the relentless pursuit of ‘innovation’ meant there was virtually no equity, no cushion for losses anywhere behind the massive creation of risky debt.”

Then, as the blazing growth in subprime mortgage borrowing started to cool, investment banks offset the impact by issuing synthetic CDOs. These securities have underlying pools of credit default swaps, unlike collateralized debt obligations composed of mortgage bonds. With credit default swaps, the CDO market was “no longer bound by earthly constraints” on the real market for mortgage financing and “could ascend skyward.”

Rescue and Reform

Numerous buyers of synthetic CDOs regarded these securities as complex but safe bets on the future of the mortgage market, so they borrowed money to buy more securities. Unfortunately, these and similar leveraged bets heightened the financial crisis that began to unfurl in 2007 amid a surge in mortgage loan defaults. Synthetic CDOs were intricate instruments that crushed unsuspecting buyers, especially those who compounded their losses with leverage.

In one case, five school districts in the state of Wisconsin invested $35 million of their cash and borrowed another $165 million to buy a synthetic CDO that went bad, and their $200 million investment plunged to $50 million. The damage spread much further: Some of the biggest financial institutions in the world lost vast sums of money on CDOs, which sank in value as mortgage defaults spread. Estimates of aggregate bank losses on all kinds of CDOs ranged from $160 billion to $190 billion, which partly explains why US regulators have made gargantuan financial commitments to rescue leading banks and investment firms from this catastrophic mess. By the end of 2008, the Fed and the Treasury Department had committed combined funding of more than $8.5 trillion to the rescue of impaired financial institutions.

Multiple regulatory reforms are necessary to contain the types of market forces that led to the financial crisis. One is a revival of the old separation of banks and investment firms that disappeared with the repeal of the Glass-Steagall Act. Credit default swaps provide insurance, so issuers should submit to insurance regulations. Credit rating agencies should lose the legal protection the First Amendment provides for freedom of expression when they issue ratings that mislead investors. The economics profession is due for reform, too. Economists could perform a valuable service to society by improving their communications with the public. They must become more “explicit and transparent” in describing the logic of ideas and their impact. Excessive reliance on opaque, mathematical explanations of economic concepts remains a pervasive weakness of the discipline.

About the Author

Yves Smith (the pen name of financial writer Susan Webber) established Naked Capitalism, a website focused on economics and finance. Her articles have appeared on Slate and in The New York Times and The Christian Science Monitor.

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