Economics could be a Science if More Economists were Scientists

By William K. Black
(Cross posted at Benzinga.com)

Raj Chetty has written an op ed in the New York Times designed to counter the abuse the Sveriges Riksbank (Sweden’s central bank) rightly received for its latest embarrassment.  Economics does not have a true Nobel Prize, so a central bank decided to create a near-beer variant.  The central bankers have frequently made a hash of it, often awarding economists who got it disastrously wrong and inflicted policies that caused immense suffering.  This year, not for the first time, the central bankers decided to hedge their bets – awarding their prize to economists who contradict each other (Eugene Fama and Robert Shiller).  The hedge strategy might be thought to ensure that the central bank’s prize winners were right at least half the time (which would be an improvement over the central bankers’ batting average in their awards), but that is a logical error.  It is perfectly possible for both of the prize winners to be wrong.  I’ll explain why I think that is the case in a future article.

In this article I respond to Chetty’s effort to defend economists from the ridicule that the most recent Riksbank award prompted.  Chetty is professionally embarrassed by that ridicule.

The first words of his article are:  “CAMBRIDGE, Mass. — THERE’S an old lament about my profession: if you ask three economists a question, you’ll get three different answers.”  Chetty’s “old lament” is accurate, but incomplete.  The “economist’s lament” has many verses.

  • If you ask three economists a question, you’ll get three different answers
  • The three answers will be opinions driven by the economists’ ideologies
  • The answers will ignore the relevant multidisciplinary literature
  • The answers will ignore the relevant economics literature that challenges the answers
  • The answers will arise from studies that fail basic requisites of the scientific method, e.g., they will implicitly assume that alternative causes do not exist
  • The empirical methodology used to support the answers will often be so biased that it seems to support answers that are the opposite of reality
  • The economists frequently water board their data until they seem to confess the answer that comports with the economist’s dogmas
  • All three answers are wrong, horribly wrong
  • The policies that the economists recommend on the basis of their ideologies and tortured data are often destructive and they breed complacency by assuming away critical risks
  • The policies that the economists recommend often produce unanticipated consequences that prove even more destructive
  • The economists are blind to conflicts of interest and eagerly seek out such conflicts to enrich themselves
  • The economists are blind to ethics, even disdainful of it
  • The economists will rarely admit that they were wrong and reconsider their dogmas

Chetty’s effort to defend economists was less than robust.  He did not defend the answers economists reach as being the product of science.  Instead, he argued that economists should not be mocked by real sciences because economists would really, really like to be scientists.

“But the headline-grabbing differences between the findings of these Nobel laureates are less significant than the profound agreement in their scientific approach to economic questions, which is characterized by formulating and testing precise hypotheses. I’m troubled by the sense among skeptics that disagreements about the answers to certain questions suggest that economics is a confused discipline, a fake science whose findings cannot be a useful basis for making policy decisions.”

Chetty thinks critics who point out that economists don’t achieve science even though they purport to aspire to it are “unfair and uninformed.”

“That view is unfair and uninformed. It makes demands on economics that are not made of other empirical disciplines, like medicine, and it ignores an emerging body of work, building on the scientific approach of last week’s winners, that is transforming economics into a field firmly grounded in fact.”

Again, Chetty’s idea of a defense reads more like a petulant confession of failure.  We are supposed to be impressed that, in late 2013, economics is seeking to “transform” itself “into a field firmly grounded in fact.”  A science does not have “transform” into a science.  Economists could have modeled the scientific method for well over a century.  A large minority of economists continue to urge us to inflict austerity in response to a Great Recession – the equivalent of pre-scientific “medicine” bleeding sick patients.

Chetty then tells us what he believes is the core problem with economics and why economists are finally “transforming” economics into a reality-based field.

“As is the case with epidemiologists, the fundamental challenge faced by economists — and a root cause of many disagreements in the field — is our limited ability to run experiments.

(Surely we don’t want to create more financial crises just to understand how they work.)

Nonetheless, economists have recently begun to overcome these challenges by developing tools that approximate scientific experiments to obtain compelling answers to specific policy questions.”

Chetty’s parenthetical says it all, for economists have “create[d] more financial crises” precisely because they do not “understand how they work” yet they dogmatically insist on policies that prove ever more criminogenic.  Economists would understand how they work if they actually followed the scientific method.

Chetty’s statement that economics is “transforming” into a “science” based on “facts” because economists have “begun” to study “natural experiments” is as bizarre as it is inaccurate.  I was taught over 40 years ago by my economics and statistics professors to study natural experiments and none of my teachers suggested that the methodology was novel.  I was taught the same thing in criminology 20 years ago.  As regulators we successfully used natural experiments for “testing precise hypotheses.”  In analyzing the causes of the current crisis I have repeatedly emphasized the usefulness of the natural experiment provided by “liar’s” loans for “testing precise hypotheses.”  As I explain below, neo-classical economists studied natural experiments 30 years ago during the S&L debacle.  The difference is that the economists’ dogmas caused them to implicitly constrain the range of alternative hypotheses to exclude accounting control fraud as a candidate explanatory variable.  As regulators, we did not arbitrarily constrain potential explanatory variables by excluding fraud.  The result is that we got it right and the economists got it as wrong as it is possible to get something wrong.

Testing natural experiments is a fine idea that all social sciences embraced decades ago.  It is bizarre and inaccurate for Chetty to claim that it is novel and that it produces “science.”  It can help and it can hurt depending on how well it is conducted.  It is one important methodology, not the holy grail of scientific methodology for economics or criminology.

I will discuss several examples of why Chetty’s “scientific experiments” have repeatedly produced what economists assured us were “compelling answers to specific policy questions” that were disastrously wrong.  It turns out that the scientific method that economists purport to embrace is frequently the thinnest of fancy veneers hiding a core composed of the cheapest pressboard.  Economists who study fields beset by financial frauds, for example, are overwhelmingly betrayed by ideology and conflicts of interest.

Economists do not study fraud.  They have a primitive tribal taboo against using the word.  This, of course, is because economics is assuredly not “firmly grounded in fact.”  Ignoring fraud is a pure ideological construct that requires economists to ignore fraud, particularly private-sector “control fraud.”  Economists do not study the criminology literature on elite white-collar crimes.  Economists do not study and do not understand sophisticated financial fraud schemes.

I will briefly mention five examples during the savings and loan debacle.  Richard Pratt, an academic economist who was Chairman of the Federal Home Loan Bank Board, exploited a series of natural experiments to study which state-chartered S&Ls reported the highest income.  The answer was Texas.  Pratt, the architect of the deregulation bill that became law as the Garn-St Germain Act of 1982, used Texas’ deregulation law as the model for the Garn-St Germain Act.

Alan Greenspan, having studied the natural experiment provided by S&Ls following different investment strategies praised Charles Keating’s Lincoln Savings as the exemplar that should be the model for the industry because Lincoln Savings reported record profits.  Greenspan assured the federal regulators that Lincoln Savings “posed no foreseeable risk of loss.”

Daniel Fischel, exploiting a similar natural experiment, praised Lincoln Savings as the Nation’s best S&L.  He also praised CenTrust as a superb S&L.  In each case the basis for his conclusion was the extreme income reported by the S&L.

George Benston used a natural experiment by studying state-chartered S&Ls that had made large amounts of “direct investments” that the federal regulators were proposing to restrict.  He found that such S&Ls reported substantially higher income than other S&Ls.

James Barth studied a natural experiment provided by failed S&Ls and concluded that their owners must have been honestly gambling for resurrection because as the S&Ls approached failure they increasingly invested in high risk assets.  Barth was the regulatory agency’s head economist.

The common denominators in these five examples are that the economists implicitly assumed accounting control fraud out of existence and as a result their conclusions were false.  The “recipe” for accounting control fraud by a lender has four ingredients.

  1. Grow extremely rapidly by
  2. Making enormous numbers of bad quality loans at a premium yield while
  3. Employing extreme leverage and
  4. Providing only trivial allowances for loan and lease losses (ALLL)

The recipe produces three “sure things.”  The lender is guaranteed to report record income in the near term, the senior officers will be made immediately wealthy by modern executive compensation, and the lender will eventually suffer severe losses.  Texas led the Nation in accounting control fraud because it deregulated and desupervised, so its S&Ls reported the highest (fictional) profits and suffered the worst losses.  Pratt’s use of Texas as the model for deregulation was the worst possible choice and caused catastrophic harm.

Greenspan’s assurance that Lincoln Savings posed no foreseeable risk of loss proved incorrect – it caused the largest loss to a federal deposit insurance fund in history.  It was impossible for Greenspan to make a larger error when writing about a single institution.

Fischel praised the worst, most fraudulent S&L in the Nation as the best S&L.  He made a 3,000 position error in an industry with 3,000 positions.  It is impossible to get it more wrong.  CenTrust was also a massive accounting control fraud that caused roughly $1 billion in losses.

Benston praised roughly 33 S&Ls that made large amounts of direct investments – they all failed.  They were overwhelmingly accounting control frauds.  It is impossible in a sample size of 33 to bat worse than 0 for 33.  Greenspan, Fischel, and Benston shared another characteristic that helps explain the astonishing extent of their errors – Lincoln Savings paid for their research.

Barth did agree that control fraud existed, but he missed the fact that firms following the fraud recipe will invest heavily in high risk assets but they will do so in a manner that demonstrates that they are engaged in accounting control fraud rather than honest gambles.  George Akerlof and Paul Romer’s 1993 article (“Looting: The Economic Underworld of Bankruptcy for Profit”) explained this point in detail.

“[M]any economists still [do] not understand that a combination of circumstances in the 1980s made it very easy to loot a [bank] with little risk of prosecution. Once this is clear, it becomes obvious that high-risk strategies that would pay off only in some states of the world were only for the timid. Why abuse the system to pursue a gamble that might pay off when you can exploit a sure thing with little risk of prosecution?”

[S]omeone who is gambling that his thrift might actually make a profit would never operate the way many thrifts did, with total disregard for even the most basic principles of lending: maintaining reasonable documentation about loans, protecting against external fraud and abuse, verifying information on loan applications, even bothering to have borrowers fill out loan applications” (Akerlof & Romer 1993: 4-5).

Akerlof and Romer made this passage their concluding paragraph in order to gives special emphasis to the message to their field.

“Neither the public nor economists foresaw that [S&L deregulation was] bound to produce looting.  Nor, unaware of the concept, could they have known how serious it would be.  Thus the regulators in the field who understood what was happening from the beginning found lukewarm support, at best, for their cause. Now we know better.  If we learn from experience, history need not repeat itself” (George Akerlof & Paul Romer1993: 60).

Economists overwhelmingly supported the deregulation of S&Ls.  Larry White’s famous phrase was that there were “no ‘Cassandras’” in his field who warned that deregulation would produce a disaster.  Economists overwhelmingly and vociferously opposed our reregulation of the S&L industry (claiming we were economically illiterate).  Economists did not provide us with “lukewarm support” – they were our leading opponents in our successful effort to contain the epidemic of accounting control fraud that drove the crisis.  Chetty denied the problem, but the “facts” are what demonstrate that economists as a field performed during the S&L debacle as “a fake science whose findings cannot be a useful basis for making policy decisions.”  In every case the policies that proved disastrous were based on precisely the econometric practices that Chetty claimed were “transforming” his field into a “science.”

George Akerlof received the Riksbank award in 2001.  The Akerlof work that the award committee singled out for praise was his 1970 article on markets for “lemons” in which he explained anti-purchaser control frauds in which the seller deceives the purchaser about the quality of the goods or services.   Akerlof (1970) and Akerlof and Romer (1993) both studied natural experiments.

Chetty’s article disses economists who are theorists and praises quants.  He mentions two theorists, Paul Krugman and Janet Yellen (both of whom have done extensive quantitative research) in a manner that implies that they are primitives who have missed the field “transforming” into a “science” based in “facts” – Paul Krugman and Janet Yellen.  Krugman is another recipient of the Riksbank prize and Yellen is President Obama’s nominee to run the Federal Reserve (and Akerlof’s spouse).  If Chetty’s dichotomy between theorists and scientists were true we would have to wonder why economics continues to bestow its top honors on economists whose work is not scientific because it is not “firmly grounded in fact.”  But Chetty’s dichotomy is false.  He is simply engaged in the highly scientific practice of a Harvard prof dissing his more prestigious peers who have taught at Princeton and Berkley.

Akerlof and Romer exposed the most fundamental problem with Chetty’s theory of the scientific method.  Fact and theory are both vital.  If economists’ dogmas and mono-disciplinary blinders prevent them from understanding that control fraud exists then Chetty’s supposed recipe for science – “formulating and testing precise hypotheses” – will consistently produce failed empirical studies that economists will interpret as supporting policies that cause our recurrent, intensifying financial crises.  Good theory is essential to constructing good empirical studies.

Akerlof and Romer worked closely with a financial regulator (me) in drafting their famous article.  That meant that they had the advantage of being firmly grounded in fact and a wealth of multi-disciplinary learning (including white-collar criminologists whose work I was drawing on) – an advantage that Akerlof and Romer enthusiastically welcomed.  Note that Akerlof and Romer rightly stressed other forms of learning that proved far superior to “scientific” economists precisely because the examiners exemplify the concept of learning that is “firmly grounded in fact.”  Akerlof and Romer praised “the regulators in the field who understood what was happening from the beginning….”

Chetty has conflated “data” with “facts.”  Accounting control fraud produces fraudulent accounting data that economists and finance scholars treat (implicitly) as facts.  During the expansion phase of a bubble or an expanding epidemic of accounting control fraud the traditional econometric study will lead the “scientific” economist to support the worst possible policies that most aid accounting control fraud.  Whatever practices best facilitate the creation of fictional income will show the highest positive correlation with the firm’s reported income (or stock price).  The true (negative) “sign” of the correlation will only emerge after the bubble bursts or years after the fraud epidemic begins.  By then, of course, it is too late to prevent the crisis brought on by the “scientific” economists’ disastrously bad policy recommendations.

Note how pernicious this methodological failure is when combined with neo-classical economists’ insistence that it be made unlawful to adopt regulations until the regulators can produce data demonstrating that the benefits of the new rule would outweigh the costs.  The D.C. Circuit, controlled by ultra-conservative law and economics devotees is using this as the pretext to block the SEC from adopting vital regulations.  The D.C. Circuit has effectively resurrected the discredited anti-regulatory “substantive due process” abuses that the judiciary abused 80 years ago.

Chetty is a mono-methodologist.  Only quant work is “scientific.”  Other social sciences that use multiple research methodologies, e.g., criminology must not be “scientific.”  Chetty’s view of the scientific method represents dogma and personal predilections rather than science.

Competent bank examiners never forget that accounting data can be the product of accounting control fraud.  Examiners produce the equivalent of hundreds of detailed case studies that can be examined rigorously for common characteristics.  It was our “autopsies” of every failed S&L that led to our development of the concept of control fraud and the subset we now call accounting control fraud.  The autopsies led to our identification of the fraud “recipe” for a lender.  We consistently studied natural experiments to test precise hypotheses in order to formulate the radical policy changes that contained the epidemic of accounting control fraud that drove the second phase of the S&L debacle.  But we did more that test hypotheses – we formulated theories such as the concepts of control fraud and accounting control fraud and the fraud recipe.

We synthesized a theory of control fraud, building it from economics, law, criminology, accounting, governance, and political science.  We built in many economic concepts that proved immensely useful.  We stressed the perverse incentives arising from “agency” problems in corporations and how modern executive compensation aggravates the incentives, allows the CEO leading the control fraud to signal other officers on the practices they should follow to aid the fraud, and serves as a means to loot the firm.  We realized that the decline of financial partnerships with “joint and several liability” greatly increased agency problems by eroding “private market discipline.”  We understood how the CEOs manipulated professional compensation to create a “Gresham’s” dynamic that drove good ethics from professions and markets.  The art was for the CEO to suborn purported “controls” and pervert them into fraud allies.  The professionals’ reputation aided the fraud scheme.  We understood that markets were frequently deeply inefficient because the fraud recipe made reporting record profits a “sure thing.”  Banks do not create private market discipline – they fund the massive growth of firms that report record profitability due to the fraud recipe.  We realized that lenders following the recipe had to gut their underwriting standards and suborn their internal controls.  We used this to identify the frauds while they were still reporting record profits.  We understood that these practices created intense “adverse selection” and meant that the lending had a “negative expected value” at the time they were made.  We determined that the recipe was a superb means of hyper-inflating a financial bubble and realized the significance of the industry expression “a rolling loan gathers no loss.”  We developed a superior understanding of “moral hazard” and the nearly universal practice of economists implicitly assuming control fraud out of existence and assuming that moral hazard led solely to honest gambles.

Understanding the recipe allowed us to identify the worst accounting control frauds at an early point while they were still reporting record profits.  The recipe also allowed us to target the frauds’ Achilles’ “heel” – the need to grow extremely rapidly.  Our rule restricting growth doomed even the S&L control frauds we could not close promptly because we lacked the funds.

As S&L regulators, we made our top supervisory priority the S&Ls reporting the highest income.  Economists viewed this as proof that we were economically illiterate.  Charles Keating famously sent a letter to much of the Nation’s political leadership on July 8, 1986 that specifically attacked us for this prioritization.  The letter calls us “Nazi” and then cheerfully mixed its sensational similes by concluding that our policy was “like Jupiter eating his children.”

Bank Board Chairman Edwin Gray began S&L reregulation in 1983 – the year after the Garn-St Germain Act implemented federal deregulation and triggered a regulatory “race to the bottom” among state regulators.  By 1984, there were 300 S&L control frauds growing at an average annual rate of 50 percent.  It is only with the benefit of hindsight informed by our experience with the current crisis that we can now understand how incredibly valuable it was that Gray began the reregulation of the industry so promptly.  The reregulation was done in the teeth of vicious opposition from the Reagan administration, James Wright, Jr., the Speaker of the House, a majority of the members of the House, the five U.S. Senators who became known as the “Keating Five,” every outside economist who expressed an opinion, the industry, and the business media.  It soon rendered Gray unemployed and unemployable for over two decades.  Absent that prompt reregulation, resupervision, and beginning criminal referrals and prosecutions the S&L debacle would have become vastly more damaging.  In retrospect we can see that good regulatory theory saved trillions of dollars and that bad economic studies that followed Chetty’s claims of proper scientific method would have led  to terrible policies that would have added trillions of dollars of losses had we (the S&L regulators) not countered the studies and followed the opposite policies.

The advantages of good theory were demonstrated in 1990-1991 during the S&L debacle when the control frauds opened a second “front” in Orange County, California (where all good U.S. financial fraud epidemics begin).  The primary “ammunition” used for accounting fraud during the debacle was commercial real estate loans.  Orange County control frauds began to make significant amounts of what are now called “liar’s” loans.  They had no such warning label in this era.  We were the regional regulators with jurisdiction over Orange County S&Ls and we listened to our examiners.  Our examiners stressed that no honest mortgage lender would make such loans without underwriting key information such as the borrower’s income.  Absent such underwriting, a mortgage lender creates severe adverse selection and the lending has a negative expected value.  In plainer English, the lender will lose money.  Liar’s loans do, however, make sense for an accounting control fraud.  We drove liar’s loans out of the S&L industry.  We did this while heavily occupied dealing with the overall S&L debacle.  It was one of the easiest supervisory calls we ever made.

Again, the current crisis, which was driven principally by an epidemic of fraudulent liar’s loans, allows us to understand for the first time how much this regulatory crackdown on liar’s loans in 1990-1991 saved the Nation and the world trillions of dollars in losses.  The current crisis could not have grown to such epic proportions absent the anti-regulatory studies and theories of economists that regulatory leaders adopted under the Clinton and Bush administration.  These theories implicitly taught that control fraud did not exist because markets must be self-correcting to be efficient.   The crisis could not have occurred without ignoring the findings and experience of competent regulators, industry experience, criminologists, and Akerlof and Romer.

The tragedy, however, is that economists’ anti-regulatory, pro-corporate biases have proven so all-consuming that most economists are so anti-scientific that they have refused to learn from the control fraud epidemics that drive our recurrent, intensifying financial crises.  The industry and the regulators during this crisis had the advantage of our crackdown on liar’s loans and the fact that the industry was now calling the loans “liar’s” loans.  There was no subtlety to this first aspect of the loan origination fraud epidemic.  No government agency or law required or recommended that lenders make liar’s loans.  But economists also had the advantage of Akerlof and Romer’s 1993 article about “looting.”  Akerlof and Romer’s general point that accounting control fraud existed and could drive crises and the admonition that now we (economists) know better and that if we learn from the looting we need not suffer a recurrence of the crises should have alerted every economist to the danger.  Even better, the article specifically warned that we could recognize the frauds by looking for lenders that failed in “maintaining reasonable documentation about loans, protecting against external fraud and abuse, verifying information on loan applications, even bothering to have borrowers fill out loan applications.”  They warned their field against the specific fraud scheme that drove the current crisis – a full decade in advance.  Their article also warned about fraudulent lenders exploiting loan brokers’ perverse incentives to originate bad loans and then sell the loans in the secondary market (1993: 29, 46).  Economists did not simply fail to warn about the fraud epidemics – they recommended doubling down on the criminogenic policies (the three “de’s” – deregulation, desupervision, and de facto decriminalization) that Akerlof and Romer warned were “bound to produce looting.”  Economists, in the rare cases where they mentioned fraud, claimed that fraud posed no risk in “sophisticated” financial markets.  Complacency is one of the most destructive mindsets a regulator can have.

I have explained in depth the lead role that fraudulently originated liar’s loans played in driving the crisis.  The brief summary is that the incidence of fraud in liar’s loans, according to the industry’s own anti-fraud experts was 90 percent.  The massive expansion of liar’s loans caused the bubble to hyper-inflate.  Liar’s loans grew by roughly 500% from 2003-2006.  By 2006, roughly half the loans that the industry called “subprime” were also liar’s loans (the two categories are not mutually exclusive) and about 40% of all home mortgage loans originated in 2006 were liar’s loans.  In 2006 alone, the industry originated over two million fraudulent liar’s loans.

The other aspect of the loan origination fraud epidemic, appraisal fraud, was even more blatant.

“From 2000 to 2007, a coalition of appraisal organizations … delivered to Washington officials a public petition; signed by 11,000 appraisers…. [I]t charged that lenders were pressuring appraisers to place artificially high prices on properties [and] “blacklisting honest appraisers” and instead assigning business only to appraisers who would hit the desired price targets” ( FCIC 2011: 18).

The petition was corroborated by two surveys of appraisers.  A survey in 2003 found that 55% of appraisers reported being coerced to inflate at least one appraisal that year.  A repeat of the survey in 2007 found that the percentage that had experienced coercion that year had risen to 90 percent.  Sixty-eight percent of appraiser reported having lost a client and 45% reported that they were not paid for their work when they resisted coercion.  Demos published a study in 2005 that reported that appraisal fraud had become “epidemic.”  Then New York Attorney General Cuomo reported that his investigation had confirmed that Washington Mutual (WaMu) had blacklisted appraisers who refused to inflate appraisals and that this practice was the norm for the industry.

The mortgage lending industry and the regulators could have figured out everything necessary to prevent the crisis had they understood accounting control fraud and the import of the petition.  Here are the key conclusions that the industry and regulators should have drawn.

  • Lenders and their agents are causing inflated appraisals
  • Appraisal fraud had become epidemic
  • No honest lender would inflate appraisals or allow them to be inflated
  • The lenders’ strategy is to generate a Gresham’s dynamic and suborn appraisers
  • Only rational if covering up underlying mortgage fraud, i.e., liar’s loans
  • There is no fraud exorcist, so the fraudulent loans are sold fraudulently
  • The MBS and CDO are backed by fraudulently inflated appraisals

Individually, each of the three control fraud epidemics (liar’s loans, appraisals, and secondary market sales through fraudulent “reps and warranties”) would have represented the most destructive financial frauds in world history.  Collectively, they caused catastrophic, global damage and unprecedented fraudulent enrichment of the officers that led the control frauds.

As remarkable as the near total failure of economists to “know better” about twin loan origination fraud epidemics that we had seen, and successfully suppressed before, the truly remarkable demonstration of how self-destructive economists’ dogmas are of their ability to go beyond a shambolic parody of the scientific method is their work after the crisis that purports to explain what caused the crisis.  In virtually all cases (1) they never consider the possibility of accounting control fraud, (2) they do not discuss or even cite Akerlof and Romer 1993, and (3) they do not discuss the relevant criminology literature.  They purport to use natural experiments “testing precise hypotheses” but they implicitly exclude accounting control fraud as a possibility.  Because the exclusion is implicit, it is not supported by reasoning.  Indeed, it is unlikely that the researchers consciously know that they have excluded control fraud.  Ideology and mono-disciplinary blinders consistently trump the scientific method.  We have the worst of all worlds because the researchers believe they are the very model of the modern scientific economist while the reality is that they are in thrall to their dogmas, which implicitly censor out alternative theories of causation that would falsify their ideologies.  To gleefully mix Gilbert and Sullivan tunes, the economists that Chetty praises became the equivalent of admirals in their field because they stuck close to their desks and never went to sea to battle the three most devastating epidemics of financial fraud in world history.

I’ll end with one such example, of over a hundred.  I picked it because it explicitly discusses liar’s loans at one of the large accounting control frauds, Bear Stearns (Bear).  It is a 2009 study entitled “Taking the Lie Out of Liar Loans.”

The researchers studied loans made by Bear and its affiliates.  They explain that Bear’s mortgage loan originations became increasingly dominated by liar’s loans.  The authors do not attempt to explain why Bear’s leadership chose to increasingly originate overwhelmingly fraudulent loans that the industry called “liar’s” loans.  The article exemplifies economists’ tribal taboo about the frightening power of the “f” word.  An article focused on fraudulent loans never uses the word “fraud.”  The article never cites Akerlof and Romer (1993), the relevant criminology literature on control fraud, or the fact that the other two modern financial crises (the S&L debacle and the Enron-era scandals) were driven by epidemics of accounting control fraud.  It ignores our 1990-1991 experience with liar’s loans.

The article implicitly assumes that accounting control fraud by lenders cannot exist – even when lenders employ a type of loan that they know will produce endemically fraudulent loan originations.  Indeed, Bear massively increased its liar’s loans knowing that they were frequently fraudulent.

The authors’ seemingly sensible, but actually bizarre presumption underlying the article is that they are developing a proposed means of underwriting to reduce the fraud incidence of inflated borrowers’ incomes in liar’s loans.  The obvious, except to economists, analytical point that explains why the authors’ presumption is bizarre is that lenders have known for centuries how to underwrite home loans in a manner that reduces fraud by borrowers to trivial levels.  The officers controlling fraudulent home lenders created the perverse compensation systems of loan officers and loan brokers and enthusiastically embraced endemically fraudulent liar’s loans because they did not wish to engage in effective underwriting.  Effective underwriting would prevent them from attaining the “sure things” offered by the fraud recipe.  The authors’ crude underwriting substitute could not reduce fraud remotely as effectively as real underwriting.  Neither fraudulent nor honest officers would use the authors’ underwriting substitute.  The fraudulent officers did not want to exclude bad loans and honest officers would have found the authors’ underwriting substitute grossly inferior to real underwriting.

Using euphemisms for fraud, the authors repeatedly confirm the endemic inflation of the borrower’s income in liar’s loans.  In no case, however, do they even consider that the officers controlling the lender could have been engaged in accounting control fraud.  The closest they come was to note that a journalist assumed that liar’s loans were actually profitable to the lender because “lenders may have incentives to encourage brokers to solicit stated-income loans because such loans may produce ‘excessive rates and penalties.’”  The authors did not bother to analyze the journalist’s claim.

The authors also implicitly assumed appraisal fraud out of existence because they rely uncritically on reported “loan-to-value” (LTV) ratios.  In one case the authors note the possibility that the “the borrower (and/or broker) may have exaggerated income to qualify for a loan that is greater than they can really afford.”  The possibility that the officers controlling the lender knew that brokers and loan officers would encourage or even directly cause the inflation of the borrower’s income pursuant to the fraud “recipe” was ignored.  In eight places in their article the authors assumed that it was solely the borrowers who must be inflating their incomes and implicitly assumed that the lender’s controlling officers would have been determined to prevent such frauds.  The authors ignored all the investigators who testified that it was lenders and their agents that put the lies in liar’s loans and all the warnings to the lenders that liar’s loans were endemically fraudulent (I have detailed these in prior articles).

The mono-disciplinary authors emphasize that they were the first to study the effect of liar’s loans on loan defaults (by which they mean the first economists to study).  Consider how crazy that is for a field that pretends to science.  The biggest development in real estate, by far, was the rise of nonprime loans, particularly liar’s loans and most particularly subprime liar’s loans.  The context was that even many economists were warning about a massive housing bubble.  The rise in liar’s loans was so rapid from 2003-2006 that they were the marginal loan driving the bubble to hyper-inflate.  The Federal Reserve’s supervisors were so worried about the spread of non-prime loans that, despite Greenspan’s disapproval they conducted an exceptionally limited inquiry into the largest banks’ origination of non-traditional mortgages.

“Sabeth Siddique, the assistant director for credit risk in the Division of Banking Supervision and Regulation at the Federal Reserve Board, was charged with investigating how broadly loan patterns were changing. He took the questions directly to large banks in 2005 and asked them how many of which kinds of loans they were making.  Siddique found the information he received ‘very alarming,’ he told the Commission.

In fact, nontraditional loans made up 59 percent of originations at Countrywide, 58 percent at Wells Fargo, 51 at National City, 31% at Washington Mutual, 26.5% at CitiFinancial, and 28.3% at Bank of America. Moreover, the banks expected that their originations of nontraditional loans would rise by 17% in 2005 to 608.5 billion. The review also noted the ‘slowly deteriorating quality of loans due to loosening underwriting standards.’ In addition, it found that two-thirds of the nontraditional loans made by the banks in 2003 had been of the stated-income, minimal documentation variety known as liar loans, which had a particularly great likelihood of going sour.

The reaction to Siddique’s briefing was mixed. Federal Reserve Governor Bies recalled the response by the Fed governors and regional board directors as divided from the beginning. ‘Some people on the board and regional presidents . . . just wanted to come to a different answer. So they did ignore it, or the full thrust of it,’ she told the Commission.

Within the Fed, the debate grew heated and emotional, Siddique recalled.  ‘It got very personal,’ he told the Commission.  The ideological turf war lasted more than a year, while the number of nontraditional loans kept growing….” (FCIC 2011: 20-21).

The Fed is dominated by neo-classical economists.  What was the reaction of many of the Fed’s senior economists to the facts of mortgage lending?  They were enraged at their own supervisory messengers.  It was just data – supplied by the biggest banks – yet because it was counter to their dogmas the reaction was “emotional” and “heated” and directed against the supervisors rather than the banks.  The telling phrase about dogma is that opponents of supervision “wanted to come to a different answer.  So they did ignore [the data].”  The Fed is supposed to be the high temple of the quants that Chetty claims are transforming economics into a science.

But here is the real takeaway about economists and their pretensions to be scientists.  The Fed employs hundreds of economists who are supposed to study important economic developments.  There were no more important micro-foundational developments than the three mortgage fraud epidemics and the hyper-inflated bubble that they produced.  The Fed’s economists, according to the authors of the study I have been discussing, failed to study the four developments that were about to cause a catastrophe.  To make it worse, only the Fed had the authority under the Home Ownership and Equity Protection Act of 1994 (HOEPA) to ban all liar’s loans and the Fed held a series of hearings mandated by Congress at which there was extensive testimony about liar’s loans.  The Fed’s economists, therefore, should have made studying the three mortgage fraud epidemics and the resultant bubble their highest research priority.  That’s what scientists would have done.

But those studies would have produced results that would have devastated the dogmas that rule the Fed’s economists.  The effectiveness of those ideological blinders in preventing serious research on the frauds by the Fed’s economists continues to this day.  This is a very old story.  Michael Jensen, when he was the managing editor of the Journal of Financial Economics, discovered that no proposed article could get through peer review if it challenged the efficient market hypothesis.  Jensen was a strong supporter of EMH, but he was appalled by this triumph of dogma over science.   He published an “anomalies” volume, though as he noted in the first volume each of the contributors professed belief in EMH.

The strength of Jensen’s endorsement for EMH, even when he discovered that his colleagues were ruled by their dogmas should be a cautionary tale with regard to Chetty’s claim that this time it’s different, this time economists will behave like scientists.  Jensen stated:  “I believe there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.”  If he is correct, then the costly collapse of EMH suggests that all other economic propositions rest on even shakier foundations built on friable dogma rather than bedrock facts.

 

34 Responses to Economics could be a Science if More Economists were Scientists

  1. Is not the fundamental error of economists the assumption that we need government-backed banks? And that we need a government-enforced monopoly money supply for all debts, not just debts to government?

    You guys best hurry with figuring out how money should be implemented since the world is only getting more dangerous. One would think that honesty and ethics would be prudent principles to follow but, of course, it is widely assumed that such things are a hindrance or at best irrelevant to money creation.

  2. Harry Truman famously asked for a one-armed economist, because the ones he had were always saying “on the other hand, …”. It seems that economics used to be more scientific, in that the economist knew that he could not conduct a controlled experiment the same way a chemist can, and because of that it was hard to determine the exact results of any policy in an uncontrolled real world environment. (Dealing with fraud is criminology, not economics.) Today, economists do seem to advocate policies that suit their politics, and tend to be dismissive, if not slanderous, of diverse opinions. If Truman were alive today, he would have his wish.

    • > (Dealing with fraud is criminology, not economics.)

      That is exactly the attitude I was dealing with in the “Why Understanding Fiat Currency Matters For Scientists: We Are Being Pitted Against Public Health” post.

      Economics has to do with the way so called “rational” economic actors act. If Economics “Scientists” rule out the idea that they have to consider “rational” economic actors who further their rational benefit through fraudulent means, then they are assuming away a significant part of the population for which they are developing theories. Significance is not determined by how many such actors there are. Significance is determined by the impact they have on the economic system. Having lived through the latest economic calamity, nobody ought to be able to deny the significance of these economic actors in our very own economy.

      If you lived through the period when Enron took down the economy in California and the governorship of Gray Davis among a large population of people whose economic nest eggs Enron destroyed, then you have to understand how a small number of bad actors can have a huge impact on the economy that these economic “Scientists” are theorizing about.

      In the Dot Com bubble when these bad actors in the Mutual Fund management universe drove out all the good Mutual Fund managers through the workings of Gresham’s Law, then you know you have to take this into account. Certainly Gresham who came up with Gresham’s Law was an economist who understood the need to consider these things.

      I don’t suppose I will have any more success getting people reading this blog article to accept this premise than I had on article where the concept was not even part of the original blog post. If a reader can’t “get it” here, I don’t know what it would take for a reader to “get it” to get it.

      • At least since Adam Smith (who, I think, considered it axiomatic) economists have known that the profit motive can be abused by those with less than ideal morals. It is the job of government (law enforcement), not economists, to make fraud, burglary, murder, and other sociopathic acts unprofitable. Government that fails to do its policing duty is one that has been corrupted by the crooks, or is populated by members of the criminal set themselves, serving only temporarily in government. We have both, and no economic policy, not free markets or command economies, not MMT, not Capitalism or Socialism or Feudalism or Communism nor any other ism that has ever existed can save us from them. Crooks have existed under all sorts of economic systems, and will not be deterred by any economic policy.

        • Steven Greenberg

          Golfer1john,

          Did you miss the point in the article where Economists were pushing on the regulators to stop regulating? The economists were using profitability numbers generated by the crooks to prove that the most profitable business were the ones the regulators were trying to over regulate. In fact the numbers the Economists were depending on were completely phony, because the liabilities were not put on the books.

          If the economists want to come up with theories that only work if humans acted the way economists think they ought to, then they should put big caution labels on all their theories. The behavioral economists at least pretend that they are doing economics based on the way people really act. The popularized versions of what I have read about the behavioral economists make their work seem almost as (or maybe more) naive than the other economists.

          I am trying to get a young behavioral economist that I know to read and think about William Black’s article.

          • “regulation” seems to mean something different to you than to me. Getting a prosecutor or auditor to ignore fraud is not what honest economists mean by reducing onerous regulation. (Blankstein, Summers, Geithner, et al. are not who I mean by “honest” economists.) Deregulating the price of natural gas is what saved us from OPEC, and ended the inflation of the 1970′s. It involved no fraud at all. Have you listened to a TV commercial for a drug recently? It’s filled with such insipid regulation-inspired drivel as “Discontinue using ____ if you have an allergic reaction to it. Tell your doctor about all your medical problems.”

            If we had two different words for these two different processes, I think we might agree that one is good for the economy and the other bad.

            • Steven Greenberg

              golfer1john,

              So, essentially your answer is that you did miss that part of the article. You may think you know what “honest” economists mean. William Black is telling you what economists did. I’d rasther pay attention to what they did than what they say they mean.

              As for Geithner and Summers, they have a well known record of what they did. It isn’t pretty. Google “Brooksley Born”, why don’t you?

  3. Very good. This is exactly what we need to see more of. A polemical stance, an uncompromising critique, AND – a willingness to call out both the intellectual corruption of academic Economics, and also the actual, literal financial corruption of the worst offenders. More “Inside Job” stuff. Some of these guys take dough. The public has a right to know which ones.

    It’s just like bribing a judge who’s already dishonest – Wall Street’s existing criminality doesn’t make economists’ collaboration with them less shocking. It makes it all the more shocking and shameful. I don’t know where this goes or what it leads to. Some of these people have a lot of power. Still. Everyone who has read “The Best Way to Rob a Bank is to Own One” knows that no one has more integrity, guts or determination than Bill Black.

    Let’s Rock.

  4. The irony of this article is that on this very web site, there is a contingent that adamantly refuses to understand the content of this article.

    Look at the discussion in the article
    Why Understanding Fiat Currency Matters For Scientists: We Are Being Pitted Against Public Health
    http://neweconomicperspectives.org/2013/09/understanding-fiat-currency-matters-scientists-pitted-public-health.html

    I repeatedly refer to the writings of William Black to urge caution in the proposals put forth by the Modern Currency Theory proponents. The person most often responding to my comments refuses to recognize the relevance of the possibility of fraud in talking about the theory.

  5. John Hemington

    You go Bill!!! About time the myth of economics as a science gets treated with all of the disrespect it deserves. There are a few attempting to be honest about this, but for the most part they, as you well know, are not permitted to be a part of the game. After all, real world information in too confounding to fit in the models of the neoclassical mindset.

  6. Yes, Steve, a lot of us have been arguing with Joe B etc for a long time here. The AMI/Huber etc ideas can look OK at first, but they aren’t carefully thought out, well grounded in the painstaking thought of MANY thinkers of the past and present like the deceptively simple ideas of MMT. They tend to get hung up on definitions of “money”; they are simply using a much less useful definition than MMT. If you complicate things at the beginning, then threading through the accounting of all the pointless smoke and mirrors is hard and one can convince oneself that the problem is that the USA, the UK etc don’t have the right money system, that they don’t spend by creating money without restriction right now. My hope is to present things as simply as possible to persuade such good folk.

    • and one can convince oneself that the problem is that the USA, the UK etc don’t have the right money system, Calgacus

      Yeah, what could possibly be wrong with a heavily subsidized usury for stolen purchasing power, especially from the poor, cartel in a supposedly free market economy? /sarc

      Like I said, much of MMT is an attempt to save banking from itself . The proper goal should be truly ethical money creation, not the perpetuation of known evil.

  7. William K. Black explained “control fraud” in 2005: “The Best Way to Rob a Bank Is to Own One: How Corporate Executives and Politicians Looted the S&L Industry.”
    Having seen him on BookTV, I bought and read the book, but at that time it was hard to conceive of control fraud as being in wide use and a factor in asset inflation, like what was going on with home values.
    As a regional planner for 35 years using the economic development precepts in program recommendations, after the 2008 financial crisis, I wanted to find out where the economics went wrong?
    The problem: economists paid no attention to private debt, assuming, apparently that for all consumer debt there was an offsetting asset. Clearly not the case and we are burdened with unpayable debt which, in the first place, was a mis-allocation of capital. the . The economists are still tweaking their models.
    “It is difficult to get a man to understand something, when his salary depends on his not understanding it,” wrote Upton Sinclair, in his 1934 book: “I, Candidate for Governor: And how I Got Licked.”
    In our society, “Fake It Till You Make It” is a legitimate strategy for those lacking self-confidence. In a confidence game, the con man’s absolute confidence in what he says is reassuring to the us, the marks, and we believe, even though she is faking it.
    We are living within a growth con.

  8. To take the point of the article one step further, the lack of scientific rigor extends well beyond the regulatory and control frauds. Take for example some very fundamental problems with the employment contract laid out by David Ellerman in “Property and Contract in Economics” as well as on his blog.

    http://www.abolishhumanrentals.org/
    http://www.ellerman.org/category/property-theory/

    In a science, like physics, once an idea is throughly discredited you basically never hear it again. It is certainly not defended in any serious manner. But in economics if the implications are too large or inconvenient the answer is changed to conform with the dominant dogma. It thus becomes hard to say things like our large financial institutions are criminal enterprises that need to be shut down and prosecuted, or the employment contract is invalid.

    • I looked at those links a little bit, and found the idea fascinating, but could not find any discussion of possible difficulties involved in prohibiting the rental of labor. Is there a blog or web site with such discussion?

  9. Whether economics is a science should be considered as a settled issue.

    There is no doubt that economics is a science. It is a branch of quantum physics.

    Economics does have immutable laws: physics laws of social science. Please check out
    http://econpapers.repec.org/paper/pramprapa/47811.htm

    Economics does have a universal mathematical framework like Maxwell’s Equations for electromagnetism: a fundamental equation of economics. Please check out
    http://econpapers.repec.org/paper/pramprapa/50695.htm

    Your time will be much better spent researching these papers than confusing philosophical debates.

    • Interesting. It certainly is obvious that human behavior is more like the behavior of fundamental particles in quantum physics than it is like Newtonian physics.

      Still, that does not negate the idea that macroeconomics can be done with Newtonian-style equations. Discovering quantum physics didn’t change the way falling objects fall. Macroeconomics is about averages, not about individual decisions, even though they make up the average. Just as you cannot predict whether a particular blackjack player will win money or not at a single session, you can still very confidently predict the percentage of players that will have winning sessions, and that the house will have a winning month every single month, notwithstanding the winning sessions. The beauty of both Newtonian physics and macroeconomics is that you don’t have to know the individual results, only the average, and the average is easily predictable.

      Two suggestions: have the English versions of the papers edited by a scientist whose first language is English; and have the comments about the laws of supply and demand reviewed by an economist. The comparison of the US housing market before and after the bubble shows a fundamental misunderstanding of the nature and scope of the laws.

      • Golfer1john,

        Great suggestions. I took those to my heart.

        Could you expand your comment “fundamental misunderstanding of nature and scope of the laws”? I will be very grateful.

        You are reading too much into the usage of the average in macroeconomics. Actually that is one source of many problems about today’s macro modeling. (1) A few years ago, Greenspan listed his main achievements as a central banker. His answer is his risk management approach to monetary policies. Risk management is all about tail risks and probabilities. It’s very hard to do risk management with just averages. (2) The dynamics of average and tail risks are often very different. Just focusing on averages, you are doing the macro modeling with your two hands tied behind the back. For example, the macro averages were just doing great in 2006 and most 2007. However, the tail risks of a severe downturn were skyrocketing because the peaking housing market and exploding volumes of synthetic CDOs. (3) By defination, the averages ignore uncertainties. At least half of economics is about uncertainties. (4) If the system is probabilistic in nature, like human society or multi-particle systems in physics or quantum systems, one can not use averages alone. That is well known in mature fields like statistical physics and quantum mechanics. I don’t think the macroeconomics is any different. (5) one could use averages to a particliar problem as long as one fully understands and declares that their work is incomplete.

        • I agree in general with your statements about averages. The old joke is that if you ask a statistician with one foot in a bucket of ice and the other in a bucket of boiling water how he feels, he says “On the average, pretty good.”

          If you want to track the progress of a large group over time, averages are pretty good. In the example of Greenspan, if he is claiming that whatever technique he used caused the average damage per year due to policy failures to go down, then the average might be a good measure of his success, if that metric is valid at all.

          If you want to fix the small number of problems in a large group, averages for the group more often obscure than reveal. The best tool I ever used for fixing performance problems on mainframes was originally called “fine grain analysis”. It presented graphical views of thousands of variables in increments down to a second, and showed things that just weren’t visible in the 1-hour averages. Of course, you have to have a monitor that gathers the stats at that level of detail. “180,000 jobs created last month” won’t help you figure out who got the jobs and why, but it will tell you that you’re not doing very well, and without having to know who got the jobs and why.

          The demand curve, and the law of demand, applies to a point in time. It tells the supermarket manager that if he lowers the price of oranges, he will sell more oranges today. Likewise in housing, sellers can get more interest and a quicker offer by lowering the price.

          The difference in housing before and after the bubble was a shift in the demand curve over time, not movement along an upward-sloping curve. The bursting of the bubble shifted the curve to the left, so that at any given price, fewer homes were demanded. It doesn’t mean that builders could have sold more homes if they just raised their prices to the level that prevailed during the bubble. That change does not represent a positively sloped demand curve. Demand curves are positively sloped only in certain rare circumstances, such as some luxury goods, where the higher price of something in very limited supply makes it an even more desirable status symbol.

          • Golfer1john,

            Thank you for your detailed explanation of demand curve shifting. I found that’s very helpful. However, I disagree that there is a fundamental misunderstanding on my part. I will explain why in the following.

            Regarding laws of supply and demand and concept of market equilibrium, there are 4 versions of interpretations:

            Version 1. Laws of supply and demand and concept of market equilibrium should be regarded as mental activities in brains. In this interpretation, price, quantity of supply and demand, market equilibrium can not be observed in the market place. Milton Friedman once said there are just intentions. Lower prices leads more intentions to buy. Make lots of sense.

            Version 2: Laws of supply and demand and concept of market equilibrium should be used only in a hypothetical world of perfect competition. In that fair tale, laws of supply and demand work perfectly as if people act exactly according to these laws like robot without free wills, and market equilibrium is easily observable in those market places.

            Version 3: Price, quantity of supply and demand, and market equilibrium are measurable in the real world as economic indicators.

            Version 4: Acknowledge that markets in the real world is not perfectly competitive markets, and these laws don’t work in the real world. Therefore, in practice, use laws of supply and demand and market equilibrium very carefully with many constrains and conditions. For example, when talking housing supply, just focus on the home builders, never mind foreclosure supplies from foreclosures, and never mind the observation that home builders would rush the clear inventories when they see home prices are falling. Under this interpretation, the applications of laws of supply and demand are a form of art, not a real science because there is no existing formula to know how to add those conditions and constrains.

            In your replies, I noticed that you were using these 4 versions of interpretations interchangeably. When you were talking about supermarket manager, you were using version 3, because both price and quantity of goods sold can be observed in the real world. When you were talking about demand curve shifting, you were using the version 1 or 2 or 4, because your demand curves could not be observed in the real world.

            Why is it very important to separate these 4 versions of interpretations? The reason is very simple: law of supply and demand DO NOT ALWAYS WORK under version 3 or in the real world. There is no way for the supermarket manager to know for sure that lowering prices must bring more sells. No, no, no, the real world does not always work that way!

            Because these laws don’t always work, economists make them work in non-observable worlds.

            In version 1, if these laws are just mental activities, then these laws do not really matter at all, because even laws of physics do not have to work in mental activities. For example, if a man is dating a pleasant and beautiful girl, his mental time goes very quick. In contrast, if a man is dating an unpleasant and ugly girl, his mental time goes very slow. Of course, the measurable time in physics laws is independent of that man’s mental states.

            Version 2 is commonly used in economic textbooks. It is a fair tale. Again even physics laws do not have to work in fair tales.

            In version 3, laws of supply and demand simply do not always work as the way Newton’s laws of motion would. It works sometimes. It does not work in other times. The supermarket manager would easily find out that lowering prices sometimes does bring more sells, sometimes does not.

            In version 4, people are just pretending they always work in the real world. If laws not work, force them work in a narrower and even narrower sense.

            123 years has passed since Marshall’s book Principles of Economics. Why are so few economists writing about these laws of supply and demand are fundamentally flawed? My guess is that laws of supply and demand are universally accepted as the central tenet of modern economics after Al Marshall. You don’t question whether Jesus is the Son of God when you go to the church because that is the central tenet of Christianity. Otherwise, you make lots of enemies really fast. Another reason is that what is better alternative anyway. We at least do know that these laws work sometimes.

            Recently I came across some writings by former UCLA economic professor Steven Cheung. He wrote that he once worked very closely with Alchian, Friedman, Coase, and Stiglitz. In personal communications, they did have many discussions why these laws and concept of market equilibrium do not seem to work in the real observable world. These folks are the best economists. Of course, they knew flaws in these laws and concept of market equilibrium. But for some reasons, they preferred to keep to themselves in private while letting millions of students of economics treat them as words from God.

            My papers on physics laws of social science and fundamental laws of physics intend to provide a valid alternative. My approach only works with observable market supply, demand, and price indicators.

            Why Paul Krugman do not walk into physics department next door and declare half of physics professors in Princeton are not real scientists? My guess is that Professor Paul Krugman know all too well that Ph.D. degrees , professorships, and decades of education and research in economics under the flawed framework of laws of supply and demand and the concept of equilibrium do not make economists all that distinguishable from astrologists down the street in Township of Princeton! That is a problem!

            Why Paul

            Version 2:

            • I think you might be trying to extend the analysis of a competitive market to other types of markets. When you do that, you run into the problems you describe. When I studied economics, they taught three types or markets. Real world markets rarely perfectly match any of the types, but do share the characteristics, to a greater or lesser extent.

              The competitive market has lots of suppliers and lots of customers, and none of them are more than a fraction of a percent of the total production or purchasing. They have no market power, no bargaining power over prices. There is no differentiation among the products or services of various producers, one is the same as another, and the prices are known to the consumers. Think of a family farmer selling into the Chicago Mercantile Exchange. His corn is the same as everyone else’s corn, and whatever the price is that day, that’s what he gets. His demand curve is horizontal.

              The opposite of competition is monopoly. The supplier (or buyer, in monopsony) is the only one, and can set the price unilaterally. Monopoly suppliers set the price to maximize their profits, based on their cost curve and the demand curve of the entire market.

              In between is oligopoly, where there are a few suppliers, and there may be differentiation among products, or the appearance of differentiation. Think automobiles. In oligopoly, each producer has some limited market power. By advertising, he can attempt to differentiate his brand in the mind of the consumer in order to charge a higher price. Other producers might take the opposite strategy, advertising only that they have the lowest prices for the same products (think Walmart).

              The demand curves faced by the individual sellers in each type of market have different shapes. If the competitor tries to raise his price, he sells nothing, because all the needs of all the customers can be satisfied by other producers at the market price. If he lowers his price, he sells all his production, but he would have sold it all anyway at the market price, and so he loses some profit. The demand curve he faces is a horizontal line. If the oligopolist raises his price, he sells less, but his profits may be larger or smaller, depending on how difficult it is for his customers to change suppliers. Grocery stores traditionally have “loss leader” products for which they advertise the price, to get customers in the door, and while they are there they also buy other items on which the price is higher than the competition and profit is positive. It is difficult for shoppers to go to several stores to find the lowest price on every item. The oligopolist faces a demand curve that is near vertical at high prices and very low quantities, horizontal at low prices, and downward sloping in between.

              The monopolist faces the demand curve of the entire market. It slopes downward because people can afford more product at lower prices, or more people can afford to buy at all if it is not a necessity. Sometimes their demand curves are very steep (inelastic) because people must buy some amount of the product at whatever price, and often never need any more of it no matter how cheap it is. Retail gasoline is like that, in the aggregate, although there is often fierce competition among nearby stations. Perishable items tend to have steep demand curves, at least at low prices.

              I don’t know how one would state A law of demand that covers all these cases in their specificity, except the very general one that the quantity demanded tends to increase as the price falls. That is so vague as to be indisputably true nearly all the time. Or you could say the law is

              D = H(p)

              where H is the function that always perfectly describes the probability of demand. And you never have to disclose the nature of H.

              All you have to do to know that it works in the real world is to see the lines of people outside the stores on Black Friday. They are there for one and only one reason: lower prices.

              The law of demand is the basis for the advertising industry. If it didn’t work, there would not be an advertising industry.

              The law of demand does not exist only in people’s minds, or in hypothetical worlds, and does not require individuals to behave predictably, like robots. Sometimes some individuals just don’t care about price at all, within the range of reasonable prices for something. But in the aggregate, it does work in the real world.

              Much is made of the imperfection of information to the consumer. I live in an RV full-time, and travel a lot. Coming into a new place and needing gas, I have no idea what the prices are at the various stations, and might stop at the first one that looks good, and might pay 20 or 40 cents a gallon more than the one 1/2 mile down the road. Except that I have the Gas Buddy app on my phone, and I can see all the prices in town and select the station that suits me for price, brand, and location. The state of information available to the consumer is critical. Imperfect information is the basis of fraud in the marketplace, as well as for many instances where the law of demand as applied to the competitive market seems not to work. When information is imperfect, the demand curve is more like the oligopoly demand curve.

              You may say that the condition of imperfect information in the real world invalidates the law. I recall a joke from the Big Bang Theory. A farmer had chickens that were not laying as many eggs as they should, so he asked a physicist for help. The physicist thought for a while, and said “I have a solution for you. But it only works for spherical chickens in a vacuum.”

              I still say that the notion that the aggregate demand curve for the US housing market is upward-sloping is a fundamental misconception. It doesn’t happen, except for spherical houses in a vacuum.

              • Steven Greenberg

                Golfer1john,

                “If the competitor tries to raise his price, he sells nothing, because all the needs of all the customers can be satisfied by other producers at the market price. If he lowers his price, he sells all his production, but he would have sold it all anyway at the market price, and so he loses some profit. The demand curve he faces is a horizontal line.”

                The demand curve is obviously not flat because anybody that lowers the price gets all the sales. The supply curve seems to be flat for an individual seller, perhaps for a while. But the shallow moat entices another seller to enter the market. That seller gets all the sales and goes from 0 market share to 100% market share. Do the other sellers just go out of business or do they lower their prices to compete? You explanations that prove your theses are very incomplete in describing the possible reactions.

                Talk about being able to sell it all at market prices ignores the entry of more customers into the market if the prices come down. In the oligopoly, if one person seller takes market share from others by lowering prices, then the other sellers would respond in order to get their share of the market back.

                Have you ever participated in, observed, or read about a real market either as a seller or as a buyer?

                • “The demand curve is obviously not flat because anybody that lowers the price gets all the sales.”

                  I may have been unclear. I should have said “in the competitive market”, not “when the competitor”. In a competitive market, when the largest supplier is less than 1% of total sales, it is not possible for him to produce enough to get all the sales. He sells all he can produce, at the market price (or any price below that).

                  The supply curve is never flat over a large range of prices for any seller. That would imply the ability to produce infinite quantity at a fixed price, or at least to produce more at the same average cost. Supply curves slope downward on the left side because of economies of scale, and upward on the right side because marginal cost increases with increased production, beyond the point where economy of scale is no longer of significant benefit. For an individual seller, in the short run (too short for him to increase current production very much) his supply curve goes vertical at the right side, not horizontal. (Think a farmer at harvest time, not a factory running one shift that could put on a 2nd shift.) Remember, it is quantity on the X axis, price on the Y axis. That has always seemed intuitively backward to me.

                  (I should have included in an earlier post that this is the only relationship the supply and demand curves pretend to represent, the relation of quantity to price. They do not show changes in price or quantity due to demographic changes, wars, droughts, or any other factors. As such, they are limited to a point in time, since all the other factors are assumed constant. It’s two dimensional, not n-dimensional.)

                  I was not intending to be complete. Yes, in oligopoly the suppliers will coordinate their pricing. If they can collude, they will, and they will set the price at the monopoly price and control their production accordingly. (Think OPEC, or major airlines in the US – as opposed to Southwest.) If not, then “price wars” may occur, especially if inventories are building up. Oligopolists tend to try to differentiate their product, so that they can charge a premium price, and if they can’t do that and they can’t collude among themselves, and if there are not high barriers to entry and a lack of close substitutes, then more suppliers will enter the market driving prices and profits down, toward the price that would prevail in a competitive market. This is not anything that economics has ever ignored, but it tends to be micro not macro.

                  More customers coming into the market as prices fall is the downward-sloping demand curve. Consumer electronics sales tend to move to the right along the demand curve as prices fall over time (ceteris paribus, of course). The underlying change was the change to the producers’ cost curves, driven by technology. They make more profit by selling more product at lower prices.

                  We all participate in real markets all the time. If you work for a living, or manage a business, you participate as a seller as well as a buyer. We participate in various types of markets, from competitive to monopolistic, with varying degrees of market power, in our everyday lives.

                  • Steven Greenberg

                    As I suspected, you probably meant supply curve when you said demand curve, when you were talking about a flat curve. The supply curve is obviously not flat either, as manufacturers are willing to supply product at lower prices when there are market forces that demand it. It is just that for a little while, they can get away with selling at a higher price until the market has a chance to adjust.

                    I don’t know where you learned about supply and demand, but when I learned about it, these adjustments were discussed as an explanation of why the law of supply and demand works.

                    http://www.mhhe.com/economics/samuelson17/students/Ch3_files/slide0008_image012.gif

                    Don’t the arrows on the curves and the words equilibrium imply dynamics in the situation? To get to the equilibrium you have to come from either Surplus or Shortage. Also the curves shown in this picture do not show the end regions where there is just no more physical resource available to supply, or on the other hand, no supply when the price drops below cost.

                  • Steven,

                    No, I meant a flat demand curve as viewed by a single supplier in a competitive market, which I described above.

                    Like you, when you want to sell some shares of common stock. If the bid is $100 and the ask is $100.10, you can sell all your stock for $100, or less, but you can’t sell any of it for $101, because at the time you want to sell there is nobody willing to pay more than $100, and there are people willing to sell at $100.10, enough of them to satisfy all the buyers at that price (there are none, currently). When you look at the demand for your stock, it is a flat line at $100, from 1 share up to all the shares you own. When the farmer wants to sell his corn on the CME, he can sell all his ears at the market price, and none at any price higher than that. The demand for his corn is a flat line at the market price and every quantity.

                    Your curves represent the entire market, not the view of a single small supplier in a market of many undifferentiated suppliers.

                    And yes, there are dynamics. There are time considerations, and the equilibrium price (the market-clearing price, actually; the word “equilibrium” would imply that there are no net forces at work to cause it to change, and that is generally not true) has to be sorted out by buyers and sellers. Surpluses will be sold as the price comes down “clearance sale”), shortages aren’t necessarily known before it is too late.

              • You can think of the downward-sloping demand curve as the curve of the probability of selling additional units at decreasing prices. The probability that individual people will make a certain choice, exercising their free will. So, macroeconomics has been using probabilistic logic for quite a long time.

              • golfer1john,

                I am very encouraged by your using free will and the probabilistic language to discuss demand. However, I found two problems with your comments.

                First, if you are doing it for the demand, what stops you from using free will and the probabilistic language to discuss price and supply as well? If you do that, you will find out that you end up with the exact identical framework as the paper describes! If you combine these demand, supply, and price probability distribution functions in a logically consistent way, mathematically you have to use the joint probability distribution function. The final result is that you find yourself completely liberated from the flawed laws of supply and demand and market equilibrium framework. The new framework always works and more powerful.

                Second, if you use the free will and the probabilistic language to discuss demand, then law of demand cannot be always true. If law of demand is always true, then you don’t have free will and you don’t need the probabilistic language to discuss demand. Logically, these two frameworks are just not compatible! For example, price downward momentum is a key factor for demand. That is why few people were rushing to buy when S&P 500 index was about 1/3 of the current level in March 2009! In the real world, low prices do not always increase demand. Sometimes, lower prices simply scare people into hiding. Now S&P 500 is up almost 200%, what do you see? People are rushing to buy stocks. Hey. Just look at the weekly mutual fund flows! Very strong IN FLOWS in all 2003. So much for law of demand!

                Through these discussions with you, I have found more confidence that my paper is indeed correct and will be helpful for future economists. So many thanks!!!

                • “what stops you from using free will and the probabilistic language to discuss price and supply as well?”

                  The supply curve is not probability, nor is it essentially behavior-oriented. It is a cost curve, for the individual producer, and for the market it is the sum of the cost curves of all the producers. It plots the unit cost of producing a number of units. There is no free will involved, except the free will of the producer to choose to make profits rather than take losses.

                  I would be wary of applying the same analysis to “investment” (some would say “speculative”) goods, i.e. the stock market, gold, and to some extent real estate, in which demand is governed more by expectations of future prices than by a desire to consume the product. Nobody buys additional coffeemakers when the price goes up, or even if they think the price will continue to rise for a while. They might buy a new one if it goes on sale, but if not they may hang on to the old one until it gives out completely. But if gold rises from $300 to $1000 and starts making headlines, people think that the trend will continue and they can buy now and sell later at a higher price. Similarly, if they see real estate going from $100,000 to $120,000 in 6 months, they figure they can buy now and sell in 6 months for $140,000. It works, for a while, and that encourages them to continue, and others to join in. (Interestingly, if gold rises enough to cause demand for the GLD ETF to go up, it may well also depress the demand for gold jewelry, driving consumers to alternatives.)

                  To say that speculative behavior negates the law of demand is equivalent to saying that wood failing to fall to the bottom of the lake negates the law of gravity. It is a different situation, requiring different analysis. I don’t think anyone knows the laws relating to asset bubbles, at least not enough to consistently profit from them or predict them, but clearly there are many who can successfully use the law of demand to sell coffeemakers at a profit.

                  And again, comparing the level of demand at different times is comparing a shifting demand curve, not movement along a curve that represents a point in time.

                  The law of demand is based on free will, and observations of human behavior. People are not pre-determined to buy things. They decide to buy things, and price is one of the main factors they consider. The law of demand isolates that consideration from all others, plotting price vs quantity. Other factors are not reflected in the demand curve, but could be reflected in the shift of the curve. When the weather turns bad, there is a run on bottled water and batteries. Not every day, and not because of price. Given given normal weather conditions, the probability of selling batteries depends largely on the price. That is why merchants have sales, and they continue to have sales because it works.

                  You may have understood more than I meant by saying the demand curve represents a probability function. If there are 100 potential consumers, and 50 of them are buying at the current price, and if you lower the price by X% then 5 more units are sold, you can construct at least part of a demand curve. You can say the probability that any individual consumer will buy has gone up from 50%to 55%. You don’t know which are the 5 additional buyers, and you don’t need to know. They exercised their free will. They were not forced by laws of demand, their behavior merely revealed the shape of the demand curve.

                  Knowing the shape of the curve allows you to apply equations like those used in probability and statistics. It’s not the same science as is used in analyzing a series of coin flips, but it is the same equations.

                  • Golfer1john,

                    You have made your points very clear. I hope I could have done the same.

                    I saw your posts on some investment web sites. One of my passion is also investing, economics, and finance. If you don’t mind, you are welcomed to send me email directly. You could the email address from my paper on “Fundamental Equation of Economics”. I found it has been very helpful to talk to you.

  10. I like your conclusion that “costly collapse of EMH suggests that all other economic propositions rest on even shakier foundations built on friable dogma rather than bedrock facts.”

    The fundamental reason is very simple: people have free wills.

    The greatest sin of economics is to generalize some special human behavior to the degree of immutable laws. If people have free wills, there is no universal behavior for humanity. It only makes senses when it expresses in probabilities.

    • Steven Greenberg

      Free will is one way to put the difference between physical systems and human centered systems.

      Another way to say it is that physical systems don’t read explanations of themselves and change their behavior because of what they learned.

      One consequence of this reflexive capability of human centered systems can be seen in the stock market. Frequently, people have invented winning stock market strategies that they first prove by back-testing against historical data. The valid ones tend to work for a while until the system becomes well known and popular. Then it stops working because everyone knows about it.

    • “It only makes senses when it expresses in probabilities.”

      Or averages, which amounts to the same thing.

      Even in microeconomics, free will is accounted for. Markets exist because different people value the same things differently. It does not negate the fact that each is maximizing his utility, as he perceives it. You might even say that his perception is irrational or insane, and you may be right, but that doesn’t matter. Don’t make the mistake of thinking that economists believe that utility can always be objectively quantified.

  11. Pingback: The Taylor Rule: Ignore Fraud Epidemics and Worship Markets | New Economic Perspectives

  12. But is regulation the cure? This cry for controlling markets happens every business cycle. They get their rules but power repeals them. To get to the root – and remove temptation – better to take land value out of mortgages, so speculators have nothing to speculate on. Then pay the raised revenue as dividends to citizens. You’d narrow the income gap and flatten the cycle, too. To help it happen, visit progress.org.