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Economy

Some Fundamental Differences between Ludwig von Mises and Nassim Taleb

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In my previous post we saw some of the areas where Taleb’s writing is strikingly Misesian: the hidden value and emergent properties of spontaneous orders, the insightfully realistic view of uncertainty and risk-taking, and the aggressive despising of econometrics and other unproper uses of math in the domain of economics.

So far the similarities. As for the differences, most of them are quite profound.

To begin with, Mises’s work, as was more customary during his time, spanned many more domains than Taleb’s. Not only an economist or a political scientist, Mises wrote intelligently on philosophy, epistemology, and history. Taleb, primarily a mathematician with a huge appetite for classics and poetry, restricts his writing to topics surrounding his One Big Idea: the poorly-understood subject of uncertainty and the mistaken models, practices and opinions that flow from it. The NYT best-selling book that made Taleb a household name, The Black Swan, explores the impact of under-appreciated tail risks.

In Fooled by Randomness he describes how during his years as a trader his risk-approach made him an object of derision among his more high-returning colleagues — until the various financial crises in the 1990s (Peso crisis of 1994, Asian financial crisis in 1997, the Russian Ruble conundrum in 1998) wiped them out (“they blew up”, in Taleb’s words) and laid the foundation for his financial and intellectual wealth .

While neither is a stranger to lots of writing (Mises’s most famous books — Theory of Money and Credit, Human Action, Theory and History, and Socialism — amount to around 2,500 pages, comparable to Taleb’s Incerto series), Mises’s writing is wide and comprehensive, Taleb’s hyper-focused with lots of illustrations derived from ancient texts and trading experience alike. Using the Oxford philosopher Isaiah Berlin’s playful analogy, we might say that Mises is a Fox and Taleb a hedgehog.

Very similar to his objection to econometrics, Mises objects to probability theory in social sciences because economic or political actions are not homogenous events. Class probability, as elaborated by Mises’s brother Richard von Mises, is essentially meaningless; while knowing something about the class of events (say, rolling a die) is interesting, it tells us nothing about the individual event. In discussing this, Rothbard even maintained that “the Mises view demonstrates that all use of probability theory in social science is illegitimate.”

Applying probabilities to the science of human action is to Mises a category error. To Taleb, it’s a rudimentary and epistemic sample-selection error; on the basis on past observations, we simply cannot — unlike Wall Street commentators or your average econometrician — reliably draw inference on the set from which the observations are drawn. Mises rejects probability theory in the social sciences; Taleb rejects the use of the central limit theorem that underlies standard Gaussian distributions.

There’s a further disagreement between Taleb and Mises when it comes to epistemology, particularly Popperian falsificationism and the use of psychology in economics. Mises doesn’t believe that psychology can provide insights about economics, whereas Taleb is squarely on the behavioral train. In Theory and History Mises writes: “Most of [the schools of experimental psychology] are even of no use to praxeology, economics, and all the branches of history.” (p. 264)

And a few pages later he writes: “All that thymology can tell us is that in the past definite men or groups of men were valuing and acting in a definite way. Whether they will in the future value and act in the same way remains uncertain.” (p. 273)

In contrast, Taleb’s trading strategies relied on people underestimating and therefore irrationally underpricing tail-risk events, events that — when they ultimately occurred — allowed him to profit immensely. The very same biases that behavioral economists love to advance underlies Taleb’s explanations for our improper use of statistics in life and markets alike. In chapter 3 of Fooled by Randomness Taleb tells us that his two most influential role models were Einstein and Keynes — but Keynes “the probabilist,” not the amateur macro economist. Taleb was attracted and informed by the “irrational” behavior and folly of man. His idolizing Charles Mackay’s poorly-researched 1841 book Extraordinary Popular Delusions and the Madness of Crowds gets at the very difference between Taleb and Mises: Mises frequently thinks very highly of the layman in contrast to the Ivory Tower (read: socialist) intellectual; Taleb comes across as denouncing intellectual and layman alike — the educated man simply has more ways of fooling himself than the layperson, but behavioral fools they all are!

As for methodology, several things connect Karl Popper to the Austrian school. First, he was a student of Mises and well-versed in the economic ideas thriving in early 20th century Vienna. Second, Hayek’s abandoning praxeology for Popperian falsificationism tied the two doctrines closer to each other. On the other hand, Mises strongly objected to Popper, maintaining that there were meaningful synthetic a priori truths about the world that we could derive from first principles. Taleb, on the contrary, is as pure a Popperian as they come. In chapter 7 of Fooled by Randomness he admits to an “extreme and obsessive Popperianism” that he only acquired upon religiously reading Popper later in his career.

While Taleb refuses to be high-jacked by this or that heterodox economic school of thought, maintaining that he’s a statistically-oriented orthodox economist, I don’t think he understands what people mean by “orthodoxy”; Taleb literally specializes in blowing up most orthodox economic thinking. He writes:

I want to take the charlatanism out of economics and there is a way to do it: examine layers of stochasticity. Detect fragility, and remove offending models. […] I just do not like unreliable models that use “some” math like regression and miss a layer of stochasticity, and get wrong results, and I hate sloppy mechanistic reliance on bad statistical methods. I do not like models that fragilize. I do not like models that work on someone’s computer but not in reality. This is standard economics. I showed in 1.7 that we cannot use standard deviations and it is not a matter of taste. Being an economist does not mean being a turkey. Yet all economists persist in these bogus methods.

He does have a point that criticizing mainstream does not automatically make him a detractor or follower of some fringe theory. Indeed, he doesn’t subscribe to any idea or theory, setting him even further apart from Mises. At one point in Antifragile, Taleb takes economists to task for being too tied to their theories. Discarding all of them, he writes “a theory is a very dangerous thing to have. And of course one can rigorously do science without it.” (2014:116)

The Misesian would not approve. Theory, Mises teaches us, is how we make sense of reality — how we know what to look for, how we separate signals from noise and how we understand the causal mechanisms producing the outcomes we observe. Theory is what makes economics a science — all else is sociology or political science or economic history.

In sum, many things unite Taleb and a Misesian-grounded economic and epistemological worldview: knowledge in emerging spontaneous orders, Antifragile systems, objection to misused statistics in the domain of economics. The student of Austrian economics can easily find topics of agreement with this strange public intellectual.

There are also very important differences: The Talebian rejection of statistics is based on sample selections, not category errors as with  Mises; Taleb happily rejects theory, which is clearly anathema to Mises; and Taleb is a Popperian, whereas Mises’s moral and scientific foundations more closely align with Kant.

Read Taleb with caution, but read him you should.



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Economy

Dorothy Theresa Sawchak Mankiw

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Above is a picture of my mother as a young woman. I would like to tell you about her.

My mother was born on July 18, 1927, the second child of Nicholas and Catherine Sawchak.

Nicholas and Catherine were immigrants from Ukraine. They came to the United States as teenagers, arriving separately, neither with more than a fourth-grade education. Catherine was from a farming area in western Ukraine. She left because her family wanted her to marry an older man rather than her younger boyfriend, who had been conscripted into the army. Her first job here was as a maid. Nicholas was from Kiev, where he had been trained to be a furrier. In the United States, he worked as a potter, making sinks and toilettes. When Nicholas and Catherine came to the United States, they thought they might return home to Ukraine eventually. But World War I and the Russian Revolution intervened, causing a change of plans. Catherine’s boyfriend died in the war. Nicholas and Catherine met each other, married, and settled in a small row house in Trenton, New Jersey, where they lived the rest of their lives.

Catherine and Nicholas had two children, my uncle Walter and my mother Dorothy. When my mother was born, her parents chose to name her “Dorothy Theresa Sawchak.” But because Catherine spoke with a heavy accent, the clerk preparing the birth certificate did not understand her. So officially, my mother’s middle name was “Tessie” rather than “Theresa.” She never bothered to change it.

Nicholas and Catherine were hardworking and frugal. They saved enough to send Walter to college and medical school. He served as a physician in the army during the Korean war. Once I asked him if he worked at a MASH unit, like in the TV show. He said no, he worked closer to the front. He patched up the wounded soldiers the best he could and then sent them to a MASH unit to recover and receive more treatment. After the war, he became a pathologist in a Trenton-area hospital. He married and had two daughters, my cousins.

My mother attended Trenton High School (the same high school, I learned years later, attended by the economist Robert Solow at about the same time). She danced ballet. She water-skied on the Delaware River. She loved to read and go to the movies.

In part because of limited resources and in part because of the gender bias of the time, my mother was not given the chance to go to college. Years later, her parents would say that not giving her that opportunity was one of their great regrets. Instead, my mother learned to be a hairdresser. She was also pressured to marry the son of some family friends.

The marriage did not work. With my mother pregnant, her new husband started “running around,” my mother’s euphemism for infidelity. They divorced, and she kicked him out of her life. But the marriage did leave her with one blessing—my sister Peg.

My mother continued life as a single mother. Some years later, she met my father, also named Nicholas, through social functions run by local Ukrainian churches. They both loved to dance. He wanted to marry her, but having been burned once, she was reluctant at first. Only when she realized that he had become her best friend did she finally accept.

In 1958, nine months after I was born, Mom, Dad, Peg, and I left Trenton for a newly built split-level house in Cranford, New Jersey. My father was working for Western Electric, an arm of AT&T, first as a draftsman and then as an electrical engineer. He worked there until his retirement. One of his specialties was battery design. When I was growing up, I thought it sounded incredibly boring. Now I realize how important it is.

My mother then stopped working as a hairdresser to become a full-time mom. But she kept all the hairdresser equipment from her shop—chair, mirrors, scissors, razors, and so on—in our basement. She would cut the hair of her friends on a part-time basis. When I was a small boy, she cut my hair as well.

I attended the Brookside School, the public grade school which was a short walk from our house. When I was in the second or third grade, my mother was called in to see the teacher. The class had been given some standardized aptitude test. “Greg did well,” the teacher said. “We were very surprised.”

At that moment, my mother decided the school was not working out for me. I was talkative and inquisitive at home but shy and lackluster at school. I needed a change.

She started looking around for the best school she could find for me. She decided it was The Pingry School, an independent day school about a dozen miles from our house. She had me apply, and I was accepted.

The question then became, how to pay for it? Pingry was expensive, and we did not have a lot of extra money. My mother decided that she needed to return to work.

She started looking for a job, and an extraordinary opportunity presented itself. Union County, where we lived, was opening a public vocational school, and they were looking for teachers. She applied to be the cosmetology teacher and was hired.

There was, however, a glitch. The teachers, even though teaching trades like hairdressing, needed teacher certification. That required a certain number of college courses, and my mother had not taken any. So she got a temporary reprieve from the requirement. While teaching at the vocational school during the day, she started taking college courses at night to earn her certification, all while raising two children.

My mother taught at the vocational school until her retirement. During that time, she also co-authored a couple of books, called Beauty Culture I and II, which were teacher’s guides. From the summary of the first volume: “The syllabus is divided into six sections and includes the following areas of instruction: shop, school, and the cosmetologist; sterilization practices in the beauty salon; scalp and hair applications and shampooing; hair styling; manicuring; and hairpressing and iron curling.” I suppose one might view this project as a harbinger of my career as a textbook author.

When my parents both retired, they were still the best of friends. They traveled together, exploring the world in ways that were impossible when they were younger and poorer. During my third year as an economics professor, I was visiting the LSE for about a month. I encouraged my parents to come over to London for a week or so. They had a grand time. I believe it was the first time they had ever visited Europe. When I was growing up, vacations were usually at the Jersey shore.

My father died a few years later. My mother spent the next three decades living alone. She was then living full-time at the Jersey shore in Brant Beach on Long Beach Island. The house was close to the ocean and large enough to encourage her growing family to come for extended visits. Two children, five grandchildren, four great-grandchildren. The more, the merrier. Nothing made her happier than being surrounded by family.

My mother loved to cook, especially the Ukrainian dishes she learned in her childhood. Holubtsi (stuffed cabbage) was a specialty. Another was kapusta (cabbage) soup. One time, the local newspaper offered to publish her kapusta soup recipe. They did so, but with an error. Every seasoning that was supposed to be measured in teaspoons was printed as tablespoons. The paper later ran a correction but probably to no avail. I am not sure if anyone ever tried the misprinted recipe and, if so, to what end.

During her free time in her later years, my mother read extensively, played FreeCell on her computer, and watched TV. A few years ago, when she was about 90 years old, I was visiting her, and I happened to mention the show “Breaking Bad.” She had not heard of it. She suggested we watch the first episode. And then another. And another. After I left, she binge-watched all five seasons.

As she aged, living alone became harder. When she had trouble going up and down the stairs, an elevator was added to her house. But slowly her balance faltered, and she fell several times. She started having small strokes, and then a more significant one. She moved into a nursing home. Whenever I visited, I brought her new books to read. Her love of reading never diminished.

This is, I am afraid, where the story ends. Last week, Dorothy Theresa Sawchak Mankiw tested positive for Covid-19. Yesterday, she died. I will miss her.



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Economy

The GDP Collapse: It Is What It Is

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Jim discussed elements of the 2020Q2 advance release on Thursday. Here, I amplify some aspects that he mentioned.

Confirmation: A Catastrophe in the Making

First, the Trump recession is truly catastrophic in scale; the pace of GDP decline is much greater than that in 2008. This is shown in Figure 1.

Figure 1: GDP in logs, normalized to 0 at 2019Q4 (NBER peak) (blue), and GDP normalized to 2008Q2 (red). NBER defined recession shaded gray, assuming trough at 2020Q2. Source: BEA, 2020Q2 advance release, NBER, author’s calculations.

 

A “No Confidence” Vote in Administration Policy and Investment

Second, investment has crashed — for both structures and equipment investment. That’significant insofar as capital investment is forward looking.

Figure 2: Fixed investment in structures (blue, left log scale), and in equipment (red, right log scale), in billions Chained 2012$, SAAR.  NBER defined recession shaded gray, assuming trough at 2020Q2. Source: BEA, 2020Q2 advance release, NBER, author’s calculations.

This decline is even more rapid than in 2008Q4; 31.5% now vs. 24% then.

Figure 3: Nonresidential fixed investment in logs, normalized to 0 in 2019Q4 (blue), and normalized to 0 in 2008Q2 (red).  NBER defined recession shaded gray, assuming trough at 2020Q2. Source: BEA, 2020Q2 advance release, NBER, author’s calculations.

Certainly, some of the crash is due to the crash in aggregate demand — as in the 2007 recession — but some is due to uncertainty, including policy uncertainty. Policy uncertainty levels currently dwarf those of the Great Recession.

Figure 4: Nonresidential fixed investment in billions Chained 2012$ SAAR (blue, left log scale), Economic Policy Uncertainty index (tan, right scale).  NBER defined recession shaded gray, assuming trough at 2020Q2. Source: BEA, 2020Q2 advance release, NBER, policyuncertainty.com via FRED, and author’s calculations.

 

No Recovery Without Recovery in Services Demand

Third, this is a different kind of recession, in many ways, but importantly in the sectoral origin. As Jim Hamilton noted, the decline in services consumption was 43.5% on an annualized basis, while durable goods consumption was relatively flat.

Figure 5: Services consumption (blue, left log scale), and durable goods consumption (red, right log scale), all in billions Chained 2012$ SAAR. NBER defined recession shaded gray, assuming trough at 2020Q2. Source: BEA, 2020Q2 advance release, NBER, and author’s calculations.

Of the 9.8 percentage point decline in GDP (not annualized), 5.9 percentage points were accounted for (in a mechanical sense) by services consumption decline. Jim provides a breakdown of the services consumption decline in his post.

Services consumption will not fully recover until such time as the Covid-19 infection rates are at manageable levels that do not deter such consumption activities. The Administration’s current policy stance is unlikely to encourage that development; one could argue that it — in toto — is impeding that outcome.

 

State and Local Government Spending Collapses

Fourth, the biggest threat to the economy may be avoidable. One of the lessons of the Great Recession is that constraints on state and local government spending — exacerbated by ill-advised state income tax cuts — was one of the reasons for the torpid pace of recovery. So far, we have not replicated completely that experience, but with Republican opposition to further Federal transfers to the state, we are in danger of repeating that error.

Figure 6: State and local government spending, billions Chained 2012$ SAAR (blue, left log scale), and state and local employment, 000’s, s.a. (teal, right log scale). Source: BEA 2020Q2 advance release, BLS employment situation June release.

This is why it is critical, as many economists have argued, for the next recovery package to include substantial aid to the states and localities.

 



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Economy

The Big Tech Hearings Could Be a Model for Corporate Accountability

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The American Prospect

See article on original site

In 2018, Democrats ran and won on a platform to hold President Trump and his cronies accountable. Many observers expected to be treated to a full schedule of oversight programming in the succeeding Congress, with a nearly endless stream of smug incompetents being caught in their lies and obfuscations. Some even dared to hope that the oversight fervor might spill over to another breed of smug incompetents: corporate CEOs. But, alas, the promised enthusiasm for oversight never seemed to materialize, let alone spread to new targets. (As usual, House Financial Services Committee chairwoman Maxine Waters, who confronted big bank CEOs within months of assuming control of her committee, stands out as a rare exception).

This general dearth of accountability made the House Judiciary Antitrust Subcommittee’s hearings last week with Big Tech CEOs all the more refreshing. Through incisive questioning, lawmakers were able to coax out consequential admissions of wrongdoing and bring to public attention the myriad harms these companies have perpetrated and then worked hard to obscure. Perhaps most critically, the information they uncovered and put into the public record lays a solid foundation for future legislative and executive action.

Arguably just as important as the policy substance, however, is the fact that the hearings were engaging and frankly satisfying to watch. As they have grown more powerful, the Big Four tech firms have slipped further and further from the grip of democratic accountability. Like private governments, they have set rules that dictate the terms of the livelihoods, social engagements, and media consumption of billions of people around the globe. But as much as they like to pretend to be sovereigns, Big Tech companies are ultimately subject to the rules and regulations our government democratically (at least in theory) sets forth. It’s good to see them reminded of that fact periodically.

As inspiring as the hearings were, however, they were also frustrating, as they begged the question: Why stop with Big Tech? Although Silicon Valley giants may be the most widely-recognized examples of corporate power run amok, they are far from the only ones. In other words, last Wednesday’s success can and should be widely replicated.

The possibilities are endless, and potentially overwhelming. Given the current crisis, committees would be well-advised to start by challenging the corporate giants who have made the pandemic worse.

As they have grown more powerful, the Big Four tech firms have slipped further and further from the grip of democratic accountability.

That includes the private equity firms whose mismanagement of nursing home conglomerates left them particularly vulnerable to COVID-19 outbreaks. In their heartless pursuit of profits, private equity firms loaded the nursing homes under their control with unsustainable debt, forcing them to cut staff, cut pay, and cut corners. Even before the pandemic, researchers documented how this led to worse outcomes and higher fatalities for patients in private equity-backed homes. And when COVID-19 hit, these facilities were particularly ill-prepared to respond.

The House Ways and Means Committee should make the heads of these private equity firms—behemoths like Carlyle Group, Blackstone, and Warburg Pincus—answer for their actions. With jurisdiction over the Centers for Medicare and Medicaid Services (CMS), which sets standards of care for nursing facilities, Ways and Means is well-positioned to not only get answers, but ensure that those answers lead to action.

Many of these same private equity titans are long overdue for an appearance before the Energy and Commerce Committee as well. When they weren’t snapping up nursing home chains, private equity firms were quietly constructing an empire of hospital chains. Just as with long-term care facilities, the aggressive pursuit of profit and mounds of debt left hospitals with little cushion to absorb unexpected blows. Sure enough, when the pandemic put lucrative elective surgeries on hold, some private equity-backed hospitals were quick to crumble. At least one leveraged its collapse into a bailout, holding healthcare amid a pandemic hostage in exchange for relief.

Given these and other bad outcomes, it’s time that Energy and Commerce put private equity CEOs under the microscope and consider the implications for the agencies under its jurisdiction like the Federal Trade Commission and the Department of Health and Human Services.

Meanwhile, the Education and Labor committee would do well to put another set of corporate villains—meatpacking companies—in the hot seat. Meatpacking plants quickly became coronavirus hotspots in the U.S. The experience in other countries shows that this was not just an inevitable function of poor working conditions, but a result of distinct choices from meatpacking companies and policymakers. Rather than working to protect their employees, meatpackers turned their attention to warding off health officials and regulation. That choice has had fatal consequences and they should be asked to account for it. A close examination of the breakdowns in the enforcement of occupational safety standards and the processes by which regulators are supposed to respond in an emergency, will also be a prerequisite to getting the response better next time.

Moreover, meatpackers appear to have claimed shortages in product from their plants as a pretense to charge groceries more for beef and pork, which resulted in higher prices for consumers. Yet at the same time, these companies were shipping record amounts of meat abroad, suggesting that they were creating the shortages themselves, and pocketing the profits. The Education and Labor Committee could join Sens. Cory Booker (D-NJ) and Elizabeth Warren (D-MA) in exploring that as well.

Furthermore, to the extent that all of these industries are highly concentrated, the House Antitrust Subcommittee itself could haul in these corporate leaders to ask them about their businesses. Big Tech isn’t the only industry requiring a second look through an antitrust lens.

As the success of last week’s hearing makes clear, House Democrats’ choice to largely spurn corporate oversight has been a big missed opportunity. Confrontations with the country’s ever more powerful corporate giants not only make for good policy but also good politics. If House Democrats are serious about either, they will fill the coming months with such clashes.

The post The Big Tech Hearings Could Be a Model for Corporate Accountability appeared first on Center for Economic and Policy Research.



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