Tag Archives: Chicago Booth

Updates from Chicago Booth

How central bankers misjudge forward guidance
By Rose Jacobs – One of the best ways to spur an economy is to get people spending, and policy makers have a number of tools to do that. Yet growing evidence suggests a favored approach of late—forward guidance by central banks—doesn’t work. Such guidance, usually focusing on the outlook for interest rates, is meant to make clear to consumers that prices are likely to rise soon, so buying big items now would be smart.

While people may agree with the buy-now logic, they still may not react as economists and policy makers expect, according to Boston College’s Francesco D’Acunto, Karlsruhe Institute of Technology’s Daniel Hoang, and Chicago Booth’s Michael Weber. That’s because they don’t understand the signal, the researchers find.

“If you’re an economist too much stuck in your model world, this is very surprising to you,” Weber says. On the other hand, he acknowledges that not everyone can follow the logic chain that leads from a central banker predicting depressed interest rates, to lower borrowing costs, to higher inflation, to the urgency of buying now. “If you’re not too detached from reality, it’s not surprising,” Weber says.

The researchers analyzed two events in which governments or central banks signaled that prices were set to rise. One was a 2005 announcement by the German government that the country’s value-added tax (similar to the US sales tax) would increase from 16 percent to 19 percent in 2007. The second was a 2013 statement by then European Central Bank president Mario Draghi that interest rates would stay low or decline further for some time. To economists, this statement was a clear signal that price inflation would soon follow. more>

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Updates from Chicago Booth

This one ubiquitous job actually has four distinct roles
The avatars of the strategist
By Ram Shivakumar – Among the occupational titles that have become ubiquitous in the 21st century, “strategist” remains something of a mystery. What does the strategist do? What skills and mindset distinguish the strategist from others?

Is the strategist a visionary whose mandate is to look into the future and set a course of direction? A planner whose charter is to develop and implement the company’s strategic plan? An organization builder whose mission is to inspire a vibrant and energetic culture? Or is it all of the above?

Academic scholarship does not settle this question. Over the past 50 years, many competing schools of thought on strategy have emerged. The two most prominent are the positioning school and the people school. The positioning school, closely associated with ideas developed by Harvard’s Michael Porter, argues that strategy is all about distinctiveness and not operational efficiency. In this view, the acquisition of a valuable position depends on the unique combination of activities that an organization performs (or controls). The people school, closely associated with the ideas of Stanford’s Jeffrey Pfeffer, posits that the principal difference between high-performance organizations and others lies in how each group manages its most important resource—people. In this view, high-performance organizations foster a culture that reward teamwork, integrity, and commitment.

Because these two schools differ in their doctrines (assumptions and beliefs) and principles (ideas and insights), each envisions a distinct role for the strategist. more>

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How can banks create safe money? Balance competition
By Áine Doris – A conundrum underscores the banking system: banks issue liquid deposits but at the same time supply loans to finance illiquid projects, such as startups. In doing this, they expose themselves to liquidity risk—the kind that can lead to bank runs. It’s a precarious way to build a banking system.

Chicago Booth PhD candidate Douglas Xu tackles this liquidity paradox in a model that identifies two market failures or “inefficiencies” that regulators and policy makers need to keep in balance to reduce systematic risks.

Banks have long occupied a critical role in the creation of money. In today’s global economy, governments create only 3 percent of the money exchanged for goods, products, and services: the paper money and coins issued by central banks or monetary authorities whose trustworthiness or integrity underscore their value. Banks create the rest of the world’s cash—a staggering 97 percent.

From early record-keeping tokens to today’s deposit taking and loan making, banks have long been in the business of issuing money-like assets in one form or another. These assets function as credible payment media and thereby facilitate the kinds of activities and transactions that drive economic fluidity and growth.

But these assets bring inherent risk. Xu created a framework that captures the way that banks create money in the economy and integrates two key concepts: banks’ intrinsic vulnerability to illiquidity, and the so-called money-multiplier effect—the chain of transactions created when a bank makes a loan that generates a concomitant deposit elsewhere in the system. Put simply, loans generate a fresh supply of deposits. more>

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Looking for a promotion? Control your temper
By Meena Thiruvengadam – Expressing anger may be a tool for attaining prestige or status, in some circles. Observers associate anger with dominance, strength, competence, and smarts, according to research published in 2001.

But a study by Chicago Booth’s Celia Gaertig and Emma Levine, New York University’s Alixandra Barasch, and University of Pennsylvania’s Maurice Schweitzer suggests there’s a limit to the respect anger commands. Too much anger, particularly in relation to the offense committed, can backfire, especially on people climbing corporate or social ladders, the researchers argue. Exhibiting too much anger can harm the perceptions of competence and warmth, traits that tend to drive hiring and leadership decisions. The more intense the anger, the more likely others may suspect self-serving or harmfully intentioned motives.

The researchers conducted seven studies, some involving fake beverage tasting. In one of the studies, they asked groups of six participants to rate the best-tasting beverage presented in a lab. Both options were actually Coca-Cola, and the researchers didn’t tabulate participants’ responses, as the study was essentially just a decoy. Each group secretly included two actors, one of whom spilled soda on the other’s cell phone, eliciting an angry reaction that was either moderate or more intense. Then the participants had to pick a leader for a group activity, and in doing so rated each other’s (including the angry actor’s) competence and leadership potential.

Actors who reacted with intense anger rather than annoyance were perceived as less competent and were less likely to be selected for leadership roles. The responses held for participants who watched a video of the lab charade rather than participating in it. “Expressing high-intensity anger can be harmful for how an individual is perceived in social settings,” the researchers write. more>

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Can regulation rein in algorithmic bias?
By Sendhil Mullainathan – Last year, you published a paper documenting how an algorithm used by health-care organizations generated racially biased results. What takeaways did that offer in terms of how algorithmic bias differs from human bias?

That paper might be, by some measures, among the strangest papers I’ve ever worked on. It’s a reminder of the sheer scale that algorithms can reach.

Exact numbers are hard to get, but about 80 million Americans are evaluated through this algorithm. And it’s not for some inconsequential thing: it is an algorithm used by many health-care systems to decide which patients should get put into what are called care-management programs. Care-management programs are for people who are going to be at the hospital a lot. If you have many conditions, you’re going to be in the system frequently, so you shouldn’t have to go through the normal front door, and maybe you should have a concierge who works just with you. You get additional resources to manage this complex care.

It costs a lot of money to put somebody in a care-management program. You really want to target these programs. So the question is, who should be in them?

Over the past five years, there have been algorithms developed using health records of people to figure out who is at highest risk of using health care a lot. These algorithms produce a risk score, and my coresearchers and I wanted to know if there was any racial bias in these scores.

The way we looked for it was to take two people given the same score by the algorithm—one white and one Black. Then we looked at those two people and asked whether, on average, the white person had the same level of sickness as the Black person. What we found is that he or she didn’t, that when the algorithm gives two people the same score, the white person tends to be much healthier than the Black person. And I mean much healthier, extremely so. If you said, “How many white people would I have to remove from the program, and how many Black people would I have to put in, until their sickness levels were roughly equalized?” you would have to double the number of Black patients. It is an enormous gap.

I say it’s one of the craziest projects I’ve worked on in part because of the sheer scale of this thing. But there are a lot of social injustices that happen at a large scale. What made it really weird was when we said, “Let’s figure out what’s causing it.” In the literature on algorithmic bias, everyone acts like algorithms are people, like they’re biased [in the sense that people are]. It’s just a little piece of code. What went wrong in the code?

What we found is something that we’re finding again and again in all of our A.I. work, that every time you see that an algorithm has done something really bad, there’s no engineering error. That’s very, very different than the traditional bugs in code that you’re used to: when your computer crashes, some engineering bug has shown up. I’ve never seen an engineering bug in A.I. The bug is in what people asked the algorithm to do. They just made a mistake in how they asked the question. more>

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Updates from Chicago Booth

Ever closer to an optimally cost-efficient assembly-line operation
By Chuck Burke and Vanessa Sumo – Companies such as Dell and BMW use an assemble-to-order production strategy that keeps common components on the factory floor, ready for final assembly into the type of personal computer or vehicle that a customer orders. This is great for companies looking to satisfy a large volume of demand but that don’t want to build whole units in advance, to avoid any unsold products.

However, the difficulty of estimating how much of each component to hold in stock and how to allocate components to each product can keep companies from maximizing ATO’s benefits in practice.

A cross between two alternate production strategies

Make-to-stock strategy: MTS managers forecast consumer demand and match anticipated orders with an inventory of fully assembled products.

Make-to-order strategy: On the other hand, MTO systems wait for a customer’s order to arrive before starting production. Because this can include procuring parts and assembling components, MTO often results in a longer lead time.

Assemble-to-order strategy: An ATO strategy aims to combine the best of both systems—its flexibility lets companies fulfill large orders relatively quickly with minimal unsold inventory, yet still allows customers to partially customize orders. Here is how it works:

Managers must decide the quantity of components to order even before they can ascertain customer demand for their products.

When customers’ orders arrive, managers must then choose how to allocate the supply of components to each product for assembly. more>

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Updates from Chicago Booth

Could anything unite the United States?
Cultural and political divisions have persisted for decades. Now there’s a growing gap in how Americans see each other.
By Rose Jacobs – As the Democratic Party battles over whether a moderate or liberal presidential candidate stands the better chance of winning the White House in November 2020, many Americans are asking a similar but broader question: Has the country ever been so divided?

Academics, for their part, are attempting to measure what often feel like widening gaps. In 2017, Stanford’s Matthew Gentzkow looked at a series of Pew Research Center surveys of Americans’ views on policies ranging from government regulation to welfare, immigration, and the environment, and noted that fewer individuals in 2014 than 10 years earlier held positions that put them across the political divide from their own, self-identified political party.

Nor do divides appear confined to politics and policy. Chicago Booth’s Marianne Bertrand and Emir Kamenica examined three national surveys that probe Americans’ consumption habits, leisure time, and social attitudes. They find that different groups of Americans—rich and poor, black and white, men and women, politically liberal and conservative, college educated and not—tend to eat different food, watch different television programs, pursue different hobbies, and adopt different social attitudes. The algorithms the researchers developed for their study were able to predict people’s income bracket with nearly 90 percent accuracy on the basis of the brands of products and services they bought; they could do the same for gender by looking at what TV shows and films people watched and what magazines they read; and they could predict race with 75–85 percent accuracy using self-reported stances on topics such as marriage, law enforcement, and government spending.

Yes, then, the nation appears to be divided.

Bertrand and Kamenica point out that cultural gaps in the categories that they studied, between rich and poor or black and white, for instance, are worrisome in part because they might dampen social and economic mobility. The real-world effects of growing partisanship are less obvious, but research is beginning to probe how a politically divided populace plays out in areas ranging from corporate finance to macroeconomics to medicine and law.

The researchers looked at the months surrounding President Trump’s election in 2016, and find that analysts registered as Democrats were more likely to issue downgrades to the companies they covered after November 8 than were Republican analysts. This effect was greater with analysts who voted more frequently. This result is in line with their wider analysis of political affiliation and presidential elections going back 18 years, which suggests that analysts whose politics do not align with the sitting president’s are more likely to downgrade companies’ debt than analysts who share a political party with the president. more>

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Updates from Chicago Booth

US small businesses have little cushion against prolonged disruptions
By Michael Maiello – Even in a growing economy, most small businesses in the United States lack sufficient reserve capital to endure a prolonged business interruption, so a natural disaster, pandemic, or any condition that interrupts normal operations can quickly lead to job cuts and business failures. If the government wants to keep small businesses afloat, its support must be enacted quickly and generously and be easy to access, according to a survey of 5,800 small businesses conducted early during the COVID-19 outbreak in the US.

University of Illinois’s Alexander W. Bartik, Chicago Booth’s Marianne Bertrand, and Harvard’s Zoë Cullen, Edward Glaeser, Michael Luca, and Christopher Stanton have been studying small-business behaviors, decision-making, and attitudes. Their research provides a detailed look at the financial health of small businesses heading into COVID-19 and underscores the need for fast and easy-to-access government interventions when businesses are interrupted.

The researchers conducted their survey as the Coronavirus Aid, Relief, and Economic Security (CARES) Act was signed into law in late March and implemented in April. By then, small-business owners, who employ 48 percent of American workers, had already cut their workforces massively, a sign of their precarious finances even ahead of the outbreak. Three quarters of survey respondents, who are all members of Alignable, a small-business network, reported they had cash on hand to cover expenses for no more than two months.

Survey respondents who believed the pandemic would last longer were more pessimistic about their companies’ chances of surviving. The researchers estimated that business closures could lead to almost 33 million job losses if the pandemic were to last four months, 35 million if it were to extend six months. more>

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Updates from Chicago Booth

The notorious failure contains valuable lessons for investors
By James E. Schrager – Amid the many stories of business turmoil this spring has produced, the legal drama surrounding WeWork and its lead investor, SoftBank Group, stands out for its roots not in disease and social distancing, but old-fashioned bad decision-making.

In early April, WeWork announced it had filed a lawsuit against SoftBank for backing out of a tender offer to purchase about $3 billion of WeWork stock, an offer made as part of a bailout package from SoftBank after WeWork’s planned initial public offering fell through last fall. About a month later, WeWork cofounder and former CEO Adam Neumann, who could have sold up to nearly $1 billion of stock as part of the tender offer, filed his own suit against SoftBank.

To the uninitiated, the saga of WeWork’s journey toward an IPO—which was abandoned after a precipitous decline in the company’s valuation, from $47 billion to $8 billion—must have raised a number of questions.

Is it typical for failed founders to demand nearly a billion dollars for their efforts, as Neumann has done, no matter how badly things turn out?

Is an entrepreneur’s compensation package directly and positively proportional to the amount of money he loses for investors?

Are startup funds so abundant, borrowing costs so low, and big risks so encouraged that giant paydays are the rule even for losing CEOs? more>

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Updates from Chicago Booth

Think you’re not racist?
Research uncovers our secret prejudices, and ways to overcome them
By Alice G. Walton – It has been 50 years since the Civil Rights Act outlawed discrimination based on race, color, religion, sex, or national origin. The landmark legislation marked the end of the era of legalized racism. Now some affirmative action programs, created to encourage and promote diversity and the presence of underrepresented minorities, are being rolled back.

However, while overt racism may be on the wane in the US, research suggests it remains just below the surface. Very few people would admit to being biased, yet there’s strong evidence that biases continue, often under the level of our expression and of our awareness.

Ten years ago Marianne Betrand, Chris P. Dialynas Distinguished Service Professor of Economics at Chicago Booth, and Sendhil Mullainathan, then at MIT, published a famous study entitled, “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,” in which 5,000 fictitious resumes were sent in response to 1,300 job postings in Chicago and Boston. The resumes were either “high quality” or “low quality,” varying in the typical things that set resumes apart—job and internship experiences, academic institutions, and languages spoken. Then, the team randomly assigned either a “white-sounding” name, such as Emily Walsh, or an “African American–sounding” name, such as Lakisha Washington, to each resume.

The results were unambiguous. White-sounding applicants got 50% more callbacks than African American–sounding candidates. This didn’t seem to be a matter of how common the names were or the apparent social status of the applicant, but simply a function of what the names suggested about the race of the fictional applicants.

Even more disturbingly, white applicants with higher-quality resumes had a strong advantage over their African American peers. The authors suggest that this makes it less enticing for African Americans to develop high-quality resumes, which makes hiring discrimination part of a destructive cycle. more> [VIDEO]

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