Tag Archives: Chicago Booth

Updates from Chicago Booth

A.I. is only human
By Jeff Cockrell – If you applied for a mortgage, would you be comfortable with a computer using a collection of data about you to assess how likely you are to default on the loan?

If you applied for a job, would you be comfortable with the company’s human-resources department running your information through software that will determine how likely it is that you will, say, steal from the company, or leave the job within two years?

If you were arrested for a crime, would you be comfortable with the court plugging your personal data into an algorithm-based tool, which will then advise your judge on whether you should await trial in jail or at home? If you were convicted, would you be comfortable with the same tool weighing in on your sentencing?

Much of the hand-wringing about advances in artificial intelligence has been concerned with AI’s effects on the labor market. “AI will gradually invade almost all employment sectors, requiring a shift away from human labor that computers are able to take over,” reads a report of the 2015 study panel of Stanford’s One Hundred Year Study on Artificial Intelligence. But whether AI ultimately creates massive unemployment or inspires new, as-yet-unknown professional fields, its perils and promises extend beyond the job market. By replacing human decision-making with automated processes, we can make businesses and public institutions more effective and efficient—or further entrench systemic biases, institutionalize discrimination, and exacerbate inequalities.

It’s an axiom of computing that results are dependent on inputs: garbage in, garbage out.

What if companies’ machine-learning projects come up with analyses that, while logical and algorithmically based, are premised on faulty assumptions or mismeasured data?

What if these analyses lead to bad or ethically questionable decisions—either among business leaders or among policy makers and public authorities? more>

Related>

Updates from Chicago Booth

Financial contagion spreads through supply chains
By Michael Maiello – As big financial institutions such as Lehman Brothers fell into distress in 2008, a credit contagion spread through the financial industry, creating a credit drought for the economy as lenders retrenched and hoarded capital.

It has been less clear how credit contagion can spread through other industries, but research by George Washington’s Şenay Ağca, Georgetown’s Volodymyr Babich, Chicago Booth’s John R. Birge, and City University of Hong Kong’s Jing Wu suggests that credit shocks follow the supply chains of distressed companies.

Ağca, Babich, Birge, and Wu examined daily changes in credit default swap (CDS) spreads for all contracts with a five-year maturity between 2003 and 2014. A CDS is a derivative contract guaranteeing the owner a payout in the event that the borrower defaults. The contract’s price is known as the spread, which is the cost to insure against the default of $100 of the issuer’s debt. A widening spread signals that the market believes the issuer is more likely to default. Because the CDS market is deep and liquid, with information priced rapidly into the spread, the researchers argue that it is a better indicator of default expectations than laggard credit ratings or notes from bond analysts.

Take Ford Motor Company’s November 2008 earnings report, which highlighted massive losses, looming layoffs, and drastic cuts in capital spending. The CDS spreads linked to the company’s debt quickly widened, as one might expect. CDS spreads of American Axle & Manufacturing, a major Ford supplier, did the same, the researchers find. It makes sense that if Ford was slashing spending, its suppliers would have been suffering, they note.

But by contrast, CDS spreads were unchanged for companies with no relationship to either Ford or American Axle, such as semiconductor manufacturer Advanced Micro Devices. This suggests the mechanism by which contagion spreads is based on quantifiable business relationships, the researchers find. more>

Related>

Updates from Chicago Booth

How to react to a colleague’s microaggression
Should you intervene when one coworker is being insensitive toward another?
By Jane L. Risen and George Wu – The fourth installment of our quarterly Business Practice feature invites you to imagine witnessing a slight in a group meeting.

Greg’s request that Becky take notes is commonly termed a microaggression, described by Columbia’s Derald Wing Sue and his coresearchers as “brief and commonplace daily verbal, behavioral, or environmental indignities, whether intentional or unintentional, that communicate hostile, derogatory, or negative . . . slights and insults.”

The term, as coined by the psychiatrist Chester Pierce, refers to an action that denigrates a racial group; but in this case, Greg’s request can be seen as disparaging Becky and women more generally.

Scholars such as Joan C. Williams of the University of California, Hastings College of the Law have observed that women get “stuck” disproportionately with administrative tasks, such as taking notes, ordering lunch, and scheduling meetings, and research by Carnegie Mellon’s Linda Babcock and Laurie Weingart, Maria P. Recalde of the International Food Policy Research Institute, and Lise Vesterlund of the University of Pittsburgh has found women are more likely to be assigned or volunteer to take on “nonpromotable work.”

Interpersonal conflict is seldom pleasant, and this scenario is especially tricky because Greg may not have meant to slight Becky. A confrontation, particularly a public one in front of other product managers, could therefore lead Greg to be defensive.

Finally, the situation is complex strategically: Should you speak to Greg now or later?

Is a subtle approach or a more direct confrontation appropriate?

Should you talk about the specific behavior or provoke a larger conversation about culture and norms? more>

Related>

Updates from Chicago Booth

Trade policy is upending markets—but not investment
By Steven J. Davis – Trade-policy concerns became a major source of US stock market volatility in 2018. For example, the S&P 500 fell 2.5 percent on March 22, 2018, reacting to news about just-announced US tariffs on tens of billions of dollars of Chinese imports. Four days later, the index rose 2.7 percent on news the United States and China had begun trade negotiations. Still, tariffs and tariff threats between the two countries ratcheted upward over the next several months.

This prominence marks a striking change, as demonstrated in my research with Northwestern’s Scott R. Baker, Northwestern PhD candidate Marco Sammon, and Stanford’s Nicholas Bloom. We took a systematic look at the role of trade-policy developments and other news in large daily stock market moves. We first identified every daily move of 2.5 percent or more, up or down, in the US stock market. By this criterion, there were 1,112 large daily moves from 1900 to the end of 2018.

For each large move, we read next-day news articles in the Wall Street Journal to classify perceptions of what moved the market. The WSJ attributed seven of 1,103 large moves from 1900 to 2017 mainly to news about trade policy. But in a remarkable turnabout, the newspaper attributed three of nine large moves in 2018 to trade-policy news. From a historical perspective, the prominent role of trade policy in recent US stock market swings is highly unusual.

The highly visible US–China dispute is only one of the heightened trade-policy concerns behind the pattern we chart. The US has also become enmeshed in trade-policy disputes with several other major trading partners since Donald Trump became president.

How much do these heightened concerns affect capital-investment expenditures by US businesses? Not as much as you might think. more>

Related>

Updates from Chicago Booth

Retailers: A better algorithm could increase online sales by 76 percent
By Brian Wallheimer – Brick-and-mortar stores use rows of candy, lip balms, and magazines in the checkout aisles to entice shoppers into making additional purchases. Online shopping sites suggest add-on products for the same reason.

New York University’s Xi Chen, MIT’s Will Ma and David Simchi-Levi, and Chicago Booth’s Linwei Xin have developed an algorithm for these online offers that could help retailers raise the number of such impulse purchases. Their study, which involved a collaboration with Wal-Mart’s online grocery division, indicates that if an algorithm were to consider the retailer’s inventory, it could nearly double add-on sales.

The algorithms behind online add-on offers can be sophisticated, drawing on shoppers’ habits and preferences. But they can also be tricky to tailor, as customers don’t always have to register accounts to purchase products online, and they may shop for a wide variety of items. Moreover, retailers can have trouble figuring out what a shopper actually needs. If a shopper buys five T-shirts, a store might suggest other T-shirts for her to buy, when what she really needs is shorts.

Wal-Mart’s online grocery platform makes add-on suggestions that are based on only the items in the customer’s current shopping cart—and it tries to use those to identify what a shopper might be missing. Say someone has purchased cereal but not milk. The algorithm would offer that customer milk, either at full price or possibly discounted.

But the method has a flaw, the researchers say: it doesn’t take inventory into account. more>

Related>

Updates from Chicago Booth

How opinion polls are presented affects how we understand them
By Alice G. Walton – Oleg Urminsky and Luxi Shen used data provided by the prominent data-driven forecasting organization FiveThirtyEight leading up to the 2016 US presidential election.

The researchers presented the then-current forecasts to two groups of study participants, but in different formats. One group saw probability projections that, on average, said Democratic candidate Hillary Clinton had a 74 percent chance of winning. The other group saw margin forecasts that said, on average, that she would get 53 percent of the vote.

On a given day, both forecasts represented the same snapshot in time—two essentially identical takes on Clinton’s expected victory. But participants interpreted the forecasts differently. When people saw the probability forecast and were then asked to estimate a margin by which Clinton would win, they overestimated, predicting she would get 60 percent of the vote on average, more than the 53 percent. Meanwhile, people shown the second, margin forecast predicted the probability of her winning at 60 percent on average rather than the actual 74 percent average.

Both predictions turned out to be incorrect, as Clinton won 48 percent of the vote and lost the election to Republican candidate Donald Trump, who received 46 percent. But they illustrated bias in people’s perceptions.

The difference in interpretations is unlikely to be explained by forecasters having the wrong assumptions in their models, the researchers say. more>

Related>

Updates from Chicago Booth

Technology is splitting the job market
Some people are prospering, while others are left behind
By Raghuram Rajan – Soon, the smartphone may be replaced by a device implanted in our body that connects with our mind and provides instant access to both computing power and enormous databases. Computer-enhanced humans are no longer the realm of science fiction. The information and communications technology (ICT) revolution has fundamentally changed what we spend time on, how we interact with one another, what work we do and where we do it, and even how people commit crime.

Most importantly, it has upset the balance between the three pillars—the state, markets, and the community.

The ICT revolution has not just followed the course of previous revolutions by displacing jobs through automation; it has also made it possible to produce anywhere and sell anywhere to a greater degree than ever before. By unifying markets further, it has increased the degree of cross-border competition, first in manufacturing and now in services. Successful producers have been able to grow much larger by making where it is most efficient. This has created spectacular winners, but also many losers.

The technology-assisted market has had widely varying effects across productive sectors in a country. Some of the effects stem naturally from technological change, and some stem from the reactions of people and companies to it. Indisputably, it has raised the premium on human capabilities. As a result, some well-educated communities in big cities have prospered, while communities with moderately (typically high-school-) educated workers in semirural areas dominated by manufacturing often have not.

More generally, as with past technological revolutions, the need for people to adapt has come rapidly, before the benefits have spread widely. Indeed, the communities that are required to adapt the most, as always, are the communities that have been experiencing the greatest adversity, and have the least resources to cope. more>

Related>

Updates from Chicago Booth

Public disclosures help hold politicians accountable
By Rebecca Stropoli – A common problem in democracies is that, once elected, politicians may fail to address the needs of their constituents, especially the poorer ones. But is there a way to empower the electorate by holding officials accountable for their actions?

MIT’s Abhijit Banerjee and Harvard’s Nils Enevoldsen, Rohini Pande, and Michael Walton examined the effect that publicizing politicians’ records had on electoral results in the 2012 municipal elections in Delhi, India. They find that being issued public report cards caused politicians to shift their spending priorities.

With more than 18 million people, Delhi is the world’s second-largest city, behind Tokyo. Poor people living in slums form a significant share of the Delhi population. Slum dwellers, in fact, account for an electoral majority in many of the city’s 272 single-member wards, each of which elects a councilor to the municipal government every five years.

The anticipation of media reports did influence the policies of politicians representing poorer areas, the findings suggest. Councilors in high-slum wards whose report cards were published shifted their spending priorities to better match the needs of their constituents.

The “effective spending” on the needs of the poor by these councilors over two years increased by about $5,000 on average, or more than 13 percent, Enevoldsen says. more>

Related>

Updates from Chicago Booth

Machine learning can help money managers time markets, build portfolios, and manage risk
By Michael Maiello – It’s been two decades since IBM’s Deep Blue beat chess champion Garry Kasparov, and computers have become even smarter. Machines can now understand text, recognize voices, classify images, and beat humans in Go, a board game more complicated than chess, and perhaps the most complicated in existence.

And research suggests today’s computers can also predict asset returns with an unprecedented accuracy.

Yale University’s Bryan T. Kelly, Chicago Booth’s Dacheng Xiu, and Booth PhD candidate Shihao Gu investigated 30,000 individual stocks that traded between 1957 and 2016, examining hundreds of possibly predictive signals using several techniques of machine learning, a form of artificial intelligence. They conclude that ML had significant advantages over conventional analysis in this challenging task.

ML uses statistical techniques to give computers abilities that mimic and sometimes exceed human learning. The idea is that computers will be able to build on solutions to previous problems to eventually tackle issues they weren’t explicitly programmed to take on.

“At the broadest level, we find that machine learning offers an improved description of asset price behavior relative to traditional methods,” the researchers write, suggesting that ML could become the engine of effective portfolio management, able to predict asset-price movements better than human managers. more>

Related>

Updates from Chicago Booth

How sales taxes could boost economic growth
By Dee Gill – The fight against sluggish global economic growth has been expensive, protracted, and unexpectedly vexing, leaving central bankers in developed economies with a laundry list of shared frustrations. Meager economic growth, flagging wages, and low inflation persist, in spite of bankers’ monetary stimuli, and threaten to quash upward mobility for young job seekers and midcareer employees in even the richest countries.

There’s a poster child for what countries do not want to become: Japan. The former economic powerhouse has been stuck in low-growth purgatory since 1991. And yet, as much as they’d like to avoid it, some countries have been sliding in that direction.

Many big economies are stagnating, and economists are running out of options to fix them. The conventional monetary policy for encouraging spending has been to drop short-term interest rates. But with rates already near, at, or below zero, that method is all but exhausted. Some economists have also started to empirically and theoretically question the power of forward guidance, in which central banks publicize plans for future interest-rate policies, at the zero lower bound.

Central banks and governments badly need a new stimulus tool, preferably one that doesn’t cost a lot of money. Some researchers are proposing a fix that might sound unappetizing: raising sales taxes as a means of jump-starting economic growth.

Francesco D’Acunto of the University of Maryland, Daniel Hoang of Germany’s Karlsruhe Institute of Technology, and Chicago Booth’s Michael Weber find evidence that a preannounced tax hike—a 3-percentage-point increase in Germany’s Value Added Tax enacted in 2007—provided just the kind of growth stimulus central banks desperately need today. more>

Related>