econminute

[econminute]

Recent court decisions could have a big impact on big business (and small business)

This has been a big year for business in the courts. A U.S. district court approved the AT&T-Time Warner merger, the Supreme Court upheld Amex’s agreements with merchants, and a circuit court pushed back on the Federal Trade Commission’s vague and heavy handed policing of companies’ consumer data safeguards.

These three decisions mark a new era in the intersection of law and economics.

AT&T-Time Warner

AT&T-Time Warner is a vertical merger, a combination of firms with a buyer-seller relationship. Time Warner creates and broadcasts content via outlets such as HBO, CNN, and TNT. AT&T distributes content via services such as DirecTV.

Economists see little risk to competition from vertical mergers, although there are some idiosyncratic circumstances in which competition could be harmed. Nevertheless, the U.S. Department of Justice went to court to block the merger.

The last time the goverment sued to block a merger was more than 40 years ago, and the government lost. Since then, the government relied on the threat of litigation to extract settlements from the merging parties. For example, in the 1996 merger between Time Warner and Turner, the FTC required limits on how the new company could bundle HBO with less desirable channels and eliminated agreements that allowed TCI (a cable company that partially owned Turner) to carry Turner channels at preferential rates.

With AT&T-Time Warner, the government took a big risk, and lost. It was a big risk because (1) it’s a vertical merger, and (2) the case against the merger was weak. The government’s expert argued consumers would face an extra 45 cents a month on their cable bills if the merger went through, but under cross-examination, conceded it might be as little as 13 cents a month. That’s a big difference and raised big questions about the reliability of the expert’s model.

Judge Richard J. Leon’s 170+ page ruling agreed that the government’s case was weak and its expert was not credible. While it’s easy to cheer a victory of big business over big government, the real victory was the judge’s heavy reliance on facts, data, and analysis rather than speculation over the potential for consumer harm. That’s a big deal and may make the way for more vertical mergers.

Ohio v. American Express

The Supreme Court’s ruling in Amex may seem obscure. The court backed American Express Co.’s policy of preventing retailers from offering customers incentives to pay with cheaper cards.

Amex charges higher fees to merchants than do other cards, such as Visa, MasterCard, and Discover. Amex cardholders also have higher incomes and tend to spend more at stores than those associated with other networks. And, Amex offers its cardholders better benefits, services, and rewards than the other cards. Merchants don’t like Amex because of the higher fees, customers prefer Amex because of the card’s perks.

Amex, and other card companies, operate in what is known as a two-sided market. Put simply, they have two sets of customers: merchants who pay swipe fees, and consumers who pay fees and interest.

Part of Amex’s agreement with merchants is an “anti-steering” provision that bars merchants from offering discounts for using non-Amex cards. The U.S. Justice Department and a group of states sued the company, alleging the Amex rules limited merchants’ ability to reduce their costs from accepting credit cards, which meant higher retail prices. Amex argued that the higher prices charged to merchants were kicked back to its cardholders in the form of more and better perks.

The Supreme Court found that the Justice Department and states focused exclusively on one side (merchant fees) of the two-sided market. The courts says the government can’t meet its burden by showing some effect on some part of the market. Instead, they must demonstrate, “increased cost of credit card transactions … reduced number of credit card transactions, or otherwise stifled competition.” The government could not prove any of those things.

We live in a world two-sided markets. Amazon may be the biggest two-sided market in the history of the world, linking buyers and sellers. Smartphones such as iPhones and Android devices are two-sided markets, linking consumers with app developers. The Supreme Court’s ruling in Amex sets a standard for how antitrust law should treat the economics of two-sided markets.

LabMD

LabMD is another matter that seems obscure, but could have big impacts on the administrative state.

Since the early 2000s, the FTC has brought charges against more than 150 companies alleging they had bad security or privacy practices. LabMD was one of them, when its computer system was compromised by professional hackers in 2008. The FTC claimed that LabMD’s failure to adequately protect customer data was an “unfair” business practice.

Challenging the FTC can get very expensive and the agency used the threat of litigation to secure settlements from dozens of companies. It then used those settlements to convince everyone else that those settlements constituted binding law and enforceable security standards.

Because no one ever forced the FTC to defend what it was doing in court, the FTC’s assertion of legal authority became a self-fulfilling prophecy. LabMD, however, chose to challege the FTC. The fight drove LabMD out of business, but public interest law firm Cause of Action and lawyers at Ropes & Gray took the case on a pro bono basis.

The 11th Circuit Court of Appeals ruled the FTC’s approach to developing security standards violates basic principles of due process. The court said the FTC’s basic approach—in which the FTC tries to improve general security practices by suing companies that experience security breaches—violates the basic legal principle that the government can’t punish someone for conduct that the government hasn’t previously explained is problematic.

My colleague at ICLE observes the lesson to learn from LabMD isn’t about the illegitimacy of the FTC’s approach to internet privacy and security. Instead, it says legality of the administrative state is premised on courts placing a check on abusive regulators.

The lessons learned from these three recent cases reflect a profound shift in thinkging about the laws governing economic activity:

AT&T-Time Warner indicates that facts matter. Mere speculation of potential harms will not satisfy the court.

Amex highlights the growing role two-sided markets play in our economy and provides framework for evaluating competition in these markets.

LabMD is a small step in reining in the administrative state. Regulations must be scrutinized before they are imposed and enforced.

In some ways none of these decisions are revolutionary. Instead, they reflect an evolution toward greater transparency in how the law is to be applied and greater scrutiny over how the regulations are imposed.

  The post Recent court decisions could have a big impact on big business (and small business) appeared first on Econ Minute.

Originally published at https://ift.tt/2Msvtra

[econminute]

Recent court decisions could have a big impact on big business (and small business)

Recent court decisions could have a big impact on big business (and small business)

This has been a big year for business in the courts. A U.S. district court approved the AT&T-Time Warner merger, the Supreme Court upheld Amex’s agreements with merchants, and a circuit court pushed back on the Federal Trade Commission’s vague and heavy handed policing of companies’ consumer data safeguards.

These three decisions mark a new era in the intersection of law and economics.

AT&T-Time…

[econminute]

Weekend reads: Big is bad edition — Truth on the Market

Big is bad, part 1: Kafka, Coase, and Brandeis walk into a bar … There’s a quip in a well-known textbook that Nobel laureate Ronald Coase said he’d grown weary of antitrust because when prices went up, the judges said it was monopoly; when the prices went down, they said it was predatory pricing; and when they stayed the same, they said it was tacit collusion. ICLE’s Geoffrey Manne and Gus Hurwitz worry that not much has changed since Coase’s time:

[C]ompetition, on its face, is virtually indistinguishable from anticompetitive behavior. Every firm strives to undercut its rivals, to put its rivals out of business, to increase its rivals’ costs, or to steal its rivals’ customers. The consumer welfare standard provides courts with a concrete mechanism for distinguishing between good and bad conduct, based not on the effect on rival firms but on the effect on consumers. Absent such a standard, any firm could potentially be deemed to violate the antitrust laws for any act it undertakes that could impede its competitors.

Big is bad, part 2. A working paper published by researchers from Denmark and the University of California at Berkeley suggest that companies such as Google, Apple, Facebook, and Nike are taking advantage of so-called “tax havens” to cause billions of dollars of income go “missing.” There’s a lot of mumbo jumbo in this one, but it’s getting lots of attention.

We show theoretically and empirically that in the current international tax system, tax authorities of high-tax countries do not have incentives to combat profit shifting to tax havens. They instead focus their enforcement effort on relocating profits booked in other high-tax places—in effect stealing revenue from each other.

Big is bad, part 3: Can any country survive with debt-to-GDP of more than 100 percent? Apparently, the answer is “yes.” The U.K. went 80 years, from 1779 to 1858. Then, it went 47 years from 1916 to 1962. Tim Harford has a fascinating story about an effort to clear the country’s debt in that second run.

In 1928, an anonymous donor resolved to clear the UK’s national debt and gave £500,000 with that end in mind. It was a tidy sum — almost £30m at today’s prices — but not nearly enough to pay off the debt. So it sat in trust, accumulating interest, for nearly a century.

How do you make a small fortune? Begin with a big one. A lesson from Johnny Depp.

Will we ever stop debating the Trolley Problem? Apparently the answer is “no.” Also, TIL there’s a field of research that relies on “notions.”

For so long, moral psychology has relied on the notion that you can extrapolate from people’s decisions in hypothetical thought experiments to infer something meaningful about how they would behave morally in the real world. These new findings challenge that core assumption of the field.

  The week that was on Truth on the Market

LabMD.

[T]argets of complaints settle for myriad reasons, and no outside authority need review the sufficiency of a complaint as part of a settlement. And the consent orders themselves are largely devoid of legal and even factual specificity. As a result, the FTC’s authority to initiate an enforcement action  is effectively based on an ill-defined series of hunches — hardly a sufficient basis for defining a clear legal standard.

Google Android.

Thus, had Google opted instead to create a separate walled garden of its own on the Apple model, everything it had done would have otherwise been fine. This means that Google is now subject to an antitrust investigation for attempting to develop a more open platform.

AT&T-Time Warner. First this:

The government’s contention that, after the merger, AT&T and rival Comcast could coordinate to restrict access to popular Time Warner and NBC content to harm emerging competitors was always a weak argument.

Then this:

Doing no favors to its case, the government turned to a seemingly contradictory argument that AT&T and Comcast would coordinate to demand virtual providers take too much content.

    The post Weekend reads: Big is bad edition — Truth on the Market appeared first on Econ Minute.

Originally published at https://ift.tt/2tn30fv

[econminute]

Weekend reads: Big is bad edition — Truth on the Market Big is bad, part 1: Kafka, Coase, and Brandeis walk into a bar … There’s a quip in a well-known textbook that Nobel laureate Ronald Coase said he’d grown weary of antitrust because when prices went up, the judges said it was monopoly; when the prices went down, they said it was predatory pricing; and […] via Weekend reads: Big is bad edition — Truth on the Market

[econminute]

Weekend reads: Big is bad edition — Truth on the Market Big is bad, part 1: Kafka, Coase, and Brandeis walk into a bar … There’s a quip in a well-known textbook that Nobel laureate Ronald Coase said he’d grown weary of antitrust because when prices went up, the judges said it was monopoly; when the prices went down, they said it was predatory pricing; and […] via Weekend reads: Big is bad edition — Truth on the Market

[econminute]

Do biased stats provide bogus economics? A primer on publication bias and power

If you do research involving statistical analysis, you’ve heard of John Ioannidis. If you haven’t heard of him, you will. He’s gone after the fields of medicine, psychology, and economics. He may be coming for your field next.

Ioannidis is after bias in research. He is perhaps best known for a 2005 paper “Why Most Published Research Findings Are False.” A professor at Stanford, he has built a career in the field of meta-research and may be one of the most highly cited researchers alive.

In 2017, he published “The Power of Bias in Economics Research.” He recently talked to Russ Roberts on the EconTalk podcast about his research and what it means for economics.

He focuses on two factors that contribute to bias in economics research: publication bias and low power. These are complicated topics. This post hopes to provide a simplified explanation of these issues and why bias and power matters.

What is bias?

We frequently hear the word bias. “Fake news” is biased news. For dinner, I am biased toward steak over chicken. That’s different from statistical bias.

In statistics, bias means that a researcher’s estimate of a variable or effect is different from the “true” value or effect. The “true” probability of getting heads from tossing a fair coin is 50 percent. Let’s say that no matter how many times I toss a particular coin, I find that I’m getting heads about 75 percent of the time. My instrument, the coin, may be biased. I may be the most honest coin flipper, but my experiment has biased results. In other words, biased results do not imply biased research or biased researchers.

Publication bias

Publication bias occurs because peer-reviewed publications tend to favor publishing positive, statistically significant results and to reject insignificant results. Informally, this is known as the “file drawer” problem. Nonsignificant results remain unsubmitted in the researcher’s file drawer or, if submitted, remain in limbo in an editor’s file drawer.

Studies are more likely to be published in peer-reviewed publications if they have statistically significant findings, build on previous published research, and can potentially garner citations for the journal with sensational findings. Studies that don’t have statistically significant findings or don’t build on previous research are less likely to be published.

The importance of “sensational” findings means that ho-hum findings—even if statistically significant—are less likely to be published. For example, research finding that a 10 percent increase in the minimum wage is associated with a one-tenth of 1 percent reduction in employment (i.e., an elasticity of 0.01) would be less likely to be published than a study finding a 3 percent reduction in employment (i.e., elasticity of –0.3).

“Man bites dog” findings—those that are counterintuitive or contradict previously published research—may be less likely to be published. A study finding an upward sloping demand curve is likely to be rejected because economists “know” demand curves slope downward.

On the other hand, man bites dog findings may also be more likely to be published. Card and Krueger’s 1994 study finding that a minimum wage hike was associated with an increase in low-wage workers was published in the top-tier American Economic Review. Had the study been conducted by lesser-known economists, it’s much less likely it would have been accepted for publication. The results were sensational, judging from the attention the article got from the New York Times, the Wall Street Journal, and even the Clinton administration. Sometimes a man does bite a dog.

Low power

A study with low statistical power has a reduced chance of detecting a true effect.

Consider our criminal legal system. We seek to find criminals guilty, while ensuring the innocent go free. Using the language of statistical testing, the presumption of innocence is our null hypothesis. We set a high threshold for our test: Innocent until proven guilty, beyond a reasonable doubt. We hypothesize innocence and only after overcoming our reasonable doubt do we reject that hypothesis.

An innocent person found guilty is considered a serious error—a “miscarriage of justice.” The presumption of innocence (null hypothesis) combined with a high burden of proof (beyond a reasonable doubt) are designed to reduce these errors. In statistics, this is known as “Type I” error, or “false positive.” The probability of a Type I error is called alpha, which is set to some arbitrarily low number, like 10 percent, 5 percent, or 1 percent.

Failing to convict a known criminal is also a serious error, but generally agreed it’s less serious than a wrongful conviction. Statistically speaking, this is a “Type II” error or “false negative” and the probability of making a Type II error is beta.

By now, it should be clear there’s a relationship between Type I and Type II errors. If we reduce the chance of a wrongful conviction, we are going to increase the chance of letting some criminals go free. It can be mathematically shown (not here), that a reduction in the probability of Type I error is associated with an increase in Type II error.

Consider O.J. Simpson. Simpson was not found guilty in his criminal trial for murder, but was found liable for the deaths of Nicole Simpson and Ron Goldman in a civil trial. One reason for these different outcomes is the higher burden of proof for a criminal conviction (“beyond a reasonable doubt,” alpha = 1 percent) than for a finding of civil liability (“preponderance of evidence,” alpha = 50 percent). If O.J. truly is guilty of the murders, the criminal trial would have been less likely to find guilt than the civil trial would.

In econometrics, we construct the null hypothesis to be the opposite of what we hypothesize to be the relationship. For example, if we hypothesize that an increase in the minimum wage decreases employment, the null hypothesis would be: “A change in the minimum wage has no impact on employment.” If the research involves regression analysis, the null hypothesis would be: “The estimated coefficient on the elasticity of employment with respect to the minimum wage would be zero.” If we set the probability of Type I error to 5 percent, then regression results with a p-value of less than 0.05 would be sufficient to reject the null hypothesis of no relationship. If we increase the probability of Type I error, we increase the likelihood of finding a relationship, but we also increase the chance of finding a relationship when none exists.

Now, we’re getting to power.

Power is the chance of detecting a true effect. In the legal system, it would be the probability that a truly guilty person is found guilty.

By definition, a low power study has a small chance of discovering a relationship that truly exists. Low power studies produce more false negative than high power studies. If a set of studies have a power of 20 percent, then if we know that there are 100 actual effects, the studies will find only 20 of them. In other words, out of 100 truly guilty suspects, a legal system with a power of 20 percent will find only 20 of them guilty.

Suppose we expect 25 percent of those accused of a crime are truly guilty of the crime. Thus the odds of guilt are R = 0.25 / 0.75 = 0.33. Assume we set alpha to 0.05, and conclude the accused is guilty if our test statistic provides p < 0.05. Using Ioannidis’ formula for positive predictive value, we find:

If the power of the test is 20 percent, the probability that a “guilty” verdict reflects true guilt is 57 percent.

If the power of the test is 80 percent, the probability that a “guilty” verdict reflects true guilt is 84 percent.

In other words, a low power test is more likely to convict the innocent than a high power test.

In our minimum wage example, a low power study is more likely find a relationship between a change in the minimum wage and employment when no relationship truly exists. By extension, even if a relationship truly exists, a low power study would be more likely to find a bigger impact than a high power study. The figure below demonstrates this phenomenon.

Across the 1,424 studies surveyed, the average elasticity with respect to the minimum wage is –0.190 (i.e., a 10 percent increase in the minimum wage would be associated with a 1.9 percent decrease in employment). When adjusted for the studies’ precision, the weighted average elasticity is –0.054. By this simple analysis, the unadjusted average is 3.5 times bigger than the adjusted average. Ioannidis and his coauthors estimate among the 60 studies with “adequate” power, the weighted average elasticity is –0.011.

(By the way, my own unpublished studies of minimum wage impacts at the state level had an estimated short-run elasticity of –0.03 and “precision” of 122 for Oregon and short-run elasticity of –0.048 and “precision” of 259 for Colorado. These results are in line with the more precise studies in the figure above.)

Is economics bogus?

It’s tempting to walk away from this discussion thinking all of econometrics is bogus. Ioannidis himself responds to this temptation:

Although the discipline has gotten a bad rap, economics can be quite reliable and trustworthy. Where evidence is deemed unreliable, we need more investment in the science of economics, not less.

For policymakers, the reliance on economic evidence is even more important, according to Ioannidis:

[P]oliticians rarely use economic science to make decisions and set new laws. Indeed, it is scary how little science informs political choices on a global scale. Those who decide the world’s economic fate typically have a weak scientific background or none at all.

Ioannidis and his colleagues identify several way to address the reliability problems in economics and other fields—social psychology is one of the worst. However these are longer term solutions.

In the short term, researchers and policymakers should view sensational finding with skepticism, especially if those sensational findings support their own biases. That skepticism should begin with one simple question: “What’s the confidence interval?”

Originally published at Truth on the Market.

  The post Do biased stats provide bogus economics? A primer on publication bias and power appeared first on Econ Minute.

Originally published at https://ift.tt/2GZPiF1

[econminute]

Do biased stats provide bogus economics? A primer on publication bias and power

Do biased stats provide bogus economics? A primer on publication bias and power

If you do research involving statistical analysis, you’ve heard of John Ioannidis. If you haven’t heard of him, you will. He’s gone after the fields of medicine, psychology, and economics. He may be coming for your field next.

Ioannidis is after bias in research. He is perhaps best known for a 2005 paper “Why Most Published Research Findings Are False.” A professor at Stanford, he has built a…

[econminute]

Unsurprising evidence that hiking the minimum wage hurts low wage workers

On July 1, the minimum wage spiked in several cities and states across the country. Portland, Oregon’s minimum wage will rise by $1.50 to $11.25 an hour. Los Angeles will also hike its minimum wage by $1.50 to $12 an hour. Recent research shows that these hikes will make low wage workers poorer.

A study supported and funded in part by the Seattle city government, was released this week, along with an NBER paper evaluating Seattle’s minimum wage increase to $13 an hour. The papers find that the increase to $13 an hour had significant negative impacts on employment and led to lower incomes for minimum wage workers.

The study is the first study of a very high minimum wage for a city. During the study period, Seattle’s minimum wage increased from what had been the nation’s highest state minimum wage to an even higher level. It is also unique in its use of administrative data that has much more detail than is usually available to economics researchers.

Conclusions from the research focusing on Seattle’s increase to $13 an hour are clear: The policy harms those it was designed to help.

A loss of more than 5,000 jobs and a 9 percent reduction in hours worked by those who retained their jobs.

Low-wage workers lost an average of $125 per month. The minimum wage has always been a terrible way to reduce poverty. In 2015 and 2016, I presented analysis to the Oregon Legislature indicating that incomes would decline with a steep increase in the minimum wage. The Seattle study provides evidence backing up that forecast.

Minimum wage supporters point to research from the 1990s that made headlines with its claims that minimum wage increases had no impact on restaurant employment. The authors of the Seattle study were able to replicate the results of these papers by using their own data and imposing the same limitations that the earlier researchers had faced. The Seattle study shows that those earlier papers’ findings were likely driven by their approach and data limitations. This is a big deal, and a novel research approach that gives strength to the Seattle study’s results.

Some inside baseball.

The Seattle Minimum Wage Study was supported and funded in part by the Seattle city government. It’s rare that policy makers go through any effort to measure the effectiveness of their policies, so Seattle should get some points for transparency.

Or not so transparent: The mayor of Seattle commissioned another study, by an advocacy group at Berkeley whose previous work on the minimum wage is uniformly in favor of hiking the minimum wage (they testified before the Oregon Legislature to cheerlead the state’s minimum wage increase). It should come as no surprise that the Berkeley group released its report several days before the city’s “official” study came out.

You might think to yourself, “OK, that’s Seattle. Seattle is different.”

But, maybe Seattle is not that different. In fact, maybe the negative impacts of high minimum wages are universal, as seen in another study that came out this week, this time from Denmark.

In Denmark the minimum wage jumps up by 40 percent when a worker turns 18. The Danish researchers found that this steep increase was associated with employment dropping by one-third, as seen in the chart below from the paper.

Let’s look at what’s going to happen in Oregon. The state’s employment department estimates that about 301,000 jobs will be affected by the rate increase. With employment of almost 1.8 million, that means one in six workers will be affected by the steep hikes going into effect on July 1. That’s a big piece of the work force. By way of comparison, in the past when the minimum wage would increase by five or ten cents a year, only about six percent of the workforce was affected.

This is going to disproportionately affect youth employment. As noted in my testimony to the legislature, unemployment for Oregonians age 16 to 19 is 8.5 percentage points higher than the national average. This was not always the case. In the early 1990s, Oregon’s youth had roughly the same rate of unemployment as the U.S. as a whole. Then, as Oregon’s minimum wage rose relative to the federal minimum wage, Oregon’s youth unemployment worsened. Just this week, Multnomah County made a desperate plea for businesses to hire more youth as summer interns.

It has been suggested Oregon youth have traded education for work experience—in essence, they have opted to stay in high school or enroll in higher education instead of entering the workforce. The figure below shows, however, that youth unemployment has increased for both those enrolled in school and those who are not enrolled in school. The figure debunks the notion that education and employment are substitutes. In fact, the large number of students seeking work demonstrates many youth want employment while they further their education.

None of these results should be surprising. Minimum wage research is more than a hundred years old. Aside from the “mans bites dog” research from the 1990s, economists were broadly in agreement that higher minimum wages would be associated with reduced employment, especially among youth. The research published this week is groundbreaking in its data and methodology. At the same time, the results are unsurprising to anyone with any understanding of economics or experience running a business.

This post was originally published at Truth on the Market.

The post Unsurprising evidence that hiking the minimum wage hurts low wage workers appeared first on Econ Minute.

Originally published at http://ift.tt/2tiywtz

[econminute]

Unsurprising evidence that hiking the minimum wage hurts low wage workers

Unsurprising evidence that hiking the minimum wage hurts low wage workers

On July 1, the minimum wage spiked in several cities and states across the country. Portland, Oregon’s minimum wage will rise by $1.50 to $11.25 an hour. Los Angeles will also hike its minimum wage by $1.50 to $12 an hour. Recent research shows that these hikes will make low wage workers poorer.

A studysupported and funded in part by the Seattle city government, was released this week, along with…

[econminute]

Do we really need an expert witness?

Yes, you do.

This week’s decision by the Seventh Circuit in Cripe v. Henkel Corp., No. 17-1231 (June 7, 2017), written by Judge Frank Easterbrook, is a reminder for litigators of the importance of mastering the fundamentals. The court held that the plaintiff in a personal-injury action had failed to disclose any experts, or provide any expert reports, under Fed. R. Civ. P. 26(a)(2) to rebut the defendant’s expert on causation. When the defendant moved for summary judgment, the trial court granted the motion, given that there was no contrary evidence. The Seventh Circuit affirmed, reaching the profound conclusion that “[y]ou can’t beat something with nothing.”

From Foley & Lardner LLP.

The post Do we really need an expert witness? appeared first on Econ Minute.

Originally published at http://ift.tt/2sU7VWG

[econminute]

Do we really need an expert witness?

Do we really need an expert witness?

Yes, you do.

This week’s decision by the Seventh Circuit in Cripe v. Henkel Corp., No. 17-1231 (June 7, 2017), written by Judge Frank Easterbrook, is a reminder for litigators of the importance of mastering the fundamentals. The court held that the plaintiff in a personal-injury action had failed to disclose any experts, or provide any expert reports, under Fed. R. Civ. P. 26(a)(2) to rebut the…

[econminute]

The Squawk Box effect on CEO pay

From the Wall Street Journal:

How big is the CNBC effect? “CEOs who appear in CNBC interviews will earn $210,239 more” on average in the following year, the professors say, compared with similar CEOs who didn’t go on.

CEOs of small companies see a bigger bump. The effect for CEOs in the smallest firms was $130,925 greater than for CEOs in the largest companies, even though big business CEOs usually get paid more.

Cable TV is better than print. A CEO who got more print coverage than average in a year got a tiny boost in pay the next year.

The post The Squawk Box effect on CEO pay appeared first on Econ Minute.

Originally published at http://ift.tt/2tJZbi4

[econminute]

The Squawk Box effect on CEO pay

The Squawk Box effect on CEO pay

From the Wall Street Journal:

How big is the CNBC effect? “CEOs who appear in CNBC interviews will earn $210,239 more” on average in the following year, the professors say, compared with similar CEOs who didn’t go on.

CEOs of small companies see a bigger bump. The effect for CEOs in the smallest firms was $130,925 greater than for CEOs in the largest companies, even though big business CEOs…

[econminute]

How to get better voter turnout in close races

Take a poll.

Make sure media reports the poll.

From NBER:

Closer elections are associated with greater turnout only when polls exist. Examining within-election variation in newspaper reporting on polls across cantons, we find that close polls increase turnout significantly more where newspapers report on them most.

  The post How to get better voter turnout in close races appeared first on Econ Minute.

Originally published at http://ift.tt/2sHa8E2

[econminute]

How to get better voter turnout in close races

How to get better voter turnout in close races

Take a poll.

Make sure media reports the poll.

From NBER:

Closer elections are associated with greater turnout only when polls exist. Examining within-election variation in newspaper reporting on polls across cantons, we find that close polls increase turnout significantly more where newspapers report on them most.

[econminute]

Refugees pay more in taxes than they collect in benefits

Research from the National Bureau of Economic Research:

Using the NBER TAXSIM program, we estimate that refugees pay $21,000 more in taxes than they receive in benefits over their first 20 years in the U.S.

Other findings:

Refugees that enter the U.S. before age 14 graduate high school and enter college at the same rate as natives.

Among refugees that entered the U.S. at ages 18-45, after 6 years in the country, these refugees work at higher rates than natives but they never attain the earning levels of U.S.-born respondents.

The post Refugees pay more in taxes than they collect in benefits appeared first on Econ Minute.

Originally published at http://ift.tt/2twgpPW

[econminute]

Refugees pay more in taxes than they collect in benefits

Refugees pay more in taxes than they collect in benefits

Research from the National Bureau of Economic Research:

Using the NBER TAXSIM program, we estimate that refugees pay $21,000 more in taxes than they receive in benefits over their first 20 years in the U.S.

Other findings:

Refugees that enter the U.S. before age 14 graduate high school and enter college at the same rate as natives.

Among refugees that entered the U.S. at ages 18-45, after 6 years…