Archives For economic studies

What Can the Stock Market Tell Us About the T-Mobile/Sprint Merger?

Alec Stapp —  14 February 2020

On Monday evening, around 6:00 PM Eastern Standard Time, news leaked that the United States District Court for the Southern District of New York had decided to allow the T-Mobile/Sprint merger to go through, giving the companies a victory over a group of state attorneys general trying to block the deal.

Thomas Philippon, a professor of finance at NYU, used this opportunity to conduct a quick-and-dirty event study on Twitter:

Short thread on T-Mobile/Sprint merger. There were 2 theories:

(A) It’s a 4-to-3 merger that will lower competition and increase markups.

(B) The new merged entity will be able to take on the industry leaders AT&T and Verizon.

(A) and (B) make clear predictions. (A) predicts the merger is good news for AT&T and Verizon’s shareholders. (B) predicts the merger is bad news for AT&T and Verizon’s shareholders. The news leaked at 6pm that the judge would approve the merger. Sprint went up 60% as expected. Let’s test the theories. 

Here is Verizon’s after trading price: Up 2.5%.

Here is ATT after hours: Up 2%.

Conclusion 1: Theory B is bogus, and the merger is a transfer of at least 2%*$280B (AT&T) + 2.5%*$240B (Verizon) = $11.6 billion from the pockets of consumers to the pockets of shareholders. 

Conclusion 2: I and others have argued for a long time that theory B was bogus; this was anticipated. But lobbying is very effective indeed… 

Conclusion 3: US consumers already pay two or three times more than those of other rich countries for their cell phone plans. The gap will only increase.

And just a reminder: these firms invest 0% of the excess profits. 

Philippon published his thread about 40 minutes prior to markets opening for regular trading on Tuesday morning. The Court’s official decision was published shortly before markets opened as well. By the time regular trading began at 9:30 AM, Verizon had completely reversed its overnight increase and opened down from the previous day’s close. While AT&T opened up slightly, it too had given back most of its initial gains. By 11:00 AM, AT&T was also in the red. When markets closed at 4:00 PM on Tuesday, Verizon was down more than 2.5 percent and AT&T was down just under 0.5 percent.

Does this mean that, in fact, theory A is the “bogus” one? Was the T-Mobile/Sprint merger decision actually a transfer of “$7.4 billion from the pockets of shareholders to the pockets of consumers,” as I suggested in my own tongue-in-cheek thread later that day? In this post, I will look at the factors that go into conducting a proper event study.  

What’s the appropriate window for a merger event study?

In a response to my thread, Philippon said, “I would argue that an event study is best done at the time of the event, not 16 hours after. Leak of merger approval 6 pm Monday. AT&T up 2 percent immediately. AT&T still up at open Tuesday. Then comes down at 10am.” I don’t disagree that “an event study is best done at the time of the event.” In this case, however, we need to consider two important details: When was the “event” exactly, and what were the conditions in the financial markets at that time?

This event did not begin and end with the leak on Monday night. The official announcement came Tuesday morning when the full text of the decision was published. This additional information answered a few questions for market participants: 

  • Were the initial news reports true?
  • Based on the text of the decision, what is the likelihood it gets reversed on appeal?
    • Wall Street: “Not all analysts are convinced this story is over just yet. In a note released immediately after the judge’s verdict, Nomura analyst Jeff Kvaal warned that ‘we expect the state AGs to appeal.’ RBC Capital analyst Jonathan Atkin noted that such an appeal, if filed, could delay closing of the merger by ‘an additional 4-5’ months — potentially delaying closure until September 2020.”
  • Did the Court impose any further remedies or conditions on the merger?

As stock traders digested all the information from the decision, Verizon and AT&T quickly went negative. There is much debate in the academic literature about the appropriate window for event studies on mergers. But the range in question is always one of days or weeks — not a couple hours in after hours markets. A recent paper using the event study methodology analyzed roughly 5,000 mergers and found abnormal returns of about positive one percent for competitors in the relevant market following a merger announcement. Notably for our purposes, this small abnormal return builds in the first few days following a merger announcement and persists for up to 30 days, as shown in the chart below:

As with the other studies the paper cites in its literature review, this particular research design included a window of multiple weeks both before and after the event occured. When analyzing the T-Mobile/Sprint merger decision, we should similarly expand the window beyond just a few hours of after hours trading.

How liquid is the after hours market?

More important than the length of the window, however, is the relative liquidity of the market during that time. The after hours market is much thinner than the regular hours market and may not reflect all available information. For some rough numbers, let’s look at data from NASDAQ. For the last five after hours trading sessions, total volume was between 80 and 100 million shares. Let’s call it 90 million on average. By contrast, the total volume for the last five regular trading hours sessions was between 2 and 2.5 billion shares. Let’s call it 2.25 billion on average. So, the regular trading hours have roughly 25 times as much liquidity as the after hours market. 

We could also look at relative liquidity for a single company as opposed to the total market. On Wednesday during regular hours (data is only available for the most recent day), 22.49 million shares of Verizon stock were traded. In after hours trading that same day, fewer than a million shares traded hands. You could change some assumptions and account for other differences in the after market and the regular market when analyzing the data above. But the conclusion remains the same: the regular market is at least an order of magnitude more liquid than the after hours market. This is incredibly important to keep in mind as we compare the after hours price changes (as reported by Philippon) to the price changes during regular trading hours.

What are Wall Street analysts saying about the decision?

To understand the fundamentals behind these stock moves, it’s useful to see what Wall Street analysts are saying about the merger decision. Prior to the ruling, analysts were already worried about Verizon’s ability to compete with the combined T-Mobile/Sprint entity in the short- and medium-term:

Last week analysts at LightShed Partners wrote that if Verizon wins most of the first available tranche of C-band spectrum, it could deploy 60 MHz in 2022 and see capacity and speed benefits starting in 2023.

“With that timeline, C-Band still does not answer the questions of what spectrum Verizon will be using for the next three years,” wrote LightShed’s Walter Piecyk and Joe Galone at the time.

Following the news of the decision, analysts were clear in delivering their own verdict on how the decision would affect Verizon:

“Verizon looks to us to be a net loser here,” wrote the MoffettNathanson team led by Craig Moffett.

…  

“Approval of the T-Mobile/Sprint deal takes not just one but two spectrum options off the table,” wrote Moffett. “Sprint is now not a seller of 2.5 GHz spectrum, and Dish is not a seller of AWS-4. More than ever, Verizon must now bet on C-band.”

…

LightShed also pegged Tuesday’s merger ruling as a negative for Verizon.

“It’s not great news for Verizon, given that it removes Sprint and Dish’s spectrum as an alternative, created a new competitor in Dish, and has empowered T-Mobile with the tools to deliver a superior network experience to consumers,” wrote LightShed.

…

In a note following news reports that the court would side with T-Mobile and Sprint, New Street analyst Johnathan Chaplin wrote, “T-Mobile will be far more disruptive once they have access to Sprint’s spectrum than they have been until now.”

However, analysts were more sanguine about AT&T’s prospects:

AT&T, though, has been busy deploying additional spectrum, both as part of its FirstNet build and to support 5G rollouts. This has seen AT&T increase its amount of deployed spectrum by almost 60%, according to Moffett, which takes “some of the pressure off to respond to New T-Mobile.”

Still, while AT&T may be in a better position on the spectrum front compared to Verizon, it faces the “same competitive dynamics,” Moffett wrote. “For AT&T, the deal is probably a net neutral.”

The quantitative evidence from the stock market seems to agree with the qualitative analysis from the Wall Street research firms. Let’s look at the five-day window of trading from Monday morning to Friday (today). Unsurprisingly, Sprint, T-Mobile, and Dish have reacted very favorably to the news:

Consistent with the Wall Street analysis, Verizon stock remains down 2.5 percent over a five-day window while AT&T has been flat over the same period:

How do you separate beta from alpha in an event study?

Philippon argued that after market trading may be more efficient because it is dominated by hedge funds and includes less “noise trading.” In my opinion, the liquidity effect likely outweighs this factor. Also, it’s unclear why we should assume “smart money” is setting the price in the after hours market but not during regular trading when hedge funds are still active. Sophisticated professional traders often make easy profits by picking off panicked retail investors who only read the headlines. When you see a wild swing in the markets that moderates over time, the wild swing is probably the noise and the moderation is probably the signal.

And, as Karl Smith noted, since the aftermarket is thin, price moves in individual stocks might reflect changes in the broader stock market (“beta”) more than changes due to new company-specific information (“alpha”). Here are the last five days for e-mini S&P 500 futures, which track the broader market and are traded after hours:

The market trended up on Monday night and was flat on Tuesday. This slightly positive macro environment means we would need to adjust the returns downward for AT&T and Verizon. Of course, this is counter to Philippon’s conjecture that the merger decision would increase their stock prices. But to be clear, these changes are so minuscule in percentage terms, this adjustment wouldn’t make much of a difference in this case.

Lastly, let’s see what we can learn from a similar historical episode in the stock market.

The parallel to the 2016 presidential election

The type of reversal we saw in AT&T and Verizon is not unprecedented. Some commenters said the pattern reminded them of the market reaction to Trump’s election in 2016:

Much like the T-Mobile/Sprint merger news, the “event” in 2016 was not a single moment in time. It began around 9 PM Tuesday night when Trump started to overperform in early state results. Over the course of the next three hours, S&P 500 futures contracts fell about 5 percent — an enormous drop in such a short period of time. If Philippon had tried to estimate the “Trump effect” in the same manner he did the T-Mobile/Sprint case, he would have concluded that a Trump presidency would reduce aggregate future profits by about 5 percent relative to a Clinton presidency.

But, as you can see in the chart above, if we widen the aperture of the event study to include the hours past midnight, the story flips. Markets started to bounce back even before Trump took the stage to make his victory speech. The themes of his speech were widely regarded as reassuring for markets, which further pared losses from earlier in the night. When regular trading hours resumed on Wednesday, the markets decided a Trump presidency would be very good for certain sectors of the economy, particularly finance, energy, biotech, and private prisons. By the end of the day, the stock market finished up about a percentage point from where it closed prior to the election — near all time highs.

Maybe this is more noise than signal?

As a few others pointed out, these relatively small moves in AT&T and Verizon (less than 3 percent in either direction) may just be noise. That’s certainly possible given the magnitude of the changes. Contra Philippon, I think the methodology in question is too weak to rule out the pro-competitive theory of the case, i.e., that the new merged entity would be a stronger competitor to take on industry leaders AT&T and Verizon. We need much more robust and varied evidence before we can call anything “bogus.” Of course, that means this event study is not sufficient to prove the pro-competitive theory of the case, either.

Olivier Blanchard, a former chief economist of the IMF, shared Philippon’s thread on Twitter and added this comment above: “The beauty of the argument. Simple hypothesis, simple test, clear conclusion.”

If only things were so simple.

In Antitrust & Competition, Financial Regulation, Google, Mergers & Acquisitions, Platforms, Telecommunications, Truth on the Market, Twitter, Wireless , , , , , , , ,
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The SHIELD Act: When Bad Economic Studies Make Bad Laws

Adam Mossoff —  15 March 2013

Earlier this month, Representatives Peter DeFazio and Jason Chaffetz picked up the gauntlet from President Obama’s comments on February 14 at a Google-sponsored Internet Q&A on Google+ that “our efforts at patent reform only went about halfway to where we need to go” and that he would like “to see if we can build some additional consensus on smarter patent laws.” So, Reps. DeFazio and Chaffetz introduced on March 1 the Saving High-tech Innovators from Egregious Legal Disputes (SHIELD) Act, which creates a “losing plaintiff patent-owner pays” litigation system for a single type of patent owner—patent licensing companies that purchase and license patents in the marketplace (and who sue infringers when infringers refuse their requests to license). To Google, to Representative DeFazio, and to others, these patent licensing companies are “patent trolls” who are destroyers of all things good—and the SHIELD Act will save us all from these dastardly “trolls” (is a troll anything but dastardly?).

As I and other scholars have pointed out, the “patent troll” moniker is really just a rhetorical epithet that lacks even an agreed-upon definition.  The term is used loosely enough that it sometimes covers and sometimes excludes universities, Thomas Edison, Elias Howe (the inventor of the lockstitch in 1843), Charles Goodyear (the inventor of vulcanized rubber in 1839), and even companies like IBM.  How can we be expected to have a reasonable discussion about patent policy when our basic terms of public discourse shift in meaning from blog to blog, article to article, speaker to speaker?  The same is true of the new term, “Patent Assertion Entities,” which sounds more neutral, but has the same problem in that it also lacks any objective definition or usage.

Setting aside this basic problem of terminology for the moment, the SHIELD Act is anything but a “smarter patent law” (to quote President Obama). Some patent scholars, like Michael Risch, have begun to point out some of the serious problems with the SHIELD Act, such as its selectively discriminatory treatment of certain types of patent-owners.  Moreover, as Professor Risch ably identifies, this legislation was so cleverly drafted to cover only a limited set of a specific type of patent-owner that it ended up being too clever. Unlike the previous version introduced last year, the 2013 SHIELD Act does not even apply to the flavor-of-the-day outrage over patent licensing companies—the owner of the podcast patent. (Although you wouldn’t know this if you read the supporters of the SHIELD Act like the EFF who falsely claim that this law will stop patent-owners like the podcast patent-owning company.)

There are many things wrong with the SHIELD Act, but one thing that I want to highlight here is that it based on a falsehood: the oft-repeated claim that two Boston University researchers have proven in a study that “patent troll suits cost American technology companies over $29 billion in 2011 alone.”  This is what Rep. DeFazio said when he introduced the SHIELD Act on March 1. This claim was repeated yesterday by House Members during a hearing on “Abusive Patent Litigation.” The claim that patent licensing companies cost American tech companies $29 billion in a single year (2011) has become gospel since this study, The Direct Costs from NPE Disputes, was released last summer on the Internet. (Another name of patent licensing companies is “Non Practicing Entity” or “NPE.”)  A Google search of “patent troll 29 billion” produces 191,000 hits. A Google search of “NPE 29 billion” produces 605,000 hits. Such is the making of conventional wisdom.

The problem with conventional wisdom is that it is usually incorrect, and the study that produced the claim of “$29 billion imposed by patent trolls” is no different. The $29 billion cost study is deeply and fundamentally flawed, as explained by two noted professors, David Schwartz and Jay Kesan, who are also highly regarded for their empirical and economic work in patent law.  In their essay, Analyzing the Role of Non-Practicing Entities in the Patent System, also released late last summer, they detailed at great length serious methodological and substantive flaws in The Direct Costs from NPE Disputes. Unfortunately, the Schwartz and Kesan essay has gone virtually unnoticed in the patent policy debates, while the $29 billion cost claim has through repetition become truth.

In the hope that at least a few more people might discover the Schwartz and Kesan essay, I will briefly summarize some of their concerns about the study that produced the $29 billion cost figure.  This is not merely an academic exercise.  Since Rep. DeFazio explicitly relied on the $29 billion cost claim to justify the SHIELD Act, and he and others keep repeating it, it’s important to know if it is true, because it’s being used to drive proposed legislation in the real world.  If patent legislation is supposed to secure innovation, then it behooves us to know if this legislation is based on actual facts. Yet, as Schwartz and Kesan explain in their essay, the $29 billion cost claim is based on a study that is fundamentally flawed in both substance and methodology.

In terms of its methodological flaws, the study supporting the $29 billion cost claim employs an incredibly broad definition of “patent troll” that covers almost every person, corporation or university that sues someone for infringing a patent that it is not currently being used to manufacture a product at that moment.  While the meaning of the “patent troll” epithet shifts depending on the commentator, reporter, blogger, or scholar who is using it, one would be extremely hard pressed to find anyone embracing this expansive usage in patent scholarship or similar commentary today.

There are several reasons why the extremely broad definition of “NPE” or “patent troll” in the study is unusual even compared to uses of this term in other commentary or studies. First, and most absurdly, this definition, by necessity, includes every university in the world that sues someone for infringing one of its patents, as universities don’t manufacture goods.  Second, it includes every individual and start-up company who plans to manufacture a patented invention, but is forced to sue an infringer-competitor who thwarted these business plans by its infringing sales in the marketplace.  Third, it includes commercial firms throughout the wide-ranging innovation industries—from high tech to biotech to traditional manufacturing—that have at least one patent among a portfolio of thousands that is not being used at the moment to manufacture a product because it may be “well outside the area in which they make products” and yet they sue infringers of this patent (the quoted language is from the study). So, according to this study, every manufacturer becomes an “NPE” or “patent troll” if it strays too far from what somebody subjectively defines as its rightful “area” of manufacturing. What company is not branded an “NPE” or “patent troll” under this definition, or will necessarily become one in the future given inevitable changes in one’s business plans or commercial activities? This is particularly true for every person or company whose only current opportunity to reap the benefit of their patented invention is to license the technology or to litigate against the infringers who refuse license offers.

So, when almost every possible patent-owning person, university, or corporation is defined as a “NPE” or “patent troll,” why are we surprised that a study that employs this virtually boundless definition concludes that they create $29 billion in litigation costs per year?  The only thing surprising is that the number isn’t even higher!

There are many other methodological flaws in the $29 billion cost study, such as its explicit assumption that patent litigation costs are “too high” without providing any comparative baseline for this conclusion.  What are the costs in other areas of litigation, such as standard commercial litigation, tort claims, or disputes over complex regulations?  We are not told.  What are the historical costs of patent litigation?  We are not told.  On what basis then can we conclude that $29 billion is “too high” or even “too low”?  We’re supposed to be impressed by a number that exists in a vacuum and that lacks any empirical context by which to evaluate it.

The $29 billion cost study also assumes that all litigation transaction costs are deadweight losses, which would mean that the entire U.S. court system is a deadweight loss according to the terms of this study.  Every lawsuit, whether a contract, tort, property, regulatory or constitutional dispute is, according to the assumption of the $29 billion cost study, a deadweight loss.  The entire U.S. court system is an inefficient cost imposed on everyone who uses it.  Really?  That’s an assumption that reduces itself to absurdity—it’s a self-imposed reductio ad absurdum!

In addition to the methodological problems, there are also serious concerns about the trustworthiness and quality of the actual data used to reach the $29 billion claim in the study.  All studies rely on data, and in this case, the $29 billion study used data from a secret survey done by RPX of its customers.  For those who don’t know, RPX’s business model is to defend companies against these so-called “patent trolls.”  So, a company whose business model is predicated on hyping the threat of “patent trolls” does a secret survey of its paying customers, and it is now known that RPX informed its customers in the survey that their answers would be used to lobby for changes in the patent laws.

As every reputable economist or statistician will tell you, such conditions encourage exaggeration and bias in a data sample by motivating participation among those who support changes to the patent law.  Such a problem even has a formal name in economic studies: self-selection bias.  But one doesn’t need to be an economist or statistician to be able to see the problems in relying on the RPX data to conclude that NPEs cost $29 billion per year. As the classic adage goes, “Something is rotten in the state of Denmark.”

Even worse, as I noted above, the RPX survey was confidential.  RPX has continued to invoke “client confidences” in refusing to disclose its actual customer survey or the resulting data, which means that the data underlying the $29 billion claim is completely unknown and unverifiable for anyone who reads the study.  Don’t worry, the researchers have told us in a footnote in the study, they looked at the data and confirmed it is good.  Again, it doesn’t take economic or statistical training to know that something is not right here. Another classic cliché comes to mind at this point: “it’s not the crime, it’s the cover-up.”

In fact, keeping data secret in a published study violates well-established and longstanding norms in all scientific research that data should always be made available for testing and verification by third parties.  No peer-reviewed medical or scientific journal would publish a study based on a secret data set in which the researchers have told us that we should simply trust them that the data is accurate.  Its use of secret data probably explains why the $29 billion study has not yet appeared in a peer-reviewed journal, and, if economics has any claim to being an actual science, this study never will.  If a study does not meet basic scientific standards for verifying data, then why are Reps. DeFazio and Chaffetz relying on it to propose national legislation that directly impacts the patent system and future innovation?  If heads-in-the-clouds academics would know to reject such a study as based on unverifiable, likely biased claptrap, then why are our elected officials embracing it to create real-world legal rules?

And, to continue our running theme of classic clichés, there’s the rub. The more one looks at the actual legal requirements of the SHIELD Act, the more, in the words of Professor Risch, one is left “scratching one’s head” in bewilderment.  The more one looks at the supporting studies and arguments in favor of the SHIELD Act, the more one is left, in the words of Professor Risch, “scratching one’s head.”  The more and more one thinks about the SHIELD Act, the more one realizes what it is—legislation that has been crafted at the behest of the politically powerful (such as an Internet company who can get the President to do a special appearance on its own social media website) to have the government eliminate a smaller, publicly reviled, and less politically-connected group.

In short, people may have legitimate complaints about the ways in which the court system in the U.S. generally has problems.  Commentators and Congresspersons could even consider revising the general legal rules governing patent ligtiation for all plaintiffs and defendants to make the ligitation system work better or more efficiently (by some established metric).   Professor Risch has done exactly this in a recent Wired op-ed.  But it’s time to call a spade a spade: the SHIELD Act is a classic example of rent-seeking, discriminatory legislation.

In Google, Intellectual Property, Law & Economics, Patent, Platforms, Regulation , , , , , , , , , , , , , , , , , , , ,
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