1. A Brief Introduction to the Basics of Game Theory by Matthew O. Jackson (Stanford University – Department of Economics)

2. Who Falls for Fake News? The Roles of Analytic Thinking, Motivated Reasoning, Political Ideology, and Bullshit Receptivity by Gordon Pennycook (Yale University) and David Rand (Yale University)

Like many others, we were both fascinated and disturbed by the phenomenon of fake news (entirely fabricated stories presented in the format of news articles) that gained prominence during the 2016 US Presidential Election. In response, we have initiated a research program aimed at understanding what affects peoples’ belief in fake news, and what can be done to improve the ability to differentiate fake from real (what we dub “Media truth discernment”). In a previous paper posted on SSRN, Prior Exposure Increases Perceived Accuracy of Fake News, we showed that just reading a fake news headline made people subsequently more likely to believe it – even if the headline was flagged as “Disputed by 3rd party fact-checkers,” ran counter to the subject’s political orientation, or was not even explicitly remembered by the subject.

In the current paper, Who Falls for Fake News? The Roles of Analytic Thinking, Motivated Reasoning, Political Ideology, and Bullshit Receptivity, we examined the cognitive profile of people who are better versus worse at media truth discernment. A common, and very pessimistic, argument is that people believe politicized fake news because they want to – that is, people use processes such as rationalization to convince themselves of the truth of stories which fit their political worldview (often called “motivated reasoning” or “cultural cognition”). Surprisingly, however, our results do not support this account, and are in a sense more optimistic – we found that people who engaged in more analytic thinking (as measured by the Cognitive Reflection Test, a set of math problems with intuitively compelling but incorrect answers) were better at discerning fake from real, even for headlines that aligned with their political ideology. If anything, analytic thinkers were even better at discounting fake news that they were politically aligned with. That is not to say, however, that political ideology played no role: people were on average more likely to believe politically aligned fake news headlines. Furthermore, Trump supporters were overall worse at differentiating fake from real (even for politically neutral headlines) – a result that was, at least in part, accounted for by Trump supporters being less likely to engage in analytic thinking. We also found that people who tended to think that randomly generated sentences are profound (i.e. that score highly on the “pseudo-profound bullshit receptivity” scale of Pennycook et al., 2015) were also more likely to believe fake news – which, again, was in part accounted for by less analytic thinking. Finally, we assessed the impact of showing versus hiding the website that each headlines came from. To our surprise, we found no effect on judgments of accuracy. We hope that the results of these studies, as well as those of other studies we are currently conducting, will help guide policy makers in their efforts to reduce belief in blatantly false information. – David G. Rand

3. Intellectual Property in the New Technological Age: 2017 – Chapters 1 and 2 by Peter Menell (University of California, Berkeley – School of Law) and Mark Lemley (Stanford Law School) and Robert Merges (University of California, Berkeley – School of Law)

4. The Impact of E-Visits on Visit Frequencies and Patient Health: Evidence from Primary Care by Hessam Bavafa (University of Wisconsin-Madison) and Lorin Hitt (University of Pennsylvania – Operations & Information Management Department) and Christian Terwiesch (University of Pennsylvania – Operations & Information Management Department)

5. How to Read a Legal Opinion: A Guide for New Law Students by Orin Kerr (The George Washington University Law School)

Like a lot of papers with tons of downloads, this paper has an audience outside academic specialists. It’s a paper for new law students on how to prepare to start law school.  With around 40,000 new law students entering law schools every fall, it draws a lot of downloads every August.  I’ve been told that a lot of law schools assign it as part of the first week of reading, too.  Either way, it is by far my most read article. Go figure. – Orin Kerr

1. Artificial Intelligence Policy: A Roadmap by Ryan Calo (University of Washington – School of Law)

2. How to Read a Legal Opinion: A Guide for New Law Students by Orin Kerr (The George Washington University Law School)

Like a lot of papers with tons of downloads, this paper has an audience outside academic specialists. It’s a paper for new law students on how to prepare to start law school.  With around 40,000 new law students entering law schools every fall, it draws a lot of downloads every August.  I’ve been told that a lot of law schools assign it as part of the first week of reading, too.  Either way, it is by far my most read article. Go figure. – Orin Kerr

3. A Brief Introduction to the Basics of Game Theory by Matthew O. Jackson (Stanford University – Department of Economics)

4. A Quantitative Approach to Tactical Asset Allocation by Meb Faber (Cambria Investment Management)

1. How to Read a Legal Opinion: A Guide for New Law Students by Orin Kerr (The George Washington University Law School)

2. Squaring Venture Capital Valuations with Reality by Will Gornall (University of British Columbia (UBC) – Sauder School of Business) and Ilya Strebulaev (Stanford University – Graduate School of Business)

Uber, AirBnB, SpaceX, and other private venture capital-backed (VC-backed) companies have delivered spectacular growth to their employees, venture capitalists, and entrepreneurs. Despite this, the true value of shares in these private companies has remained a black box. Our paper develops a financial model to estimate the fair value of venture capital-backed companies and of each type of security these companies issue. We estimate true values for more than 116 U.S. unicorns (VC-backed companies with a reported valuation above $1 billion) by applying our model to their most recent financing rounds using data from legal filings. We find that the average unicorn reports a valuation 49% above its fair value, with common shares overvalued by 59%. Almost one half (53 out of 116) of unicorns see their value fall below the $1 billion threshold when their valuation is recalculated and 11 unicorns are overvalued by more than 100%. Overvaluation arises because the reported valuations assume all of a company’s shares have the same price as the most recently issued shares. In practice, these most recently issued shares almost always have better cash flow rights than the previously issued shares. Equating their prices therefore significantly inflates valuations. Specifically, we find 53% of unicorns have given their most recent investors either a return guarantees in IPO (14%), the ability to block IPOs that do not return most of their investment (20%), seniority over all other investors (31%), or other important terms. Better knowledge of these terms and their impact on valuation will help entrepreneurs, employees, and venture make better decisions. – Will Gornall

The idea for this piece started back when I read Charles Dunlap’s 1992 piece “Reflections on the Coup of 2012,” which was published in Parameters, the journal of the Army War College.  Ideas often percolate with me for a long time (my Ham Sandwich Nation piece also went  20+ years from conception to execution) and this one stayed in the back of my mind until I decided to start writing it in 2015.  At the time, I had no idea that all the coup-talk that surrounded (and followed) Donald Trump’s election to the White House was coming, and just saw it as an interesting example of how structure and relationship in the Constitution can take some issues largely off the table, often without people even realizing it.  Research was fun because it required me to learn a lot more about how to plan and execute a coup d’etat than most law professors ever learn.

I do think the piece also offers a useful warning about excessive constitutional tinkering.  If the Constitution makes a military coup fairly unlikely without most people even noticing that it does so, it may well be preventing other bad things from happening in a similar unnoticed fashion.  It’s possible that America’s comparatively long run of peace and prosperity has something to do with constitutional design, and isn’t just a result of the superior virtue of the American polity.  At least it’s a reason why we should think twice before making substantial changes. – Glenn Reynolds

1. Battlefield Casualties and Ballot Box Defeat: Did the Bush-Obama Wars Cost Clinton the White House? by Douglas Kriner (Boston University – Department of Political Science) and Francis Shen (University of Minnesota Law School)

We have been writing about the causes and political consequences of inequality in military sacrifice for more than a decade. But the issue typically gets overlooked, and this was the case with analysis of the 2016 presidential election. Few commentators argue that antiwar sentiment was a key to Trump’s victory. But we think that’s a credible argument, and this paper lays out the data to support it.

As we write at the start of the paper: Imagine a country continuously at war for nearly two decades. Imagine that the wars were supported by both Democratic and Republican presidents. Continue to imagine that the country fighting these wars relied only on a small group of citizens—a group so small that those who served in theater constituted less than 1 percent of the nation’s population, while those who died or were wounded in battle comprised far less than 1/10th of 1 percent of the nation’s population.  And finally, imagine that these soldiers, their families, friends, and neighbors felt that their sacrifice and needs had long been ignored by politicians in Washington. Would voters in these hard hit communities get angry? And would they seize an opportunity to express that anger at both political parties? We think the answer is yes. And the proof is the 2016 victory of Donald J. Trump.

Trump’s campaign rhetoric was well-crafted to appeal to voters in communities that have borne the brunt of fifteen years of fighting.  He pledged both to rebuild the military, and to be more restrained in its use – to avoid the “stupid” wars of his predecessors.   Our analysis suggests that this gambit may have tilted the election.  Even controlling in a statistical model for many other alternative explanations, we find that there is a significant and meaningful relationship between a community’s rate of military sacrifice and its support for Trump. Our statistical model suggests that if three states key to Trump’s victory – Pennsylvania, Michigan, and Wisconsin – had suffered even a modestly lower casualty rate, all three could have flipped from red to blue and sent Hillary Clinton to the White House. We argue that politicians from both parties would do well to more directly recognize and address the needs of those communities whose young women and men are making the ultimate sacrifice for the country. – Francis Shen

2. A Brief Introduction to the Basics of Game Theory by Matthew O. Jackson (Stanford University – Department of Economics)

3. Improving U.S. Stock Return Forecasts: A ‘Fair-Value’ Cape Approach by Joseph Davis (The Vanguard Group) and Roger Aliaga-Diaz (The Vanguard Group, Inc.) and Harshdeep Ahluwalia (The Vanguard Group, Inc.) and Ravi Tolani (The Vanguard Group, Inc.)

The cyclically-adjusted P/E (or, CAPE) ratio is arguably the most widely-followed metric in the investment profession to judge whether or not a stock market is fairly valued. Yet the accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. This deterioration has coincided with the secular rise in the CAPE ratio over the past three decades.

In this paper, we show that the issue is not the CAPE ratio, but CAPE regressions that assume it reverts mechanically to its long-run average. Our approach conditions mean reversion in the CAPE ratio on the state of the economy, as measured by real (not nominal) bond yields, inflation, and financial volatility. In our framework, lower real bond yields imply lower real earnings yields and a higher “fair-value CAPE ratio, all else equal. Our approach reduces out-of-sample forecast errors of future 10-year-ahead U.S. stock returns by as much as 50%.

Overall, we encourage investment professionals to adopt our straightforward framework when forecasting stock returns for strategic asset allocation. Our fair-value approach can be estimated in real-time using standard software, it does not involve “look-ahead bias,” and, for the U.S. stock market, it only requires the variables in the CAPE ratio data file conveniently provided by Professor Robert Shiller’s website. As of June 2017, our model projects a guarded, lower-than-historical return on U.S. stocks of approximately 4.9% over the coming decade. This muted forecast for U.S. stock returns is not simply because the CAPE ratio is above its long-run mean. – Joeseph Davis

4. A Stakeholder Approach to Strategic Management by R. Freeman (University of Virginia – Darden School of Business) and John McVea (University of Virginia – Darden School of Business)

5. A Century of Evidence on Trend-Following Investing by Brian Hurst (AQR Capital Management, LLC) and Yao Hua Ooi (AQR Capital Management, LLC) and Lasse Pedersen (AQR Capital Management, LLC)