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
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
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)