というNBER論文が上がっている。原題は「A Return Based Measure of Firm Quality」で、著者はRavi Jagannathan(ノースウエスタン大)、Yang Zhang(オプション・クリアリング・コーポレーション)。

We show that superior performance relative to peers during stressful times identifies higher quality firms as measured by conventional historical financial statement based measures as well as default probability measures. Quality measured this way is persistent, but different from price momentum. Further, a managed portfolio that takes a long position in top quintile (Stable) firms and a short position in bottom quintile (Vulnerable) firms earns superior risk adjusted returns in excess of the risk-free rate. The portfolio has an annualized Fama and French three-factor alpha of 5.2% (t=5.04) and a five-factor alpha of 3.3% (t=3.38)


というNBER論文をサマーズらが上げている(H/T アレックス・タバロック)。原題は「A Calculation of the Social Returns to Innovation」で、著者はBenjamin F. Jones(ノースウエスタン大)、Lawrence H. Summers(ハーバード大)。

A simple social returns calculation can proceed as follows. Let income per capita be y, innovation investment per capita be x, and the discount rate be r. If a year's worth of innovation investments creates a g percent increase in productivity, then the ratio of benefits to costs is:
𝜌 = (𝑔/𝑟) / (𝑥/𝑦)
The key idea here, as in endogenous growth theory, is that, by investing a GDP share 𝑥/𝑦 in innovation today (i.e., once), we permanently raise productivity in the economy by 𝑔 percent, the present value of which is 𝑔/𝑟. Notably, this approach suggests that the average social returns to innovation may be enormous. For example, if we take an R&D investment orientation, with the R&D share of GDP at its usual level in the U.S., 𝑥/𝑦 ≈ 2.7%, and let these investments drive productivity growth, then we have 𝑔 ≈ 1.8%. Standard discount rates then imply that 1$ of R&D investment today on average creates over $10 of economy-wide benefits in today’s dollars. This return is extremely large, but it follows from the basic mechanics of growth, as understood in advanced economies. That is, a permanent gain in living standards from a seemingly small investment in innovation will, by the above logic, tend to suggest enormous returns.
𝜌 = (𝑔/𝑟) / (𝑥/𝑦)
ここで鍵となる考え方は、内生的成長理論におけるのと同様、GDP比にしてx/yのイノベーション投資を今日行う(即ち一回だけ行う)ことにより、我々は経済の生産性を恒久的にg%引き上げ、その現在価値はg/rとなる、ということである。注目すべきことに、この手法が示唆するイノベーションへの平均の社会的リターンは非常に大きなものとなる。例えば、研究開発投資を用いることにすれば、米国のGDPの研究開発費比率の通常水準からx/y ≈ 2.7%となり、その投資が生産性成長をもたらすとすれば、𝑔 ≈ 1.8%となる。すると標準的な割引率から、今日の1ドルの研究開発投資が、現在のドルにして平均10ドル以上の便益を経済全体にもたらすことになる。このリターンは非常に大きいが、先進国経済で理解されているところの成長の基本的なメカニズムから得られるものである。即ち、表面的には少額のイノベーション投資がもたらす生活水準の恒久的な利得は、上述の論理によって、非常に大きなリターンを示すものとなる傾向がある。


  1. 波及効果
    • 研究開発から利益が上がるのには時間が掛かり、そのため便益の達成時期が遅れ、現在価値が下がる。
  2. 資本深化の役割
    • 生産性利得には資本深化が一部貢献している。また、それと関連する話として、研究開発投資の価値が新たな種類の固定資産への投資によってのみ実現される場合、資本に体化される技術変化の役割も考える必要がある。
  3. 研究開発以外の役割
    • 起業や実践的学習など、正式な研究開発以外の活動によって生産性成長が起きる可能性。


  1. インフレバイアス
    • インフレバイアスにより、GDP実質成長率において、製品の改良や新製品の開発による利得を過小評価。
  2. 医療
    • 医療は研究開発投資の主要な対象であり、大きな社会的リターンをもたらすものであるものの、死亡率や疾病率は一人当たりGDP指標ではうまく捉えきれない。
  3. 国際的波及効果
    • 先端的な経済で行われたイノベーション投資により世界中の経済が恩恵を受ける。



アセモグルのNBER論文をもう一丁。以下はDaron Acemoglu(MIT)、Giuseppe De Feo(レスター大)、Giacomo De Luca(ボゼン・ボルツァーノ自由大)、Gianluca Russo(ポンペウ・ファブラ大)による表題の論文ungated版、原題は「War, Socialism and the Rise of Fascism: An Empirical Exploration」)の要旨。

The recent ascent of right-wing populist movements in many countries has rekindled interest in understanding the causes of the rise of Fascism in inter-war years. In this paper, we argue that there was a strong link between the surge of support for the Socialist Party after World War I (WWI) and the subsequent emergence of Fascism in Italy. We first develop a source of variation in Socialist support across Italian municipalities in the 1919 election based on war casualties from the area. We show that these casualties are unrelated to a battery of political, economic and social variables before the war and had a major impact on Socialist support (partly because the Socialists were the main anti-war political movement). Our main result is that this boost to Socialist support (that is “exogenous” to the prior political leaning of the municipality) led to greater local Fascist activity as measured by local party branches and Fascist political violence (squadrismo), and to significantly larger vote share of the Fascist Party in the 1924 election. We document that the increase in the vote share of the Fascist Party was not at the expense of the Socialist Party and instead came from right-wing parties, thus supporting our interpretation that center-right and right-wing voters coalesced around the Fascist Party because of the “red scare”. We also show that the veterans did not consistently support the Fascist Party and there is no evidence for greater nationalist sentiment in areas with more casualties. We provide evidence that landowner associations and greater presence of local elites played an important role in the rise of Fascism. Finally, we find greater likelihood of Jewish deportations in 1943-45 and lower vote share for Christian Democrats after World War II in areas with greater early Fascist activity.


というNBER論文をアセモグルらが上げているungated版)。原題は「Institutional Change and Institutional Persistence」で、著者はDaron Acemoglu(MIT)、Georgy Egorov(ノースウエスタン大)、Konstantin Sonin(シカゴ大)。

In this essay, we provide a simple conceptual framework to elucidate the forces that lead to institutional persistence and change. Our framework is based on a dynamic game between different groups, who care both about current policies and institutions and future policies, which are themselves determined by current institutional choices, and clarifies the forces that lead to the most extreme form of institutional persistence (“institutional stasis”) and the potential drivers of institutional change. We further study the strategic stability of institutions, which arises when institutions persist because of fear of subsequent, less beneficial changes that would follow initial reforms. More importantly, we emphasize that, despite the popularity of ideas based on institutional stasis in the economics and political science literatures, most institutions are in a constant state of flux, but their trajectory may still be shaped by past institutional choices, thus exhibiting “path-dependent change”, so that initial conditions determine both the subsequent trajectories of institutions and how they respond to shocks. We conclude the essay by discussing how institutions can be designed to bolster stability, the relationship between social mobility and institutions, and the interplay between culture and institutions.

集団免疫論者は正しかったのか? スペインの事例


After a relatively calm early summer, Spain has been at the forefront of a second wave of COVID-19. In Spain’s hardest hit provinces from the first wave of the pandemic the proportion of the population with antibodies to SARS-CoV-2 (the virus that causes COVID-19) is 10–15% or higher.
If the model(s) with the lowest projections for herd immunity threshold(s )(HIT) are correct, then by the end of the May many provinces in Spain would have been very close to achieving herd immunity. During the second wave, the areas at or close to HIT would be expected to experience much slower and lower growth of cases.
Did this happen? Were Spain’s hardest hit provinces in the spring spared in the second wave?
実際にそうなっただろうか? スペインで春に打撃が最も深刻だった県は第2波を免れただろうか?





In response, many of the herd immunity theorists strike back and ask “where are the deaths“? But that is not the right question for testing herd immunity claims. Those claims were about transmission slowing down, and those claims should be true about Covid-19 cases whether or not more people are surviving in the hospital. (Imagine for instance a perfect antiviral that saved everybody — would that mean herd immunity was true a priori? Nope.)
Another claim from some of the less careful herd immunity theorists is that cases are rising again because testing is rising. That doesn’t seem to explain observed patterns in Israel, Spain, or England, where in all instances actual Covid cases are rising above and beyond what is going on with testing policy, and by some considerable margin. It probably does explain some parts of America, however.
It is very likely that death rates will be much lower this time around, because of better procedures, younger victims, lower doses, and possible (speculative!) variolation through mask use over time, exposing people to lower doses repeatedly and boosting their immune responses.
これに対して、多くの集団免疫論者は反撃し、「死亡率はどうなんだ?」と言う。しかし集団免疫の主張を検証する上でこれは正しい質問ではない。彼らの主張は感染が鈍化することであり、病院で生き残る人々が増えるかどうかに関係なくその主張はCovid-19感染者数について成立するはずのものである(例えば完全な抗ウイルス薬によって全員が救われたと想像してみよう――そのことから集団免疫が正しいと推論できるだろうか? いいや、できない)。


というNBER論文が上がっているungated(SSRN)版)。原題は「Man vs. Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases」で、著者はJules H. van Binsbergen(ペンシルベニア大)、Xiao Han(エジンバラ大)、Alejandro Lopez-Lira(BIノルウェービジネススクール)。

We use machine learning to construct a statistically optimal and unbiased benchmark for firms' earnings expectations. We show that analyst expectations are on average biased upwards, and that this bias exhibits substantial time-series and cross-sectional variation. On average, the bias increases in the forecast horizon, and analysts revise their expectations downwards as earnings announcement dates approach. We find that analysts' biases are associated with negative cross-sectional return predictability, and the short legs of many anomalies consist of firms for which the analysts' forecasts are excessively optimistic relative to our benchmark. Managers of companies with the greatest upward biased earnings forecasts are more likely to issue stocks.

*1:ungated版の本文では、「we break stocks into 10 decile portfolios based on the anomaly score. The long legs are defined as the stocks in the top decile portfolio. The short legs are defined as the stocks in the bottom decile portfolio.」と定義されている。investopiaも参照。