というIMFワーキングペーパーが出ている(H/T Edward Hugh)。原題は「Is Japan’s Population Aging Deflationary?」で、著者はDerek Anderson、Dennis P. J. Botman、Ben Hunt 。


Japan has the most rapidly aging population in the world. This affects growth and fiscal sustainability, but the potential impact on inflation has been studied less. We use the IMF’s Global Integrated Fiscal and Monetary Model (GIMF) and find substantial deflationary pressures from aging, mainly from declining growth and falling land prices. Dissaving by the elderly makes matters worse as it leads to real exchange rate appreciation from the repatriation of foreign assets. The deflationary effects from aging are magnified by the large fiscal consolidation need. Many of these factors will beset other advanced countries as well, but we find that deflation risk from aging is not inevitable as ambitious structural reforms and an aggressive monetary policy reaction can provide the offset.






という趣旨の5年前の論文がなぜかEconomist's Viewのサイドバーの「Monetary Economics Working Papers」の欄に浮上していた。原題は「The Macroeconomic Effects of Losing Autonomous Monetary Policy after the Euro Adoption in Poland」で、著者はMichal GradzewiczとKrzysztof Makarski(いずれもポーランド国立銀行)。


There are many issues associated with the Eurozone accession of Poland. The goal of this paper is to analyse one, but very important aspect, namely - the macroeconomic impact of the loss of autonomous monetary policy. In order to answer this question, we build a two country DSGE model with sticky prices. We begin by evaluating the performance of our model. Next, we investigate how joining the Eurozone will affect the business cycle behaviour of the main macroeconomic variables in Poland. We find that the Euro adoption will have a noticeable impact on the Polish economic fluctuations. In particular, the volatility of domestic output increases and the volatility of inflation decreases. Also, in order to quantify the effect of the Euro adoption, we compute the welfare effect of this monetary policy change. Our findings suggest that the welfare cost is not large.






昨日エントリで紹介したワルドマンの考察に内容的に近い表題のNBER論文をタイラー・コーエンが紹介している論文の原題は「…and the Cross-Section of Expected Returns」で*1、著者はCampbell R. Harvey(デューク大)、Yan Liu(テキサスA&M大)、Heqing Zhu(オクラホマ大)。


At least 316 factors have been tested to explain the cross-section of expected returns. Most of these factors have been proposed over the last ten years. Indeed, Cochrane (2011) refers to this as “a zoo of new factors”. Our paper argues that it is a serious mistake to use the usual statistical significance cutoffs (e.g., a t-ratio exceeding 2.0) in asset pricing tests. Given the plethora of factors and the inevitable data mining, many of the historically discovered factors would be deemed “significant” by chance.

Our paper presents three conventional multiple testing frameworks and proposes a new one that particularly suits research in financial economics. While these frameworks differ in their assumptions, they are consistent in their conclusions. We argue that a newly discovered factor today should have a t-ratio that exceeds 3.0. We provide a time-series of recommended “cutoffs” from the first empirical test in 1967 through to present day. Many published factors fail to exceed our recommended cutoffs.

While a ratio of 3.0 (which corresponds to a p-value of 0.27%) seems like a very high hurdle, we also argue that there are good reasons to expect that 3.0 is too low. First, we only count factors that are published in prominent journals and we sample only a small fraction of the working papers. Second, there are surely many factors that were tried by empiricists, failed, and never made it to publication or even a working paper. Indeed, the culture in financial economics is to focus on the discovery of new factors. In contrast to other fields such as medical science, it is rare to publish replication studies of existing factors. Given that our count of 316 tested factors is surely too low, this means the t-ratio cutoff is likely even higher.








*3:原注:In astronomy and physics, even higher threshold t-ratios are often used to control for testing multiplicity. For instance, the high profile discovery of Higgs Boson has a t-ratio of more than 5 (p-value less than 0.0001%). See ATLAS Collaboration (2012), CMS Collaboration (2012), and Harvey and Liu (2014c).
天文学物理学では、多重性の検定のコントロールのために、さらに大きなt値の閾値が使われることが多い。例えば、有名なヒッグスボソンの発見の際にはt値は5を超えた(p値は0.0001%未満)。ATLAS共同研究(2012)(訳注:ここ)、CMS共同研究(2012)(訳注:ここ)、Harvey and Liu (2014c)(訳注:ここ)参照。




ここで紹介した2010年のバーナンキ宛書簡の署名者の一人であるAQRキャピタルのCliff Asness――アルファベット順なので筆頭署名者になっている――が、クルーグマンらの批判に対し、ドイツ人真珠湾を爆撃した時のように*1まだ決着は付いちゃいねえ、と猛然と反論した。データによって間違いが明らかになったモデルに執着するAsnessの心理を不思議がったデロングのエントリをMark Thomaが引用し、以下のように書いている

There's a version of this in econometrics, i.e. you know the model is correct, you are just having trouble finding evidence for it. It goes as follows. You are testing a theory you came up with, but the data are uncooperative and say you are wrong. But instead of accepting that, you tell yourself "My theory is right, I just haven't found the right econometric specification yet. I need to add variables, remove variables, take a log, add an interaction, square a term, do a different correction for misspecification, try a different sample period, etc., etc., etc." Then, after finally digging out that one specification of the econometric model that confirms your hypothesis, you declare victory, write it up, and send it off (somehow never mentioning the intense specification mining that produced the result).

Too much econometric work proceeds along these lines. Not quite this blatantly, but that is, in effect, what happens in too many cases. I think it is often best to think of econometric results as the best case the researcher could make for a particular theory rather than a true test of the model.





The first implication of this practice is common knowledge: "statistical significance" never means what it claims to mean. When an effect is claimed to be statistically significant — p < 0.05 — that does not in fact mean that there is only a 1 in 20 chance that the effect would be observed by chance. That inference would be valid only if the researcher had estimated a unique, correctly specified model. If you are trying out tens or hundreds of models (which is not far-fetched, given the combinatorics that apply with even a few candidate variables), even if your data is pure noise then you are likely to generate statistically significant results. Statistical significance is a conventionally agreed low bar. If you can't overcome even that after all your exploring, you don't have much of a case. But a determined researcher need rarely be deterred.





アニマル・ハウス スペシャル・エディション [DVD]

アニマル・ハウス スペシャル・エディション [DVD]




The Everyday Economistブログを運営するジョシュ・ヘンドリクソン(Josh Hendricksonが)、Peter Howittの1992年論文*1を参照しつつ、ジョン・コクランらフィッシャー式逆さ眼鏡派/新フィッシャー派*2のニューケインジアンモデル解釈は正しい、と論じている



   y_t = -¥sigma (i_t - E_t ¥pi_{t+1} - r^*)


   ¥pi_t = E_t ¥pi_{t+1} + ¥phi y_t

ここでyは生産ギャップ、πはインフレ率、iは名目金利、rは自然利子率、Eは期待演算子、σとφはパラメータである。 中銀が金利を固定し、π*を望ましいインフレ率と考えるならば、合理的期待均衡において

   ¥pi_t = E_t ¥pi_{t+1} = ¥pi^*


   ¥pi_t = i_t - r^* = ¥pi^*




Thus, we are left with an unfortunate conclusion. The New Keynesian discussion of policy doesn’t fit with the New Keynesian model of policy. Thus, either the model is wrong and the discussion is correct or the discussion is wrong and the model is correct. But consider the implications. Much of policy advice that is given today is informed by this New Keynesian discussion. If the model is correct, then this advice is actually wrong. However, if the model is wrong and the discussion is correct, then the New Keynesians are correct in spite of themselves. In other words, they still have no idea how policy is working because their model is wrong. Either way we are left with the conclusion that New Keynesians have no idea how policy works.



コメント欄では、あるコメンターが冒頭部の以下の文章を「This is a great sentence」として激賞している。

However, I would submit that John Cochrane understands the New Keynesian Model better than the New Keynesians and that if his prediction is wrong, then this has more to do with how little New Keynesian models teach us about monetary policy.



また、Nick Roweが以下のようにコメントしている。

Good post Josh. But I would say it a little differently. The New Keynesians have an equilibrium model, but a disequilibrium story of what keeps us on that equilibrium path.



*1cf. ここ

*2cf. ここ

*3cf. ここで紹介したRoweのエントリ。