Another terrible graph from Nature… With vertical bars meaning nothing. Nothing more than the list of three values and both confidence intervals. But the associated article is quite interesting in investigating the difficulties in assessing the number of deaths due to COVID-19, when official death statistics are (almost) as shaky as the official COVID-19 deaths. Even in countries with sound mortality statistics and trustworthy official statistics institutes. This article opposes prediction models run by the Institute for Health Metrics and Evaluation and The Economist. The later being a machine-learning prediction procedure based on a large number of covariates. Without looking under the hood, it is unclear to me how poor entries across the array of covariates can be corrected to return a meaningful prediction. It is also striking that the model predicts much less excess deaths than those due to COVID-19 in a developed country like Japan. Survey methods are briefly mentioned at the end of the article, with interesting attempts to use satellite images of burial grounds, but no further techniques like capture-recapture or record linkage and entity resolution.
Archive for Jeune economist
how to count excess deaths?
Posted in Books, Kids, pictures, Statistics with tags bad graph, capture-recapture, COVID-19, death certificate, entity resolution, excess mortality, image analysis, infographics, INSEE, Japan, Jeune economist, Nature, official statistics, record linkage, satellite, The Economist on February 17, 2022 by xi'anPrix Le Monde Jeune Economiste 2011
Posted in Books, University life with tags Jeune economist, Le Monde, Nassim Taleb, The Black Swan, Xavier Gabaix on May 29, 2011 by xi'anEach year, Le Monde nominates a French economist for its Jeune Economiste Prize. The past winners are
- 2000 Agnès Bénassy-Quéré et Bruno Amable
- 2001 Pierre Cahuc
- 2002 Philippe Martin et Thomas Piketty
- 2003 Pierre-Cyrille Hautcœur
- 2004 David Martimort
- 2005 Esther Duflo et Elyès Jouini
- 2006 Thierry Mayer et Étienne Wasmer
- 2007 David Thesmar
- 2008 Pierre-Olivier Gourinchas
- 2009 Yann Algan et Thomas Philippon
- 2010 Emmanuel Saez
(Some of those recipients are or were researchers at CREST. And Elyès is my colleague in Paris-Dauphine. When he is not minister in Tunisia!) The 2011 winner is Xavier Gabaix, who is professor of economics at NUY. I know nothing of his research and of its impact on Economics, nor do I want to to criticise the 2011 prize in any respect, however in a fairly bland and uninformative interview with Le Monde, Xavier Gabaix focused on the Zipf laws (connected with the Benford law I mentioned a while ago about the Iranian elections):
Pour la théorie économique classique, les phénomènes économiques se distribuent selon une courbe de Gauss (en cloche), et la modélisation raisonne généralement à partir de moyennes, d’agrégats. Or, la recherche a montré que, dans des domaines très variés, la distribution des objets, par exemple par rang de taille pour les villes ou par fréquence d’occurrence pour les mots d’un texte, obéit à des lois mathématiques comme les lois de Zipf, du nom du linguiste qui les a mises en évidence. Dans un article de Nature paru en 2003 et écrit avec des physiciens, j’ai montré que la fréquence des baisses boursières atteignant certains seuils (10 %, 20 %, 30 %) obéissait à la même loi mathématique que la fréquence des séismes… L’observation du volume de transactions boursières, de la taille des firmes, des évolutions de la croissance, permet également de déceler de telles lois de distribution.
which google-translates as
In classical economic theory, economic phenomena are distributed according to a Gaussian (bell) distribution, and modeling reasons usually based on averages and aggregates. However, research has shown that in various fields, the distribution of objects, for example in the size ranks of cities or in the frequency of occurrence of words in a text, obeys mathematical laws such as the Zipf laws, named after the linguist who has identified them. In a Nature paper published in 2003 and written with physicists, I showed that the frequency of stock market declines reaching certain thresholds (10%, 20%, 30%) obey the same mathematical law as the frequency of earthquakes .. . The observation of the volume of stock transactions, the size of firms, changes in growth, can also identify such distributions.
This somehow reminds me of the criticisms on the normal/Gaussian distribution in Nassim Taleb’s (outrageous) Black Swan. I would think the same type of criticism applies here: The interview mentions the fact that a few actors have a considerable impact on financial markets. This kind of observation applies to an extreme value phenomenon. hence a particularly-difficult-to-estimate statistical problem. Especially given the lack of stationarity on those financial markets…