# Bertrand Russells Brief an Gottlob Frege, in dem er die 'Russellsche Antinomie' beschreibt (1902)

Staatsbibliothek zu Berlin, Preußischer Kulturbesitz

Read MoreA blog about: philosophy, economics, altruism, anything not on this list

Staatsbibliothek zu Berlin, Preußischer Kulturbesitz

Read MoreValerio Filoso (2013) writes:

Read MoreMost econometrics textbooks limit themselves to providing the formula for the vector of the type

Although compact and easy to remember, this formulation is a sort black box, since it hardly reveals anything about what really happens during the estimation of a multivariate OLS model. Furthermore, the link between the and the moments of the data distribution disappear buried in the intricacies of matrix algebra. Luckily, an enlightening interpretation of the s in the multivariate case exists and has relevant interpreting power. It was originally formulated more than seventy years ago by Frisch and Waugh (1933), revived by Lovell (1963), and recently brought to a new life by Angrist and Pischke (2009) under the catchy phrase regression anatomy. According to this result, given a model with K independent variables, the coefficient for the k-th variable can be written as

where is the residual obtained by regressing on all remaining independent variables.

The result is striking since it establishes the possibility of breaking a multivariate model with independent variables into bivariate models and also sheds light into the machinery of multivariate OLS. This property of OLS does not depend on the underlying Data Generating Process or on its causal interpretation: it is a mechanical property of the estimator which holds because of the algebra behind it.

I made a big diagram describing some assumptions (MLR1-6) that are used in linear regression. In my diagram, there are five categories (in rectangles with dotted lines) of mathematical facts that follow from different subsets of MLR1-6.

Read MoreI took Oxford’s advanced undergraduate econometrics course. My experience of the course, and really of the entire field, was the following: the concepts are simple, the real challenge is making sense of notation so obfuscatory that you wonder if it’s done on purpose.

Read MoreI made a diagram of this, based on Sider’s *Logic for philosophy*. An orange arrow from sytems S to system S’ means anything that is provable (and hence valid) in S is provable (and valid) in S’. I don’t add lables to the orange arrows since their meanings are clear. A green arrow from axiom schema to another says that the second schema is provable from the first in a particular system which I label.

Les dons à des organismes d’intérêt général ouvrent droit à une réduction d’impôt au taux de 66%, dans la limite de 20% du revenu imposable. Cette réduction permet donc de tripler ses dons. En effet, si je souhaite dépenser 1000€ en donnant, je peux donner 3000€, et l’administration fiscale me rembourse 3000 * 0.66=2000€ sous forme de réduction d’impôt. Ce régime fiscal du don est extrêmement généreux: à titre de comparaison, la législation britannique du “Gift Aid” permet d’augmenter ses dons de 25% au lieu de 200% pour la France!

Read More a computing machine is really a logic machine. Its circuits embody
the distilled insights of a remarkable collection of logicians, developed
over centuries.

-- Martin Davis (2000)

Philosophical problems are never solved for the same reason that treasonous conspiracies never succeed: as successful conspiracies are never called “treason,” so solved problems are no longer called “philosophy.”

-- John P. Burgess

In online discussions, the number of upvotes or likes a contribution receives is often highly correlated with the social status of the author within that community. This makes the community less epistemically diverse, and can contribute to feelings of groupthink or hero worship.

Read MoreFrom SMBC-comics.com

Read More*By Jacob Lagerros and Tom Sittler*

I recently discovered something about myself: I have a particularly strong aversion to the experience of confusion. For example, yesterday I was looking into the relationship between common knowledge of rationality and Nash equilibrium in game theory. I had planned to spend just an hour on this, leisurely dipping into the material and perhaps coming out with a clarified understanding. Instead, something else happened. I became monomanically focused on this task. I found some theorems, but there was still this feeling that things were just *slightly* off, that my understanding was not *quite* right. I intensely desired to track down the origin of the feeling. And to destroy the feeling. I grew restless, especially because I was making *some* progress: I wasn’t completely stuck, it felt like I must be on the cusp of clarity. The first symptom of this restlessness was skipping my pomodoro breaks, usually a sure sign that I am losing self-control and will soon collapse into an afternoon nap. The second smyptom was to develop an unhelpful impatience, opening ever more new tabs to search for the answer elsewhere, abandoning trains of thought earlier and earlier. In the end I didn’t have time to do any of the other work I had planned that day!

Cross-posted to the effective altruism forum.

Cost-effectiveness estimates are often expressed in $/QALYs instead of QALYs/$. But QALYs/$ are preferable because they are more intuitive. To avoid small numbers, we can renormalise to QALYs/$10,000, or something similar.

Read MoreIn Adam Elga’s 2000 paper “Self-locating belief and the Sleeping Beauty problem”, he opens with:

Read MoreIn addition to being uncertain about what the world is like, one can also be uncertain about one’s own spatial or temporal location in the world. My aim is to pose a problem arising from the interaction between these two sorts of uncertainty, solve the problem, and draw two lessons from the solution.

J’entends souvent des dialogues de ce genre quand il s’agit de faire un effort personnel pour aider les autres:

Read More

Alice:Face à toute la souffrance dans le monde, je me sens impuissante. Même si je changeais mon comportement, mon action individuelle ne résoudrait pas nos problèmes. Par exemple, même si je faisais un don pour aider un agriculteur pauvre au Kenya, d’autres ne donneront rien, et ce n’est pas grâce à moi que nous allons éliminer la pauvreté. Ce n’est pas à moi, mais aux puissants de ce monde d’agir.

Bernard:Si tout le monde raisonnait comme toi, nous ne ferions jamais rien pour aider les plus vulnérables. Au contraire, si chacun agit à son niveau, nous pouvons éliminer la pauvreté ensemble. Ainsi, en prenant partie à une action sociale, chacun peut changer les choses. Tu n’es donc pas impuissante.

When we take a sample mean, we should think of it as a random variable, and our measured sample mean as a realisation of that random variable. The sample mean is a random variable because it is the result of random sampling. Repeated sampling involves observing repeated realisations of the random variable.

Read MoreOxford, 15 janvier 2016

Read MoreEvénement de lancement de l’association Altruisme Efficace France, à Paris le 5 juillet 2016

Read MoreThis my book review of Nicholas Kristof and Sheryl WuDunn’s ”A Path Appears”. (Also available on scribd here). In 2015, the review won the Sciences Po - Books prize, a book review competition organized by my University and the magazine Books. It was published in French translation in the June 2015 edition of Books, of which I’ve scanned the relevant pages.

Read MoreValerio Filoso writes:

Read MoreMost econometrics textbooks limit themselves to providing the formula for the vector of the type

Although compact and easy to remember, this formulation is a sort black box, since it hardly reveals anything about what really happens during the estimation of a multivariate OLS model. Furthermore, the link between the and the moments of the data distribution disappear buried in the intricacies of matrix algebra. Luckily, an enlightening interpretation of the s in the multivariate case exists and has relevant interpreting power. It was originally formulated more than seventy years ago by Frisch and Waugh (1933), revived by Lovell (1963), and recently brought to a new life by Angrist and Pischke (2009) under the catchy phrase regression anatomy. According to this result, given a model with K independent variables, the coefficient for the k-th variable can be written as

where is the residual obtained by regressing on all remaining independent variables.

The result is striking since it establishes the possibility of breaking a multivariate model with K independent variables into bivariate models and also sheds light into the machinery of multivariate OLS. This property of OLS does not depend on the underlying Data Generating Process or on its causal interpretation: it is a mechanical property of the estimator which holds because of the algebra behind it.