Tootfinder

Estoy pasando mis notas del curro a limpio con #orgroam y se pueden hacer gršficos tan chulis y molones como este mediante #orgroamui

Erste Klasse im #Zug (B19) von #Algier nach #Oran. Mit brauchbar grosser Gepäckablage, starker Klimaanlage, Strom und neben jedem Sitz eine eigenes Fach für bspw. einen Rucksack. Und einem Türsteher an jeder Zugtür. 😅…

Identification of Causal Effects with a Bunching Design
Carolina Caetano, Gregorio Caetano, Leonard Goff, Eric Nielsen
https://arxiv.org/abs/2507.05210 htt…

Identification of Causal Effects with a Bunching Design
We show that causal effects can be identified when there is bunching in the distribution of a continuous treatment variable, without imposing any parametric assumptions. This yields a new nonparametric method for overcoming selection bias in the absence of instrumental variables, panel data, or other popular research designs for causal inference. The method leverages the change of variables theorem from integration theory, relating the selection bias to the ratio of the density of the treatment…

I used the #PrincessLamplighter for a trip to the grocery store, which I recorded on #Strava or … actually I should say that I tried to record it. The recording failed, thus it is not on Strava and as all Strava users know, that means it never actually happened and so my family wi…

Up until this year, I have never done a CSA. I picked up my first share today from a grocery store in my area. They just had a cart sitting out in the produce section.

Causal Inference for Aggregated Treatment
Carolina Caetano, Gregorio Caetano, Brantly Callaway, Derek Dyal
https://arxiv.org/abs/2506.22885 https://…

Causal Inference for Aggregated Treatment
In this paper, we study causal inference when the treatment variable is an aggregation of multiple sub-treatment variables. Researchers often report marginal causal effects for the aggregated treatment, implicitly assuming that the target parameter corresponds to a well-defined average of sub-treatment effects. We show that, even in an ideal scenario for causal inference such as random assignment, the weights underlying this average have some key undesirable properties: they are not unique, the…

I actually went to the grocery store to pick up some Dr. Pepper ahead of the week even though I could have done it tomorrow, because I want to do as little as possible tomorrow.