Andrew & All about that Bayes!

Andrew Gelman is giving a talk on 11 October at 2 p.m. in Campus Pierre et Marie Curie (Sorbonne Université), room 16-26-209. He will talk about

Prior distribution for causal inference

In Bayesian inference, we must specify a model for the data (a likelihood) and a model for parameters (a prior). Consider two questions:

1. Why is it more complicated to specify the likelihood than the prior?
2. In order to specify the prior, how could can we switch between the theoretical literature (invariance, normality assumption, …) and the applied literature (experts elicitation, robustness, …)?

I will discuss those question in the domain of causal inference: prior distributions for causal effects, coefficients of regression and the other parameters in causal models.

causal inference makes it to Stockholm

Yesterday, Joshua Angrist and Guido Imbens, whose most cited paper is this JASA 1996 article with Don Rubin, were awarded the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for 2021. It is one of these not-so-rare instances when econometricians get this prize, with causality the motive for their award. I presume this will not see the number of Biometrika submissions involving causal inference go down! (Imbens wrote a book on causal inference with Don Rubin, and is currently editor of Econometrica. And Angrist wrote Mostly Harmless Econometrics, with J.S. Pischke, which I have not read.)

Introductory overview lecture: the ABC of ABC [JSM19 #1]

Here are my slides [more or less] for the introductory overview lecture I am giving today at JSM 2019, 4:00-5:50, CC-Four Seasons I. There is obviously quite an overlap with earlier courses I gave on the topic, although I refrained here from mentioning any specific application (like population genetics) to focus on statistical and computational aspects.

Along with the other introductory overview lectures in this edition of JSM:

• Sunday 28, 2:00-3:50, CC-Four Seasons I: CSI at the JSM: Forensic Statistics and the Value of Scientific Evidence in Court by Hal Stern (University of California, Irvine)
• Monday 29, 8:30-10:20, CC-205: Assessing Procedures vs. Assessing Evidence by Michael Levine (University of Massachusetts, Amherst)
• Monday 29, 2:00_3:50, CC-205: Causal inference in modern statistics by Jennifer Hill (New York University)and Avi Feller (UC Berkeley)
• Tuesday 30, 8:30-10:20, CC-205: Modern Risk Analysis  by Walter Piergorsch (University of Arizona) and David Banks (Duke University)

econometrics summer masterclass at Warwick, 15 May

There is an Econometrics Summer Masterclass taking place in the department of economics next week in Warwick, on May 15, with Don Rubin as one of the speakers and the masterclass teacher.