This Thursday, I will present at the CIREQ Séminaire Marcel-Dagenais en Économétrie at Université de Montréal, ou paper Optimal Transport for Counterfactual Estimation: A Method for Causal Inference, written with Emmanuel Flachaire and Ewen Gallic.
Many problems ask a question that can be formulated as a causal question: “what would have happened if…?” For example, “would the person have had surgery if he or she had been Black?” To address this kind of questions, calculating an average treatment effect (ATE) is often uninformative, because one would like to know how much impact a variable (such as skin color) has on a specific individual, characterized by certain covariates. Trying to calculate a conditional ATE (CATE) seems more appropriate. In causal inference, the propensity score approach assumes that the treatment is influenced by x, a collection of covariates. Here, we will have the dual view: doing an intervention, or changing the treatment (even just hypothetically, in a thought experiment, for example by asking what would have happened if a person had been Black) can have an impact on the values of x. We will see here that optimal transport allows us to change certain characteristics that are influenced by the variable we are trying to quantify the effect of. We propose here a mutatis mutandis version of the CATE, which will be done simply in dimension one by saying that the CATE must be computed relative to a level of probability, associated to the proportion of x (a single covariate) in the control population, and by looking for the equivalent quantile in the test population. In higher dimension, it will be necessary to go through transport, and an application will be proposed on the impact of some variables on the probability of having an unnatural birth (the fact that the mother smokes, or that the mother is Black).
Slides are available online. I will try to mention additional papers published this year, such as Fairness in Multi-Task Learning via Wasserstein Barycenters, Mitigating Discrimination in Insurance with Wasserstein Barycenters or more recently A Sequentially Fair Mechanism for Multiple Sensitive Attributes.
Wednesday, at lunch time, I will give a talk on insurance pricing at the (internal) economics seminar, at UQAM. Slides are now online.
In May, I will also give a seminar on the same topic at the Computational Science seminar…
Tomorrow Thursday, I will give a talk at the statistical seminar at UQaM, on “Using Transformations of Variables to Improve Inference“. It’s based on old results, with a new perspective, related to recent work with Emmanuel Flachaire (not mentioned in the slides, but that I will discuss tomorrow).
Next Wednesday, I will be giving a seminar at Università degli studi dell’Insubria on Machine Learning and Econometrics. The presentation is based on Econométrie et Machine Learning (so far only in French) written with Emmanuel Flachaire and Antoine Ly. Slides are now available online…
I will be back in Lausanne (I was already there last summer) to spend a few days, visiting Florian, at HEC Lausanne. I will also give a talk on old and new results on (standard) families of copulas. There will be also a discussion on tail dependence. Slides can be downloaded from here,
I was last Friday at Laval University for a conference by David Cummins and Mary Weiss (here). I will be back tomorrow, this time to give a talk, on “distorting probabilities in actuarial science” (the talk will be extremely close to the one I gave at McGill in November). “In this talk, we will first get back on properties of distortion operators for pricing financial and insurance risks. Based on the dual version of the expected utility framework, we will see how distorted risk measures have been introduced, from VaR and TVaR, to Esscher premium and Wang’s measures. Then we will discuss extensions in higher dimension. We will discuss tail properties of distorted copulas (in the particular case of Archimedean copulas). A natural application will be aging problems (in survival analysis or in credit risk).” Slides can be downloaded from here.
This talk can be seen as a first part, the second one behing the talk I will give in 15 days, again at Laval University, but this time for the Seminar of Statistics. The talk will be on “Beta kernel and transformed kernel : applications to quantile estimation, and copula density estimation“.
I will give a talk at McGill university this afternoon, on “distorting probabilities in actuarial science“. Note that Louis Paul Rivest will give a talk just after, but at UQAM, at the statistical seminar (here)