👇Great summary of our paper —couldn’t have said it better myself!

We've been comparing models based on how they *fit* for too long now! Adam Smith and Stephan Seiler show us how to compare models based on how they *perform*.

Bayesians and Quasi-Bayesians rejoice!!

Congratulations to #UCLSoM's Yiting Deng on being named one of the Best 40-Under-40 Business School Professors by Poets&Quants. Yiting said: “I am extremely honoured & deeply grateful for the support from my amazing colleagues and students..." ow.ly/5WJV30sjQpv UCL

Great move to grow the QME community. The journal has a history of publishing high-impact papers worth reading and discussing. And the account is run by two of the best out there in Brad Shapiro and Stephan Seiler.

One of these names is not like the others... 🧐 Today is the last day to register and (among many exciting talks) see me present a brand new (!!??) project on influencing 3rd party design of pricing algorithms (joint w/ Liz Lyons).

The UCL School of Management marketing group is hiring! Can confirm the “swank location + good vibes.”

TIL that Poisson misspelled Rev. Thomas Bayes' name throughout his work in the 1830s

Happy to have this out at QME! Regularization is important for large models and/or weakly informative data, and researchers stand to gain by thinking carefully about what estimates are shrunk towards. Using domain knowledge may be better than (arbitrary) zeros.

Very cool paper showing how Zalando does demand forecasting at scale. This is the second recent paper I've seen describing how companies think about large-scale pricing systems, the other being Amazon's recent paper: assets.amazon.science/ba/f5/f761c2a0… 1/

Marketing & Analytics at UCL School of Management is hiring again this year! Come join our fantastic quant group for an awesome research environment, low teaching loads, panoramic views over LDN from Canary Wharf and great vibes! Apply here: apply.interfolio.com/127232

🚨🚨 New working paper!!! 🚨🚨 Demand Estimation with Text and Image Data (together with Giovanni Compiani and Ilya Morozov) papers.ssrn.com/sol3/papers.cf… We propose a method to include product similarity measured using unstructured data into a demand estimation framework. 1/7

I wrote my first blog post, which is me quickly testing the value of combining two approximate demand estimation approaches that I like. Fun to write, but I can tell I have some work to do on blog-style writing. We'll see if there's ever a follow-up! jamesbrandecon.com/blog/0jxkvfr6z…

ML/AL-based algorithmic pricing tools soften competition, according to Daniel Ershov of University College London. Catch an MSI #webinar of him discussing his work supporting this side of the debate July 30, 12-12:30: ow.ly/MYis50SIFLg #AI #ML #marketingresearch #marketing

I’m very happy to share a “new" working paper on the dynamic/learned complementarity that arises between different products. This is joint work with Adam Smith and Max Pachali (Tilburg University) and its been really years in the making! 1/12

We have a beautiful literature on experiments with interference between units but what if there’s interference between experimenters? Estimands change and in a way we can understand and unpack. I hope you enjoy this one! 😊

🚨📜CALL FOR PAPERS 📜🚨 Send us your best work using non-standard data (e.g., unstructured data, clickstreams, data from genAI) to learn about consumer preferences. More details below.