The theory and measurement brief will save you time by delivering summaries of recent applied research papers in Economics & Computation and Causal Inference and its industry applications right to your inbox.
Academia and the tech industry produce an ever growing amount of research in economics, computation and causal measurement relevant for designing, building and optimising smart and impactful products. Product managers and industry researchers need to keep up with research to become or remain cutting edge. This can be challenging not only due to the sheer amount of research available.
The theory and measurement brief will solve this challenge for you by regularly sending you research briefs right to your inbox that will take you no longer than 10 minutes to read. We will cover the topics economics & computation and causal inference and their industry applications, such as advertising auctions, platform and market design as well as content incrementally measurement, a/b testing and counterfactual machine learning. Our focus will be on applications, but highly relevant theory will find its place too. Also, we will dive into software and systems whenever relevant to the core topics economics & computation and causal inference. In terms of recency, most of the briefs will cover work published a few weeks or months ago. From time to time, we will mix in some classics that stood the test of time.
In the first season, the research briefs will appear weekly on Monday morning and will be posted on the blog. Please sign up to the newsletter so you don’t miss a post. The first season is from beginning February until the end of June. The brief will then take a summer break and then start again in August. Before we start the summer break, we will ask our readers for feedback on how to improve the theory and measurement brief.
In the first season, we will cover, among others, the following papers:
- Pacing Equilibrium in First-Price Auction Markets
- Online Learning for Measuring Incentive Compatibility in Ad Auctions
- Improving Treatment Effect Estimators Through Experiment Splitting
- Multiplicative Pacing Equilibria in Auction Markets
- Uplift Modeling for Multiple Treatments with Cost Optimization
- Improve User Retention with Causal Learning
- Stakeholders as Researchers: Empowering non-researchers to interact directly with consumers
- Online Second Price Auction with Semi-bandit Feedback Under the Non-Stationarity Setting
- Understanding Market Functionality and Trading Success
- Deep Landscape Forecasting for Real-time Bidding Advertising
- Machine Learning Estimation of Heterogenous Treatment Effects with Instruments
- Autobidding with Constraints
- Automated Mechanism Design via Neural Networks
- Optimal Auctions through Deep Learning
- Optimal Dynamic Auctions are Virtual Welfare Maximizers
- Dynamic Mechanism Design in the Field
- Methods for Measuring Brand Lift of Online Ads
Please contact me via e-mail to suggest additional papers that we should cover in the brief!
This is the first season of the theory and measurement brief. We will see how it goes and improve on the way. Be prepared for some rough edges at the start and please help me improve the brief by sending your feedback and paper suggestions by email.
theory and measurement brief 