Kody Carmody

Did the CHIPS Act Trigger the Manufacturing Construction Boom? A forensic accounting of industrial policy effects

Did the CHIPS Act Trigger the Manufacturing Construction Boom? www.factorysettings.org/cp/190371400

What the Challenger Layoff Tracker Really Measures Why announced layoffs often diverge from the government’s layoff data.

I started a substack! First piece looks at the Challenger layoff data compared to JOLTS.

Why did Challenger, but not JOLTS, show an increase in layoffs the last three years?

besttrousers.substack.com/p/what-the-c...

For researchers working with the IPEDS dataset (nces.ed.gov/ipeds/), which can be kind of a bear to work with, especially over time, I've constructed some code to harmonize the data into a single DuckDB database

github.com/paulgp/ipeds...

At least it's an ethos? The limits of optimal control, from the maximalist and minimalist perspectives

The limits of optimal control, from the maximalist and minimalist perspectives.

Defining Normal to See Abnormal The data scientific techniques used to find dietary allowances.

Digging into the primordial data science used to find dietary allowances. See if you can back out the p-values.

Raghuram Rajan: Breaking the QE Ratchet Effect Raghuram Rajan on liquidity dependence, the Fed’s expanding balance sheet, and how to restore normalization as the default.

Latest newsletter outlining Raghu Rajan's liquidity dependence and QE ratchet arguments, its relationship to Kevin Warsh's balance sheet vision, and my response to questions: macroeconomicpolicynexus.substack.com/p/macro-musi...

Many workers have missed shifts without jobs being destroyed making it challenging to measure labor impacts with conventional sources.

We use real-time daily data from Homebase to measure impacts. Thanks to UChicago and Homebase for making the data available.
#EconSky #NumbersDay

Mathematics in the Library of Babel — Daniel Litt Mathematics isn't only about saying true things. It's about asking the right questions, being confused, stumbling about, getting distracted, being wrong, recognizing when you're wrong, being stuck. Mo...

Some thoughts on AI and math, inspired by “First Proof”: www.daniellitt.com/blog/2026/2/...

The Condorcet Jury Theorem under Ambiguity Bele Wollesen Leibniz University Hannover This paper evaluates the Condorcet Jury Theorem in the context of ambiguity. It explores the effects on the assumption of voter competence when voters face situations in which they can no longer ascribe a single probability. In contrast to voting in situations where voters are able to assign such probabilities, this paper demonstrates that voters may fail to vote competently under ambiguity, even if they are honest, practically rational, and epistemically competent. Thus, the conditions under which voter competence can be guaranteed become unclear once we adopt a less idealised framework of uncertainty. Specifically, conditions that ensure voter competence under risk do not necessarily guarantee voter competence under ambiguity. The second contribution is a more positive one. It outlines a fruitful research agenda aimed at identifying collective decision procedures that are better suited to less idealised uncertainty frameworks. In this regard, the paper shows how allowing abstention can have positive effects on the epistemic benefits of voting and extends the Condorcet Jury Theorem accordingly.

Former LSE student Bele Wollesen has a paper coming out in Ergo that I am a big fan of (www.belewollesen.com/uploads/1/4/...).

Economics Puzzle Leads to a New Understanding of a Fundamental Law of Physics The research provides a deeper understanding of the Boltzmann distribution.

Popular science piece about a math paper with physics motivation by Caltech and Princeton economists.

www.caltech.edu/about/news/e...

Love this post liorpachter.wordpress.com/2026/02/19/t...

also the Medicaid and SNAP cuts! I think people have in mind the CBO distributional score, e.g.,
Wolfers: finance.yahoo.com/news/trumps-...

Bernie Sanders: www.facebook.com/photo/?fbid=...

I think the "greatest shift of wealth from the working class to the 1%" line is coming from talking points about OBBB over the 10 year budget window

41% of black adults:

Price controls cause chaos Price controls are worse than you think

I'm super excited for my new paper with Alex Tabarrok
and Mark Whitmeyer.

tl;dr: price controls cause chaos. That chaos causes misallocation. We develop new tools to measure that misallocation, which is 1-9 the size of the Harberger triangle www.economicforces.xyz/p/price-cont...

Narrative mixed strategies

This looks super cool

Education of a Grandmaster Kenneth Rogoff, Our Dollar, Your Problem: An Insider’s View of Seven Turbulent Decades of Global Finance, and the Road Ahead. Yale 2025.

This review of Kenneth Rogoff’s new book by Perry Mehrling is great. It gives a strong overview of a Kindleberger-esque view of the IMFS while critiquing Rogoff. I think @rajakorman.bsky.social would enjoy it. www.ineteconomics.org/perspectives...

This is a great thread

What the Housing Market Teaches Us About Who’s Really Rich in America Some simple arithmetic on inequality and housing costs

open.substack.com/pub/everywhe...

I'm teaching a new course at Stern on AI in Finance and opening it up!

Syllabus/slides on Github: github.com/arpitrage/ai...

Weekly summaries on Substack
arpitrage.substack.com/p/1-three-ru...

First post is on Amdahl's Law, Jevons' Paradox, and why finance was slow to learn the bitter lesson

Same Shock, Separate Channels: House Prices and Firm Performance in the Great Recession I find evidence of house prices working through collateral and local banking channels. I incorporate these channels into a quantitative macro model.

New Census Working Paper: "Same Shock, Separate Channels: House Prices and Firm Performance in the Great Recession" by G. Jacob Blackwood www.census.gov/library/work...

**Part 1: From Bayesian inference to Bayesian workflow** 1. Bayesian theory and Bayesian practice 2. Statistical modeling and workflow 3. Computational tools 4. Introduction to workflow: Modeling performance on a multiple choice exam **Part 2: Statistical workflow** 5. Building statistical models 6. Using simulations to capture uncertainty 7. Prediction, generalization, and causal inference 8. Visualizing and checking fitted models 9. Comparing and improving models 10. Statistical inference and scientific inference **Part 3: Computational workflow** 11. Fitting statistical models 12. Diagnosing and fixing problems with fitting 13. Approximate algorithms and approximate models 14. Simulation-based calibration checking 15. Statistical modeling as software development

**4. Case studies** 16. Coding a series of models: Simulated data of movie ratings 17. Prior specification for regression models: Reanalysis of a sleep study 18. Predictive model checking and comparison: Clinical trial 19. Building up to a hierarchical model: Coronavirus testing 20. Using a fitted model for decision analysis: Mixture model for time series competition 21. Posterior predictive checking: Stochastic learning in dogs 22. Incremental development and testing: Black cat adoptions 23. Debugging a model: World Cup football 24. Leave-one-out cross validation model checking and comparison: Roaches 25. Model building and expansion: Golf putting 26. Model building with latent variables: Markov models for animal movement 27. Model building: Time-series decomposition for birthdays 28. Models for regression coefficients and variable selection: Student grades 29. Sampling problems with latent variables: No vehicles in the park 30. Challenge of multimodality: Differential equation for planetary motion 31. Simulation-based calibration checking in model development workflow **Appendices** A. Statistical and computational workflow for Bayesians and non-Bayesians B. How to get the most out of Bayesian Data Analysis

Bayesian Workflow by
Andrew Gelman, Aki Vehtari, @rmcelreath.bsky.social with @danpsimpson.bsky.social, @charlesm993.bsky.social, @yulingy.bsky.social, Lauren Kennedy, Jonah Gabry, @paulbuerkner.com, @modrakm.bsky.social, @vianeylb.bsky.social

(in production, estimated copy-editing time 6 weeks)

Atop the Forces of Production Announcing the launch of the Forces of Production macro data newsletter

okay so fun news, I am launching a macro newsletter from Common Wealth about the supply side data and the US economy called Forces of Production

Charts for bsky forthcoming at: @forcesofproduction.com
Launch essay below:

www.forcesofproduction.com/p/atop-the-f...

READ THIS POST!!!!!!!!!

New paper: “Uncertain Network Dynamics”
I analyze the dynamic transmission across a network of shocks with uncertain dynamic properties, which can capture both exogenous stochastic shocks & uncertainty in the network structure.
Paper here: drive.google.com/file/d/12ogG...

Saw an ancestor of this paper as a talk and liked it a lot! Glad to see it’s found a good home. Everything Matthias does is must-read imho

After 21 years, I'm going to stop the daily posting to my blog Calculated Risk. Thanks to everyone!

I'm still going to write the real estate newsletter and I've started a weekly economic newsletter to replace the blog (but just once a week).
economicweekly.substack.com

It Wasn't A Recession - How Age Divergence & A Participation Boom Drove A 1% Rise In The Unemployment Rate Summary: The unemployment rate has risen 1% from its post-pandemic trough three years ago, but this rise likely overstates the degree of labor market and business cycle deterioration relative to what ...

Latest @employamerica.bsky.social

It Wasn't A Recession - How Age Divergence & A Participation Boom Drove A 1% Rise In The Unemployment Rate

www.employamerica.org/labor-market...