Sitemap - 2025 - Scott's Mixtape Substack
Two imminent workshops starting with shift-share IV by Peter Hull (Brown)
Noise versus signal in LLM assessment of quality
[Rerun] Tymon Słoczyński, Econometrician, Brandeis University
Heading to Madrid, leaving Seville
Continuous diff in diff, regressions and the 2x2
On Leaving Switzerland; Getting Robbed on a Train; Getting to Nerja, Spain
[Rerun] Jon Roth, Econometrician, Brown University
A wedding in Lucca, Pizzas at a party outside of town, and working
More Lucca, Plus Thoughts About My Fall Class at Harvard
[Rerun]: Mohammad Akbarpour, Microeconomic Theory, Stanford
Arriving at Lucca and starting two weeks of cloistered study and prep
Day 1 in Turin, Day t-1 before diff-in-diff workshop at Collegio Carlo Alberto
S4E24: Amitava Krishna Dutt, Development Economist, Notre Dame
Wrapping up CodeChella second edition
S4E23: Vítor Possebom, Econometrcian, Sao Paulo School of Economics (EESP)
End of semester causal inference assignment
Assessing the economics of AI class
S4E22: Jessica Brown, Labor Economist, University of South Carolina
Kindness, repeated use, and longrun distortionary effects from ChatGPT
Final AI Assignment for "Economics of AI" Class
S4E21: Michael Anderson, Public and Labor Economist, UC Berkeley
The Soul in the Machine: Exploring the New AI–Human Relationships
Day One: My Body Asked Me To Run Again So I'm Training Now For an Ultramarathon
Quick Correction: Synthetic Control Workshop is April 26–27
Two Upcoming Causal Inference Workshops (Corrected Dates Included)
A Simple Explainer of Acemoglu’s Simple Macroeconomics of AI
Science as Society and Dealing with Empirical Crises in Social Science
Personal updates (no Saturday links due to headaches)
S4E20: Philip Oreopoulos, Labor Economist, University of Toronto
How a Nobel physicist saw productivity—and why it matters for us now
Synthetic controls and CodeChella: Coming soon workshops
The Simple Power of The 2x2: Personal Reflection on Difference-in-Differences
Teaching David Autor at Economics of AI This Week
What I Learned at the OpenAI Economics Event
Long Differences, Short Gaps, and the Principle of Falsification in Event Studies
S4E18: Liyang Sun, Econometrics, University of College London
Walking Through Practitioners Guide (Baker, et al. 2025)
Mixtape University: Diff-in-Diff with a checklist. Simulating the Importance of Weighting
Closing tabs: Cold Harbor Edition
Personal thoughts about how I'm feeling about going to Harvard
Economics of AI Assignment: Interview Roleplay, Deep Research, Roleplay again
Mixtape Mailbag: Covariates, Regression, and Homogeneity
Mixtape University: Diff-in-diff with a checklist. Defining your target parameters
Closing tabs: Goodbye South Africa
The Wages of Nations: How AI Changes What It Means to Learn, Earn, and Grow
S4E17: Nathan Nunn, Economic History and Development, University of British Columbia
Mixtape University series: Diff-in-diff with a checklist. Where does Parallel Trends come from?
Closing tabs: South Africa edition
Causal 2 workshop announcement
My Day in San Francisco at OpenAI Economics Event
Designing your diff in diff with a checklist, step 2: counting the treated counties
Mixtape Mailbag: Staggered Adoption and Combining Synthetic Controls
Introducing Mixtape University: The Diff-in-Diff Checklist (and Why I’m Doing It)
Closing tabs: sleep deprived edition
Looks Can Be Deceiving: Why Visual Pre-trend Checks Aren’t Enough in Difference-in-Differences
Many Analyst Designs, Data Preparation and the Sources of Non Standard Errors
Economics of Generative AI on Workers and Work (plus some diff in diff stuff)
S4E16: Jérémy L'Hour, Econometrics and Machine Learning, Capital Fund Management and CREST
Mixtape Mailbag: Why is My Simple ATT Significant, but Not My Event Study?
My Field Guide for Deeply Feeling
Cleaning out my browser tabs: Eminem edition
The Hidden Curriculum Workshop: February 28 and March 1
Step 1: More about weighting heterogenous treatment effects
Does Being Nice to AI Make It Smarter? Experimental Evidence
Machine Learning Causal Forests Workshop Announcement!
Saturday closing out my open browser tabs: Valentines edition
Fourth Week of the Economics of AI Done: Some Reflection
Step 1: Looking Backwards through IV, TWFE and OLS vs Looking Forward Towards the Target Parameter
Firing Someone, Without Blame or Pleasing: An Adlerian Approach
S4E15: Dmitry Arkhangelsky, Econometrics and Machine Learning, CEMFI
A Primer on Acemoglu, AI and Automation
Saturday tabs: Super Bowl edition
Reflecting on Week 3 of my Economics of AI class
How I use AI to care for myself
T-minus 5 days, 15 days and 23 days to February workshops
Step 1: Defining the Target Parameter When All You have is Aggregate Data
Saturday tabs: Texas brisket edition
Week 2 of my economics of AI class: discussing the news and the dangers of LLM for learning
Peter Hull Teaches Instrumental Variables
Personal: Adler vs Becker Part 2
S4E12: Diane Whitmore Schanzenbach, Labor, Northwestern University
Closing tabs: missed opportunities
Week 1 of my new Economics of AI class
CodeChella Madrid 2024: Reflections and Insights
Designing your Diff-in-Diff: Still Talking About Target Parameters
Wishing us all a successful semester with classes drenched in AI
Closing tabs: Penultimate Week Before Spring Semester Edition
Designing Diff-in-Diff: Continuing Target Parameter Discussion plus Workshop Announcements
My Spring 2025 Economics of AI Syllabus (or the substack summary anyway)
S4E11: Marie Connolly, Labor Economist, Université du Québec à Montréal
Designing difference in differences: lessons from concealed carry laws in crime
Closing my tabs: the Lonesome Traveler edition