Econ PhDs who will be on the #EconJobMarket:
Next Tues Aug 19 at 1pm ET is a NABE (@nabe-econ.bsky.social) Career Week panel on "Industry, Government, or Academia? Choosing Your Path in Applied Economics"
Register here 👉 www.nabe.com/NABE/Events/...
Pleased to share op-ed in Le Monde: "Impact Evaluation: For GAFAM or for Citizens?"
🔗 French version (Le Monde):
www.lemonde.fr/idees/articl...
🔗 English translation (Sciences Po):
www.sciencespo.fr/department-e...
Tech companies routinely use impact evaluation tools to optimize their services...
New study: The relative wage premium for going to college has halved for low-income Americans since 1960.
What is to blame? Rising selectivity? Tuition hikes? State disinvestment? We decompose changes in the premium since 1900 to find out.
🧵#EconTwitter nber.org/papers/w33797
11/ We revisit the city-size premium using our estimated location effects and find an elasticity of 0.007. This is 2-3 times lower than estimates not controlling for establishment composition.
10/ Alternative approaches that don’t separate between the role of establishments and the “pure” location effect attribute ~30% of spatial disparities to the location (in both France and the US).
9/ MAIN RESULTS: location effects account for only 2-5% of spatial wage differences. Worker and establishment composition for 30% and 17%, respectively. Remaining half stems from the co-location of high-ability workers & high-paying firms, particularly in high-paying locations.
8/ We provide a series of tests that confirm the validity of our design, including quartile by quartile event study graphs, placebo tests and a survey of entrepreneurs.
7/ Identification: “double-movers” design, leveraging both workers who move across establishments and locations, and establishments that relocate across CZs.
6/ We estimate a three-way fixed effects model that accounts for (a) worker ability, (b) establishment productivity / pay policy, and (c) location-specific factors—such as infrastructure and agglomeration forces.
5/ We present a stylized spatial equilibrium model with firm and worker mobility. The model reproduces empirical facts, predicts sorting of workers and firms within and between locations, & generates log-linear additive wage equation.
4/ Establishments which relocate to another commuting zone replace ~50% of their workforce. Establishments relocating to a 1% higher paying location increase pay by ~0.15%.
3/ Establishments which relocate maintain the same activity, organization, and overall input composition.
2/ In both France and the US, 4% of establishments relocate every year. 25% of those moves involve a change in commuting zone (CZ).
1/ Our paper in 3 steps:
1. Characterizes establishment mobility in FRA and the US.
2. Builds a spatial model with worker and firm mobility.
3. Estimates three-way fixed effects model to decompose spatial wage differences into worker, firm, and location effects in FRA.
Why are wages in Paris or NYC higher than in other cities?
In a new WP with @paulinecarry.bsky.social & @bennykleinman.bsky.social, we decompose spatial disparities btw “location effects” and the local composition of workers and establishments.
New data on firm mobility + double-mover design.
🧵⬇️
Love labor and employment research?
New opportunity to join the team @upjohninstitute.bsky.social in Kalamazoo as a research analyst.
Bachelors required, more experience & education desirable.
#econ_ra
www.upjohn.org/sites/defaul...
This year’s 10 Upjohn Institute Early Career Research Awards bring the total to 256 grants awarded since the program’s founding in 2007. See this year's awardees and those from the full history of the #ECRA program. #Econsky
Cornell ILR is recruiting a Postdoc in Global Labor and Work - focusing on AI and labor. Deadline May 15, 2025. Please circulate widely! academicjobsonline.org/ajo/program/...
Looking for #Cornell #CornellEcon GRA to assist me as @aeadata.bsky.social (sorry, Cornell only). LDI Lab implementing the policy includes a part-time assistant & <=25 undergrads. Job: tackle hard cases, help undergrads handle easier ones. aeadataeditor.github.io
Here are the first five sets of slides:
01 Introduction: psantanna.com/DiD/01_Intro...
02 Classical 2x2 setup: psantanna.com/DiD/02_two_b...
03 Clustering issues: psantanna.com/DiD/03_Clust...
04 Functional form: psantanna.com/DiD/04_Funct...
05 Covariates: psantanna.com/DiD/05_Covar...
