Hi,

The full program is here;

docs.google.com/document/d/1...

The CJE special issue in honour of James is accepting submissions until December 1st,
see more details here:
drive.google.com/file/d/1GJRm...

The conference has a deadline of July 15th. For more information see the conference website: www.econ.queensu.ca/about/events... 3/3

The special issue is edited by Steve Lehrer, Morten Nielsen, and myself, with a submission deadline of December 1st. For more information, see the call for papers: drive.google.com/file/d/1GJRm... 2/3

Or get a fancy printer.

youtu.be/D4dwETeyMrQ?...

​boottest is now also much faster for calculating the WRE thanks to both partialling out exogenous controls, before the bootstrap, and from reducing the total number of calculations by first calculating groupwise inner products​ similar to doi.org/10.1016/j.ec... . 4/4

boottest is normally quite fast. When there are many clusters, it can be a bit slow. David Roodman added a #JuliaLang option ",julia" which can 10x speed. See arxiv.org/pdf/2404.09309 for more about interfacing Stata with Julia​. 3/4

​The standard wild cluster bootstrap is usually quite reliable.
onlinelibrary.wiley.com/doi/full/10.... introduces WCR-S, which improves reliability with heterogenous clusters. This can be invoked using the ", jackknife" option. 2/4

For sure.

That said, the four U Sports divisions seems like a good middle ground between 1 and 10/13.

Our Monte Carlo simulations confirm the theoretical results: Standard TWFE, CS-DID, and FLEX, are biased when the two-way CCC is violated, while our DID-INT estimator is unbiased. Any comments are greatly appreciated. 5/5

We define three types of CCC assumptions: state-invariant, time-invariant, and two-way CCC. Time-varying covariates are OK as long as we account for the specific CCC violations. We need to adapt the estimator to match the way that the covariates enter the DGP. 4/5

We introduce a new estimator: (Two-Way) Intersection Difference-in-Differences (DID-INT), which provides unbiased estimates of the ATT even when CCC is violated. This approach can reveal parallel trends that are otherwise hidden. 3/5

Existing DiD methods often assume that covariate effects are constant across groups and time, which we term the two-way CCC assumption. We show that when this assumption fails, both conventional TWFE and CS-DID estimators can be biased. 2/5

This paper uses new data on the spatial distribution of firearms and firearm owners in Canada. We hope it is informative for firearms regulation in Canada and elsewhere. Any comments are greatly appreciated as we hope to submit it for publication soon. 3/3

Finding little relationship between legal gun density and crime is in the context of the existing firearms regulations. Legal owners need to go through in person training, pass tests, provide references, and can have licenses revoked due to crimes or safety concerns. 2/