Your paper is very clear and useful to the field. It confirms concerns that I voiced publicly in 2017. Seeing it is a bit like someone saying to me "you weren't crazy after all," years after I witnessed a somewhat implausible traumatic event in which people didn't believe my testimony. I was an remain a free trade enthusiast, but I also wanted to understand the 2016 election, and Autor et al's work was a big theme that I felt I needed to explore. I had long admired Autor's labor market research on skills and tasks. My 2016 work on presidential preferences used their data and found no relationship at all between trade exposure or even manufacturing exposure and Trump support, which was my first clue that something was off. This was less notable when it became clear that the Autor et al trade exposure variable had no meaningful correlation with any economic outcome (unemployment rate, household income, etc) that I had been studying during my time at the Brookings Metro Program as a key indicator of regional prosperity. What was very surprising to see was that I could not replicate their results until I a) used their exact data and b) used their exact code. Using alternatives for either failed to replicate, and I told them so privately. In fact, not only was the regional data not playing out as expected (more "exposed" areas were no worse off in 2015 than other areas), but other national data were inconsistent with the story. Manufacturing layoffs and separations per worker were less common than those in domestic un-exposed sectors. After realizing that the stacked model was the key issue (comparing late 1990s outcomes to ~2007 outcomes), I wrote up my results, shared it with them, and tried to publish as a comment but could not find a receptive journal--so tried as a full paper at AER, since they published the original work. Debating Autor et al did nothing to help my career and became a major distraction from work I was supposed to be doing. It is easy to understand why many people don't do it. My 2017 paper was rejected by the (now) incoming AEA President Penny Goldberg, who as editor at AER at the time, on the flimsiest of excuses. I'm sure the Borusyak et al paper hides the bad results for Author et al to avoid controversy and facilitate publication. Their Supplemental Table C3 is very similar to my preferred results. It is reassuring to see that their other results, relaxing various assumptions, are consistent with what I was finding. I have nothing against Author, Dorn, and Hanson. They have every right to defend themselves vigorously against criticism of their work. I'm sure they believed they were right. At the same time it has become astonishingly clear to me that a) academics in every field are not capable of objectively reconsidering their own work (probably myself included), and should not be assumed to be capable of doing so; b) they follow and perpetuate narratives, often erroneous ones, to advance their careers. These narratives are rarely, if ever, directly tested, because doing so would be professionally awkward, embarrassing to many others, and run counter to the political preferences of most of their colleagues. I have seen this to an incredible degree in sociology, as I am working on a meta-analysis that completely contradicts a dominate narrative, and I have seen it across social sciences and humanities with respect to the lasting influence of Marxism, which still leads many academic writers to posit--without even trying to prove it--that there are large causal effects of growing up with low socio-economic status, and these effects would be eliminated with income/wealth redistribution.