RT @f_montag: @giulia_bran and I are looking for a pre-doc to work with us on topics related to Industrial Organization and Trade @NYUStern….

My job market's done, and I'm heading back to the NYC area! Excited to join @PrincetonEcon as a postdoc next year and @NYUSternEcon as an AP in 2026. In a happy twist of fate, this means @conlon_chris and I will be colleagues exactly 10 years after our first PyBLP commit:

RT @nummoose: Thanks for the shout out, @marxmatt! . We plan to release this data publicly next year. Please reach out if you’re interested….

7/6 Also: I'm on the job market! If you're interested in the economics of (industrial policy for) open source or want to see a (very simple) example of micro BLP in action, check out my job market paper:

6/6 All this to say: if you're doing methods research, there are some clear private benefits that can come jointly with doing open source work (impact, transparency, networking, etc.) but also others that could be more surprising.

5/6 Having an open source package lets you show students exactly how the method works with real-time examples. I used PyBLP to teach one of @causalinf @kylefbutts's Mixtape sessions (, which would have been far less accessible without it.

4/6 When others rely on your code, you write more tests, which can benefit your (future) self. For every PyBLP version, I run ~2k tests across ~50 functions. These made it easy to broaden the scope of our papers by adding new simulations and empirical examples with confidence.

3/6 For micro BLP, I spent time iterating on PyBLP's interface to balance usability and flexibility. Feedback from users helped improve my design, which mapped directly into our standardized econometric framework, a key contribution of the 2nd paper.

2/6 I expected PyBLP's issue tracker ( to be mostly bug reports, but most are questions. Our 2nd paper was motivated by these interactions, and many of our explanations were informed by discussions on the tracker and emails from less vocal users.

Happy to share that this paper was just accepted @JEconometrics!. It's my and @conlon_chris's 2nd paper tied to our PyBLP software, so here's a thread on surprising (to me) benefits of combining methods research with open source work. 1/6.

RT @BrandonZborows1: 1/12 I’m excited to share my job market paper, “Delay Your Rivals? Vertical Integration in Securitization and Lending….

RT @SuproteemSarkar: Economic valuations fluctuate in ways empirical research cannot fully explain. What information are we missing? Econom….

RT @shani_cn: Excited to share that I'm on the 2024-2025 job market! .My job market paper is about failures of contingent thinking -- the a….

18/18 This has been a joy to write and present (not only because I get to use PyBLP screenshots to illustrate US-China collaboration). I'm excited to keep studying the tech sector from an IO perspective, and building econometric tools on the way. Links:

17/ Subsidies seem more effective and generate large innovation spillovers, especially if the US responds in kind. Subsidies can be cheap because OSS investment is rare (weak private benefits), but impactful because OSS use is widespread (strong public benefits).

16/ What if China tightened its restrictions?. Benefits don't seem localized enough for a "tax" on foreign collaboration to boost domestic OSS investment. Instead, lost spillovers raise web development costs globally.

15/ These estimates are key inputs into my policy simulations. Weak private benefits may justify subsidies that reduce underprovision, while strongly localized benefits may justify policies that coordinate domestic investment.

14/ Subject to the production function, firms' cost-minimizing choices reveal web development costs. Firms prefer OSS with more, own, and domestic investment. The model translates these patterns into public, private, and localized benefits of OSS investment.

13/ I estimate website quality's production function using timing assumptions. A weak link between OSS use and traffic translates into a weak effect of OSS use on quality, limiting the effect of OSS on competition and consumers in policy simulations.

12/ Consumers choose websites based on country, language, and quality. I get to use my own OSS PyBLP to estimate demand! I find strong "home bias," limiting international competition in policy simulations.