@TechReport{borusyak.etal2018.xxx,
  author      = {Borusyak, Kirill And Hull, Peter And Jaravel, Xavier},
  institution = {National Bureau of Economic Research},
  title       = {Quasi-Experimental Shift-Share Research Designs},
  doi         = {10.3386/w24997},
  number      = {24997},
  type        = {Working Paper},
  url         = {http://www.nber.org/papers/w24997},
  abstract    = {Many empirical studies leverage shift-share (or “Bartik”) instruments that combine a set of aggregate shocks with measures of shock exposure. We derive a necessary and sufficient shock-level orthogonality condition for these instruments to identify causal effects. We then show that orthogonality holds when observed shocks are as-good-as-randomly assigned and growing in number, with the average shock exposure sufficiently dispersed. We recommend that practitioners implement quasi-experimental shift-share designs with new shock-level regressions, which help visualize identifying shock variation, correct standard errors, choose appropriate specifications, test identifying assumptions, and optimally combine multiple sets of quasi-random shocks. We illustrate these points by revisiting Autor et al. (2013)'s analysis of the labor market effects of Chinese import competition.},
  file        = {:borusyak.etal2018.xxx.pdf:PDF},
  groups      = {READ, planethealth, shift-share},
  month       = sep,
  series      = {Working Paper Series},
  year        = {2018},
}

@TechReport{adao.etal2018.xxx,
  author      = {Adão, Rodrigo And Kolesár, Michal And Morales, Eduardo},
  institution = {National Bureau of Economic Research},
  title       = {Shift-Share Designs: Theory and Inference},
  doi         = {10.3386/w24944},
  number      = {24944},
  type        = {Working Paper},
  url         = {http://www.nber.org/papers/w24944},
  abstract    = {We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression designs.},
  file        = {:w24944.pdf:PDF},
  groups      = {READ, shift-share},
  month       = aug,
  series      = {Working Paper Series},
  year        = {2018},
}

@Article{adao.etal2019.tqjoe,
  author   = {Adão, Rodrigo And Kolesár, Michal And Morales, Eduardo},
  title    = {{Shift-Share Designs: Theory and Inference*}},
  doi      = {10.1093/qje/qjz025},
  eprint   = {http://oup.prod.sis.lan/qje/article-pdf/134/4/1949/30044734/qjz025.pdf},
  issn     = {0033-5533},
  number   = {4},
  pages    = {1949--2010},
  volume   = {134},
  abstract = {{We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. commuting zones. Tests based on commonly used standard errors with 5\\% nominal significance level reject the null of no effect in up to 55\\% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independent of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show using popular applications of shift-share designs that our methods may lead to substantially wider confidence intervals in practice.}},
  file     = {:adao.etal2019.tqjoe.pdf:PDF},
  groups   = {READ, planethealth, shift-share},
  journal  = {The Quarterly Journal of Economics},
  month    = aug,
  year     = {2019},
}

@TechReport{jaeger.etal2018.xxx,
  author      = {Jaeger, David A And Ruist, Joakim And Stuhler, Jan},
  institution = {National Bureau of Economic Research},
  title       = {Shift-Share Instruments and the Impact of Immigration},
  doi         = {10.3386/w24285},
  number      = {24285},
  type        = {Working Paper},
  url         = {http://www.nber.org/papers/w24285},
  abstract    = {A large literature exploits geographic variation in the concentration of immigrants to identify their impact on a variety of outcomes. To address the endogeneity of immigrants' location choices, the most commonly-used instrument interacts national inflows by country of origin with immigrants' past geographic distribution. We present evidence that estimates based on this "shift-share" instrument conflate the short- and long-run responses to immigration shocks. If the spatial distribution of immigrant inflows is stable over time, the instrument is likely to be correlated with ongoing responses to previous supply shocks. Estimates based on the conventional shift-share instrument are therefore unlikely to identify the short-run causal effect. We propose a "multiple instrumentation" procedure that isolates the spatial variation arising from changes in the country-of-origin composition at the national level and permits us to estimate separately the short- and long-run effects. Our results are a cautionary tale for a large body of empirical work, not just on immigration, that rely on shift-share instruments for causal inference.},
  file        = {:bib/jaeger.etal2018.xxx.pdf:PDF},
  groups      = {READ, planethealth, shift-share, canaan},
  month       = feb,
  series      = {Working Paper Series},
  year        = {2018},
}

@Article{goldsmithpinkham.etal2020.aer,
  author  = {{Goldsmith}-{Pinkham}, Paul And Sorkin, Isaac And Swift, Henry},
  title   = {Bartik Instruments: What, When, Why, and How},
  doi     = {10.1257/aer.20181047},
  number  = {8},
  pages   = {2586--2624},
  url     = {https://www.aeaweb.org/articles?id=10.1257/aer.20181047},
  volume  = {110},
  file    = {:goldsmithpinkham.etal2020.aer.pdf:PDF},
  groups  = {planethealth, shift-share},
  journal = {American Economic Review},
  month   = aug,
  year    = {2020},
}

@Misc{borusyak.etal2021.xxx,
  author        = {Kirill Borusyak And Xavier Jaravel And Jann Spiess},
  title         = {Revisiting Event Study Designs: Robust and Efficient Estimation},
  year          = {2021},
  archiveprefix = {arXiv},
  eprint        = {2108.12419},
  file          = {:borusyak.etal2021.xxx.pdf:PDF},
  groups        = {DiD, shift-share},
  primaryclass  = {econ.EM},
}

@TechReport{borusyak.hull2020.xxx,
  author      = {Borusyak, Kirill And Hull, Peter},
  institution = {National Bureau of Economic Research},
  title       = {Non-Random Exposure to Exogenous Shocks: Theory and Applications},
  doi         = {10.3386/w27845},
  number      = {27845},
  type        = {Working Paper},
  url         = {http://www.nber.org/papers/w27845},
  abstract    = {We develop new tools for estimating the causal effects of treatments or instruments that combine multiple sources of variation according to a known formula. Examples include treatments capturing spillovers in social and transportation networks, simulated instruments for policy eligibility, and shift-share instruments. We show how exogenous shocks to some, but not all, determinants of such variables can be leveraged while avoiding omitted variables bias. Our solution involves specifying counterfactual shocks that may as well have been realized and adjusting for a summary measure of non-randomness in shock exposure: the average treatment (or instrument) across such counterfactuals. We further show how to use shock counterfactuals for valid finite-sample inference, and characterize the valid instruments that are asymptotically efficient. We apply this framework to address bias when estimating employment effects of market access growth from Chinese high-speed rail construction, and to boost power when estimating coverage effects of expanded Medicaid eligibility.},
  file        = {:borusyak.hull2020.xxx.pdf:PDF},
  groups      = {shift-share},
  month       = sep,
  series      = {Working Paper Series},
  year        = {2020},
}

@TechReport{borusyak.etal2022.sej,
  author       = {Kirill Borusyak And Rafael Dix-carneiro And Brian Kovak},
  title        = {Understanding Migration Responses to Local Shocks},
  date         = {2022},
  doi          = {10.2139/ssrn.4086847},
  file         = {:borusyak.etal2022.sej.pdf:PDF},
  groups       = {canaan, shift-share},
  journaltitle = {{SSRN} Electronic Journal},
  publisher    = {Elsevier {BV}},
}

@Article{cadena.kovak2016.aejae,
  author       = {Brian C. Cadena And Brian K. Kovak},
  date         = {2016-01},
  journaltitle = {American Economic Journal: Applied Economics},
  title        = {Immigrants Equilibrate Local Labor Markets: Evidence from the Great Recession},
  doi          = {10.1257/app.20140095},
  number       = {1},
  pages        = {257--290},
  volume       = {8},
  file         = {:cadena.kovak2016.aejae.pdf:PDF},
  groups       = {shift-share},
  publisher    = {American Economic Association},
}

@Article{borusyak.hull2023.ea,
  author    = {Borusyak, Kirill and Hull, Peter},
  journal   = {Econometrica},
  title     = {Nonrandom Exposure to Exogenous Shocks},
  year      = {2023},
  issn      = {0012-9682},
  number    = {6},
  pages     = {2155--2185},
  volume    = {91},
  doi       = {10.3982/ecta19367},
  file      = {:borusyak.hull2023.ea.pdf:PDF},
  groups    = {shift-share},
  keywords  = {Instrumental variables, formula instruments, recentered instruments, market access},
  publisher = {The Econometric Society},
}

 
@Article{borusyak.etal2021.troes,
  author    = {Borusyak, Kirill and Hull, Peter and Jaravel, Xavier},
  journal   = {The Review of Economic Studies},
  title     = {Quasi-Experimental Shift-Share Research Designs},
  year      = {2021},
  issn      = {1467-937X},
  month     = jun,
  number    = {1},
  pages     = {181--213},
  volume    = {89},
  doi       = {10.1093/restud/rdab030},
  editor    = {Krueger, Dirk},
  file      = {:borusyak.etal2021.troes.pdf:PDF},
  groups    = {shift-share},
  publisher = {Oxford University Press (OUP)},
}