[2011.06695] When Should We (Not) Interpret Linear IV Estimands as LATE? Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Economics > Econometrics arXiv:2011.06695 (econ) [Submitted on 13 Nov 2020 ( v1 ), last revised 29 Apr 2026 (this version, v8)] Title: When Should We (Not) Interpret Linear IV Estimands as LATE? Authors: Tymon Słoczyński View a PDF of the paper titled When Should We (Not) Interpret Linear IV Estimands as LATE?, by Tymon S{\l}oczy\'nski View PDF HTML (experimental) Abstract: In this paper I revisit the interpretation of the linear instrumental variables (IV) estimand as a weighted average of conditional local average treatment effects (LATEs). I focus on a situation in which additional covariates are required for identification while the reduced-form and first-stage regressions may be misspecified due to an implicit homogeneity restriction on the effects of the instrument. I show that the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect under a weaker version of monotonicity, i.e. when there are compliers but no defiers at some covariate values and defiers but no compliers elsewhere. The problem of negative weights disappears in the interacted specification of Angrist and Imbens (1995), which avoids misspecification and seems to be underused in applied work. I illustrate my findings in an application to the causal effects of pretrial detention on case outcomes. In this setting, I reject the stronger version of monotonicity, demonstrate that the interacted instruments are sufficiently strong for consistent estimation using the jackknife methodology, and present several estimates that are economically and statistically different, depending on whether the interacted instruments are used. Subjects: Econometrics (econ.EM) ; Methodology (stat.ME) Cite as: arXiv:2011.06695 [econ.EM] (or arXiv:2011.06695v8 [econ.EM] for this version) https://doi.org/10.48550/arXiv.2011.06695 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Tymon Sloczynski [ view email ] [v1] Fri, 13 Nov 2020 00:04:30 UTC (25 KB) [v2] Mon, 14 Dec 2020 18:36:43 UTC (26 KB) [v3] Fri, 30 Apr 2021 15:56:11 UTC (93 KB) [v4] Fri, 25 Jun 2021 17:48:48 UTC (94 KB) [v5] Mon, 28 Feb 2022 21:06:16 UTC (95 KB) [v6] Tue, 20 Sep 2022 23:57:40 UTC (98 KB) [v7] Sat, 5 Oct 2024 22:53:29 UTC (38 KB) [v8] Wed, 29 Apr 2026 04:23:37 UTC (51 KB) Full-text links: Access Paper: View a PDF of the paper titled When Should We (Not) Interpret Linear IV Estimands as LATE?, by Tymon S{\l}oczy\'nski View PDF HTML (experimental) TeX Source view license Current browse context: econ.EM < prev | next > new | recent | 2020-11 Change to browse by: econ stat stat.ME References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from