Local average treatment effect

In <a href="/facts/Econometrics/7U52gzHt">econometrics</a> and related empirical fields, the local average treatment effect (LATE), also known as the complier average causal effect (CACE), is the <a href="/facts/Rubin_causal_model/m6h998gw">effect of a treatment</a> for subjects who comply with the experimental treatment assigned to their sample group. It is not to be confused with the <a href="/facts/Average_treatment_effect/rju6xf4B">average treatment effect</a> (ATE), which includes compliers and non-compliers together. Compliance refers to the human-subject response to a proposed experimental treatment condition. Similar to the ATE, the LATE is calculated but does not include non-compliant parties. If the goal is to evaluate the effect of a treatment in ideal, compliant subjects, the LATE value will give a more precise estimate. However, it may lack <a href="/facts/External_validity/M5Q3z42b">external validity</a> by ignoring the effect of non-compliance that is likely to occur in the real-world deployment of a treatment method. The LATE can be estimated by a ratio of the estimated <a href="/facts/Intention-to-treat_analysis/LboWJXpj">intent-to-treat</a> effect and the estimated proportion of compliers, or alternatively through an <a href="/facts/Instrumental_variables_estimation/cEQ1xwT6">instrumental variable</a> estimator.
The LATE was first introduced in the econometrics literature by <a href="/facts/Guido_Imbens/euLHE2Az">Guido W. Imbens</a> and <a href="/facts/Joshua_Angrist/tBXRTFlh">Joshua D. Angrist</a> in 1994, who shared one half of the <a href="/facts/2021_Nobel_Memorial_Prize_in_Economic_Sciences/gNgV5DHx">2021 Nobel Memorial Prize in Economic Sciences</a>. As summarized by the Nobel Committee, the LATE framework "significantly altered how researchers approach empirical questions using data generated from either <a href="/facts/Natural_experiment/mLI7HCd1">natural experiments</a> or <a href="/facts/Randomized_experiment/MoDQXKsT">randomized experiments</a> with incomplete compliance to the assigned treatment. At the core, the LATE interpretation clarifies what can and cannot be learned from such experiments."
The phenomenon of non-compliant subjects (patients) is also known in <a href="/facts/Medical_research/lSVBFxDJ">medical research</a>. In the biostatistics literature, Baker and Lindeman (1994) independently developed the LATE method for a binary outcome with the paired availability design and the key monotonicity assumption. Baker, Kramer, Lindeman (2016) summarized the history of its development. Various papers called both Imbens and Angrist (1994) and Baker and Lindeman (1994) seminal.
An early version of LATE involved one-sided noncompliance (and hence no monotonicity assumption). In 1983 Baker wrote a technical report describing LATE for one-sided noncompliance that was published in 2016 in a supplement. In 1984, Bloom published a paper on LATE with one-sided compliance. For a history of multiple discoveries involving LATE see Baker and Lindeman (2024).

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Local average treatment effect