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Constructing valid instrumental variables in generalized linear causal models from directed acyclic graphs

Øyvind Hoveid

arXiv 16 Feb 2021 · Econometrics

arXiv:2102.08056 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Unlike other techniques of causality inference, the use of valid instrumental variables can deal with unobserved sources of both variable errors, variable omissions, and sampling bias, and still arrive at consistent estimates of average treatment effects. The only problem is to find the valid instruments. Using the definition of Pearl (2009) of valid instrumental variables, a formal condition for validity can be stated for variables in generalized linear causal models. The condition can be applied in two different ways: As a tool for constructing valid instruments, or as a foundation for testing whether an instrument is valid. When perfectly valid instruments are not found, the squared bias of the IV-estimator induced by an imperfectly valid instrument -- estimated with bootstrapping -- can be added to its empirical variance in a mean-square-error-like reliability measure.

Citation extraction

11
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13
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Haavelmo (1943) `The statistical implications of a system of simultaneous equations', Econometrica, Journal of the Econometric Society 11(1), 1–120.64422100%
2Pearl (2009) Causality, Cambridge University Press0.51121100%
3Angrist \ Krueger (2001) `Instrumental variables and the search for identification: From supply and demand to natural experiments', Journal of Economic p…0.40511100%
4Fisher (1960) The design of experiments, Oliver and Boyd0.40511100%
5Heckman \ Pinto (2013) Causal analysis after Haavelmo, Technical report, National Bureau of Economic Research0.40511100%
6Imbens (2020) `Potential outcome and directed acyclic graph approaches to causality: Relevance for empirical practice in economics', Journal o…0.40511100%
7Reiersl (1950) `Identifiability of a linear relation between variables which are subject to error', Econometrica: Journal of the Econometric So…0.40511100%
8Stock \ Trebbi (2003) `Retrospectives: Who invented instrumental variable regression?', Journal of Economic Perspectives 17(3), 177–1940.40511100%
9Wikipedia (2020) `Instrumental variables estimation'0.40511100%
10Wright (1921) `Correlation and causation', Journal of agricultural research 20(7), 557–5850.40511100%

Showing the top 10 of 11 scored citations.