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Cited by 3,377Advanced Statistical Methods and ModelsAdvanced Causal Inference TechniquesStatistical and numerical algorithms

The Estimation of Economic Relationships using Instrumental Variables

Sargan, J. D.·1958·Econometrica
DOI 10.2307/1907619
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Abstract

which the relationships are not exact, so that a set of ideal economic variables is assumed to be generated by a set of dynamic stochastic relationships, as in Koopmans [12], and the actual economic time series are assumed to differ from the ideal economic variables because of random disturbances or measurement errors. The asymptotic error variance matrix for the coefficients of one of the relationships is obtained in the case in which these relationships are estimated using instrumental variables. With this variance matrix we are able to discuss the problem of choice that arises when there are more instrumental variables available than the minimum number required to enable the method to be used. A method of estimation is derived which involves a characteristic equation already considered by Hotelling in defining the canonical correlation [10]. This method was previously suggested by Durbin [7]. The same estimates would be obtained by the maximum-likelihood limited

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  • A final important source of bias in MR, and indeed all studies of observational data, is selection bias.

    “A final important source of bias in MR, and indeed all studies of observational data, is selection bias.64,65”

    From Mendelian randomization (2022) · cites this paper as [65]

  • Population stratification, dynastic effects and assortative mating all induce bias by creating an artefactual relation at the population level between the genetic variants and the outcome, violating the second IV condition.

    “However, population stratification, dynastic effects and assortative mating all induce bias by creating an artefactual relation at the population level between the genetic variants and the outcome, violating the second IV condition.65,163–166”

    From Mendelian randomization (2022) · cites this paper as [65]

  • All forms of selection biases could bias MR estimates, so careful assessment of the potential for selection into the sample or samples used in an MR study is important.

    “All forms of selection biases could bias MR estimates and so careful assessment of the potential for selection into the sample or samples used in an MR study is important.65”

    From Mendelian randomization (2022) · cites this paper as [65]

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Authors
Sargan, J. D.
Corresponding author
Sargan, J. D.
ORCID
Sargan, J. D.
Venue
Econometrica
Publisher
JSTOR
Published
1958-07
Volume
26
Issue
3
Pages
393
ISSN
0012-9682 (ISSN-L)
DOI
10.2307/1907619
OpenAlex
W2045357062
Cited by
3,377
References
6
Citations by year
2026: 149 · 2025: 169 · 2024: 184 · 2023: 208 · 2022: 192 · 2021: 204 · 2020: 172 · 2019: 162 · 2018: 147 · 2017: 135 · 2016: 157 · 2015: 123 · 2014: 133 · 2013: 129 · 2012: 137
FWCI
2.96
Type
journal article
Language
en
Open access
closed
Locations
Econometrica (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Keywords
instrumental variables, over-identification, multiple instruments, measurement error, canonical correlation analysis, maximum likelihood estimation, econometric estimation

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