The Role of Instrumental Variables in Causal Inference Based on Independence of Cause and Mechanism

Sokolovska, Nataliya; Wuillemin, Pierre-Henri

doi:10.3390/e23080928

Cited by 3 publications

(3 citation statements)

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“…Failing to adjust such a confounder will lead to spurious association between the explanatory variable and the outcome. Analysis of instrumental variables (IV) has gained popularity in causal inference, such as investigating causal graphical structures [ 1 , 2 ] and controlling for unmeasured confounding [ 3 , 4 ]. An instrument is a variable that is correlated with the explanatory variable but not associated with any unmeasured confounders.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Maximum Likelihood Estimation for Piecewise Linear Instrumental Variable Models

Liu

Zhu

2022

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Analysis of instrumental variables is an effective approach to dealing with endogenous variables and unmeasured confounding issue in causal inference. We propose using the piecewise linear model to fit the relationship between the continuous instrumental variable and the continuous explanatory variable, as well as the relationship between the continuous explanatory variable and the outcome variable, which generalizes the traditional linear instrumental variable models. The two-stage least square and limited information maximum likelihood methods are used for the simultaneous estimation of the regression coefficients and the threshold parameters. Furthermore, we study the limiting distribution of the estimators in the correctly specified and misspecified models and provide a robust estimation of the variance-covariance matrix. We illustrate the finite sample properties of the estimation in terms of the Monte Carlo biases, standard errors, and coverage probabilities via the simulated data. Our proposed model is applied to an education-salary data, which investigates the causal effect of children’s years of schooling on estimated hourly wage with father’s years of schooling as the instrumental variable.

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Section: Introductionmentioning

confidence: 99%

Simultaneous Maximum Likelihood Estimation for Piecewise Linear Instrumental Variable Models

Liu

Zhu

2022

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“…Instrumental variable in causal inference. Papers [ 1 , 2 , 3 ] investigate models using instrumental variable in causal inference. Paper [ 1 ] deals with the challenge to reconcile the approaches to causal inference based on independence of cause and mechanism, and approaches based on conditional independence.…”

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confidence: 99%

“…Papers [ 1 , 2 , 3 ] investigate models using instrumental variable in causal inference. Paper [ 1 ] deals with the challenge to reconcile the approaches to causal inference based on independence of cause and mechanism, and approaches based on conditional independence. It is shown that methods based on the independence of cause and mechanism indirectly contain traces of the existence of hidden instrumental variables (IV).…”

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confidence: 99%