A Note on the Use of Proxy Variables

By M. Wickens. 1972

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Citations in the corpus

Causal Effect Inference with Deep Latent-Variable Models (2017, neutral): “Proxy variables and the challenges of using them correctly have long been considered in the causal inference literature [54, 14].”
Estimation issues with PLS and CBSEM: Where the bias lies! ☆ (2016, background): “That is, all measures of conceptual variables are approximations of or proxies for conceptual variables, independent from how theywere derived (e.g.,Wickens, 1972).”
On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations (2017, background): “…in econometrics, however, will likely subscribe to the proxy nature of measurement, as their field has long dealt with issues related to the use of a proxy when a variable specified in a theoretical model was unobservable and thus unavailable for statistical model estimation (e.g., Wickens, 1972).”
Controlling for endogeneity with instrumental variables in strategic management research (2008, background): “ent coefficients can be hard to predict (Greene, 2003; McCallum, 1972; Wickens, 1972).”
Measuring living standards with proxy variables (2011, background): “This line of thinking is appealing and can be shown to be correct in special cases (Aigner 1974; Bollen 1989; Maddala 1977; Montgomery et al. 1999; Wickens 1972).”
Policy Evaluation with Latent Confounders via Optimal Balance (2019, background): “Finally there has been a long history of work in causal inference using proxies for true confounders [11, 42].”
Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method (2019, background): “Regardless of researchers’ preference for one method or the other, common factors and weighted composites serve as standins for the unobservable conceptual variables in statistical models, and thus represent proxy variables (e.g., Teräsvirta, 1987; Wickens, 1972).”
Fixed Effects Estimation of the Intensive and Extensive Margins of Irrigation Water Demand (2012, background): “However, estimated coefficients on other variables are asymptotically unbiased if the other variables are orthogonal to actual precipitation and ET (Wickens, 1972).”