Sensitivity analysis of the unconfoundedness assumption with an application to an evaluation of college choice effects on earnings

• Published in: Journal of applied statistics 2014-08, Vol.41 (8), p.1767-1784
• Main Authors: de Luna, Xavier, Lundin, Mathias
• Format: Article
• Language: English
• Subjects: Applied statistics; Approximation; causal inference; College choice; Colleges; Correlation analysis; Earnings; effects of education; Mathematical analysis; Profits; propensity score; register data; Registers; Sensitivity analysis; Statistics; statistik; Studies
• ISSN: 0266-4763; 1360-0532; 1360-0532
• DOI: 10.1080/02664763.2014.890178

We evaluate the effects of college choice on earnings using Swedish register databases. This case study is used to motivate the introduction of a novel procedure to analyse the sensitivity of such an observational study to the assumption made that there are no unobserved confounders - variables affecting both college choice and earnings. This assumption is not testable without further information, and should be considered an approximation of reality. To perform a sensitivity analysis, we measure the departure from the unconfoundedness assumption with the correlation between college choice and earnings when conditioning on observed covariates. The use of a correlation as a measure of dependence allows us to propose a standardised procedure by advocating the use of a fixed value for the correlation, typically 1% or 5%, when checking the sensitivity of an evaluation study. A correlation coefficient is, moreover, intuitive to most empirical scientists, which makes the results of our sensitivity analysis easier to communicate than those of previously proposed methods. In our evaluation of the effects of college choice on earnings, the significantly positive effect obtained could not be questioned by a sensitivity analysis allowing for unobserved confounders inducing at most 5% correlation between college choice and earnings.