Significance of control variables with measurement errors in register data when estimating causal effects
The project aims to study systematic errors that arise due to measurement errors of control variables in estimates of causal effects, which is especially important when control variables are retrieved from register data. More specifically, the project aims to study a specific type of measurement error that is common, namely one-sided error classification. This is a measurement error that occurs, for example, due to under-reporting in registers. This means that individuals who have a registered property actually have the property, but there are also individuals in the register who have the property without the property being registered.
More information about the project is available on the Swedish version of this page.