Research Note: The treatment of control variables in Demography from 1995 to 2020

Model specification is a critical step in demographic research. In model specification, control variables serve as an important tool for ensuring that the estimate of a relationship between X and Y is properly specified. However, control variables have often been uncritically included and potentially misspecified in observational social science, risking several types of bias. Using the journal Demography as a window into the discipline, we reviewed the use of control variables in statistical models published in the journal from 1995 to 2020. Results show that control variables are usually under-explained, making it difficult to evaluate their quality. When they are explained, variables are often included with logic that is out-of-step with current causal inference literature. There were just marginal improvements over the study period, and results were similar across topics. We discuss the implications for demographic science and recommend that a more rigorous selection of control variables and clear descriptions of that decision process are detailed as part of demographic scholarship.