The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the causes of effects by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely understood as estimates of causal effects. The standard approach to infer the effects of causes in natural sciences and psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible. Most research in population studies is based on non-experimental designs (observational or survey designs) and rarely on quasi-experiments or natural experiments. Non-experimental designs are used to infer causal relationships, which can ultimately inform policies or interventions.