Income inequality is often studied using longitudinal quantitative methods. In the social sciences, such studies often adopt pooled time series cross-section, or panel designs. This has the advantage of pooling multiple cases (i.e., countries) together over time, generating larger datasets, and allowing more complex models to be specified. Yet in doing so, we may be missing important variation between countries by "controlling out" these differences. In this case study, I discuss two longitudinal approaches to the study of income inequality. The first uses a panel design to investigate factors associated with the income share of the top 1%. The second adopts a comparative approach. It uses single-unit time series models of labor’s share of gross national income for two countries (Denmark and Ireland), and compares their results. The case study discusses the design decisions involved in choosing between both. It considers technical and statistical issues, what kinds of research question can be answered, what kinds of theory tested or constructed, and why taking a comparative approach can reveal important things we may miss by relying on pooled methods alone.