The difference in difference (DID) design is a quasi-experimental research design that researchers often use to study causal relationships in public health settings where randomized controlled trials (RCTs) are infeasible or unethical. However, causal inference poses many challenges in DID designs. In this article, we review key features of DID designs with an emphasis on public health policy research. Contemporary researchers should take an active approach to the design of DID studies, seeking to construct comparison groups, sensitivity analyses, and robustness checks that help validate the method's assumptions. We explain the key assumptions of the design and discuss analytic tactics, supplementary analysis, and approaches to statistical inference that are often important in applied research. The DID design is not a perfect substitute for randomized experiments, but it often represents a feasible way to learn about casual relationships. We conclude by noting that combining elements from multiple quasi-experimental techniques may be important in the next wave of innovations to the DID approach.

Different levels of government often interact on the ground, providing closely related services. While multilevel governance arrangements have been studied broadly, scarce literature has explored the contribution of national governments to achieving subnational policy goals. By reconceptualizing administrative decentralization as coexisting devolution (to subnational governments) and deconcentration (through field units), this research explores the indirect national contribution to subnational performance by delivering associated services. This article tests the following hypotheses: (1) there is a positive effect of national deconcentrated capacity on subnational policy outputs, and (2) under policy overlap, this contribution diminishes with increasing levels of subnational capacity. While Colombian schooling is decentralized, the national government indirectly contributes to education through a national agency that administers child protection services. Analyzing data for Colombian subnational governments over a decade reveals that national capacity boosts education provision while the least endowed regions benefit the most, thus providing evidence supporting both hypotheses.

Colombia’s duality between the relative strength of the central government and the broad process of decentralization towards subnational and local governments has shaped the country’s response to the COVID-19 pandemic. Substantial tensions have arisen between the national and subnational governments in the handling of the crisis. Thus, blurred policy boundaries challenge multi-level government coordination. Yet, intergovernmental relations and multi-level governance have worked at some extent. Meanwhile, leadership styles, the level of political support, the local governance environment and the level of local institutional capacity have affected the strategies of local government leaders and their success to tackle the pandemic. Moreover, uneven healthcare capacity across the Colombian territory posits further challenges for a national response to the pandemic that ensures both effectiveness and equity.

The decentralization of responsibilities has led to considerable variation in subnational performance. In this chapter, we explore the determinants of subnational government performance by suggesting that governors’ education (codified knowledge) and experience (uncodified knowledge) explain education outputs and health outcomes. We test our propositions in two data sets derived from 32 Mexican states and 32 Colombian departments during 1995–2010 and 2004–2013, respectively. Based on their findings, we caution against generalizing results, because factors driving performance in Mexican states differ from those boosting performance in Colombian departments. Neither governors’ codified nor uncodified knowledge drives subnational performance in Colombia. However, governors’ uncodified knowledge (experience) does explain health outcomes in Mexican states. Moreover, although political factors (e.g., partisanship and party ideology) explain health performance in Mexican states, no political factor does so in the Colombian departments. In sum, what drives performance in one country may not have the same explanatory power in another country.

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