Politics and Policies

A growing split has characterized political science, international relations, and political economy since the 1990s as the formal modeling and testing wing of these disciplines, based on quantitative analysis, has gained ascendancy over the older mainstream, grounded in narrative and richly informed by history. The questions, methods, execution, and presentation of projects found in these two approaches are so different that, in effect, scholars in these two traditions tend to coexist in parallel universes. This split affects scholars, policy analysts, and policy makers who study and operate within Latin America as much as those who observe and interact with Latin America from other countries or regions—poor, middle income, or rich. As a result, the study of politics and policies occurs most of the time in parallel, rather than interacting, universes.

On the one hand, some analysts follow the lively and messy process of everyday politics in a given place or places, whose developments are reported by journalists, sources in government or private business, and increasingly users of social media (e.g., Facebook, Twitter, YouTube). Analysts are also influenced by fieldwork and relevant actors on the ground, both of which tend to make them ask questions with imminent, real-life implications and ramifications. Scholars who adhere to this tradition diligently are very skeptical of generalizations, let alone grand predictions. Those who do so realize sooner rather than later that the complexity of human affairs is such that a significant number of social, political, and economic outcomes are the unintended consequences of policy.

On the other hand, some analysts study the creation and simulation of general conditions that can lead to replicable effects in both domestic and foreign contexts when public policies are formulated, implemented, evaluated, reformulated, reapplied, and so on, as inputs and outputs follow one another. The answers to the questions normally asked by these analysts can be tested statistically to create general frameworks and propositions. The goal is to improve the intended consequences of responses to social problems and to accommodate those responses to changing circumstances on the ground. Most who follow this research diligently concede that effective, one-size-fits-all policies cannot be assumed and that a chasm of varying widths exists between Pareto-optimal solutions (which benefit some while not hurting others) and real-life outcomes. Still, they aim to generalize about policies that have had success in particular contexts, in an effort to replicate them.

Fortunately, these two approaches are neither mutually exclusive nor necessarily antagonistic. Although most scholars and analysts gravitate toward and work in one or the other of these approaches, there is also a growing body of literature devoted to bridging the gap between them.¹ The four volumes reviewed here are solid examples of such efforts. All of them seek to engage the realms of both theoretical and applied knowledge, of cumulative learning and its messy interaction with unrepeatable human events.

The two approaches, if used concomitantly and appropriately, can help to enrich both the theory and the practice of mixing politics and policies. For orthodox scholars who make an effort not to draw policy implications in their work, learning the outcomes that particular policies have had in particular political contexts should be useful as a way to test general propositions. In turn, for those with one foot...