Reverse engineering and policy design

Abstract

A mechanistic perspective on policy analysis and design has been described as focused on “a theory of a system of interlocking parts that transmit causal forces from X to Y” (Beach and Pedersen, 2013, p. 29). Hedström and Ylikoski (2010, p. 53) argue that a “mechanism-based explanation describes the causal process selectively. It does not aim at an exhaustive account of all details but seeks to capture the crucial elements of the process by abstracting away the irrelevant details.” In the approach used in this volume, first-order causal mechanisms are seen as those that “alter the behavior of individuals, groups and structures to achieve a specific outcome” through use of policy activators embedded in government policy (Capano, Howlett and Ramesh, Chapter 1 this volume). Second-order causal mechanisms are the use of knowledge about mechanisms at work in individual and collective behaviors to inform revisions to policy “activators.” This chapter examines the firstand second-order causal mechanisms at work in a policy sector that many governments have tried to influence through use of policy activators: retirement savings by households. It uses that analysis to draw broader implications for the understanding and utilization of causal mechanisms in policy research, and in particular the potential of and limitations on reverse engineering, that is, using an understanding of how causal mechanisms operate to design mechanisms whose predicted outcomes “coincide with the desirable outcome” (Maskin, 2008, p. 567; emphasis in original) sought by government. Reverse engineering can thus be seen as one form of second-order mechanism. In this analysis, government policy activators are one of several factors that shape individual and household decisions on (and ultimately aggregate levels of) retirement savings. In the terminology used in this volume, the causal mechanisms at work in moving from Stage 2 to Stage 3 of the simplified causal model shown in Figure 10.1 – both policy activators and other factors that may influence individual and household retirement savings behavior – are first-order causal mechanisms. Retirement savings behavior in turn affects