Causal logics and mechanisms in policy design: How and why adopting a mechanistic perspective can improve policy design

Publication Date01 April 2021
Date01 April 2021
AuthorGiliberto Capano,Michael Howlett
SubjectSpecial Issue Articles
Special Issue: Mechanisms
Causal logics and
mechanisms in policy
design: How and why
adopting a mechanistic
perspective can improve
policy design
Giliberto Capano
University of Bologna, Italy
Michael Howlett
Simon Fraser University, Canada
Policy design undertakes to develop effective policies and hence must understand
whether and how effective policies can be formulated and implemented. However,
very often policy design has failed to focus on the causal chain that represents the
actual driver of policy effects and thus misconstrues the potential effectiveness of a
policy design. A mechanistic perspective is extremely helpful for conceptualising and
pinpointing such causal chains, as it focuses on the real processes that must be activated
by policy-makers in implementing policy designs. This article identifies the main steps to
be taken when adopting such a mechanistic approach to policy design.
Causality, mechanisms, policy design
In this paper, we reflect on the usefulness of adopting a mechanistic perspective for
the creation and analysis of policy designs. A mechanistic perspective focuses on
the ways the elements of a policy design can advance its goals, namely by better
understanding how the behaviour of both implementers and the targets of the
design are altered by policy instruments in order to better achieve desired policy
Public Policy and Administration
2021, Vol. 36(2) 141–162
!The Author(s) 2019
Article reuse guidelines:
DOI: 10.1177/0952076719827068
Corresponding author:
Giliberto Capano, University of Bologna, Strada Maggiore 45, Bologna 40125, Italy.
outputs and outcomes. As is argued below, a mechanistic perspective can enhance
the technical design capacities of decision-makers by making it clear which behav-
iours are likely to be altered by any given policy intervention and why this expect-
ation is a reasonable one.
From a mechanistic perspective, policy solutions are comprised of policy instru-
ments whose adoption is expected to be conducive to a desired outcome, with a
policy design in turn composed of a mix of such tools expected to more or less
comprehensively attain a set of goals.
Policy-makers thus need a realistic causal theory about what occurs when policy
tools are deployed and how it occurs if they want to design something that will
actually happen more often than not, and to escape the trap of poorly conceived
and related tacit knowledge, experience and heuristics. To date, however, many
policy designs have been based on anecdotal or co-variational logics of expected
outcomes from instrument deployment, without necessarily understanding the pre-
cise mechanisms which cause these outcomes to occur. In a sense then, much
existing policy design thinking jumps from a proposed solution to an outcome,
bypassing the ‘black box’ of behavioural and organisational change and target
behaviour which generate outputs which allow this outcome to come to pass
(Astbury and Leeuw, 2010)
Too often in the field of policy design, as in policy sciences and public policy
more generally, explanations of ‘what works when’ are based on weak causation or
a ‘heuristic’ framework, an often acknowledged to be unrealistic set of assumptions
about irrational/rational behaviour, or a set of correlations between government
actions and outcomes which are often mistaken for causes. Or, they can be based
on a causation ‘derived,’ from ‘‘what works’’ approaches, based on counterfactual
estimates (Goertz and Mahoney, 2012; Heckman, 2005).
Overall, an actual focus on realistic causation is often absent. Thus, one of the
most important questions for policy design remains highly problematic for policy
designers: how does a policy design encourage, constrain and otherwise structure
policy targets’ behaviour to achieve desired outcomes; and how can the box of
policy tools available to policy-makers be organised in an effective (implementable)
way to achieve desired behavioural changes?
A mechanistic approach to design addresses these issues but requires careful
reasoning both in terms of the kinds of processes and interactions that can be
activated by a policy instrument and how policy development can occur to help
these happen (Moynihan and Soss, 2014; Pierson, 1993, 2000a, 2000b; Schneider
and Sydney, 2009). Such a mechanistic perspective potentially not only reinforces
existing analyses and explanations of how design works, but it can also show how
the policy capacity of government can be strengthened. That is, a mechanistic
approach to policy design strengthens decision-makers’ analytical capacity by
making it clearer what should be analysed and why. This approach then allows
appropriate policy tools to be chosen to ‘fit the job’ and helps inform the calibra-
of those tools to ensure their effectiveness.
142 Public Policy and Administration 36(2)

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