Developing a micro-level model of tool calibrations

Wikis > Contemporary conceptions of instrument choice > Developing a micro-level model of tool calibrations

In 1989, Linder and Peters first described eight ‘attributes of instruments’ which they argued affected specific micro-level tool choices. These were: complexity of operation, level of public visibility, adaptability across uses, level of intrusiveness, relative costliness, reliance on markets, chances of failure, and precision of targeting (1989: 56). In his later work, however, Peters (2000) reduced this number to seven and altered their content so that they became: directness, visibility, capital/labour intensity, automaticity or level of administration required, level of universality, reliance on persuasion versus enforcement, and their ‘forcing vs enabling’ nature (39). This was no doubt due to the conclusion he drew from further study that drawing a sharp distinction between ‘market-based’ and ‘state-based’ tools is less useful than thinking about these as ‘modes of governance; while ‘chances of failure’ is also a highly contextual item which does not ‘adhere’ to an instrument as a fundamental characteristic. The other difference between the two lists is the addition of several sub-elements to ‘level of intrusiveness’ which, if removed, leaves five main instrument characteristics or appraisal criteria: automaticity, visibility, intrusiveness, cost, and precision of targeting. The first four criteria are linked to specific tool choices from within a resource category and all deal with the level of resource intensiveness of an instrument choice: that is, to the degree to which it utilizes, respectively, organizational, nodality, treasure or authority resources. Precision of targeting, on the other hand, is a key criterion related to tool calibrations or ‘settings’.

Putting these considerations together with those found at the governance mode and policy regime lever generates a set of nested implementation tool criteria involved in a typical design situation, as set out in Figure 1.

Figure 1: Final model of implementation tools selection process involved in policy design

The multi-level and nested nature of policy designs

Over the course of the past thirty years, the study of policy implementation instruments has advanced through the various stages of social scientific theory construction and now contributes a great deal of knowledge to policy formulation and policy design (Hood 2007; Lascoumes and Le Galès, 2007).

Current policy design theory is based on the insights developed during this period that while policy goals are manifold and alter over time, and while the choice of policy means is context driven and resource contingent, the toolbox with which designers must work is essentially generic (Majone 1989). That is, as Hood, Lowi and others noted, the reasons behind the actual choice a government may make to implement its policy goals may be complex, but the set of possible choices is limited in nature, bound as they are to the limited number of types of different governing resources they have at their disposal. Understanding the basic types of instruments available to policy-makers and establishing the criteria that policy experts use for assessing the advantages and disadvantages of their use is essential knowledge required to understand how designs emerge and thus to aid in the creation of new ones as well as the assessment and improvement of existing ones (Gibson 1999). That is, as Renate Mayntz (1983) argued, ‘to approach the problems of effective programme design’, it was ‘necessary first to identify the relevant programme elements and characteristics which are the object of decision in a process of programme design’ (126).

 

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