MODELS AND POLICY FORMULATION
What Policy Formulation Tasks do Models Seek to Perform?
Computer models frequently aim to provide information that informs various steps in the policy cycle. A cycle in which policies are formulated
Note: Steps 1-5 are part of policy formulation.
Figure 5.2 The development cycle for natural resource management policies
is a highly complex, non-linear and iterative process. Howlett (2011) subdivides it in terms of agenda setting, policy formulation, decision making, implementation and evaluation. Computer models as discussed in this chapter are aimed primarily at supporting the stage in which options that might help resolve issues and problems recognized at the agenda-setting stage are identified, refined, appraised and formalized (Howlett 2011, p. 29). Applied to land use and natural resource management problems, the policy formulation step can be structured as in Figure 5.2 (van Ittersum et al. 2004; Dent and Ridgway 1986). Again, this is highly stylized and hypothetical compared with the reality. In the first step, the current situation and the resource base are described and analysed to make an inventory of problems (in other words, problem definition and diagnosis); creation of awareness is very important in this phase. In the second step, objectives are identified that steer policy formulation. Stakeholders should agree about a set of objectives and the way they are quantified. In the third and fourth steps, natural resource-use options are explored; especially the degree to which they satisfy a range of objectives. In the third step, the emphasis is on biophysically feasible options, meaning that system designs are explored which are possible from a biophysical and technical point of view, while little is said about how feasible or desirable they are from a socio-economic point of view. In the fourth step, socially acceptable and economically viable options are identified. In the fifth step, policy measures are assessed in an analytical and participatory process.
It is important to mention that the term 'policies' as used here includes specific projects and programmes, that is, we are not only talking about, for example, a price or input subsidy policy, but also about projects to construct, for example, an irrigation scheme or a road, or an extension programme. In the sixth step, the selected options are implemented and their impact is monitored and evaluated. This can then lead to a new policy cycle and the (re-)formulation of existing policies. The cycle is centred on the stakeholders, including the different actors affected by the policies. This facilitates the endorsement of both the process of policy formulation and its eventual outcomes, and prevents the procedure becoming too top-down (Dent et al. 1994; Fresco 1994).
Explorative studies are thought to be useful in steps 3 and 4 of Figure 5.2, that is, to identify ways to realize objectives and ultimate consequences of particular objectives. In Stirling's (2008) terms, these studies aim to 'open up' (as opposed to 'close down') the future; they must not take for granted past and present states and evolutions of the system, but indicate which (strategic) options for change exist. The required longer time horizon of such models implies greater uncertainty (see Figure 5.1). In step 3, the emphasis is on exploration of biophysically and technically feasible options, under different societal priorities; hence the studies have a relatively strong biophysical orientation. Predictive studies (Figure 5.1) can play a role particularly in steps 4 and 5. In step 4 economically viable and socially acceptable options must be identified, with the studies requiring a relatively strong socio-economic orientation. In the phase of identification of policy measures (step 5), predictive studies are introduced, particularly to estimate which policy instruments lead to the desired outcome in terms of defined indicators. This is a core activity in impact assessment procedures, as for instance employed in the European Commission.