Technocracy in energy policy A critique

Traditional conceptions of the role of experts in policymaking draw on the so-called technocratic-rationalistic model (Vedung, 1991; Pawson and Tilley, 1997, p. 6), which assumes that decisions are based on objective scientific advice and that policymakers have clearly defined preferences and policy goals. It further assumes that experts use rigorous scientific methods of analysis, and then provide their advice to decision makers who, in turn, act rationally by adjusting policies in the light of the advice received (Owens et al., 2004, p. 1945). In practice, policy-making is far more complex, and expert advice often fails to have the expected impact. Analysing change in terms of socio-technical transitions suggests that future policy pathways, however desirable they may appear, are not something that experts alone can decide upon. Instead they are negotiated in deliberations among various stakeholders, and the expert's role is much less clear-cut.

Scientific findings and expert advice are frequently used as 'ammunition' in political battles, in order to justify policies, to persuade others to adopt a certain line of action, to criticise others or in defence against criticisms (Valovirta, 2002). Ironically, experts can become 'stealth issue advocates' precisely because of their claim to objectivity and value-neutrality. Their findings may be ruthlessly exploited by policymakers to lend authority to their own agendas (Leviton and Hughes, 1981; Pollit, 1998; Weiss, 1999, p. 470; Pielke Jr, 2007). Findings and advice may not have the expected direct effects, but may nonetheless influence policies indirectly, by shaping frameworks of thought and problem definitions, and defining what are considered legitimate arguments in a debate. Moreover, in less technocratic modes, the process of producing policy advice can stimulate learning, networking and joint problemsolving among participants (e.g. Forss et al., 2002; Patton, 1998).

Even though abandoned by a large majority of academic scholars, and considered as unrealistic by many policy practitioners, the technocratic-rationalist model is still pervasive in legislative texts and policy rhetoric. The separation of powers between experts and politicians provides a convenient and protective myth to both, and the conception remains an intuitively appealing ideal. Consequently a whole set of institutions has been built around the model (Owens et al., 2004). However, 'institutionalised technocracy' is inadequate for the challenges of steering energy transitions because of the complexity and uncertainty concerning facts, values and worldviews.

Changing an energy system involves not only technology choices, but also considerations about the legal, regulatory and market framework, infrastructure (such as housing and land use decisions), the factors shaping individual behaviour and prevailing values and norms in society. In principle, a team of experts with sufficiently broad expertise could address these complexities. In practice, the assembled experts are more likely to disagree on actions needed because of their divergent views on both the objectives to be achieved and the means to attain them. In a situation characterised by both scientific uncertainty and controversy objective expert advice along the traditional lines becomes impossible. Under these conditions expert knowledge often cannot tell us what the 'optimal' or the 'best' solution for society is. Nevertheless policy advice tools such as CBA and forecasting are widely used in addressing complex energy policy questions in efforts to provide this sort of absolute guidance.

CBA remains the 'gold standard' of economic appraisal in energy policy, despite the many problems identified with the method (Vatn and Bromley, 1994; O'Neill, 1996; O'Neill, 1997; Soderbaum, 2007; Stagl, 2007, pp. 12-3) and recognition of its limits, even by some of its strongest advocates (Farrow and Toman, 1999; Pearce, 2000). Monetary and non-monetary (e.g. environmental) gains and losses (across society and through time) are aggregated in money terms. Methods such as eliciting respondents' 'willingness to pay' are used to value non-monetary gains and losses. The method then aggregates costs and benefits into a single figure or ratio that is a purportedly comprehensive and objectively defined estimate of the net cost or benefit to society of a project or policy. To do so it often, in practice, selectively (and at times spuriously) reduces pervasive uncertainties into mere probabilities of known risks.

CBA elevates economic efficiency as the only rational aim and appropriate framing for certain policy questions. The method was initially designed for clearly defined situations of project appraisal (Spash, 2007), yet it has recently been applied in complex policy appraisals, notably in the recent Stern review on the economics of climate change (Stern, 2006b). The way in which this report applies CBA to estimate the costs and benefits of climate policies is problematic for several reasons: it reduces the issue of intergenerational equity to a matter of choosing the appropriate discount rate; it estimates climate change impacts through conventional risk analysis, which fails to account for 'strong' uncertainties, and it uses monetary valuation to compare very different types of impacts and values (for instance the loss of human life in Bangladesh with growth of consumption possibilities in the North) (Spash, 2007).

By linking to one of the dominant meta-discourses of our society -the imperative of continuous economic growth (see Chapter 3) - the Stern review lent additional credibility to calls for stronger climate policies. Even if one agrees with the message, however, the way in which it was formulated is very technocratic, and gives a false sense of the findings being definitive and beyond question. Efforts to apply CBA to the decision of whether or not to build more nuclear power stations can be criticised on the same grounds, given the complexity, uncertainty and plurality of values involved.

Forecasting techniques are another type of tool frequently used in energy and transport policymaking. Forecasting techniques try to anticipate future demand, often through modelling, for example to provide a basis for infrastructure planning. Forecasting typically involves extrapolating past demand growth into the future, based on the expected growth in GDP. In the context of falling energy prices and economic stability in the post-war era, such forecasting exercises helped to justify policies and investments that fuelled economic growth and facilitated access to energy by all. However, this approach has become a root cause of undesirable momentum towards growth in present energy and transport systems. Growth forecasts have tended to become self-fulfilling prophecies: once a road section reaches a given vehicle density or the difference between electricity supply capacity and demand reaches a given threshold, a complex infrastructure planning machinery is set in motion.

This expert-led 'predict and provide' approach was appropriate to the cultural and ideological setting of Europe in the early post-war era, when experts and central planning were more trusted. It was acceptable as long as there were clear, uncontroversial demands to be met, and thus no apparent need to discuss where we were going as industrialised societies. The trouble with the 'predict and provide' approach today is that capacity improvement feeds the growth of demand and undermines efforts to reduce emissions and resource use. No matter how many new roads are built, after a while they reach the critical indicator of vehicle density, setting in motion the road building 'automat' again (Jordan, 2002; Tapio, 2002). Forecasting sustains this momentum, and provides little help envisaging new solutions.

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