Using Shadow Pricing to Value Outcomes from Regeneration Programmes: Evidence from the New Deal for Communities Programme in England

Article excerpt

Regeneration initiatives, such as the New Deal for Communities (NDC) Programme in England, aim to transform places over time to improve the quality of life for local people. The outcomes of such programmes tend not to have market values and therefore do not sit easily within the UK Government's guidance on evaluation which requires outcomes to be monetised and compared with costs. Shadow pricing is a useful approach to adopt because it allows a monetary value to be placed on many of the core outcomes of regeneration programmes. Applying shadow-pricing unit values to outcome change data for the NDC Programme reveals monetised benefits far in excess of Programme costs, a finding which would not have emerged had more intangible outcomes not been monetised. This finding has implications for the justification, and design of all area regeneration schemes; an important consideration in the context of austerity measures currently being adopted by many governments.

Keywords: shadow pricing, New Deal for Communities, regeneration, monetising, evaluation

(ProQuest: ... denotes formula omitted.)

This paper investigates how a shadow-pricing methodology, using a self-reported quality-of-life measure, can be used to monetise core outcomes delivered by regeneration initiatives. For more than 50 years, UK governments have sought to address physical, social and economic problems evident within UK towns and cities through area-based initiatives (ABIs). A similar strand of urban policy has been apparent in both the United States (Oakley and Tsao, 2006), and in Europe (Carpenter, 2006; Hamedinger et al., 2008). One rationale underpinning this locality approach has been that concentrations of multiple forms of deprivation within certain identifiable areas help create additional and cumulative problems for local residents, and hence in turn impose additional pressures on mainstream services. In addition, spatial concentrations of deprived households provide policy with an opportunity to target substantial numbers of deprived people effectively.

Especially since the mid-1980s, ABIs have been subject to evaluation aimed at identifying their impacts and learning policy lessons for wider dissemination. In 2003 the UK Treasury set out an idealised approach to appraisal and evaluation in The Green Book (HM Treasury, 2003). According to the Green Book, 'evaluation comprises a robust analysis...[and] focuses on conducting a cost benefit analysis, in the knowledge of what actually occurred' (HM Treasury, 2003, paragraph 7.3). A preference for cost- benefit analysis to appraise and evaluate government initiatives is also apparent in many other parts of the world, including the United States (OMB, 1992) and Europe (European Commission, 2008).

Cost-benefit analysis involves systematically calculating and comparing benefits and costs of a project or policy. Ideally this should be done by expressing all benefits and costs in money terms, making adjustments for the time value of money, and then calculating an efficiency indicator comparing monetised benefits to costs. One consequence of adopting cost-benefit analyses is the need to express impacts in money terms. When assessing ABIs this creates a number of philosophical and methodological problems, not least because many of the impacts associated with ABIs are 'soft' perceptional or quality-of-life outcomes, the value of which is not obvious.

Previous ABI evaluations have tended to concentrate on tangible economic benefits, such as, for example, the additional gross value added from new jobs created, or fiscal savings as a result of interventions supported by regeneration schemes. As such they have tended to play down or even exclude what in many instances has been a primary aim of many ABIs: to improve the lives of residents within 'deprived communities'.

This paper considers the benefit for ABI evaluations in adopting a different approach to valuing outcomes: shadow pricing using quality of life. …