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2019 | OriginalPaper | Chapter

Multi-criteria Evaluation in Public Economics and Policy

Author : Giuseppe Munda

Published in: New Perspectives in Multiple Criteria Decision Making

Publisher: Springer International Publishing

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Abstract

Public administrations need to assess policy options before their implementation; often there is some uncertainty if cost-benefit analysis (CBA) or multi-criteria evaluation (MCE) should be used. This Chapter aims at showing that MCE may help economics at overcoming some of its current difficulties in the empirical assessment of public policy options; thus MCE has to be placed in the future of welfare economics with no doubt. To corroborate this conclusion, a structured comparison of the main distinguishing features of CBA and MCE is carried out according to the following ten comparison criteria: efficiency, fairness, democratic basis, effectiveness, problem structuring, alternatives taken into account, policy consequences, comprehensiveness, transparency and mathematical aggregation rule.

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May, 2018, more than 300 readers commented the initial debate between Tom Clark, editor of Prospect Magazine and Chris Giles, the FT’s economics editor.

See e.g. comments by Maurice Obstfeld, director of the International Monetary Fund research department and Tony Yates, former monetary economist at the Bank of England.

Statement due to Martin Wolf, FT’s chief economics commentator.

Statement due to Gavin Jackson FT’s economics reporter.

Mariana Mazzucato, professor at University College London.

Diana Coyle, professor at University of Cambridge.

From the technical point of view, one should note that the fact that intensity of preference is taken into account inside a linear aggregation rule, has the consequence that weights must be considered as trade-offs. A question then arises: in their standard use, are distributional weights used as importance coefficients or as trade-offs? The basic idea underlying all the different weighting methods can be summarized by quoting the following sentence: “if the decision-maker considers individual 2 more “deserving” than individual 1 he will weight 2’s losses more heavily than 1’s gains i.e. 2 > 1” (Dasgupta and Pearce 1972, p. 65), thus weights should be considered as importance coefficients. Unfortunately, since CBA is based on a completely compensatory mathematical model, weights can only have the meaning of a trade-off ratio, as a consequence a theoretical inconsistency exists (see Munda 1996 for more details on this issue).

It has to be clarified that the concept of fairness is different from the one of an equal distribution of income. A society could have a fair inequality if the economic system promotes and rewards individual efforts. Clearly ethical connotations are there; this implies that people, social scientists and governments differ significantly on what they consider to be fair. Overall there is agreement on the fact that evaluation of fairness should be linked to the social process leading to a certain outcome and not to the outcome itself (i.e. when differences in the final income distribution of a society exist, this does not mean that the society has unfair rules).

Late lessons from early warnings: the precautionary principle 1896–2000, European Environment Agency, Environmental issue report, No. 22, 2001.

Arrow’s axiom of “the independence of irrelevant alternatives” states that the choice made in a given set of alternatives A depends only on the ordering made with respect to the alternatives in that set. Alternatives outside A (irrelevant since the choice must be made within A) should not affect the choice inside A.

This property is a necessary condition for the existence of a linear aggregation rule. From an operational point of view this means that an additive aggregation function permits the assessment of the marginal contribution of each cost and benefit separately. Each marginal contribution can then be added together to yield a total value. This implies that among the different aspects of a policy option there are no phenomena of synergy or conflict, this is rather unrealistic from a scientific point of view.

Complete compensability is not desirable for the problem we are dealing with, since it implies that e.g. a good performance on efficiency would offset a very bad one on effectiveness or vice versa. It has to be noted that CBA always allows the highest degree of compensability since it is explicitly based on the Kaldor-Hicks compensation principle and costs and benefits are aggregated linearly (and thus in a compensatory fashion).

This relates to the famous bald paradox in Greek philosophy (how many hairs one has to cut off to transform a person with hairs to a bald one?), later on Poincaré (1935, p. 69) and finally Luce (1956) made the point that the transitivity of indifference relation is incompatible with the existence of a sensibility threshold below which an agent either does not sense the difference between two objects, or refuses to declare a preference for one or the other. Luce was the first one to discuss this issue formally in the framework of preference modelling. Mathematical characterizations of preference modelling with thresholds can be found in Roubens and Vincke (1985).

This of course applies to discrete methods only and implies that the aggregation rules belong to the family of non-frontier methods.

In social choice, the reaction to Arrow’s theorem has been the search for less ambitious voting structures; there is a need to keep a few basic requirements only. These basic requirements are generally three:

1. Anonymity: all criteria must be treated equally.

2. Neutrality: all alternatives must be treated equally.

3. Monotonicity: more support for an alternative cannot jeopardize its success.

One should note that, while anonymity is clearly essential in the case of voters, it is not so in the multi-criterion problem since criterion weights can be normally introduced.

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Title: Multi-criteria Evaluation in Public Economics and Policy
Author: Giuseppe Munda
Publisher: Springer International Publishing
Book: New Perspectives in Multiple Criteria Decision Making
Print ISBN: 978-3-030-11481-7

Electronic ISBN: 978-3-030-11482-4

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-11482-4_11