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Saturday, 8 February 2014

Exponential growth in the number of words used for the European Common Fisheries Policy (CFP): Does better management require more text?

Abstract

The European Common Fisheries Policy (CFP) is a common policy that originates from 1983 and has been renewed every 10 years. The policy generally aims for sustainable fisheries in terms of living resources, economics and social aspects. The most recent version of the policy was agreed in co-decision by the European Parliament and the European Council of Ministers in 2013. The CFP has often been criticised for not delivering on the objectives and for developing into micro-management with very detailed regulations. In this paper, the evolution of the CFP has been analysed using a simple word-count indicator. The results show a strong increase in the number of words used to describe the basic regulation of the CFP from 3500 words in 1983 to 21,000 words in the agreed regulation in 2013. The expansion of words fits closely to an exponential growth curve. The co-decision process between the European Parliament and the Council showed a 55% increase in words and the article describing the new landing obligation showed a 360% increase in words. First reports on the new CFP have already shown that the complexity in the regulation could increase the likelihood of misunderstanding and suboptimal decisions. Word-counts are obviously a crude way to measure regulatory complexity but they are easy to generate and intuitive to understand to different audiences. The challenge is to create conceptual models that can link this intuitive indicator into an empirical framework that attempts to measure the relative regulatory complexity.

Graphical abstract

The development of the number of words in the Common Fisheries Basic Regulation from 1993 to 2013, separated into the introductory text (white), the article text (grey) and the annex text (black). The increase in the word-count fits almost perfectly to an exponential growth curve (Fig. 2r2=0.99). Word-counts are obviously a crude way to measure regulatory complexity but they are very easy to generate and intuitive to understand to different audiences. The challenge is to create conceptual models that can link this intuitive indicator into an empirical framework that attempts to measure the relative regulatory complexity.