African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6786


Approaches and methods used in analyzing compliance with fishery regulations

Sanaa Abusin
  • Sanaa Abusin
  • Environmental Economics consultant, Qatar.
  • Google Scholar

  •  Received: 30 October 2014
  •  Accepted: 09 January 2015
  •  Published: 07 May 2015


This paper reviews existing literature on analytical framework and methodological approaches to study noncompliance with fishery regulations. The causes of the problem of illegal fishing and noncompliance with fishery regulations are analysed and reasons behind the failure of current management regimes to promote sustainable management and exploitation of fishery are investigated.  Several deterrence models have been developed to study this problem in static and dynamic decision frameworks. The shortcomings of static model versus dynamic are specified and the static model found to be limited. Dynamic model on the other hand, consider allocation of resources overtime and hence account for the effect of discount future benefits and the repeated nature of the crime and detection. Extensions of both models are also discussed in details. Results from theoretical models are tested empirically using survey data. Different econometric models have been specified to conduct empirical deterrence analysis on determinants and extent of the decision to violate. Intensity of violation and frequency of violation as measures of violation rate are compared. Non-compliance determinants variables include socio-economic attributes, deterrence, and social and legitimacy factors. Empirical studies estimate both violation rate and extent of violation. Deep understanding of how fishers behave and their reaction to regulations is very crucial to tackle the problem and help policy makers to formulate policies accordingly.


Key words: compliance, dynamics, fishery, fisher’s behavior, inconstant probability, management, static.