Genetic Algorithms and Stochastic Forest Property Rights Enforcement

Abstract This paper analyses the impact of corruption in a timber industry by comparing stochastic and determinis-tic approximations of a ‘log poaching-enforcement ’ difference game. In the paper it is argued that corruption leads to certainty about the effectiveness of enforcement efforts, a situation best represented by a deterministic game. By adding uncertainty, therefore, some light is shed on the impact of corruption. The model is hard to solve ana-lytically, so results are demonstrated by developing heuristic genetic algorithms. The results show that increasing uncertainty induces a government to spend more on enforcement and an illegal logger to harvest less