Migration of Husbands, Remittances and Agricultural Production: Impacts when Wives Head Households in Rural Kenya

This paper uses data collected from migrants' wives in the Nyeri district of Kenya. The main objective is to determine whether migration and remittances contribute to the development of agriculture. Our results suggest that most migrants are pushed out of rural areas, belong to the group of low-paid workers in urban areas, send little and irregular remittances to their wives back in rural areas and that these remittances are mainly used for consumption purposes and do not contribute to any significant development in agriculture. Our results also indicate that altruism or social obligation might be the main reason for migrants sending remittances back to their rural wives.

Will Bangladesh's economic growth solve its environmental problems?

Bangladesh has experienced rising GDP and rising per capita incomes now for at least three decades. This article considers whether its continuing economic growth is likely to solve its environmental problems. In doing so, it critically considers the application to Bangladesh of Environmental Kuznets Curve relationships and applies other macro-methods of assessing the relationship between economic growth and the environment to Bangladesh’s situation. The consequences of Bangladesh's economic reforms for the economic welfare of Bangladeshis and the state of Bangladesh's environment are also examined. Particular attention is given to environmental change in agriculture in the light of Bangladesh economic growth, reforms and proposed growth strategy. Doubts are expressed about the environmental benefits claimed by the Bangladeshi Government for its agricultural development strategy. Indeed, it may exacerbate many existing environmental problems, such as depletion of soil fertility and water supplies, already present.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.