Education's role in economic development and in assisting the poor

Much faith has been put in the increased supply of education as a means to promote national economic development and as a way to assist the poor and the disadvantaged. However, the benefits that nations can obtain by increasing the level of education of their workforce depends on the availability of other forms of capital to complement the use of its educated workforce in production. Generally, less developed nations are lacking in complementary capital compared to more developed ones and it is appropriate for less developed countries to spend relatively less on education. The contribution of education to economic growth depends on a nation’s stage of economic development. It is only when a nation becomes relatively developed that education becomes a major contributor to economic growth. It is possible for less developed nations to retard their economic growth by favouring investment in educational capital rather than other forms of capital. Easy access to education is often portrayed as a powerful force for assisting the poor and the disadvantaged. Several reasons are given here as to why it may not be so effective in assisting the poor and in promoting greater income equality even though the aim is a worthy one. Also, an economic argument is presented in favour of special education for the physically and mentally handicapped. This paper is not intended to belittle the contribution of education to economic development nor to devalue the ideal of making basic education available to all. Instead, it is intended as an antidote to inflated claims about the ability of greater investment in education to promote economic growth and about the ability of more widespread access to education to reduce poverty and decrease income inequality.

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.