Managing Development: EU and African Relations through the evolution of the Lomé and Cotonou Agreements

The relationship between the European Union 1 and Africa has been formalised since the beginning of the European integration project in the evolving Yaoundé, Lomé and now Cotonou Agreements. The relationship has shifted in line with the emerging global framework for neoliberal accumulation. This shift has involved the re-designing’ of developmental strategies and their ‘locking-in’ in the long term. Theoretically, this global shift in the organisation of both production and social relations (including popular understandings) has been well documented and the changing dominant patterns of production in advanced industrial economies has been highlighted at length. However, this article aims to develop further the idea of ‘locking-in’, outlined in the work of Stephen Gill, and to place an increased emphasis on the phenomena of both re-designing and locking-in as they apply to the alteration of developmental strategies in Less Developed Countries (LDCs), among which those in Africa have suffered from extreme marginalisation and exploitation. This article reveals the often ignored role of the EU in this process. It argues that the EU, through its institutionalised link with Africa, has played a key role in re-designing developmental strategies to complement the global shift to neoliberal accumulation which, in its latest phase, is aimed particularly at the complex, multifaceted and increasingly integrated project to ‘lock-in’ the gains of capital over labour on a global scale. The article begins with a brief introduction to the complementary projects of ‘re-designing’ and ‘locking-in’ before considering these against the historical evolution of the Lomé and Cotonou relationship

The introduction of microfiche for disseminating technical information in the United States

Development of microfiche for disseminating technical informatio

A Cluster Elastic Net for Multivariate Regression

We propose a method for estimating coefficients in multivariate regression when there is a clustering structure to the response variables. The proposed method includes a fusion penalty, to shrink the difference in fitted values from responses in the same cluster, and an L1 penalty for simultaneous variable selection and estimation. The method can be used when the grouping structure of the response variables is known or unknown. When the clustering structure is unknown the method will simultaneously estimate the clusters of the response and the regression coefficients. Theoretical results are presented for the penalized least squares case, including asymptotic results allowing for p >> n. We extend our method to the setting where the responses are binomial variables. We propose a coordinate descent algorithm for both the normal and binomial likelihood, which can easily be extended to other generalized linear model (GLM) settings. Simulations and data examples from business operations and genomics are presented to show the merits of both the least squares and binomial methods.Comment: 37 Pages, 11 Figure