A Methodology for Neural Spatial Interaction Modeling

This paper attempts to develop a mathematically rigid and unified framework for neural spatial interaction modeling. Families of classical neural network models, but also less classical ones such as product unit neural network ones are considered for the cases of unconstrained and singly constrained spatial interaction flows. Current practice appears to suffer from least squares and normality assumptions that ignore the true integer nature of the flows and approximate a discrete‐valued process by an almost certainly misrepresentative continuous distribution. To overcome this deficiency we suggest a more suitable estimation approach, maximum likelihood estimation under more realistic distributional assumptions of Poisson processes, and utilize a global search procedure, called Alopex, to solve the maximum likelihood estimation problem. To identify the transition from underfitting to overfitting we split the data into training, internal validation, and test sets. The bootstrapping pairs approach with replacement is adopted to combine the purity of data splitting with the power of a resampling procedure to overcome the generally neglected issue of fixed data splitting and the problem of scarce data. In addition, the approach has power to provide a better statistical picture of the prediction variability. Finally, a benchmark comparison against the classical gravity models illustrates the superiority of both, the unconstrained and the origin constrained neural network model versions in terms of generalization performance measured by Kullback and Leibler's information criterion.     

An alternative policy approach to rural development in regions facing population decline

ABSTRACT

Many rural regions in Europe used to be characterized by weak economic performance and negative population development. While in a long-term perspective this is not any more valid for large parts of Western Europe, a number of rural regions face persistent population decline. By analysing the case of Austria, where approximately one-third of rural areas have experienced such negative population change over the past decades, this paper will examine the impact on economic performance, income levels and well-being patterns. Addressing the crucial and persistent obstacles to positive population trends, new theoretical approaches and perspectives are discussed for overcoming limitations in development. Future approaches for regional development have to go beyond strategies for targeting economic growth, but have to address issues of local participation, social innovation and establishing trust as preconditions to effectively impact well-being dimensions. Such a mobilization effort would be the result of a comprehensive social transition process which would foster an altered narrative for these rural regions compared to the current and predominant focus on compensation and growth policies. Despite strong interlinkages with other regions and actors, the needs of local people would be central and both would be a cornerstone for social innovation.     

The Failed European Union: Franco-German Relations during the Great Depression of 1929–321

French scholars have led a revival of interest in inter-war efforts at European integration and the prominent role played by the French Foreign Minister, Aristide Briand. Franco-German rapprochement was integral to this effort, but with the death in October 1929 of his like-minded German counterpart, Gustav Stresemann, it is generally held that Berlin adopted a more confrontational foreign policy even before Hitler took power. However, this article demonstrates that in spite of a series of upsets, an intense and sustained effort continued during the years of the Great Depression (1929–32) to forge Franco-German détente. This culminated in September 1931 in a Franco-German treaty that established the mechanisms for far-reaching integration of the two countries’ economies, with a customs union and European union as the ultimate goals. It then examines in detail how and why this remarkable effort collapsed during 1932, paying particular attention to an unforeseen crisis in trading relations and the impact of a media scandal surrounding the publication of Stresemann's memoirs. Despite this failure, efforts to integrate Europe around a Franco-German axis between 1929 and 1932 can nonetheless be understood as part of a deeper process that survived Hitler and saw the emergence of the current European Union.     

The Dark Sides of Social Policy: From Neoliberalism to Resurgent Right-wing Populism

This Forum Debate explores the confluence of neoliberal, populist, conservative and reactionary influences on contemporary ideologies and practices of social policy, with a focus on the poorer peripheries of global capitalism. Several fundamental tensions are highlighted, which are largely overlooked by the social policy and development literatures. First, many recent social policy innovations have been discredited by their association with neoliberalism. The rising political Right has been much more successful than the Left at exploiting this discontent, despite simultaneously deepening many aspects of neoliberalism once in power. At the same time, right-wing movements have proactively used social policy as a political tool to fashion the social order along lines deemed amenable for their interests and ideologies, expressed along nationalist, racialized, ethnicized, nativist, religious, patriarchal or other lines, and to innovate practices of segregation, exclusion and subordination. While these synergies of neoliberal and right-wing populism are observed globally, they need to be carefully and differentially interpreted from the perspective of late industrializing (or late welfare state) peripheral countries. Nonetheless, common themes occurring across both centres and peripheries, as identified by the invited contributions to this Debate section, include exclusionary identity politics, hierarchical and subordinating inclusions, and patriarchal familialism. In this context, segregationism is an ominous possibility of post-neoliberal social policy.     

Optimization in an Error Backpropagation Neural Network Environment with a Performance Test on a Spectral Pattern Classification Problem

This paper attempts to develop a mathematically rigid framework for minimizing the cross-entropy function in an error backpropagating framework. In doing so, we derive the backpropagation formulae for evaluating the partial derivatives in a computationally efficient way. Various techniques of optimizing the multiple-class cross-entropy error function to train single hidden layer neural network classifiers with softmax output transfer functions are investigated on a real-world multispectral pixel-by-pixel classification problem that is of fundamental importance in remote sensing. These techniques include epoch-based and batch versions of backpropagation of gradient descent, PR-conjugate gradient, and BFGS quasi-Newton errors. The method of choice depends upon the nature of the learning task and whether one wants to optimize learning for speed or classification performance. It was found that, comparatively considered, gradient descent error backpropagation provided the best and most stable out-of-sample performance results across batch and epoch-based modes of operation. If the goal is to maximize learning speed and a sacrifice in classification accuracy is acceptable, then PR-conjugate gradient error backpropagation tends to be superior. If the training set is very large, stochastic epoch-based versions of local optimizers should be chosen utilizing a larger rather than a smaller epoch size to avoid unacceptable instabilities in the classification results.     

BEYOND THE RATIONALITY PROJECT: POLICY ANALYSIS AND THE POSTPOSITIVE CHALLENGE

Peter deLeon. 1988. Advice and Consent: The Development of the Policy Sciences
Deborah A. Stone. 1988. Policy Paradox and Political Reason
John S. Dryzek and Davis B. Bobrow. 1987. Policy Analysis by Design