The Political Economy of Global Financial Governance: The Costs of Basle II for Poor Countries

The 1990s financial crises triggered many changes to the design of the international financial system, the so-called international financial architecture. While much affected, developing countries have had very little influence on the changes, which the formulation of the new Basle capital accord (B-II) illustrates. The article shows that B-II has largely been formulated to serve the interests of powerful market players, with developing economies being left out. For developing countries, B-II can make domestic financing more costly and raise the costs of and reduce the access to external financing. Importantly, B-II can exacerbate fluctuations in the supply of external financing, an unfortunate outcome, given that developing countries already suffer from volatility.Basle Committee, capital adequacy, financial governance, financial architecture, financial reform, international standards, capital flows, poor countries, cost of capital, international development

Compliant and flexible business processes with business rules.

When modeling business processes, we often implicitly think of internal business policies and external regulations. Yet to date, little attention is paid to avoid hard-coding policies and regulations directly in control-flow based process models. The standpoint of this analysis is the role of business rule modeling in achieving business process flexibility. In particular, it is argued that flexible business process models require business rules as a declarative formalism to capture the semantics of policy and regulation. Four kinds of business rules can be used as a starting point to generate less complex control-flow-based business process models. It is shown that these different kinds of business rules relate to different perspectives in the taxonomy of business process flexibility.

Building Credit-Risk Evaluation Expert Systems Using Neural Network Rule Extraction and Decision Tables.

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried out on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed. The rule extraction algorithms, Neurolinear, Neurorule, Trepan and Nefclass, have different characteristics with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree (rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional ifthen rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.Credit; Information systems; International; Systems;

Influence of notch orientation on ductile tearing in SENT specimens

There is a growing interest for the use of spiral welded pipes in strain based design related applications. Since the influence of the spiral weld on the plastic behaviour of the pipe is not yet fully understood, further research on this topic is required. An important aspect of this plastic behaviour is the effect of mixed mode loading on weld defects located in the helical weld. This paper elaborates on the first experimental trials to evaluate ductile tearing by means of single edge notched tensile specimen (SENT) testing with slanted notches. Tests were performed on two SENT specimens, one with a slanted notch and another with a straight notch in order to investigate the influence of mixed mode loading. The crack mouth opening displacement and crack extension were determined experimentally by means of digital image correlation and potential drop measurements respectively. The crack extension and the potential drop measurements were related by means of finite element simulations

Alchemical normal modes unify chemical space

In silico design of new molecules and materials with desirable quantum properties by high-throughput screening is a major challenge due to the high dimensionality of chemical space. To facilitate its navigation, we present a unification of coordinate and composition space in terms of alchemical normal modes (ANMs) which result from second order perturbation theory. ANMs assume a predominantly smooth nature of chemical space and form a basis in which new compounds can be expanded and identified. We showcase the use of ANMs for the energetics of the iso-electronic series of diatomics with 14 electrons, BN doped benzene derivatives (C$_{6-2x}$(BN)$_{x}$H$_6$ with $x = 0, 1, 2, 3$), predictions for over 1.8 million BN doped coronene derivatives, and genetic energy optimizations in the entire BN doped coronene space. Using Ge lattice scans as reference, the applicability ANMs across the periodic table is demonstrated for III-V and IV-IV-semiconductors Si, Sn, SiGe, SnGe, SiSn, as well as AlP, AlAs, AlSb, GaP, GaAs, GaSb, InP, InAs, and InSb. Analysis of our results indicates simple qualitative structure property rules for estimating energetic rankings among isomers. Useful quantitative estimates can also be obtained when few atoms are changed to neighboring or lower lying elements in the periodic table. The quality of the predictions often increases with the symmetry of system chosen as reference due to cancellation of odd order terms. Rooted in perturbation theory the ANM approach promises to generally enable unbiased compound exploration campaigns at reduced computational cost

The Tamm-Dancoff Approximation as the boson limit of the Richardson-Gaudin equations for pairing

A connection is made between the exact eigen states of the BCS Hamiltonian and the predictions made by the Tamm-Dancoff Approximation. This connection is made by means of a parametrised algebra, which gives the exact quasi-spin algebra in one limit of the parameter and the Heisenberg-Weyl algebra in the other. Using this algebra to construct the Bethe Ansatz solution of the BCS Hamiltonian, we obtain parametrised Richardson-Gaudin equations, leading to the secular equation of the Tamm-Dancoff Approximation in the bosonic limit. An example is discussed in depth.Comment: Submitted to the proceedings of the Group28 conference (Newcastle-upon-Tyne, UK). Journal of Physics: Conference Serie

Improving upon the efficiency of complete case analysis when covariates are MNAR.

Missing values in covariates of regression models are a pervasive problem in empirical research. Popular approaches for analyzing partially observed datasets include complete case analysis (CCA), multiple imputation (MI), and inverse probability weighting (IPW). In the case of missing covariate values, these methods (as typically implemented) are valid under different missingness assumptions. In particular, CCA is valid under missing not at random (MNAR) mechanisms in which missingness in a covariate depends on the value of that covariate, but is conditionally independent of outcome. In this paper, we argue that in some settings such an assumption is more plausible than the missing at random assumption underpinning most implementations of MI and IPW. When the former assumption holds, although CCA gives consistent estimates, it does not make use of all observed information. We therefore propose an augmented CCA approach which makes the same conditional independence assumption for missingness as CCA, but which improves efficiency through specification of an additional model for the probability of missingness, given the fully observed variables. The new method is evaluated using simulations and illustrated through application to data on reported alcohol consumption and blood pressure from the US National Health and Nutrition Examination Survey, in which data are likely MNAR independent of outcome