Properties of an approximate hazard transform

The calculation of the exact reliability of complex systems is a difficult and tedious task. Consequently simple approximating techniques have great practical value. The hazard transform of a system is an invertible transformation of its reliability function which is convenient and useful in both applied and theoretical reliability work. A simple calculus for finding an approximate hazard transform for systems formed by series and parallel combinations of components is extended so that it can be used for any coherent system. The extended calculus is shown to lead to conservative approximations. A first order version of the extended calculus is also discussed. This method of approximation is even more simple to use, but is not always conservative. Examples of its application indicate that it is capable of giving quite accurate results.     

Military Expenditure,Economic Growth and Heterogeneity

This paper examines the impact of military expenditure on economic growth on a large balanced panel, using an exogenous growth model and dynamic panel data methods for 106 countries over the period 1988–2010. A major focus of the paper is to consider the possibility group heterogeneity and non-linearity. Having estimated the model for all of the countries in the panel and finding that military burden has a negative effect on growth in the short and long run, the panel is broken down into various groupings based upon a range of potentially relevant factors, and the robustness of the results is evaluated. The factors considered are different levels of income, conflict experience, natural resources abundance, openness and aid. The estimates for the different groups are remarkably consistent with those for the whole panel, providing strong support for the argument that military spending has adverse effects on growth. There are, however, some intriguing results that suggest that for certain types of countries military spending has no significant effect on growth.     

Staying Power and the American Future: Problems of Primacy,Policy, and Grand Strategy

Many scholars, strategists and pundits contend that the US is in decline. They argue that America's national capabilities are significantly eroding, and that with the rise of important regional powers, its primacy in world affairs is rapidly diminishing as well. Yet America continues to possess significant advantages in critical sectors such as economic size, technology, competitiveness, demography, force size, power projection, military technology, and in the societal capacity to innovate and adapt. This article argues that the nature of material problems has been overstated, and that the US should be able to withstand modest erosion in its relative strength for some time to come without losing its predominant status. Instead, where limits to American primacy do exist, they are as or more likely to be ideational as they are material. The problem inheres as much or more in elite and societal beliefs, policy choices, and political will, as in economic, technological or manpower limitations at home, or the rise of peer competitors abroad.     

A stock redistribution model

Multi-depot supply systems are subject to stock distribution imbalances; i. e., the fraction of total system stock located at a depot may be too small to support the fraction of system demand expected to be placed on it. In the supply system of concern, a cutomer is always satisfied if there is stock anywhere in the system. Stock redistributions to correct imbalances may reduce both transportation costs and customer waiting times. A model for determining optimum redistribution quantities is formulated, and a practical method of solution for the two depot case is described. Selected numerical illustrations are given.     

MILITARY EXPENDITURE AND GRANGER CAUSALITY: A CRITICAL REVIEW

A large literature has used tests for Granger (1969) non‐causality, GNC, to examine the interaction of military spending with the economy. Such tests answer a specific although quite limited question: can one reject the null hypothesis that one variable does not help predict another? If one can reject, there is said to be Granger causality, GC. Although the limitations of GNC tests are well known, they are often not emphasised in the applied literature and so may be forgotten. This paper considers the econometric and methodological issues involved and illustrates them with data for the US and other countries. There are three main issues. First, the tests may not be informative about the substantive issue, the interaction of military expenditure and the economy, since Granger causality does not correspond to the usual notion of economic causality. To determine the relationship of the two notions of causality requires an identified structural model. Second, the tests are very sensitive to specification. GNC testing is usually done in the context of a vector autoregression, VAR, and the test results are sensitive to the variables and deterministic terms included in the VAR, lag length, sample or observation window used, treatment of integration and cointegration and level of significance. Statistical criteria may not be very informative about these choices. Third, since the parameters are not structural, the test results may not be stable over different time periods or different countries.