CHOOSING GENOCIDE: ECONOMIC PERSPECTIVES ON THE DISTURBING RATIONALITY OF RACE MURDER

An economic theory of genocide is presented with application to Rwanda‐1994. The theory considers ‘macro’ conditions under which an authority group chooses genocide and ‘micro’ conditions that facilitate the spread of genocide. From the macro perspective, a bargaining model highlights four rational explanations for an authority’s choice of genocide: prevention of loss of power, indivisibility, elimination of a persistent rival, and political bias. From the micro perspective, an evolutionary game model shows how supporters of genocide gain the upper hand in group dynamics over resisters and bystanders. The theory and application suggest that the conditions for genocide are not exceptional.     

THE FRAGILE TRADITION OF NUCLEAR RESTRAINT

The Tradition of Non-Use of Nuclear Weapons by T.V. Paul. Stanford University Press, 2009. 319 pages, $29.95.     

Helpless or Deliberate Bystander: American Policy towards South Vietnam's Military Coups, 1954–1975

The USA's role in fomenting and responding to military coups remains an understudied and politically contentious subject despite it being a recurring foreign policy problem exemplified most recently in both Egypt and Mali. To the extent this topic has been addressed in any depth by scholars, it is mainly limited to an examination of a small number of coups that occurred during the Cold War that the CIA was accused of sponsoring. However, this emphasis on well-known cases to the exclusion of lesser-known cases has resulted in a biased view of omnipotent US power. This limitation is reflected in the case of South Vietnam, in which the focus has been placed on the 1963 coup that overthrew President Ngo Dinh Diem, whereas the numerous other coups that occurred have received little or no attention. In this article, a more inclusive approach will be taken in which US policy will be examined with respect to all of the main coups and coup attempts that occurred during the period 1954–1975.     

End effects in capacity expansion models with finite horizons

Capacity expansion models are typically formulated in the context of some finite horizon. Because the firm lasts longer than the horizon, a bias can enter into the optimal solution from the model horizon chosen. Recently, Grinold [8] has proposed a “dual-equilibrium method” for ameliorating possible distortions. Although the dual-equilibrium method has superior analytical properties to other methods, it is conceptually more complex. In this paper it is shown that there are situations where the “primal-equilibrium” approach of Manne [15] provides equivalent results and that the use of annualized capital costs in the objective function, although somewhat less efficient, results in a similar model.     

Book reviews

Soviet Nuclear Strategy from Stalin to Gorbachev: a Revolution in Soviet Military and Political Thinking. By Honore M. Catudal. Mansell, London (1988), ISBN 0–7201–2000–4, £25.00

The Military: More Than Just a Job? Edited by Charles C. Moskos and Frank R. Wood. Pergamon‐Brassey's, London (1988), ISBN 0–08–034321‐X, £17.00 ($30.00)

Douglas Haig, 1861–1928. By Gerard J. de Groot. Unwin Hyman, London (1988), ISBN 004 4401922, £20.00

Defence Policy Making. A Comparative Analysis. Edited by G. M. Dillon. Leicester University Press, Leicester (1988), ISBN 0–715–1268–5, £10.95

The Future of U.K. Air Power. Edited by P. Sabin. Brassey's, London (1988), ISBN 0–08–035825‐X (hardcover), 0–08–036256–7 (flexicover), hardcover £18.95 ($34.00), flexicover £9.95 ($17.95)     

Statistical analysis of very high-dimensional data sets of hierarchically structured binary variables with missing data: An application to marine corps readiness evaluations

The present analysis deals with very high-dimensional data sets, each one containing close to 900 binary variables. Each data set corresponds to an evaluation of one complex system. These data sets are characterized by large portions of missing data where, moreover, the unobserved variables are not the same in different evaluations. Thus, the problems which confront the statistical analysis are those of multivariate binary data analysis, where the number of variables is much larger than the sample size and in which missing data varies with the sample elements. The variables, however, are hierarchically structured and the problem of clustering variables to groups does not exist in the present study. In order to motivate the statistical problem under consideration, the Marine Corps Combat Readiness Evaluation System (MCCRES) is described for infantry battalions and then used for exposition. The present article provides a statistical model for data from MCCRES and develops estimation and prediction procedures which utilize the dependence structure. The E-M algorithm is applied to obtain maximum-likelihood estimates of the parameters of interest. Numerical examples illustrate the proposed methods.