Measuring defense conversion in Russian industry

This paper develops and implements a methodology for quantifying defense conversion in Russian manufacturing in the early 1990s. A two‐sector, three‐good model is employed to analyze the flows of resources from military to non‐military uses and applied to firm‐level survey data under alternative definitions of military production and the MIC. An aggregation framework is constructed to estimate the total quantity and change in Russian military production, the latter decomposed into intrafirm and intersectoral resource reallocation and overall industrial decline. Although there is evidence of substantial decline in military production, the data show little reallocation to productive civilian uses, neither within the MIC nor to other manufacturing sectors.     

Comment: Why “an identified systemic model of the democracy‐peace nexus” does not persuade*

In their article in this journal, James, Solberg and Wolfson (1999) challenge our findings that two states are more likely to have peaceful relations if they are both democratic. They claim to develop a simultaneous system of two equations showing that peace and democracy foster each other, and that the effect of peace in encouraging democracy is stronger than that of democracy on peace. Their analysis, however, is flawed. Their research design employs measures of dispute and joint democracy that are inferior to those now common in the literature, and their equation for predicting peace is not properly specified. These problems distort their results. Even so, their results provide evidence of the pacific benefits of democracy. Analyses we conduct with a more completely specified model reveal stronger support for the democratic “ peace. Furthermore, a test of the effect of interstate conflict on democracy should be done at the national (or monadic) level of analysis; but James et al. perform a dyadic analysis. In a monadic test using vector autoregression, we find that disputes make no contribution to explaining the character of regimes. Even with their dyadic method, their finding that peace promotes democracy is not robust Including a crucial control variable, the ratio of militarily relevant national capabilities, that James et al. omitted, dramatically alters their findings.     

When is model complexity too much? Illustrating the benefits of simple models with Hughes' salvo equations

The simulations that many defense analysts rely upon in their studies continue to grow in size and complexity. This paper contrasts the guidance that the authors have received—from some of the giants of military operations research—with the current practice. In particular, the analytic utility of Hughes' simple salvo equations is compared with that of the complex Joint Warfighting System (JWARS), with respect to JWARS' key performance parameters. The comparison suggests that a family of analytic tools supports the best analyses. It follows that smaller, more agile, and transparent models, such as Hughes' salvo equations, are underutilized in defense analyses. We believe that these models should receive more attention, use, and funding. To illustrate this point, this paper uses two very simple models (by modern standards) to rapidly generate insights on the value of information relative to force strength. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Approximations and empirics for stochastic war equations

The article develops a theorem which shows that the Lanchester linear war equations are not in general equal to the Kolmogorov linear war equations. The latter are time‐consuming to solve, and speed is important when a large number of simulations must be run to examine a large parameter space. Run times are provided, where time is a scarce factor in warfare. Four time efficient approximations are presented in the form of ordinary differential equations for the expected sizes and variances of each group, and the covariance, accounting for reinforcement and withdrawal of forces. The approximations are compared with “exact” Monte Carlo simulations and empirics from the WWII Ardennes campaign. The band spanned out by plus versus minus the incremented standard deviations captures some of the scatter in the empirics, but not all. With stochastically varying combat effectiveness coefficients, a substantial part of the scatter in the empirics is contained. The model is used to forecast possible futures. The implications of increasing the combat effectiveness coefficient governing the size of the Allied force, and injecting reinforcement to the German force during the Campaign, are evaluated, with variance assessments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.