TIME-VARYING CHARACTERISTICS OF SOUTH KOREA-UNITED STATES AND JAPAN-UNITED STATES MILITARY ALLIANCES UNDER CHINESE THREAT: A PUBLIC GOOD APPROACH

This paper investigates the nature of two military alliances under Chinese threat. The findings are as follows: First, South Korea does not consider China a significant threat while Japan and the United States have recognized China as a serious threat since the 1990s and the 2000s, respectively. Second, the relationship between South Korea and the United States is a true military alliance for all time periods, but the nature of the alliance has changed since the 1970s. Third, although Japan began to form an alliance relationship with the United States in the 1990s, Japan is considered a more significant ally by the United States. This paper implies that, should China provoke a military confrontation, it might be difficult to deduce a common solution among the three countries because of the different response to military threats from China.     

DOES MILITARY EXPENDITURE MATTER FOR INFLATION AND ECONOMIC GROWTH?

This paper sets up a monetary endogenous growth model, and uses it to explain the ambiguous linkage between the military burden and the inflation rate observed in existing empirical studies. It is found that an expansion in the military burden has an ambiguous effect on the inflation rate depending upon the relative extent of two conflicting forces. More specifically, if the increase in the marginal benefit from holding money exceeds (falls short of) the increase in the marginal product of private capital, the inflation rate will rise (fall) in response. Moreover, it is found that an increase in the military burden will stimulate the balanced growth rate, confirming Benoit’s famous empirical findings.     

ISS Recent publications

The popular adage has it that ‘prevention is better than cure’. Given the heavy and enduring costs of armed conflicts, there is no disputing the fact that making efforts to prevent them from breaking out in the first place is better than waiting until it is too late. This entails two things: conflict prevention measures and early warning systems. Anything that could be done to effectively address the root causes of a conflict before it turns violent may fit into the former, while the latter aims to identify threats to these elements so that effective conflict prevention measures can be taken. In other words, ensuring ‘human security’ is the thrust of the former, while the latter serves as a surveillance camera for any deficit in providing the different components of this ‘human security’. It is with these two important issues that this essay deals, with particular reference to West Africa.     

Demand forecasting by temporal aggregation

Demand forecasting performance is subject to the uncertainty underlying the time series an organization is dealing with. There are many approaches that may be used to reduce uncertainty and thus to improve forecasting performance. One intuitively appealing such approach is to aggregate demand in lower‐frequency “time buckets.” The approach under concern is termed to as temporal aggregation, and in this article, we investigate its impact on forecasting performance. We assume that the nonaggregated demand follows either a moving average process of order one or a first‐order autoregressive process and a single exponential smoothing (SES) procedure is used to forecast demand. These demand processes are often encountered in practice and SES is one of the standard estimators used in industry. Theoretical mean‐squared error expressions are derived for the aggregated and nonaggregated demand to contrast the relevant forecasting performances. The theoretical analysis is supported by an extensive numerical investigation and experimentation with an empirical dataset. The results indicate that performance improvements achieved through the aggregation approach are a function of the aggregation level, the smoothing constant, and the process parameters. Valuable insights are offered to practitioners and the article closes with an agenda for further research in this area. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 479–498, 2013     

Comparison between constant‐stress and step‐stress accelerated life tests under Time Constraint

By running life tests at higher stress levels than normal operating conditions, accelerated life testing (ALT) quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. In constant‐stress testing, a unit is tested at a fixed stress level until failure or the termination time point of test, whereas step‐stress testing allows the experimenter to gradually increase the stress levels at some prefixed time points during the test. In this work, the optimal k‐level constant‐stress and step‐stress ALTs are compared for the exponential failure data under complete sampling and Type‐I censoring. The objective is to quantify the advantage of using the step‐stress testing relative to the constant‐stress one. Assuming a log‐linear life–stress relationship with the cumulative exposure model for the effect of changing stress in step‐stress testing, the optimal design points are determined under C/D/A‐optimality criteria. The efficiency of step‐stress testing to constant‐stress one is then discussed in terms of the ratio of optimal objective functions based on the information matrix. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 00: 000–000, 2013