How Useful Is an Asian Currency Unit (ACU) Index for Surveillance in East Asia?

An Asian Currency Unit (ACU) index is constructed using an alternative procedure which minimizes a basket or portfolio of assets expressed in terms of national currencies. Using this estimated ACU index and an ACU Deviation Indicator, the main finding of this study based on the current trajectory of East Asian currencies relative to this regional ACU average or benchmark is that there is a formation of two contrasting groups of countries in the region - one a group of strong currencies and the other a group of weak currencies. We emphasize that the implication of this contrasting trajectory in East Asian intra-regional exchange rates is to disturb the competitive trading relationships in the region which may result in wasteful beggar-thyneighbor policies in the region. As emphasized by other recent studies, e.g., Kawai and Takagi (2012), the region needs a kind of framework for exchange rate policy coordination that will promote intra-regional exchange rate stability. We suggest several ways in which the region can capitalize on using this ACU index in the immediate term for surveillance purposes, particularly, for purposes of assessing "over- and undervaluation" of the individual currencies from the regional ACU average and for flagging emerging vulnerabilities in individual economies in the region

Deriving priorities from inconsistent PCM using network algorithms

In several multiobjective decision problems Pairwise Comparison Matrices (PCM) are applied to evaluate the decision variants. The problem that arises very often is the inconsistency of a given PCM. In such a situation it is important to approximate the PCM with a consistent one. One of the approaches is to minimize the distance between the matrices, most often the Euclidean distance. In the paper we consider the problem of minimizing the maximum distance. After applying the logarithmic transformation we are able to formulate the obtained subproblem as a Shortest Path Problem and solve it more efficiently. We analyze the structure of the set of optimal solutions and prove some of its properties. This allows us to provide an iterative algorithm that results in a unique, Pareto-efficient solution