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This paper compares two methods of analyzing aggregate data that is classified by period and age. Because there is a linear relationship among age, period, and cohort, it is not possible to distinguish the separate effects without employing an identifying assumption. The first method, which is applied in the economics literature, assumes that period effects are orthogonal to a linear time trend. The second method, which is applied in the statistics literature, assumes that the effect parameters change gradually. Simulation results suggest that the performances of both methods are comparable. The results of applying the second method to household saving rates suggest that period effects had a negligible influence in the United States but considerable influence in Japan. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper provides a framework for analyzing flood fatalities and injuries, and it describes the derivation of a generalized flood risk (i.e., flood consequences and their probabilities) function by introducing an integrated index (the number of residential buildings affected by a flood) that represents the major change in the power relation among the flood intensity, regional vulnerability, and resilience. Both the probabilities and the numbers of fatalities and injuries clearly increase significantly after the flood severity (in terms of the number of inundated buildings) passes a branch point. Below the branch point, it is still possible for fatalities and injuries to occur because of the variability in the data and the uncertainty in the predicted fatality values. The empirical models of fatalities and injuries due to floods in Japan suggested the usefulness in predicting fatalities and injuries and evaluating the efficacy of the warning or other emergency response measures. [ABSTRACT FROM AUTHOR]