A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

Awareness of the requested quantity and characteristics of emergency supplies is crucial for facilitating an efficient relief operation. With the aim of focusing on the quantitative study of immediate food supplies, this article estimates the numerical autoregressive integrative moving average (ARIMA) model based on the actual data of 14 key commodities in the Sendai City of Japan during the 2011 Tohoku earthquake. Although the temporal patterns of key food commodity groups are qualitatively similar, the results show that they follow different ARIMA processes, with different autoregressive moving averages and difference order patterns. A key finding is that 3 of the 14 items are significantly related to the number of temporary residents in shelters, revealing that the relatively low number of different items makes it easier to deploy these key supplies or develop regional purchase agreements so as to promptly obtain them from distributors.

Testing For Weak-Level Efficiency In The Secondary Market For Developing Country Debt

This paper investigates the presence of weak level efficiency in the secondary market for developing country debt y modeling as ARIMA processes debt price variations of eight large debtor countries that were actively traded during the period January 1986 to December 1992. The analysis suggests that in some cases the secondary market for developing-country debt was weakly inefficient and that there existed at least one trading rule capable of generating above-average returns. Moreover, the narrowing of above-average returns in the period following the announcement of the Brady Plan suggests that the secondary market for developing country debit became more efficient, possibly due to a reduction in default risk and an increase in the availability of timely investment information.