Numerical Comparison Between Different Empirical Prediction Intervals Under the Fay-Herriot Model

Recently, an empirical best linear unbiased predictor is widely used as a practical approach to small area inference. It is also of interest to construct empirical prediction intervals. However, we do not know which method should be used from among the several existing prediction intervals. In this article, we first obtain an empirical prediction interval by using the residual maximum likelihood method for estimating unknown model variance parameters. Then we compare the later with other intervals with the residual maximum likelihood method. Additionally, some different parametric bootstrap methods for constructing empirical prediction intervals are also compared in a simulation study.     

Does affective forecasting change motivation for disaster preparedness? Motivation one month after a hypothetical earthquake / ¿Influye la predicción afectiva en la motivación para la preparación ante las catástrofes? La motivación un mes después de un terremoto hipotético

The present study examined how disaster preparedness would change after people predicted their affective reactions in the event of a major earthquake. In Study 1, participants (N = 255) completed an assessment of disaster preparedness. One week later, participants predicted their thoughts and feelings if a major earthquake were to strike, and then responded to the motivation measure. Study 2 (N = 129) examined the status of participants’ motivation after one month. The results showed that greater motivation was only seen immediately after affective forecasting, and the same level of motivation was not maintained after one month. When people imagine a potential earthquake the expected negative affective reactions are overestimated. Disaster preparedness allows people to mitigate their future negative affective reactions. In order to avoid these affective reactions, affective forecasters had greater motivation for disaster preparedness.