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This paper introduces a test for the comparison of multiple misspecifed conditional interval models, for the case of dependent observations. Model accuracy is measured using a distributional analog of mean square error, in which the approximation error associated with a given model, say model i, for a given interval, is measured by the expected squared difference between the conditional confidence interval under model i and the "true" one. When comparing more than two models, a "benchmark"doi:10.1017/s0266466605050498 fatcat:dw2mck74ibg2dpcuk2off37gf4