Abstract
In this paper, we take a functional errors-in-variables approach to modeling longitudinal duration data containing observed inconsistencies. This approach separates the problem into two parts: an errors-in-variables problem and an estimation problem. This approach also enables us to develop measures of the effect of the data inconsistencies on the parameter estimates from a duration model. One measure is the loss in precision in the parameter estimates that results from the inconsistencies. We refer to the proportion of parameter variances that is due to the inconsistencies in the data as information loss. The second is a distance measure which is used to provide information about how close we are to a consistent estimator. An example is provided using a four-month panel of Current Population Survey data.
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