Inference with Large Clustered Datasets

Inference using large datasets is not nearly as straightforward as conventional econo- metric theory suggests when the disturbances are clustered, even with very small intra- cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would if the observations were independent. More- over, inferences become increasingly unreliable as the dataset gets larger. These asser- tions are based on an extensive series of estimations undertaken using a large dataset taken from the U.S. Current Population Survey.


Issue Date:
2016-09
Publication Type:
Working or Discussion Paper
Record Identifier:
http://ageconsearch.umn.edu/record/274691
Language:
English
Total Pages:
18
Series Statement:
Working Paper No. 1365




 Record created 2018-06-29, last modified 2018-06-29

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