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Testing Rank Similarity
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DOI：10.1162/REST_a_00675.png)
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We introduce a test of the rank invariance or rank similarity assumption common in treatment effects and instrumental variables models. The test probes the implication that the conditional distribution of ranks should be identical across treatment states using a regression-based test statistic. We apply the test to data from the Tennessee STAR class-size reduction experiment and show that systematic slippages in rank can be important statistically and economically.
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INSTRUMENTAL VARIABLE ESTIMATION
QUANTILE REGRESSION
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