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Inference with Few Heterogeneous Clusters
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DOI：10.1162/REST_a_00545.png)
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摘要
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Suppose estimating a model on each of a small number of potentially heterogeneous clusters yields approximately independent, unbiased, and Gaussian parameter estimators. We make two contributions in this setup. First, we show how to compare a scalar parameter of interest between treatment and control units using a two-sample t-statistic, extending previous results for the one-sample t-statistic. Second, we develop a test for the appropriate level of clustering; it tests the null hypothesis that clustered standard errors from a much finer partition are correct. We illustrate the approach by revisiting empirical studies involving clustered, time series, and spatially correlated data.
Keyword:
PANEL-DATA
ROBUST INFERENCE
IN-DIFFERENCES
TIME-SERIES
T-TEST
HETEROSKEDASTICITY
TESTS
ERRORS
BOUNDS
VARIABLES
期刊
IF:
6.8
论文数:
3.6K
被引数:
2.1W
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ECONOMETRICAIF7.1
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