TY  - BOOK
AU  - Paz,Lourenço S.
AU  - West,James E.
ED  - National Bureau of Economic Research.
TI  - Should We Trust Clustered Standard Errors?  A Comparison with Randomization-Based Methods
T2  - NBER working paper series
PY  - 2019///
CY  - Cambridge, Mass.
PB  - National Bureau of Economic Research
N1  - June 2019; Hardcopy version available to institutional subscribers
N2  - We compare the precision of critical values obtained under conventional sampling-based methods with those obtained using sample order statics computed through draws from a randomized counterfactual based on the null hypothesis.  When based on a small number of draws (200), critical values in the extreme left and right tail (0.005 and 0.995) contain a small bias toward failing to reject the null hypothesis which quickly dissipates with additional draws.  The precision of randomization-based critical values compares favorably with conventional sampling-based critical values when the number of draws is approximately 7 times the sample size for a basic OLS model using homoskedastic data, but considerably less in models based on clustered standard errors, or the classic Differences-in-Differences.  Randomization-based methods dramatically outperform conventional methods for treatment effects in Differences-in-Differences specifications with unbalanced panels and a small number of treated groups
UR  - https://www.nber.org/papers/w25926
UR  - http://dx.doi.org/10.3386/w25926
ER  -