Before revision:  Our findings are relevant even for settings in which the number of treated units is usually considered as large enough to rely on clustered robust standard errors.
After revision:  These alternative inference methods are valid even when the relevant distance metric across units is unavailable. Moreover, they may be relevant alternatives even for settings in which the number of treated units is usually considered as large enough to rely on clustered robust standard errors.