Why has no bootstrapping being applied to assess standard errors of indices?

TRIM uses analytical methods to calculate standard errors. Re-sampling methods, such as bootstrapping, may also generate standard errors or confidence intervals. Bootstrapping is not implemented in TRIM because (1) the processing time would be too long for large datasets and (2) it is difficult to apply in case of models with covariates, because it is uncertain whether these models can be estimated for each separate bootstrap sample.