*! version 1.0.0 14sept2025

undid_stage_three

undid

undid - Estimate difference-in-differences with unpoolable data.

Command Description

undid_stage_three Takes in all of the filled diff df CSV files and uses them to compute group level ATTs as well as the aggregate ATT and its standard errors and p-values.

Required parameters:

- dir_path : A string specifying the filepath to the folder where all of the filled diff CSV files for this analysis are stored.

Optional parameters:

- agg : A string which specifies the aggregation methodology for computing the aggregate ATT. Options are:
-> "silo", "g", "gt", "sgt", "time", or "none". Defaults to "g".

- weights : A string, determines which of the weighting methodologies should be used. Options are:
-> "none", "diff", "att", or "both". Defaults to the weighting methodology specified in the filled diff CSV files.

- covariates : Integer, either 1 (true) or 0 (false), which specifies whether to use the `diff_estimate` column or the `diff_estimate_covariates` column from the filled diff df CSV files when computing ATTs.
Setting to 1 (true) selects the `diff_estimate_covariates` column and 0 (false) selects the `diff_estimate` column. Defaults to 0 (false).

- use_pre_controls : Integer, either 1 (true) or 0 (false), which declares if the not-yet-treated differences from treated silos should be used as controls when computing relevant sub-aggregate ATTs.
Defaults to 0.

- nperm : An integer specifying the number of unique random permutations to consider when performing the randomization inference. Defaults to 1000.

- verbose : An integer value that controls progress reporting frequency during the randomization inference procedure. When set to a positive integer N, progress updates will be displayed every N permutations.
Setting to 0 disables the progress messages. Defaults to 0.

- seed : An integer value, the seed used for randomization inference.

- max_attempts : An integer, sets the maximum number of attempts to find a new unique random permutations during the randomization inference procedure. Defaults to 100.

- check_anon_size : An integer, either 0 (false) or 1 (true), which if toggled on, displays which silos enabled the 'anonymize_weights' argument in stage two, and the respective 'anonymize_size' values.
Defaults to 0.

Syntax

undid_stage_three dir_path(string) agg(string) [weights(int) covariates(int) imputation(string) save_csv(int) filename(string) filepath(string) nperm(int) verbose(int)]

Examples

undid_stage_three,

filler filler

Author

Eric Jamieson

For more information about undid, visit the https://github.com/ebjamieson97/undid GitHub repository.

Citation

Please cite: Sunny Karim, Matthew D. Webb, Nichole Austin, Erin Strumpf. 2024. Difference-in-Differenecs with Unpoolable Data. https://arxiv.org/abs/2403.15910