The National Tax Journal encourages authors of empirical papers to provide data and analysis sufficient for replication. Upon acceptance, authors should post the following on NTJ’s Dataverse: - Code and programs that can be used for replication, - Dataset(s) used to run the final models, and - “Readme” files detailing how data and programs are combined to generate the final analysis. Such files should include a description of how intermediate data files were used to create the final dataset. Authors who choose to post replication files for NTJ accepted papers are strongly encouraged to do so prior to submitting final files to the journal office for publication so that the link to the data can be included in the published paper. In that case, the following line (with unique identifier information) should be included at the end of the paper’s acknowledgment note: Data are provided through Dataverse at https://doi.org/XX.XXXX/XXX/XXXXXX
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

1 to 10 of 1,519 Results
Jun 24, 2025
Derby, Elena; Dowd, Connor; Mortenson, Jacob, 2025, "Replication Code for "Statistical Bias in Racial and Ethnic Disparity Estimates Using BIFSG"", https://doi.org/10.7910/DVN/F2HIWR, Harvard Dataverse, V1
This replication package provides code for the data analysis reported in "Statistical Bias in Racial and Ethnic Disparity Estimates Using BIFSG". The majority of data used in this paper comes from administrative tax data and proprietary data from the US Department of Housing and Urban Development. These data were accessed and handled solely by the...
R Syntax - 23.7 KB - MD5: 286848a353369b42219d38316e4a8e19
R Syntax - 44.7 KB - MD5: 66c1f803c1e1af091bd0bdcce858ce80
R Syntax - 21.4 KB - MD5: a7e932de808fde17f1b47b9c31294191
Jun 24, 2025
Coleman, Thomas; Weisbach, David, 2025, "Replication Data for How Much Does U.S. Fiscal System Redistribute?", https://doi.org/10.7910/DVN/M43QLB, Harvard Dataverse, V1, UNF:6:dPMA3GaWtN9Fx/6Mp9YRDA== [fileUNF]
Code and data repository for Coleman-Weisbach paper "How Much Does U.S. Fiscal System Redistribute?"
MS Excel Spreadsheet - 248.7 KB - MD5: 4a0f589530313aa332440cad522fd8ba
CBO data, downloaded November 2023 from https://www.cbo.gov/publication/58353 entry 'Supplemental Data'
MS Excel Spreadsheet - 7.4 MB - MD5: 48061ce531598dc41b7011c06d24e33c
Spreadsheet with detailed data from Auten, Gerald, and David Splinter. 2024. “Income Inequality in the United States: Using Tax Data to Measure Long-Term Trends.” Journal of Political Economy 132 (7): 2179–2227. https://doi.org/10.1086/728741. Auten & Splinter (2024) - Downloaded September 2024 from http://davidsplinter.com/AutenSplinter-IncomeI...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.