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
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41 to 44 of 44 Results
Replication Data for: Race, Ethnicity, and Taxation of the Family: The Many Shades of the Marriage Penalty/Bonus
May 16, 2023
Leguizamon, J. Sebastian; Alm, James; Leguizamon, Susane, 2023, "Replication Data for: Race, Ethnicity, and Taxation of the Family: The Many Shades of the Marriage Penalty/Bonus", https://doi.org/10.7910/DVN/U6VILS, Harvard Dataverse, V1
Includes formatted data from CPS samples between 1991 and 2017. The do files include all the files needed to get the variables used in the graphs and tables. One of the do files has an example of the code used to generate the graphs from the variables created, but for brevity we do not include every one of those graphing files.
Replication Files for: "Bias in Tax Progressivity Estimates"
Jan 10, 2023
Koenig, Johannes, 2023, "Replication Files for: "Bias in Tax Progressivity Estimates"", https://doi.org/10.7910/DVN/4IRSWB, Harvard Dataverse, V1, UNF:6:DthlCzcnyhtth/5DsDt7/w== [fileUNF]
This replication archive provides the computer codes and final analysis files for the paper "Bias in Tax Progressivity Estimates".
Replication Code for Delivering aid to businesses through the payroll tax system: the case of the Employee Retention Credit
Replication Code for Delivering aid to businesses through the payroll tax system: the case of the Employee Retention Credit
Jan 5, 2023
Goodman, Lucas, 2023, "Replication Code for Delivering aid to businesses through the payroll tax system: the case of the Employee Retention Credit", https://doi.org/10.7910/DVN/89ZI4V, Harvard Dataverse, V1
This archive contains redacted code used in this paper. The data and unredacted code cannot be posted due to section 6103 of the Internal Revenue Code.
Replication Data for: Revealing Values
Jan 4, 2023
Embree, Robert, 2023, "Replication Data for: Revealing Values", https://doi.org/10.7910/DVN/XMVHEL, Harvard Dataverse, V1
This contains replication data for the paper "Revealing Values" by Robert Embree, published in the National Tax Journal in 2023. Included are TAXSIM output codes, state SOI data, and Matlab code to perform the inverse-optimum calculation. Data on underlying parameter estimates are also included. There is a Readme file as a Word file with instructio...
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