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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Python Source Code - 8.3 KB - MD5: 5f7cf40181ec848f9ea696fb4b2448e6
reads data from PSZ and AS spreadsheets, CBO .csv files, and produces alternate versions of Figure 3 (Figures A1 & A2) that compares PSZ vs AS for Before-vs-After-Tax income (not consistent rankings) and for PSZ Factor Income and Pre-Tax ('hybrid') Income
Python Source Code - 17.2 KB - MD5: e035c2c394ba8b324db063678989a83a
reads data from PSZ, AS, and CBO spreadsheets, and produces Figures 5, A3, A4
Python Source Code - 18.2 KB - MD5: 520131dd28e03ed3491f0764bbee63ff
reads data from PSZ and AS spreadsheets, and produces Figures 6, 7, A5
Python Source Code - 16.6 KB - MD5: 24d1ad0bb2ee1832c6f0b08f444bb678
reads data from AS spreadsheet, and produces Figure 8
Tabular Data - 146.0 KB - 9 Variables, 1640 Observations - UNF:6:h6XzYQA/3tC/LnRPWxS8Bw==
- CBO data, downloaded November 2022 from https://www.cbo.gov/publication/58353 entry 'Additional Data for Researchers (zip file)'
Tabular Data - 146.0 KB - 9 Variables, 1640 Observations - UNF:6:7DHF/SPxV7bq1QkvTij1/Q==
- CBO data, downloaded November 2022 from https://www.cbo.gov/publication/58353 entry 'Additional Data for Researchers (zip file)'
MS Excel Spreadsheet - 4.9 MB - MD5: a2d10dd5060b8311cd52a03458cbbd8e
- Spreadsheet with detailed data from Piketty, Thomas, Emmanuel Saez, and Gabriel Zucman. 2018. “Distributional National Accounts: Methods and Estimates for the United States.” Quarterly Journal of Economics 133 (2): 553–609. https://doi.org/10.1093/qje/qjx043. - Downloaded August 2023 from https://gabriel-zucman.eu/usdina/ (listed as 'Tables II:...
Markdown Text - 2.3 KB - MD5: 3d6560c9deb0e26a54c1b8b503154523
Python Source Code - 5.4 KB - MD5: 625d8969ec4f114087b187d3692e7c4f
reads data from PSZ and AS spreadsheets, calculates and prints Table 1
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