Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/248348 
Year of Publication: 
2021
Series/Report no.: 
WIDER Working Paper No. 2021/134
Publisher: 
The United Nations University World Institute for Development Economics Research (UNU-WIDER), Helsinki
Abstract: 
The quality of data on employment income is explored using Tanzanian and Zambian household survey datasets. The extent of missing and implausible income data is assessed and four different methods are applied to impute missing or implausible values. The four imputation methods are also applied to artificial missing data for Tanzania and Zambia, and-using one approach-for a South Africa dataset. Post-imputation results are assessed. It is argued that the treatment of missing data cannot be generalized, and that tax compliance should also be taken into account when assessing the validity of a microsimulation model's simulation of direct taxes.
Subjects: 
income imputation
microsimulation
missing data
Tanzania
Zambia
JEL: 
C63
C81
H24
D31
Persistent Identifier of the first edition: 
ISBN: 
978-92-9267-074-0
Additional Information: 
Update (September 2021): The technical note mentioned in the text is available as WIDER Technical Note 2021/15 here: https://doi.org/10.35188/UNU-WIDER/WTN/2021-15
Document Type: 
Working Paper

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