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Tagging and Taxing: The Optimal Use of Categorical and Income Information in Designing Tax/Transfer Schemes
Author(s) -
Immonen Ritva,
Kanbur Ravi,
Keen Michael,
Tuomala Matti
Publication year - 1998
Publication title -
economica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.532
H-Index - 65
eISSN - 1468-0335
pISSN - 0013-0427
DOI - 10.1111/1468-0335.00122
Subject(s) - categorical variable , revenue , economics , constraint (computer aided design) , transfer (computing) , tax revenue , microeconomics , econometrics , relation (database) , income tax , public economics , computer science , mathematics , data mining , machine learning , finance , geometry , parallel computing
This paper explores aspects of the optimal design of tax/transfer schemes that involve elements of both ‘tagging’ (the use of categorical benefits) and ‘means‐testing’ (income‐relation of benefits). Simulations suggest a striking qualitative dissimilarity between the group‐specific schedules optimally imposed on poorer and richer groups: broadly speaking, the optimal marginal tax rate is decreasing in income among the latter but increasing among the former. This latter observation, potentially important for policy, runs counter to the conventional wisdom from previous simulations. The reconciliation, we argue, lies in the role played in optimal tax design by the revenue constraint.