Government Expenditure in the DINA Framework: Allocation Methods and Consequences for Post-Tax Income Inequality

Lukas Riedel and Holger Stichnoth

Working Papers of BETA from Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg

Abstract: Constructing measures of post-tax income inequality that are consistent with national accounts requires the allocation of the entirety of government expenditure to individuals. About half of government expenditure in the United States takes the form of in-kind collective expenditure (e.g., education, defense, infrastructure). The dominant assumption in the literature is to allocate this expenditure proportionally to post-tax cash income. We show that the gap in post-tax income shares between the Top 10% and Bottom 50% in the United States is reduced by half (from about 20 to 10 percentage points in recent years) when this assumption is replaced by a lump-sum allocation. We further provide direct evidence on how a substantial part of collective expenditure is actually distributed. When adopting the cross-sectional perspective of the Dina approach, we find that public education spending goes disproportionately to the bottom half of the income distribution. A lump-sum allocation provides a good approximation. Moving beyond the crosssection, we find that public education expenditure is positively correlated with both lifetime earnings and parents’ socio-economic status. Keywords: inequality, redistribution, education, in-kind transfers.

Keywords: inequality; redistribution; education; in-kind transfers. (search for similar items in EconPapers)
JEL-codes: D31 H41 H52 I24 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-pub
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Government expenditure in the DINA framework: Allocation methods and consequences for post-tax income inequality (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:ulp:sbbeta:2022-06

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