Income shifting by multinational enterprises as a source of mismeasurement in aggregate statistics

Serena Fatica; Wildmer Daniel Gregori; Serena Fatica; Wildmer Daniel Gregori

doi:10.3934/NAR.2024025

National Accounting Review

2024, Volume 6, Issue 4: 548-563. doi: 10.3934/NAR.2024025

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Research article

Income shifting by multinational enterprises as a source of mismeasurement in aggregate statistics

Joint Research Centre, European Commission, Via Enrico Fermi 2749, 21027 Ispra, Italy

Received: 20 May 2024 Revised: 14 November 2024 Accepted: 27 November 2024 Published: 16 December 2024
JEL Codes: E01, E24, F23

This paper studies income shifting by European multinational enterprises as a potential source of mismeasurement in aggregate statistics, with a focus on labour productivity. We use firm level data to implement different types of formulary apportionments and to reattribute earnings among entities of multinational groups operating across the European Union (EU). The results suggest that income shifting affects the measurement of the output-per-worker in the corporate sector. Bottom-up approaches grounded in representative microdata can improve its computation.
- mismeasurement,
- official statistics,
- multinational enterprises,
- income shifting,
- labour productivity,
- firm-level data
Citation: Serena Fatica, Wildmer Daniel Gregori. Income shifting by multinational enterprises as a source of mismeasurement in aggregate statistics[J]. National Accounting Review, 2024, 6(4): 548-563. doi: 10.3934/NAR.2024025

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Abstract

This paper studies income shifting by European multinational enterprises as a potential source of mismeasurement in aggregate statistics, with a focus on labour productivity. We use firm level data to implement different types of formulary apportionments and to reattribute earnings among entities of multinational groups operating across the European Union (EU). The results suggest that income shifting affects the measurement of the output-per-worker in the corporate sector. Bottom-up approaches grounded in representative microdata can improve its computation.

References

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