Corporate Restructuring and Creative Destruction

Natalia Kuosmanen, Timo Kuosmanen and Terhi Maczulskij

No 177, ETLA Reports from The Research Institute of the Finnish Economy

Abstract: Abstract A substantial share of firm entries and exits observed in administrative data occur through mergers, acquisitions, and other forms of corporate restructuring rather than genuine market entry or exit. This report examines the association of labor productivity and corporate restructuring. We utilize register-based data of worker flows to develop a more granular distinction of genuine entries and exits from restructuring-related events. Our results demonstrate that the average labor productivity of acquiring firms drops on average 23 percent immediately after the acquisition, or even 30 percent in the manufacturing industries. In addition, we find that restructuring entry and exit of firms does not follow the conventional pattern of creative destruction. To support productivity enhancing structural change, it is essential to distinguish between genuinely new economic activity and the reorganization of existing activity.

Keywords: Corporate restructuring; Firm dynamics; Labor productivity; Mergers and acquisitions; Worker flows (search for similar items in EconPapers)
JEL-codes: D24 L25 L60 O47 (search for similar items in EconPapers)
Pages: 14 pages
Date: 2026-05-19
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.etla.fi/wp-content/uploads/ETLA-Raportit-Reports-177.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rif:report:177

Ordering information: This working paper can be ordered from
https://www.etla.fi/ ... li-luovassa-tuhossa/

Access Statistics for this paper

More papers in ETLA Reports from The Research Institute of the Finnish Economy Contact information at EDIRC.
Bibliographic data for series maintained by Kaija Hyvönen-Rajecki ().