A Systematic Literature Review on the Relations between “Firm-Region Nexus” and Firm Productivity

Pierre-François Wilmotte, Didier Van Caillie, Isabelle Reginster, Marcus Dejardin and Jean-Marie Halleux

REGION, 2026, vol. 13, No 1, 21 pages

Abstract: An increasing number of studies focus on the impact of firm location on firm productivity. Here, location refers to localised resources or externalities available to firms. These studies have become possible due to advancements in firm-level data availability and productivity estimation methods. There is a growing need to better identify the effects of localised externalities -- "the firm-region nexus" -- on firms, which are the primary targets of many regional development policies. However, relying solely on administrative regions risks committing the ecological fallacy: attributing to all firms in a region the effects observed for a region as a whole. This article presents the state of the art as of 2025, highlighting key issues in this area of research. A total of 165 articles were selected, mainly published in the past decade. From a methodological perspective, there is no real consensus on the models utilised, whether to estimate productivity or to investigate the relationships between the "firm-region nexus" and firm productivity. Spatial integration is still not adequately taken into account: (a) Total Factor Productivity estimations do not account for spatial dependence among methodological concerns; (b) 70% of the articles do not discuss methodological issues linked to the use of firm locations. A deeper grasp of firm location, particularly the "head office bias", emerges as critical to improving the robustness of analyses. Quantifying the "firm-region nexus" remains heterogeneous across national and local contexts (diverging points of interest, data availability, etc.). Comparing the effects of various types of externalities across countries therefore appears ambitious. Some articles focus on the effect of one category of localised externalities, aiming not only to identify a relationship but also its type: spatial or temporal effect, linear or non-linear relationships, and threshold effects.

Date: 2026
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