JOURNAL ARTICLE
Is it all in Marshall, still? An appreciation of Marshall's contribution to modern economics.
Published In: Cambridge Journal of Economics, 2025, v. 49, n. 3. P. 385 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Konzelmann, Suzanne J; Pitelis, Christos N; Tomlinson, Philip R 3 of 3
Abstract
This article focuses on the centenary of Alfred Marshall's death and revisits his foundational contributions to modern economics, particularly through his 1890 work, *Principles of Economics*, which helped formalize the discipline and establish neoclassical economics. It highlights Marshall's distinctive approach that combined mathematical formalism with a strong emphasis on social, communitarian, and evolutionary aspects of economic life, including his insights on value theory, increasing returns to scale, knowledge as a production factor, and industrial districts. The article also introduces eight papers in a Special Issue that explore Marshall's philosophical and methodological perspectives, his less-explored contributions, and their contemporary relevance for economic theory and policy, especially in areas such as regional development, labor markets, and innovation ecosystems. While acknowledging Marshall's lasting influence, the article discusses limitations in his work, including his static analysis of inherently dynamic processes and the omission of transaction costs and intra-societal conflict, situating his legacy within ongoing economic debates and policy challenges.
Additional Information
- Source:Cambridge Journal of Economics. 2025/05, Vol. 49, Issue 3, p385
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:0309-166X
- DOI:10.1093/cje/beaf017
- Accession Number:186989445
- Copyright Statement:Copyright of Cambridge Journal of Economics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.