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Territorial Servitization and Manufacturing Productivity Growth in Mexico: A Spatial Panel Data Approach

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  • Jose Antonio Cabrera‐Pereyra

Abstract

While most existing research on territorial servitization has focused on its potential to revitalize mature industrial regions, much less has been said about its potential to incentivize knowledge‐driven changes in manufacturing across developing economies. This article contributes to this topic by analyzing evidence for territorial servitization processes in Mexico, adopting a spatial panel data model approach, which uncovers space‐time patterns to local‐regional servitization processes. Findings reveal servitization positively impacts manufacturing productivity. Results also signal the relevance of local industrial contexts, as well as firm conditions, as key factors to the presence of positive impacts on productivity due to KIBS‐manufacturing linkages, or manufacturing servitization.

Suggested Citation

  • Jose Antonio Cabrera‐Pereyra, 2025. "Territorial Servitization and Manufacturing Productivity Growth in Mexico: A Spatial Panel Data Approach," Growth and Change, Wiley Blackwell, vol. 56(3), September.
  • Handle: RePEc:bla:growch:v:56:y:2025:i:3:n:e70046
    DOI: 10.1111/grow.70046
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    References listed on IDEAS

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    1. Eduardo Sisti & Arantza Zubiaurre Goena, 2020. "Panel analysis of the creation of new KIBS in Spain: The role of manufacturing and regional innovation systems (RIS)," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 48, pages 37-50.
    2. Manuel Araya & Krisztina Horváth & Juan Carlos Leiva, 2020. "The role of county competitiveness and manufacturing activity on the development of business service sectors: A precursor to territorial servitization," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 48, pages 19-35.
    3. Jens Matthias Arnold & Beata Javorcik & Molly Lipscomb & Aaditya Mattoo, 2016. "Services Reform and Manufacturing Performance: Evidence from India," Economic Journal, Royal Economic Society, vol. 126(590), pages 1-39, February.
    4. Lombardi, Silvia & Santini, Erica & Vecciolini, Claudia, 2022. "Drivers of territorial servitization: An empirical analysis of manufacturing productivity in local value chains," International Journal of Production Economics, Elsevier, vol. 253(C).
    5. Lafuente, Esteban & Vaillant, Yancy & Vendrell-Herrero, Ferran, 2017. "Territorial servitization: Exploring the virtuous circle connecting knowledge-intensive services and new manufacturing businesses," International Journal of Production Economics, Elsevier, vol. 192(C), pages 19-28.
    6. Igor Roberto Amancio & Glauco Henrique de Sousa Mendes & Herick Fernando Moralles & Bruno Brandão Fischer & Eduardo Sisti, 2022. "The interplay between KIBS and manufacturers: a scoping review of major key themes and research opportunities," European Planning Studies, Taylor & Francis Journals, vol. 30(10), pages 1919-1941, October.
    7. Jeroen Content & Koen Frenken, 2016. "Related variety and economic development: a literature review," European Planning Studies, Taylor & Francis Journals, vol. 24(12), pages 2097-2112, December.
    8. Helmut Lütkepohl & Fang Xu, 2012. "The role of the log transformation in forecasting economic variables," Empirical Economics, Springer, vol. 42(3), pages 619-638, June.
    9. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).
    10. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    11. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    12. Jan Mutl & Michael Pfaffermayr, 2011. "The Hausman test in a Cliff and Ord panel model," Econometrics Journal, Royal Economic Society, vol. 14, pages 48-76, February.
    13. Amado Villarreal Gonzalez & Elizabeth A. Mack & Miguel Flores, 2017. "Industrial complexes in Mexico: implications for regional industrial policy based on related variety and smart specialization," Regional Studies, Taylor & Francis Journals, vol. 51(4), pages 537-547, April.
    14. John B Parr, 2002. "Agglomeration Economies: Ambiguities and Confusions," Environment and Planning A, , vol. 34(4), pages 717-731, April.
    15. Esteban Lafuente & Yancy Vaillant & Ferran Vendrell-Herrero, 2019. "Territorial servitization and the manufacturing renaissance in knowledge-based economies," Regional Studies, Taylor & Francis Journals, vol. 53(3), pages 313-319, March.
    16. Juliana Bonomi Santos, 2019. "Knowledge-intensive business services and innovation performance in Brazil," Innovation & Management Review, Emerald Group Publishing Limited, vol. 17(1), pages 58-74, September.
    17. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
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