Accounting for unobserved individual heterogeneity in spatial stochastic frontier models: the case of Italian innovative start-ups

Federica Galli

Spatial Economic Analysis, 2024, vol. 19, issue 4, 620-645

Abstract: Spatial correlation and individual effects are two key sources of heterogeneity that should be handled in empirical applications investigating the productive performance of firms, especially when dealing with start-up activity. Therefore, in this work, we propose a fixed-effects spatial autoregressive stochastic frontier model for unbalanced panel data, we test the finite sample properties of our spatial estimator and we provide an empirical application on Italian innovative start-ups. The results of our analysis indicate that Italian start-ups are characterised by a significant level of global spatial dependence, especially overall and among firms belonging to the information and communication sector.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17421772.2024.2306953 (text/html)
Access to full text is restricted to subscribers.

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:taf:specan:v:19:y:2024:i:4:p:620-645

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RSEA20

DOI: 10.1080/17421772.2024.2306953

Access Statistics for this article

Spatial Economic Analysis is currently edited by Bernie Fingleton and Danilo Igliori

More articles in Spatial Economic Analysis from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().