Spatial Distribution of Knowledge-Intensive Industries in Hungary

Izabella Szakálné Kanó () and Zsófia Vas ()

Transition Studies Review, 2013, vol. 19, issue 4, 431-444

Abstract: Knowledge-intensive industries have attracted a great attention nowadays in researches because of its contribution to the development of knowledge-driven economy. They generate positive effects on the regional economy and have increasingly high importance in less developed regions, like Hungary. The identification of spatial distribution, the geographical co-location of knowledge-intensive economic activities is substantial to define potential leading industrial branches in regions. This paper aims to identify the spatial coherence and concentration of knowledge-intensive industries nationwide in Hungary at subregional level, and presents results using Ellison-Glaeser geographic concentration index and the measure of spatial autocorrelation with Moran index. Copyright CEEUN 2013

Keywords: Knowledge-intensive industry; Geographical concentration; Spatial agglomeration; Hungary; C10; O14; R12 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11300-013-0261-y (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:spr:trstrv:v:19:y:2013:i:4:p:431-444

Ordering information: This journal article can be ordered from
http://www.springer. ... ration/journal/11300

DOI: 10.1007/s11300-013-0261-y

Access Statistics for this article

Transition Studies Review is currently edited by G. Dominese

More articles in Transition Studies Review from Springer, Central Eastern European University Network (CEEUN)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().