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Italian firms' geographical location in high-tech industries: A robust analysis

*Corresponding author for this work
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Research
 Peer-review

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Research
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 185-192 (8 pages)

Publication milestones

  • Published - 01/01/2011

Publication status

Published - 01/01/2011

Publisher

Kluwer Academic Publishers

Publication series

  • Publication series name: Studies in Classification, Data Analysis, and Knowledge Organization
    ISSN (Print): 1431-8814

ISBN (Print)

9783642133114

Publication IDs

  • Scopus: 84888255452

Host publication title

Classification and Multivariate Analysis for Complex Data Structures

Abstract

Recent debates in economic-statistical research concern the relationship between firms' performance and their capabilities to develop new technologies and products. Several studies argue that economic performance and geographical proximity strongly affect firms' level of technology. The aim of the paper is twofold. Firstly, we propose to generalize this approach and to develop a model to identify the relationship between the firm's technology level and some firm's characteristics. Secondly, we use an outlier detection method to identify units that affect the analysis results and the estimates stability. This analysis is implemented using a generalized regression model with a diagnostic robust approach based on forward search. The method we use reveals how the fitted regression model depends on individual observations and the results show how the firms' technology level is influenced by their geographical proximity.

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