Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Statistical Models in Finance and Insurance
Guest editors: Arkady Shemyakin and Vladimir Ladyzhets
Article type: Research Article
Authors: Kravchenko, Nataliya* | Goryushkin, Anton | Ivanova, Anastasiya | Khalimova, Sofia | Kuznetsova, Svetlana | Yusupova, Almira
Affiliations: Institute of Economics and Industrial Engineering SB RAS, Novosibirsk State University, Novosibirsk, Russia
Correspondence: [*] Corresponding author: Nataliya Kravchenko, Institute of Economics and Industrial Engineering SB RAS, Novosibirsk State University, Novosibirsk, Russia. E-mail: natakravchenko20@mail.ru.
Abstract: High-technology business acts as an important driver of any economy. Microeconomic factors influencing employment in small high-technology companies are identified and assessed in the paper. The case of high-technology manufacturing and knowledge-intensive services in Russian transition economy is discussed. The empirical part of this research is based on data provided by Business Environment and Enterprise Performance Survey (BEEPS). A two-step assessment procedure was applied in order to determine and estimate the factors of growth. Significant factors were selected with the help of best subsets regression and then these factors were further analyzed using OLS. Such an approach enables an increased explanatory power of the obtained results. It was found that younger companies have greater influence on job creation than older ones. Significant differences in growth factors between companies in high-technology manufacturing and knowledge-intensive services were demonstrated. This difference constitutes a new result in the research of growth of high-technology companies in transition economies. The suggested model could help to construct the companies’ rating, which would be useful for investors in the emerging markets with high volatility of assets’ prices and lack of information for investment analysis.
Keywords: High-technology firms, determinants of growth, Russia, multiple regression, best subsets approach JEL Classification Codes: C10, O30, O14
DOI: 10.3233/MAS-170407
Journal: Model Assisted Statistics and Applications, vol. 12, no. 4, pp. 399-412, 2017
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl