Research output: Contribution to journal › Article › peer-review
Determinants of growth of small high-tech companies in transition economies. / Kravchenko, Nataliya; Goryushkin, Anton; Ivanova, Anastasiya et al.
In: Model Assisted Statistics and Applications, Vol. 12, No. 4, 01.01.2017, p. 399-412.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Determinants of growth of small high-tech companies in transition economies
AU - Kravchenko, Nataliya
AU - Goryushkin, Anton
AU - Ivanova, Anastasiya
AU - Khalimova, Sofia
AU - Kuznetsova, Svetlana
AU - Yusupova, Almira
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
KW - best subsets approach JEL Classification Codes: C10
KW - determinants of growth
KW - High-technology firms
KW - multiple regression
KW - O14
KW - O30
KW - Russia
UR - http://www.scopus.com/inward/record.url?scp=85039157395&partnerID=8YFLogxK
U2 - 10.3233/MAS-170407
DO - 10.3233/MAS-170407
M3 - Article
AN - SCOPUS:85039157395
VL - 12
SP - 399
EP - 412
JO - Model Assisted Statistics and Applications
JF - Model Assisted Statistics and Applications
SN - 1574-1699
IS - 4
ER -
ID: 10065552