Abstract
In this article, we analyze a large database of job vacancies in Ukraine, webscrapped from Work.ua website in January–February 2017. The obtained dataset was processed with bag-of-words approach. Exploratory data analysis revealed that experience and city influence wages. For example, wages in the capital are much higher than in other cities. To explain variation in wages, we used three models to predict wages: multiple linear regression, decision tree and random forest; the latter has demonstrated the best explanatory power. Our work has confirmed the old finding by Mincer that experience is an important variable that explains wages. In fact, this factor was the most informative. Education, however, was an unimportant factor to determine wages. English, teamwork, sales skills, car driving and programming languages are the skills for which modern employers are willing to pay.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Mincer, J.: Schooling, Experience, and Earnings. National Bureau of Economic Research, New York (1974). Distributed by Columbia University Press, New York
Lemieux, T.: The Mincer Equation, Thirty Years after Schooling Experience, and Earnings. Center for Labor Economics, University of California-Berkeley, Berkeley (2003)
Del Carpio, X., Kupets, O., Muller, N., Olefir, A.: Skills for a Modern Ukraine. Directions in Development - Human Development. World Bank, Washington, D.C. (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Sinichenko, V., Shmihel, A., Zhuk, I. (2019). Explaining Wages in Ukraine: Experience or Education?. In: Chertov, O., Mylovanov, T., Kondratenko, Y., Kacprzyk, J., Kreinovich, V., Stefanuk, V. (eds) Recent Developments in Data Science and Intelligent Analysis of Information. ICDSIAI 2018. Advances in Intelligent Systems and Computing, vol 836. Springer, Cham. https://doi.org/10.1007/978-3-319-97885-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-97885-7_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97884-0
Online ISBN: 978-3-319-97885-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)