Forecasting the Demand in the Educational Services Market in Ukraine (on the Example of Admission Volumes to Ukrainian Higher Educational Establishments)

Authors

DOI:

https://doi.org/10.29038/2411-4014-2016-01-83-89

Keywords:

higher education, educational services market, demand, forecasting, parallel time series, correlation and regression analysis, point and interval estimation of forecast.

Abstract

The predictive estimate of the demand for higher educational services in Ukraine based on a regression model of depending on fertility rates is carriedout in the article. The article contains a review of the existing domestic and foreign publications on the theory and practice of forecasting the dynamics in the educational services market. The conclusion that most existing researches in Ukraine are theoretical and are not accompanied by the approbation of available methods in the solution of applied problems of forecasting the demand for university educational services is formulated. To predict the demand for higher educational services in Ukraine the main indicators of the quantitative assessment of potential and real demand for higher education are grounded. The methodology of forecasting the demand for university services based on the regression analysis of parallel time series of admission volumes to Ukrainian universities and fertility rates (with consideringthe lag) is used The results of evaluation of the adequacy of a built regression model, as well as the comparison of the confidence intervals of the forecast to the real admission volumes to Ukrainian universities give grounds to conclude that the offered approach to forecasting the demand for educational services is an effective tool of strategic management in higher education.

Published

2016-07-02

How to Cite

[1]
2016. Forecasting the Demand in the Educational Services Market in Ukraine (on the Example of Admission Volumes to Ukrainian Higher Educational Establishments). Economic journal of Lesya Ukrainka Volyn National University. 2, 6 (Jul. 2016), 83–89. DOI:https://doi.org/10.29038/2411-4014-2016-01-83-89.