Dynamics modelling of demand for educational service market in the case of kharkiv region - Danich, V. M.; Sokil , A. O. (Bulletin of V. N. Karazin Kharkiv National University Economic Series, 2018)
The work deals with methods of construction of models of long-term dynamics of potential demand in the market of educational services. The supply consists of higher educational institutions (universities) of a certain educational center (the regional center, as a rule), the demand is created by school leavers, applicants from other educational institutions of the cluster of regions – which create a set of regions or their geographical parts that are characterized by a certain socio-economic unity and surround the educational center. The key factor in demand is the demographic dynamics of the cluster. The information base of this dynamics is made up of statistical data on the birth rate, the number of pupils in the classes, on the basis of which the proportions of age or school groups are determined, which pass from year to year to the next age (school) level. The sources of such data is published information of the State Statistics Service of Ukraine, its regional branches, electronic information resources of the Ministry of Education and Science of Ukraine - EDEBO (Unified State Electronic Database on Education) and vstup.info (Information system "Competition"), university data, results of Surveys of the target groups. The modelling of dynamics is based on the use of the laws of resource conservation (the volume of the age level, hence the volume of demand varies depending on the influx and outflow of the age group of subjects), as well as on the methods of mathematical statistics in determining the coefficients of age changes,and certain trends of subjective preferences. Models are iterative schemes or difference equations with discreteness of one year. Statistical data on the number of pupils in classes for several consecutive years and data on fertility statistics make it possible to predict the number of school leavers for 10-17 years ahead, which in turn allows forecasting demand in the education market, providing a reliable long-term forecast of the number of entrants, students, Personnel and material situation of universities.