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Estimating the transition time from school to university using a stochastic mortality model

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  • Stöver, Britta

Abstract

The sufficient provision of university places is of high sociopolitical importance as it facilitates the participation in higher education as well as the accumulation of human capital both being important factors for wealth and economic growth. The aim of this paper is to use the concept of mortality rates for forecasting the transition from school graduates into university in order to enrich and enhance the planning of the needed university places for first-year students. The transition rates differentiated in 16 Federal States and two types of university entrance qualifications were interpreted as mortality rates, fitted with the classical Lee-Carter approach and forecasted with automatically selected ARIMA processes. The results suggest that the constancy assumption used for the original planning provides indeed the best approach for many Federal States. Nevertheless, the application of the well-established Lee-Carter mortality model offers the opportunity to estimate an alternative number of first-year students and to open up a range of possible solutions.

Suggested Citation

  • Stöver, Britta, 2019. "Estimating the transition time from school to university using a stochastic mortality model," Hannover Economic Papers (HEP) dp-657, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-657
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    References listed on IDEAS

    as
    1. Anastasia Novokreshchenova, 2016. "Predicting Human Mortality: Quantitative Evaluation of Four Stochastic Models," Risks, MDPI, vol. 4(4), pages 1-28, December.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Mortality rates; mortality model; transition rates; university enrolment; first-year students;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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