Using Dynamic Microsimulation as an Integrated Modelling Framework to Assess the Impact of Rising Education and Variation in Economic Context on Past and Future Fertility Trends.

Karel Neels , University of Antwerp
Leen Marynissen , University of Antwerp
Jonas Wood , University of Antwerp

Low fertility levels in European countries since the 1970s have been a major force contributing to population ageing. Several individual-level and contextual factors have been proposed to explain changing patterns of fertility, with increasing education and labour force participation, variation in economic cycles and lack of supportive policies in many countries figuring prominently. While there has been no shortage of candidate causal factors, no integrated modelling framework has hitherto been developed to investigate the interplay between these factors and to assess the actual contribution of various factors to change in aggregate fertility trends. This paper uses longitudinal microdata from the 2001 and 2011 Belgian censuses to model the impact of prolonged enrolment in education, rising educational attainment and variation in economic context on entry into parenthood and subsequent family formation in Belgium between 1950 and 2010. Discrete-time hazard models with shared frailties for entry into parenthood and subsequent parity progressions are subsequently integrated into a dynamic microsimulation framework that allows to assess the sensitivity of aggregate fertility trends to increasing enrolment in education and variation in economic contexts, while acknowledging the constraining effect of population structures that have been shaped by past demographic trends. Finally, the dynamic microsimulation model is used to generate out of sample predictions of aggregate fertility trends for 2010-2070 using observed economic indicators for the period 2011-2020, whereas indicators for the period 2021-2070 are obtained from the economic prospects generated by the Belgian Federal Planning Bureau.

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 Presented in Session 62. New Methodological Approaches in Fertility Research