Abstract
Marriage has become less common, while the incidence of divorce has risen in Iran. These have made marriage facilitation and divorce prevention as the cornerstone of population policy. It is clear that prediction of the incidence of marriage and divorce will help policy makers to design effective interventions. This paper uses the number of marriages and divorces between 1980 and 2017, published by the Statistical Center of Iran, to predict the incidence of marriage and divorce through 2027 at the national level. Given the limitations of common methods, such as ARMAX, ARMA, MR and AR, in predicting time series with abrupt changes, this paper applies a mixed method, which combines the Neural Network and the Wavelet mathematical tools. The comparison between the data and the results obtained from the wavelet-neural network confirms the precision of the model. The precision and validity of the neural-wavelet network model is further confirmed by the fact that it has been able to reduce the mean sum of square of errors to a larger extent than the Neural Network models. The findings show a 3% decrease in the number of marriages, from 704,716 in 2017 to 683,190 in 2027. On the other hand, the number of divorces has increased by 30%, from 181,049 in 2017 to 235,407 in 2027. Thus, the number of divorces per 100 marriages will increase from 25.7 to 34.5 just in a decade, which calls for effective interventions if family formation and consolidation are to be improved in Iran.
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Torabi, F., Esmaeili, N. Application of neural-wavelet network in predicting the incidence of marriage and divorce in Iran. China popul. dev. stud. 4, 439–457 (2021). https://doi.org/10.1007/s42379-020-00072-4
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DOI: https://doi.org/10.1007/s42379-020-00072-4