A fuzzy bi-level method for modeling age-specific migration. (December 2019)

• Record Type: Journal Article
• Authors: Demirel, Duygun Fatih; Basak, Melek
• Is Part Of: Socio-economic planning sciences. Number 68(2019)
• Publication Date: 2019-12
• Subjects: Migration modeling -- Lee-Carter method -- Fuzzy modeling -- Bayesian forecasting -- Singular value decomposition; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2018.11.001
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: Modeling and forecasting international migration are significant research areas since migration forecasts are vital in decision making and policy design regarding economy, security, society, and resource allocation. The methods for modeling and forecasting migration rely on strict subjective or statistical assumptions which may not always be met. In addition, lack of a universally accepted definition of the term "migrant" and the ambiguities in data due to recording and collection systems result in inconsistencies and vagueness in migration modeling. Considering these, in this paper, a fuzzy bi-level age-specific migration modeling method is proposed. The bi-level structure embedded in the model makes use of the well-known Lee-Carter method as well as fuzzy regression, singular value decomposition technique, and hierarchical clustering to reflect the general characteristics of the country of concern together with the distinct emigration and immigration behaviors of the age groups. Bayesian time series models are fitted to the time-variant fuzzy parameters obtained through the proposed method to forecast future migration values. The proposed method is applied on female and male age-specific emigration and immigration counts of Finland for 1990–2010 period and Germany for 1995–2012 period, and the future values are forecasted for 2011–2025 and 2013–2025 respectively. The method is compared with an existing Bayesian approach and the numerical findings display that the proposed fuzzy method is superior to the existing one in modeling and forecasting age-specific migration values within significantly narrower prediction intervals. Highlights: A fuzzy migration modeling method is proposed to eliminate the restrictive assumptions of the existing methods The bi-level structure of the model reflects general country characteristics and distinct age group behaviors. The proposed method is applied on migration data of Finland and Germany; and compared with an existing Bayesian approach. The proposed method is superior to the existing one in forecasting migration values within narrower prediction intervals. This paper shows the applicability of fuzzy approach in modeling and forecasting the inherent uncertainty for migration.