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• W2187777495 abstract "The paper is devoted to the development of Bayesian methodology for international migration forecasting. Its aim is to present a statistical framework for (1) a formal selection of a forecasting model, and (2) combining knowledge from various competing models in order to obtain averaged forecasts. The main benefit of pooling forecasts yielded by different models is the reduction of forecast error resulting from the uncertainty of model specification. The Bayesian framework ensures the formal status of applied statistical tools in addressing the uncertainty issues, allowing at the same time for an explicit incorporation of subjective expert opinion in the model selection process, as well as in the models themselves. In the paper, a theoretical discussion is supported by an empirical application of the presented methodology to a forecast of migration flows between Germany and three European countries: Poland, Italy, and Switzerland, for the period 2005–2010. The analysis employs macro-level data from the population registers of the countries under study, and is restricted to forecasting models based on simple stochastic processes." @default.
• W2187777495 created "2016-06-24" @default.
• W2187777495 creator A5063239904 @default.
• W2187777495 date "2006-01-01" @default.
• W2187777495 modified "2023-09-27" @default.
• W2187777495 title "Bayesian Model Averaging in Forecasting International Migration" @default.
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• W2187777495 hasPublicationYear "2006" @default.
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