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Stochastic population forecasts based on conditional expert opinions

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  • F. C. Billari
  • R. Graziani
  • E. Melilli

Abstract

We develop a method for the derivation of expert-based stochastic population forecasts. The full probability distribution of forecasts is specified by expert opinions on future developments, elicited conditional on the realization of high, central, low scenarios. The procedure is applied to forecast the Italian population, using scenarios from the Italian National Statistical Office (ISTAT) and the Statistical Office of the European Union (EUROSTAT).
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  • F. C. Billari & R. Graziani & E. Melilli, 2012. "Stochastic population forecasts based on conditional expert opinions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(2), pages 491-511, April.
    • Handle: RePEc:bla:jorssa:v:175:y:2012:i:2:p:491-511
    DOI: j.1467-985X.2011.01015.x
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    References listed on IDEAS

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    1. Shripad Tuljapurkar & Ronald D. Lee & Qi Li, 2004. "Random Scenario Forecasts Versus Stochastic Forecasts," Working Papers wp073, University of Michigan, Michigan Retirement Research Center.
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    Cited by:

    1. Gianni Corsetti & Marco Marsili, 2013. "Previsioni stocastiche della popolazione nell’ottica di un Istituto Nazionale di Statistica," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(2-3), pages 5-29.
    2. Matteo Gomellini & Cormac Ó Gráda, 2011. "Outward and Inward Migrations in Italy: A Historical Perspective," Quaderni di storia economica (Economic History Working Papers) 08, Bank of Italy, Economic Research and International Relations Area.
    3. Demirel, Duygun Fatih & Basak, Melek, 2019. "A fuzzy bi-level method for modeling age-specific migration," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    4. Atsede D. Tegegne & Marianne Penker & Maria Wurzinger, 2016. "Participatory Demographic Scenarios Addressing Uncertainty and Transformative Change in Ethiopia," Systemic Practice and Action Research, Springer, vol. 29(3), pages 277-296, June.
    5. Tongzheng Pu & Chongxing Huang & Jingjing Yang & Ming Huang, 2023. "Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction," Sustainability, MDPI, vol. 15(13), pages 1-23, July.
    6. Nico Keilman, 2018. "Probabilistic demographic forecasts," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 16(1), pages 025-035.
    7. Robert Stewart & Marie Urban & Samantha Duchscherer & Jason Kaufman & April Morton & Gautam Thakur & Jesse Piburn & Jessica Moehl, 2016. "A Bayesian machine learning model for estimating building occupancy from open source data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1929-1956, April.
    8. Heinz Stefan, 2014. "Uncertainty quantification of world population growth: A self-similar PDF model," Monte Carlo Methods and Applications, De Gruyter, vol. 20(4), pages 261-277, December.
    9. Tom Wilson & Fiona Shalley, 2019. "Subnational population forecasts: Do users want to know about uncertainty?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(13), pages 367-392.
    10. repec:bdi:workqs:qse_8 is not listed on IDEAS
    11. Zhang Zhen & Bhattacharjee Arnab & Marques João & Maiti Tapabrata, 2021. "Spatio-Temporal Patterns in Portuguese Regional Fertility Rates: A Bayesian Approach for Spatial Clustering of Curves," Journal of Official Statistics, Sciendo, vol. 37(3), pages 611-653, September.
    12. Francesco Billari & Rebecca Graziani & Eugenio Melilli, 2014. "Stochastic Population Forecasting Based on Combinations of Expert Evaluations Within the Bayesian Paradigm," Demography, Springer;Population Association of America (PAA), vol. 51(5), pages 1933-1954, October.
    13. Patrizio Vanella & Philipp Deschermeier & Christina B. Wilke, 2020. "An Overview of Population Projections—Methodological Concepts, International Data Availability, and Use Cases," Forecasting, MDPI, vol. 2(3), pages 1-18, September.

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