IDEAS home Printed from https://ideas.repec.org/r/dem/demres/v6y2002i15.html
   My bibliography  Save this item

Why population forecasts should be probabilistic - illustrated by the case of Norway

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


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. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
  3. Juha Alho & Nico Keilman, 2010. "On future household structure," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 117-143, January.
  4. Patrizio Vanella & Moritz Heß & Christina B. Wilke, 2020. "A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 943-974, June.
  5. Stefan Rayer & Stanley Smith & Jeff Tayman, 2009. "Empirical Prediction Intervals for County Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 28(6), pages 773-793, December.
  6. Vanella, Patrizio & Deschermeier, Philipp, 2018. "A Probabilistic Cohort-Component Model for Population Forecasting - The Case of Germany," Hannover Economic Papers (HEP) dp-638, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  7. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
  8. Warren C Sanderson & Sergei Scherbov & Patrick Gerland, 2017. "Probabilistic population aging," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-12, June.
  9. Tom Wilson & Huw Brokensha & Francisco Rowe & Ludi Simpson, 2018. "Insights from the Evaluation of Past Local Area Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 137-155, February.
  10. Vasiliki Mebelli & Maria Drakaki & Panagiotis Tzionas, 2023. "An Investigation of Time Series Models for Forecasting Mixed Migration Flows: Focusing in Germany," SN Operations Research Forum, Springer, vol. 4(2), pages 1-11, June.
  11. Nico Keilman, 2020. "Evaluating Probabilistic Population Forecasts," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 520-521, pages 49-64.
  12. Warren Sanderson & Sergei Scherbov & Brian O'Neill & Wolfgang Lutz, 2003. "Conditional Probabilistic Population Forecasting," VID Working Papers 0303, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
  13. Tom Wilson, 2016. "Visualising the demographic factors which shape population age structure," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(29), pages 867-890.
  14. Niall Newsham & Francisco Rowe, 2021. "Projecting the demographic impact of Syrian migration in a rapidly ageing society, Germany," Journal of Geographical Systems, Springer, vol. 23(2), pages 231-261, April.
  15. 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.
  16. Richard S. Grip & Meghan L. Grip, 2020. "Using Multiple Methods to Provide Prediction Bands of K-12 Enrollment Projections," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(1), pages 1-22, February.
  17. 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.
  18. Marek Ogryzek & Krzysztof Rząsa & Edita Šarkienė, 2019. "Demographic Forecasts Using the Game Theory," IJERPH, MDPI, vol. 16(8), pages 1-13, April.
  19. Mangirdas Morkunas & Elzė Rudienė & Lukas Giriūnas & Laura Daučiūnienė, 2020. "Assessment of Factors Causing Bias in Marketing- Related Publications," Publications, MDPI, vol. 8(4), pages 1-16, October.
  20. Dag Kolsrud, 2015. "A Time‐Simultaneous Prediction Box for a Multivariate Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 675-693, December.
  21. Deschermeier Philipp, 2014. "Prognose der Anzahl der Erwerbspersonen: Eine Vorausberechnung auf Basis der Funktionalen Datenanalyse am Beispiel der Metropolregion Rhein-Neckar," ZFW – Advances in Economic Geography, De Gruyter, vol. 58(1), pages 50-65, October.
  22. Maarten Alders & Nico Keilman & Harri Cruijsen, 2007. "Assumptions for long-term stochastic population forecasts in 18 European countries," European Journal of Population, Springer;European Association for Population Studies, vol. 23(1), pages 33-69, March.
  23. Dag Kolsrud, 2007. "Time-simultaneous prediction band for a time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 171-188.
  24. 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.
  25. Hal Caswell & Nora Sánchez Gassen, 2015. "The sensitivity analysis of population projections," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(28), pages 801-840.
  26. Jeff Tayman & Stanley Smith & Jeffrey Lin, 2007. "Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(3), pages 347-369, June.
  27. Rodríguez, Julio, 2008. "A methodology for population projections: an application to Spain," DES - Working Papers. Statistics and Econometrics. WS ws084512, Universidad Carlos III de Madrid. Departamento de Estadística.
  28. 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.
  29. Härdle, Wolfgang Karl & Myšičková, Alena, 2009. "Stochastic population forecast for Germany and its consequence for the German pension system," SFB 649 Discussion Papers 2009-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  30. Jeff Tayman, 2011. "Assessing Uncertainty in Small Area Forecasts: State of the Practice and Implementation Strategy," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(5), pages 781-800, October.
  31. Guy Abel & Jakub Bijak & Jonathan J. Forster & James Raymer & Peter W.F. Smith & Jackie S.T. Wong, 2013. "Integrating uncertainty in time series population forecasts: An illustration using a simple projection model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(43), pages 1187-1226.
  32. Shang, Han Lin & Smith, Peter W.F. & Bijak, Jakub & Wiśniowski, Arkadiusz, 2016. "A multilevel functional data method for forecasting population, with an application to the United Kingdom," International Journal of Forecasting, Elsevier, vol. 32(3), pages 629-649.
  33. David Coleman, 2010. "Projections of the Ethnic Minority Populations of the United Kingdom 2006–2056," Population and Development Review, The Population Council, Inc., vol. 36(3), pages 441-486, September.
  34. Han Lin Shang & Rob J Hyndman & Heather Booth, 2010. "A comparison of ten principal component methods for forecasting mortality rates," Monash Econometrics and Business Statistics Working Papers 8/10, Monash University, Department of Econometrics and Business Statistics.
  35. Nasibeh Esmaeili & Mohammad Jalal Abbasi-Shavazi, 2024. "Forecasting number of births and sex ratio at birth in Iran using deep neural network and ARIMA: implications for policy evaluations," Journal of Population Research, Springer, vol. 41(4), pages 1-21, December.
  36. Amancio Betzuen Zalbidegoitia & Amaia Jone Betzuen Álvarez, 2021. "Is Longevity Acceleration Sustainable? An Entropy-Based Trial of the Population of Spain vs. Japan," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
  37. Han Lin Shang & Heather Booth & Rob Hyndman, 2011. "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(5), pages 173-214.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.