Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 342

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Demographic forecasting: 1980 to 2005 in review

Booth, Heather·2006·International Journal of Forecasting
DOI 10.1016/j.ijforecast.2006.04.001
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.ijforecast.2006.04.001

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 249

  1. Ahlburg, 1982, How accurate are the U.S. Bureau of the Census projections of total live births?, Journal of Forecasting, 1, 365, 10.1002/for.3980010404 · DOI
  2. Ahlburg, 1983, Good times, bad times: A study of the future path of US fertility, Social Biology, 30, 17
  3. Ahlburg, 1986, A relative cohort size forecasting model of Canadian total live births, Social Biology, 30, 51
  4. Ahlburg, 1987, Population forecasts for South Pacific nations using autoregressive models, Journal of the Australian Population Association, 4, 157, 10.1007/BF03029414 · DOI
  5. Ahlburg, 1995, Simple versus complex models: Evaluation, accuracy, and combining, Mathematical Population Studies, 5, 281, 10.1080/08898489509525406 · DOI
  6. Ahlburg, 1992, Population forecasting: Guest editors' introduction, International Journal of Forecasting, 8, 289, 10.1016/0169-2070(92)90048-E · DOI
  7. Ahlburg, D. A., & Lutz, W. (1999). Introduction: The need to rethink approaches to population forecasts. In W. Lutz & J. W. Vaupel (Eds.), Frontiers of population forecasting (pp. 1–14). New York: Population Council. A supplement to Population and Development Review, Volume 24, 1998.
  8. Ahlburg, D. A., Lutz, W., & Vaupel, J. W. (1999). Ways to improve population forecasting: What should be done differently in the future? In W. Lutz & J. W. Vaupel (Eds.), Frontiers of population forecasting (pp. 191–198). New York: Population Council. A supplement to Population and Development Review, Volume 24, 1998.
  9. Ahlburg, 1990, Alternative projections of the U.S. population, Demography, 27, 639, 10.2307/2061575 · DOI
  10. Alders, 2004, Assumptions on fertility in stochastic population forecasts, International Statistical Review, 72, 65, 10.1111/j.1751-5823.2004.tb00224.x · DOI
  11. Alho, 1990, Stochastic methods in population forecasting, International Journal of Forecasting, 6, 521, 10.1016/0169-2070(90)90030-F · DOI
  12. Alho, 1991, Effect of aggregation on the estimation of trend mortality, Mathematical Population Studies, 2, 53, 10.1080/08898489109525323 · DOI
  13. Alho, 1992, The magnitude of error due to different vital processes in population forecasts, International Journal of Forecasting, 8, 301, 10.1016/0169-2070(92)90049-F · DOI
  14. Alho, 1992, Estimating the strength of expert judgement: The case of US mortality forecasts, Journal of Forecasting, 11, 157, 10.1002/for.3980110206 · DOI
  15. Alho, 1997, Scenarios, uncertainty and conditional forecasts of the world population, Journal of the Royal Statistical Society. Series A, 160, 71, 10.1111/1467-985X.00046 · DOI
  16. Alho, 1997, Mixed estimation of old-age mortality, Mathematical Population Studies, 6, 319, 10.1080/08898489709525440 · DOI
  17. Alho, 1985, Uncertain population forecasting, Journal of the American Statistical Association, 80, 306, 10.2307/2287887 · DOI
  18. Alho, 1990, Error models for official mortality forecasts, Journal of the American Statistical Association, 85, 609, 10.2307/2289992 · DOI
  19. Alho, 1990, Effects of targets and aggregation on the propagation of error in mortality forecasts, Mathematical Population Studies, 2, 209, 10.1080/08898489009525307 · DOI
  20. Alho, 1991, A population forecast as a database: Implementing the stochastic propagation of error, Journal of Official Statistics, 7, 295
  21. Alho, 1997, The practical specification of the expected error of population forecasts, Journal of Official Statistics, 13, 203
  22. Ashley, 1983, On the usefulness of macroeconomic forecasts as inputs to forecasting models, Journal of Forecasting, 2, 211, 10.1002/for.3980020304 · DOI
  23. Bell, 1997, Comparing and assessing time series methods for forecasting age-specific fertility and mortality rates, Journal of Official Statistics, 13, 279
  24. Bell, W.R., & Monsell, B.C. (1991). Using principal components in time series modeling and forecasting of age-specific mortality rates. Paper presented at the American Statistical Association 1991 Proceedings of the Social Statistics Section.
  25. Bloom, 1982, What's happening to the age at first birth in the United States? A study of recent cohorts, Demography, 19, 351, 10.2307/2060976 · DOI
  26. Bloom, 1992, Projecting the number of new AIDS cases in the United States, International Journal of Forecasting, 8, 339, 10.1016/0169-2070(92)90052-B · DOI
  27. Bloom, 1984, What are the determinants of delayed childbearing and permanent childlessness in the United States?, Demography, 21, 591, 10.2307/2060917 · DOI
  28. Bongaarts, 1989, A model of the spread of HIV infection and the demographic impact of AIDS, Statistics in Medicine, 8, 301, 10.1002/sim.4780080111 · DOI
  29. Bongaarts, 2005, Long-range trends in adult mortality: Models and projection methods, Demography, 42, 23, 10.1353/dem.2005.0003 · DOI
  30. Bongaarts, 1999, Completing the demographic transition, Population and Development Review, 25, 515, 10.1111/j.1728-4457.1999.00515.x · DOI
  31. Bongaarts, 1998, On the quantum and tempo of fertility, Population and Development Review, 24, 271, 10.2307/2807974 · DOI · Paper page
  32. Bongaarts, 2002, How long do we live?, Population and Development Review, 28, 13, 10.1111/j.1728-4457.2002.00013.x · DOI
  33. Bongaarts, 2003, Estimating mean lifetime, Proceedings of the National Academy of Sciences, 100, 13127, 10.1073/pnas.2035060100 · DOI
  34. Bongaarts, J., & Feeney, G. (2005). The quantum and tempo of life-cycle events (Working Paper No. 207). New York: Population Council. · DOI
  35. Booth, 2002, Applying Lee–Carter under conditions of variable mortality decline, Population Studies, 56, 325, 10.1080/00324720215935 · DOI · Paper page
  36. Booth, H., Tickle, L., & Smith, L. (2005). Evaluation of the variants of the Lee–Carter method of forecasting mortality: A multi-country comparison. New Zealand Population Review, Special Issue on Stochastic Population Projections (edited by A. Dharmalingam and I. Pool), 31, 13–37.
  37. Bos, 1992, The demographic impact of AIDS in sub-Saharan Africa: Short and long-term projections, International Journal of Forecasting, 8, 367, 10.1016/0169-2070(92)90053-C · DOI
  38. Bozik, J.E., & Bell, W.R. (1987). Forecasting age specific fertility using principal components. Paper presented at the Proceedings of the Social Statistics Section, American Statistical Association, San Francisco, California.
  39. Brass, 1974, Perspectives in population prediction: Illustrated by the statistics of England and Wales, Journal of the Royal Statistical Society, Series A, 137, 532, 10.2307/2344713 · DOI
  40. Brass, 1981, The use of the Gompertz relational model to estimate fertility, vol. 3, 345
  41. Brouhns, 2002, A Poisson log-bilinear regression approach to the construction of projected life-tables, Insurance: Mathematics and Economics, 31, 373, 10.1016/S0167-6687(02)00185-3 · DOI · Paper page
  42. Buettner, 2002, Approaches and experiences in projecting mortality patterns for the oldest–old, North American Actuarial Journal, 6, 14, 10.1080/10920277.2002.10596053 · DOI
  43. Buettner, 2005, Prospects for increasing longevity as assessed by the United Nations, Genus, 213
  44. Carrière, 1992, Parametric models for life tables, Transactions of the Society of Actuaries, 44, 77
  45. Carter, 1996, Forecasting U.S. mortality: A comparison of Box–Jenkins ARIMA and structural time series models, The Sociological Quarterly, 37, 127, 10.1111/j.1533-8525.1996.tb02334.x · DOI
  46. Carter, 2000, Imparting structural instability to mortality forecasts: Testing for sensitive dependence on initial conditions with innovations, Mathematical Population Studies, 8, 31, 10.1080/08898480009525472 · DOI
  47. Carter, 1986, Joint forecasts of U.S. marital fertility, nuptiality, births and marriages using time series models, Journal of the American Statistical Association, 81, 902, 10.2307/2289058 · DOI
  48. Carter, 1992, Modelling and forecasting US sex differentials in mortality, International Journal of Forecasting, 8, 393, 10.1016/0169-2070(92)90055-E · DOI
  49. Carter, L. R., & Prskawetz, A. (2001). Examining structural shifts in mortality using the Lee–Carter method (MPIDR Working Paper No. WP 2001-007): Max Planck Institute for Demographic Research. · DOI
  50. Chandola, 1999, Recent European fertility patterns: Fitting curves to ‘distorted’ distributions, Population Studies, 53, 317, 10.1080/00324720308089 · DOI
  51. Chandola, 2000, A reply to J. Antonio Ortega Osona and H.-P. Kohler, Population Studies, 54, 351, 10.1080/713779095 · DOI
  52. Chauhan, 1997, Graduation of infant deaths by age, Demography India, 26, 261
  53. Chen, 1991, Recent trends in the timing of first births in the United States, Demography, 28, 513, 10.2307/2061420 · DOI
  54. Coale, 1989, Revised regional model life tables at very low levels of mortality, Population Index, 55, 613, 10.2307/3644567 · DOI
  55. Coale, 1990, Defects in data on old-age mortality in the United States: New procedures for calculating schedules and life tables at the highest ages, Asian and Pacific Population Forum, 4, 1
  56. Coale, 1972, The distribution by age of the frequency of first marriage in a female cohort, Journal of the American Statistical Association, 67, 743, 10.2307/2284631 · DOI
  57. Coale, 1974, Model fertility schedules: Variations in the age structure of childbearing in human populations, Population Index, 40, 185, 10.2307/2733910 · DOI · Paper page
  58. Cohen, 1986, Population forecasts and confidence intervals for Sweden: A comparison of model-based and empirical approaches, Demography, 23, 105, 10.2307/2061412 · DOI
  59. Cohen, J. E. (1999). Should population projections consider “limiting factors” — And if so how? In W. Lutz, J. W. Vaupel & D. A. Ahlburg (Eds.), Frontiers of population forecasting (pp. 118–138). New York: Population Council. A supplement to Population and Development Review vol. 24 (1998).
  60. Congdon, 1980, Forecasting births in greater London: An application of the Easterlin hypothesis, Population Studies, 34, 267, 10.1080/00324728.1980.10410389 · DOI
  61. Congdon, 1989, Fertility forecasts and structural interpretations: An application to London and England and Wales, Espaces, Populations et Sociétés, 1989-2, 177, 10.3406/espos.1989.1318 · DOI
  62. Congdon, 1990, Graduation of fertility schedules: An analysis of fertility patterns in London in the 1980s and an application to fertility forecasts, Regional Studies, 24, 311, 10.1080/00343409012331346014 · DOI
  63. Congdon, 1993, Statistical graduation in local demographic analysis and projection, Journal of the Royal Statistical Society, 156, 237, 10.2307/2982731 · DOI
  64. Crimmins, 1981, The changing pattern of American mortality decline, 1947–1977, and its implication for the future, Population and Development Review, 7, 229, 10.2307/1972622 · DOI
  65. Currie, 2004, Smoothing and forecasting mortality rates, Statistical Modelling, 4, 279, 10.1191/1471082X04st080oa · DOI · Paper page
  66. De Beer, 1985, A time series model for cohort data, Journal of the American Statistical Association, 80, 525, 10.2307/2288465 · DOI
  67. De Beer, 1988, Predictability of demographic variables in the short run, European Journal of Population, 4, 283, 10.1007/BF01797130 · DOI
  68. De Beer, 1989, Projecting age-specific fertility rates by using time-series methods, European Journal of Population, 5, 315, 10.1007/BF01796791 · DOI
  69. De Beer, 1991, From birth expectations to birth forecasts: A partial adjustment approach, Mathematical Population Studies, 3, 1127, 10.1080/08898489109525330 · DOI
  70. De Beer, 1997, The effect of uncertainty of migration on national population forecasts: The case of the Netherlands, Journal of Official Statistics, 13, 227
  71. De Cooman, 1987, The next birth and the labour market: A dynamic model of births in England and Wales, Population Studies, 41, 237, 10.1080/0032472031000142786 · DOI
  72. De Jong, 2006, Extending Lee–Carter mortality forecasting, Mathematical Population Studies, 13, 1, 10.1080/08898480500452109 · DOI
  73. Easterlin, 1968, Population, labour force, and long swings in economic growth: The America experience, vol. 86
  74. Edwards, 2005, Inequality in life spans and a new perspective on mortality convergence across industrialized countries, Population and Development Review, 31, 645, 10.1111/j.1728-4457.2005.00092.x · DOI · Paper page
  75. Ermisch, 1988, Econometric analysis of birth rate dynamics in Britain, Journal of Human Resources, 23, 563, 10.2307/145814 · DOI
  76. Evans, 1986, American fertility patterns: A comparison of white and nonwhite cohorts born 1903–56, Population Development Review, 12, 267, 10.2307/1973111 · DOI
  77. Ewbank, 1983, A reducible four-parameter system of model life tables, Population Studies, 37, 105, 10.1080/00324728.1983.10405927 · DOI · Paper page
  78. Forfar, 1988, On graduation by mathematical formula, Journal of the Institute of Actuaries, 115, 97, 10.1017/S0020268100042633 · DOI
  79. Forfar, 1987, The changing face of English life tables, Transactions of the Faculty of Actuaries, 40, 98, 10.1017/S0071368600009137 · DOI
  80. Gage, 1993, Some laws of mortality: How well do they fit?, Human Biology, 65, 445
  81. Goldstein, 2004, Simpler probabilistic population forecasts: Making scenarios work, International Statistical Review, 72, 93, 10.1111/j.1751-5823.2004.tb00226.x · DOI
  82. Goldstein, 2002, Long-range population projections made simple, Population and Development Review, 28, 121, 10.1111/j.1728-4457.2002.00121.x · DOI
  83. Goss, 1998, Historical and projected mortality for Mexico, Canada, and the United States, North American Actuarial Journal, 2, 108, 10.1080/10920277.1998.10595757 · DOI
  84. Granger, 1989, Invited review: Combining forecasts — Twenty years later, Journal of Forecasting, 8, 167, 10.1002/for.3980080303 · DOI · Paper page
  85. Granger, 2001, Invited review: Combining forecasts — Twenty years later, 411
  86. Guillot, 2003, The cross-sectional average length of life (CAL): A period mortality measure that reflects the experience of cohorts, Population Studies, 57, 41, 10.1080/0032472032000061712 · DOI
  87. Gutterman, 1998, Forecasting changes in mortality: A search for a law of causes and effects, North American Actuarial Journal, 2, 135, 10.1080/10920277.1998.10595759 · DOI
  88. Hannerz, 2001, Presentation and derivation of a five-parameter survival function intended to model mortality in modern female populations, Scandinavian Actuarial Journal, 2001, 176, 10.1080/03461230152592809 · DOI
  89. Hannerz, 2001, Manhood trials and the law of mortality, Demographic Research, 4, 185, 10.4054/DemRes.2001.4.7 · DOI
  90. Hannerz, 2001, An extension of relational methods in mortality estimation, Demographic Research, 4, 337, 10.4054/DemRes.2001.4.10 · DOI
  91. Hartmann, 1987, Past and recent attempts to model mortality at all ages, Journal of Official Statistics, 3, 19
  92. Hauser, 2005, Survey design and methodology in the Health and Retirement Study and the Wisconsin Longitudinal Study, vol. 30, 209
  93. Heckman, 1989, Forecasting aggregate period-specific birth rates: The time series properties of a microdynamic neoclassical model of fertility, Journal of the American Statistical Association, 84, 958, 10.2307/2290070 · DOI
  94. Heligman, 1980, The age pattern of mortality, Journal of the Institute of Actuaries, 107, 49, 10.1017/S0020268100040257 · DOI · Paper page
  95. Himes, 1994, A relational model of mortality at older ages in low mortality countries, Population Studies, 48, 269, 10.1080/0032472031000147796 · DOI
  96. Hoem, 1981, Experiments in modelling in recent Danish fertility curves, Demography, 18, 231, 10.2307/2061095 · DOI
  97. Kaneko, 2003, Elaboration of the Coale–McNeil nuptiality model as the generalized log gamma distribution: A new identity and empirical enhancements, Demographic Research, 9, 223, 10.4054/DemRes.2003.9.10 · DOI
  98. Kannisto, 1994, Reductions in mortality at advanced ages: Several decades of evidence from 27 countries, Population and Development Review, 20, 793, 10.2307/2137662 · DOI · Paper page
  99. Keilman, 1997, Ex-post errors in official population forecasts in industrialized countries, Journal of Official Statistics, 13, 245
  100. Keilman, 1999, How accurate are the United Nations world population projections?, vol. 24, 15
  101. Keilman, 2001, Uncertain population forecasts, Nature, 412, 490, 10.1038/35087685 · DOI
  102. Keilman, 2001, Data quality and accuracy of United Nations population projections, 1950–95, Population Studies, 55, 149, 10.1080/00324720127686 · DOI
  103. Keilman, 2002, TFR predictions based on Brownian motion theory, Yearbook of Population Research in Finland, 38, 207
  104. Keilman, 2000, Predictive intervals for age-specific fertility, European Journal of Population, 16, 41, 10.1023/A:1006385413134 · DOI
  105. Keilman, 2004, Time series based errors and empirical errors in fertility forecasts in the Nordic countries, International Statistical Review, 72, 5, 10.1111/j.1751-5823.2004.tb00220.x · DOI
  106. Keilman, 2002, Why population forecasts should be probabilistic — Illustrated by the case of Norway, Demographic Research, 6, 409, 10.4054/DemRes.2002.6.15 · DOI
  107. Keyfitz, 1972, On population forecasting, Journal of the American Statistical Association, 67, 347, 10.2307/2284381 · DOI
  108. Keyfitz, 1981, The limits of population forecasting, Population and Development Review, 7, 579, 10.2307/1972799 · DOI · Paper page
  109. Keyfitz, 1982, Can knowledge improve forecasts?, Population and Development Review, 8, 729, 10.2307/1972470 · DOI
  110. Keyfitz, 1982, Choice of function for mortality analysis: Effective forecasting depends on a minimum parameter representation, Theoretical Population Biology, 21, 329, 10.1016/0040-5809(82)90022-3 · DOI
  111. Keyfitz, 1985, Demography in the twenty-first century: The uses of forecasting, vol. 1, 59
  112. Keyfitz, 1991, Experiments in the projection of mortality, Canadian Studies in Population, 18, 1, 10.25336/P6C01S · DOI
  113. Keyfitz, N. (1996). Foreword. In W. Lutz (Ed.), The future population of the world: What can we assume today? (Revised Edition). London: Earthscan.
  114. Knudsen, 1993, Forecasting fertility: An application of time series methods to parameterized model schedules, Social Science Research, 22, 1, 10.1006/ssre.1993.1001 · DOI
  115. Kohler, 2002, Tempo-adjusted period parity progression measures, fertility postponement and completed cohort fertility, Demographic Research, 6, 91, 10.4054/DemRes.2002.6.6 · DOI
  116. Kohler, 2001, Variance effects in the Bongaarts–Feeney formula, Demography, 38, 1, 10.1353/dem.2001.0004 · DOI
  117. Kostaki, 1992, A nine parameter version of the Heligman–Pollard formula, Mathematical Population Studies, 3, 277, 10.1080/08898489209525346 · DOI
  118. Land, 1986, Methods for national population forecasts: A review, Journal of the American Statistical Association, 81, 888, 10.2307/2289057 · DOI
  119. Le Bras, 2005, Mortality tempo versus removal of causes of mortality: Opposite views leading to different estimations of life expectancy, Demographic Research, 13, 615, 10.4054/DemRes.2005.13.25 · DOI
  120. Leach, 1981, Re-evaluation of the logistic curve for human populations, Journal of the Royal Statistical Society. Series A, 144, 94, 10.2307/2982163 · DOI
  121. Lee, 1974, Forecasting births in post-transition populations: Stochastic renewal with serially correlated fertility, Journal of the American Statistical Association, 69, 607, 10.2307/2285990 · DOI
  122. Lee, 1980, Aiming at a moving target: Period fertility and changing reproductive goals, Population Studies, 34, 205, 10.1080/00324728.1980.10410385 · DOI
  123. Lee, 1990, Long-run global population forecasts: A critical appraisal, Population and Development Review, 16, 44, 10.2307/2808062 · DOI
  124. Lee, 1992, Stochastic demographic forecasting, International Journal of Forecasting, 8, 315, 10.1016/0169-2070(92)90050-J · DOI
  125. Lee, 1993, Modeling and forecasting the time series of US fertility: Age distribution, range, and ultimate level, International Journal of Forecasting, 9, 187, 10.1016/0169-2070(93)90004-7 · DOI
  126. Lee, 1999, Probabilistic approaches to population forecasting, vol. 24, 156
  127. Lee, 2000, The Lee–Carter method for forecasting mortality, with various extensions and applications, North American Actuarial Journal, 4, 80, 10.1080/10920277.2000.10595882 · DOI
  128. Lee, 2000, Long-term population projections and the US social security system, Population and Development Review, 26, 137, 10.1111/j.1728-4457.2000.00137.x · DOI
  129. Lee, 2005, Quantifying our ignorance: Stochastic forecasts of population and public budgets, vol. 30, 153
  130. Lee, 1992, Modelling and forecasting U.S. mortality, Journal of the American Statistical Association, 87, 659, 10.2307/2290201 · DOI
  131. Lee, 1995, Disaggregation in population forecasting: Do we need it? And how to do it simply?, Mathematical Population Studies, 5, 217, 10.1080/08898489509525403 · DOI
  132. Lee, 2001, Evaluating the performance of the Lee–Carter method for forecasting mortality, Demography, 38, 537, 10.1353/dem.2001.0036 · DOI · Paper page
  133. Lee, 1994, Modelacion y proyeccion de la mortalidad en Chile, NOTAS de Poblacion, XXII, 183
  134. Lee, 1994, Stochastic population forecasts for the United States: Beyond high, medium, and low, Journal of the American Statistical Association, 89, 1175, 10.2307/2290980 · DOI
  135. Li, 2005, Coherent mortality forecasts for a group of populations: An extension of the Lee–Carter method, Demography, 42, 575, 10.1353/dem.2005.0021 · DOI · Paper page
  136. Li, 2004, Using the Lee–Carter method to forecast mortality for populations with limited data, International Statistical Review, 72, 19, 10.1111/j.1751-5823.2004.tb00221.x · DOI
  137. Li, 1999, Population momentum for gradual demographic transitions, Population Studies, 53, 255, 10.1080/00324720308078 · DOI
  138. Li, 2000, The solution of time-dependent population models, Mathematical Population Studies, 7, 311, 10.1080/08898480009525464 · DOI
  139. Li, 2003, Forecasting cohort incomplete fertility: A method and an application, Population Studies, 57, 303, 10.1080/0032472032000137826 · DOI
  140. Li, S. -H., & Chan, W. -S. (2005). The Lee–Carter model for forecasting mortality revisited. Paper presented at the Living to 100 and Beyond Symposium, Orlando, Florida. Retrieved October 25, 2005 from http://library.soa.org/library-pdf/m-li05-1_XI.pdf.
  141. Long, 1984, U.S. national population projections methods: A view from four forecasting traditions, Insurance, Mathematics and Economics, 3, 231, 10.1016/0167-6687(84)90027-1 · DOI
  142. Long, 1995, Complexity, accuracy, and utility of official population projections, Mathematical Population Studies, 5, 203, 10.1080/08898489509525402 · DOI
  143. Long, 2004, Developing official stochastic population forecasts at the US Census Bureau, International Statistical Review, 72, 201, 10.1111/j.1751-5823.2004.tb00233.x · DOI
  144. Lundstrom, 2004, Mortality forecasting and trend shifts: An application of the Lee–Carter model to Swedish mortality data, International Statistical Review, 72, 37, 10.1111/j.1751-5823.2004.tb00222.x · DOI
  145. Lutz, W. (Ed.) (1996). The future population of the world: What can we assume today? (Revised ed.) London: Earthscan.
  146. Lutz, 2004, Introduction: How to deal with uncertainty in population forecasting?, International Statistical Review, 72, 1, 10.1111/j.1751-5823.2004.tb00219.x · DOI
  147. Lutz, 1999, Demographic dimensions in forecasting: Adding education to age and sex, vol. 24, 42
  148. Lutz, 1997, Doubling of world population unlikely, Nature, 387, 803, 10.1038/42935 · DOI
  149. Lutz, 1999, Expert-based probabilistic population projections, vol. 24, 139
  150. Lutz, 2001, The end of world population growth, Nature, 412, 543, 10.1038/35087589 · DOI · Paper page
  151. Lutz, 1998, An expert-based framework for probabilistic national population projections: The example of Austria, European Journal of Population, 14, 1, 10.1023/A:1006040321755 · DOI
  152. Lutz, 2004, Probabilistic population projections for India with explicit consideration of the education–fertility link, International Statistical Review, 72, 81, 10.1111/j.1751-5823.2004.tb00225.x · DOI
  153. 1999, vol. 24
  154. Manton, 1980, Mortality model based on delays in progression of chronic diseases: Alternative to cause elimination model, Public Health Reports, 95, 580
  155. Manton, 1991, Limits to human life expectancy: Evidence, prospects, and implications, Population and Development Review, 17, 603, 10.2307/1973599 · DOI
  156. Manton, 1992, Projecting the future size and health status of the US elderly population, International Journal of Forecasting, 8, 433, 10.1016/0169-2070(92)90057-G · DOI
  157. Martinelle, 1993, The timing of first birth: Analysis and prediction of Swedish first birth rates, European Journal of Population, 9, 265, 10.1007/BF01266020 · DOI
  158. McDonald, 1979, A time series approach to forecasting Australian total live-births, Demography, 16, 575, 10.2307/2060937 · DOI
  159. McDonald, 1981, Modelling demographic relationships: An analysis of forecast functions for Australian births, Journal of the American Statistical Association, 76, 782, 10.2307/2287568 · DOI
  160. McDonald, 1983, The emergence of countercyclical US fertility: A reassessment of the evidence, Journal of Macroeconomics, 5, 421, 10.1016/0164-0704(83)90032-0 · DOI
  161. McNown, 1989, Forecasting mortality: A parameterized time series approach, Demography, 26, 645, 10.2307/2061263 · DOI
  162. McNown, 1992, Forecasting cause-specific mortality using time series methods, International Journal of Forecasting, 8, 413, 10.1016/0169-2070(92)90056-F · DOI
  163. McNown, 1995, Simplicity and complexity in extrapolative population forecasting models, Mathematical Population Studies, 5, 235, 10.1080/08898489509525404 · DOI
  164. Miller, 1986, A bivariate model for total fertility rate and mean age of childbearing, Insurance, Mathematics and Economics, 5, 133, 10.1016/0167-6687(86)90037-5 · DOI
  165. Mode, 1982, An eight-parameter model of human mortality — The single decrement case, Bulletin of Mathematical Biology, 44, 647
  166. Mode, 1984, A parametric algorithm for computing model period and cohort human survival functions, International Journal of Biomedical Computing, 15, 341, 10.1016/0020-7101(84)90040-0 · DOI
  167. Morgan, 1981, Intention and uncertainty at later stages of childbearing: The United States 1965 to 1970, Demography, 18, 267, 10.2307/2060997 · DOI
  168. Morgan, 1982, Parity-specific fertility intentions and uncertainty: The United States 1970 to 1976, Demography, 19, 315, 10.2307/2060974 · DOI
  169. Morgan, 1992, Predicting childlessness for recent cohorts of American women, International Journal of Forecasting, 8, 477, 10.1016/0169-2070(92)90059-I · DOI
  170. Murphy, 1990, Methods of forecasting mortality for population projections, vol. 38, 87
  171. Murphy, 1995, The prospect of mortality: England and Wales and the United States of America, 1962–1989, British Actuarial Journal, 1, 331, 10.1017/S1357321700001100 · DOI
  172. Noack, 1985, Fertility expectations: A short cut or dead-end in predicting fertility?, vol. 7, 48
  173. North American Actuarial Journal (1999). Special issue on mortality forecasting, 2(4).
  174. Oliveira, 2004, AIDS in Portugal: Endemic versus epidemic forecasting scenarios for mortality, International Journal of Forecasting, 20, 131, 10.1016/S0169-2070(03)00011-6 · DOI
  175. Olshansky, 1987, Simultaneous/multiple cause–delay (SIMCAD): An epidemiological approach to projecting mortality, Journal of Gerontology, 42, 358, 10.1093/geronj/42.4.358 · DOI
  176. Olshansky, 1988, On forecasting mortality, The Milbank Quarterly, 66, 482, 10.2307/3349966 · DOI
  177. Olshansky, 1997, Ever since Gompertz, Demography, 34, 1, 10.2307/2061656 · DOI
  178. O'Neill, 2004, Conditional probabilistic population projections: An application to climate change, International Statistical Review, 72, 167, 10.1111/j.1751-5823.2004.tb00231.x · DOI
  179. Ortega, 2005, Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models, International Journal of Forecasting, 21, 539, 10.1016/j.ijforecast.2005.02.005 · DOI
  180. Pflaumer, 1988, Confidence intervals for population projections based on Monte Carlo methods, International Journal of Forecasting, 4, 135, 10.1016/0169-2070(88)90015-5 · DOI
  181. Pflaumer, 1992, Forecasting US population totals with the Box–Jenkins approach, International Journal of Forecasting, 8, 329, 10.1016/0169-2070(92)90051-A · DOI
  182. Pollard, 1987, Projection of age-specific mortality rates, Population Bulletin of the United Nations, 21–22, 55
  183. Pollard, 1992, The Gompertz distribution and its applications, Genus, 48, 15
  184. Quesnel-Vallée, 2003, Missing the target? Correspondence of fertility intentions and behavior in the U.S., Population Research and Policy Review, 22, 497, 10.1023/B:POPU.0000021074.33415.c1 · DOI · Paper page
  185. Renshaw, 1991, Actuarial graduation practice and generalised linear and non-linear models, Journal of the Institute of Actuaries, 118, 295, 10.1017/S0020268100019454 · DOI
  186. Renshaw, 2003, Lee–Carter mortality forecasting with age-specific enhancement, Insurance: Mathematics and Economics, 33, 255, 10.1016/S0167-6687(03)00138-0 · DOI · Paper page
  187. Renshaw, 2003, On the forecasting of mortality reduction factors, Insurance: Mathematics and Economics, 32, 379, 10.1016/S0167-6687(03)00118-5 · DOI
  188. Renshaw, 2003, Lee-Carter mortality forecasting: A parallel generalized linear modelling approach for England and Wales mortality projections, Applied Statistics, 51, 119
  189. Renshaw, 1996, The modelling of recent mortality trends in United Kingdom male assured lives, British Actuarial Journal, 2, 449, 10.1017/S1357321700003470 · DOI
  190. Rogers, 1986, Parameterized multistate population dynamics and projections, Journal of the American Statistical Association, 81, 48, 10.2307/2287967 · DOI
  191. Rogers, 1988, Age patterns of elderly migration: An international comparison, Demography, 25, 355, 10.2307/2061537 · DOI
  192. 1995, vol. 5(3)
  193. Rogers, 1995, Population forecasting: Do simple models outperform complex models?, Mathematical Population Studies, 5, 187, 10.1080/08898489509525401 · DOI
  194. Rogers, 2005, Model migration schedules: Three alternative linear parameter estimation methods, Mathematical Population Studies, 12, 17, 10.1080/08898480590902145 · DOI
  195. Rogers, 1991, Applications of the Heligman/Pollard model mortality schedule, Population Bulletin of the United Nations, 30, 79
  196. Rogers, 1994, Parameterizing age patterns of demographic rates with the multiexponential model schedule, Mathematical Population Studies, 4, 175, 10.1080/08898489409525372 · DOI
  197. Rogers, 1978, Model migration schedules and their applications, Environment and Planning, A, 10, 475, 10.1068/a100475 · DOI
  198. Rogers, 1987, General versus elderly interstate migration and population redistribution in the United States, Research on Aging, 9, 483, 10.1177/0164027587094002 · DOI
  199. Rogers, 1991, Assessing state population projections with transparent multiregional demographic models, Population Research and Policy Review, 10, 1, 10.1007/BF00122150 · DOI
  200. Ryder, 1983, Cohort and period measures of changing fertility, vol. 2, 737

200 of 249 shown

Cited by

See all 342

Metadata

Authors
Booth, H.
Venue
International Journal of Forecasting
Publisher
Elsevier BV
Published
2006-01
Volume
22
Issue
3
Pages
547-581
ISSN
0169-2070 (ISSN-L)
DOI
10.1016/j.ijforecast.2006.04.001
OpenAlex
W2066317317
Cited by
342
References
1
FWCI
36.36
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.