Nico Keilman

Peer reviewed journals

• Keilman, Nico (2020). Modelling education and climate change. Nature Sustainability April 2020.https://rdcu.be/b3xJZ
• Keilman, Nico (2019). Mortality shifts and mortality compression in period and cohort life tables. Demographic Research 41(40). s.1147-1196
• Borgan, Ørnulf & Keilman, Nico (2018). Do Japanese and Italian Women Live Longer than Women in Scandinavia? European Journal of Population.  ISSN 0168-6577.  s 1- 13 . doi: 10.1007/s10680-018-9468-2 Vis sammendrag
• Linder, Dennis; Frigessi, Arnoldo; Piaserico, Stefano & Keilman, Nico (2017). Simulating the life course of psoriasis patients: the interplay between therapy intervention and marital status. Journal of the European Academy of Dermatology and Venereology.
• Keilman, Nico (2016). A combined Brass-Random Walk approach to probabilistic household forecasting: Denmark, Finland, and the Netherlands 2011-2041. Journal of Population Research () 1-27. 
• Keilman, Nico (2016). Household forecasting: Preservation of age patterns. International Journal of Forecasting 32(3) 726-735.
• Keilman, Nico; Tymicki, Krzysztof & Skirbekk, Vegard (2014). Measures for human reproduction should be linked to both men and women. International Journal of Population Research.  ISSN 2090-4029.
• Arkadiusz Wiśniowski, Jakub Bijak, Solveig Christiansen, Jonathan Forster, Nico Keilman, James Raymer, Peter Smith (2013) Utilising expert opinion to improve the measurement of international migration in Europe. Journal of Official Statistics 29(4)2013, 583-607 dx.doi.org/10.2478/jos-2013-0041
• Solveig Christiansen and Nico Keilman (2013) Probabilistic household forecasts based on register data - the case of Denmark and Finland. Demographic Research 28, 1263-1302. 10.4054/DemRes.2013.28.43
• Cohen, Joel; Kravdal, Øystein & Keilman, Nico (2011). Childbearing impeded education more than education impeded childbearing among Norwegian women. Proceedings of the National Academy of Science of the United States of America.  ISSN 0027-8424.  108(29), s 11830- 11835 . doi: 10.1073/pnas.1107993108
• Juha Alho and Nico Keilman, On future household structure. Journal of the Royal Statistical Society Series A 173(1)2010, 117-143
• Nico Keilman and Solveig Christiansen, Norwegian elderly less likely to live alone in the future. European Journal of Population 26 2010, DOI 10.1007/s10680-009-9195-9
• Nico Keilman, Concern in the European Union about Low Birth Rates, European View 2008
• Nico Keilman, European demographic forecasts have not become more accurate during the past 25 years, Population and Development Review, 2008, 34(1)
• Maarten Alders, Nico Keilman and Harri Cruijsen, Assumptions for long-term stochastic population forecasts in 18 European countries, European Journal of Population, 2007, 23:33-69
• Juha Alho, Maarten Alders, Harri Cruijsen, Nico Keilman, Timo Nikander and Dinh Quang Pham, New forecast: Population decline postponed in Europe, Statistical Journal of the United Nations ECE12, 2006, 23:1-10
• Nico Keilman, The Impact of Demographic Uncertainty on Liabilities for Public Old Age Pensions in Norway, New Zealand Population Review 31(1), 2005, 35-50
• Nico Keilman and Dinh Quang Pham, Time series based errors and empirical errors in fertility forecasts in the Nordic countries, International Statistical Review 72(1), 2004, 5-18, summary
• Nico Keilman, Biodiversity: The threat of small households, Nature 421, 30 January 2003, 489-490
• Nico Keilman, Dinh Quang Pham and Arve Hetland, Why population forecasts should be probabilistic - illustrated by the case of Norway, Demographic Research 6-15 May 2002, 409-454
• Nico Keilman, TFR predictions and Brownian motion theory, Yearbook of Population Research in Finland 38, 2002, 209-221
• Nico Keilman, Data quality and accuracy of United Nations population projections, 1950-95, Population Studies 55(2), 2001, 149-164
• Nico Keilman, Uncertain population forecasts, Nature 412, 6846, 2001, 490-491
• Nico Keilman and Dinh Quang Pham, Predictive intervals for age-specific fertility, European Journal of Population 16(1), 2000, 41-66
• Nico Keilman, How accurate are the United Nations' world population projections?,Population and Development Review supplement to Volume 24, 1998, 15-41

Working papers

• Nico Keilman and Dinh Quang Pham, Empirical errors and predicted errors in fertility, mortality and migration forecasts in the European Economic Area, Oslo: Statistics Norway, 2004
• Nico Keilman, Demographic implications of low fertility for family structures in Europe, Strasbourg: Council of Europe, 2003
• Nico Keilman, Children and time: The Norwegian model, NIDI Hofstee Lectures Series nr. 6, Netherlands Interdisciplinary Demographic Institute, 2001.

Books

• Tommy Bengtsson, Nico Keilman (eds.) Old and New Perspectives on Mortality Forecasting. Springer Nature Switzerland 2019, 342 pp. https://doi.org/10.1007/978-3-030-05075-7
• N. Keilman, J. Lyngstad, H. Bojer, and I. Thomsen (eds.) Poverty and Economic Inequality in Industrialized Western Societies. Oslo: Scandinavian University Press, 1998, 334 pp. http://urn.nb.no/URN:NBN:no-nb_digibok_2010052503035
• J.-P. Gonnot, N. Keilman and C. Prinz, Social Security, Household and Family Dynamics in Ageing Societies. Dordrecht: Kluwer Academic Publishers, 1995, 235 pp.
• E. van Imhoff and N. Keilman, LIPRO 2.0: An Application of a Dynamic Demographic Projection Model to Household Structure in the Netherlands. Amsterdam and Berwyn, PA: Swets and Zeitlinger Publishers, 1991, 239 pp.
• N. Keilman, Uncertainty in National Population Forecasting: Issues, Backgrounds, Analyses, Recommendations. Amsterdam and Rockland, MA: Swets and Zeitlinger Publishers, 1990, 211 pp.
•  N. Keilman, A. Kuijsten, and A. Vossen (eds.), Modelling Household Formation and Dissolution. Oxford: Clarendon Press, 1988, 298 pp.

• Divino, Fabio; Belay, Denekew Bitew; Keilman, Nico & Frigessi, Arnoldo (2021). Spatial modelling of Lexis mortality data. Spatial Statistics. ISSN 2211-6753. doi: 10.1016/j.spasta.2021.100532.
• Kastrati, Avni & Keilman, Nico (2021). Culture, tradition, and the registration of deaths: The case of Kosovo. Statistical Journal of the IAOS. ISSN 1874-7655. pre-press(1), s. 1–13. doi: 10.3233/SJI-210840. Vis sammendrag

  Population statistics for Kosovo show an unusually high share of male deaths (SMD) among all deaths. Women have a very low status in traditional parts of Kosovo – a direct consequence of the so-called Kanun of Lekë Dukagjini. This set of behavioural rules, practiced in Northern Albania and Kosovo, is strongly associated with a patriarchal culture. According to the code, a woman cannot own immovable property. Thus, to register the death of a family member at the office for civil registration is less urgent for women than for men. We assume that female deaths are under-registered. (i) A high SMD is more prevalent among the population with primary education, compared to secondary or tertiary education. (ii) More women aged 65+ receive the basic pension than there are resident women in that age group. (iii) Islamic societies report SMDs in 2017–2019 that are markedly lower than SMDs from vital registration. Registration of a death at the Islamic society is required before the funeral can take place. Other factors could also explain the high SMD: under-registration of deaths among Serbs in Kosovo, violent deaths and smoking among men, and bad physical and mental health among veterans of the war of 1999.

• Divino, Fabio; Bitew, Denekew; Keilman, Nico & Frigessi, Arnoldo (2021). Spatial Modelling of Lexis Mortality Data. Spatial Statistics. ISSN 2211-6753. 44. doi: 10.1016/j.spasta.2021.100532. Vis sammendrag

  We present a spatial approach to investigate mortality data referenced over a Lexis structure. We decompose the force of mortality into two interpretable components: a Markov random field, homogeneous with respect to age, period and cohort which explains the main pattern of mortality; and a secondary component of independent shocks, accounting for additional non structured patterns. Inference is based on a hierarchical Bayesian model with Markov chain Monte Carlo computations. We present an application to data from the Human Mortality Database, with respect to Italy and Sweden, two countries with very different histories in terms of demographic and epidemiological transitions. For each country the primary surface of spatially structured mortality and the secondary surface of additional mortality are estimated. The importance of each component is valuated by the estimated value of the respective precision parameter. In both Italy and Sweden, we discovered an interesting band of extra mortality in the secondary surface across the time domain, in the age interval between 60 and 90 years, with a slightly positive slope. The band represents a significant amount of extra mortality for the elderly population, which is otherwise incompatible with a structured dynamics in age, period and cohort.

• Keilman, Nico (2020). Évaluer les prévisions probabilistes de population. Economie et Statistique. ISSN 0336-1454. 520-521, s. 51–68.
• Keilman, Nico & Kristoffersen, Sigve (2020). European Mortality Forecasts: Are the Targets Still Moving? I Mazzuco, Stefano & Keilman, Nico (Red.), Developments in Demographic Forecasting. Springer Nature. ISSN 978-3-030-42471-8. s. 179–192. doi: 10.1007/978-3-030-42472-5_9. Fulltekst i vitenarkiv
• Keilman, Nico (2020). Evaluating probabilistic population forecasts. Economie et Statistique. ISSN 0336-1454. 520-521, s. 49–64. doi: 10.24187/ecostat.2020.520d.2033. Fulltekst i vitenarkiv
• Keilman, Nico (2020). Uncertainty in population forecasts for the twenty-first century. Annual Review of Resource Economics. ISSN 1941-1340. 12, s. 449–470. doi: 10.1146/annurev-resource-110319-114841.
• Keilman, Nico (2019). Mortality shifts and mortality compression in period and cohort life tables. Demographic Research. ISSN 1435-9871. 41, s. 1147–1196. doi: 10.4054/DemRes.2019.41.40. Fulltekst i vitenarkiv
• Keilman, Nico (2019). Erroneous population forecasts. I Bengtsson, Tommy & Keilman, Nico (Red.), Old and New Perspectives on Mortality Forecasting. Springer Nature. ISSN 978-3-030-05074-0. s. 95–111. doi: 10.1007/978-3-030-05075-7. Fulltekst i vitenarkiv Vis sammendrag

  More than 10 years have gone since the Swedish Social Insurance Agency published a series of booklets entitled Perspectives on Mortality Forecasting. Five volumes appeared in print, on different topics that all are relevant for anyone faced with the task of computing a forecast of mortality in future years. Each volume contained the papers presented in a series of workshops organized by the Stockholm Committee on Mortality Forecasting during the years 2002–2007. The current volume contains reprints of the contributions to the five booklets. Each part of this book corresponds to one original booklet. The field of mortality forecasting is in continuous change. The purpose of the current volume is to track this development by showing the reader what the main issues were some 10–15 years ago, together with an update. Therefore, the book starts with an introductory chapter, which summarizes recent new insights on the following topics: – The need for accurate mortality forecasting today for systems for pension, health care, and elderly care – Determinants and dynamics of life expectancy – Causes of death and lifestyle factors, such as smoking and obesity – Cohort and period perspectives – Compression of mortality – Joint forecasting of mortality in similar populations – From scenarios to stochastic modelling – The way conditions in early life affect mortality in later life – The increasing gap in life expectancy with respect to position in the income distribution Some of the material in the introductory chapter relates to only one of the five sections, while other items in the list above cut across themes. The last item brings up a new topic of mortality forecasting, which was not dealt with in any of the workshops.

• Keilman, Nico (2019). Family projection methods: A review. I Schoen, Robert (Red.), Analytical Family Demography. Springer Nature. ISSN 978-3-319-93227-9. s. 277–301. doi: 10.1007/978-3-319-93227-9_12. Fulltekst i vitenarkiv
• Borgan, Ørnulf & Keilman, Nico (2019). Do Japanese and Italian Women Live Longer than Women in Scandinavia? European Journal of Population. ISSN 0168-6577. 35(1), s. 87–99. doi: 10.1007/s10680-018-9468-2. Fulltekst i vitenarkiv Vis sammendrag

  Life expectancies at birth are routinely computed from period life tables. When mortality is falling, such period life expectancies will typically underestimate real life expectancies, that is, life expectancies for birth cohorts. Hence, it becomes problematic to compare period life expectancies between countries when they have different historical mortality developments. For instance, life expectancies for countries in which the longevity improved early (like Norway and Sweden) are difficult to compare with those in countries where it improved later (like Italy and Japan). To get a fair comparison between the countries, one should consider cohort data. Since cohort life expectancies can only be computed for cohorts that were born more than a hundred years ago, in this paper we suggest that for younger cohorts one may consider the expected number of years lost up to a given age. Contrary to the results based on period data, our cohort results then indicate that Italian women may expect to lose more years than women in Norway and Sweden, while there are no indications that Japanese women will lose fewer years than women in Scandinavia. The large differences seen for period data may just be an artefact due to the distortion that period life tables imply in times of changing mortality.

• Linder, Dennis; Frigessi, Arnoldo; Piaserico, Stefano & Keilman, Nico (2017). Simulating the life course of psoriasis patients: the interplay between therapy intervention and marital status. Journal of the European Academy of Dermatology and Venereology. ISSN 0926-9959. 32(1), s. 62–67. doi: 10.1111/jdv.14567. Fulltekst i vitenarkiv Vis sammendrag

  Background Psoriasis, a chronic relapsing inflammatory disease affecting primarily the skin, shows multiple comorbidities including depression, cardiovascular diseases and other relevant conditions. Psoriasis patients experience social isolation, job loss, financial difficulties and partnership problems. Inversely, psychosocial impairments may negatively influence the disease course. Objective To explore the feasibility of a model describing the interaction of psychosocial and clinical factors over the life course of patients. Methods We considered only seven states for members of a hypothetical population: single and healthy, single and having a psoriasis flare, single and ‘cured’, coupled and healthy, coupled and having a psoriasis flare, coupled and ‘cured’, and dead. Transition probabilities between states were taken from the Norwegian Population Register for the healthy population and from epidemiological research articles. Clinical experience allowed adjustments on the assumed parameters. Results Our macromodel, which simulates the effect of therapy intervention on patients’ partnership status, yields a description of the transitions between the seven states. Treatment efficacy shows only a negligible effect on the chances of living with a partner. Conclusions Mathematical modelling of interactions between social and health variables is in principle feasible. However, complex models, comprising more variables (for instance: employment status, depression level, obesity etc.), are needed for more realistic simulations for the interactions studied. As increasing the number of variables leads to an exponential increase of the model’s state space, switching to micromodelling (representing each individual separately) may be necessary.

• Keilman, Nico (2016). A combined Brass-random walk approach to probabilistic household forecasting: Denmark, Finland, and the Netherlands, 2011–2041. Journal of Population Research. ISSN 1443-2447. 34(1), s. 17–43. doi: 10.1007/s12546-016-9175-y. Vis sammendrag

  Probabilistic household forecasts to 2041 are presented for Denmark, Finland, and the Netherlands. Future trends in fertility, mortality and international migration are taken from official population forecasts. Time series of shares of the population in six different household positions are modelled as random walks with drift. Brass’ relational model preserves the age patterns of the household shares. Probabilistic forecasts for households are computed by combining predictive distributions for the household shares with predictive distributions of the populations, specific for age and sex. If current trends in the three countries continue, we will witness a development towards more and smaller households, often driven by increasing numbers of persons who live alone. We can be quite certain that by 2041, there will be between two and four times as many persons aged 80 and over who live alone when compared with the situation in 2011.

• Keilman, Nico (2016). Household forecasting: Preservation of age patterns. International Journal of Forecasting. ISSN 0169-2070. 32(3), s. 726–735. doi: 10.1016/j.ijforecast.2015.10.007. Vis sammendrag

  We formulate a time series model for household dynamics for different age groups. We model the share of the population who are in a certain household position (living alone, living with partner etc.). These household positions have very pronounced age patterns. The age profiles change slowly over time, caused by changes in home leaving behaviour of young adults, differences in survival of men and women, etc. When forecasting household positions to 2040, we want to preserve the characteristics of the age profiles. We test the Lee-Carter model and the Brass Relational method using household data for the Netherlands for the period 1996-2010. Annual shares of the population by household position, age, and sex are modeled as Random Walks with a Drift (RWD). While the Brass model has its limitations, in our application it performs better than the Lee-Carter model. The predicted age patterns based on the Brass model look more reasonable, because the Brass model is a two-parameter model, while the Lee-Carter model contains only one parameter. Also, the model parameters and standard errors of the Brass model are easier to estimate than those of the Lee-Carter model.

• Keilman, Nico; Tymicki, Krzysztof & Skirbekk, Vegard (2014). Measures for human reproduction should be linked to both men and women. International Journal of Population Research. ISSN 2090-4029. doi: 10.1155/2014/908385. Fulltekst i vitenarkiv Vis sammendrag

  We introduce the two-sex net reproduction rate (2SNRR) and the two-sex total fertility rate (2STFR)—two demographic indicators that reflect the number of children born, given age specific fertility and mortality of the adults. The main quality of these indicators is that they measure the childbearing behaviour of both women and men. The indicators have intuitive value, since they tell us to what extent adults are replaced by children. While the traditional net reproduction rate (NRR) describes general replacement trends among women only, the 2SNRR is an indicator of a population’s growth potential, irrespective of sex. We demonstrate the use of the indicators with data from Bejsce parish in Poland for the period 1800–1967 and with data from UN projections for China for future years. We discuss the consequences for our understanding of fertility trends when sex ratios deviate from normal levels.

• Wisniowski, Arkadiusz; Bijak, Jakub; Christiansen, Solveig Tobie Glestad; Forster, Jonathan; Keilman, Nico & Raymer, James [Vis alle 7 forfattere av denne artikkelen] (2013). Utilising Expert Opinion to Improve the Measurement of International Migration in Europe. Journal of Official Statistics. ISSN 0282-423X. 29(4), s. 583–607. doi: 10.2478/jos-2013-0041.
• Keilman, Nico & Keller, Lisa Dahl (2013). Hvor robust er det nye pensjonssystemet med hensyn til levealdersutviklingen? Samfunnsøkonomen. ISSN 1890-5250. s. 28–38.
• Christiansen, Solveig Tobie Glestad & Keilman, Nico (2013). Probabilistic household forecasts based on register data - the case of Denmark and Finland. Demographic Research. ISSN 1435-9871. 28, s. 1263–1302. doi: 10.4054/DemRes.2013.28.43. Vis sammendrag

  BACKGROUND Household forecasts are important for public planning and for predicting consumer demand. OBJECTIVE The purpose of this paper is to compute probabilistic household forecasts for Finland and Denmark, taking advantage of unique housing register data covering the whole populations dating back to the 1980s. A major advantage is that we do not have to rely on small population samples, and we can get quite reliable estimates even for infrequent transitions. A further merit is having time series containing the population in different household positions (dependent child, living with a spouse, living in a consensual union, living alone, lone parent, living in other private household and institutional households) by age and sex. METHODS These series enable us to estimate the uncertainty in the future distribution of the population across household positions. Combining these uncertainty parameters with expected shares computed in a deterministic household forecast, we simulate 3000 sample paths for the household shares for each age and sex. These paths are then combined with 3000 simulations from a stochastic population forecast covering the same period to obtain the predicted number of households and persons in each household position by age and sex. RESULTS According to our forecasts, we expect a strong growth in the number of private households during a 30-year period, of 27% in Finland and 13% in Denmark. The number of households consisting of a married couple or a person who lives alone are the most certain, and single parents and other private households are the most uncertain.

• Cohen, Joel; Kravdal, Øystein & Keilman, Nico (2011). Childbearing impeded education more than education impeded childbearing among Norwegian women. Proceedings of the National Academy of Sciences of the United States of America. ISSN 0027-8424. 108(29), s. 11830–11835. doi: 10.1073/pnas.1107993108.
• Keilman, Nico (2010). On age structures and mortality. I Tuljapurkar, Shripad; Ogawa, Naohiro & Gauthier, Anne (Red.), Ageing in Advanced Industrial States. Springer. ISSN 978-90-481-3552-3. s. 23–46.
• Alho, Juha & Keilman, Nico (2010). On future household structure. Journal of the Royal Statistical Society: Series A (Statistics in Society). ISSN 0964-1998. 173, s. 117–143. Vis sammendrag

  We develop a method for computing probabilistic household forecasts which quantifies uncertainty in the future number of households of various types in a country. A probabilistic household forecast helps policy makers, planners and other forecast users in the fields of housing, energy, social security etc. in taking appropriate decisions, because some household variables are more uncertain than others. Deterministic forecasts traditionally do not quantify uncertainty.We apply the method to data from Norway.We find that predictions of future numbers of married couples, cohabiting couples and one-person households are more certain than those of lone parents and other private households. Our method builds on an existing method for computing probabilistic population forecasts, combining such a forecast with a random breakdown of the population according to household position (single, cohabiting, living with a spouse, living alone etc.). In this application, uncertainty in the total numbers of households of different types derives primarily from random shares, rather than uncertain future population size. A similar method could be applied to obtain probabilistic forecasts for other divisions of the population, such as household size, health or disability status, region of residence and labour market status. Keywords: Household forecast; Norway; Population forecast; Probabilistic forecast; Random shares

• Keilman, Nico & Christiansen, Solveig Tobie Glestad (2010). Norwegian Elderly Less Likely to Live Alone in the Future. European Journal of Population. ISSN 0168-6577. 26(1), s. 47–72. doi: 10.1007/s10680-009-9195-9. Vis sammendrag

  We analyse the future household status of elderly men and women in Norway. An important finding is that persons aged 80+ are less likely to live alone in the future, and more often with a partner. The level of mortality, the mortality sex gap, union dissolution at young and intermediate ages, and entry into and exit from institutions for the elderly are possible determinants for this new trend. We use the macro simulation program LIPRO to simulate the household dynamics in Norway to 2032, and investigate the demographic reasons for the increased likelihood of living with a partner among Norwegian elderly. Mortality plays an important role, but part of the trend is already embodied in the household structure of the current population. Keywords: Elderly, Living arrangements, Household projection, Norway, LIPRO

• Keilman, Nico; Cruijsen, Harri & Alho, Juha (2008). Changing views of future demographic trends. I Alho, Juha; Hougaard Jensen, Svend & Lassila, Jukka (Red.), Uncertain demographics and fiscal sustainability. Cambridge University Press. ISSN 978-0-521-87740-4. s. 11–33.
• Alho, Juha; Cruijsen, Harri & Keilman, Nico (2008). Empirically based specification of forecast uncertainty. I Alho, Juha; Hougaard Jensen, Svend & Lassila, Jukka (Red.), Uncertain demographics and fiscal sustainability. Cambridge University Press. ISSN 978-0-521-87740-4. s. 34–54.
• Keilman, Nico (2008). Erroneous population forecasts. I Festy, Patrick & Sardon, Jean-Paul (Red.), Hommage à Gérard Calot - Profession: démographe. Institut national d'études démographiques. ISSN 978-2-7332-4023-6. s. 237–254.
• Keilman, Nico (2008). European demographic forecasts have not become more accurate over the past 25 years. Population and Development Review. ISSN 0098-7921. 34(1), s. 137–153. Vis sammendrag

  Nowadays, demographers, population statisticians, and population forecasters have richer data, more refined theories of demographic behavior, and more sophisticated methods of analysis than they had two or three decades ago. This scientific progress should have made it easier to predict demographic behavior. But my analysis of the errors in old forecasts shows that demographic forecasts published by statistical agencies in 14 European countries have not become more accurate over the past 25 years. The findings demonstrate that scientific progress in population studies during the previous two to three decades has not kept up with less predictable demographic behavior of populations in European countries. There is no reason to be more optimistic about US Census Bureau forecasts. Population forecasts are intrinsically uncertain, and hence should be couched in probabilistic terms.

• Alders, Maarten; Keilman, Nico & Cruijsen, Harri (2007). Assumptions for long-term stochastic population forecasts in 18 European countries. European Journal of Population. ISSN 0168-6577. 23, s. 33–69. doi: 10.1007/s10680-006-9104-4. Vis sammendrag

  The aim of the ‘Uncertain Population of Europe’ (UPE) project was to compute long-term stochastic (probabilistic) population forecasts for 18 European countries. We developed a general methodology for constructing predictive distributions for fertility, mortality and migration. The assumptions underlying stochastic population forecasts can be assessed by analysing errors in past forecasts or model-based estimates of forecast errors, or by expert judgement. All three approaches have been used in the project. This article summarizes and discusses the results of the three approaches. It demonstrates how the––sometimes conflicting––results can be synthesized into a consistent set of assumptions about the expected levels and the uncertainty of total fertility rate, life expectancy at birth of men and women, and net migration for 18 European countries.

• Keilman, Nico (2007). UK national population projections in perspective: How successful compared to those in other European countries? Population Trends. ISSN 0307-4463. s. 20–30. Vis sammendrag

  Compared to population forecasts of other European countries, those made in the United Kingdom during the past 30 years had somewhat larger forecast errors for fertility and smaller errors for mortality. Migration forecasts in the UK were about as accurate as the European average. After controlling for various effects such as relative data volatility both at the time a projection is made and during the period of the projection, there is no indication that recent forecasts in European countries have been more accurate than older ones. Hence population forecasts are intrinsically uncertain, and a forecast for the UK in the form of probability distributions is presented.

• Keilman, Nico (2006). Demographic Translation: From Period to Cohort Perspective and Back. I Wunsch, Guillaume; Caselli, Graziella & Vallin, Jacques (Red.), Demography: Analysis and Synthesis, A Treatise in Population Studies Volume 1. Elsevier. ISSN 978-0-12-765660-1. s. 213–223.
• Alho, Juha; Alders, Maarten; Cruijsen, Harri; Keilman, Nico; Nikander, Timo & Pham, Dinh Quang (2006). New forecast: Population decline postponed in Europe. Statistical Journal of the United Nations Economic Commision for Europe ECE12. ISSN 0167-8000. 23(1), s. 1–10. Vis sammendrag

  We present results of a probabilistic forecast for the population in 18 European countries, to 2050. Other forecasts have recently predicted a falling population size for those countries. However, there are reasons to expect higher immigration and lower mortality than the earlier forecasts did. Hence, we find that population decline is postponed in our forecast. The forecast also alerts us to the fact that many demographic developments cannot be forecasted accurately. Although ageing is certain, the extent to which this will occur is difficult to predict accurately. The number of elderly persons is very uncertain in the long run. This has major implications for all European countries in which reforms for pension systems and the provision of health care for the elderly are considered. The reforms must be robust against unexpected demographic developments.

• Keilman, Nico (2006). Households and families. I Wunsch, Guillaume; Caselli, Graziella & Vallin, Jacques (Red.), Demography: Analysis and Synthesis. Academic Press. ISSN 0-12-765664-2. s. 457–476.
• Keilman, Nico (2005). Erroneous population forecasts. I Keilman, Nico (Red.), Perspectives on Mortality Forecasting No. 2: Probabilistic Models. Swedish Social Insurance Agency. ISSN 91-7500-326-0. s. 7–26. Vis sammendrag

  This is the second volume in a series presenting papers from workshops on mortality organized by the Stockholm Committee on Mortality Forecasting. The chapters focus on probabilistic (also labeled as stochastic) forecasts, in other words forecasts in which uncertainty has been quantified. Given a history of sizable forecasting errors, the first paper, by Nico Keilman, addresses the question of why demographic forecasts are uncertain. In the second paper Juha Alho outlines the statistical background of uncertain events and forecasts of these. In the third paper Maarten Alders and Joop de Beer sketch the approach taken by Statistics Netherlands in their stochastic forecast of mortality, while in the fourth paper Shripad Tuljapurkar presents a model for mortality analysis and forecasting that has proven to be feasible for probabilistic forecasts. He gives illustrations of US and Swedish mortality, and discusses also possible implications of uncertain mortality for future pension expenditures.

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• Mazzuco, Stefano & Keilman, Nico (2020). Developments in Demographic Forecasting. Springer Nature. ISBN 978-3-030-42471-8. 261 s.
• Bengtsson, Tommy & Keilman, Nico (2019). Old and New Perspectives on Mortality Forecasting. Springer Nature. ISBN 978-3-030-05074-0. 350 s. Vis sammendrag

  More than 10 years have gone since the Swedish Social Insurance Agency published a series of booklets entitled Perspectives on Mortality Forecasting. Five volumes appeared in print, on different topics that all are relevant for anyone faced with the task of computing a forecast of mortality in future years. Each volume contained the papers presented in a series of workshops organized by the Stockholm Committee on Mortality Forecasting during the years 2002–2007. The current volume contains reprints of the contributions to the five booklets. Each part of this book corresponds to one original booklet. The field of mortality forecasting is in continuous change. The purpose of the current volume is to track this development by showing the reader what the main issues were some 10–15 years ago, together with an update. Therefore, the book starts with an introductory chapter, which summarizes recent new insights on the following topics: – The need for accurate mortality forecasting today for systems for pension, health care, and elderly care – Determinants and dynamics of life expectancy – Causes of death and lifestyle factors, such as smoking and obesity – Cohort and period perspectives – Compression of mortality – Joint forecasting of mortality in similar populations – From scenarios to stochastic modelling – The way conditions in early life affect mortality in later life – The increasing gap in life expectancy with respect to position in the income distribution Some of the material in the introductory chapter relates to only one of the five sections, while other items in the list above cut across themes. The last item brings up a new topic of mortality forecasting, which was not dealt with in any of the workshops.

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• Keilman, Nico (2021). New population forecasts predict too few births in sub-Saharan countries. The Lancet. ISSN 0140-6736. 398.
• Keilman, Nico & Mazzuco, Stefano (2020). Introduction. I Mazzuco, Stefano & Keilman, Nico (Red.), Developments in Demographic Forecasting. Springer Nature. ISSN 978-3-030-42471-8. s. 1–20. doi: 10.1007/978-3-030-42472-5_1. Fulltekst i vitenarkiv
• Keilman, Nico (2020). A probabilistic forecast for the population of Norway, Norway’s 2020 population projections: National level results, methods and assumptions. Statistics Norway. ISSN 978-82-587-1149-7. s. 177–182.
• Keilman, Nico (2020). Modelling education and climate change. Nature Sustainability. ISSN 2398-9629. s. 497–498. doi: 10.1038/s41893-020-0515-8.
• Keilman, Nico (2019). Probabilistic household and living arrangement forecasts.
• Keilman, Nico (2019). Probabilistic household and living arrangement forecasts.
• Bengtsson, Tommy; Keilman, Nico; Alho, Juha; Christensen, Kaare; Palmer, Edward & Vaupel, James W. (2019). Introduction. I Bengtsson, Tommy & Keilman, Nico (Red.), Old and New Perspectives on Mortality Forecasting. Springer Nature. ISSN 978-3-030-05074-0. s. 1–19. Vis sammendrag

  More than 10 years have gone since the Swedish Social Insurance Agency published a series of booklets entitled Perspectives on Mortality Forecasting. Five volumes appeared in print, on different topics that all are relevant for anyone faced with the task of computing a forecast of mortality in future years. Each volume contained the papers presented in a series of workshops organized by the Stockholm Committee on Mortality Forecasting during the years 2002–2007. The current volume contains reprints of the contributions to the five booklets. Each part of this book corresponds to one original booklet. The field of mortality forecasting is in continuous change. The purpose of the current volume is to track this development by showing the reader what the main issues were some 10–15 years ago, together with an update. Therefore, the book starts with an introductory chapter, which summarizes recent new insights on the following topics: – The need for accurate mortality forecasting today for systems for pension, health care, and elderly care – Determinants and dynamics of life expectancy – Causes of death and lifestyle factors, such as smoking and obesity – Cohort and period perspectives – Compression of mortality – Joint forecasting of mortality in similar populations – From scenarios to stochastic modelling – The way conditions in early life affect mortality in later life – The increasing gap in life expectancy with respect to position in the income distribution Some of the material in the introductory chapter relates to only one of the five sections, while other items in the list above cut across themes. The last item brings up a new topic of mortality forecasting, which was not dealt with in any of the workshops.

• Keilman, Nico (2018). Training Course on Demographic Analysis and Population Projections, Pristina, Kosovo, 4-7 December 2018 .
• Keilman, Nico (2018). Forventet levealder og komprimering av dødelighet: perioder og kohorter. Vis sammendrag

  Forventet levealder beregnet for et bestemt kalenderår kan gi et misvisende bilde av den virkelige levealderen. Jeg viser hvordan periode-levealderen endrer seg når aldersmønsteret for dødelighet i kohorter endrer seg. Jeg analyserer også komprimering av dødelighet rundt forventet levealder i kohorter og perioder. Jeg viser hvorfor det er stadig sterkere komprimering i periode-dødeligheten. Funnene er basert på periode- og kohortdødelighet fra Human Mortality Database for 10 land, inkludert Norge.

• Keilman, Nico (2018). Mortality shifts and mortality compression in period and cohort life tables.
• Keilman, Nico (2018). Increasing (but insufficient?) optimism about future life expectancy. N-IUSSP. Vis sammendrag

  In June 2018, Statistics Norway (2018) published its latest population forecast. The agency expects that the lifespan of men will increase to 87 years in 2050. This is six years more than the current value of 81 years. In a forecast published in 1993, the life expectancy prediction for 2050 was eight years lower than in today's population forecast. For women, the life expectancy prediction for 2050 increased by "only" four and a half years - from 84.5 years in the 1993 forecast to 89 years now. Demographers and other social scientists, in Norway as well as in other developed countries, have systematically underestimated the rate of increase of the life expectancy. Governments should be concerned about stronger ageing than official forecasts suggest.

• Keilman, Nico (2018). Økende optimisme om forventet levealder. Forskning.no. ISSN 1891-635X.
• Keilman, Nico (2018). Eldrebølgen avlyst? Bedre termometer, men pasienten er fortsatt syk. Forskning.no. ISSN 1891-635X.
• Syse, Astri; Pham, Quang Dinh & Keilman, Nico (2018). Dødelighet og levealder. I Leknes, Stefan; Løkken, Sturla Andreas Kise; Syse, Astri & Tønnessen, Marianne (Red.), Befolkningsframskrivingene 2018: Modeller, forutsetninger og resultater. Statistics Norway. ISSN 978-82-537-9767-0. s. 57–86.
• Keilman, Nico (2018). Psoriasispasientenes livsløp - påvirker behandling deres parforhold? . BestPractice Dermatologi. 9(28), s. 18–19. Vis sammendrag

  Vår analyse viser at matematisk modellering av samspillet mellom sosiale og helsevariabler i prinsippet er mulig. Vår modell er en makromodell som simulerer livsløpet til en gruppe pasienter, som befinner seg i ulike tilstander i løpet av livet. Imidlertid trenger vi mer komplekse modeller som omfatter flere variabler (for eksempel sysselsettingsstatus, depresjon, fedme etc.) for mer realistiske simuleringer av interaksjoner som studeres. Flere variabler medfører mer komplekse simuleringsmodeller. I slike tilfeller kan det være nødvendig å bytte fra en makromodell til en mikromodell. I en slik modell simuleres livsløpet til hver enkelt person.

• Keilman, Nico (2018). Morgendagens eldre: større sjanse for å bo med partner og mindre sjanse for å bo alene.
• Keilman, Nico (2017). Population Projection in Kosovo, 2017-2061: Methodology and key findings.
• Keilman, Nico; Pham, Quang Dinh & Syse, Astri (2017). Mortality shifts and mortality compression in Norway 1900-2100: periods and cohorts. Vis sammendrag

  BACKGROUND: Life expectancies and compression indicators from period life tables give a distorted picture of average life times and concentration of time of death. Cohort life tables reflect reality better. OBJECTIVE: To derive expressions for life expectancy and variance of age at death in period and cohort life tables METHODS: Focus on d_x-columns of period and cohort life tables. When radix l_0 = 1, d_x is the Age at Death Distribution (AADD). RESULTS: We derived translation formulae for period life expectancy and variation in period age at death as a function of the moments of the cohort AADD.

• Keilman, Nico (2017). Period and cohort life expectancy, mortality compression, and age at death distribution. Vis sammendrag

  We analyse the age at death distribution (AADD) of the life table, conventionally known as its d(x)-column. We derive general analytical expressions for the moments of this distribution in a period life table, written as functions of the moments in a cohort life table. The first moment is the life expectancy, while the second moment reflects compression of the age at death. The expressions are partly based on an empirical regularity that we found for Norway in observed mortality data for the years 1900-2015, and projected mortality trends until 2100. Using the formula for the first period moment of the AADD, we derive the conditions under which cohort life expectancy increases faster than period life expectancy. We also find expressions for the period life expectancy in the year a birth cohort reaches an age equal to its own life expectancy, and for the gap between the period life expectancy in a certain year and the cohort life expectancy for the cohort born that year. Furthermore, we establish a relation between the period life expectancy in a certain year t, and the lag λ that leads to an equally large cohort life expectancy for a cohort born in year t – λ. This is the number of years it takes a period life expectancy to reach the current level of cohort life expectancy. Finally, using formulae for the second moment of the AADD, we derive expressions for lags and gaps in the standard deviations of the period and cohort AADDs. The latter measures are useful for describing trends in the compression of mortality. Our data show that under this model, as long as cohort life expectancies are lower than 94 years of age for Norwegian men and lower than 92 years of age for Norwegian women, their cohort life expectancies will be below period life expectancies a number of years later, where the time interval equals the cohort’s life expectancy. When cohort life expectancies are higher, they will exceed the period life expectancies at this particular lag. The gap between cohort and period life expectancies will grow by roughly half a year for every one-year increase in cohort life expectancy – or by about one year of age for every period of 6-7 years. The lag λ defined above widens rapidly for Norwegian men and women, by approximately three to four years for every one-year increase of the cohort life expectancy. For women we find that compression of morbidity, as judged by the standard deviation of the AADD above age 30, went more than twice as fast in reality (i.e. in birth cohorts) than what we see by inspecting period data only.

• Keilman, Nico (2016). A two-sex model for first marriage.
• Keilman, Nico (2016). Probabilistic demographic forecasts.
• Keilman, Nico (2016). Barnefamilier, fruktbarhetsnivå og samfunnsplanlegging .
• Keilman, Nico (2016). Befolkning: Statistisk sentralbyrå bør endre praksis og publisere sannsynlighetsprognoser. Samfunnsøkonomen. ISSN 1890-5250. s. 59–66. Vis sammendrag

  Med jevne mellomrom beregner Statistisk sentralbyrå (SSB) prognoser for befolkningen fram til 2100: alderssammensetningen for hvert år, årlige antall fødsler og dødsfall, størrelsen på inn- og utvandringsstrømmene, antall innvandrere med ulik landbakgrunn, osv. Publisering av en ny prognose er planlagt for den 21. juni i år. I denne kommentaren bruker jeg resultater fra SSBs forrige befolkningsprognose fra 2014 for å gjøre rede for et viktig poeng: den framtidige befolkningsutviklingen er (som alle prognoser) usikker, men noen utviklinger er mer sannsynlige enn andre. Derfor bør SSB publisere sannsynlighetsprognoser, og ikke bare befolkningstall for framtidige år uten at brukeren vet hvor stor sjanse SSB knytter til den ene eller den andre befolkningsutviklingen.

• Keilman, Nico (2016). Probabilistic household forecasts for Denmark, Finland, and the Netherlands 2011-2041: Combining the Brass relational method with a Random Walk model . Vis sammendrag

  Probabilistic household forecasts to 2041 are presented for Denmark, Finland, and the Netherlands. Future trends in fertility, mortality and international migration are taken from official population forecasts. Time series of shares of the population in six different household positions are modelled as Random Walks with a Drift. Brass’ relational model preserves the age patterns of the household shares. Probabilistic forecasts for households are computed by combining predictive distributions for the household shares with predictive distributions of the populations, specific for age and sex. If current trends in the three countries continue, we will witness a development towards more and smaller households, often driven by increasing numbers of persons who live alone. We can be quite certain that by 2041, there will be between two and four times as many persons aged 80 and over who live alone when compared with the situation in 2011.

• Keilman, Nico (2016). Tar SSB høyde for den usikre demografiske utviklingen i framtiden? .
• Bernhoft, Aksel; Albihn, Ann; Hessen, Dag Olav; Holmboe-Ottesen, Gerd; Keilman, Nico & Børresen, Trond [Vis alle 9 forfattere av denne artikkelen] (2016). Hvordan skal vi sikre et landbruk som kan fø oss i framtiden? Vis sammendrag

  Menneskenes endring av naturen og jordas ressurser truer framtidens landbruk. Så hvordan skal den sårbare matproduksjonen best foregå på lang sikt når jordas befolkning øker?

• Bijak, Jakub; Alberts, Isabel; Alho, Juha; Bryant, John; Buettner, Thomas & Falkingham, Jane [Vis alle 16 forfattere av denne artikkelen] (2015). Letter to the Editor: Probabilistic Population Forecasts for Informed Decision Making. Journal of Official Statistics. ISSN 0282-423X. 31(4), s. 537–544. doi: 10.1515/JOS-2015-0033. Vis sammendrag

  Demographic forecasts are inherently uncertain. Nevertheless, an appropriate description of this uncertainty is a key underpinning of informed decision making. In recent decades, various methods have been developed to describe the uncertainty of future populations and their structures, but the uptake of such tools amongst the practitioners of official population statistics has been lagging behind. In this letter we revisit the arguments for the practical uses of uncertainty assessments in official population forecasts, and address their implications for decision making. We discuss essential challenges, both for the forecasters and forecast users, and make recommendations for the official statistics community.

• Keilman, Nico (2015). Jordens befolkning, "antall munner å mette".
• Keilman, Nico (2015). Dimension reduction by Brass' Relational Model: Household Dynamics in Five European Countries. Vis sammendrag

  We use techniques of data dimension reduction to model and predict age patterns of household dynamics in a multi-country context. Probabilistic household forecasts are computed to 2041 for Denmark, Finland, Germany, the Netherlands and Norway. Time series of shares of the population by household position are modelled as Random Walk with Drift. Brass’ relational model preserves the age patterns of the household shares. Predictive distributions for the household shares are combined with predictive distributions of the populations. The predicted continuation of current trends towards more and smaller households is driven by increasing numbers of persons who live alone. Relative prediction uncertainty in more numerous household types is smaller than that in less numerous types.

• Keilman, Nico (2015). Stochastic household forecasts for five countries in Europe.
• Keilman, Nico (2015). Stochastic household forecasts for Denmark, Finland, Germany, Netherlands, Norway.
• Keilman, Nico (2014). Probabilistic population and household forecasts.
• Keilman, Nico (2014). Dimension reduction of household parameter time series by the Brass logit model.
• Keilman, Nico (2014). Norway’s new public pension system: Is it robust against unexpected life expectancy developments? Vis sammendrag

  Norway introduced a new system for public old age pensions in January 2011. The new system leads to lower pension expenditures than the old system, because annual pension benefits under the new system are inversely proportional to the remaining life expectancy of those who retire. We can expect public pension expenditures equal to 170 billion Norwegian crowns (NOK) in 2030 and 288 billion NOK in 2050. But expenditures will be larger if retirees live longer than expected. We cannot be certain about the pace of mortality decline in the future. Therefore we have computed a probabilistic population forecast for Norway to 2050 and analysed the consequences of population growth for public old age pension expenditures. A new insight is that the new system is much less robust against unexpected longevity shocks than what was assumed earlier, in spite of the longevity adjustment. The reason is that annual pension benefits are determined when a person retires. After retirement, a retiree’s annual benefits remain the same, even when mortality changes.

• Keilman, Nico (2013). Pensjonsreformen kan bli mye dyrere enn mange tror. Vis sammendrag

  Det nye pensjonssystemet medfører lavere offentlige utgifter enn det gamle systemet. Statistisk sentralbyrå forventer en innsparing på 31 mrd. kroner i 2030 og 50 mrd. kroner i 2050. Hvis pensjonistenes levealder øker fortere enn forventet blir innsparingene mindre. Det er usikkert hvor høy denne levealderen kommer til å bli i fremtiden. Derfor har vi laget en sannsynlighetsprognose for befolkningsutviklingen fram til 2050 og beregnet konsekvensene for pensjonsutgifter. Vi finner at de forventede pensjonsutgifter i 2050 er langt fra sikre.

• Keilman, Nico (2013). Probabilistic demographic projections.
• Keilman, Nico (2013). Uncertainty in population projections - with special reference to the UK.
• Keilman, Nico (2013). "What is happening in modern demography: life course analysis, policy evaluation, dimension reduction, prediction intervals in demographic forecasting".
• Christiansen, Solveig Tobie Glestad & Keilman, Nico (2012). Probabilistic household forecasts based on register data: the case of Denmark and Finland.
• Keilman, Nico (2012). Integrated modelling of European migration flows: Methodology and main results.
• Keilman, Nico (2012). Missing girls in China will lead to fewer future births than previously thought.
• Keilman, Nico (2012). Missing girls in China will lead to fewer future births than previously thought.
• Keilman, Nico & Van Duin, Coen (2012). Stochastic household forecasts by coherent random shares predictions.
• Keilman, Nico (2012). College huishoudensprognoses.
• Keilman, Nico (2012). Challenges for statistics on households and families.
• Keilman, Nico (2012). Onzekerheid in demografische prognoses.
• Keilman, Nico (2010). On future households. Vis sammendrag

  We develop a method for computing probabilistic household forecasts which quantifies uncertainty in the future number of households of various types in a country. A probabilistic household forecast helps policy makers, planners and other forecast users in the fields of housing, energy, social security etc. in taking appropriate decisions, because some household variables are more uncertain than others. Deterministic forecasts traditionally do not quantify uncertainty. We apply the method to data from Norway.We find that predictions of future numbers of married couples, cohabiting couples and one-person households are more certain than those of lone parents and other private households. Our method builds on an existing method for computing probabilistic population forecasts, combining such a forecast with a random breakdown of the population according to household position (single, cohabiting, living with a spouse, living alone etc.). In this application, uncertainty in the total numbers of households of different types derives primarily from random shares, rather than uncertain future population size. A similar method could be applied to obtain probabilistic forecasts for other divisions of the population, such as household size, health or disability status, region of residence and labour market status.

• Keilman, Nico (2009). Failure and success: In-sample and out-of-sample demographic forecasts. Vis sammendrag

  There is a growing literature on the quality of population forecasts. All of these forecasts relate to the future, and their accuracy can be established ex post facto. However, a large literature is concerned with explanation and prediction of current, not future behaviour. This paper explores the predictive success of those in-sample predictions. Likelihood statistics for 96 life course analyses published in key demographic journals are investigated. To what extent does predictive success depend on subject matter, on sample size, on type of dependent variable? We find that variables for fertility/reproduction and pair formation/dissolution are difficult to explain, in particular events. For mortality and health variables the situation is somewhat better.

• Keilman, Nico (2008). Using deterministic and probabilistic population forecasts. Interdisciplinary Communications. ISSN 0809-8735.
• Keilman, Nico (2008). Concern in the European Union about Low Birth Rates. European View. ISSN 1781-6858. 7, s. 333–340. doi: 10.1007/s12290-008-0055-5. Vis sammendrag

  While the European Union recognizes the importance of ageing and falling populations in a number of official documents, the findings require focus. In this article, the author first identifies the documents’ failure to name a target birth rate. Second, he stresses that the often mentioned fertility level of an average of 1.5 children per woman underestimates the real figure. Thirdly, he points out the futility of fertility policies when ageing processes will continue regardless of birth rate changes. In response, policies must be coordinated in a number of areas including gender policy, employment policy, immigration policy, housing policy, family policy and economic policy.

• Keilman, Nico & Veløy, Chris (2008). AFP en ulykke for landet. [Internett]. http://nrk.no/programmer/tv/schrodingers_katt/1.6224469.
• Keilman, Nico & Veløy, Chris (2008). Europa kan halveres på to generasjoner. [Internett]. http://nrk.no/programmer/tv/schrodingers_katt/1.6224278.
• Keilman, Nico (2008). Scenarios of demographic change: the role of probabilistic approaches in population projection. Vis sammendrag

  This brief note first summarizes the four main demographic trends that are expected for the coming decades, and discusses two techniques that demographers use for mapping future population trends, namely scenarios and probabilistic projections.

• Keilman, Nico (2008). Uncertain population forecasts.
• Keilman, Nico (2008). Emerging family and household types in Europe: Issues, definitions and classifications. Vis sammendrag

  Earlier work in connection with the preparation of the 2010 round of Population and Housing Censuses for member countries of the United Nations Economic Commission of Europe revealed that in the 2000 round countries experienced difficulties in collecting data for reconstituted families and same-sex couples. Other problematic issues were the distinction between private and institutional households, and the notions of de facto and legal marital status. In addition to problems encountered in population censuses, some emerging family and household types pose problems when mapped by means of sample surveys. The UNECE Task Force on Families and Households has identified a number of additional types for which problems exist. In this paper I shall briefly discuss the problems mentioned above, and refer to possible definitions and classifications for reconstituted families, same-sex couples and couples in a LAT-relationship (Living Apart Together).

• Keilman, Nico (2006). Livslängd och invandring spräckte prognoserna. Välfärd. ISSN 1651-6710. s. 6–7. Vis sammendrag

  En analys av befolkningsprognosernas träffsäkerhet i 18 europeiska länder har visat att demograferna har varit för försiktiga i sina antaganden. I Europa har både medellivslängden och invandringen ökat kraftigare under de senaste decennierna än vad demograferna räknade med.

• Keilman, Nico (2006). European demographic forecasts have not become more accurate during the past 25 years. Vis sammendrag

  Nowadays, demographers, population statisticians, and population forecasters have richer data, more refined theories of demographic behaviour, and more sophisticated methods of analysis than they had two or three decades ago. This scientific progress should have made it easier to predict demographic behaviour. But my analyses of the errors in old forecasts show that demographic forecasts published by statistical agencies in 14 European countries have not become more accurate over the past 25 years. My findings demonstrate that scientific progress in population studies during the previous two to three decades might have been too slow to keep up with less predictable demographic behaviour of populations in European countries. There is no reason to be more optimistic about US Census Bureau forecasts. I argue that population forecasts are intrinsically uncertain, and hence should be couched in probabilistic terms.

• Alho, Juha; Cruijsen, Harri & Keilman, Nico (2006). Empirically-based specification of forecast uncertainty.
• Keilman, Nico; Cruijsen, Harri & Alho, Juha (2006). Diverging views of future demographic trends.
• Keilman, Nico & Aristotelous, Georgios (2021). Expert opinion on migration data. QuantMig Deliverable D6.1. ingen. Fulltekst i vitenarkiv
• Keilman, Nico; Pham, Quang Dinh & Syse, Astri (2018). Mortality shifts and mortality compression: The case of Norway, 1900-2060. Statistics Norway. ISSN 1892-753X. Vis sammendrag

  Historically, official Norwegian mortality projections computed by Statistics Norway have consistently under-predicted life expectancy. The projected age distribution of deaths may be used to check if the official mortality projections are plausible. The aim of the paper is to verify whether the projections predict a continuation of the ongoing compression in mortality and of the steady upward shift in the ages at which people die. We use official period data on observed (1900-2015) and projected (2016- 2060) sex- and age-specific mortality to estimate the age distribution of life table deaths. We analyse trends in life expectancy at birth, modal and median ages at death, and standard deviation of the age distribution at ages > 30. The historical shifts towards longer longevity are projected to continue into the future. The projections suggest a steady increase in the modal and the median age at death for men and women towards values between 90 and 94 years in 2060. At present these ages are in the range 83-90 years. Simultaneously, deaths become more concentrated around the mean, as the standard deviation of the age distribution is projected to fall continuously. Statistics Norway’s projection methodology is capable of tracking ongoing processes of mortality shifts towards higher ages and a compression of mortality around the modal and mean ages. Mortality projections could potentially benefit from including assessments of the age distribution of deaths.

• Kastrati, Avni; Uka, Sanije; Sojeva, Arijeta & Keilman, Nico (2017). Kosovo Population Projection 2017-2061. Kosovo Agency of Statistics. ISSN 978-9951-22-420-8.
• Keilman, Nico (2016). Fødsler og fruktbarhet i Norge. Akademika AS. Vis sammendrag

  I dette vedlegget gjøres det rede for at fruktbarhetsnivået i Norge er høyere enn det Samlet fruktbarhetstall (SFT) har vist de siste årene. Samtidig er det meget sannsynlig med en økning i årlig antall fødsler fra rundt 60 000 nå til i underkant av 70 000 om ti år. En tilfredsstillende forklaring for dagens fruktbarhetsnivå er vanskelig å gi. Derfor er predikeringer av framtidens fruktbarhet usikre. En viktig konsekvens er at Statistisk sentralbyrå bør publisere sine befolkningsprognoser i form av sannsynlighetsprognoser. Hvis vi ønsker å løse de problemene en aldrende befolkning medfører med hensyn til vårt velferdssystem, er ikke fruktbarhetsnivået av stor betydning. I denne sammenhengen er det viktig at politikere og samfunnsplanleggere vurderer tiltak innenfor arbeidsmarkedet samt skatte-, helse-, og pensjonssystemene.

• Keilman, Nico (2015). Probabilistic household forecasts for five countries in Europe. ingen. Fulltekst i vitenarkiv Vis sammendrag

  We show how techniques of data dimension reduction can be used to predict patterns of household dynamics in a multi-country context. Probabilistic household forecasts are presented for Denmark, Finland, Germany, the Netherlands, and Norway, spanning the period 2011-2041. Starting point is the population of each country broken down by age, sex, and household position as reported in the census round of 2011. Future trends in fertility, mortality and international migration are taken from official population forecasts. For changes in household structure we rely on time series of household data. Long series of household data, in which the population is broken down by household position, age, and sex, are available for Denmark (1981-2007) and Finland (1988-2009) from the population registers in these countries. For the Netherlands the series are rather short (1995-2011). Annual shares of the population by household position, age, and sex for the three time series countries are modeled using an approach that builds on Brass’ relational model originally developed to model the age pattern of mortality. We find that the household shares can be modelled as Random Walks with Drifts (RWD), independent of country. The Brass approach preserves the age patterns of the household shares. Future household shares are found by extrapolating the RWD processes. This results in household share forecasts, as well as standard errors of the forecasts. Correlations across ages and between men and women are estimated from model residuals. No time series data are available for Germany or Norway. For Germany, we use household transition rates borrowed from Denmark and Finland, but adjusted to cohabitation and marriage levels from the German Generation and Gender Survey. For Norway, we have household transition rates for the year 2010 from the population register. Future household patterns for these two countries are computed by using the multistate household model LIPRO, in which the household transition rates are applied to the household pattern from the census. Uncertainty parameters are borrowed from the time series analyses for Denmark, Finland and the Netherlands. The results show a continuation of current trends towards more and smaller households, often driven by increasing numbers of persons who live alone. The number of households increases faster than population size, which leads to falling average household size. A very consistent finding is that larger households are easier to predict than smaller households, at least when uncertainty is considered in a relative sense.

• Wisniowski, Arkadiusz; Keilman, Nico; Bijak, Jakub; Christiansen, Solveig; Forster, Jonathan & Smith, Peter [Vis alle 7 forfattere av denne artikkelen] (2011). Augmenting migration statistics with expert knowledge. NORFACE.
• Graziani, Rebecca & Keilman, Nico (2010). The sensitivity of the Scaled Model of Error with respect to the choice of the correlation parameters: A Simulation Study. Økonomisk institutt. ISSN 0809-8786. 2010(22). Vis sammendrag

  Abstract: The Scaled Model of Error has gained considerable popularity during the past ten years as a device for computing probabilistic population forecasts of the cohort-component type. In this report we investigate how sensitive probabilistic population forecasts produced by means of the Scaled Model of Error are for small changes in the correlation parameters. We consider changes in the correlation of the age-specific fertility forecast error increments across time and age, and changes in the correlation of the age-specific mortality forecast error increments across time, age and sex. Next we analyse the impact of such changes on the forecasts of the Total Fertility Rate and of the Male and Female Life Expectancies respectively. For age specific fertility we find that the correlation across ages has only limited impact on the uncertainty in the Total Fertility Rate. As a consequence, annual numbers of births will be little affected. The autocorrelation in error increments is an important parameter, in particular in the long run. Also, the autocorrelation in error increments for age specific mortality is important. It has a large effect on long run uncertainty in life expectancy values, and hence on the uncertainty around the elderly population in the future. In empirical applications of the Scaled Model of Error, one should give due attention to a correct estimation of these two parameters. Key words: Scaled model of error, Stochastic population forecast, Probabilistic cohort component model, Sensitivity, Correlation JEL classifications: C15, C49, C63, J41

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