Nico Keilman

Peer reviewed journals

• Alho, Juha & Keilman, Nico (2026) Assessing the accuracy of probabilistic  population forecasts. International Journal of Forecasting. DOI: link
• 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.

• Alho, Juha & Keilman, Nico (2026). Assessing the accuracy of probabilistic population forecasts. International Journal of Forecasting. ISSN 0169-2070. doi: 10.1016/j.ijforecast.2025.12.005. Fulltekst i vitenarkiv Vis sammendrag

  Stochastic demographic forecasts indicate to their users the ex ante level of uncertainty to be expected. There are approximately 25 years’ worth of data for population stocks and flows on the performance of such forecasts. The demographic context has numerous special features. The data come in the form of counts. The vital processes of births and deaths, and migration, combine to produce the future counts, so it is not obvious how their separate effects might be assessed. Finally, the ex post assessment is hampered by quality problems in the official population data. These issues are tackled in the context of a stochastic forecast of Norway for the years 2003–2023. A novel approach infers predictions of births, deaths, and net migration from changes in predicted population stocks in carefully chosen age segments. We use the deviance as a scoring rule to measure the lack of fit between the predictive distribution and the realized value. For a 20-year forecast horizon, predictive distributions for deaths in ages 80 years and over are less accurate than the birth distributions. The situation is the reverse for ages below 75 years. The accuracy of the predictive distribution for births appears to deteriorate much more rapidly than that of age-specific deaths for forecast horizons beyond 20 years. Forecasts for net migration are systematically less accurate than those for births or deaths.

• Smith, Peter; Keilman, Nico; Aristotelous, Georgios & Bijak, Jakub (2024). Estimating European migration flows, From Uncertainty to Policy: A Guide to Migration Scenarios. Edward Elgar Publishing. ISSN 9781035319794. s. 53–64. doi: 10.4337/9781035319800.00014. Fulltekst i vitenarkiv
• Maiolo, Valeria; Keilman, Nico & Gjertsen, Finn (2023). Sex-differences in life expectancy at birth: A descriptive analysis of the contributions of age and causes of death to the gap in Norway, 1881–2011. Social Sciences & Humanities Open (SSHO). 8(1). doi: 10.1016/j.ssaho.2023.100450. Fulltekst i vitenarkiv Vis sammendrag

  Official mortality statistics provide ample evidence that women live longer than men. In many European countries, the sex difference in life expectancy began to increase near the end of the nineteenth century, peaking between the 1960s and the 1980s, before declining again. In Norway, there was another earlier peak before the sex gap started to converge to that in other European countries. This study investigated changes in sex differences in life expectancy at birth in Norway from 1881 to 2011 as well as the contribution of broad age groups and causes of death to those differences. The total sex gap was broken down by age and cause using decomposition methods. Available mortality statistics were used for every tenth year between 1881 and 2011, excluding the war year of 1941. We regrouped the causes of death into 14 categories to reduce comparability problems across different classification systems. At the end of the 19th century, the gap in life expectancy at birth was largely due to the excessive mortality in males aged 15–29, particularly external causes of death, and in infant mortality in boys (under 1 year) due to perinatal and congenital causes. Since the 1970s, excess mortality in males aged 60 years and over has explained more than half of the sex gap, and the most relevant contributors have been circulatory diseases, neoplasms, and external causes. The recent narrowing of this gap has been related to the increase in pathologies affecting women in old age, such as senility and dementia. Differences in smoking behavior have likely played a role as well: women started smoking a few decades later than men, and they also reduced their smoking later.

• Keilman, Nico (2023). Can We Rely on Projections of the Immigrant Population? The Case of Norway. European Journal of Population. ISSN 0168-6577. 39(1). doi: 10.1007/s10680-023-09675-2. Fulltekst i vitenarkiv Vis sammendrag

  Demographic forecasters must be realistic about how well they can predict future populations, and it is important that they include estimates of uncertainty in their forecasts. Here we focus on the future development of the immigrant population of Norway and their Norwegian-born children (“second generation”), grouped by three categories of country background: 1. West European countries plus the United States, Canada, Australia, and New Zealand; 2. Central and East European countries that are members of the European Union; 3. other countries. We show how to use a probabilistic forecast to assess the reliability of projections of the immigrant population and their children. We employ the method of random shares using data for immigrants and their children for 2000–2021. We model their age- and sex-specific shares relative to the whole population. Relational models are used for the age patterns in these shares, and time series models to extrapolate the parameters of the age patterns. We compute a probabilistic forecast for six population sub-groups with immigration background, and one for non-immigrants. The probabilistic forecast is calibrated against Statistics Norway’s official population projection. We find that a few population trends are quite certain: strong increases to 2060 in the size of the immigrant population (more specifically those who belong to country group 3) and of Norwegian-born children of immigrants. However, prediction intervals around the forecasts of immigrants and their children by one-year age groups are so wide that these forecasts are not reliable.

• Divino, Fabio; Belay, Denekew Bitew; Keilman, Nico & Frigessi, Arnoldo (2021). Spatial modelling of Lexis mortality data. Spatial Statistics. 44. doi: 10.1016/j.spasta.2021.100532. Fulltekst i vitenarkiv 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.

• Kastrati, Avni & Keilman, Nico (2021). Culture, tradition, and the registration of deaths: The case of Kosovo. Statistical Journal of the IAOS. ISSN 1874-7655. 37(4), s. 1125–1137. doi: 10.3233/SJI-210840. Fulltekst i vitenarkiv 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.

• 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. 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 Vis sammendrag

  We demonstrate how a probabilistic population forecast can be evaluated, when observations for the predicted variables become available. Statisticians have developed various scoring rules for that purpose, but there are hardly any applications in population forecasting literature. A scoring rule measures the distance between the probability distribution of the predicted variable, and the actual outcome. We use scoring rules that reward accuracy (the outcome is close to the expected value of the prediction)and sharpness (the predictive distribution has low variance, which makes it difficult to hit the target). We evaluate probabilistic population forecasts for France, the Netherlands, and Norway. For all three countries, we use results from the UPE-project ("Uncertain Population of Europe"). We inspect prediction intervals for population size in the period 2004-2019 and 3000 sample paths for population pyramids for the year 2010. For the Netherlands and for Norway, we compare the UPE-results with findings from the official probabilistic population forecast by Statistics Netherlands (2001-2019) and from a probabilistic forecast for Norway (1997-2019). All forecasts were computed using the cohort-component method and stochastically varying parameters for fertility, mortality and migration. We show that the UPE-forecasts for the Netherlands and for Norway performed better than the other forecasts for these two countries. The error in the jump-off population caused a bad score for the French forecast. We evaluate the 3000 UPE-simulations of the age and sex composition predicted for the year 2010. When normalized for population numbers in each age-sex category, the predictions for the Netherlands received the best scores, except for the oldest old. The age pattern for the Norwegian score reflects the under-prediction of immigration after the enlargement of the European Union in 2005.

• 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 9783030424718. s. 179–192. doi: 10.1007/978-3-030-42472-5_9. Fulltekst i vitenarkiv Vis sammendrag

  Many statistical agencies routinely produce population forecasts, and revise these forecasts when new data become available, or when current demographic trends indicate that an update is necessary. When the forecaster strongly revises, from one forecast round to the next one, a forecast for a certain target year (for instance the life expectancy in 2050), this indicates large uncertainty connected to mortality predictions. The aim of this chapter is to shed more light on the uncertainty in mortality forecasts, by analysing the extent to which life expectancy predictions for 2030 and 2050 were revised in subsequent rounds of population forecasts published by statistical agencies in selected countries. It updates and extends earlier work that focused on United Nations and Eurostat forecasts published between 1994 and 2004. There the conclusion was that life expectancy forecasts for 18 European countries for the year 2050 had been revised upwards systematically, by around 2 years on average during the 10-year publication period. A recent analysis based on official population forecasts for Norway published in the period 1999–2018 led to the same conclusion. Here we will show that the period of upward revisions seems to have ended for some European countries.

• Keilman, Nico (2020). Évaluer les prévisions probabilistes de population. Economie et Statistique. ISSN 0336-1454. 520-521, s. 51–68. Fulltekst i vitenarkiv Vis sammendrag

  Résumé – Les statisticiens ont développé des règles de notation pour évaluer les prévisions probabilistes par rapport aux observations. Toutefois, on en trouve peu d’applications dans la littérature sur les prévisions de population. Une règle de notation mesure la distance entre la distribution prédictive et le résultat. Nous passons en revue les règles de notation qui privilégient l’exactitude (le résultat est proche de l’espérance de la distribution) et la précision (la distribution présente une faible variance, de sorte qu’il est difficile d’atteindre l’objectif). Nous évaluons les prévisions de population probabilistes établies pour la France, les Pays‑Bas et la Norvège. Les prévisions de la taille de la population totale des Pays‑Bas et de la Norvège ont obtenu de bons scores. L’erreur sur la population de base a engendré un mauvais score pour la prévision française. Nous évaluons aussi la prévision de la composition par âge et par sexe pour 2010. Les prédictions relatives aux Pays‑Bas ont reçu les meilleurs scores, excepté celles concernant les personnes très âgées. Pour la Norvège, le score de la structure par âge reflète la sous‑prédiction de l’immigration après l’élargissement de l’Union européenne en 2005.

• Keilman, Nico (2020). Modelling education and climate change. Nature Sustainability. s. 497–498. doi: 10.1038/s41893-020-0515-8. Fulltekst i vitenarkiv Vis sammendrag

  The Intergovernmental Panel on Climate Change (IPCC) is preparing its Sixth Assessment Report, to be published in 2022. The IPCC provides policy makers with the latest scientific insights on global climate change, its consequences and risks, and suggests possibilities for adaptation and mitigation. Because the future is unknown, the IPCC uses various models and scenarios for exploring how greenhouse gas emissions and other factors of climate change might develop, determined by natural science variables and socioeconomic variables. Here I argue that not only do the scenarios fail to cover a large enough range of possible futures, we do not know how probable they are, and that confuses policy makers.

• Keilman, Nico (2019). Erroneous population forecasts. I Bengtsson, Tommy & Keilman, Nico (Red.), Old and New Perspectives on Mortality Forecasting. Springer Nature. ISSN 9783030050740. s. 95–111. doi: 10.1007/978-3-030-05075-7. Fulltekst i vitenarkiv Vis sammendrag

  Given a history of sizable forecasting errors, this chapter addresses the question of why demographic forecasts are uncertain. It summarizes main patterns in ex-post observed errors in historical population forecasts, and discusses probabilistic forecasts. Illustrations come from a probabilistic forecast for the population of Norway.

• 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.

• Keilman, Nico (2019). Family projection methods: A review. I Schoen, Robert (Red.), Analytical Family Demography. Springer Nature. ISSN 9783319932279. s. 277–301. doi: 10.1007/978-3-319-93227-9_12. Fulltekst i vitenarkiv Vis sammendrag

  I review methods for projecting the family structure of a population into the future. The focus is on Western countries. I define the concept of “family”, and stress the close link between family and household. There is an important distinction between family position (the attribute of individuals) and family type (the attribute of families). I propose a typology of family projection models, and review a large number of approaches. Consistency problems (being a generalization of the two-sex problem of demography) arise when interrelated events experienced by members of the same family are modelled. Little is known about the accuracy of various types of family projection models. The chapter concludes with an evaluation and assessment of various types of family projection models, using criteria such as data requirements, output detail, ease of programming, and extrapolation of parameters. Agent Based Models and probabilistic projection models are promising avenues for future work. © Springer International Publishing AG, part of Springer Nature 2019

• Keilman, Nico (2019). Mortality shifts and mortality compression in period and cohort life tables. Demographic Research. ISSN 1435-9871. 41(40), s. 1147–1196. doi: 10.4054/DEMRES.2019.41.40. Fulltekst i vitenarkiv Vis sammendrag

  Background: When age-specific mortality falls, period life tables give a distorted view of the life expectancy (LE) and the degree of mortality compression in birth cohorts. Objective: To derive mathematical expressions for the link between LEs and compression in period life tables on the one hand and corresponding variables in birth cohorts on the other hand. Methods: We analyse the age at death distribution (AADD) computed from the life table’s d(x)-column. We derive general expressions for the moments of this distribution in a series of annual period life tables, written as functions of the moments in the AADD of cohorts. Results: We use data for Norwegian men and women to illustrate simple versions of the new expressions. The LE increases twice as fast across cohorts compared to what period life tables suggest under this model. Compression in Norwegian mortality, expressed in terms of decreasing variance of the AADDs, is approximately 40% slower in period than in cohort mortality. Conclusions: We show how one can analyse the amount of distortion in period LEs compared to cohort LEs. In addition, we show how period compression is determined by cohort compression, together with both period and cohort LEs. Contribution: We derive new expressions that link the period AADD to the cohort AADD. Under a simple linear model, we show why compression in the period AADD often goes together with increases in the period LE.

• Keilman, Nico (2018). Psoriasispasientenes livsløp - påvirker behandling deres parforhold? BestPractice Dermatologi. 9(28), s. 18–19. Fulltekst i vitenarkiv 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). Eldrebølgen avlyst? Bedre termometer, men pasienten er fortsatt syk. Forskning.no. ISSN 1891-635X. Fulltekst i vitenarkiv
• Keilman, Nico (2018). Økende optimisme om forventet levealder. Forskning.no. ISSN 1891-635X. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv 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. Fulltekst i vitenarkiv 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.

• 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. Fulltekst i vitenarkiv 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.

• Keilman, Nico & Keller, Lisa Dahl (2013). Hvor robust er det nye pensjonssystemet med hensyn til levealdersutviklingen? Samfunnsøkonomen. ISSN 1890-5250. s. 28–38. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv
• 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 (PNAS). ISSN 0027-8424. 108(29), s. 11830–11835. doi: 10.1073/pnas.1107993108. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv 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

• 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. Fulltekst i vitenarkiv 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 (2010). On age structures and mortality. I Tuljapurkar, Shripad; Ogawa, Naohiro & Gauthier, Anne (Red.), Ageing in Advanced Industrial States. Springer. ISSN 9789048135523. s. 23–46. Fulltekst i vitenarkiv
• Keilman, Nico; Cruijsen, Harri & Alho, Juha (2008). Changing views of future demographic trends. I Alho, Juha; Jensen, Svend Hougaard & Lassila, Jukka (Red.), Uncertain demographics and fiscal sustainability. Cambridge University Press. ISSN 9780521877404. s. 11–33. Fulltekst i vitenarkiv
• Alho, Juha; Cruijsen, Harri & Keilman, Nico (2008). Empirically based specification of forecast uncertainty. I Alho, Juha; Jensen, Svend Hougaard & Lassila, Jukka (Red.), Uncertain demographics and fiscal sustainability. Cambridge University Press. ISSN 9780521877404. s. 34–54. Fulltekst i vitenarkiv
• 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 9782733240236. s. 237–254. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv 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.

• 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. Fulltekst i vitenarkiv 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.

Se alle arbeider i NVA

• Bijak, Jakub & Keilman, Nico (2024). From Uncertainty to Policy: A Guide to Migration Scenarios. Edward Elgar Publishing. ISBN 9781035319794. 184 s. Fulltekst i vitenarkiv
• Mazzuco, Stefano & Keilman, Nico (2020). Developments in Demographic Forecasting. Springer Nature. ISBN 9783030424718. 261 s. Fulltekst i vitenarkiv Vis sammendrag

  This open access book presents new developments in the field of demographic forecasting, covering both mortality, fertility and migration. For each component emerging methods to forecast them are presented. Moreover, instruments for forecasting evaluation are provided. Bayesian models, nonparametric models, cohort approaches, elicitation of expert opinion, evaluation of probabilistic forecasts are some of the topics covered in the book. In addition, the book is accompanied by complementary material on the web allowing readers to practice with some of the ideas exposed in the book. Readers are encouraged to use this material to apply the new methods to their own data. The book is an important read for demographers, applied statisticians, as well as other social scientists interested or active in the field of population forecasting. Professional population forecasters in statistical agencies will find useful new ideas in various chapters.

• Bengtsson, Tommy & Keilman, Nico (2019). Old and New Perspectives on Mortality Forecasting. Springer Nature. ISBN 9783030050740. 350 s. 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.

Se alle arbeider i NVA

• Leknes, Stefan; Løkken, Sturla A K; Thomas, Michael; Jia, Zhiyang; Bergsvik, Janna & Rattsø, Jørn Gisle [Vis alle 9 forfattere av denne artikkelen] (2025). FUTUREPOP project kickoff meeting. Fulltekst i vitenarkiv
• Keilman, Nico (2023). Projections of migrant and ethnic minority populations. Fulltekst i vitenarkiv Vis sammendrag

  I discuss some of the issues connected to projections and forecasts of migrant and ethnic minority populations. Focusing on examples from the United Kingdom and Norway, I will address problems around definitions of ethnic minority and migrant groups, of data availability, of the handling of components of change, and of forecast uncertainty. I illustrate the latter topic more in detail by a probabilistic forecast to 2060 for the immigrant population of Norway and their Norwegian-born children ("second generation"), grouped by three categories of country background: 1. West-European countries plus the United States, Canada, Australia, and New Zealand; 2. Central and East-European countries that are members of the European Union; 3. other countries. I show how to use a probabilistic forecast to assess the reliability of projections of the immigrant population and their children. The results suggest that a few population trends are quite certain: strong increases to 2060 in the size of the immigrant population (more specifically those who belong to group 3) and of Norwegian-born children of immigrants. However, prediction intervals around the forecasts of immigrants and their children by one-year age groups are so wide that these forecasts are not reliable.

• Keilman, Nico (2022). Recent demographic trends in Nordic countries, with a focus on fertility in Finland and Norway. Fulltekst i vitenarkiv
• Keilman, Nico (2021). Trends in population health and demography. The Lancet. ISSN 0140-6736. 398(10300), s. 581–581. doi: 10.1016/S0140-6736(21)01113-2. Fulltekst i vitenarkiv
• Keilman, Nico (2021). New population forecasts predict too few births in sub-Saharan countries. The Lancet. ISSN 0140-6736. 398. 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 9788258711497. s. 177–182. Fulltekst i vitenarkiv
• Keilman, Nico & Mazzuco, Stefano (2020). Introduction. I Mazzuco, Stefano & Keilman, Nico (Red.), Developments in Demographic Forecasting. Springer Nature. ISSN 9783030424718. s. 1–20. doi: 10.1007/978-3-030-42472-5_1. Fulltekst i vitenarkiv Vis sammendrag

  Future trends in population size, age structure, regional distribution, and other demographic variables are important for a wide range of planning situations. Hence, many statistical agencies and independent researchers compute demographic forecasts at various levels of detail. The primary aim of this book is to sketch new developments in the field of demographic forecasting. This chapter addresses various issues taken up by the authors of this volume. We discuss deterministic and probabilistic approaches to forecast uncertainty, Bayesian and frequentist perspectives, the role of experts compared to purely data driven methods, and ways to communicate forecast results to the users.

• Keilman, Nico (2019). Probabilistic household and living arrangement forecasts. Fulltekst i vitenarkiv Vis sammendrag

  First, we discuss the shortcomings of deterministic forecasting models, and argue why probabilistic household and living arrangement forecasts are necessary for informed decision-making. Probabilistic forecasts inform the user of the uncertainty around expected household trends. As opposed to a deterministic forecast, which predicts only a few numbers (when projection variants are used) for a certain year, a probabilistic forecast tells us how likely it is that the number of households for a given year in the future will be within a certain range. Information of this kind allows policy makers, planners, and other forecast users in the fields of housing, energy, social security etc. to take appropriate decisions, because some household variables are more difficult to predict, and hence more uncertain, than others. It also guides them once actual developments start to deviate from the most likely path. New actions or updated plans are unnecessary as long as developments are likely to remain close to the expected future. Next, we review probabilistic household forecasts published since the turn of the century. An important issue is how to evaluate, ex-post facto, the accuracy of these probabilistic forecasts. We introduce the notion of a scoring function, the general idea of which is that a forecast that predicts the actual outcome with high probability should receive a better score than one that predicts the same outcome with lower probability. Scoring functions are useful for evaluating both interval forecasts (given in the form of prediction intervals with pre-specified coverage probability), and forecasts available in the form of a full probability distribution, either analytically or as a sample. Finally, we give empirical results for scoring functions applied to the first known probabilistic household 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 9783030050740. s. 1–19. 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). Probabilistic household and living arrangement forecasts. Fulltekst i vitenarkiv Vis sammendrag

  First, we discuss the shortcomings of deterministic forecasting models, and argue why probabilistic household and living arrangement forecasts are necessary for informed decision-making. Information from probabilistic forecasts allows policy makers, planners, and other forecast users in the fields of housing, energy, social security etc. to take appropriate decisions, because some household variables are more difficult to predict, and hence more uncertain, than others. It also guides them once actual developments start to deviate from the most likely path. New actions or updated plans are unnecessary as long as developments are likely to remain close to the expected future. Next, we review probabilistic household forecasts published since the turn of the century. An important issue is how to evaluate, ex-post facto, the accuracy of these probabilistic forecasts. We introduce the notion of a scoring function, the general idea of which is that a forecast that predicts the actual outcome with high probability should receive a better score than one that predicts the same outcome with lower probability. Scoring functions are useful for evaluating both interval forecasts (given in the form of prediction intervals with pre-specified coverage probability), and forecasts available in the form of a full probability distribution, either analytically or as a sample. Finally, we give empirical results for scoring functions applied to the first known probabilistic household forecasts.

• Feeney, Griffith; Keilman, Nico; Schmertmann, Carl & Bijak, Jakub (2019). Editorial: The past, present, and future of demographic research. Demographic Research. ISSN 1435-9871. 41, s. 1197–1204. doi: 10.4054/DEMRES.2019.41.41. Fulltekst i vitenarkiv
• Bengtsson, Tommy & Keilman, Nico (2019). Preface. Demographic Research Monographs. ISSN 1613-5520. s. vii–viii. Fulltekst i vitenarkiv
• 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 9788253797670. s. 57–86. Fulltekst i vitenarkiv Vis sammendrag

  Denne rapporten gjennomgår hvordan den norske befolkningen ble framskrevet i 2018. Den gir en beskrivelse av resultatene for den nasjonale befolkningen fram til 2100 og den regionale befolkningen fram mot 2040. Rapporten dokumenterer framskrivingsmodellene BEFINN og BEFREG, og beskriver hvilke forutsetninger som ligger til grunn for dette årets framskrivinger.

• Keilman, Nico (2018). Mortality shifts and mortality compression in period and cohort life tables. Fulltekst i vitenarkiv
• Keilman, Nico (2018). Increasing (but insufficient?) optimism about future life expectancy. N-IUSSP. Fulltekst i vitenarkiv 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). Morgendagens eldre: større sjanse for å bo med partner og mindre sjanse for å bo alene. Fulltekst i vitenarkiv
• Keilman, Nico (2018). Training Course on Demographic Analysis and Population Projections, Pristina, Kosovo, 4-7 December 2018. Fulltekst i vitenarkiv
• Keilman, Nico (2018). Forventet levealder og komprimering av dødelighet: perioder og kohorter. Fulltekst i vitenarkiv 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 (2017). Population Projection in Kosovo, 2017-2061: Methodology and key findings. Fulltekst i vitenarkiv
• Keilman, Nico (2017). Period and cohort life expectancy, mortality compression, and age at death distribution. Fulltekst i vitenarkiv 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; Pham, Quang Dinh & Syse, Astri (2017). Mortality shifts and mortality compression in Norway 1900-2100: periods and cohorts. Fulltekst i vitenarkiv 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 (2016). A two-sex model for first marriage. Fulltekst i vitenarkiv
• Keilman, Nico (2016). Probabilistic demographic forecasts. Fulltekst i vitenarkiv
• Keilman, Nico (2016). Tar SSB høyde for den usikre demografiske utviklingen i framtiden? Fulltekst i vitenarkiv
• Keilman, Nico (2016). Barnefamilier, fruktbarhetsnivå og samfunnsplanlegging. Fulltekst i vitenarkiv
• Keilman, Nico (2016). Befolkning: Statistisk sentralbyrå bør endre praksis og publisere sannsynlighetsprognoser. Samfunnsøkonomen. ISSN 1890-5250. s. 59–66. Fulltekst i vitenarkiv 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. Fulltekst i vitenarkiv 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 (2015). Dimension reduction by Brass' Relational Model: Household Dynamics in Five European Countries. Fulltekst i vitenarkiv 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.

• 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. Fulltekst i vitenarkiv 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). Stochastic household forecasts for Denmark, Finland, Germany, Netherlands, Norway. Fulltekst i vitenarkiv
• Keilman, Nico (2015). Jordens befolkning, "antall munner å mette". Fulltekst i vitenarkiv
• Keilman, Nico (2014). Norway’s new public pension system: Is it robust against unexpected life expectancy developments? Fulltekst i vitenarkiv 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 (2014). Dimension reduction of household parameter time series by the Brass logit model. Fulltekst i vitenarkiv
• Keilman, Nico (2014). Probabilistic population and household forecasts. Fulltekst i vitenarkiv
• Keilman, Nico (2013). Uncertainty in population projections - with special reference to the UK. Fulltekst i vitenarkiv
• Keilman, Nico (2013). Pensjonsreformen kan bli mye dyrere enn mange tror. Fulltekst i vitenarkiv 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). "What is happening in modern demography: life course analysis, policy evaluation, dimension reduction, prediction intervals in demographic forecasting". Fulltekst i vitenarkiv
• Keilman, Nico (2013). Probabilistic demographic projections. Fulltekst i vitenarkiv
• Christiansen, Solveig Tobie Glestad & Keilman, Nico (2012). Probabilistic household forecasts based on register data: the case of Denmark and Finland. Fulltekst i vitenarkiv
• Keilman, Nico (2012). Integrated modelling of European migration flows: Methodology and main results. Fulltekst i vitenarkiv
• Keilman, Nico (2012). Onzekerheid in demografische prognoses. Fulltekst i vitenarkiv
• Keilman, Nico (2012). Missing girls in China will lead to fewer future births than previously thought. Fulltekst i vitenarkiv
• Keilman, Nico (2012). College huishoudensprognoses. Fulltekst i vitenarkiv
• Keilman, Nico (2012). Challenges for statistics on households and families. Fulltekst i vitenarkiv
• Keilman, Nico (2012). Missing girls in China will lead to fewer future births than previously thought. Fulltekst i vitenarkiv
• Keilman, Nico & Duin, Coen Van (2012). Stochastic household forecasts by coherent random shares predictions. Fulltekst i vitenarkiv
• Keilman, Nico (2010). On future households. Fulltekst i vitenarkiv 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. Fulltekst i vitenarkiv 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). Uncertain population forecasts. Fulltekst i vitenarkiv
• Keilman, Nico (2008). Using deterministic and probabilistic population forecasts. Interdisciplinary Communications. ISSN 0809-8735. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv 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). Europa kan halveres på to generasjoner. [Internet]. http://nrk.no/programmer/tv/schrodingers_katt/1.6224278. Fulltekst i vitenarkiv
• Keilman, Nico (2008). Emerging family and household types in Europe: Issues, definitions and classifications. Fulltekst i vitenarkiv 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 (2008). Scenarios of demographic change: the role of probabilistic approaches in population projection. Fulltekst i vitenarkiv 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 & Veløy, Chris (2008). AFP en ulykke for landet. [Internet]. http://nrk.no/programmer/tv/schrodingers_katt/1.6224469. Fulltekst i vitenarkiv
• Keilman, Nico (2023). A probabilistic forecast of the immigrant population of Norway. Statistisk sentralbyrå (SSB). Fulltekst i vitenarkiv Vis sammendrag

  Abstract: We present a probabilistic forecast for the immigrant population of Norway and their Norwegian-born children (“second generation”) broken down by age, sex, and three types of country background: 1. West European countries plus the United States, Canada, Australia, and New Zealand; 2. East European countries that are members of the European Union; 3. other countries. First, we compute a probabilistic forecast of the population of Norway by age and sex, but irrespective of migration background. The future development of the population is simulated 3 000 times by stochastically varying parameters for mortality, fertility and international migration to 2060. We add migrant group detail using stochastically varying random shares to split up each result from the previous step into six sub-groups with immigration background, and one for the non-immigrants. The probabilistic forecast is calibrated against the Medium Variant of Statistics Norway’s official population projection.

• 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. Statistisk sentralbyrå (SSB). Fulltekst i vitenarkiv 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 9789951224208. Fulltekst i vitenarkiv
• Keilman, Nico (2016). Fødsler og fruktbarhet i Norge. Akademika AS. Fulltekst i vitenarkiv 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. Fulltekst i vitenarkiv
• 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. Fulltekst i vitenarkiv 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

Se alle arbeider i NVA