
Keilman, Nico
(2022).
Recent demographic trends in Nordic countries, with a focus on fertility in Finland and Norway.


Keilman, Nico
(2021).
New population forecasts predict too few births in subSaharan countries.
The Lancet.
ISSN 01406736.
398.


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.
p. 177–182.


Feeney, Griffith; Keilman, Nico; Schmertmann, Carl & Bijak, Jakub
(2019).
Editorial: The past, present, and future of demographic research.
Demographic Research.
ISSN 14359871.
41,
p. 1197–1204.
doi:
10.4054/DEMRES.2019.41.41.

Bengtsson, Tommy & Keilman, Nico
(2019).
Preface.
Demographic Research Monographs.
ISSN 16135520.
p. vii–viii.

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.
In Bengtsson, Tommy & Keilman, Nico (Ed.),
Old and New Perspectives on Mortality Forecasting.
Springer Nature.
ISSN 9783030050740.
p. 1–19.
Show summary
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, 47 December 2018
.

Keilman, Nico
(2018).
Forventet levealder og komprimering av dødelighet: perioder og kohorter.
Show summary
Forventet levealder beregnet for et bestemt kalenderår kan gi et misvisende bilde av den virkelige levealderen. Jeg viser hvordan periodelevealderen 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 periodedødeligheten. 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.
NIUSSP.
Show summary
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.



Syse, Astri; Pham, Quang Dinh & Keilman, Nico
(2018).
Dødelighet og levealder.
In Leknes, Stefan; Løkken, Sturla Andreas Kise; Syse, Astri & Tønnessen, Marianne (Ed.),
Befolkningsframskrivingene 2018: Modeller, forutsetninger og resultater.
Statistics Norway.
ISSN 9788253797670.
p. 57–86.

Keilman, Nico
(2018).
Psoriasispasientenes livsløp  påvirker behandling deres parforhold?
.
BestPractice Dermatologi.
9(28),
p. 18–19.
Show summary
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, 20172061: Methodology and key findings.

Keilman, Nico; Pham, Quang Dinh & Syse, Astri
(2017).
Mortality shifts and mortality compression in Norway 19002100: periods and cohorts.
Show summary
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_xcolumns 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.
Show summary
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 19002015, 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 oneyear increase in cohort life expectancy – or by about one year of age for every period of 67 years. The lag λ defined above widens rapidly for Norwegian men and women, by approximately three to four years for every oneyear 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 twosex 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 18905250.
p. 59–66.
Show summary
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 20112041: Combining the Brass relational method with a Random Walk model
.
Show summary
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?
.


Bijak, Jakub; Alberts, Isabel; Alho, Juha; Bryant, John; Buettner, Thomas & Falkingham, Jane
[Show all 16 contributors for this article]
(2015).
Letter to the Editor: Probabilistic Population Forecasts for Informed Decision Making.
Journal of Official Statistics.
ISSN 0282423X.
31(4),
p. 537–544.
doi:
10.1515/JOS20150033.
Show summary
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.
Show summary
We use techniques of data dimension reduction to model and predict age patterns of household dynamics in a multicountry 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 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?
Show summary
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.
Show summary
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.
Show summary
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 oneperson 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: Insample and outofsample demographic forecasts.
Show summary
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 insample 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).
Concern in the European Union about Low Birth Rates.
European View.
ISSN 17816858.
7,
p. 333–340.
doi:
10.1007/s1229000800555.
Show summary
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.
[Internet].
http://nrk.no/programmer/tv/schrodingers_katt/1.6224469.

Keilman, Nico & Veløy, Chris
(2008).
Europa kan halveres på to generasjoner.
[Internet].
http://nrk.no/programmer/tv/schrodingers_katt/1.6224278.


Keilman, Nico
(2008).
Uncertain population forecasts.

Keilman, Nico
(2008).
Emerging family and household types in Europe: Issues, definitions and classifications.
Show summary
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 samesex 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, samesex couples and couples in a LATrelationship (Living Apart Together).

Keilman, Nico
(2006).
Livslängd och invandring spräckte prognoserna.
Välfärd.
ISSN 16516710.
p. 6–7.
Show summary
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.
Show summary
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).
Empiricallybased specification of forecast uncertainty.

Keilman, Nico; Cruijsen, Harri & Alho, Juha
(2006).
Diverging views of future demographic trends.

Alho, Juha; Alders, Maarten; Cruijsen, Harri; Keilman, Nico; Nikander, Timo & Pham, Quang Dinh
(2005).
Population decline postponed in Europe.
Statistical Magazine.
Show summary
The United Nations and Eurostat recently predicted that the population in 18 European countries will fall in the future. However, the results of a new forecast show that there is reason to expect higher immigration and lower mortality than that predicted by the UN and Eurostat. Hence, the population decline will happen later, and perhaps as late as 2050. For Norway, a population of 5.75 million is anticipated by 2050, slightly higher than the official forecast by Statistics Norway in 2002.

Alders, Maarten; Keilman, Nico & Cruijsen, Harri
(2005).
Assumptions for national stochastic population forecasts in 18 European countries.
Show summary
In order to develop and implement stochastic population forecasting for European countries, the European Commission has commissioned the project �Changing population of Europe: uncertain future� to researchers from Joensuu University and the statistical offices of Finland, the Netherlands and Norway. The objective was to develop a general methodology for assessing predictive distributions for fertility, mortality and migration. Generally speaking the assumptions underlying stochastic population forecasts can be assessed by means of analyses of errors of past forecasts, modelbased estimates of forecast errors, and expert judgement. All these approaches have been thoroughly investigated in the project. The paper summarises and discusses the results of the different approaches. It demonstrates how the, sometimes conflicting, results can be synthesised into a consistent set of assumptions. Finally, the paper presents the main assumptions about the total fertility rate, life expectancy at birth of men and women, and net migration for 18 European countries.

Keilman, Nico & Vogt, Yngve
(2004).
Utrygg pensjonsreform: Samfunnet kan tape skyhøye beløp.
Aftenposten (morgenutg. : trykt utg.).
ISSN 08043116.
Show summary
Datasimuleringer viser at pensjonskommisjonen og politikerne er naive. De har ikke tatt hensyn til usikkerhetsanalyser i befolkningsutviklingen under planleggingen av det nye pensjonssystemet. Det kan koste samfunnet dyrt.

Keilman, Nico
(2004).
Long term public old age pension obligations in a stochastic demographic setting in Norway.

Keilman, Nico Willem
(2003).
Model based errors and empirical errors in fertility and mortality forecasts for the Nordic countries.

Keilman, Nico Willem
(2003).
Do Cause of Death analyses improve the accuracy of mortality forecasts?

Keilman, Nico Willem
(2002).
Book review of S. K. Smith, J. Tayman, and D. Swanson ¿ State and Local Population Projections: Methodology and Analysis¿.
Population Studies.
ISSN 00324728.
56(3),
p. 340–341.

Keilman, Nico Willem & Pham, Quang Dinh
(2002).
Time series based errors and empirical errors in fertility forecasts in the Nordic countries.
Show summary
We use time series models to derive model based prediction intervals for the Total Fertility Rate (TFR) in Norway, Sweden, Finland, and Denmark up to 2050. For the short term (510 yrs), expected TFRerrors are compared with empirical forecast errors observed in historical population forecasts prepared by the statistical agencies in these countries since 1969. Moreover, we analyse mediumterm and longterm (up to 50 years) error patterns based on socalled naïve forecasts, i.e. forecasts that assume that recently observed TFRlevels also apply for the future.

Keilman, Nico Willem
(2002).
DEMOGRAPHIC AND SOCIAL IMPLICATIONS OF LOW FERTILITY FOR FAMILY STRUCTURES IN EUROPE.
Show summary
This text is a progress report for the study on ¿Demographic and social implications of new patterns in the family and nonfamily sectors¿ undertaken for the Council of Europe. The study investigates the relationship between low fertility and new patterns in the family and nonfamily sectors. The nonfamily sector is to be understood as consisting of oneperson households and childless couples (i.e. couples who have not, or not yet, given birth to any children). The study discusses also the social implications of childlessness, single child families, and other family sizes, thereby focusing on social cohesion.
The study is limited to birth orderspecific fertility, and couples, thereby not distinguishing between married and cohabiting couples. First, a theoretical perspective on childlessness is given. Next, the impact of changes in birth orderspecific fertility on family size is analysed, by using the results from a simulation study, in which I analyse how family sizes change when the quantum and tempo of age and birth orderspecific fertility change. The model applied here is a multidimensional life table. The final section discusses possible consequences for social cohesion and social exclusion of the trends identified in the previous section.

Keilman, Nico Willem
(2001).
Types of models for projecting mortality.
Show summary
The short paper presents a systematic overview of various types of models for projecting mortality. The framework is that of population forecasts of the cohortcomponent type for the elderly at the national level.I distinguish between demographic and nondemographic models. Demographic models are rather mechanistic, although they include various degrees of judgement. Demographic models can be divided further into extrapolation models and interpolation models. Nondemographic models build on epidemiology and biomedical sciences, and thus are much more of a causal nature than the demographic ones. I distinguish between macro models and micro models.

Keilman, Nico Willem; Pham, Dinh Quang & Hetland, Arve
(2001).
Norway's uncertain demographic future.
Show summary
The demographic future of any country is uncertain. There is not just
one possible future, but many. Some of these are more probable than
others. Therefore, an exploration of a country's demographic future
should include two elements: first, a range of possible outcomes, and
second, a probability attached to that range. Together, these two
constitute a predictive interval for the variable concerned.
The current paper presents predictive intervals for the future size and
agesex composition of Norway's population up to the year 2050. These
intervals have been obtained by stochastic simulation, on the basis of
repeated runs of the cohortcomponent model. We describe the method
briefly. We also compare our results with those of the official
population forecast computed by Statistics Norway, and explain why the
latter forecast does not give an appropriate indication of forecast
uncertainty.

Keilman, Nico Willem
(2001).
Population Forecasting.
Show summary
Cohort component method, ratio method, empirical forecast accuracy, stochastic forecasts, use of population forecasts

Keilman, Nico Willem
(2001).
Age structural transitions in historical perspective: What can we learn from the past?
Show summary
The paper reviews what can we learn from age structures, and changes therein, when using stable population theory, inverse/back projections and generalizations thereof, variable growth rate method, and old population forecasts. Following the discussion of the accuracy of age structure forecasts for the elderly, I also speculate how we can improve the accuracy of mortality forecasts. The focus is on industrialized countries.

Keilman, Nico Willem
(2000).
Andrew Hinde, Demographic Methods. London: Arnold Publishers 1998.
European Journal of Population.
ISSN 01686577.
16(2),
p. 187–188.


Keilman, Nico; Pham, Quang Dinh & Syse, Astri
(2018).
Mortality shifts and mortality compression: The case of Norway, 19002060.
Statistics Norway.
ISSN 1892753X.
Show summary
Historically, official Norwegian mortality projections computed by Statistics Norway have consistently underpredicted 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 (19002015) and projected (2016
2060) sex and agespecific 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 8390 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 20172061.
Kosovo Agency of Statistics.
ISSN 9789951224208.

Keilman, Nico
(2016).
Fødsler og fruktbarhet i Norge.
Akademika AS.
Show summary
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.
Full text in Research Archive
Show summary
We show how techniques of data dimension reduction can be used to predict patterns of household dynamics in a multicountry context.
Probabilistic household forecasts are presented for Denmark, Finland, Germany, the Netherlands, and Norway, spanning the period 20112041. 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 (19812007) and Finland (19882009) from the population registers in these countries. For the Netherlands the series are rather short (19952011). 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
[Show all 7 contributors for this article]
(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 08098786.
2010(22).
Show summary
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 cohortcomponent 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 agespecific fertility forecast error increments across time and age, and changes in the
correlation of the agespecific 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

Keilman, Nico Willem & Pham, Quang Dinh
(2004).
Empirical errors and predicted errors in fertility, mortality and migration forecasts in the European Economic Area.
Statistics Norway.
ISSN 1892753X.
Show summary
We analyse empirical errors observed in historical population forecasts produced by statistical agencies in 14 European countries since 1950. The focus is on forecasts for three demographic variables: fertility (Total Fertility Rate  TFR), mortality (life expectancy at birth), and migration (net migration). We inspect forecast bias and forecast accuracy in the historical forecasts, as well as the
distribution of the errors. Finally, we analyse for each of the three variables correlation patterns in forecast errors across countries and, for mortality, the correlation between errors for men and women.
In the second part of the report we use time series model to construct prediction intervals to 2050 for the TFR, the life expectancy for men and women, and net migration in 18 European countries. GARCH models are used for fertility and mortality, while net migration is modelled as an autoregressive process.
Keywords: stochastic population forecast, empirical forecast errors, prediction intervals, GARCHmodels, TFR, life expectancy, net migration, EEA.
JEL classification: C22, J11.

Keilman, Nico Willem
(2004).
Conséquences démographiques et sociales d'une faible fécondité pour les structures familiales en Europe.
Council of Europe Publishing/Editions du Conseil de l'Europe.
ISSN 9287154414.


Keilman, Nico Willem
(2003).
Demographic implications of low fertility for family structures in Europe.
Strasbourg: Council of Europe.
Show summary
This text reports the findings from the study on
�Demographic and social implications of new patterns in the family and nonfamily sectors� undertaken for the Council of
Europe. The study investigates the relationship between low fertility and new patterns in the family and non family sectors. The study discusses also the social implications
of childlessness, single child families, and other family sizes, thereby focusing on social cohesion.
The study is limited to birth orderspecific fertility, and couples, thereby not distinguishing between married and cohabiting couples. First, a theoretical perspective on childlessness is given. Next, the impact of changes in birth orderspecific fertility on family size is analysed, by using the results from a simulation study, in which I
analyse how family sizes change when the quantum and tempo of age and birth orderspecific fertility change. The model applied here is a multidimensional life table. The final section discusses possible consequences for social cohesion and social exclusion of the trends identified in the previous section, with a focus on poverty.

Keilman, Nico Willem
(2003).
Demographic and social implications of low fertility for family structures in Europe.
Council of Europe Publishing.
ISSN 9287153426.
Show summary
The study sets out to investigate the relationship between low fertility and new patterns in the family and nonfamily sectors. It examines the social implications of childlessness, single child families, and other family sizes, with an emphasis on questions of social cohesion.
Firstly a theoretical perspective on childlessness is given. This is followed by an analysis of the impact of changes in birth orderspecific fertility on family size using the results from a simulation study which analyses how family sizes change when the level and timing of age and birth orderspecific fertility change. The final section discusses possible consequences for social cohesion and social exclusion of the trends identified in the previous sections with a focus on poverty.

Keilman, Nico Willem; Pham, Quang Dinh & Hetland, Arve
(2001).
Norway's Uncertain Demographic Future.
Statistics Norway.
ISSN 8253750021.
Show summary
This report presents prediction intervals for the future population of Norway broken down by age and sex to the horizon 2050. We combined Monte Carlo simulation with a cohortcomponent population projection model to obtain 5,000 simulations of the population. The odds are four
to one (80 per cent chance) that Norway's population, now 4.5 million, will number between 4.3 and 5.4 million in the year 2025, and 3.76.4 million in 2050. There is a clear tradeoff between greater accuracy
(higher odds) and higher precision (narrower intervals). Odds of 19 to one (95 per cent chance) result in a wider interval: 4.15.7 million in 2025, and 3.27.3 million in 2050. The probabilistic population forecasts of the youngest and the oldest age groups show largest
uncertainty, because fertility and mortality are hard to predict. As a result, prediction intervals in 2030 for the population younger than 20 years are so wide, that the forecast is not very informative.
International migration shows large prediction intervals around expected levels, but its impact on the age structure is modest. In 2050, uncertainty has cumulated so strongly, that intervals are very large for virtually all age groups, in particular when the intervals are judged in a relative sense (compared to the median forecast).
According to our statistical model, the expected accuracy of the total population size forecast published by Statistics Norway is somewhat below twothirds on the long run, and a little above that level on the short run.

Keilman, Nico Willem
(2001).
Children and time: The Norwegian model.
Netherlands Interdisciplinary Demographic Institute.
Show summary
Norway's family policy has received widespread attention in the Netherlands in recent years. The extremely generous parental leave arrangements and reasonable level of childcare facilities are designed to make it easier for Norwegian women to combine a family and a professional career. In this lecture I shall look into the impact of this family policy on the labour force participation and fertility of women in Norway. The more unintentional effects, such as the time pressures this places on many families with young children, will also be dealt with. Should the Netherlands follow Norway's example?

Keilman, Nico Willem
(2000).
Demographic Translation: From Period To Cohort Perspective And Back.
Department of Economics, University of Oslo.
ISSN 08011117.
Show summary
[Internet http://www.sv.uio.no/sosoek/memo/memopdf/memo0600.pdf]
When successive birth cohorts of women get their children at
progressively lower ages, births that would have occurred during a
certain period without changes in the timing, are now "squeezed" into a
shorter period. This pushes period fertility up, and the period Total
Fertility Rate (TFR) will be inflated, compared to the TFR that would
have occurred without changes in the timing. In general, even when the
number of children per woman is constant over successive birth cohorts,
period fertility levels may vary  they are inflated in years in which
childbearing is accelerated, and deflated when women postpone
childbearing. Thus period fertility cannot be used as a reliable
indicator for the level of cohort fertility: period fertility may be
"distorted" in times of tempo changes in cohort fertility. At the same
time cohort fertility cannot be fully understood without studying
periods.
These qualitative links between period and cohort fertility are
straightforward. But the detailed interplay between period and cohort
fertility, both its quantum (level) and tempo (timing) aspects, can be
formalized mathematically. The resulting expressions constitute the
core of what has become known as the theory of demographic translation,
a term coined by Norman Ryder. This chapter gives a brief general
overview of demographic translation theory. It integrates Ryder's
findings from the 1960s that he applied to agespecific fertility, with
more recent insights, which can be used for analysing other demographic
processes, such as childlessness, first marriage, and divorce.

Imhoff, Evert Van & Keilman, Nico Willem
(1999).
On the quantum and tempo of fertility: Comment.
Netherlands Interdisciplinary Demographic Institute, The Hague.
Show summary
[Internet: http://www.nidi.nl/public/nidi_wp_1999_2.pdf]
The paper comments on the Bongaarts/Feeney adjustment method for period
Total Fertility. First, the method is based on unsuitable fertility
measures, which tend to exaggerate translational distortion caused by
tempo shifts in the fertility of birth cohorts. Second, the BF
assumption that periodbyperiod changes are independent of age and
cohort is not supported by the data.