The population of Finland in 2050 and beyond

During the next fifty years, the growth of the population of Finland is expected to slow down, and turn into decline. The age-distribution is expected to become older because mortality declines. In particular, the share of the working age population will decline. This development is accentuated by the fact that the large post war birth cohorts reach retirement age during the next decade. Although there is general agreement about these broad features, it is difficult to say exactly when a decline might begin, or how high the age-dependency ratio will be like in the future. A study of past forecasts shows that demographic developments have repeatedly taken forecasters by surprise. We show that the forecast errors in Finland have not been related to other social phenomena, such as wars or economic crises, in a simple way. In fact, our understanding of the causes of the past errors is poor. Therefore, it is important to recognize that our current view of future population development may similarly be in error. We account for the uncertainty by statistical modeling. In this way it is possible to estimate, how large errors one should expect, if future demographic development is as volatile as in the past. Using stochastic simulation, we derive a predictive distribution for the future population vector that gives a realistic indication of the uncertainty to be expected

A statistical look at Modeen's forecast of the population of Finland in 1934

Gunnar Modeen made the first cohort-component forecast for Finland in 1934. This was a time when demographic transition was just over, but that fact could not have been known at the time. Would it have made any difference if Modeen had had the tools of modern time-series analysis available? We find that the essential question of how to deal with changing trends would have still been difficult. However; the modern tools would have given the forecast user a realistic indicator of the uncertainty of the forecast being made. This suggests that in developing countries that are undergoing transition now, more effort should he paid to the analysis of uncertainty of forecasting

A note on the use of anticipatory covariates in event history analysis

Anticipatory covariates are regressors whose values become known only after the value of the dependent variable has been ascertained. Hoem (1995) has given an informal discussion concerning the possible pitfalls in the use of such covariates in event history analysis. This paper complements Hoem’s findings by using simple linear regression as the framework. It turns out that complex patterns of bias may be introduced by the use of anticipatory covariates. In all cases it may not be possible to guarantee that the magnitude of the bias remains small. Therefore, extreme care is needed in interpreting results from studies that have relied on anticipatory covariates

Metsien tulevan kehityksen ennakointi

Tieteen tori: Metsien kehityksen ennustamisen epävarmuu

Aggregate mortality risk and the insurance value of annuities

Future improvements in mortality are difficult to forecast. In this paper, we incorporate uncertainty about future mortality, or aggregate mortality risk, into an otherwise standard life cycle model with an intertemporal consumption-savings decision. The aggregate mortality process is calibrated based on European mortality series. We use the model to quantify the welfare cost of aggregate mortality risk and the extent to which individuals can insure themselves against it using life annuities with a constant payout stream

On the fade-away of an initial bias in longitudinal surveys

We propose a novel view of selection bias in longitudinal surveys. Such bias may arise from initial nonresponse in a probability sample, or it may be caused by self-selection in an internet survey. A contraction theorem from mathematical demography is used to show that an initial bias can "fade-away" in later panel waves, if the transition laws in the observed sample and the population are identical. Panel attrition is incorporated into the Markovian framework. Extensions to Markov chains of higher order are given, and the limitations of our approach under population heterogeneity are discussed. We use empirical data from a German Labour Market Panel to demonstrate the extend and speed of the fade-away effect. The implications of the new approach on the treatment of nonresponse, and attrition weighting, are discussed

Aging of a giant: a stochastic population forecast for China, 2001-2050

This paper presents a stochastic population forecast for China with a special emphasis on population aging. Stochastic forecasting methods have the advantage of producing a projection of the future population including a probabilistic prediction interval. The socalled scaled model for error was used to quantify the uncertainty attached to the population predictions in this study. Data scarcity was a major problem in the specification of the expected error of the population forecast. Therefore, the error structures estimated for European countries were employed with some modifications taking the large size and heterogeneity of the Chinese population into account. The stochastic forecast confirms the expectation of extremely rapid population aging during the first half of the 21st century in China. The old age dependency ratio (OADR) will increase with certainty. By mid-century, with 80% probability, the OADR will lie between 0.41 and 0.56, with the median of the predictive distribution being 0.48, nearly five-fold its current value of 0.1. In particular, the oldest-old population will grow faster than any other age group. This development has major implications for China: to smoothly adjust current birth control policies to less restrictive ones, strengthen the family support system, and improve the social security system for the elderly.China

The Role and Potential of Social Intranet in an Organisational Context : A Case Study of Yleisradio - The National Broadcasting Company of Finland

This thesis explores the relationship of social software and organisations. It discusses how social intranet can create value for the adopting company, what impact and role it has inside an organisation and how organisation can generate return on investment for social intranet. The literature presented in this paper establishes an understanding that social knowledge management software does not create value for organisation by itself, but that its value is strongly dependent on the context it is implemented. Although we refer to technology and IT while discussing about social intranets, the adoption of these type of systems should be regarded for being much more than pure technical projects. The literature presented takes a comprehensive approach in the purpose of understanding the complexity of the topic, where a variety of factors influence the outcome of software implementation and value of utilisation. In the context of organisational information and knowledge management-, internal communications- and collaboration development, organisational culture and managerial behaviour are key determinants for software’s value creation. The case study of this thesis will provide a cross-section throughout the adoption project of social intranet Yle+. This thesis suggests that already starting from establishing project scope and system design, it is important that the organisation and its’ people are involved in the process. The level of individual awareness, desire and knowledge - terms that are often encountered in the field of change management – are in key position in determining the success of IT implementation. Before the implementation can take place, it is crucial that the organisation is ready and positive for the adoption. Naturally, a succesfull adoption will create favourable basis for future development of work whilst providing a healthy basis for organisation-technology fit. The case study also suggests that organisation should prepare for change in how work is conducted inside the organisation. For extending the potential and significance of social intranet in an organisational context, new tools are suggested for requiring new approach in how work, collaboration and communications takes place. If the organisation is not capable, willing or brave enough to change the existing processes and communication methods, the value of social intranet is unlikely to reach its highest level. Therefore, this thesis suggests that compared to traditional static intranets and organisational databanks, the utilisation of social software requires change in how organisation works and communicates internally. As the case study will show, the true potential of social intranet may be revealed after some time has passed from the adoption and this is something that may not have been comprehended in the original vision and motivation for adoption

The fade away effect of initial nonresponse bias in regression analysis

High nonresponse rates have become a rule in survey sampling. In panel surveys there occur additional sample losses due to panel attrition, which are thought to worsen the bias resulting from initial nonresponse. However, under certain conditions an initial wave nonresponse bias may vanish in later panel waves. We study such a "Fade away" of an initial nonresponse bias in the context of regression analysis. By using a time series approach for the covariate and the error terms we derive the bias of cross-sectional OLS-estimates of the slope coefficient. In the case of no subsequent attrition and only serial correlation an initial bias converges to zero. If the nonresponse affects permanent components the initial bias will decrease to a limit which is determined by the size of the permanent components. Attrition is discussed here in a worst case scenario, where there is a steady selective drift into the same direction as in the initial panel wave. It is shown that the fade away effect dampens the attrition effect to a large extent depending on the temporal stability of the covariate and the dependent variable. The attrition effect may by further reduced by a weighted regression analysis, where the weights are estimated attrition probabilities on the basis of the lagged dependent variable. The results are discussed with respect to surveys with unsure selection procedures which are used in a longitudinal fashion, like access panels