Advances in population projections

The urban population projection is an important tool for planning and policy making. There are so many projection methods available, one of the standard methods is the United Nations method. This article aims to examine the best urban population projection method among different methods viz. Modified Exponential curve, Gompertz curve and Logistic growth curve by using the Mean Absolute Percentage Error (MAPE) and Mean Algebraic Percentage Error (MALPE). The estimation of urban population for sixty years from 1961-2011 is computed and later the urban population is projected for next fifty years by using growth models.
The data collected for this study is from different census reports for India, from www.indexmundi.com for China and from www.worldbank.org for the World. The results revels that there is a strong relationship between the forecast error and the bias with growth rate of urban population during the base period for all the three curves. The Gompertz curve has smaller forecast error compared to other curves and it shows underestimate for India and China. The study also reveals that the logistic growth has the smaller forecast error compared to other growth curves and it shows overestimate for World.

This paper uses a methodology to forecast the spatial distribution of households and empirically addresses how the urban sprawl within a geographical boundary evolves over time. Our case study is the city of Belo Horizonte in 2020 and 2030. The city of almost 2.6 million inhabitants is the third most economically important in Brazil and has witnessed an important trend of increasing density and verticalization. The hypotheses used in the simulation were created from the following data sources: the Brazilian demographic census of 2000 and 2010, zoning laws of Belo Horizonte, the Development Plan for the Metropolitan Area of Belo Horizonte (PDDI, 2010), and spatial data from urban sprawl. This information delineates the characteristics and conditions for future housing growth and density. We use Complex Systems models (cellular automata-CA) within a Geographic Information Systems (GIS) environment to simulate prospective scenarios, and thus achieving precision at very low scales (an intra-urban scale named “blocks”) in 2020 and 2030. The empirical exercise in Belo Horizonte provides a contribution to the analysis of demographic dynamics applied to urban and regional planning, and in particular, how to integrate small area population projections to information on land use and occupation of urban land.

The paper presents a reconstruction of educational attainments by sex, five-year age groups, and six levels of education from 2010 to 1960 in 170 countries, based on a multi-state back-projection method that takes into account migration and mortality differentials by gender and age group. We discuss the methodology and validation of results against the available empirical data and discuss the methodological advantages as compared to other existing databases of past educational attainment. We also outline additional possibilities of still further-reaching back-projection that would cover most of the 20th century for a reduced number of countries and education categories. The database will enable a better understanding of the manifold social and private returns to education and a more accurate population forecasting.

The purposes of this study are to examine a method to overcome the shortage of historical data on mortality of the elderly and to find the best model to forecast Korean mortality rates overall. To extend the mortality for ages 75 and over, we test two methods of estimating death probabilities: the 2-parameter logistic model and the Brass-Logit model. Based on the Mean Absolute Percent Error (MAPE), the logistic model has better performance than the Brass-Logit model. Four stochastic forecasting models (the Lee-Carter Model, the adjusted Lee-Carter Model, the Lee-Miller Model, and the Coherent Lee-Carter Model) are fitted to the period 1970-2010. The forecasts are compared to actual mortality for that period. The results of this evaluation show that the Coherent Lee-Carter Model is consistently more accurate in forecasting Korean mortality rates than other compared models. The Coherent Lee-Carter model yields a higher life expectancy at birth for both sexes and a larger difference between sexes than other models in which sex differentials diminish rapidly.

Levels of educational attainment are the main component of human capital that is used in many models, mostly related to economics. However a large majority of data on education suffer from severe flows, hampering any trend and regression analysis on levels of educational attainment. We show in this paper how picking the right data and adjusting it so that it becomes consistent across ages and countries can be a real hassle. This exercise was done in the framework of Wittgenstein Centre for Demography and Global Human Capital new round of population projections by levels of educational attainment from 2000 to 2060 and the reconstruction of the same data back to 1960. Both exercises require base-year data on population disaggregated by levels of educational attainment by age and sex. These were gathered for 170 countries for six education categories between 2000 and 2011.

This paper estimates how far current fertility levels and rates of population growth in Kenya can be reduced purely by relying on family planning or – more precisely – the elimination of unwanted fertility. Using a similar approach to Bongaarts decomposition model, the paper projects the population, starting in 2010, using the Age Specific Fertility rates of each respective 5-year period, but adjusted by a factor. By 2050, the population implied by this scenario would be 104.1 million, compared to 96.9 million under the UNPD Medium projection and 94.6 million under the previous scenario with uniform reduction of the ASFRs. By 2070, the Perfect Reproductive Health scenario would imply a population of 168.6 million, compared to the 127.3 million projected by the UN Population Division. If maternal mortality is completely eliminated and a further reduction of 50% in child mortality is assumed, the former number rises to 176.1 million. Although the immediate attainment of perfect reproductive health would lower population growth rates in the short run, such improvements – in the absence of changes in fertility preferences - would soon exhaust their potential, resulting in long-term population growth rates in the order of 2-2.5%.

Although substantial research has been made in identifying and quantifying determinants of international migration, most official population projections do not include these determinants in an explicit migration model. In Norway, gross immigration is currently 1.5 percent of total population, and immigration is the main driver of population change. Statistics Norway is projecting immigration to Norway using an econometric model based on standard migration theories. The main variables included are income level, unemployment and population size in Norway and the sending countries, previous immigration from the sending countries to Norway, and dummies for policy changes or special events. Data from 1970-2011 are used to estimate the effect of the different variables for three country groups: Western countries, Eastern EU-countries and the rest of the world. Projections of exogenous variables are partly drawn from international sources and partly from national Norwegian forecasts. For the income variables, three different paths are specified leading to three different forecasts for immigration until 2100. These forecasts suggest high immigration at least for another decade. However, the alternatives indicate high uncertainty. Even if we condition on a specific path of explanatory variables, prediction intervals are wide.

The average size, number and distribution by size of private households in Turkey are projected based on the official population projection and an extension of the headship rates method. Our results imply the plausibility of a quadrupled number of single-person households along with almost a doubling of the overall number of households in 2000-2025. Appreciating these changes is essential for evaluating housing needs, socio-economic developments and environmental issues in Turkey. Under current consumption patterns, change in households’ composition is potentially more important for economic growth prospects than the population growth.

Demographic forecasting models simulate the likely future development of a population with assumptions in mortality, fertility, and migration.
If demographic behavior is heterogeneous in a population,
projection accuracy can be affected substantially.
To overcome this problem,
we propose a new general framework that can be used to disaggregate heterogeneous populations in as many homogeneous subpopulations as needed that can then be projected with separate assumptions in mortality and fertility.
The advantage of our general framework is that subpopulations cannot only be constructed with typical characteristics like age and sex,
but also with other characteristics like country of origin or level of education.
We apply this general framework in projections for Germany up to 2050 in order to show the impact of expected demographic heterogeneity on projection outcome.
In the first projection, we use the variables age and sex to construct subpopulations,
and in the second and third projection, we add the variables migration status and reason to migrate.
As expected, our preliminary results indicate that projection error accumulates over time,
and that it is higher for the first than for the second projection.
We also discuss how this general framework can be easily applied to conduct multiregional projections.

Using empirical fertility rates and population distributions, we study comparative contributions to births’ prediction errors of choices for the fertility model and of the approximation errors of three main fertility indicators (the total fertility, the mean and the standard deviation of age at birth, respectively: TFR, MAB, SDAB). Agreeing with theories of dynamic populations, we find high importance of accuracy of TFR and MAB. Yet, the role is limited in population projections of the estimates of SDAB and of the choice of the fertility model form. More attention may be paid in population projections to working out (interdependent) scenarios for TFR and MAB, while relaxing complexity of other aspects of fertility projection models. Our results suggest widening the uncertainty range for TFR in cases when the MAB projections are based on regressions on TFR or other simplified assumptions.