Population - TIAM-UCL: Difference between revisions
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Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century. | Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century. | ||
=== Households === | === Households === | ||
Revision as of 12:26, 10 October 2016
| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | University College London (UCL), UK, https://www.ucl.ac.uk. |
| Solution concept | Partial equilibrium (price elastic demand) |
| Solution method | Linear optimisation |
| Anticipation | Perfect Foresight
(Stochastic and myopic runs are also possible) |
Population
Population figures up to 2050 are based on UN estimations (UN, 2009). For the second half of the 21st century, population growth is assumed to follow the pattern of the first half, i.e. that population growth rates decline or become negative.
It is assumed that world population will increase from 6.7 billion people in 2005 to 9.3 billion people in 2050, reach the peak in 2090 with 9.8 billion and then decline slightly.
The biggest population increase over the 21st century is expected to happen in Africa, India, Other Developing Asia and the Middle East .
Under the given assumptions China, Eastern Europe, Former Soviet Union, Japan, Mexico, South Korea and Western Europe experience negative population growth rates in the second half of the 21st century.
Especially for South Korea and Japan, it is assumed that the population will shrink significantly over the course of the 21st century.
Households
The growth rate of household numbers during 2005-2100 for different regions are represented in the model. The number of households is based on population estimates and occupancy rate. There exists no database for the occupancy rate for each region in the TIAM-UCL model. Therefore, the numbers in this section rely on national statistics. For some countries, there exist forecasts for the near future (up to 2030) concerning the development of the average number of people in a household. These have been used where available in order to determine the household growth for the near future. For the longer term, it is assumed that the occupancy rate will increase in line with historic data to 1.7 to 3 persons per household, depending on the region. The reason for this range is the difference in current average persons per household, e.g. in 2005 the average Indian household consisted of 5.3 persons, while the average Western European household consisted of 2.1 persons per household.
In order to simplify the data needed for the calculation, characteristic countries have been chosen for regions that consist of more than two countries. Those are South Africa for Africa, Brazil for Central and South America, Poland for Eastern Europe, Russia for Former Soviet Union, Iran for Middle East, Indonesia for Other Developing Asia and Germany for Western Europe. Numbers for the driver ?GDP per household? have been calculated as the ratio of GDP and number of households for each given region.
Sectoral drivers
There exist no reliable data for the forecast of industrial production, agricultural or service output for the next 90 years. Industrial production is subdivided into chemical industry, iron & steel and non-ferrous metals, pulp & paper and non-metallic minerals, and other industries. Initial numbers are based on number from ETSAP-TIAM published by KANORS (2010). The development of sectoral growth rates are geared to the GDP numbers and imply a shift in GDP composition towards the service sector, so that agriculture and industry will become less important for the whole economy over the 21st century. To this end, the GDP composition of the most important regions has been extracted from national statistics according to the sectoral aggregation in TIAM. In a next step, the sectoral drivers have been calibrated in such a way that they yield a more service orientated economy. In addition, the driver for the iron & steel industry is geared to historical data on steel production obtained from statistics of the World Steel Association.