International Workshop on Subnational Population Projections using Census Data

17 – 18 January 2013 Beijing, China

Session I:

Projecting subnational populations: Introduction • • • Main approaches to subnational projections: top-down or bottom-up Elements of subnational projections: Demographic components revisited Projecting urban and rural populations

Main approaches to subnational projections: top-down or bottom-up

Overview

Top-down or bottom-up

• Subnational population projections are increasingly in demand. They are an important information source for regional and local policy makers. Subnational population projections are also important for countries that are large and have a diverse population. In such circumstances, national population projections may not effectively and accurately reflect the demographic settings in its administrative or regional entities.

Top-down or bottom-up

• • Generating sub-national projections that are both internally consistent and consistent with a national projection is usually more challenging than preparing a national projection.

Each subnational entity presents the same data problems as the national projection but, in addition, preserving consistency across regions and dealing with data problems that are often more severe than those at the national level adds to the challenge.

Top-down

• • • A projection for the whole country is created, and the results are then disaggregated (downscaling).

Ratio methods are most common methods for this basic approach.

Bottom-up

• • Projections for all sub-national entities are created separately and then aggregated to obtain the results for the total country. Multi-state or multi-regional projection models are a variation of this approach, but are much more demanding, as it performs simultaneously the projections for all sub national populations.

Top-down or bottom-up

• • • Each of the basic approaches has advantages and disadvantages. Choosing the right approach depends on data availability, time horizon, expected users, etc.

Top down approaches are preferred for smaller administrative or regional entities, and situations with limited data Bottom-up approaches are recommended for large population: Not lower than the first subnational administrative level.

Top-down or bottom-up

• In addition to the two main approaches, combinations of different approaches/methods have been used. India has produced population projections for the country and its states using the cohort component projections for all large states (with more than 10 million Inhabitants). For smaller states or locale, a variant of the Growth Differential methods has been used, and for very small entities, extrapolations with appropriate mathematical formula were applied

Elements of subnational projections: Demographic components revisited

Overview

Demographic components revisited • The preparation of subnational projections in general does not require other input information than the projections of national populations. However, one has to be aware of the following challenges:

Demographic components revisited • • Because subnational populations are smaller than the national one, data may show more irregularities and fluctuations. This affects all elements of demographic components: Births or fertility, deaths or mortality and migration. If a population is small, its age composition is also subject to random fluctuations.

Demographic components revisited • • International migration for national populations is usually integrated into the projection as net migration, that is the balance of immigration and emigration. If migration is of relatively small magnitude, international migration has often even been ignored (e.g. assumed to be zero). The same is almost always not possible for subnational projections, for the magnitude of internal migration is in most cases larger than international migration, and therefore has significant demographic impact that cannot be ignored.

Projecting urban and rural populations

Overview

Projecting urban and rural populations • • • Projections for urban and rural populations are an important part of national projection exercises as they illustrate the demographic dynamics of two main socioeconomic population groups. In principal, all projections methods are applicable, for instance the cohort-component projection method or appropriate ratio methods. The United Nations has developed and used for many years a robust and parsimonious method that uses the Urban Rural Growth Differential (URGD) as driving force (United Nations, 1974). The URGD method follows a logistic growth pattern and is therefore adequate for modeling urbanization as a diffusion process.

URGD Method Percentage Urban

U t

 Urban population at time t

R t

 Rural population at time t

URR t

 Urban-rural ratio at time t

URR t



U t R t PU t

 1

URR t



URR t

URGD Method Percentage Urban

n

n rur t

u t  Growth rate of URR between time t and t+n  Growth rate of urban population r n t  Growth rate of rural population

n rur t

 1

n ln

  

URR URR t

  

n

URGD Method Percentage Urban

s ubstituting URR with 1 n   ln   

U R

   - ln    U R

U R t t

     = 1 n ln   

U U t

   1 n ln   

R R t

   t n t

URGD Method Projecting URR

• The growth rate of the urban-rural ratio n rur t is equivalent to the difference between the growth rates of the urban and the rural populations. Also known as the urban-rural growth difference, it is the basis for the interpolation and extrapolation of the proportion urban.

URGD Method Projecting URR t

e

 n 

URGD examples I

Proportion Urban: China

100% 75% 50% 25% 0% 1950 1975 2000 URGD 2025 2050 UN 2011 2075 2100

URGD examples II

Proportion Urban: Indonesia

100% 75% 50% 25% 0% 1950 1975 2000 URGD 2025 2050 UN 2011

Proportion Urban: Nepal

2075 2100 100% 75% 50% 25% 0% 1950 1975 2000 URGD 2025 2050 UN 2011 2075 2100

Proportion Urban: Lao

100% 75% 50% 25% 0% 1950 1975 2000 URGD 2025 2050 UN 2011

Proportion Urban: Japan

2075 2100 100% 75% 50% 25% 0% 1950 1975 2000 URGD 2025 2050 UN 2011 2075 2100