A vast range of demographic, socioeconomic, and related analyses are based on census data, and those mentioned here are only indicative. In the past, census data were accessed through published volumes, but currently digital outputs predominate, ranging from online tabulations to customized data runs and the use of data labs. Data labs allow analysis down to the level of individual records, usually involving strict conditions of confidentiality. Two examples of these are the PUMS (Public Use Microdata Samples) in the US and the SARs (Samples of Anon ymised Records) in the UK.

Demographic and Socioeconomic Analyses

The mainstays of demographic analysis are fertility and mortality. In countries which have birth registration systems, fertility rates are usually calculated from these data combined with census data on the cohorts of women of reproductive age. Birth registration systems usually collect a limited range of information related to the characteristics of the mother such as place of residence, age, and ethnicity but censuses which collect fertility information such as age at first birth, ever born children, etc. allow analysis using a much greater range of variables than is possible with the birth registration data. Also, in many less developed countries, vital registration systems are absent or unreliable, so census data are critical to the analysis of fertility. Likewise, basic rates of mortality can be derived from death registration data, but the popu lation on which these rates are based is almost always derived from a census. Other important demographic processes and characteristics which are usually derived from census data include population size and change, population distribution and movement, ethnic com position, age–sex structure, and household and family structure.

Much socioeconomic analysis is also derived from census data using variables such as income sources and levels, educational levels, occupation, industrial sector of employment, and so on. Further, multivariate indicators are constructed from these basic variables. For example, much effort has gone into the development of indicators of deprivation or well being such as the work on social indicators by the Canadian Council on Social Develop ment, which uses a range of census and non census sources.

Migration Analysis

While the statistical analysis of international migration relies on some data external to the census (arrival and departure data, residence permit data, etc.), census an alysis is important in analyzing immigration outcomes. Questions on birthplace and duration of residence within a country allow the identification of the migrant popu lation, and cross tabulations with various social and economic variables allow an assessment of levels of mi grant participation and well being. A limitation of the census method, however, is that longitudinal analysis of individuals or families is not possible except in some cases by inference between censuses.

The analysis of internal migration is highly dependent on census data in countries which do not have com prehensive systems of residence registration. A question on usual residence at a previous point in time (e.g., 1 or 5 years ago) allows the construction of matrices of move ment between different areas of a country. The degree of mobility measured by this method is dependent on the spatial resolution used, with the most detailed scale (any household movement) resulting in the highest levels of measured mobility. A common use of this method is to assess economic well being of different regions of a country in relation to population mobility, especially in relation to the educational and occupational character istics of the migrant population.

The residual method of migration analysis may be used in the absence of census data on movement into or out of an area. Age–sex characteristics of the population of an area are compared between censuses so that a survival rate is applied to age–sex cohort between census 1 and census 2 and the difference between the hy pothesized number of survivors at census 2 is compared to the actual cohort at census 2; the differences are taken to represent the net migration of each cohort between censuses.


Although the term ‘geodemographics’ was first used by geographers more than a century ago to classify neighborhoods within cities, its contemporary usage can be attributed to its use within business demography to refer to the analysis of demographic data, usually using relatively small spatial units, for the purposes of market analysis and related purposes. The term and approach have more recently been used in other contexts, especially for social research and the provision of public services. One of the central approaches of geodemographics is the clustering of statistically similar neighborhoods or other areas. Census data are usually central to these approaches since geodemographics demands information at a detailed spatial scale and often involves a number of variables. Census data are then often supplemented by data from other sources such as market surveys, records of housing sales, electoral rolls, and so on.

Population Projections

Planning at national, regional, and local levels is usually dependent on the projection of future populations. Critical to projection methodologies is robust data to construct base populations and to develop assumptions. Since undercount is likely in nearly all censuses, pro jection base populations are often constructed by in corporating the undercounted elements of the population, so these may be seen to be better represen tations of the usual population of a country than the census counts themselves. Fertility assumptions are usu ally derived from birth registration statistics but usually use census populations as their base, and similarly life tables used in projections are derived from both death registration data and census data.

International and internal migration assumptions for population projection may be the most problematic since there may be large and unexpected fluctuations in mi gration resulting from government immigration policy changes, economic cycles, or dramatic political or natural events. Nevertheless, census data on past migration trends may be useful in modeling possible and/or likely migration patterns over time.


The changing nature of census geography is being driven by several forces. The most obvious of these is techno logical change. The rapid acceleration of computer power has revolutionized all stages of the census process, ranging from enumeration to data entry to analysis to dissemination of results. Even more fundamentally, this acceleration and the development of GIS have altered the potential for spatial conceptualizations that were not possible earlier. Another force, partly related to techno logical change, is the ability of governments to gather a vast range of information on their citizens which has reduced the need for the comprehensive census taken at a fixed point in time. Thus some countries have abandoned the traditional census approach and it is likely that many more will follow. However, potentially at odds with this development is another significant force, namely the emergence of identity politics in many places which challenges the whole classificatory process that censuses or population registration systems represent. Parallel to this are concerns about the confidentiality of data col lected by governments and by private agencies and on going monitoring via registration systems may appear to be more intrusive than an occasional census was.