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Demographic data for development planning

Population data

Demographic data are at the heart of population dynamics because they are the concrete basis that make it possible to observe demographic trends in a country. Although data gaps persist, digitalisation is boosting the efficiency of analysis and of sources such as censuses, surveys and birth and death records.

Demographic data provide information about a country’s current population and about population trends. When disaggregated by age, sex, place of residence and marital status, in addition to variables such as income, ethnicity, level of education or disability, they reflect the population structure and can supply information on demographic characteristics such as distribution and density in various regions, as well as on urbanisation trends or international migration. Demographic data are thus an essential basis for any country’s policy planning. Population data are also required by the international community to measure development progress.

Sources of population data include censuses, surveys and routine data collection

Various data sources such as censuses, household surveys and routine data systems provide statistical information on the population of a country. This is collected using methods such as oral interviews, written questionnaires and the transfer of data from population registers.

The United Nations recommend conducting a national census every 10 years. A census is a unique source of information, providing valuable data on population size, structure and distribution, broken down to the smallest geographical and statistical unit. However, censuses provide only a snapshot at a given point in time and are very expensive for poorer countries to carry out without international support.

In the long intervals between censuses, attempts are made to meet the demand for real-time data through population projections. These forecasts are based on available demographic data and reflect assumptions regarding the future evolution of factors such as fertility, mortality and migration. Because even slight deviations in the underlying assumptions can have a major impact on forecasts, projections have only limited reliability. This often leads demographers to calculate several variants – e.g. on the basis of low, medium and high assumptions concerning fertility – that lead to significantly different results. One example are the biannual population projections published by the UN, whose low, medium and high projection variants show that by 2100 the world population could shrink to 7.3 billion or grow to 11.2 billion – or even as high as 16.5 billion (UN World Population Prospects, 2017). The middle variant is most often used.

Household surveys such as Demographic and Health Surveys (DHS) or Multiple Indicator Cluster Surveys (MICS) collect information on a particular set of topics from a representative sample of the population. On this basis conclusions can be drawn for the population as a whole or for individual population groups. Like censuses, such large-scale household surveys represent a ‘snapshot’ in time and LMICs often require international financial and technical support to carry them out.
Such a one-time collection of population statistics is a major operation that can place a strain on government budgets and logistics. A solution to this dilemma is the development of routine data systems such as for civil registration and vital statistics (CRVS), which are explained in this section.

Locally collected population data enable local data-based decision-making

CRVS systems record all demographically relevant life events such as births, deaths (including cause of death), adoptions, marriages and divorces. Each of these events can be clearly assigned to an individual or consolidated according to various criteria, and taken all together, these data can provide insights into population size, age structure and sex ratio. Routine data are taken primarily from official population registers and from the administrative systems of sector-specific institutions such as hospitals and schools. These routine data are produced on an ongoing basis as part of the existing administrative process, and when stored digitally, are available in real time and – compared to censuses and large-scale household surveys – require no additional funding.

The functioning of CRVS systems
The functioning of CRVS systems

Locally collected data are particularly relevant for decentralised administrations, as municipalities and provinces can respond more directly to local and regional developments than can the national level. On the other hand, often data collected at the local level – due to inadequate capacities or coordination – are not fully or consistently compiled at the national level.

Digitalisation imposes new standards for handling population data

Recording and processing data in digital form significantly reduce the time and cost involved in data collection and decrease transmission errors and data losses. All political and administrative levels, particularly at the local level and including in remote areas, stand to benefit from digitally collected population data.

However, data are fundamentally vulnerable to political, commercial or criminal manipulation. In the case of new digital data sources such as ‘big data’ from private providers, a further problem is that the quality of the data is difficult to verify. The standards applied when collecting data are often unclear, as are the groups covered by the data.

Key issues in this regard are accountability and data security. Including in a refugee context, under generally challenging conditions, it is essential to maintain the security and confidentiality of all personal data at all times. The anonymity of personal data, respect for personal rights and the right to privacy must always be ensured. German development cooperation therefore includes data protection as part of its approach to human rights.

German development cooperation supports efforts in its partner countries to reform administrative structures and processes in such a way that the rule of law, credibility, efficiency, transparency, integrity and citizen orientation are guaranteed. Key public representatives such as parliamentarians and civil society organisations need the opportunities and capacities to access and analyse data on population trends, and on this basis demand accountability from their government. Statistics and research institutes have a key responsibility to analyse and compile demographic data in a transparent and comprehensible manner.

Monitoring the 2030 Agenda depends on reliable population data

The 2030 Agenda states: ‘Quality, accessible, timely and reliable disaggregated data will be needed to help with the measurement of progress and to ensure that no one is left behind.’ Fully 43% of SDG indicators rely on demographic data. And yet, in many countries obtaining, processing and presenting reliable, up-to-date and sufficiently detailed population data remain a challenge. Supporting partner countries in this domain is a focus of German development cooperation. To strengthen innovative, transferable and sustainable approaches to implementing and monitoring the 2030 Agenda, BMZ through its 2030 Implementation Initiative, promotes, among other things, measures to increase partner country capacities to monitor and review the 2030 Agenda.

For more information on demographic data, please refer to Chapter 5 of the handbook.

Tips for supporting demographic data systems

German development cooperation is committed to supporting its partner countries in producing, interpreting and using reliable, high-quality population data. The following should be taken into consideration when designing projects of this kind:

  • Needs orientation: Investments in data information systems should always be guided by the concrete needs of the partner country, whose systems are often at very different stages of development. South-South cooperation between countries facing similar systems development issues can be relevant in this context.
  • Promoting routine data systems: These should be given priority, as only routine data systems can provide population development information on a timely and sustainable basis. Meanwhile, alternative data sources such as household surveys should continue to be used.
  • Costs and benefits: In determining whether data collection is necessary, it is worth checking whether other sources of the required population information already exist or whether other actors are also planning to collect similar data that could be used.
  • Data protection: Personalised information must always be handled confidentially and protected, in accordance with national and international data protection guidelines.
  • Using standardised indicators: To ensure that data are collected in line with uniform principles, indicators must be defined and categorised in a standardised way. Data collected at the national level can thus be more easily fed into international monitoring databases and compared.
  • Presenting population statistics in an accessible manner: For evidence-based planning and best use of scarce resources, demographic data and their analyses by professional demographers and statisticians should be easily accessible and understandable for policy-makers and planners. Research institutes and policy think tanks can help by highlighting the information content of data through studies, analyses and interpretations. 
  • Capacity development: At national and regional level, but especially at local level – where most data are collected – staff of statistics institutes and public agencies must have appropriate training in data collection and communication. 
  • Avoiding fragmentation and duplication of data systems: This requires the joint definition and application of interoperability standards by all those involved in collecting, processing and analysing population data, i.e. countries’ public administration, national statistics institutes and development partners supporting their data systems, so that the same data can be fed into, and used by, all their different systems. 
  • Data transparency: Open access to demographic data contributes to good governance and offers civil society the opportunity to review the findings presented by the government. Since demographic data and their interpretation are vulnerable to manipulation and can be coloured by political interests, governments have a special responsibility in this regard.

Resources

For websites providing up-to-date population data, see at end of the section ‘Population Trends’ on this portal.

© GIZ/Dirk Ostermeier
© GIZ

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