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Statistical resources
Statistics & indicators
Main types of social security data


Social security statistics and activities in this field are crucial for the formulation, monitoring and evaluation of social security policies and programmes, for advocacy purposes, and for enhancing the capacity of an increasing number of member States to generate comprehensive social security data.

What are the needs?

The main reasons that statistics are needed in the field of social security are:

  • To measure coverage and evaluate options for extension
    • Scope: "Who is legally covered for what contingency?"
      This is mostly legislative information available in several publications and databases. 
    • Extent: How many are currently covered? For what kind of risk?
    • Options for extension: "Who are those who are not covered? What are their needs and characteristics?"
      Combined with information on the social, economic and polical context and on the existing social security systems and infrastructures — "What could be the options for extension?"
  • To assess effectiveness of existing social protection schemes and formulate policies
    • "Who benefits and how many poor/non-poor, vulnerable groups?"
    • "What are the benefits (amount)?"
    • "Who pays and how much (for benefits, for administration)?"
Activities and related tools

The Social Security Department performs three main types of activities in this field:

  • Building a knowledge base at the global level and promoting a minimum set of data, indicators and analytical results. For this the Department has developed the Social security inquiry and additional associated databases to collect, store and disseminate, on a regular and sustainable basis, comparable statistics on social security systems/programme financing, expenditure, benefit levels and coverage for both formal and community based schemes.
  • Activities at the country level. Providing technical assistance and training to ILO member States (in cooperation with field offices)
    • In countries where statistics are available, activities focus on analysing data to help countries to i) define their social protection policies and ii) improve the effectiveness of existing schemes and extending their scope;
    • In many developing countries the priority is to improve the capacity of member States to i)generate and use data at the scheme level and ii) generate comprehensive social security data at the national level
  • Developing tools and methodologies to collect statistics on social security; to analyse data with the aim of monitoring social security systems and developing policies
» Main Resources
 
Social Security Statistical Resources
[Top]
ILO Databases

Global statistics on social security

Other social security databases

Household survey resources

Non-ILO social security statistical databases
  • International Social Security Association
     
    More ...
  • Eurostat | ESSPROS datatabase under the Living conditions and welfare database [More...]
  • OECD | SOCX database on social expenditure [More ...]
  • World Health Organization
    • WHOSIS | WHO Statistical Information System [More ...]
    • National Health Account [More ...]
  • Household survey resources
  •  
    More ...
Methodological tools
 
 
 
 
» NEWS
  • Crisis | Monthly data on unemployment benefit recipients
    Crisis | Monthly data on unemployment benefit recipientsGraph and data on the latest trends | ...   More info
  • Social security expenditure database
    The social security expenditure database is available online. It ...   More info
» Library
  • Financing social protection
    Quantitative Methods in Social Protection Series
    M Cichon et al.; ILO, Financial, Actuarial and Statistical Services Branch; ISSA ,  2004     More info...
  • Social Security Inquiry | powerpoint 2009
    SECSOC,  2009     More info...
» Links
» Glossary
  • administrative data
    In the context of social ... More info...
  • qualitative data
    There are, at least, two definitions of the term ... More info...
  • quantitative data
    Quantitative variables include measurable values. Many variables ... More info...