The Origins of Data; Evolutionary or Theocratic?

1. The Origins of Data; Evolutionary or Theocratic? The tensions between technical and international ideological policy considerations and their impact on the development of national statistical systems

2. The Roles of Different Agencies • The United Nations and its Regional Commissions • The UN Specialised Agencies • The Bilateral Aid Donors • The NGOs • The Bretton Woods institutions

3. Some Basic Premisses • All raw data are essentially ‘local’ and collected at the national level • International bodies and foreign agencies generally compile national statistics and do not collect raw data directly. • Most international totals are aggregated from national totals and use gap-filling methods. • National data collections and international data compilations are unable to measure or monitor truly global phenomena • Perceptions of priorities and data uses between international and national institutions are different

4. The UN and Regional Commissions • The agenda and programme of the UN Statistics Division is determined by the [UN] Statistical Commission, composed of nationally selected representatives from UN member countries. • The SC is also responsible for setting and monitoring standards; establishing classification procedures and data frameworks, e.g., the SNA • Three key data initiatives, not taken by the UNSD, have been, at its instigation, criticised and held up • a] HDI • b] ICP • c] City Groups [Special Topic Studies] • In earlier times, the UNSO [as it was] blocked efforts to compile data on household income inequality, the social structure and social indicators.

5. UN achievements • Standard classification systems and common statistical definitions • Population and demographic data • The System of National Accounts • Environmental and Resource Use Accounts • Data coordination and methodological harmonisation • Training and technical cooperation • UN Regional Commission Statistical Offices are essentially branches of the UNSD acting as local implementation agencies.

6. The UN Specialised Agencies • Their coverage speaks for itself; FAO [agriculture output, food production], ILO [employment, wages and prices], UNESCO [schools, teachers and pupils; science and culture], UNFPA [population and female health], UNICEF [women and children], WHO [health, medicine, doctors, patients], UNIFEM [gender distinction] • Others; environment, refugees, food relief aviation, telecommunications, postal services, policing, etc are very specific • Some problems of overlap of subject areas and definitions reflecting differences in perception that affect data comparability.

7. UN Agencies [contd] • Each agency has developed its own definitions and classification schemes. • Examples; a] ICD [diseases]. Most data relate to mortality not to morbidity conditions. Reflects medical interest; recent epidemic notifications refer to symptoms not to illness, e.g. SARS and Avian Flu b] ISCED [schools and enrolments]. Relies on administrative reports, i.e., on government departments monitoring their own performance. Census and household survey data on primary and secondary enrolments show lot lower figures

8. The Bretton Woods Institutions A. The World Bank [and IFC] • Has moved slowly from a neo-classical project focussed approach to more policy emphasis on societal development programmes • Inherits a growth economics ideology driven by investment and K/O ratios that affects how social development is conceived • Over past decade has become more oriented to poverty reduction and enhancing living conditions, but with a strong income and employment generation direction

9. Specialised Bank Data • Bank has adopted small scale survey evaluation and monitoring procedures since the outset to assess the effectiveness of project lending • Has developed its own specialised measure of GNP per capita [the ‘Atlas’ income per head] used for guiding loan and investment decisions. • Launched the ambitious but non-comparable LSMS studies, SDA and CWIQ programs for assessing improvements in household well-being and evaluating poverty status • Has organised the global comparisons of GDP and sub-component expenditures under the ICP

10. B. The IMF Responsible [uniquely] for four key data areas; • The Real Economy [GDP expenditure] • The External Account [Balance of Payments and international debt] • Government Finance [Current and Capital] • Financial Statistics [Money and Banking] The ‘Fund’ a] provides precise manuals to guide compilation b] uses SDDS, GDDS, DQAF and ROSC procedures to assess data quality and ensure the standards it has set are kept.

11. NGOs and NPISH • Usually the mandates of these organisations are very specific – OXFAM, SCF, Ford Foundation - and data collection is primarily designed to pursue certain goals and specific situations, such as emergency relief to provide drugs, medical supplies, tents and water purification equipment. • Data are used for both managing situations and ‘propaganda’ or awareness raising. • Operations are often location specific

12. Bilateral Donors and Data • Key operators; Scandanavian countries, France, Japan, US, UK, Germany, Canada Australia and, in the past, Russia • Provide recipient countries with technical support and advice to run surveys, manage administrative data collection and censuses, strengthen computer skills and operations. • Have sometimes encouraged local decentralised data collection. • Agenda sometimes reflects donor country preferences [USAID, SIDA], specific policy emphases [female health], and subject areas.

13. UNDP • UNDP is a unique specialised agency that coordinates, at the national level, the delivery of UN and associated programmes of development. • Responsible for the Human Development Report [that has superceded UN’s ‘World Social Report’] with its emphasis on people’s progress, and NOT on economic growth and material standards • Calculates the HDI, a much criticised [and much maligned] multi-dimensional index of household access to market and non-market commodities that goes beyond purely income considerations • Keeps tabs on the MDGs and progress towards their achievement, and on post-conflict support

14. HDR and HDI • People read the HDR to find out where their countries stand on the development index • The HDI is a simple [bounded] average of income, health and education indices, first promoted to counteract the heavy emphasis of countries on GNP and GDP and to reflect both economic and social progress • Now perceived as a measure of governance insofar as it influences governments positively

15. Other Institutions • The regional banks; AfDB, ADB, MEDB, IADB, CDB etc all compile their own data but usually as a consolidation of member country national data • ASEAN, Caricom and regional political organisations have similar harmonisation and consolidation mandates • EUROSTAT [and OECD, including DAC] develop their own data coordination and compilation mechanisms