Users of the Atlas sometimes ask: Where does the data come from? This page is in response to that question. The UC Atlas of Global Inequality draws on data from a variety of sources. The main source of data for Atlas maps and the Atlas database is the World Bank's World Development Indicators. Other data sets are used for some maps, figures, graphs and tables. As new content is added, additional data sets will be used and added to the database. Data Collection Process Most data in the World Bank WDI dataset comes from the governments of individual countries. The World Bank collects data on living standards and debt, but not much else. Some also comes from various international and national agencies with which World Bank partners (see world bank partners http://www.worldbank.org/data/wdi2004/partners.pdf for more info). The following provides a rough outline of the data collection process for the World Bank data set. Several other global agencies, such as the IMF, the UN Development Program, and the World Health Organization, collect data from national governments in a simlar way.
Because data is collected by many governments, differences in
methods and conventions may cause discrepancies when comparing data
between countries and over time. These, and other data limitations, are
described below.
Limits on the data There are many sources of error and omission in the data. Here we describe three. Averaged and aggregated data Most of the numbers generated by international agencies, including the World Bank, are national averages. Nation-states have become the principal units through which we view the world and understand global change. For many purposes national numbers have utility. But such numbers overlook the diversity of conditions facing rich and poor, women and men, minorities and majorities. Ideally, national measures should be supplemented by indicators of the spread of the results across social and economic divides. Omissions and priorities Some numbers are collected and others are not. Frequently, there are historical reasons for these omissions associated with the goals of the collecting agency. Important omissions for the student of inequality include: distributions of wealth, income, representation and power across social divides of class, gender and ethnicity. Since 1990, a limited global debate about the measurement of social progress has been occurring between the UN Development Program (UNDP) and the World Bank. With the publication of the UNDP's Human Development Report, the range of numbers about national populations has been expanded. The Human Development Report took up ideas suggested by Amartya Sen that social progress could be more effectively measured through social outcomes, such as life expectancy and infant mortality, rather than through measures of economic output, such as Gross National Product. The Human Development Report developed the Human Development Index (HDI) as a measure of national achievement. The HDI provides a single indicator reflecting life expectancy, literacy and Gross Domestic Product. Errors and Biases In addition to errors arising from the priorities of government collection agencies and differences in methods of data collection, there are some important biases in these data. Effectively all economic data excludes work that is not monetized. This means that global statistics exclude all domestic work, done primarily by women, and may provide poor estimates of production for direct consumption. These exclusions may bias statistics about income (GDP) and work (employment, labor force). Checks To deal with problems of statistical distortion, agencies that collect and distribute final national data sets in global reports, specifically the World Bank and the UNDP, have established a framework to promote consistency and accuracy between indicators and countries. At the core of this framework is the United Nations' Fundamental Principles of Official Statistics , which was established following the collapse of the Soviet Union as the former Soviet bloc transitioned to market economies. This document covers the wide range of scientific and ethical issues inherent in the collection and dissemination of national statistics that every country and agency submitting the data must abide by. The International Monetary Fund and the World Bank have taken an additional step in developing the General Data Dissemination System (GDDS) which is intended to improve data collection, analysis and reporting techniques, as well as the Data Quality Assessment Framework (DQAF) which combines the Fundamental Principles of Official Statistics, the GDDS, and other "best practices and internationally accepted concepts and definitions in statistics." This set of dissemination standards is intended to promote fairness, accuracy, and comparability in data sets between countries.As global numbers are more widely distributed it is likely that independent estimates and comparisons, by agencies and individuals outside government and international organizations, will be generated. Main Data Sets Used in the Atlas The table below shows the main data sets used in different elements of the Atlas. There is also a larger listing of online datasets avaliable.
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