Common Indicators

Population data, fertility rates, education levels, and gross domestic product (GDP) are among the indicators most frequently used in analyzing health programs, interventions, and systems. However, two major issues may arise when scientists, policymakers, and others use these indicators:

  1. Sources may estimate different values for the same indicator. For example, the population of a country may be reported differently by the World Health Organization and the United Nations.
  2. Different standards may be used for measuring the same indicator. For example, GDP can be reported in international dollars or in real US dollars.

The goal of the Common Indicators Work Group is to create a standardized set of indicators. These will be used across IHME work groups and projects. They also will be made publicly available, enhancing the continuity and comparability of scientific research.

A top priority is the creation of standardized indicators of national populations, fertility rates, and GDP, variables that are especially useful in a wide array of analyses. In some cases, we are extending existing time series, including producing time series of comparable education, tobacco consumption, and permanent income indicators that can be used across all countries. In others, we are creating one set of estimates from multiple, competing data sources.  We have produced an international dollar and real US dollar GDP series for all countries from 1970 to present. And we have created a conversion table that allows users to map country codes from different sources that do not use the same coding schemes to identify countries and regions. For example, the World Bank and World Health Organization use different regional codes, adding a translational challenge to analyses that draw from both sources.

Major activities in Common Indicators:

Estimate a set of indicators on education that can be used interchangeably across countries:

IHME researchers are developing a complete time series of educational attainment adjusted for differential mortality by sex from 1970 to present using all available data.

Estimate a set of permanent income indicators to measure wealth comparably across and within countries:

The permanent income hypothesis is that individuals tend to base consumption decisions not solely on current earnings but also on potential for future earnings based on factors such as education, age, sex, and economic opportunities. This is especially true for poorer families where income fluctuates rapidly. Permanent income is therefore not calculated using observed variables, but instead by documenting owned assets through a household survey. A list of assets can then be created and cut points between sets of assets drawn to indicate income quintiles. This approach is beneficial for several reasons. It is cost-effective to gather the information, and there are low rates of measurement error. Asset lists can be made contextually specific to a country or region. Finally, different asset lists can be used in different countries and still provide comparable information. IHME is currently compiling and analyzing available household surveys for this purpose.

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