Each country starts at the same level in the Index. Data from between 2010-2014 (where the most data is available) or an average of the years in this period was used in the calculations.
National and regional data (including from national websites) was added to data from public sources to complete the data sources where gaps exist. Sources for the Index include: African Airlines Association, African Development Bank, ECA, International Air Transport Association, International Trade Centre, UN COMTRADE, UNCTAD, United States’ Energy Information Administration, and the World Economic Outlook database of the IMF.
For the First Edition, as part of a pilot data collection and training exercise, data was collected by trained Statistical Focal Points in 26 countries, across four regional corridors and in the regions of Eastern and Southern African over a period of three months.
The Index was built in five steps in line with good practice:
1. Selection of Indicators
2. Standardization process
3. Calculation of Index by Dimension
4. Calculation of overall Index for countries
5. Calculation of overall Index by REC
About the Index
The Index aims to be an accessible, comprehensive, practical and results-focused regional integration tool that focuses on the policy level and on-the-ground realities.
- Indicators were included where 80% of countries had quality data available. Where data was missing, the most similar data sets or an average of the scores from a comparable country were used.
- Overall Index calculations are based on the sum of the average of all the Dimensions. The Index does not prioritize any particular topic on regional integration.
- Each of the Indicators is given equal weight in the calculation of Dimension scores using the sum of the average of the Indicators in a Dimension (except on Free movement of people).
- The Index uses the standard MinMax method of scaling results from 0-1 (best). That includes a standardization of the results to get the same unity of measurement to aggregate the data.
- Indicators that are chosen are not linked so there is no double counting in the calculations.
Notes: Higher Dimension scores for countries in one REC over another.
Countries that are members of more than one REC show differences between their rankings and scores in a particular Dimension in one REC as opposed to another. This can be explained by historical links, comparative advantages, regional policies and geography.
Geographical closeness goes a long way to explaining integration intensity. With common borders, countries exchange more among themselves and transaction costs are reduced. For example, in the case of Zimbabwe its geographical proximity to SADC member countries in Southern Africa can help to explain why it has the highest integration score on productive integration in SADC and yet is a low performer in this Dimension in COMESA.