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- background information Africa Regional Integration Index - background information William Davis African Trade Policy Centre (ATPC) RITD Xuan Che Statistical Development Section (SDS) ACS
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Purpose M&E framework to measure implementation of African integration agreements Compare countries’ progress vis-a-vis another and over time (approach validated by multiple African Ministerial conferences) Provide ‘dashboard’ for policy makers on regional integration issues Improve dataset for African regional integration policy analysis
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Consultations SROs, ACS, RITD EGM including internal and external experts Indicators based on AU MIP, PIDA and energy frameworks (since infrastructure, energy not in MIP). These most recent and detailed expressions of priorities (Agenda 2063 not specific) Mix of input, output, intermediate result indicators Compare and rank member states against each other MiniMax scaling, average aggregation Cross-border component Availability of data, measurability CoM 2014, COMAI 2014 endorse, add macroeconomic policy convergence, social integration, gender
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Merger with AfDB index Merged with separate AfDB project endorsed by AfDB Board Many similarities in methodology – joint index respects principles endorsed by CoM 2014 and COMAI 2014 and AfDB Board Dimensions remain the same as before merger, individual indicators reviewed against measurability, availability of data and changed All other elements also remain the same ‘Political Economy’ dimension added to measure strength of RECs driving integration process.
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Further refinement Indicators further refined through consultations with NSOs, Member States (31 Member States in total), RECs (3), AfDB, AUC. Criteria: Based on data-collection ground: 85% completeness. Based on conceptual ground.
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Justification - balance of input and output indicators Some countries have advantages e.g. regional integration – greater complementarity of exports (e.g. South Africa) – boosts intra-regional trade, independent of integration measures taken by South African government Doesn’t reflect efforts Not fair if countries that do their best still score poorly because of geographical disadvantages etc.
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Justification - balance of input and output indicators Therefore use adoption of policies etc? BUT won’t measure implementation and won’t capture everything Therefore also use outcomes and intermediate outputs (not the aims, but the expected results of the policy – e.g. low cost of transport is output, high trade is outcome)
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Data collection Four approaches to collect regional integration data: First approach: questionnaires collected from countries. Second approach: from REC and corridor management agencies (CMA). Third approach: from national databases, websites and publications. Fourth approach: from international organizations’ statistical databases.
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Seven dimensions of indicators Regional migration and the labour market Trade integration Political economy Productive integration Financial integration and macroeconomic policy Regional infrastructure and interconnection (Social and cultural integration) TOTAL: 43 indicators.
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First approach: national questionnaire The first preference is to collect data directly from national governments and national statistical offices. For each country, a focal point is selected. Focal points are given national questionnaires, two months to collect data. Three training sessions trained 25 national focal points: From East and South African REC. Two days of training on data collection questionnaire and metadata guide.
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Second approach: REC and CMA Some indicators are better positioned to be collected through REC and CMA. e.g.: payment of REC financial due, cost of shipping along corridors. A separate questionnaire on REC and CMA levels. The REC questionnaire follows the same format of those for national focal points.
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Third approach: national databases If national focal points cannot locate indicator data, the RII team will try pulling data from national databases, NSO websites, publications, etc. We are seeking help from the SRO.
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Fourth approach: international sources Where appropriate, data from other reputable organizations may be used: online database, international organizations, etc. Whenever data has been provided by national government on its own score for a particular indicator, they will always be preferred over any other source.
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Data completeness Numbers of core indicators: 43. Numbers of core indicators with 85% or more completeness: 27. Still to go: 16. We are confident these indicators will pass the 85% rule. We keep track of: which indicators are collected for each country.
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SRO involvement Coordinate between RII team and NSO, countries. Advocate regional integration at sub-regional level. Analyse the success of best practices. Deposit data to the data bank. Improve data completeness for First and Third approaches. Check country data release calendar to ensure data timeliness.
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Multicollinearity critique Misunderstands purpose of index Not for statistical attribution – for fair aggregate ranking Unless variables perfectly collinear, omission will disadvantage some countries
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Overall scores Indicators will be scaled and aggregated Indicators will be scaled and aggregated Score = Score = (raw value – lowest raw value in dataset) (raw value – lowest raw value in dataset) (highest raw value in dataset – lowest raw value in dataset) Weighting – simple average but possible upcoming consultation of experts to see if some indicators should be more important Weighting – simple average but possible upcoming consultation of experts to see if some indicators should be more important
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Any questions? Contact: wdavis@uneca.org xche@uneca.org
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