Africa 2010-2020: poverty reduction beyond the global crisis
What are the implications of the global financial crisis and its aftermath, regionally and globally, for Africa taking a 5-15 year view? The purpose of this paper is to outline a set of four post-crisis global economic scenarios to 2020,
and will consider their impacts across a range of low income countries. Design/methodology/approach ‐ The scenarios were developed using a version of the morphological scenarios approach, Field anomaly relaxation (FAR). This approach creates a
backdrop of internally consistent futures for policy formation and decision making through identifying and analysing the most significant drivers of change within the global financial and political system. This was then linked to a modelling approach to identify country impacts. The work was
developed and tested with stakeholders in the United Kingdom and Kenya. Findings ‐ Scenarios are plausible, coherent, multiple views of the future, which enable policy-makers and managers to evaluate strategy or policy choices under conditions
of uncertainty. The work creates a structured approach to reviewing outcomes for growth, poverty reduction and the Millennium Development Goals for different types of developing economies, against the background of the financial crisis. Research limitations/implications
‐ The work was conducted for a public sector client in the United Kingdom, with a limited budget and a limited timescale. Practical implications ‐ The combination of scenarios and modelling, applied to the field of development,
enables greater clarity about the choices presently facing developing African nations. In particular, the economic typology used shows that for the majority of African countries, strategies which improve resilience in the face of rising energy costs and possible food shortages will also generate
economic opportunities. Originality/value ‐ Innovatively, the scenarios were tightly connected to a "soft" model which identifies possible pathways, causal linkages and transmission variables between the scenarios and associated levels of economic
growth and poverty reduction via key economic variables. This permits more granular interpretation of the scenario outcomes than conventional scenario analysis techniques.
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