Imperfect Data Increases Uncertainty
9 May 2013
The world is a complex place where risk and uncertainty are an everyday challenge. Decision makers at all levels say they are drowning in information; they are longing for clarity and knowledge, rather than conflicting information and opinions.
The complexity challenge is one important source of inspiration for researchers in ReCom – Research and Communication on Foreign Aid. In the ReCom position paper on ‘Aid, Environment and Climate Change’ there is, for instance, discussion on what the lack of systemic scientific information means for policy action (see also the research project 'Development under Climate Change').
It is important to understand that risk and uncertainty mean different things.
Risk vs. uncertainty
Risks in the form of undesirable shocks and events are predictable with some degree of certainty. There are parts of the world like Mozambique where floods are about every five years part of life. If we know how often these events have occurred in the past, then it is possible to plan around them. These are also the kinds of risks that aid donors are able to incorporate into their decision-making.
The real problem is uncertainty, which is a deeper and more systemic absence of knowledge. Will climate change mean a drier or wetter climate? We do not know. How much will the surface temperatures rise and what does it mean? Again, there is uncertainty. What we do know is that people and societies need to develop their capacity to adapt to climate change, both on an individual and an institutional level.
Duncan Green from Oxfam was thinking along similar lines when he noted in his recent blog post: ‘How to plan when you don’t know what is going to happen?’ He pointed to the fact that aid donors often pursue a linear model of change that overlooks the complexity of economic and power relationships in a country.
Decision makers need better numbers to cope with complexity and uncertainty, but they also—as Duncan Green suggests—need a new learning approach based on fast feedback and a focus on problems instead of solutions. Rejecting a results-based approach in foreign aid is probably wrong, but it needs to be infused with more realistic considerations as proposed in this ReCom video interview with a series of experts in the health sector.
In the ReCom Results meeting ‘Aid and our Changing Environment’ on 4 June 2013 in Stockholm there will be plenty of opportunity to discuss complexity and how researchers can help turn this into more manageable risk. Registration for onsite, as well as webcast participation is still open.
The data challenge
Uncertainty is not only an issue when trying to prepare for the future, but researchers often have to confront this challenge when trying to analyse our past.
There are huge knowledge gaps in our understanding of development. Even our measurement of economic progress is challenged by uncertainties. Many claim that the last decade has seen a resurgence of growth in Sub-Saharan Africa. Yet, in a challenging new book, ‘Poor Numbers: How we are misled by African development statistics and what to do about it’, Morten Jerven questions the validity of almost any statement on Africa’s growth that is based on statistical evidence. Data supplied by national records and statistical offices can prove to be highly unreliable. This implies that foreign aid might be poorly allocated: if underlying facts are wrong there is no chance that ‘evidence-based policy’ will work.
Examples of this can be found in real life; in November 2010 Ghana announced that GDP estimates had been revised upwards by more than 60 per cent. That is about US$13bn worth's of economic activity that was ‘missing’ from official statistics. The revision helped reclassify Ghana from ‘low-income’ to ‘middle-income’ status. This raises difficult questions for foreign aid. Was Ghana receiving more foreign aid than it should have? Is it meaningful to allocate foreign aid based on numbers that are measured with so much uncertainty?
We recently discussed Africa’s data challenge with Professor Andy McKay from the University of Sussex in a UNU-WIDER interview. McKay noted that the fastest growing countries are actually those where researchers have the hardest time understanding the situation of the poorest people, like Angola, Sudan, and also Nigeria. There is a troubling discrepancy between economic realities and the statistical metrics used to express and analyse wealth and poverty. ‘We don’t really have a consistent story about what happens to poverty’, he said.
But is the situation really as dire as some would have us believe? Is it possible to improve the way we measure economic progress in Africa? Jeffery Round, from Warwick University, thinks that foreign aid can help. He concludes in a WIDER Working Paper ‘Aid and Investment in Statistics for Africa’ (Summary), that foreign aid has already been effective in creating more reliable numbers, even though there is still plenty of room for improvement: ‘In little over two decades the pace of effort into building improved capacity to produce more and better databases (higher quality, with more coverage, timeliness, periodicity and higher integrity) has been substantial’, he writes.
This debate about the uncertainty of statistics has far-reaching implications, both for foreign aid and for development research. It is one of the core issues that will be addressed in UNU-WIDER’s September conference in Helsinki on ’Inclusive Growth in Africa. Both Morten Jerven and Andy McKay will participate in the conference and discuss, among other topics, the measurement of growth and poverty, and highlight new initiatives to reduce uncertainties for governments and researchers in Africa.
Carl-Gustav Lindén is Senior Communications Specialist at UNU-WIDER.