Reviewing DRC’s poverty estimates, 2005-2012: Unprecedented GDP growth without trickle down - Marivoet, Wim; De Herdt, Tom; Ulimwengu, John M. (Secure Livelihoods Research Consortium, 2019)
The first decade of the Democratic Republic of the Congo’s (DRC) post-conflict reconstruction period (2004-2013) was marked by an unprecedented economic growth in per capita gross domestic product (GDP) of 3-4% per year, but was this ‘peace dividend’ translated into widespread poverty reduction within the Congolese population? This working paper answers this question by focusing on the percentage of people in poverty (or poverty headcounts) using micro-level data. The paper uses two national household surveys: the first was conducted in 2004-2005, right before the 2006 elections that inaugurated the first post-conflict government; and the second was carried out in 2012-2013, about seven years after the first round. Both the Institut National de la Statistique (INS) (RDC, 2014) and the World Bank (2016) estimate very high poverty rates; and both point to a significant decrease in poverty between the two survey periods. Using the same datasets, both institutions find that the poverty headcount decreased by five to eight percentage points. The problem with both estimates, however, is that they cannot be replicated. The World Bank reports its poverty estimates without elaborating on the methodology, nor explaining why they differ from the INS results. Although INS provides more detail on the methodology they followed, this information only enabled the authors to replicate its 2005 poverty estimates (RDC, 2006), not its 2012 estimates. When applying the INS’s methodology from 2005 to the 2012 survey, the authors found that the percentage of people in poverty substantially increased from 72% to 81% – in sharp contrast to the INS’s own reported results, and also runs counter to current understandings on the evolution of the DRC’s economy. To produce more accurate poverty estimates and trends, the authors made a number of modifications to the INS methodology.