Poverty Dynamics in the Congo A Markovian Approach

In this article, a Markov model was used to analyze poverty dynamics in the Congo, assuming that changes in poverty status observed at the household level follow a finite, discrete-time Markov process. The descriptive method was used to calculate the indicators associated with the transition matrix derived from the Markov chain. These various indicators derived from the transition matrix made it possible to assess household mobility. The data used were drawn from household surveys, and a synthetic panel was constructed. The analysis reveals that Congolese households exhibit mobility within poverty. However, this mobility is not significant enough; most households remain in their initial states. Consequently, the reduction of extreme poverty is slow, and it takes 15 years to achieve it. The anti-poverty policies implemented between 2005 and 2011 did not enable a significant proportion of households to escape poverty. Keywords: Congo, synthetic panel, poverty dynamics, Markov chain, chronic poverty.