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Cameroon has witnessed substantial economic growth in the new millennium, while poverty reduction has been limited and inequality has worsened. In this context, this chapter investigates the different facets of poverty in Cameroon, factors affecting them and policy options to tackle poverty and achieve inclusive and sustainable development. We apply two prominent poverty measurement methods (Alkire-Foster and Foster-Greer-Thorbecke) to a series of household consumption and living standards (ECAM) surveys and Demographic and Health Surveys (DHS) collected between 2001 and 2018, and perform various empirical analyses to elucidate poverty dynamics and features. Our results indicate that both monetary and multidimensional poverty have decreased in Cameroon between 2001 and 2018, albeit slowly and to varying degrees across the different demographic, socioeconomic and spatial groups of the population. We find that the proportion of multidimensional poor people is always higher than the proportion of the monetary poor. At the same time, multidimensional poverty has reduced much faster than monetary poverty at the national level. Lastly, we find that higher levels of poverty in Cameroon are strongly associated with rural livelihoods, large family size, less education, employment in agriculture and the Northern regions of the country. Our micro-economic analysis is complemented with a review of structural factors affecting poverty at the macro level. We point out the need to accelerate the structural transformation of the Cameroonian economy, to reduce inequalities across the different regions and sub-groups of the population and expand economic opportunities for the youth to achieve the demographic dividend.

As many other countries, India leverages on a pre‐existing workfare programme as a COVID‐19 response. We combine monthly administrative data with migration and poverty statistics and provide four insights on the recent expansion of the programme. First, poorer districts include more households, that is, increasing extensive margin. Second, in districts with a high proportion of return migrants, there is no increase, and third, unmet demand for work is higher than the national average of 22.7%. Fourth, despite the expansion, the programme provided just 13.5 days per rural household. The programme requires attention to fulfil its promise as a credible safety net.