Understanding inequality is a key part of understanding how poverty affects different groups in different ways. In India recently, we’ve analysed survey data to highlight how caste discrimination has slowed poverty reduction. We’ve shown how a lack of recent poverty data means the true impact of Covid-19 and climate change is unclear. And our work has stressed the risks of replacing missing data with broad population estimates.

Climate change has been one focus area of our work in India. By using machine learning to analyse temperature data and very localised estimates of household wealth, we’ve shown how climate change could pose significant challenges to poverty reduction. One study also highlighted the complex links between poverty and climate change and the need for strategies that address both. And, in a groundbreaking piece of research, we suggested that poverty in India since 2011 may actually have reduced less than some estimates suggest, leading to interest from the World Bank and the Asian Development Bank.

By supporting local policymakers and researchers with new tools and insights, we aim to enable successful action to reduce poverty. In India, one recent study highlighted how effective urban planning could make a critical difference to poverty reduction strategies. Another more localised project analysed the economic effects of the pandemic on two Indian villages. We explored the impact of job losses, inequality and loss of income, and considered the strengths and inconsistencies of social support.