We are ICIMOD, a unique intergovernmental institution leading the global effort to protect the pulse ...
With a vast array of partners, we organize our work in what we call Regional ...
Successful interventions can change lives for the better. We hope that the stories of success ...
3 mins Read
Capturing mountain specificities requires that multi-dimensional poverty indices extend beyond health, education, and living conditions to include inaccessibility and access to resources and services
Poverty assessments are both income and multidimensional but even the more complex multidimensional assessments do not allow us to target and design effectively. Coupled with other problems such as inadequate data, information, and knowledge about the nature, causes, incidence and severity of mountain poverty, alleviating poverty as envisioned by the global community in the SDGs has remained a major challenge in the HKH region.
Realizing the serious gaps in knowledge and understanding about mountain poverty, we undertook a comprehensive assessment of poverty in the HKH region using both an income (consumption) based approach and a multidimensional approach in analysing. While conventional multidimensional poverty indices use three dimensions of poverty (health, education, and living conditions) we added two more dimensions – inaccessibility and access to resources and services – to capture mountain specificities. We used nationally representative household survey data of different periods and different surveys. Where survey data are not available, we used published reports by government, development agencies and research reports to assess the status and trends of poverty, to analyse causes and drivers and to examine HKH government poverty alleviation policies and programmes.
Poverty is declining across the HKH, except in Afghanistan. The pace of poverty alleviation is not uniform; it is fast in China and Bhutan, relatively moderate in Bangladesh, India, Myanmar, Nepal, and Pakistan, but slow in Afghanistan. In Afghanistan, poverty has increased since 2011. One striking finding is that poverty incidence in urban and mountain regions of Nepal is higher in 2010 as compared to 2004.
Poverty incidence is higher in mountain regions. There are what might be called “poverty pockets” within the HKH region, even within countries. Generally, the incidence and severity of poverty both in terms of consumption and multidimensional poverty is higher in mountain regions compared to plain areas, except in Afghanistan and in Bhutan, where the entire country is considered mountainous.
Multidimensional poverty is higher than income poverty in all of the HKH countries. However, there is strong positive relationship between income and multidimensional poverty. As in income poverty, multidimensional poverty is higher in mountain areas compared to the national average (see graph).
We hope that this work will allow improved understanding about mountain poverty. Since mountain challenges such as physical distance and poor connectivity lead to higher costs in education, health, credit, business and other basic services social exclusion is reinforced and disadvantage and marginalization compounded for mountain people. Since there are poverty pockets within the HKH region, policy makers need specific information in order to better target poverty alleviation programmes.
Demand-driven, context-specific workshop allows for module testing
An application enables better data visualization of and access to ICIMOD data from the HKH
Key steps towards more data generation, sharing and regional cooperation to understand and mitigate climate change impacts
Advocating ecosystem-based adaptation approaches to address the complex impacts of climate change on communities and their environments