Abstract

Approximately 211 million people live in the Hindu Kush–Himalaya region. Although poverty levels in this region are high, there is a lack of cohesive information on the socioeconomic status of its populations that would enable decision-makers to understand different manifestations of poverty and design effective poverty alleviation programs. Hence, the International Centre for Integrated Mountain Development (ICIMOD), in consultation with international and regional partners, has developed the Multidimensional Poverty Measure for the Hindu Kush–Himalayas (MPM-HKH). This measure aims to identify and describe poor and vulnerable households across the Hindu Kush–Himalaya region—which is predominantly rural and mountainous and covers several of the world’s least developed countries—in a consistent manner. This article documents how the MPM-HKH was developed and demonstrates the utility of this approach, using Nepal as an example, by analyzing household survey data from 23 districts. The analysis gives important clues about differences in the intensity and composition of multidimensional poverty across these locations, which highlights the need for location-specific poverty alleviation strategies. The findings should help decision-makers to identify areas of intervention and choose the best measures to reduce poverty.

Highlights

  • 211 million people live in the greater Himalayan region

  • Policymakers and development planners have little of the information they need to improve the effectiveness of their poverty alleviation programs in mountainous areas

  • Every second to every fourth household in the Hindu Kush– Himalayas (HKH) lives in poverty

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Summary

Introduction

211 million people live in the greater Himalayan region. The 8 countries of the Hindu Kush– Himalayas (HKH) are Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal, and Pakistan (ICIMOD 2015). Poverty levels in this predominantly mountainous region are high. A recent regional study found that national poverty rates range from 23% to 46% (Gerlitz et al 2012). The study showed that available national survey data had limitations in terms of mountain-specific indicators, consistency across countries, and representativity for smaller administrative units. Policymakers and development planners have little of the information they need to improve the effectiveness of their poverty alleviation programs in mountainous areas

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