GCRF: Developing an Environmentally-adjusted Index for Multidimensional Poverty

GCRF：制定多维贫困的环境调整指数

• 批准号: ES/P003583/1
• 负责人: Bhaskar Vira
• 金额: $ 22.23万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FP003583%2F1
• 关键词: GCRF; Developing; Environmentally; adjusted; Index

The intersection of poverty and environment policies that is the focus of the Sustainable Development Goals provides an important opportunity for the use of secondary data. Whilst both areas have been intensively individually studied, most if not all globally accepted poverty indicators have ignored the role of the natural environment. ESRC funded research programmes such as ESPA (Ecosystem Services for Poverty Alleviation) have furthermore highlighted that much of the ecosystem services literature in low and middle income countries has been primarily concerned with the role of ecosystems as an instrument for getting food, energy or better living standards (i.e. ecosystem's provisioning services). However, there is growing recognition that being able to engage with the natural environment in a meaningful way (culturally, spiritually) and the ability to withstand shocks and reduce vulnerability through access to nature are intrinsically valuable, in addition to the generally accepted provisioning services. These dimensions of human dependence on nature are so-called 'functionings' in the Capabilities Approach, developed by Amartya Sen (1999), and allow people to live a 'good life'. This approach forms the theoretical basis of the well known Multidimensional Poverty Index (MPI), officially used by over 100 countries to identify the poor. The MPI provides rigorous statistics on poverty incidence and intensity, and includes dimensions related to health, education and living standards. It is therefore a strong instrument to support the SDG agenda, which pays particular attention to the inclusion of environmental factors. Operationalisation of a post-2015 global MPI that allows cross-country comparison in relation to the SDGs depends on the availability of adequate and appropriate secondary data on environment and poverty. This proposal aims to develop such a measure. Using secondary data from Brazil (see details justifying this focus in the Case for Support), we propose to develop and test the possibility of developing an environmentally-adjusted MPI that can help measure progress towards the achievement of the post-2015 SDG agenda. We will compare the environmentally-adjusted MPI statistics to existing MPI statistics to understand the patterns of incidence and experience of poverty and wellbeing, as measured by these alternative indicators. For instance, poverty may be the same if people identified as being poor under the current MPI are the same as those unable to deal with risks of natural hazards and climate change, and unable to access and engage meaningfully with the natural environment. Secondly, there is a need to understand whether the observed improvement in GDP and income (in Brazil) are reflected in the more broadly defined environmentally-adjusted MPI. Therefore, we will look into the trends in the different MPI dimensions over time and space. We will aim to evaluate national level poverty-alleviation strategies in Brazil, such as the Bolsa Familia programme of Brazil's Fome Zero programme, to evaluate if the focus of these policies (in terms of the choice of targeted interventions and choice of beneficiaries) can explain the observed trends in both the existing MPI and an environmentally-adjusted measure. Building on the detailed analysis of the Brazilian case, we propose to use our strong existing research and collaborative networks in Nepal to test this measure in a contrasting ODA-eligible context. For globally comparative analyses, it is important for the measures that emerge from this project to be applicable in diverse contexts. Data availability, research capacity and the context for implementation all matter, and are very different in Nepal relative to Brazil. By collaboratively exploring the different needs and challenges of an environmentally-adjusted MPI measure in Nepal with key research and impact partners, we will investigate the potential for such a globally comparable measure.

贫困与环境政策的交叉是可持续发展目标的焦点，这为使用二级数据提供了重要机会。虽然对这两个领域都进行了深入的研究，但大多数（如果不是所有的话）全球公认的贫困指标都忽视了自然环境的作用。环境与社会研究中心资助的研究方案，如生态系统服务促进减贫方案（ESPA），进一步强调，低收入和中等收入国家的许多生态系统服务文献主要关注生态系统作为获得粮食、能源或提高生活水平的工具的作用（即生态系统的供应服务）。然而，人们日益认识到，除了普遍接受的供应服务之外，能够以有意义的方式（文化上、精神上）与自然环境接触，以及通过接触自然抵御冲击和减少脆弱性的能力，具有内在的价值。人类依赖自然的这些方面是Amartya Sen（1999年）提出的能力方法中所谓的“功能”，使人们能够过上“美好的生活”。这一方法构成了著名的多维贫困指数的理论基础，100多个国家正式使用该指数来确定穷人。MPI提供了关于贫困发生率和贫困程度的严格统计数据，包括与健康、教育和生活水平有关的方面。因此，它是支持可持续发展目标议程的有力工具，该议程特别关注环境因素的纳入。2015年后全球多指标计量表的运作，允许与可持续发展目标有关的跨国比较，取决于是否有足够和适当的环境和贫困二级数据。本提案旨在制定这样一项措施。利用来自巴西的二手数据（详见支持案例中证明这一重点的细节），我们建议开发和测试开发环境调整的MPI的可能性，该MPI可以帮助衡量实现2015年后可持续发展目标议程的进展。我们将比较环境调整的MPI统计数据与现有的MPI统计数据，以了解这些替代指标衡量的贫困和福祉的发生率和经验的模式。例如，如果根据目前的多指标衡量标准被确定为穷人的人与那些无法应对自然灾害和气候变化风险、无法接触和有意义地参与自然环境的人相同，那么贫穷可能是相同的。第二，需要了解所观察到的国内生产总值和收入（巴西）的改善是否反映在更广泛定义的按环境调整的多指标指数中。因此，我们将研究不同MPI维度随时间和空间的趋势。我们的目标是评价巴西的国家一级减贫战略，例如巴西的零贫穷方案的家庭补助方案，以评价这些政策的重点（在选择有针对性的干预措施和选择受益者方面）是否能够解释现有的多指标指数和环境调整措施中观察到的趋势。基于对巴西案例的详细分析，我们建议利用我们在尼泊尔强大的现有研究和合作网络，在符合ODA条件的背景下测试这一措施。就全球比较分析而言，重要的是该项目产生的措施应适用于不同的情况。数据的可得性、研究能力和执行环境都很重要，尼泊尔与巴西有很大不同。通过与主要研究和影响合作伙伴合作探索尼泊尔环境调整MPI措施的不同需求和挑战，我们将调查这种全球可比措施的潜力。

项目成果

Poorer without It? The Neglected Role of the Natural Environment in Poverty and Wellbeing

• DOI: 10.1002/sd.1692
• 发表时间: 2018
• 期刊: Sustainable Development
• 影响因子: 12.5
• 作者: J. Schleicher;M. Schaafsma;N. Burgess;C. Sandbrook;F. Danks;C. Cowie;B. Vira

Will the Sustainable Development Goals address the links between poverty and the natural environment?

• DOI: 10.1016/j.cosust.2018.09.004
• 发表时间: 2018-10
• 期刊: Current Opinion in Environmental Sustainability
• 影响因子: 7.2
• 作者: J. Schleicher;M. Schaafsma;B. Vira

Protecting half of the planet could directly affect over one billion people

• DOI: 10.1038/s41893-019-0423-y
• 发表时间: 2019-12-01
• 期刊: NATURE SUSTAINABILITY
• 影响因子: 27.6
• 作者: Schleicher, Judith;Zaehringer, Julie G.;Sandbrook, Chris
• 通讯作者: Sandbrook, Chris

Incorporating Environmental and Natural Resources within Analyses of Multidimensional Poverty

将环境和自然资源纳入多维贫困分析

• 发表时间: 2018
• 作者: Thiry, G.