Regional Workshop on Poverty Measurement and Monitoring in the Era of Big Data
The Economic and Social Commission for Western Asia (ESCWA), within the framework of the United Nations Development Account (DA) Programme to improve statistics, data and the 2030 Sustainable Development Agenda, and specifically the Social and Demographic Pillar, is implementing the project on "Poverty and Inequality Statistics". The project aims to strengthen the capacity of Arab countries to improve disaggregation and frequency of household surveys. Specifically, it addresses the lack of data coming from household surveys that are used for monitoring targets under Sustainable Development Goal (SDG) 1 “End poverty in all its forms everywhere” and SDG 10 “Reduce inequality within and among countries” and aims to provide the necessary inputs for better measurement of indicators based on those surveys.
Moreover, the Cape Town Global Action Plan for Sustainable Development Data recognized the need to facilitate the application of modern technologies and new data sources in mainstream statistical activities to support the implementation of the 2030 Agenda as well as tracking progress of the SDGs.
As part of the project’s activities, several studies have been conducted by ESCWA to assess the availability of information and data gaps in existing household surveys in the Arab region and make recommendations for their improvements. In addition, a regional workshop was convened in July 2019 in Tunis to present and discuss the studies and resulting recommendations as well as to identify best practices and lessons learned at regional level that would improve the measurement of some household-based indicators for Goals 1 and 10, and to identify the training needs by countries in the area of poverty and inequality.
The outbreak of coronavirus pandemic (COVID 19) earlier this year severely affected the production of data which relies on face to face interviews, and this includes the household income, expenditure and consumption surveys. There is therefore an urgent need for National Statistical Offices (NSOs) to use non-traditional data sources such as big data, new cloud technologies, and new methods of data capture through high frequency surveys. In this context and as a follow up to the DA project’s activities, ESCWA is organizing a virtual regional workshop on poverty measurement and monitoring in the era of big data.
The workshop explores recent developments in statistical methodologies and new data sources for measuring and monitoring poverty at various levels and dimensions. Specifically, the workshop aims to provide guidance to the NSOs on new knowledge and methodologies to measure and monitor SDGs and Agenda 2030 and identify opportunities, challenges and limitations of using big data for official poverty measurement in low- and middle-income countries. The workshop will also explore the potential of high frequency surveys to monitor poverty over time and across small areas, particularly targeting vulnerable groups such as refugee populations, and identify future research needs in statistical methodologies and the use of new data sources for living conditions and poverty indicators. Ultimately the workshop will help to achieve a common and improved understanding of new knowledge, methodologies and data sources that would contribute to monitoring poverty over time and across small areas and improving the measurement of some living conditions and poverty indicators for Goals 1 and 10.
- The feasibility of using Big Data for development (Mr. Vedran Sekara, UNICEF)
The use of big data / non-traditional data sources in the compilation of SDG indicators in Arab countries: an overview (Mr. Ismail Lubbad, UN-ESCWA)
- Poverty measurement – case of Denmark and some global aspects (Mr. Maciej Truszczynski and Mr. Niels Ploug, Statistics Denmark)
- Mapping poverty with remote sensing and other Big Data sources (Mr. Giovanni Savio, Expert on Big Data for SDGs)
- Using financial transaction Big Data to support household surveys: the case of monitoring consumer spending behaviors during COVID19 pandemic (Mr. Hatem ElSherif, FCSC, UAE)
- Which model for poverty predictions? (Mr. Paolo Verme, World Bank)
- Using social media advertising data to map poverty among migrants and refugees (Mr. Ingmar Weber, Qatar Computing Research Institute)
- Assessing the living conditions of refugee communities in Turkey, Lebanon and Jordan through the lens of cellphone metadata: promise, challenges, and future directions (Mr. Emmanuel Letouzé and Ms. Roaa Al Feel, Data-Pop Alliance)
- Lebanon case: Assessing non-traditional data sources for the conditions of refugees and host communities (Mr. Fouad Mrad, UN-ESCWA);
- Monitoring COVID-19 impacts and poverty using innovative methods (Mr. Utz Pape, World Bank)
Statistical and operational challenges of shifting from face-to-face to CATI LFS (Mr. Nader Keyrouz, ILO Regional Office)