Description: Background As countries strive to meet growing demands for granular statistics, national statistical offices (NSOs) are increasingly adopting innovative approaches to complement traditional data sources. Among these, Small Area Estimation (SAE) has emerged as a powerful technique for producing reliable estimates at lower geographic and administrative levels, particularly for development indicators related to poverty, food security, health, and labour markets. The World Bank, through its Knowledge for Change Program (KCP), has supported research and methodological development to integrate georeferenced survey and census data with EO data for SAE purposes. This includes practical resources such as the GeoLink and povmap packages in R, as well as the joint United Nations Statistics Division (UNSD)–World Bank “Primer on Using Geospatial Data for Small Area Estimation”1. To support the implementation and practical adoption of the Primer, ESCAP, ECA, UNSD, and the World Bank have developed a how-to guide2 to provide a step-by-step walkthrough for using geospatial data to perform SAE. Building on this foundation, ESCAP, UNSD, and the World Bank have collaborated to deliver capacity development programs introducing NSOs to these methods and tools. Initiated in 2024, the programs combined e-learning with in-person workshop, with the 2025 cohort of participants attending weeks of online classes and in-person hands-on workshop to learn about the latest tools and techniques for geospatial SAE and apply them to their datasets to produce a range of socio-economic and development estimates. Against this backdrop, ESCAP, in collaboration with UNSD and the World Bank, is organizing a Stats Café to provide an overview of the latest developments in SAE using geospatial data to a wider audience and highlight some country experiences in geospatial SAE. Join us for an interactive session on 27 January 2026 (11:00–12:15 Bangkok time). Register for the Stats Café by clicking on the REGISTER button on the top right of the page or scan the QR code in the flyer. Why attend? In particular, this Stats Café aims to: Demonstrate the applicability and use cases of the how-to guide on geospatial SAE to a wide range of audience, advancing the adoption of SAE as an essential tool to fill data gaps for effective policymaking. In a panel discussion, showcase country experiences in applying geospatial SAE in their work following the November 2025 workshop and facilitated e-learning course. Highlight the latest methodologies and tools available for audience to start experimenting with geospatial SAE in their workstreams. Highlights: Demonstration: Using the how-to guide for geospatial SAE. Panel Discussion: Experiences, challenges, and future plans for integrating SAE with geospatial data. , Stats Café Home: Upcoming events Concluded events
Description: Background: Small area estimation (SAE) techniques are a proven approach to generate reliable and disaggregated data on poverty, food insecurity, health and nutrition, and labor outcomes. Recognizing this, NSOs have consistently requested additional technical guidance and training. The rapid growth of Earth Observation (EO) data has expanded the scope and applicability of SAE, while also highlighting the need to strengthen standards and build NSO capacity in foundational SAE techniques with EO data. Building on this momentum, the Economic and Social Commission for Asia and the Pacific (ESCAP) and the Statistics Division of the UN Department of Economic and Social Affairs (UNSD), in partnership with the World Bank delivered a successful capacity development programme in 2024 to expose participants to small area estimation using earth observation data. The workshop built on existing small area estimation training materials, including an e-learning course on small area estimation, developed jointly by ESCAP, UNSD, and World Bank, and exposed participants to tools and techniques to integrate survey and geospatial data. Since these workshops, however, the field has continued to advance at a rapid pace. Against this background, ESCAP, UNSD and the World Bank are collaborating to organize a follow-up capacity development workshop for NSOs in Asia and the Pacific. The workshop will expose participants to (a) the latest software tools that make it easier to use and manipulate EO data and combine it with survey data for SAE purposes, and (b) the latest SAE modeling methods, including those inspired by recent advances in AI (Zhuo et al., 2025). It also facilitates experience-sharing by participants of last year’s workshop on the use of SAE in their work and lessons learned on integrating SAE in their organization’s workflows. The learning programme will consist of a guided e-learning course, ongoing mentoring and support, and an in-person workshop in Bangkok from 24–28 November 2025. Objectives: Showcase initiatives involving the use of SAE by participants in their organization Understand the range of geospatial data and tools available for SAE and their integration with survey data, Be able to apply (a) simple SAE models in R using real-world geospatial data, and (b) AI-based methods that utilize satellite imagery and geospatial features, and Strengthen their knowledge of how to transition from experimental projects to the regular production of official statistics in this area. Workshop format: The in-person workshop will be delivered by Dr. Joshua D. Merfeld, who is a senior lecturer at the University of Queensland and a consultant for the World Bank, supported by staff from ESCAP, UNSD and World Bank. The workshop and the materials will be in English. Post-learning Activities: Following the completion of the learning programme, participants will be expected to demonstrate their newly acquired skills by producing a knowledge product that demonstrates SAE for official statistics. Ongoing support, including access to online resources, will be provided after the workshop.
Organizer(s): UNSD UN ECA ESCAP ECLAC World Bank AI Generated
Description: This side event of the 56th session of the United Nations Statistical Commission aims to promote the adoption of small area estimation (SAE) in national statistical offices through two key initiatives: the innovative use of geospatial data and capacity-building initiatives.
Description: Transforming Agrifood Systems for our Blue Pacific Continent through Better Production, Better Nutrition, a Better Environment and a Better Life
Description: For several decades, area-level models have played a critical role in the theory and practice of small area estimation. For an area-level model, we propose a random effects variance estimator that simultaneously (i) improves on the estimation of the related shrinkage factors, (ii) protects empirical best linear unbiased predictors (EBLUP) of the random effects from the common over-shrinkage problem, (iii) avoids complex bias correction in generating strictly positive second-order unbiased mean square error (MSE) estimator either by the Taylor series or single parametric bootstrap method. The idea of achieving multiple desirable properties in an EBLUP method through a suitably devised random effects variance estimator is the first of its kind and holds promise in providing good inferences for random effects under the EBLUP framework. The proposed methodology is also evaluated using a Monte Carlo simulation study and real data analysis. This is a joint work with Prof. Partha Lahiri at the University of Maryland, College Park.
Description: This talk will cover recent developments in the literature on small area estimation in developing countries from a practitioner’s perspective. It will consider the merits of non-traditional sources of auxiliary data, particularly geospatial data. It will also consider different statistical methods for estimation, software packages to carry out estimation, and propose a research agenda to fill knowledge gaps.
Description: Organized by the United Nations Committee of Experts on Food Security, Agriculture and Rural Statistics (UN-CEAG) on the sidelines of the 55th Session of the United Nations Statistical Commission.
Description: This side event of 55th session of the United Nations Statistical Commission, aims to showcase the experiences and lessons learned from the Global Training on Small Area Estimation across three key regions: Latin America and the Caribbean, Asia Pacific, and Africa.
Source: Eurostat (Data extracted on: 25 Jan 2024 )
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Organizer(s): Eurostat
Description: Are you interested in regional statistics and want to learn more about the nomenclature of territorial units for statistics, the so-called NUTS? During this webinar, you will get valuable insight into European regional statistics. How can we compare small EU countries like Luxembourg to Germany, which is the most populous one? Comparing regional data is often more informative compared with country data: it may reveal the disparities or similarities between EU members or even within EU countries themselves. Speakers will give fascinating insights into the lives of the 448 million people living in the EU. They will be covering a variety of topics, from demography to education, labour market, and economy. With the help of interactive visuals, the speakers will show how the EU regions are coping with the green and digital transition. In addition, you can learn how to make your own statistical map for regions.
Description: In unit-level small area models, the response variable corresponds to an individual element within a small area. Unit-level models serve a fundamental role in the field of small area estimation. Predictors based on unit-level models have been demonstrated to be more efficient than predictors based on area-level models, where the response variable is a direct estimator for an area. The seminal work on unit-level small area models is Battese, Harter, and Fuller (1988). This work uses unit-level small area models to predict crop areas at the county level. The model of Battese, Harter, and Fuller (1988) is linear and postulates normal distributions for the random terms. The assumptions of linearity and normality fail to hold in many practical situations. Therefore, research on the unit-level model has expanded in a variety of directions. Extensions of the Battese, Harter, and Fuller (1988) model include lognormal models, zero-inflated models, models with gamma response distributions, models for count data, and methods to incorporate an informative sample design. In this webinar, we discuss the use of the unit-level model for small area estimation, with emphasis on recent developments.
Description: Labor market statistics are of major importance when addressing social and economic challenges. These statistics are typically derived from complex survey data collected on a monthly or quarterly basis. However, when it comes to small geographical areas or domains, survey samples often fail to provide reliable estimates. To address this issue, the Economic Commission for Latin America and the Caribbean (ECLAC) has put forth a standardized approach that utilizes area-level models, taking into account the multinomial nature of occupation statuses. Within a Bayesian framework, we define a both a linkage and a sampling model that enable the simultaneous estimation of a diverse set of indicators of interest, such as unemployment rates, occupation rates, and participation rates. This innovative approach proposed by ECLAC aims to overcome the limitations associated with traditional survey sampling methods, particularly in smaller areas where the precision of estimates may be compromised. To validate the effectiveness of our methodology, we conducted a design-based simulation, which revealed promising results and demonstrated the favorable performance of the proposed approach. Building upon this success, we proceeded to implement the methodology across several countries in Latin America, leveraging the extensive and reliable data repository provided by ECLAC's BADEHOG survey database. By adopting this standardized approach, ECLAC aims to enhance the accuracy and reliability of labor market statistics at both national and subnational levels. The utilization of area-level models and the incorporation of Bayesian techniques allow for more reliable estimations, thus enabling policymakers, researchers, and practitioners to make informed decisions and develop effective strategies to address labor market challenges in Latin America and the Caribbean region.
Title in Spanish: Seminario regional sobre metodologías de estimación en áreas pequeñas y desagregación de datos
Organizer(s): ECLAC Centro Regional de Estudios para el Desarrollo de la Sociedad de la Información
Description: El énfasis de la Agenda 2030 para el desarrollo sostenible en no dejar a nadie atrás y atender particularmente a los más vulnerables hace necesario contar con indicadores suficientemente desagregados según diversas características de la población y escalas geográficas.
Description: UNSD conducted a capacity building training workshop on the Degree of Urbanisation(DEGURBA) Methodology for national statistics offices and geospatial institutions of countries in Central Asia. The workshop was organized in cooperation with the European Commission Joint Research Center (EC-JRC) and UN-Habitat and included the participation of statisticians and geospatial specialists from Azerbaijan, Kazakhstan, Kyrgyzstan, Tajikistan and Uzbekistan, as well as experts from UNSD, ESCAP, EC-JRC and UN-Habitat. As national Statistical Offices use different national criteria to define cities, urban and rural areas, the Degree of Urbanisation methodology was developed by the European Commission, UN-Habitat, FAO and other partners as a way to harmonize these definitions and promote international and regional data comparability, particularly in the context of reporting on the Sustainable Development Goals (SDGs) and on the New Urban Agenda (NUA). DEGURBA was endorsed by the Statistical Commission at its 51stSession in 2020. Through theoretical and practical sessions the participants were trained on 1) the need for this methodology 2) theory and concepts 3) data inputs, data preparation and technical capacity 4) applying the methodology, reviewing and evaluating the results and5) its applications for reporting of data and SDG indicators by degree of urbanization. The participants also exchanged experiences/challenges and learned from each other. Finally, this capacity building workshop further emphasized and provided practical knowledge on the importance of integrating census data with geospatial information.
Description: The launch of the new eLearning course on Small Area Estimation (SAE) was an event to remember. UNSD, UN ECLAC Statistics Division, and UNFPA gathered a prestigious panel of experts to discuss how Small Area Estimation (SAE) methods can support SDGs and countries, and how the eLearning course is an essential tool for disseminating knowledge and making information more accessible. The panel discussion featured insights from internationally renowned professors, as well as experiences from countries and international organizations, all of which inspired the audience and highlighted how much still needs to be done. The launch of this eLearning course marks a milestone in the journey on SAE, which started with the launch of the Toolkit on SAE on the Wiki platform requested by IAEG-SDG one year ago. With over 220 people attending the online event, it's clear that the topic of SAE is highly popular. More information on the event page.
Description: Co-organized by the United Nations Committee of Experts on Food Security, Agriculture and Rural Statistics (UN-CEAG) and the Food and Agriculture Organization of the United Nations (FAO) on the sidelines of the 54th Session of the United Nations Statistical Commission, the event took stock of the latest developments and progress in implementing the UN-CEAG's programme of wo...
Source: World Bank (Data extracted on: 03 Feb 2023 )
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Organizer(s): World Bank
Description: Advancing the World Bank’s twin goals of ending extreme poverty and boosting shared prosperity requires knowing who the poor are and where they live. By reaching the most granular levels of geographic aggregation, policymakers can significantly improve outcomes for the world’s poorest. However, survey data alone is not sufficient for targeting at the lowest levels. This is where small area estimation becomes necessary. The publication of Guidelines to Small Area Estimation for Poverty Mapping caps more than two decades of poverty mapping experience at the World Bank since the launch of an innovative method combining census and survey data to study the spatial dimensions of poverty. The guidelines build upon the lessons learned from experience and seek to guide readers on the best methods available for a variety of data landscapes.
Description: Model-based small area estimation approaches are in great demand by institutions interested in reliable statistics at disaggregated levels. Such tools overcome estimation challenges using small or incomplete survey data, in part, by combining data from multiple sources. The course starts with an overview of important small area estimation concepts. Area-level models are the main focus of the course, as proven to be of great practical use. Hierarchical Bayes inference is adopted. Software programs are provided for the model fit, validation, prediction, and comparison, with model specification scrips in R STAN. Illustrations use public-use data from the U.S. Census Bureau, for state-level poverty rate estimation research. Learning outcomes to be covered Learn how to conduct area-level model-based small area estimation analyses using freely available software.
Target Audience: The course is intended for statisticians interested in hierarchical Bayes model-based small area estimation.
Topics:
Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
IASS Webinar: Hukum Chandra prize 2022: Small area estimation: a novel approach on estimation of mean squared prediction error of small-area predictors
Description: Background The Pacific region has recently finalised its next strategic framework for statistics covering 2022-2030 (replacing the previous Ten-Year Pacific Statistics Strategy). At the same time, the broader Asia-Pacific statistical community adopted a Collective Vision and Framework for Action in 2016, recognising the shared ambition for the 2030 Agenda. Separate thematic statistics strategies are also operating (for example, the Pacific Roadmap for Gender Statistics, the Asian and Pacific CRVS Decade 2015-2024 and Regional Action Framework). Objectives: To enhance awareness of existing regional statistics strategies, their use at the country level alongside national strategies for the development of statistics, and their role in guiding development partner support to the production and use of statistics in priority areas. Target Participants: National Statistics Office representatives, statistics users, regional and international partners engaged in statistical capacity building, donors. Issues to be explored: What gaps do/can regional statistics strategies fill that National Strategies do not? How can we monitor regional statistics strategies to ensure their full effectiveness (capacity development and outputs)? How does each key stakeholder benefit from regional strategies? How are thematic statistics strategies being used as effective tools for engaging data users? , Committee on Statistics, 8th Session Side events during the CST8 week
Description: Co-organized by the UN-CEAG and FAO on the sidelines of the 53rd Session of the United Nations Statistical Commission, the event took stock of the latest developments and progress in implementing the UN-CEAG's programme of work (2020-2023) and discussed additional topics of interest in the area of food security and agricultural statistics.
Description: This side event, organized by the Food and Agriculture Organization of the United Nations (FAO) in partnership with the United Nations Economic Commission for Africa (UNECA) and PARIS21, will look at the potential role of the Global Strategy to Improve Agriculture and Rural Statistics (GSARS), in the development of agricultural statistics in the 25 beneficiary countries Date Thursday, 10 February 2022, 11:00-12:30 PM (New York Time) Opening remarks and welcome José Rosero Moncayo, Director, Statistics Division, Food and Agriculture Organization of the United Nations and Chair, 50x2030 Partnership Council Speakers Sidney Nii Oko Bampoe Addo, Deputy Director, Statistics, Research and Information Directorate, Ministry of Food and Agriculture, Ghana Aurelio Mate Junior, Head of Statistics Department, Ministry of agriculture and Rural Development (MADER), Mozambique Neli Georgieva, Statistician, FAO Lassina Paré, Statistician, FAO Catherine Krüger, Inter-Regional Advisor,Paris 21 Q&A Moderator Joseph Ilboudo, Chief, Statistical Development, Data Innovation and Outreach Section, African Centre for Statistics, UNECA This side event, organized by the Food and Agriculture Organization of the United Nations (FAO) in partnership with the United Nations Economic Commission for Africa (UNECA) and PARIS21, will look at the potential role of the Global Strategy to Improve Agriculture and Rural Statistics (GSARS), in the development of agricultural statistics in the 25 beneficiary countries. Representatives from countries NSOs will share their experience of introduction of the GSARS plan in their countries, how it fits with the national strategies of development of agricultural statistics and with opportunities offered with the future implementation of 50x2030 Initiative. The Q&A session will give participants the opportunity to ask questions to the presenters, as well as to share their own challenges and expectations.
Description: As many countries have turned their attention to the estimation of poverty at the subnational level, this webinar aims to discuss practical aspects of poverty mapping.
Title in Arabic: دورة متقدمة في أساليب تقدير المناطق الصغيرة
Organizer(s): AITRS ESCWA UNFPA
Description: زاد الطلب، من القطاع العام والقطاع الخاص، على التقديرات الموثوقة للمجالات الصغيرة إلى حدٍ كبير في جميع أنحاء العالم. وهذا يرجع إلى إستخدامها المتزايد في صياغة السياسات والبرامج وتخصيص الأموال الحكومية والتخطيط الإقليمي. تقدير المنطقة الصغيرة هو مجال بحث في الإحصاءات الرسمية والإحصاءات المسحية ذات أهمية عملية كبيرة للمعاهد الإحصائية الوطنية والمنظمات ذات الصلة. على الرغم من التطورات السريعة في المنهجية والبرمجيات، وسوف يستفيد الباحثون والمستخدمون من وجود إرشادات عملية تساعد في عملية تقدير المجالات الصغيرة. تقدير المناطق الصغيرة كان ولا يزال في الغالب مجالًاً خصبًا جدًا للبحث الأكاديمي في الإحصاءات الرسمية مع مساهمات نظرية وتطبيقية مهمة. في العقد الماضي وبشكل متزايد تم الإعتراف والإدراك لدى العديد من المعاهد الإحصائية الوطنية والمنظمات الأخرى في جميع أنحاء العالم بأهمية إنتاج إحصاءات المجالات الصغيرة. ومن الأمثلة على ذلك، مكتب الإحصاء الأمريكي، والبنك الدولي، ومكتب المملكة المتحدة للإحصاءات الوطنية، والمكتب الإحصائي لإيطاليا، وغيرها. هذا الإهتمام ساهم في تكوين مجموعات بحثية في علم تقدير المناطق الصغيرة من خلال تطوير منهجيات وأدوات حسابية جديدة متاحة للإستخدام العام.
Description: Within its recently initiated Webinar Series on Statistical Experience Sharing, SESRIC will organise a webinar on ‘Measurement Methods for SDG 11 and the New Urban Agenda in the OIC Countries’ 31 May 2021 in collaboration with the United Nations Human Settlements Programme (UN-HABITAT) and United Nations Economic and Social Commission for Western Asia (UN-ESCWA) with the participation of official statisticians working in National Statistical Offices (NSOs) of the OIC countries. The main objective of the Webinar is to introduce to the participants the SDG 11 (Making Cities and Human Settlements Inclusive, Safe, Resilient and Sustainable) and the New Urban Agenda (NUA) monitoring frameworks, their measurement approaches as well as tools to aid in the computation of the relevant indicators. The Webinar aims to achieve the following related to SDG 11 indicators: Introduce the SDG 11 and the NUA targets, indicators and monitoring framework; Share experiences in urban reporting and dissemination of urban indicators; Introduce the Global Urban Monitoring framework, the urban observatory model and the National Sample of Cities concept as useful tools for the urban agenda monitoring; and Discuss challenges on urban monitoring at national and local levels in the OIC countries. During the Webinar, SESRIC will brief the participants on the outcomes of the questionnaire on the human settlements / population indicators to monitor and report on SDG 11. The Webinar will be conducted through a video conferencing platform by following synchronous learning and instruction approaches designed in line with the virtual training solutions undertaken by SESRIC in order to better serve the Centre’s training activities and keep participants motivated and engaged during this time of global crisis due to COVID-19. Webinar Documents: Concept Note and Agenda (English) (Arabic) (French) Questionnaire on Human Settlements / Population Indicators to Monitor and Report on SDG 11 (English) (Arabic) (French)
Description: تُستخدم المسوحات بالعينات التي ترعاها الحكومات والتي تجريها المعاهد الإحصائية على نطاق واسع لإنتاج تقديرات للمجاميع والمعدلات والنسب على المستوى الكلي في المجتمعات المنتهية الحقيقية. في السنوات الأخيرة أصبح الاهتمام منصباً على توفير تقديرات أو مؤشرات على مستوى أكثر تفصيلاً، أي للمجموعات الجزيئة من المجتمع الكلي، والتي لم يكن مخططاً لها في تصميم المسح الأصلي، دون تكبد تكاليف إضافية بسبب زيادة حجم عينة المسح، والذي هو هدف تقدير المناطق أو المجالات أو المساحات الصغيرة. على سبيل المثال معدلات البطالة للمجموعات السكانية الجغرافية الإجتماعية الديموغرافية. في الأدبيات، يعبر عادة على التقسيمات الفرعية التي من أجلها تكون البيانات الإحصائية (أو التقديرات) مطلوبة بالمناطق أو المجالات، بغض النظر عما إذا كانت بالفعل تتوافق مع مناطق جغرافية أو مجموعات فرعية إجتماعية إقتصادية، أو تقاطعات لكليهما. وتهدف الورشة الى : * التعريف باشكاليلت تقدير المناطق الصغيرة * التعرف على التقديرات المباشرة - تقدير المناطق المعتمدة على تصميم المسح * التعرف على التقديرات غير المباشر - التقديرات المركبة
Description: The second meeting of the UN-CEAG will discuss progress in the implementation of the work programme. This meeting is the second one since the adoption of UN-CEAG Programme of work (2020-2023). Its objective is to: discuss progress in the implementation of the work programme; provide comments and direction on the activities and outputs of the various task teams and agree on the proposed consultations mechanisms and timelines; learn more about initiatives relevant to UN-CEAG’s mandate in other UN groups and agree on coordination mechanisms as necessary; discuss next UN-CEAG meetings. More information: Concept note Presentations
