Technical Network on Poverty Analysis (THINK-PA)

20/9

2022

Virtual Event, 20/09/2022

The promotion of technology adoption can have unexpected social equity implications. Bouwman, Andersson, and Giller of Wageningen University will present the results of a study on the impact of herbicide adoption on casual labour relations (ganyu) in Central Malawi. 

19/7

2022

Virtual Event, 19/07/2022

Anna Fabry of KU Leuven will present results from agro-industrial companies and small-scale farms in the horticultural sector of Senegal.

28/6

2022

Virtual Event, 28/06/2022

Professor Alix-Garcia will present investigations into the use of key informants as an alternative targeting method. The research finds asset and poverty indices calculated from key informants to be highly correlated with those based on data collected from households. 

24/5

2022

Virtual Event, 24/05/2022

In this meeting, Yeshwas Bogale (Economist, ESA) and Sophie Scharlin-Pettee (Research and Policy Manager, OPHI). He will present two recent studies to show how the Multidimensional Poverty Index can be adapted to measure poverty and guide interventions in emergency and fragile contexts, with a particular focus on intra-household inequalities

16/2

2022

Virtual Event, 16/02/2022

Understanding what causes poverty is key to eradicating it. Poverty traps have often been indicated as a fundamental reason why many people remain poor. The idea behind poverty traps is that poor people keep engaging in low-earning occupations, not because they lack innate ability, but simply because they lack better opportunities.

15/2

2022

Virtual Event, 15/02/2022

In this webinar, Clarie Duquennois will present a method to construct labour calendars for rural areas and for specific crops. Using national household survey data from Malawi, she will show how total unemployment in rural areas can be decomposed between high-season unemployment and seasonal unemployment. 

8/12

2021

Virtual Event, 08/12/2021

The ability to precisely identify who the poor are is key to increasing the effectiveness of targeted rural poverty reduction interventions. Traditionally, the poor are identified based on their income or consumption expenditures. 

2/12

2021

Virtual Event, 02/12/2021

Improving the effectiveness, efficiency and monitoring of rural poverty reduction interventions requires measuring poverty for rural areas at subnational level and for specific populations subgroups such as those engaged in primary activities. 

17/11

2021

Virtual Event, 17/11/2021

Natural disasters prevent people from moving out of poverty and pull back into poverty people who were able to escape it. They are a particularly important determinant of poverty in rural areas of developing countries, where livelihoods are strongly dependent on natural resources and climatic conditions. 

26/10

2021

Virtual Event, 26/10/2021

Launch event of this new publication, where we will provide an overview of the guide, exploring possible applications indifferent areas and discussing how to integrate this into FAO’s work so that no one is left behind. 

16/9

2021

Virtual Event, 16/09/2021

Reducing rural poverty is a key objective of FAO. To achieve this goal, the Organization must reach the poor and the extremely poor in rural areas, analysing their needs and aspirations and providing effective guidance for the design of policies and investments that foster inclusive and sustainable development.

8/9

2021

Virtual Event, 08/09/2021

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28/6

2021

Virtual Event, 28/06/2021

In this webinar, Luna Yue Huang will show how the impact of anti-poverty programmes can be measured using only satellite images and deep learning techniques. She will present evidence from a recent poverty reduction programme in rural Kenya, comparing the performance of this new method against traditional impact evaluations based on household surveys.

17/6

2021

Virtual Event, 17/06/2021

In this webinar, R. Andrés Castañeda Aguilar explains how the World Bank estimates global poverty, highlighting the main methodological challenges of using the current approach for rural areas. Finally, he will discuss potential ways to improve global rural poverty estimates, using an example from Latin America to illustrate their implications.

8/6

2021

Virtual Event, 08/06/2021

In this webinar, the second of a series on the use of artificial intelligence for poverty analysis, Kamwoo Lee will present a new method to map poverty at the village level using machine learning and readily available geospatial data including OpenStreetMap and satellite images. 

18/5

2021

Virtual Event, 18/05/2021

In this webinar, Professor Joshua Blumenstock will present ongoing work that uses recent advances in machine learning, applied to data from satellites and mobile phone networks, to target and deliver cash transfers to individuals and families living in extreme poverty.