Asset ownership from a gender perspectiveAdd to learning list

Course

Self-paced e-learning

UN Partner

United Nations Statistics Division

United Nations Entity for Gender Equality and the Empowerment of Women

Asian Development Bank

World Bank Group

Food and Agriculture Organization of the United Nations

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Length: 5 days
Effort: >3 hours
Level: Intermediate; Advanced
Language: English
Venue: Online
Certificate: Yes
Price: Free

The course translates in an interactive manner key concepts and recommendations from the United Nations Guidelines on Measuring Asset Ownership from a Gender Perspective. It covers the conceptual framework, data sources, implementation guidance and data processing, analysis and dissemination.

Sustainable Development Goals: No poverty; Gender equality; Decent work and economic growth
Statistics: Methodology and statistical processes; Gender and special population groups; Economic statistics
Subject: Gender Statistics
Keywords: gender statistics; methodology; equality; inequality; economic opportunity

About this course

This course is based on the United Nations guidelines on Producing Statistics on Asset Ownership from a Gender Perspective, which has been developed under the Evidence and Data for Gender Equality (EDGE) initiative implemented to improve the integration of gender issues into the regular production of official statistics for better, evidence-based policies. It contributes to the development of gender statistics on asset ownership, which are instrumental in building an evidence-base of the drivers and consequences of gender inequality for informing policy making. For that purpose, data on asset ownership should be collected at the individual level.

The course provides guidance on collecting, processing, analyzing and disseminating individual-level data on asset ownership for the production of gender statistics related to three objectives:

measuring the gender asset gap;
measuring the gender wealth gap; and
understanding the gender dynamics of asset ownership within households.

Target audience

Specialists of national statistical offices who are involved in a data collection project, including specialists in
- gender statistics
- household surveys
- sampling
- national accounts
- agricultural land
- field operations
- data managers
- data analysts

Data users including
- the government
- civil society
- researchers
- the general public

Learning objectives

At the end of this course, participants will gain an improved understanding of:

Conceptual Framework:

The conceptual framework for measuring asset ownership and control from a gender perspective;
Defining asset and asset ownership as a bundle of rights;
The different forms of ownership and modes of asset acquisition;
The recommended respondent rules for data collection;
Defining wealth;
The importance of valuing assets for measuring the gender wealth gap;
The principles for valuing assets and their application;
The different units of observation that can be used to collect data;
The implications of using different units of observations for the calculation of key measures;

Data sources:

Which data sources should be considered when collecting individual level data on asset ownership and control;

Guidance for implementation:

The three recommended data collection strategies;
The principles in sampling and specific issues pertaining to collecting data on asset ownership at the individual level;
The approaches for selecting respondent(s) within households;
The principles for designing a questionnaire to collect data at the individual level on asset ownership and control;
The principles guiding the organization of field work, the training of field staff and the field work itself;

Data processing, analysis and dissemination:

The issues in data processing that are crucial for surveys on asset ownership and control from a gender perspective;
The criteria for national and global indicators to monitor women’s and men’s ownership and control of physical and financial assets at global and national levels;
The purpose of the analysis;
How to organize the data file to facilitate the analysis;
How to calculate key measures; and
How to disseminate results.