SDG Indicators 2.3.1 and 2.3.2 – Labour productivity and income of small-scale food producers

Course

Self-paced e-learning

UN Partner

Food and Agriculture Organization of the United Nations

Effort: 2 hours
Level: Intermediate
Language: English; French; Spanish
Venue: Online
Certificate: Yes
Price: Free

This course presents tools, methods and processes to monitor and report on Indicators 2.3.1 and 2.3.2 within Goal 2 of the 2030 Sustainable Development Agenda.

Sustainable Development Goals: 2030 Agenda; No poverty; Zero hunger
Statistics: Labour; Methodology and statistical processes; Living conditions, poverty and inequality
Subject: Small-scale food producers
Keywords: 2030 Agenda; income; production; methodology; data collection

About this course

This course has been developed to support countries in computing and monitoring Indicators 2.3.1 and 2.3.2 of the 2030 Sustainable Development Goals (Labour productivity and income of small-scale food producers), and to facilitate the understanding of the main concepts underpinning the methodology.

The course consists of five lessons, ranging from approximately 15 to 30 minutes duration each:

Lesson 1 – Introduction to the SDG Indicators 2.3.1 and 2.3.2
Lesson 2 – Identifying small-scale food producers
Lesson 3 – Computing Indicators 2.3.1 and 2.3.2
Lesson 4 – Collecting data
Lesson 5 – Applying all content

Watch this video to find out more: https://youtu.be/Jaw9Ke7RJOY

Download syllabus

Target audience

This course is primarily intended for professionals who play a role in the data collection, analysis and reporting on SDG Indicators 2.3.1 and 2.3.2. This includes:

Policy-makers or advisors
Statisticians
Representatives of NGOs, regional organizations, academia/researchers and the donor community.

Learning objectives

You will learn about:

Nature and importance of the role of small-scale food producers;
Rationale of Indicators 2.3.1 and 2.3.2 within the 2030 Agenda;
Main tools to measure the Indicators 2.3.1 and 2.3.2;
Methodology to perform data collection, identification of the national target population and computation of the indicators;
The types of data required for the computation of Indicators 2.3.1 and 2.3.2 and critical data gaps to be addressed.