The leading source of labour statistics

Statistical Methodology Series 10 – Identification of ICSE-18 through labour force surveys

This report illustrates Key findings and implications for questionnaire design obtained from the pilot studies carried out by the ILO in Uganda and Peru in relation to the identification of status in employment based on the International Classification of Status in Employment (ICSE-18). Working relationships are inextricably linked to – and have direct implications for – the identification and measurement of informality. Thus, ensuring both are measured well is key to improving our understanding of informality.

Statistical Methodology Series 9 – Engendering informality project

The report provides an overview of the labour force survey pilot studies carried out by the ILO Department of Statistics in Uganda and Peru under the Engendering Informality Statistics project funded by the Bill & Melinda Gates Foundation. The main activity of the project was to test statistical concepts and measurement approaches in household survey questionnaires to generate evidence on what works when collecting data with a gender lens.

Own-use provision of services: Measurement guide

This guide provides guidance on implementing the ILO add-on module for own-use provision of services (OPS) in national labour force surveys. It is aimed at low- and middle-income countries and is designed to support NSOs to produce statistics on OPS when resource constraints or other considerations impede an independent time-use survey.

LFS questionnaire viewer

This viewer allows users to take a close look at questions in the ILO model LFS questionnaires for PAPI.

New ILO database updates work-related indicators to meet latest standards

The framework on work statistics has been widely publicized over the years, particularly to data producers and policymakers, as it was designed to improve labour market and gender analysis. But little has been said to data users interested in international comparisons. Until now. Here is the ILOSTAT solution to handling the impacts of revised definitions occurring on different schedules across the globe.

What to know when comparing data on women and men’s work

How many men and women were employed last week? How many hours did they work in their main jobs? And how many hours did they work in unpaid activities such as caring for children? These are seemingly straightforward questions but measuring paid and unpaid work through household surveys is anything but straightforward. This holds true especially for women in developing countries, who are more often engaged in informal activities such as microenterprises or small-scale farming — activities that can fall through the cracks of traditional surveys.

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