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.
Generating high quality statistics relies on eliminating gender bias at all stages of the production process. This blog looks at how gender bias occurs in statistics and what the ILO is doing to support efforts to minimize it.
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.
Losing the ability to collect data may not be one of the more obvious negative effects of the COVID-19 pandemic. However, nearly all countries in the world found it difficult to gather data precisely when demand was highest. A recent global survey by the ILO has highlighted just how great the impact was on the production of labour statistics and how countries responded to meet user needs for data.
The data is abundantly clear on one point: the COVID-19 pandemic has had a disproportionately negative impact on women. Because more women work in the tourism, retail, and informal sectors, which have been hardest hit by the pandemic, their livelihoods have been upended. Understanding the extent of this impact is the first step in reversing course. Yet the pandemic has also exposed and exacerbated data gaps that undermine our ability to act intentionally and craft effective policy responses.
Containing more than 100 million data points, the ILOSTAT portal is truly a gold mine for seasoned data scientists, but it can be challenging to use for those with less experience. Here we explain five typical rookie mistakes so you can avoid them.
The pandemic is radically impacting our lives. But what about the statistics used to assess those impacts? Without timely and accurate information, we will not act through adequate and informed policies. Though numbers should focus on the health of the population, we also need to understand what is happening in the domain of labour statistics. That is, how is COVID-19 affecting our working lives? What is less obvious, however, is that the pandemic is also affecting our ability to compile such statistics.
The quality of our job determines to a great extent our well-being and life quality, but measuring it requires taking into account numerous aspects of our working conditions.
Work and employment may be used indistinctly in everyday language, but for the labour market they mean very different things. Employment is a very specific form of work. Other forms of work include own-use production work, volunteer work and unpaid trainee work.
