Understanding the gender pay gap

We have written before about the gender pay gap in the UK. According to the Office for National Statistics the average hourly (gross, excluding overtime) gender pay gap in the UK for all employees fell from 17.8 per cent in 2018 to 17.3 per cent in 2019.  However, nee research has revealed cross-national gaps vary from as much as -5 per cent in Wigan to 32 per cent in Slough suggesting that only focusing on a national perspective might be overly simplistic.

The Centre for Cities has found that 7 of the 10 cities with the highest gender pay gap are located either in the South East or East of England. They say that “as cities in these regions tend to perform economically better than cities in the North of England, economic performance seems to influence the gender pay gap in cities. In general, cities with higher average weekly earnings (e.g. Cambridge, London, Reading, Crawley, Slough) tend to have a higher gender pay gap.”

Another factor the Centre for Cities things is driving higher gender pay gaps in the south of England is the bigger difference between men and women holding a managerial position. While 5.2 of men and 3.2 per cent of women in the north east hold such a position, 8.1 per cent of managers in the south east are men while only 4.4 per cent are women (data is not available below regional level).”

Six out of the ten cities with the smallest gender pay gap are located in the North of England: Wigan, Burnley, Warrington, Sunderland, Blackburn and Middlesbrough. These cities have weaker economies and lower rates of employment

The Centre for Cities has looked at the industrial composition of the labour market in Warrington and Wigan, finding that both cities have a higher share of jobs in education, human and health activities and social work than cities with higher gender pay gaps such as Slough and Crawley.

The composition of sectors in and around cities is seen as important and since women are more likely to be employed in the public sector, for instance, as teachers, social workers and nurses, the gender pay gap tends to be lower in cities with a higher proportion of public sector jobs such as in Middlesbrough, Blackburn, Swansea and Glasgow.

The future of Digital Skills

There is currently a great deal of debate over what digital skills are needed for future jobs.

A new report written by Erika Kispeter about the current and future demand for digital skills at work has just been published by the Department for Digital, Culture, Media and Sport (DCMS) – “What digital skills do workers need to succeed in the workforce in the next ten years”.

Although much of the relevant literature discusses ‘digital skills’, this term is used as a shorthand to mean, among others skills, knowledge, behaviours, attitudes, competencies, capabilities, and character traits. Current frameworks for digital skills include a handful of key areas of skills and competencies, namely Information and data literacy, Digital communication and collaboration, Digital content creation, Digital safety, Digital identity and Awareness of digital rights at different levels of proficiency. Digital skills also include non-technical, so called ‘21st century skills’, which can be grouped under a cognitive, intrapersonal and interpersonal domain.

While there is a trend to create comprehensive frameworks for digital skills, these attempts to give a general definition of ‘digital skills’ has been criticised. There is a call for more context-specific definitions.

The review has found that it is difficult to establish the boundary between essential and more specialised digital skills for the general workforce and identify a list of digital skills beyond the essential level. Descriptions of digital competence as a ‘T-shaped skill set’, in which individuals possess in depth knowledge in one area and good knowledge across many other areas may be useful here.

The future demand for general digital skills points at 21st century skills, especially interpersonal skills and cognitive competencies and learning strategies. It is argued that occupations where workers use digital skills creatively and to solve problems are likely to grow, while occupation where digital skills are used for routine tasks are likely to decline.

The drivers of change are suggested to be the effect of automation on future occupations, but there is much debate as to whether jobs will be fully automated or whether there will be a major change in task composition.

the report can be downloaded from the UK Government publications website.

Skills for Green Jobs


Addressing climate change and setting economies and societies more firmly onto a path towards a sustainable, low-carbon future is one of the defining challenges of our time. Such shift will entail far-reaching transformations of our economies, changing the ways we consume and produce, shifting energy sources, and leveraging new technologies.

The European Centre for Vocational Education and Training, Cedefop, has released a new report on Skills for Green Jobs. The report is based on country studies undertaken in collaboration with the International Labour Organization (ILO) in six countries (Denmark, Germany, Estonia, Spain, France and the UK) since 2010.

A key outcome, says CEDEFOP, is that countries vary in their approach to defining, classifying and collecting data on green jobs and skills. However, they have observed increased efforts are observed on data collection on developments in the ‘green economy’.

Since 2010, green employment trends have tended to parallel general economic trends. Carbon reduction targets and associated incentives and subsidies have been especially influential on green jobs and skills; other green policies, such as legislation to protect the environment, have also been important.

Although few countries have a strategy on skills for green jobs, “the updating of qualifications and VET programmes has soared, reflecting increased demand for green jobs and skills since 2010.” Updates mainly concern adding ‘green’ components to existing qualifications/programmes, since changes in skill demands are perceived more pertinent to including new green skills within existing occupations rather than the creation of new green ones.

 

More information is available in the CEDEFOP magazine promoting learning for work, Skillset and Match.

Making sense and meanings from Labour Market Data

The increasing power of processors and the advent of Open Data provides us information in many areas of society including about the Labour Market. Labour Market data has many uses, including for research in understandings society, for economic and social planning and for helping young people and older people in planning and managing their occupation and career.

Yet data on its own is not enough. We have to make sense and meanings from the data and that is often not simple. Gender pay gap figures released by the UK Office of National Statistics last week reveal widespread inequality across British businesses as every industry continues to pay men more on average than women. This video by Guardian newspaper journalist Leah Green looks at the figures and busts some of the common myths surrounding the gender pay gap.

Find out about jobs and automation from the ONS chatbot

According to the Office for National Statistics, around 1.5 million jobs in England are at high risk of some of their duties and tasks being automated in the future.

The ONS analysed the jobs of 20 million people in England in 2017, and has found that 7.4% are at high risk of automation.

Automation involves replacing tasks currently done by workers with technology, which could include computer programs, algorithms, or even robots.

Women, young people, and those who work part-time are most likely to work in roles that are at high risk of automation.

It is important to understand automation as it may have an impact on the labour market, economy and society and on the skills and qualifications young people will need in the future.

The ONS have developed a chatbot for people to find out more about automation. You can try it out below and you can download the data here.