ADR UK Research Fellows: Annual Survey of Hours and Earnings linked to Census 2011

This project aims to answer the following research questions:  

1. To what extent does the disability pay gap vary across different parts of England and what are the underlying drivers of spatial disparities? 
2. How do other important socio-demographic characteristics (e.g. race and gender) intersect with disability with regard to differences in pay? 
3. What are the underlying drivers of the disability pay gap in England? 
4. Can the ASHE-Census 2011 dataset be used to explore factors relating to disability in years other than 2011?  

The methodology used in this study:  

• This project is using the ASHE-Census 2011 to investigate how the disability pay gap varies around the country, for example in the south west versus north east of England.
• The project will also compare the disability pay gap between men and women to see if the disability pay gap is bigger for men or women. Similarly, the data will be used to look at ethnic disability pay gaps, to see whether the disability pay gap is bigger for disabled people from minority ethnic groups. 
• Another part of the project will explore the factors that contribute to the disability pay gap and show the extent to which it can be explained by other factors. These other factors could include differences in the industry that disabled and non-disabled people work in, or differences in the average age between disabled and non-disabled people. This will allow identification how much of the disability pay gap cannot be explained by other factors and is due to labour market discrimination. 

Funded value: £174,384 

Duration: June 2024 – November 2025

This project aims to answer the following research questions:  

1. How does hiring discrimination influence the skills UK workers have? 
2. How does hiring discrimination impact outcomes for workers (e.g. in terms of their earnings)? 
3. How does hiring discrimination affect the productivity of industries and the UK economy as a whole? 

The methodology used in this study:

• This project uses a model where people move through the UK economy, searching for, applying, and moving to new jobs. These people have different ethnicities and genders and possess different skills. Over time, as they move from job to job, they will become more adept in the skills they use more (or need to be better at in their current job) and less adept in those skills they use less.   
• Within the model, people consider job prospects, factoring in things like wages, the industry the job is in, and how far away the new job is. When many people apply for the same job, the best candidate will be hired – judged based on who has the best combination of the most suitable skills, comes from the most similar industry, and is geographically closest. The movements of these workers create patterns of job-to-job movement between and within different industries, occupations, and regions within the UK.
• We can introduce hiring discrimination to the model, by adding people’s personal characteristics (like gender and ethnicity) as factors that influence hiring teams’ decisions, therefore creating long-term repercussions for all the candidates (e.g. because they miss an opportunity to earn more or develop new skills) and affecting their future job prospects.
• Using this model, we will explore different scenarios – with and without different levels or types of hiring discrimination - to better understand how hiring discrimination impacts individuals, industries, and the UK economy. 

Funded value: £163,523 

Duration: September 2024 – March 2026 

This project aims to answer the following research questions:  

1. Do differences in local economic opportunities affect workers in the same way? 
2. Does changing jobs frequently increase the wage growth of both workers with more formal education and those with less?  
3. Does the local area where workers start their first job matter for their future careers and wage growth? 
4. Do differences in firm productivity across local areas matter for workers with more formal education and workers with less? 

The methodology used in this study:  

• The project will estimate how much individual wage growth is due to the worker changing jobs and how this varies by city size. Event-study analysis - a research method that looks at the effects of specific events over time - will be used to compare the wage growth of comparable workers with the same education level employed in different local areas. 
• The analysis will use firm closures to estimate the effect of city size on workers’ re-employment probability and wage growth. This method allows one to isolate the role of city size from other confounding factors, such as individual characteristics, that affect a worker’s decision to change jobs and firms. 
• Third, the project will focus on the type of firms that are located in big versus small labour markets and analyse how the distribution of firms in the local area impacts workers’ wage growth.

Funded value: £146,941

Duration: October 2024 – March 2026 

This project aims to explore the following research questions:

1. How do labour market outcomes including pay, hours of work, occupational skill level and type of employment contract differ between UK-born and immigrant (non-UK-born) employees? ​
2. What are the main drivers of any differences in labour market outcomes; and what is the influence of other personal and work-related characteristics, or the role played by individual employers?​
3. Does the labour market performance of immigrants vary by factors related to immigration and integration (language proficiency, years of residence in the UK, year of arrival, holding a UK passport or self-defined national identity)?​
4. How do labour market outcomes of immigrant employees progress over time; and how do the labour market dynamics of immigrants compare to those born in the UK?

The methodology used in this study: 

This research will use established econometric methods with three core elements. 

• First, regression analysis will be used to explore the labour market performance of immigrant workers in each labour market outcome, in comparison to that of UK-born workers. This will be followed by a more detailed analysis of the drivers of any observed differences using an established decomposition method. This method isolates the contribution of observable characteristics and the role of individual employers from unobserved influences, where the latter will include unequal treatment in the labour market. 
• Second, the analysis will focus on the role of factors related to immigration and integration, and regression analysis will be used to explore whether and how these factors determine the labour market performance of non-UK-born workers. 
• Third, a dynamic analysis will be undertaken to explore how the labour market performance of immigrant workers progresses over time in terms of considered outcomes, in comparison to UK-born workers. This part of the analysis will exploit the longitudinal nature of the data which allows us to follow the same individuals over time. 

Throughout the analysis, differences between people will be explored, specifically to determine whether the findings vary based on gender and country of origin.

Funded value: £158,441 (full economic cost)

Duration: August 2023 – February 2025 

Publications

• Blog: Migration research: What can we learn from linked administrative data? November 2023

• Blog: Labour market performance of immigrants: New evidence from linked administrative data. April 2024

• Discussion paper: Labour Market Performance of Immigrants: New Evidence from Linked Administrative Data, April 2024

• Data Insight: Labour market differences between immigrant and UK-born employees: What is the role of employers? July 2024
• Data Explained: Exploring the nexus between immigration, integration and labour market outcomes, November 2024
• Policy briefing: Immigration, integration and labour market outcomes, March 2025
• Journal publication: Differences in labour market outcomes between immigrant and UK‐born employees: evidence from linked data, The Scandinavian Journal of Economics - July 2025

This project aims to explore the following research questions:

1. What constitutes a green job and how should it be measured in different contexts?
2. What is the extent of green jobs growth in England and Wales and how have economic conditions and environmental policies affected this?
3. What are the characteristics of those working in green jobs in England and Wales, and do they vary by type of green job?
4. Is there a pay premium or pay penalty for working in a green job in England and Wales, and does this outcome differ across demographic groups, such as gender, ethnic group, disability, and across regions?
5. How do the early labour market experiences of green job employment affect an individual's subsequent labour market experience and wage progression?

The methodology used in this study: 

• By combining the high-quality employment data in the Annual Survey of Hours and Earnings (ASHE) with the detailed demographic information in the 2011 Census, the project will use advanced mathematical and statistical modelling techniques (e.g., panel data estimation) to describe and analyse the characteristics and relationship of green jobs in England and Wales, and those that work in them. 
• The ASHE survey collects data on the wages and employment of the same individual each year. This enables the characteristics of jobs undertaken to be explored and the career progression of individuals to be tracked over time. Using the industrial and occupational variables it is possible to construct alternative, but meaningful measures of green jobs. While the linked 2011 Census data will enable the results to be analysed by cohorts, including those with protected characteristics (e.g., disability, race, religion). 

Funded value: £141,986 (full economic cost)

Duration: September 2023 – February 2024

Publications

• Blog: Green jobs in England and Wales, November 2023
• Data Insight: Working towards an environmentally sustainable and equitable future? New evidence on green jobs, April 2025
• Data Explained: Annual Survey of Hours and Earnings Linked to Census 2011 and O*NET Data, May 2025