Cross-Sectional and Longitudinal Weights in the Annual Survey of Hours and Earnings (ASHE)

Recording available here.

Join the Wage and Employment Dynamics team for an overview of new alternative weights developed for the Annual Survey of Hours and Earnings (ASHE).

About this event

The Wage and Employment Dynamics project, funded by ADR UK, is linking data from various official surveys and administrative datasets, with the objective of providing new insights into the dynamics of earnings and employment in the UK. At the heart of this work is the Office for National Statistics’ Annual Survey of Hours and Earnings (ASHE), which forms a critical source of information on the earnings of employees in the UK.

In this webinar, the WED team will explain two new sets of alternative weights developed for the ASHE.

The first is an alternative set of cross-sectional weights. Weights are provided with the existing ASHE dataset, enabling it to be representative of employees by gender, age, occupation and region. However, while the ASHE is based on a sample of employee jobs, the survey is completed by employers. We explore the characteristics of employers responding to ASHE, and find that certain types of organisations are over or under-represented in the achieved sample. We develop an adjusted set of cross-sectional weights that reduce these biases.

The second is a set of longitudinal weights for users wishing to analyse the ASHE data across adjacent years. Records within ASHE are linkable longitudinally, and it is often assumed that the panel sample is free of any attrition biases. We explore the validity of this assumption by comparing rates of year-on-year sample retention in ASHE with rates of employment retention estimated from a reference dataset (the Longitudinal Annual Population Survey). We find systematic patterns of longitudinal attrition in ASHE, which have the potential to introduce bias into longitudinal analyses of these data. In response, we construct longitudinal weights that correct for estimated attrition biases over adjacent years in ASHE.

The webinar will consist of two 15-minute presentations, focusing on the cross-sectional and longitudinal weights respectively, followed by 15 minutes for questions and discussion.

The webinar is likely to be of interest to both existing and new users of the ASHE data.


Adding Employee Characteristics to the Annual Survey of Hours and Earnings (ASHE) using the 2011 Census

Join the Wage and Employment Dynamics team for an introduction to a new dataset that expands the set of personal characteristics observed for employees in the Annual Survey of Hours and Earnings (ASHE) via record linkage with the 2011 Census for England and Wales.

About this event

The Wage and Employment Dynamics project, funded by ADR UK, is linking data from various official surveys and administrative datasets, with the objective of providing new insights into the dynamics of earnings and employment in the UK. At the heart of this work is the Office for National Statistics’ Annual Survey of Hours and Earnings (ASHE), which forms a critical source of information on the earnings of employees in the UK.

In this webinar, the WED team will explain the results of work to link individual records in ASHE with individual records in the 2011 Census for England and Wales. Where a link has been established, it has been possible for ASHE to incorporate employee-level data from the 2011 Census on a range of personal characteristics, including the employee’s educational qualifications, country of birth, ethnicity, religion, and disability status. These Census data items are available for the matched individual in any year that they appear in ASHE. The linked dataset is being made available to researchers via the ONS Secure Research Service and provides opportunities for new research on issues such as the returns to education and wage inequality.

The webinar will provide researchers with an overview of the linkage process and linkage outcomes. It will also describe the weights that have been constructed to account for linkage biases, and explain how potential users can gain access to the linked data.

The webinar will consist of one 25-minute presentation, followed by 20 minutes for questions and discussion.

The webinar is likely to be of interest to both existing and new users of the ASHE data.

The session will be led by WED research team members:

  • John Forth, Senior Lecturer in Human Resource Management, Bayes Business School
  • Van Phan, Research Associate, University of the West of England

When: Tuesday 21 June 2022

Time: 13:00 – 13:45

Where: Online event

Cost: Free

Recording available here.