About the research
Valeria was a BSc(Hons) student in Economics at the University of Manchester.
Valeria’s project examined the link between immigration and productivity in the UK. She aimed to understand how productivity was affected in industries more and less exposed to European Union (EU) migration.
Data
Valeria used data from the Quarterly Labour Force Survey (2000-2016) to compute employment figures for the period 2000-2016 at the industry grouping level, looking at the share of EU born and non-EU born migrants. Alongside this, she used the industry grouping level quarterly Multi-Factor Productivity (MFP) estimates published by the Office for National Statistics.
“As I wanted to cover employment and migration in the UK, which are variables that affect society as a whole, I needed access to a national-level Survey that gathered time-series employment data from a representative sample of UK’s households.”
Methodology
Valeria investigated her research questions by using the enlargement of the EU in 2004 as a natural experiment to perform a Difference-in-Differences research design. This is a quasi-experimental design that makes use of differences between groups to estimate a causal effect. Using this method, she was able to exploit differences in the exposure to EU migration across the UK industry groupings before and after the 2004 EU enlargement. This allowed her to examine the effect differences in levels of migration had on these industries’ MFP.
Findings
The main findings from Valeria’s project were that:
An increase in the share of EU-born people in more migrant dependent industries causes an increase in the multifactor productivity – showing that EU immigration into specific industries after 2004 had a positive impact on UK productivity.
Valeria’s findings also had implications for UK immigration policy, especially in the context of new immigration rules, including the point based system. Her findings suggest that those industries which rely heavily on free movement labour may face new pressures if it is ended.
Top Tips
Valeria’s top tips for students about to start a project or dissertation with secondary data are:
- Take the time to explore the source of your data, take advantage of all the resources available e.g. take time to read the information on the variables to find ones that may be useful or relevant to your research
- Take time to understand how the survey was collected and what the implications of this are when it comes to interpreting your results. This information is usually provided in a User Guide (as part of the data documentation) and also in the online data exploration system (Nesstar).
“I would encourage more students to use secondary data from the UK Data Service for the purposes of their research. The statistics provided by secondary data allows for the study of so many different subjects. When writing an original piece of research, you use your own approach to exploit the available data and that can be very enriching for the academic community and society as a whole.”
Skills gained
Valeria listed some of the skills she has gained from completing a quantitative dissertation using secondary data:
- made her highly capable of preparing and analysing quantitative data, interpreting results and presenting them.
- allowed her to further her effective oral and written communication skills , allowing her to feel capable of presenting technical analysis and concepts to different audiences.
- helped her develop a degree of expertise with the software packages R and Stata
Future plans
Valeria planned to use her skills to go on to study an MSc in Finance.