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PhD Studentship: Understanding the Local and Regional Impacts of Immigration on Local Educational and Labour Market Trajectories

University of Sheffield

Qualification Type: PhD
Location: Sheffield
Funding for: UK Students
Funding amount: £16,062
Hours: Full Time, Part Time
Placed On: 16th March 2023
Closes: 10th April 2023
Reference: SH76
 

Project Partner: UK Home Office, Managed Migration Research (MMR) team 

Primary Supervisor: Gwilym Pryce (g.pryce@sheffield.ac.uk; webpage: here

Academic Supervisors: Aneta Piekut, Gurleen Popli

Research Themes: Geography and Spatial Analysis, Economics, Social Inequality 

Project description:

Immigration remains one of the most pressing political issues of our time. Estimates at the national level suggest that immigration has no material impact on employment, but it’s possible that the effects vary considerably within and between regions. Theoretically, migrants can potentially increase local employment by boosting aggregate demand and helping local firms become more competitive. However, estimates of these effects at the local level are virtually non-existent, particularly with respect to the individual-level impacts on the educational and labour market prospects of (both UK-born and foreign-born) locals. This project offers an outstanding opportunity to address some of these important gaps in the UK evidence base using cutting-edge methods and data. Working in partnership with the Managed Migration Research (MMR) team at the Home Office, the PhD student will utilise the exceptional Longitudinal Education Outcomes (LEO) dataset to follow the life trajectories of several million individuals in England and Wales. The large sample sizes and fine-grained spatial resolution afforded by LEO will facilitate investigation of the local impacts of migrant inflows into the locality over the preceding decade on individual-level outcomes of residents, and provide new insights into how the impacts of immigration vary geographically in the UK.  

The PhD student will be part of an active and multicultural cohort of PhD students based in the Department of Economics working on topics related to economic geography, the spatial distribution of economic activities and local labour markets. The student will also be part of the Sheffield Urban, International Trade and Environmental Economics (SUITE) research group and benefit from access to the doctoral training in economics programme, PhD reading groups,  and the annual departmental PhD conference (visit www.sheffield.ac.uk/economics/postgraduate/phd for more information). . 

This project would be well suited to a student with a background in economics, regional studies, or economic geography. Solid data analysis skills and a strong interest in economic geography and the economics of immigration would be an advantage.

Entry requirements

Qualification

  • 2:1 honours degree, or equivalent, in a relevant subject area

English language requirements (for international/EU candidates)

You have must have one or more of the following:

  • IELTS (International English Language Testing System) – 7 overall, 7 writing, 6 other sections
  • TOEFL (Test of English as a Foreign Language) Internet based test – 100 overall, 25 writing, 22 other sections
  • A degree in any subject completed in the English language from a majority English speaking country may also be acceptable – please check here www.leeds.ac.uk/admissions-qualifications for the country where you completed your degree.

Funding

A standard studentship covers the cost of tuition fees, provides a doctoral stipend of £16,062, ( 2022 rate- to increase slightly each year with inflation), and a Research Training Support Grant, for four years. Applications will be open to both Home and International fee rated applicants.

Study mode

Options to study part-time are available, if you wish to study part-time please indicate this when you apply. If selected for interview, the project supervisor will discuss options with you.

This studentship is part of the Data Analytics and Society CDT. Applications should be made through the University of Leeds portal. More information is available here.

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