Funding

Self-funded

Project code

ECFN5100220

Department

Economics and Finance

Start dates

October, February and April

Application deadline

Applications accepted all year round

This project is now closed. The details below are for information purposes only. View our current projects here.

Applications are invited for a self-funded, 3-year full-time or 6-year part-time PhD project to commence in October or February.

The PhD project will be based in the Faculty of Business and Law, and will be supervised by Dr Ali Sina Onder, Dr Sercan Ozcan and Professor Lester Hunt. 

This project aims to investigate the linkage between research funds and scientific outputs. To provide specific recommendations for funding policies and strategies, this study will focus on the UK. To gain a better understanding of how research funding affects research output in a broad set of emerging fields and hence to increase the efficiency of funding, this project proposes to investigate causal linkages between funding related variables (i.e. size, type and frequency of funds) and output related variables (i.e. number, quality and dissemination of outputs). 

The work on this project could involve:

  • analysing the causal relationship between research funding and (a) the quality of output, (b) patterns of collaboration between co-authors or co-inventors and (c) diffusion and pervasiveness of research
  • investigating the extent, efficiency and cost-effectiveness of inter-disciplinary research funding by analysing causal links between researchers’ academic background, impact of their research and the level of funding
  • documenting research funding profile and characteristics in the UK and developing a funding policy to increase the efficiency of the funding mechanisms in the UK.

Economics of science and innovation is an emerging field at the crossroads of public economics, labour economics and innovation management. Science and innovation drive long term economic growth and development. Persistent success in science and innovation hinges among other things upon the size and availability of public and private research funds to support scientists’ endeavours. The current literature in this field fails to establish a clear causal relationship between research funding and output.

Considering the gap in the literature, proposed study will make use of targeted text-mining techniques to create a large micro-level databases of research funding and output of British institutes, especially in particular emerging sectors. Specific institutional settings of research funding will be used for establishing causality in a rigorous microeconometric analysis. 

References:

Jacob, B.A., Lefgren, L. 2011. The impact of research grant funding on scientific productivity. Journal of Public Economics, 95(9-10): 1168-1177.

Li, D., Agha, L. 2015. Big names or big ideas: Do peer-review panels select the best science proposals? Science, 348: 434-438.

Stavropoulou, C., Somai, M., Ioannidis, J.P.A. 2019. Most UK Scientists who Publish Extremely Highly-cited Papers do not Secure Funding from Major Public and Charity Funders: a Descriptive Analysis. Plos One 14(2): e0211460.

Stephan, P. 1996. The economics of science. Journal of Economic Literature, 34(3): 1199–1235.

Fees and funding

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only – eligibility criteria apply).

 

2022/2023 fees (applicable for October 2022, February and April 2023 start) 

PhD and MPhil

UK, Channel Islands and Isle of Man students 

  • Full-time: £4,596 (may be subject to annual increase)
  • Part-time and part-time distance learning: £2,298 (may be subject to annual increase)

EU students
(including Transition Scholarship)

  • Full-time: £4,596 (may be subject to annual increase)
  • Part-time and part-time distance learning: £2,298 (may be subject to annual increase)

International students

  • Full-time: £17,000 per year (may be subject to annual increase)
  • Part-time and part-time distance learning: £8,500 per year (may be subject to annual increase)

All fees are subject to annual increase. If you are an EU student starting a programme in 2022/23 please visit this page.

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

We welcome applications from highly motivated prospective students with a background in economics, econometrics, information management, or computer science and other relevant disciplines with an interest in the proposed research. Familiarity with data science and bibliometric methods is desirable (not essential). We encourage prospective students to design their own research strategies depending on their interest and core skills.

How to apply

We’d encourage you to contact Dr Ali Sina Onder (ali.onder@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process. 

Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.

If you want to be considered for this self-funded PhD opportunity you must quote project code ECFN5100220 when applying.

October start

Apply now

February start

Apply now