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King's College London PhD Studentships in Economic Measurement: Economic Statistics Centre of Excellence 2017, UK

Publish Date: Apr 17, 2017

Deadline: Apr 28, 2017

PhD Studentships in Economic Measurement: Economic Statistics Centre of Excellence

We are seeking to recruit two PhD students who are interested in economic statistics and measurement. The students will contribute to King’s College London’s partnership with the ONS funded Economics Statistics Centre of Excellence (ESCoE) www.escoe.ac.uk. ESCoE is a joint initiative between the National Institute of Economic and Social Research who will host the Centre, Cambridge, King’s College London, Nesta, Strathclyde and Warwick Business School.

One studentship will be concerned with output and productivity growth with a focus on services sectors, Project 2.1: Measuring activity in services sectors (see details below). The successful candidates’ main supervisors will be Professor Mary O’Mahony and Dr Augustin de Coulon. The second studentship will be concerned with improving the measurement of GDP at different publication horizons with a focus on nowcasting and reconciling the discrepancies in the different approaches to the measurement of GDP, Project 1.2: Measuring GDP at different publication horizons (see details below). The successful candidates’ main supervisors will be Professor Martin Weale and Professor George Kapetanios, with whom there may be the possibility of working on big data.

The students will also work with individuals in other ESCoE partner institutes such as Nicholas Oulton (LSE) and Diane Coyle (Manchester) on the productivity side and Simon Kirby (NIESR) and Ivan Petrella (WBS) on the nowcasting side.

Candidates should have a quantitative Masters degree in Economics or related areas (normally with Distinction) from an internationally recognised academic institution; and be interested in developing their research interests in economics statistics and applied micro/macro econometrics.

Project details

Measuring activity in services sectors (Project 2.1)

Lead: Mary O’Mahony (King’s)
Co-Leads: Sylaja Srinivasan (NIESR, Bank of England), Augustin de Coulon (King’s) and Martin Weale (King’s)
Objectives: The Bean Review highlighted the need for better measures of services activities given their increasing importance as a share of value added and employment. Also much of the increased productivity growth associated with the information technology revolution occurred in services sectors. Although there have been significant improvements in measuring service sector activity, both conceptually and practically, there is no doubt that much more effort is required.
This project will investigate the deficiencies in the current measures of services activities for the UK and how might they be improved. Specifically this project will:
1. Define and value the activities provided by the services sector in measuring nominal output
2. Identify the most appropriate deflators to use to construct real output measures and how these might be adjusted for quality change
3. Identify additional measures that can be used in measuring real output, such as volumes of activity, in the public sector and how these might be adjusted for quality
4. Identify which sources of data might be employed to estimate outputs and prices in the services sectors

The research will also examine case studies of specific sectors such as financial services, retail trade, insurance and education provision.

Measuring GDP at different publication horizons (Project 1.2)

Lead: Andrew Harvey (Cambridge)
Co-Leads: George Kapetanios (King’s), Simon Kirby (NIESR) and Ivan Petrella (WBS)
Objectives: Our overarching aim is to enhance the quality of the estimates of GDP and their subcomponents across the publishing horizon, from the preliminary release to the 'final' Blue Book measure, and further to increase the informational content available to users of ONS data.
This includes providing a procedure which adds greater structure to the rebalancing process of GDP via econometric modelling; providing guidance in how to identify and organise additional data outside of official statistics such that they can be used within predictive econometric models; building and evaluating a suite of nowcasting models which are designed to deal with large datasets; and investigating the ability to identify turning points in real time through econometric methods.

Funding information

Funding applies to:
Open to applicants from a range of countries
Funding notes:

The studentship is open to Home/EU and International/Overseas students for 3 years from October 2017, plus the possibility of extension to a fourth year, and includes:

1) Tuition fees at Home/EU rate (currently £4600).
Please note that International/Overseas students will be required to find funding to cover the difference between Home/EU fees and international fees.

2) A stipend of circa £16,296 pa for 3 years

Administrative contact and how to apply:

Candidates should apply to mary.omahony@kcl.ac.uk and provide the following documents:

1) A curriculum vitae
2) A covering letter explaining your interest and aptitude for these research projects, in particular

a) why you are attracted to this particular opportunity
b) details of your quantitative skills
c) details of your knowledge of economics, statistics and econometrics
d) descriptions of previous projects you have completed
e) how the studentship fits with your career aspirations.

The successful candidates will be required to apply formally to King’s College London Doctoral programme, at which time the following document will be required:

3) A 2000 word research proposal describing the research project you wish to carry out.

Applications should be submitted by April 28 2017.

Shortlisted candidates will be contacted with further details soon after the closing date for applications.

For more information please click "Further Official Information" below.


This opportunity has expired. It was originally published here:

http://www.kcl.ac.uk/sspp/departments/management/study/research.aspx

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Disciplines

Economics

Statistics

Study Levels

PhD

Opportunity Types

Scholarships

Eligible Countries

International

Host Countries

United Kingdom