Research Fellow Econometric Modelling for Energy & Environment


About us

Set within UCL’s Faculty of The Built Environment, The Bartlett School of Environment, Energy and Resources (BSEER) is comprised of four world-class Institutes, providing the expert knowledge collaborative research and teaching.

About the role

This post is created to expand UCL ISR econometric analysis expertise. The work of the post holder will be focused on microeconometric policy evaluation (DiD, RDD, PSM, Change-in-Changes, SCM, IV) to estimate the causal impact of schemes focused on the energy field, including both supply and demand policies. We are currently focusing on policies increasing energy efficiency and promoting decarbonisation in the built environment, and those promoting innovation in the supply side of the energy system, although this may change. The successful candidate will work on projects associated with:

  • the UK Emissions Trading Scheme (ETS)
  • the Social Housing Decarbonisation Main Fund (SHDF)
  • the Public Sector Decarbonisation Scheme (PSDS)

As part of the UK ETS evaluation, the successful candidate will focus on 1) assessing the evolution and relationships among market indicators using time series techniques; 2) assessing the nature of transactions and relationships among units using machine learning and big data techniques, such as cluster and network analysis; 3) quantifying the impact of the ETS on emission intensity, competitiveness and carbon leakage using innovative quasi-experimental approaches and counter-factual machine learning methods; 4) quantifying the carbon cost pass-through down the value chain. As part of the PSDS and SHDF evaluations, the successful candidate will focus on 1) examining the impact of these schemes on energy, carbon savings and other outcomes using innovative quasi-experimental approaches; 2) assessing their value for money using cost-benefit and cost-effectiveness analyses. This post is available from 01 April 2023 and is funded for 24 months in the first instance, further f! unding to support the post may be available. A job description and person specification can be accessed at the bottom of this page If you have any queries regarding the vacancy or the application process, please contact: bseer- If you have specific questions about the role please contact Professor Michael Grubb, ().

About you

The successful candidate will have a first and higher degree in a data analysis discipline, e.g., econometrics, economics, statistics, machine learning or engineering, together with a PhD or near to completion, or commensurate experience, in econometrics, economics, statistics, machine learning or engineering. Practical experience of quasi experimental methods for program evaluation is essential, with excellent ability to deploy several data analysis techniques, beyond quasi experimental methods. To be considered for appointment at Grade 8, an independent research reputation or comparable professional standing/experience is essential, as well as a track record of prominent roles in completed research, consultancy, or policy analysis projects (up journal publication if conducted in an academic environment) and the ability to make substantial contributions to research funding proposals.

Customer advert reference: B04-03511

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