We're hiring: RF / SRF in Econometric Modelling for Energy and the Environment

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About the role

This post is created to expand the econometric analysis expertise at UCL Institute for Sustainable Resources. 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:

• UK Emissions Trading Scheme (ETS)
• Social Housing Decarbonisation Main Fund (SHDF)
• 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 counterfactual 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 1 April 2023 and is funded for 24 months in the first instance, further funding to support the post may be available.

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.

Further information

• Download the Job Description for this role: RF SRF Econ Modelling Energy & Env
• To apply for this vacancy click on the Apply Now button at the top of the page.
• If you have any queries regarding the vacancy or the application process, please contact: bseer-recruitment@ucl.ac.uk.
• If you have specific questions about the role please contact Professor Michael Grubb: m.grubb@ucl.ac.uk.
• Please use these links to find out more about the UCL working life including the benefits we offer and UCL Terms and Conditions related to this job.