Outline
Word limit (10,000 words)
Key Words:
• Green Innovation for Net Zero
• Energy Efficiency Gap
• Heat and Building Strategy UK
• Decarbonisation of homes for Net Zero
• Heat Pump Adoption for Net Zero
• WTP for Heat Pumps
Background
The Heat and Buildings Strategy is one of the UK's planned decarbonisation strategies to reach Net Zero by 2050. This strategy outlines how the United Kingdom will decarbonize its residential, commercial, industrial, and public buildings to reach net-zero emissions by 2050.
Heat Pumps are a key solution for decarbonizing homes and will be essential for the United Kingdom to meet its net-zero emissions target by 2050. Approximately 14% of UK emissions are caused by residential heating. The United Kingdom government encourages the use of heat pumps to reduce these emissions. They are powered by electricity, which should be entirely renewable by 2035. Even on cold days, they draw latent heat from the outdoors, making them three to four times more efficient than conventional heaters.
The installation of energy-efficient and low-carbon heating like a Heat Pump compared to a Gas Boiler reduces households' fuel costs significantly. The household bills can decrease by 14% or approximately £160. Heat pumps save carbon emissions. Unlike burning oil, gas, LPG or biomass, a heat pump produces no carbon emissions on site (and no carbon emissions at all, if a renewable source of electricity is used to power them).
Research Question 1
Ques1: What factors drive/influence the adoption of Heat Pumps in the UK
Data
Secondary data set: EPC register
The entire dataset of residential EPCs for England and Wales going back to 2008 can be downloaded here (it’s about 22 million EPCs!): https://epc.opendatacommunities.org/
o The full dataset is broken up into chunks based on each county or local authority. To get started on cleaning it up, write some code to clean up one of the csv file for one of these areas first (maybe even pick your local area where you live as you can probably find your own flat/house in there!). Then create a loop that repeats that code for all the other areas you want to study, and then combine it all into one nice, finished dataset.
Variables required:
-Properties with heat pumps/ Gas Boilers/electricity (code as 0-1)
-Location (focus only on London)
-Owner occupied vs rented
-Postcode (indicative of a wealthy area, thus maybe adoption is more)
-EPC ratings
-income merged into areas/location/postcode
-Energy consumption merged into areas/location/postcode
-For local measures of neighbourhood average incomes, this is a good starting point:
• https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/smallareaincomeestimatesformiddlelayersuperoutputareasenglandandwales
-For local measures of neighbourhood average energy consumption, these are now even available at the postcode level for gas and electricity here:
• https://www.gov.uk/government/collections/sub-national-gas-consumption-data and
• https://www.gov.uk/government/collections/sub-national-electricity-consumption-data
Note: once you know the answer to this, what could you do with that information (e.g. highlight potential challenges to future adoption).
Research Question 2
Ques 2: Does a heat pump usage and EPC rating impact property values in London/UK
Note: Usually this kind of analysis is intended to show whether house buyers/sellers do a good job of understanding the potential benefits/savings from a given technology like a heat pump. Note we also mentioned the perverse way heat pumps currently lower EPCs which could be an interesting thing to show if you see it in the data.
• The property transactions dataset is also for England and Wales and goes back to 1995. You can match on the exact address with a bit of wrangling https://www.gov.uk/government/statistical-data-sets/price-paid-data-downloads
Methodology- Logistic Regression analysis using STATA
Obtain a cleaned-up data set with the required variables using the above-mentioned dataset.
-Properties with heat pumps/ Gas Boilers/electricity (code as 0-1)
-Location (focus only on London)
-Owner occupied vs rented
-Postcode (indicative of a wealthy area, thus maybe adoption is more)
-EPC ratings
-income merged into areas/location/postcode
-Energy consumption merged into areas/location/postcode
-property value of the properties
• To answer ques 1 (what are the factors or drivers that affect the uptake of heat pumps)
(What factors influence the adoption of heat pumps in the UK (income, location, property type, occupancy type).
• To answer ques 2 (does EPC rating from using heat pumps affect property values)
Results and Discussion: What factors influence the adoption of heat pumps in the UK (owner occupied vs rented, location, type of property, income)
Energy Efficiency Gap: Market Failure and Behavioural anomalies that can lead to fewer adoption. (Principal-Agent Problem, Incomplete Information, Prospect Theory (risk aversion).
Review of Literature (some starting points)
• This kind of review article on the energy efficiency gap might be good place to start.
• Research on willingness to pay for heat pumps like the study we discussed (or energy efficiency investments more generally)
• Research on subsidies for technology adoption (e.g. like this one on solar subsidies in California)
• Papers on capitalisation into property values (e.g. like this recent one on the US, or this older one on EPCs in the UK) (do this only after I feel I okay)
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