The heat paper measures whether the market prices heat-resilient housing, across five margins built from listings, the energy-certificate register, and grid temperature. This page sets out the analysis variables, the sources, their summary statistics, and the estimators. The variable roles are those of the estimation code: the workhorse is a cross-sectional hedonic whose dependent variable is the log asking price and whose regressor of interest is the high-EPC indicator, with the covariates below held fixed.

Variables

Dependent variable

  • Asking price: the listed sale price or monthly rent, used in logs. This is the outcome the hedonic explains.

Independent and control variables (the inputs)

  • High-EPC indicator: whether the home carries an A to C energy-performance band. Its coefficient is the premium the paper tracks.
  • EPC efficiency score: the continuous 1 to 100 score behind the band.
  • Air conditioning: whether the listing text advertises cooling, the most direct marker of heat readiness.
  • Floor area, bedrooms: size controls (bathrooms, living rooms, new-build status, property type, and region also enter as controls).
  • Summer heat anomaly: the June-to-August maximum-temperature departure from the 1991 to 2020 normal, by area and year, the chronic-exposure regressor.

Data source

Rightmove listings from 2018 to 2025 (a hedonic sample of about 10.1 million with a valid energy band and positive price), matched to the English domestic Energy Performance Certificate register by unique property identifier; the cooling indicator from the listings text; Met Office HadUK-Grid temperature summarised to the summer anomaly; and the 2019 English Index of Multiple Deprivation for the equity cut.

Summary statistics of the analysis variables

Sale listings (N = 6,122,310):

VariableRoleMeanSDMinMax
Asking price (£)dependent401,828475,52610,00082,500,000
Log asking pricedependent12.640.709.2118.23
Floor area (m²)input115.8116.01510,556
Bedroomsinput2.911.07010
High-EPC (A–C) indicatorinput0.4370.5001
EPC efficiency score (1–100)input65.511.81100
Air-conditioning indicatorinput0.000550.02301

Rent listings (N = 4,002,380):

VariableRoleMeanSDMinMax
Asking rent (£/month)dependent1,5091,51110050,000
Log asking rentdependent7.100.614.6110.82
Floor area (m²)input87.977.6159,870
Bedroomsinput2.351.23010
High-EPC (A–C) indicatorinput0.5570.5001
EPC efficiency score (1–100)input68.610.41100
Air-conditioning indicatorinput0.001090.03301

Summer heat anomaly, the chronic-exposure regressor, by area and year (N = 54 area-years, 2017–2025):

VariableRoleMeanSDMinMax
Summer heat anomaly (°C)input0.860.92−0.552.54

Floor area is populated for 5,893,314 sale and 3,871,459 rent listings; the air-conditioning share is computed over all listings (8,376,744 sale, 5,439,449 rent). The indicator standard deviations are those of a 0/1 variable.

Method

The dependent variable is the log asking price. Five margins build on the same hedonic: a monthly cross-sectional regression of log price on the high-EPC indicator with the size, type, and region controls, read as the premium and summarised into a seasonal profile and an interrupted time series around the July 2018 and July 2022 heatwaves; a two-step regression of the area-by-year premium on the summer anomaly with area and year fixed effects; a pooled hedonic interacting the anomaly with the high-EPC and air-conditioning indicators; and an energy-band boundary regression discontinuity, whose interaction with heat gives a difference-in-discontinuities. Standard errors are clustered by local authority.