House Prices and Rents
Micro Evidence from a Matched Dataset in Central London
Philippe Bracke
London School of Economics
...
About me
Studied economics
Wanted to become a theoretical
macroeconomist
PhD: discovered the joys of data analysis
Python ...
Today’s Talk
Roadmap
1. Introduction
2. Data
3. Matching procedure
4. Some findings
5. More matching
6. Summary and way for...
(http://www.telegraph.co.uk/property/propertypicturegalleries/9054056/
The-best-Matt-cartoons-on-property.html)
Focus of this research
Price
Rent
or
Rent
Price
(Rental yield)
They matter hugely for...
Households Buy vs rent
Landlords ...
Aggregate ratio between house prices and rents:
important indicator of housing market conditions
Micro-level differences in rental yields: equally important
Why does Rent
Price change?
(over time and over space)
Rent = User cost · Price (“no-arbitrage”)
Rent
Price
= rf + δ - Eg ...
Data
1. House prices
2. (Private-sector) rents
Land Registry Price Paid data
All registered property sales in England and Wales, 1995–2013
→ 18.5m records, freely availa...
Transaction prices in London, 2006–2012
The problem: Data on private rents
Rental data are much less available than house price data
A gap exists in official privat...
The problem: Data on private rents (cont’d)
The Office for National Statistics (ONS) released in 2013 an
experimental quarte...
John D Wood & Co.
Rental Dataset
Real estate agency with 14 London offices and 6 offices in the
South-East of England
Focus on...
John D Wood & Co. (cont’d)
Rental Dataset
new contracts, no
roll-overs
internal records +
exchange of data with
other agen...
Weekly rent, Agency Dataset
Central-Western London, 2006–2012
Matching procedure
Matching issues
Address format
Land Registry
Clean and easy:
postcode W2 3DB
paon 5
saon FLAT K
street WESTBOURNE CRESCENT...
Matched dataset
Construction
try as much as possible to harmonise the two datasets
all variables in upper case letters as ...
Matched dataset
Distance between sale and rental contract
0500100015002000
Matches
−2000 −1000 0 1000 2000
Days
Descriptive stats
Matched Units Complete Dataset
Land Registry & Rentals Rentals
Observations 1,922 48,341
Median rent 595...
Descriptive stats (cont’d)
Matched Units Complete Dataset
Land Registry & Rentals Rentals
Bedrooms (%)
1-bedroom property ...
Some findings
Matched dataset
Rent-price ratio over time
.02.04.06.08
01jul2006 01jan2008 01jul2009 01jan2011 01jul2012
R/P ratio 10−yea...
Matched dataset
Rent-price ratio vs. property value
0.02.04.06.08.1
0 1000 2000 3000 4000
Price (in £1,000)
Rent−price rat...
Matched dataset
Rent-price ratio vs. property type
.02.04.06.08.1
0 1000 2000 3000 4000
Price (in £1,000)
Rent−price ratio...
Depreciation/maintenance costs and rent-price ratios
Rent
Price
= rf + δ − g + m
House = land + structure
More expensive l...
More Matching
Repeat sales, repeat rentals
How to measure future appreciation and risk?
Rent
Price
= rf + δ − Eg + m
Need to find future sales and/or rentals of the s...
The effect of future appreciation and risk
Sales
Rentals
Matched Dataset Matched + Repeat Rentals Dataset
1,922 properties ...
Summary and way forward
Summary
Novel dataset on prices and rents in Central London
Measure rent-price ratios directly for matched properties
Find...
Next steps
The Land Registry is a recent open data resource with huge
potential
Can be matched with many other datasets
pr...
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House Prices and Rents: Micro Evidence from a Matched Dataset in Central London by Philippe Bracke

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House Prices and Rents: Micro Evidence from a Matched Dataset in Central London by Philippe Bracke

  1. 1. House Prices and Rents Micro Evidence from a Matched Dataset in Central London Philippe Bracke London School of Economics PyData 2014, London (Feb 23)
  2. 2. About me Studied economics Wanted to become a theoretical macroeconomist PhD: discovered the joys of data analysis Python (and R, Stata) Current research focus Housing markets Twitter @PhilippeBracke
  3. 3. Today’s Talk Roadmap 1. Introduction 2. Data 3. Matching procedure 4. Some findings 5. More matching 6. Summary and way forward
  4. 4. (http://www.telegraph.co.uk/property/propertypicturegalleries/9054056/ The-best-Matt-cartoons-on-property.html)
  5. 5. Focus of this research Price Rent or Rent Price (Rental yield) They matter hugely for... Households Buy vs rent Landlords Return on investment
  6. 6. Aggregate ratio between house prices and rents: important indicator of housing market conditions
  7. 7. Micro-level differences in rental yields: equally important
  8. 8. Why does Rent Price change? (over time and over space) Rent = User cost · Price (“no-arbitrage”) Rent Price = rf + δ - Eg + m Interest rate Risk Expected growth Maintenance
  9. 9. Data 1. House prices 2. (Private-sector) rents
  10. 10. Land Registry Price Paid data All registered property sales in England and Wales, 1995–2013 → 18.5m records, freely available! full address price paid date of transfer property type: Detached, Semi, Terraced or Flat/Maisonette new build or not freehold or leasehold http://www.landregistry.gov.uk/market-trend-data/public-data/ price-paid-data
  11. 11. Transaction prices in London, 2006–2012
  12. 12. The problem: Data on private rents Rental data are much less available than house price data A gap exists in official private rental statistics with no official private rental index currently available The National Statistician’s Review of Official Housing Market Statistics, September 2012
  13. 13. The problem: Data on private rents (cont’d) The Office for National Statistics (ONS) released in 2013 an experimental quarterly index of the private rental market The index is based on individual rental data from the Valuation Office Agency (VOA), who deploys rental officers to collect the price paid for privately rented properties This data is not publicly available
  14. 14. John D Wood & Co. Rental Dataset Real estate agency with 14 London offices and 6 offices in the South-East of England Focus on upper market: Central/South-West London and countryside
  15. 15. John D Wood & Co. (cont’d) Rental Dataset new contracts, no roll-overs internal records + exchange of data with other agencies
  16. 16. Weekly rent, Agency Dataset Central-Western London, 2006–2012
  17. 17. Matching procedure
  18. 18. Matching issues Address format Land Registry Clean and easy: postcode W2 3DB paon 5 saon FLAT K street WESTBOURNE CRESCENT Ambiguous: postcode UB4 8FJ paon MARSH COURT, 561 saon 4 street UXBRIDGE ROAD Agency data Clean and easy: hsename Flat K hseno 5 address1 Westbourne Crescent postcode W2 Ambiguous: hsename hseno 2 address1 Rupert House address2 Nevern Square
  19. 19. Matched dataset Construction try as much as possible to harmonise the two datasets all variables in upper case letters as in LR rename “hseno” as “paon”, and “hsname” as “saon” join together all transactions sharing the same “street”, “paon” and “saon” Rule 1 for each sale, keep the closest rent Rule 2 for each rent, keep the closest sale
  20. 20. Matched dataset Distance between sale and rental contract 0500100015002000 Matches −2000 −1000 0 1000 2000 Days
  21. 21. Descriptive stats Matched Units Complete Dataset Land Registry & Rentals Rentals Observations 1,922 48,341 Median rent 595 525 Median price 650,000 Median gross rent-price ratio 0.05 Property type (%) Lower-ground apartment 0.07 0.08 Ground-floor apartment 0.12 0.13 First-floor apartment 0.17 0.18 Second-floor apartment 0.17 0.15 Third-floor apartment 0.11 0.11 Fourth-floor+ apartment 0.12 0.16 Multi-level apartment 0.04 0.06 House 0.20 0.11
  22. 22. Descriptive stats (cont’d) Matched Units Complete Dataset Land Registry & Rentals Rentals Bedrooms (%) 1-bedroom property 0.33 0.36 2-bedroom property 0.41 0.41 3-bedroom property 0.16 0.15 4-bedroom+ property 0.10 0.07 Apartment block 0.16 0.31 Median floor area (sqft) 797 860 Furnished/unfurnished (%) Unfurnished 0.25 0.24 Partly furnished 0.34 0.27 Furnished 0.41 0.49
  23. 23. Some findings
  24. 24. Matched dataset Rent-price ratio over time .02.04.06.08 01jul2006 01jan2008 01jul2009 01jan2011 01jul2012 R/P ratio 10−year UK Government Bond Yield
  25. 25. Matched dataset Rent-price ratio vs. property value 0.02.04.06.08.1 0 1000 2000 3000 4000 Price (in £1,000) Rent−price ratios vs Prices 0.02.04.06.08.1 0 500 1000 1500 2000 2500 Rent (in £ per week) Rent−price ratios vs Rents
  26. 26. Matched dataset Rent-price ratio vs. property type .02.04.06.08.1 0 1000 2000 3000 4000 Price (in £1,000) Rent−price ratios vs Prices (Apartm.) 0.02.04.06.08.1 0 1000 2000 3000 4000 Price (in £1,000) Rent−price ratios vs Prices (Houses) .02.04.06.08.1 0 1000 2000 3000 4000 Floor area (sqft) Rent−price ratios vs Floor areas NW1 NW3 NW8 SW1 SW10 SW11 SW3 SW5 SW6 SW7 SW8 W1W10 W11W14 W2 W8 W9 .046.048.05.052.054.056 400 600 800 1000 1200 Average Price (in £1,000) Rent−price ratios vs Prices (by Postcode) Patterns confirmed by multivariate regression: Rent Price = α + Type β1 + Size β2 + Location β3 + Date β4 + ε
  27. 27. Depreciation/maintenance costs and rent-price ratios Rent Price = rf + δ − g + m House = land + structure More expensive locations: higher land share ⇒ Rent Price ↓
  28. 28. More Matching Repeat sales, repeat rentals
  29. 29. How to measure future appreciation and risk? Rent Price = rf + δ − Eg + m Need to find future sales and/or rentals of the same property → Match within-Land Registry or within-Agency data easier Repeat sales: not frequent Repeat rentals: many
  30. 30. The effect of future appreciation and risk Sales Rentals Matched Dataset Matched + Repeat Rentals Dataset 1,922 properties 859 properties Max gap = 180 days Average gap = 85 days Max gap = 2,360 days Average gap = 578 days Regression results One-standard deviation higher future rent appreciation ⇒ Rent Price ↓ by 1.6% Ambiguous results on rent volatility (one measure of risk)
  31. 31. Summary and way forward
  32. 32. Summary Novel dataset on prices and rents in Central London Measure rent-price ratios directly for matched properties Find lower rent-price ratios for expensive properties → Effect of size → Effect of location and other effects Consistent with economic theory
  33. 33. Next steps The Land Registry is a recent open data resource with huge potential Can be matched with many other datasets private datasets public housing-related websites Let’s collaborate! Github, philippebracke Thank you!

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