that they do track each other more closely. They
both record the price “on completion,” that is, the price returned to the Land
Registry as part of the legal process of registering the completed sale. They are
comprehensive in their coverage of transactions, at
least for England and Wales. There is
a need to control for the changing mix in the quality of houses sold. More
expensive houses may be sold one month leading us to think average prices have
increased when this may not be the case. The repeat sales methodology employed
by Land Registry constrains its coverage to properties transacted more than
once, so that an average of the price changes of the same houses is compiled. The
prices of like are, broadly speaking, compared with like, at the cost of using
a more limited sample and a selection bias. AcadHPI
uses the Land Registry’s entire transaction database. Its mechanism of adjusting
for the differential quality mix is to weight strata categorized
by property type and location. The
weights are transactions-based relative quantities between
January 2000 and December 2003. Land Registry is implicitly weighted by the
relative number of repeat transactions in the sample.
Nationwide and Halifax
include prices for properties for which they are the mortgagee. The DCLG index
covers all transactions bought with a mortgage issued by one of about 50
lenders (about 55 percent of mortgage transactions—more than Nationwide and Halifax) reporting to the
Regulated Mortgage Survey of the Council of Mortgage Lenders. All three indices
cover transactions in the United
Kingdom but, unlike the Land Registry-based
indices, exclude cash sales—about 25 percent of all purchase. While the
lender-based source data have some similarities, there is much in their
construction that differs.
Nationwide and Halifax are based on the asking price
when a mortgage is first approved—when the property is under offer, that is
later than when first advertised but prior to completion. Not all approved
applications will go through to completion.
DCLG is based on transaction prices “on completion.” DCLG is a
average of individual stratum indices with weights updated annually based on a
three year moving average. Nationwide and Halifax are complied
as stock quantity-weighted averages of the strata. Weights for Nationwide are updated every two years based on four year
moving averages of data, while Halifax uses constant weights from
1983. All three indices use hedonic regressions to minimize the
effect of changes in the quality-mix on price measurement, though the
specifications of the regressions differ. DCLG strata are both valued and defined
by quality (price-determining) characteristics of properties estimated from
hedonic regressions. As an example,
DCLG include in their regression variables relating to location (local
authority district or London borough), property type (PT), type of neighborhood
(using the ACORN classification), local authority cluster membership, defined
by the Office for National Statistics, number of habitable rooms, old or new
(New), first-time buyer or former owner-occupier (FT), plus interaction terms
for ACORN and PT, ACORN and FT, and PT and New. Each combination of the
variables in the regression forms a stratum defined by the combinations of
characteristics of the property, about 1,000 property types/strata. Halifax and
Nationwide define “typical” properties by fixed characteristic sets and value
them over time using the estimated coefficients of hedonic regression
In spite of these quite substantial differences, the
indices can be seen to track the broad phenomena of the trend and turning
points in residential property prices. Interestingly, there is no more
commonality between mortgage-based indices than those based on Land Registry
advertises properties for sale online throughout the United Kingdom covering
asking prices of the 90 percent of estate agents stated to advertise on their
site. Properties that do not sell are also included. The index is compiled from
the asking prices of properties, the prices at the very beginning of the buying
and selling process. Weights (and mix-adjustment) are according to the stock of
properties in terms of geographical distribution and property type. Rightmove is
distinct in its use of asking price and has the least commonality with other
Do the commonalities in measurement matter?
points are apparent:
But these points are based on a single
country’s experience. Consider a further example, the United States.
House price indices for the United States
States has two main indices for residential property prices, the Federal
Housing Finance Agency (FHFA)
“purchases only” house price index and the S&P/Case-Shiller
National Home Price Index. The FHFA produces an “all transactions” HPI that includes refinance appraisals that are
not sales that comprise nearly 90 percent (about 35 million of the 40 million
repeat transactions). FHFA itself notes evidence that prices based on
appraisals submitted for refinancing tend to lag market trends and have an
appraisal bias. The “purchases-only” HPI excludes refinancing transactions. Leventis (2008) estimates that removing appraisals accounts
for 1.54 percentage points of FHFAs 4.27 percent average difference over Case-Shiller for the four-quarter price change estimates over
2006Q3-2007Q3for the ten original MAs. Both
FHFA and Case-Shiller use the same repeat-sales
methodology to control for quality changes in the mix of houses sold. They have
the same coverage of type of properties; that is, they include transactions on
one-family houses and exclude 2- to 4-family houses, condominiums and
cooperatives, and weight changes in regional price indices over 9 US census
The FHFA, Case-Shiller and
Census Bureau indices do not incorporate Condominiums. However, in
November 2008, Standard & Poor's launched indices designed to track
condominium prices in five major metropolitan areas—Boston, Chicago, Los
Angeles, New York and San Francisco. The National Association of Realtors
provides median values (by quarter) for a larger number of cities for
condominium prices, but these are not quality adjusted.
Figure 3 shows the Census
Bureau’s index to be quite different from FHFA and Case-Shiller,
though this is to be expected since its coverage is of new houses only.
We can of course look to further evidence
from other countries for the effects of differences in estimates of boom and
busts using differing indices of house prices. There exists for Russia a
national price index for both new and existing dwellings. Figure 5 shows that
while the differences can be sizable in absolute terms, about 15 percentage
points in 2006 Q3, the two series broadly track each other.
Information on coverage and methodology for
these indexes is less readily available, at least to the author, than for the US and UK, but appear to be
comparable. Both are produced by the national statistical office, cover
apartments in urban areas, and are measured as average prices (rubles) of
properties subject to market transactions. Qualitative and quantitative
characteristics including location are stated as being taken into account at
the time of valuation, but it is not immediately apparent how this is done.
Both the average prices for new and existing dwellings are compiled for the
Russian Federation from average prices of Federal districts, weighted by some
combination of population and number of apartments commissioned.
BIS: Q:RU:9:1:1:1:1:0 and Q:RU:9:1:2:1:1:0; Indices
of Prices in Primary/Secondary Market of Dwellings; original source: Federal
State Statistics Service: Link.
United Kingdom: BIS:
Q:GB:3:1:0:2:0:0; Halifax House Price Index; original source and further
series: Halifax Research: Link
(historical house price data). BIS:
Q:GB:0:1:2:1:0:0; Communities and Local Government House Price Index; original
source and further series: Department of Communities and Local Government,
available at: Link.
Also available from UK (Office for) National Statistics at: Link.
(© Crown copyright 2008 Land Registry). Acadametrics;
LSL Property Services/Acadametrics House Price Index;
Land Registry; House Price Index; source: Link.
Nationwide; Nationwide House Price Index; source: Link.
Rightmove; House Price Index; source: Link.
Stijn, M. Ayhan Kose, and Marco E. Terrones, 2008,
“What Happens During Recessions, Crunches
and Busts?” IMF Working Paper 08/274 (Washington: International Monetary
Sumit (2007) “House Price
Indices of the UK – Methods Explained,” UK Office for National Statistics, Economic & Labour
Market Review, 1,1, January. Link.
Diewert, W. Erwin (2004), “The Treatment of Owner
Occupied Housing and Other Durables in a Consumer Price Index.” In W.E. Diewert, J. Greenless and C. Hulten (eds.), Price Index Concepts and Measurement, NBER
Studies in Income and Wealth, University of Chicago Press.
Eurostat, (2010a), European Commission, Directorate G:
Business Statistics, Unit G-6: Price Statistics;
Purchasing Power Parities, Research Paper, Experimental
House Price Indices for the Euro Area and the European Union, December.
Available at: Link.
(2010b), European Commission, Draft Technical Manual on Owner-Occupied Housing
for the Harmonised Index of Consumer Prices, v.1.9, February. Available at:
European Commission, Directorate G: Business Statistics, Unit G-6: Price Statistics; Purchasing Power
Parities, draft Handbook on Residential
Property Price Indices. Available
Fenwick, David (2006), “Statistics
on Real Estate Prices: The Need for a Strategic Approach.” Paper presented at the OECD-IMF Workshop on Real Estate Price
Indexes, November 6-7, OECD: Paris. Available at:
(2011), “Hedonic Price Indexes for Housing,” OECD Statistics Directorate Working Paper 35, STD/DOC(2011)1/REV1,
Leventis, Andrew 2008, “Revisiting the Differences
between the OFHEO and S&P/Case-Shiller House
Price Indexes: New Explanations,” Office of Federal
Housing Enterprise Oversight, January, Available at: www.ofheo.gov/media/research/OFHEOSPCS12008.pdf .
Mason, Phil and Gwilym Pryce
(2011), “Controlling for Transactions Bias in Regional House Price Indices,”
forthcoming, Housing Studies.
Meissner, Chris and Stephen Satchell
(2010), “A Comparison of the Case-Shiller House Price Index Methodology with the Academetrics House Price index Methodology,” Acadametrics Limited, December. Available at:
Reinhart, Carmen M. and Kenneth S. Rogoff, 2009, “This Time is Different, Eight Centuries of
Financial Folly,” Princeton University
Press, Princeton and Oxford.
Shiller, R.J., (1991). “Arithmetic Repeat Sales Price
Estimators,” Journal Housing Economics, 1,
U.K. Government Statistical Service (GSS), (2010), National Statistician's Review of House Price Statistics,
London: GSS, December. Available at: Link.
Wood, Robert (2005), “A Comparison of UK Residential House Price Indices.”
In Real Estate Indicators and Financial
Stability, Bank of International
Settlements Papers 21, 212–217. Proceedings of a joint Conference Organized
by the BIS and IMF in Washington DC 27-28 October, 2003.
 The views expressed herein are those of the author and should not
be attributed to the IMF, its Executive Board, or its management.
 Available at: Link.
 Claessens, Kose, and Terrones (2008, page 25)
 There remains a
sample selection bias if the indices are used to represent price changes of the
stock of houses (Mason and Pryce, 2011).
 The Land Registry data is a record of all residential property
transactions made in England
since January 1995. At the time of writing it contained details on over 15
million sales. Of these, just over five million were identifiable matched
 Due to delays in processing Land Registry (LR) data, the AcadHPI results are not termed “final” until a significant
volume of LR data is available which is normally after three months have
forecast results makes use of Halifax,
Nationwide, and DCLG indices. One month after any given month, LR provides
average house prices based upon circa 70% of the eventual total transactions,
which are used to replace the AcadHPI “forecast”
result with an AcadHPI "updated" result. A
further month later, LR provides prices based upon circa 90% of the eventual
total transactions which are used to replace the first with a second AcadHPI "updated" result. Three months after any
given month, LR provides prices based upon circa 95% of the total transactions
for the month. Taking the current month as month T, in month T + 4 the AcadHPI results are regarded as sufficiently updated to be
described as the AcadHPI “final” index (Meissner and Satchell, 2010, page
 Fixed quantity baskets are applied to estimated prices in the
months compared yielding a value-weighted index of price changes.
 See Dey-Chowdhury, 2007.
 At least in terms of its correlation. The
correlation coefficient between Rightmove and each of
Halifax, DCLF, Land Registry, AcadHPI, and Nationwide
are, respectively, 0.71, 0.55, 0.68, 0.62, and 0.73. No other correlation
coefficient for comparison between these series has a lower correlation
coefficient. Land Registry and AcadHPI, based on the
same source data, has a correlation of 0.98.
 The Federal Housing
Finance Agency regulates Fannie Mae, Freddie Mac and the 12 Federal Home Loan
 The upper end is also not fully represented
both because such transactions are less likely to use conventional mortgage
loans, and because the size of the associated mortgages can lie above the
conforming loan limits (loan amount restrictions) in the agencies. However, the
study found that the bias due to this was limited.
 This procedure is well justified when phrased as a correction for heteroskedastic error variances as greater noise
accompanies ratios over longer periods. The correction reduces the error but
does not increase bias.
 See Link.