Halifax House Price Index (HHPI) 2019 Index Manual for HHPI

Halifax House Price Index (HHPI) 2019

Halifax House Price

Index (HHPI) 2019

Index Manual for HHPI

model introduced in 2019

Table of Contents

1) Significant Index Administration Events....................................................................................................3

2) HHPI (2019) Overview..............................................................................................................................3

3) Index Methodology....................................................................................................................................4

3.1) Index Calculation........................................................................................................5

3.2) Property Characteristics............................................................................................ 6

3.3) Index Performance..................................................................................................... 8

4) Governance and Regulatory Compliance...............................................................................................10

5) Restatement Policy ................................................................................................................................10

6) Construction of this Index Manual .........................................................................................................11

7) Licensing and Trademark ...................................................................................................................... 11

8) Further Information .................................................................................................................................11

9) ESG Disclosures..................................................................................................................................... 12

A) Glossary.................................................................................................................................................. 13

Disclaimer.................................................................................................................................................... 13

Halifax House Price Index (HHPI) 2019 2

1) Significant Index Administration Events

The following Index Administration events apply to each index of the Halifax House Price Index (HHPI)

2019 family.

Table 1: Index Administration Events

Date Index Administration Event

January 2021 Governance and Regulatory Compliance sections are

consolidated under Section 4) — Governance and Regulatory

Compliance

April 2019 IHS Markit Benchmark Administration Limited (IMBA

UK) officially commences Index Administration

January 2018 Annual attestation of IOSCO compliance

January 1983 Index Commencement Date

January 1992 Index Base Date (base level = 100)

2) HHPI (2019) Overview

When first introduced in 1984, the Halifax House Price Index (HHPI) represented a major advance in the

measurement of house price changes in the United Kingdom.

Unlike earlier series, and house price statistics produced by other institutions, the new figures issued

by the then Halifax Building Society were standardised rather than based on simple price averages.

By allowing for the influence of the different characteristics of houses on their prices, using a database

especially established by the Halifax, and maintained by Lloyds Banking Group (LBG), for this purpose,

the new series placed the measures on a truly comparable footing, thereby providing a more accurate

indication of like-for-like house price movements than was previously possible.

Broadly speaking, the HHPI methodology was left unchanged since its inception in 1983. Whilst the

hedonic regression on which the original model is based remains a pre-eminent method of house

price index generation in 2019, during the years that have passed since 1983 there have been several

developments that encourage methodological upgrading. For instance, changes in the mix of UK housing

stock – both geographical and physical housing attributes – plus the reduced influence of certain property

characteristics in price determination led, especially in recent years, to an undesirable effect of increasing

HHPI index volatility.

Borne out of both a deep knowledge of the original HHPI model, which we define in this document as

HHPI (1983) and a careful assessment of the current literature on house price determination provided by

Halifax House Price Index (HHPI) 2019 3

statistics agencies based in the UK and the euro area, S&P DJI has subsequently undertaken a number of

methodological enhancements to tackle the aforementioned issues with HHPI (1983). These include:

•

refreshing the data exclusion criteria, with particular focus on the inclusion of shared ownership

transactions

•

replacing existing model characteristics with a more parsimonious set. This selection includes

improving the granularity of location characteristics

•

creating an enhanced weighting system based on the chain-linking methods used by statistical

agencies around the world

•

remapping the HHPI sample to current Government Office Region (GOR) specifications to create UK

regions consistent with UK official statistics

These enhancements have been combined to create a new set of HHPI indices for users, which we refer

to as HHPI (2019), covering the following indices at both the UK national and regional level:

Table 2: List of Halifax House Price Index (HHPI) 2019 family

Index Series Frequency Total Number of indices

UK AHAB, SA + NSA

UK New Homes, NSA

UK Existing Homes, NSA

UK First Time Buyers, NSA

UK Former Owner Occupiers, NSA

Monthly 6

UK+12 Regions AHAB, SA + NSA

UK New Homes, NSA

UK+12 Regions Existing Homes, NSA

UK+12 Regions First Time Buyers, NSA

UK+12 Regions Former Owner Occupiers,

NSA

Quarterly 66

UK+12 UK Regions AHAB, NSA

UK New Homes, NSA

UK+12 Regions Existing Homes, NSA

UK+12 Regions First Time Buyers, NSA

UK+12 Regions Former Owner Occupiers,

NSA

Annual 53

3) Index Methodology

The following sections present an overview of the HHPI (2019) methodology.

The sole source of data for HHPI (2019) remains Lloyds Banking Group (LBG). Using mortgage approval

data provided by LBG, it is possible to determine not only the price information related to property

transactions, but also several attributes related to the type (detached, semi-detached, terraced etc.), size

(bedrooms, floor space in square metres), age (new/old), and location. The dataset is then combined with

hedonic regression techniques to generate house price indices.

Halifax House Price Index (HHPI) 2019 4

With the core aim of HHPI (2019) to provide a robust measure of changes in residential property prices,

as in the case of HHPI (1983), several types of transaction are excluded from index generation. These

include:

•

Re-mortgages

•

Business use, capital raising, or building mortgages

•

Discounted mortgages relative to market value (as determined by observed data that shows the

property valuation < 75% of purchase price e.g. the “Right-to-Buy” scheme).

An exception to the discounted mortgage rule is shared ownership mortgages which are, for the first time,

included in the new version of the HHPI. We also now include buy-to-let properties and those bought

directly from less-conventional vendors e.g. builders.

The effects of including shared ownership mortgages enable the HHPI (2019) to:

•

better reflect the current structure of the UK housing market, especially in relation to the trend towards

increasing levels of shared ownership among first-time buyers

•

enjoy a higher sample size and help to reduce the period-to-period volatility of HHPI both at national

and regional levels.

3.1) Index Calculation

The HHPI is calculated by estimating the price of a fixed ‘basket’ of attributes of houses sold in different

time periods (an analogy is with the standard basket of goods in the retail price index). By taking a ratio of

two valuations we subsequently estimate the change in property prices across a time period.

To reflect the idea that the mix of properties is not necessarily constant and can change between periods,

the HHPI (2019) basket of attributes is fixed to a 12-month period and subsequently updated once a year

using three years of LBG transactional data (although an exception is the regional weights for the UK level

indices, which are calculated using external data from the Land Registry, HMRC and Council of Mortgage

Lenders. This is to help guard against any regional bias that may be present in the LBG transactional

dataset).

Given that successive years of data are not directly comparable, each basket runs for a 13-month period

from January to January (or in the case of a quarterly index, Q1 to Q1). Individual ‘in-year’ price indices

for each basket of goods are created with the first January (or Q1) index value set to 100. The ‘in-year’

indices are subsequently ‘chained’ together to provide a continuous time series by taking the month 13

January figure (or quarter 5 figure) as the first reading of the next year’s basket.

This should be viewed as a considerable improvement on the original methodology, which used a

standardised house determined in 1983. Throughout recent years there have been a number of changes

in property development (such as a rise in the number of bathrooms, the increased use of central heating

etc.) that has made the standardised house in 2019 look different to that of 1983. Chain-linking methods

subsequently help to address these changes in the housing market and, going forward, provide a natural

protection against future changes.

A further update to the methodology is to use a parsimonious and more targeted set of property

characteristics. HHPI (1983) utilised a vast array of attributes. Whilst these were relevant in 1983, a

number have unfortunately become obsolete or hard to measure e.g. central heating statistics, garage

spaces etc. In line with empirical evidence and indices produced around the globe, our new set of

characteristics has been chosen to focus primarily on size, type, and location.

Valuing the standardised property with the use of these price-determining characteristics is achieved

using the same semi-logarithmic hedonic regression specification employed by the original 1983 HHPI

model. In the case of housing, prices reflect the valuation placed by purchasers on a particular set of

locational and physical attributes (or characteristics) possessed by each house. The subsequent need

Halifax House Price Index (HHPI) 2019 5

for ‘standardisation’ arises out of the observation that two houses are not alike: they can differ according

to a variety of quantitative and qualitative characteristics relating to the physical attributes of the houses

themselves or to their locations.

The difficulty is the implicit value placed by a purchaser on each characteristic cannot be observed

because transactions take place in terms of a single total price. Therefore, in order to remove that part

of price variation due to changes in the mix of house characteristics over time, and so to measure the

variation caused by inflationary factors, it is necessary to disaggregate prices into their constituents

statistically. This is achieved by using a multivariate regression equation of the form:

Here reflects the price of an individual property which is determined by a set of

characteristics . If the property has a particular characteristic then it takes the value of 1 or 0, with the

exceptions of the number of bedrooms (between 1 and 8) and floor area (m

bounded between 30 and

500).

The set of regression coefficients correspond to the qualitative and quantitative

characteristics, whilst the group of unmeasured factors (assumed to be randomly distributed) which are

specific to each house but for which data are not available is captured by the statistical error .

The regression is subsequently calculated using the widely-used technique of Ordinary Least Squares

(OLS).

3.2) Property Characteristics

The index uses a variety of characteristics to determine a standardised house in the UK which, when

taken together, help to explain the majority of the variation in house prices. Compared to HHPI (1983), the

new version of the model takes a more targeted approach to the standardised house price, focusing on

value-added characteristics such as type, size, age and location.

Taking each of these in isolation:

a. Property Type

LBG attributes a property type to each mortgage offer, these being:

Detached, Semi-Detached, Terraced, Flat, Bungalow

As would be expected, detached properties tend to command higher selling prices than semi-detached,

which in turn tend to be higher than terraced properties etc.

b. Size

The LBG mortgage data includes information on the size of each property in square metres. Not

surprisingly we find that this is a key, statistically significant, determinant of the price of a property i.e.

Ceteris Paribas the larger the property the greater the value.

The price of the property is also partly explained by the number of bedrooms that it possesses. The higher

the number of bedrooms the higher the price tends to be. LBG mortgage offers contain information on

bedroom numbers and, as such, this variable is included in the regression specification.

c. Age

Halifax House Price Index (HHPI) 2019 6

New houses tend to attract a price premium relative to older properties with similar attributes. Including a

categorical characteristic that encapsulates this (i.e. new or not new) is found to be statistically significant

in our hedonic regression specification and is subsequently included as an explanatory variable.

d. Location

In line with HHPI (1983), a set of dummy variables that encapsulates a particular UK region that the

property resides within continues to be used. A slight variation on the original methodology is the use of

Government Office Region classifications (GOR) for England, rather than the original Economic Planning

Region (EPR) classification. This provides us with nine English regions: Eastern England, East Midlands,

Greater London, North East, North West, South East, South West, West Midlands and Yorkshire &

Humberside. These are combined with Northern Ireland, Scotland and Wales to provide 12 UK regions.

A notable difference between the 1983 and 2019 HHPI indices has been greater focus on the treatment of

locational property characteristics. The existing methodology used the EPR as the only price-determining

locational factor. However, within any given region there will variance in terms of desirability between

postcode areas and this will be reflected in respective house prices. Greater granularity within the location

variables can be expected to notably improve the ability to accurately estimate house prices.

Whilst a commercially available location variable (ACORN) is used by the Nationwide and the Office for

National Statistics (ONS) in the generation of their own, similar, house price indices, S&P DJI has created

its own propriety classification system to help determine an area's house-price level in the context of its

GOR region and housing-mix.

Note UK and regional HHPI (2019) models may contain differences in explanatory variables employed

in respective hedonic regression specifications. These difference are seen in Table 3: HPI Regression

Specifications.

Halifax House Price Index (HHPI) 2019 7

Table 3: HPI Regression Specifications

3.3) Index Performance

The model changes have resulted in a number of improvements to HHPI performance, which we define

from the perspective of three key metrics:

•

statistical output from the regression calculations e.g. explanatory power (RSQ statistics), parameter

significance as measured by t-statistics

•

sample size

•

index volatility

Table 4: HHPI (2019) Key Metrics (July 2007 to June 2018) provides some summary statistics related

to these metrics at the UK level, not only for the All House All Buyers (AHAB) indices, but also the sub-

indices of First-Time Buyers (FTB), Former Owner Occupiers (FOO) and Existing (EXI).

Halifax House Price Index (HHPI) 2019 8

Table 4: HHPI (2019) Key Metrics (July 2007 to June 2018)

Index Series

(United Kingdom)

Sample Gain RSQ

Volatility

Improvement

(y/y inflation rates)

Standardised Price

(at Jun-18)

Price Difference

to HHPI1

(% 5-Year Average)

AHAB 35% 82.4% 43.1% £231,903 2.2%

First-Time Buyers 36% 82.3% 49.0% £183,536 5.2%

Former Owner

Occupiers

33% 83.7% 48.3% £278,868 4.2%

Existing Houses 20% 84.2% 63.5% £220,398 -4.7%

New Houses n/a 84.1% n/a £244,815 n/a

Notes: Gain columns reflect the difference between equivalent HHPI1 (1983) and HHPI (2019) data.

In this instance, a positive number equates to a higher reading for HHPI (2019) models. Note all

comparisons cover the period July 2007 to June 2018 and, reflective of their market sensitivity, we do

not include raw sample size numbers. We measure volatility by taking the square root of the average

squared monthly movement in annual rates of change for both the HHPI (1983) and HHPI (2019) indices.

Using a ratio of these two numbers provides an estimate of the relative difference between the monthly

movements of the two data series. A positive number in the tables reflect favourable performance for

HHPI (2019) models.

Table 4: HHPI (2019) Key Metrics (July 2007 to June 2018) highlights the positive impacts that the model

refinements have made on all of our key performance metrics.

Firstly, amendments of the data cleansing rules to include shared-ownership, buy-to-let and non-typical

vendors such as builders has led to a noticeable gain in sample size over the test period. At the UK level

the increase is 35%. There is a slightly stronger increase in the number of first-time buyers (FTB) and we

also have a greater representation of new properties in our sample (as implied by the number of existing

houses rising by 20% on average). Note this is broadly expected given the inclusion of shared ownership

and direct purchases from builders. With this in mind, we have taken the opportunity to supply a New

Houses Index which had been previously discontinued.

Secondly, the addition of our new property location characteristics, allied with a parsimonious regression

specification focusing on size, age, location and property type leads to noticeable and considerable gains

in the explanatory power of the indices compared to HHPI (1983).

The AHAB UK model, with a RSQ average of 82.4%, is a considerable improvement on HHPI (1983) –

an increase of 14.2 ppts. The three other currently available models – FTB, FOO and EXI – also enjoy

noticeable gains in explanatory power, whilst the RSQ reading for new houses is over 80%.

Thirdly, the implied volatility of all indices is reduced, reflective of the new parsimonious regression

specification which has removed variables that have proven difficult in recent years to identify coefficient

values for i.e. central heating, garage spaces etc. At 43.1%, the improvement in volatility seen at the

UK level is considerable, with even larger improvements seen for FTB (49.0%), FOO (48.3%) and EXI

(63.5%).

Halifax House Price Index (HHPI) 2019 9

4) Governance and Regulatory Compliance

IHS Markit Benchmark Administration Limited (IMBA UK) is the Administrator of HHPI 2019 Index family.

Information on IMBA UK's governance and compliance approach can be found here. This document

covers:

•

Governance arrangements, including external committees

•

Input data integrity

•

Conflicts of interest management

•

Market disruption and Force Majeure

•

Methodology changes and cessations

•

Complaints

•

Errors and restatements

•

Reporting of infringements and misconduct

•

Methodology reviews

•

Business continuity

More details about IMBA UK can be found on the Administrator’s website.

5) Restatement Policy

IHS Markit Benchmark Administration Limited (IMBA UK or the Administrator) is the appointed

Administrator of the Halifax House Price Index (HHPI). The Administrator is committed to conducting its

business with integrity and to providing index information of the highest quality to its customers and index

stakeholders. However, the Administrator recognizes that, in some situations, inaccuracies can arise

that may warrant a restatement of one or more indices. Such inaccuracies may be caused by a range of

events including:

•

Incorrect mortgage transaction data provided by the contributor;

•

Unavailability of up-to-date mortgage transaction data at the time of index calculation;

•

Failure of exclusion criteria; or

•

Index model calculation error.

The Administrator has implemented a wide range of pre-calculation checks throughout the data collection

process to capture and validate exceptions which could indicate an error or data problem. These include

checks on large transaction volume movements. Additional comparative and consistency checks are also

in place. Any exception or warning alert is reviewed and analyzed for potential problems. In the event that

exceptions are caused by an error, the HHPI index analysts will correct the error before official publication.

In the instance an inaccuracy is not caught and resolved before index calculation and publication or if

input data received is revised retrospectively, the Administrator will review the impact on affected index

values. In order to decide whether to restate an index, the Administrator takes multiple factors into

consideration including:

•

The size of the deviation between published and updated index levels;

•

Dates of the restatement period, in particular:

•

how recent the restatement period occurred; and

•

the length of the period to be restated.

•

Client impact; and

•

Index usage.

Halifax House Price Index (HHPI) 2019 10

If the analysis indicates that a revision of the Index could be warranted, Index Administration Committee

(IAC) will make a restatement determination. If the IAC decides to revise the HHPI values, the reason for

the restatement together with the revised index values will be published.

In addition, the Administrator will compile an incident report to summarize the incident, the root cause and

set forth remedial actions to avoid reoccurrence in the future, where such remedial actions are applicable.

Use of the Halifax name and logo on the Halifax House Price Index (HHPI) Restatement Policy by S&P

DJI is under license from Lloyds Banking Group and its affiliates.

6) Construction of this Index Manual

The Index Manual is published by the Index Administrator. In the event of any inconsistency between the

English language version of this Index Manual and that translated into any other language, this English

version shall prevail.

7) Licensing and Trademark

All intellectual property rights in the Index belong to S&P DJI unless otherwise specified. The use of

the Halifax name and logo on the Index by S&P DJI is under licence from Lloyds and its affiliates. Any

unauthorised use of any content appearing herein may violate the intellectual property rights of S&P DJI or

Lloyds under relevant intellectual property laws such as copyright laws, trademark laws, regulations and

statutes and is strictly prohibited. Persons seeking to place reliance on the Index for their own or third

party commercial purposes do so at their own risk. A licence from S&P DJI is required for benchmark and

all other uses of the Halifax House Price Index (HHPI) 2019 family.

8) Further Information

Formal complaints can be sent electronically to a specifically dedicated email address –

[email protected]. Please note that this dedicated email address should only be used to

log formal complaints.

For any general index enquiries, please contact [email protected].

Ownership: the Index Owner is S&P DJI.

Halifax House Price Index (HHPI) 2019 11

9) ESG Disclosures

EXPLANATION OF HOW ENVIRONMENTAL, SOCIAL & GOVERNANCE (ESG) FACTORS

ARE REFLECTED IN THE KEY ELEMENTS OF THE BENCHMARK METHODOLOGY [1]

1 Name of the benchmark administrator. IHS Markit Benchmark Administration

Limited (IMBA)

Underlying asset class of the ESG

benchmark. [2]

N/A

3 Name of the S&P Dow Jones Indices

benchmark or family of benchmarks.

Halifax HPI 2019 Benchmark Statement

Do any of the indices maintained by this

methodology take into account ESG

factors?

Appendix latest update: March 2023

Appendix first publication March 2023

[1] The information contained in this Appendix is intended to meet the requirements of the European

Union Commission Delegated Regulation (EU) 2020/1817 supplementing Regulation (EU) 2016/1011

of the European Parliament and of the Council as regards the minimum content of the explanation of

how environmental, social and governance factors are reflected in the benchmark methodology and

the retained EU law in the UK (The Benchmarks (amendment and Transitional Provision) (EU Exit)

Regulations 2019.

[2] The ‘underlying assets’ are defined in European Union Commission Delegated Regulation (EU)

2020/1816 supplementing Regulation (EU) 2016/1011 of the European Parliament and of the Council as

regards the explanation in the benchmark statement of how environmental, social and governance factors

are reflected in each benchmark provided and published.

Halifax House Price Index (HHPI) 2019 12

A) Glossary

Term Definition

HHPI means Halifax House Price Index (HHPI) 2019 family.

IHS Markit Benchmark Administration

Limited (IMBA UK)

means the Administrator of the HHPI 2019 index family

Index Base Date

is the date of the initial level of the index. See Table 1: Index Administration Events.

Index Commencement Date

is the date the index level was first published. See Table 1: Index Administration

Events.

Index Manual means this document, as amended, replaced or substituted, from time to time.

Index Owner

means S&P DJI.

S&P DJI Website

means the following website: https://www.spglobal.com/spdji/en/.

Disclaimer

Performance Disclosure/Back-Tested Data

Where applicable, S&P Dow Jones Indices and its index-related affiliates (“S&P DJI”) defines various

dates to assist our clients in providing transparency. The First Value Date is the first day for which there

is a calculated value (either live or back-tested) for a given index. The Base Date is the date at which

the index is set to a fixed value for calculation purposes. The Launch Date designates the date when the

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Please refer to the methodology for the Index for more details about the index, including the manner in

which it is rebalanced, the timing of such rebalancing, criteria for additions and deletions, as well as all

index calculations.

Information presented prior to an index’s launch date is hypothetical back-tested performance, not

actual performance, and is based on the index methodology in effect on the launch date. However,

when creating back-tested history for periods of market anomalies or other periods that do not reflect the

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universe of securities to simulate the target market the index is designed to measure or strategy the index

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and may be considered to reflect survivor/look ahead bias. Actual returns may differ significantly from, and

be lower than, back-tested returns. Past performance is not an indication or guarantee of future results.

Halifax House Price Index (HHPI) 2019 13

Typically, when S&P DJI creates back-tested index data, S&P DJI uses actual historical constituent-

level data (e.g., historical price, market capitalization, and corporate action data) in its calculations. As

ESG investing is still in early stages of development, certain datapoints used to calculate certain ESG

indices may not be available for the entire desired period of back-tested history. The same data availability

issue could be true for other indices as well. In cases when actual data is not available for all relevant

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of ESG data for the calculation of back-tested historical performance. “Backward Data Assumption” is a

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prior historical instances in the index performance. For example, Backward Data Assumption inherently

assumes that companies currently not involved in a specific business activity (also known as “product

involvement”) were never involved historically and similarly also assumes that companies currently

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methodology and factsheets of any index that employs backward assumption in the back-tested history

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calculates the index levels and performance shown or discussed but does not manage any assets.

Index returns do not reflect payment of any sales charges or fees an investor may pay to purchase the

securities underlying the Index or investment funds that are intended to track the performance of the

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securities/fund to be lower than the Index performance shown. As a simple example, if an index returned

10% on a US $100,000 investment for a 12-month period (or US $10,000) and an actual asset-based fee

of 1.5% was imposed at the end of the period on the investment plus accrued interest (or US $1,650),

the net return would be 8.35% (or US $8,350) for the year. Over a three-year period, an annual 1.5%

fee taken at year end with an assumed 10% return per year would result in a cumulative gross return of

33.10%, a total fee of US $5,375, and a cumulative net return of 27.2% (or US $27,200).

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Halifax House Price Index (HHPI) 2019 14

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