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Housing Price Index (HPI)

• 1Contact
  • 1.1Contact organisation
    National Statistics Institute of Spain
    
  • 1.5Contact mail address

    Avenida de Manoteras 50-52 - 28050 Madrid

    
    
• 2Metadata update
  • 2.1Metadata last certified
    05/03/2024
  • 2.2Metadata last posted
    08/06/2022
  • 2.3Metadata last update
    05/03/2024
• 3Statistical presentation
  • 3.1Data description

    The objective of the Housing Price Index (HPI) is to measure the evolution of the sale price of free-market housing acquired by resident and non-resident households in Spain.

  • 3.2Classification system
    • Comunidades y Ciudades Autónomas
      01   Andalucía
      02   Aragón
      03   Asturias, Principado de
      04   Balears, Illes
      05   Canarias
      06   Cantabria
      07   Castilla y León
      08   Castilla - La Mancha
      09   Cataluña
      10   Comunitat Valenciana
      11   Extremadura
      12   Galicia
      13   Madrid, Comunidad de
      14   Murcia, Región de
      15   Navarra, Comunidad Foral de
      16   País Vasco
      17   Rioja, La
      18   Ceuta
      19   Melilla
    • Estado de la vivienda
      1   Vivienda nueva
      2   Vivienda usada
        .
  • 3.3Sector coverage

    The HPI covers all transactions for homes acquired by private households - residents and non-residents - within the economic territory. Homes acquired by legal persons or financial entities thus fall outside the scope of this indicator.

  • 3.4Statistical concepts and definitions
    • Adjustment due to change in quality
      Adjustment of certification prices in order to remove changes in composition and quality of dwellings transferred between one period and another.
    • Aggregate index
      Weighted arithmetic average of basic indices.
    • Índice elemental por tipología de vivienda
      Cociente entre el precio estimado en el trimestre corriente y el precio estimado en el cuarto trimestre del año anterior, para cada tipología multiplicado por 100.
    • Interaction
      Interaction: Regression model explanatory variable, obtained as a combination of other explanatory variables (main effects) of the model.
    • Reference period of the base index or period
      Period for which the average for indices equals 100, in the HPI, in the year 2007 (2007=100).
      
      With the calculation formula used for the HPI (linked Laspeyres) the reference period of the prices varies each year, and is the last quarter of the year immediately prior to the year considered.
    • Product or aggregate weight
      The weight of a product or aggregate is the relative importance it has in relation to the rest of products or aggregates in the basket, according to expenditure/income.
    • Prices
      The prices considered for calculating the HPI are dwelling certification prices, without taxes.
    • Contribution
      The contribution of a product measures how much the general index would change if only the price of the aforementioned product changed (in other words, if the other prices remain constant).
    • Variation
      This shows the evolution of prices between the time periods.
    • Second-hand housing
      Dwelling subject to second and successive transfers in the merchanting deed.
    • New housing
      Dwelling subject to the first transfer in the merchanting deed, normally carried out by the developer or builder in favour of the first purchaser.
    • Dwellings acquired by households within the econom
      This includes all types of dwelling, whether new or second-hand, flats or single-family dwellings, and regardless of the means of payment. According to HICP criteria, this excludes subsidised housing, as access to such housing is restricted to one part of the population.
  • 3.5Statistical unit

    The HPI studies the evolution of the prices of homes purchased by households within the Spanish economic territory.

  • 3.6Statistical population

    All households that purchase a home within Spanish territory, both residents and non-residents.

  • 3.7Reference area

    The geographical scope is made up of the entire national territory (the 52 provinces).

    The results are available at the national level and by autonomous community.

  • 3.8Time coverage

    The survey is carried out on a quarterly basis.

    The index series start in the first quarter of 2007.

  • 3.9Base period

    Index reference period or base period

    The reference period of the index or base period is the year 2015 (2015=100).

    Price reference period

    The period with whose prices current prices are compared; that is, the period used to calculate the elementary indices.

    With the calculation formula used for the HPI (Chained Laspeyres), the reference period for prices varies each year and is the last quarter of the year immediately prior to that considered.

    Reference period of the weightings

    The period to which the expenses used in the calculation of the index weightings refer. The weightings are said to be hybrid when the quantities of one period are valued at the prices of another period. In this case, the reference period of the weighting is the period to which the quantities refer.

    The weightings are updated annually.

    For the HPI, the reference period of the weightings is that formed by the two previous calendar years. The quantities obtained with the information for the two years are valued at the fourth quarter prices for the last available year.

• 4Unit of measure
  • 4.1Unit of measure

    The series published in the INE have the following units of measurement:
    - Indices: without unit.
    - Variations in quarterly prices, so far this year and annually: both per hundred.
    - Weightings: both per hundred.

• 5Reference period
  • 5.1Reference period

    The reference period of the data is the quarter.

    Data referred to the period: Trimestral A: 2023 TRI: IV

• 6Institutional mandate
  • 6.1Legal acts and other agreements

    The compilation and dissemination of the data are governed by the Statistical Law No. 12/1989 "Public Statistical Function" of May 9, 1989, and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2021-2024, approved by Royal Decree 1110/2020, of 15  December, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2021-2024. (Statistics of the State Administration).

    
    

    In February 2013, Commission Regulation (EU) No. 93/2013 was approved, which establishes the provisions for the application of Regulation (EC) No. 2494/95, relating to harmonised consumer price indexes, in which refers to the elaboration of price indices for owner-occupied dwellings.

    Regulation (EU) 2016/792 of the European Parliament and of the Council on harmonised consumer price indices and the house price index, approved in May 2016, repeals Regulation (EC) No. 2494/95. This Regulation establishes a common framework for the development, preparation and dissemination of harmonized consumer price indices and the home price index on a national and Union scale.

    The HPI is used as the basis for obtaining the indicators included in this Regulation: the housing price index harmonised with the rest of the countries of the Union (HPI), and the price index for owner-occupied housing (OOHI).

  • 6.2Data sharing
    The exchanges of information needed to elaborate statistics between the INE and the rest of the State statistical offices (Ministerial Departments, independent bodies and administrative bodies depending on the State General Administration), or between these offices and the Autonomic statistical offices, are regulated in the LFEP (Law of the Public Statistic Function). This law also regulates the mechanisms of statistical coordination, and concludes cooperation agreements between the different offices when necessary.
    

    The information used in HPI preparation is obtained from the registry of notaries. The General Council of Notaries through the Notarial Certification Agency (ANCERT) supplies the data to the INE for statistical use.

• 7Confidentiality
  • 7.1Confidentiality - policy

    The Statistical Law No. 12/1989 specifies that the INE cannot publish, or make otherwise available, individual data or statistics that would enable the identification of data for any individual person or entity. Regulation (EC) No 223/2009 on European statistics stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society

    
    
  • 7.2Confidentiality - data treatment
    INE provides information on the protection of confidentiality at all stages of the statistical process: INE questionnaires for the operations in the national statistical plan include a legal clause protecting data under statistical confidentiality. Notices prior to data collection announcing a statistical operation notify respondents that data are subject to statistical confidentiality at all stages. For data processing, INE employees have available the INE data protection handbook, which specifies the steps that should be taken at each stage of processing to ensure reporting units' individual data are protected. The microdata files provided to users are anonymised.
    

    The information disseminated is aggregated and the microdata are not available to the public.

• 8Release policy
  • 8.1Release calendar

    The advance release calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.

    
    
  • 8.2Release calendar access

    The calendar is disseminated on the INEs Internet website (Publications Calendar)

    
    
  • 8.3User access

    The data are released simultaneously according to the advance release calendar to all interested parties by issuing the press release. At the same time, the data are posted on the INE's Internet website (www.ine.es/en) almost immediately after the press release is issued. Also some predefined tailor-made requests are sent to registered users. Some users could receive partial information under embargo as it is publicly described in the European Statistics Code of Practice

    
    
• 9Frequency of dissemination
  • 9.1Frequency of dissemination

    The HPI is disseminated quarterly.

• 10Accessibility and clarity
  • 10.1News release

    The results of the statistical operations are normally disseminated by using press releases that can be accessed via both the corresponding menu and the Press Releases Section in the web

    
    
  • 10.2Publications

    Press release, the day of publication.

    Generic publications such as Spain in Figuresand Statistical Yearbook of Spain contain information related to the HPI.

  • 10.3On-line database

    INEbase is the system the INE uses to store statistical information on the Internet. It contains all the information the INE produces in electronic formats. The primary organisation of the information follows the theme-based classification of the Inventory of Statistical Operations of the State General Administration . The basic unit of INEbase is the statistical operation, defined as the set of activities that lead to obtaining statistical results on a determined sector or subject based on the individually collected data. Also included in the scope of this definition are synthesis preparation.

    
    

    Access to the HPI online database, which contains information on both indices and variations and weightings, is as follows:

    https://www.ine.es/dyngs/INEbase/en/operacion.htm?c=Estadistica_C&cid=1254736152838&menu=ultiDatos&idp=1254735976607

    The number of queries to the data tables in 2022 was AC1=257,780 accesses and the number of acceses to metadata was AC2=2,533.

     

  • 10.4Micro-data access
    A lot of statistical operations disseminate public domain anonymized files, available free of charge for downloading in the INE website Microdata Section
    

    In the case of the HPI, no microdata information is provided.

  • 10.5Other

    All information related to this index is published on the INE website.

  • 10.6Documentation on methodology

    The IPV methodology can be consulted at:

    https://www.ine.es/daco/daco42/ipv/metodologia2015.pdf

     

    Publications in specialized magazines:

    - In the Statistics and Operations Research Bulletin (BEIO): “The regression model in the House Price Index," Volume 28 Number 23 / October 2012

    https://www.seio.es/beio/BEIOVol28Num3.pdf

    - In the Spanish Statistical Magazine: “Using the hedonic method to adjust for quality changes: the HPI experience". Number 179 / Third quarter of 2012

    https://www.ine.es/ss/Satellite?L=0&c=INERevEstad_C&p=1254735226759&pagename=ProductosYServicios%2FPYSLayout&_charset_=utf-8&cid=1259941931757

     

    The completion rate for the metadata is AC3=100%.

  • 10.7Quality documentation

    Since the IPV is a statistic based on administrative records and uses practically the entire population for its elaboration, sampling errors are not calculated.

    Fields 10.6 to 17 of this document are the user-oriented quality report for this operation.

• 11Quality management
  • 11.1Quality assurance

    Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 16 principles, gathered in three areas: Institutional Environment, Processes and Products. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, Self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation.

    
    

    The IPV is a high quality statistic. Its methodology follows the recommendations of the "Technical Manual on Home Ownership and House Price Indices," prepared by Eurostat and agreed upon by the countries of the European Union (EU), with the aim of harmonizing the calculation of price indices housing in the EU:

    http://ec.europa.eu/eurostat/documents/7590317/0/Technical-Manual-OOH-HPI-2017/

    Since it is a statistic based on administrative records, practically the entire population is used for the calculation, which allows for highly accurate results to be published.

    In addition, the HPI elaboration process has established automatic controls to detect and correct errors in the data file received, as well as a subsequent manual purification and validation process, in order to guarantee their quality.

  • 11.2Quality assessment

    Since the HPI uses administrative records, the sample used to calculate the indicator is nearly exhaustive. At present, the publication of the HPI includes approximately 95% of the transfers of dwellings made during the reference quarter.

    The use of an administrative source to obtain the data reduces the cost of the survey without affecting the accuracy of the indices. In addition, to ensure such accuracy, the data go through validation and consistency checks between the variables used, which ensures that the accuracy and reliability of the final data is very high.

    Likewise, since the beginning of its publication, the publication deadlines have been reduced on two occasions.

• 12Relevance
  • 12.1User needs

    The main users of the HPI are the Bank of Spain, the Ministry of the Economy, other public administrations, companies and financial institutions, economic analysts and universities.

    The IPV is used to measure the evolution of the housing purchase price over time.

  • 12.2User satisfaction

    The INE has carried out general user satisfaction surveys in 2007, 2010, 2013,  2016 and 2019 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...

    On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date.(Click  next link)

     

    
    

    In response to the demand for more detailed information, starting in 2010, indexes were published by type of home (new and second-hand) by autonomous community. Until then, only regional data were published for all dwellings.

  • 12.3Completeness

    Indices are prepared for new and second-hand homes and for all homes.

    The mandatory statistical result rate available for HPI is R1=100%.

• 13Accuracy and reliability
  • 13.1Overall accuracy

    The use of administrative data for the calculation of the HPI allows for a high degree of statistical precision and reliability.

    The publication contains practically all home sales made during the quarter. In addition, in the index production process, different actions are carried out to control the quality of the data and the results, such as debugging errors, imputation of missing values, and analysis of outliers.

    In addition, the HPI places special emphasis on the adjustment for changes that occur in the composition and quality of the dwellings that are part of index calculation, from one quarter to the next. An econometric model is used, which makes this statistic different compared to those previously produced from the public sector.

  • 13.2Sampling error

    Since statistics obtain the information from a record, not by sampling, this concept is not applicable.

  • 13.3Non-sampling error

    A control of non-sampling errors is carried out throughout the statistical process.

    The data files for calculating the HPI have around 95% of the deeds signed in the reference quarter. However, in 2022 this percentage was one point lower. Therefore, the non-response rate per unit is about A4=5%.

    On the other hand, applications have been developed to detect and reduce the possible errors included in the records and to estimate the possible lack of information in some variables.

    The imputation rate is A7=0.21%.

• 14Timeliness and punctuality
  • 14.1Timeliness

    Since 2014, HPI results, at all levels of disaggregation, are published approximately 70 days after the reference quarter, therefore, TP2=70 days.

  • 14.2Punctuality

    Survey results are published according to theINE short-term statistics calendar of publications (https://www.ine.es/daco/daco41/calen.htm)

    Since the beginning of its publication, in October 2008, the HPI has been disclosed on the date announced in said publication calendar, therefore, TP3=0.

• 15Coherence and Comparability
  • 15.1Comparability - geographical

    The HPI data are fully comparable between regions. The calculation method of this statistical operation, in all its phases, is the same across the entire national territory.

  • 15.2Comparability - over time

    The IPV data are fully comparable over time, from the start of the series (first quarter 2007).

    In February 2024, the length of the comparable data series is CC2=68 quarters.

  • 15.3Coherence - cross domain

    There are many statistics currently available that offer information on the price of housing in Spain.

    In particular, and from the public sector, the statistics on Housing Prices published by the Ministry of Development pursues objectives that are distinct from the HPI, such as providing average prices. To do this, it uses another source of information (home appraisal values provided by ATASA) and uses another calculation methodology (quality adjustment is not performed).

    Though they show similar trends, the results of the surveys are not the same, since they have different objectives, data sources and methodologies.

    Furthermore, the HPI is consistent with the harmonised housing price index (also HPI, 2), likewise prepared by the INE, and sent to Eurostat for the calculation of a house price indicator of the Monetary and European Union.

    However, since the HPI is conceived to obtain a harmonised measure of the evolution of housing prices, it has certain methodological differences with the HPI in question:

    - The new home price index in the HPI(2) includes VAT, while the HPI does not.

    - The HPI(2) weighting are calculated using housing sales information relative to the last year, and two years of information are used to calculate the weightings in the HPI.

  • 15.4Coherence - internal

    The HPIs are internally consistent. Aggregations are made from the lowest level of information to the highest, both geographically and functionally.

• 16Cost and burden
  • 16.1Cost and burden

    The cost of the National HPI is 108.11 thousand euros, according to the budgetary forecasts of the 2024 Annual Program.

    Since it is a statistic based on administrative records, there is no burden on the informants.

     

• 17Data revision
  • 17.1Data revision - policy

    The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (link).

    This general policy sets the criteria that the different type of revisions should follow:  routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.

    
    

    The HPI data are definitive from the first time it is published and therefore are not subject to revision.

  • 17.2Data revision - practice
• 18Statistical processing
  • 18.1Source data

    The source of information used to calculate the HPI is the registry of notaries, which contains, among other data, the official prices of all sales that have taken place in the Spanish territory. This is the best source, taking into account the criteria of information availability, timeliness, coverage and content.

    The database of notaries, in addition to the home transfer price, contains detailed information regarding quality of the house: exact location, size, type of house, etc.

  • 18.2Frequency of data collection

    The General Council of Notaries through the Notarial Certification Agency (ANCERT) periodically sends the INE information on home transfers. Data on transfers during the previous four months are received monthly. In each shipment, the previous monthly files are updated.

    Data files received approximately a month and a half after the index reference period are used to calculate the HPI; these contain around 95% of the housing transactions carried out in the quarter.

  • 18.3Data collection

    The data is received by e-mail in electronic format.

  • 18.4Data validation

    The data validation process focuses mainly on the variables related to the house’s size and its location (the most relevant characteristics in the price of the property). In this process, the following basic tasks are carried out:

    1. Study and correction of geographic inconsistencies (postal code not belonging to the municipality). These errors are automatically detected and resolved, one by one.
    2. Control of extreme values. Most of the outliers are detected through the residuals of the regression model. It is therefore an objective procedure, in which all explanatory variables are jointly analysed to determine whether an observation is atypical or not. However, before applying the regression model, a basic analysis of extreme values is carried out, in the area and the price. The cadastral information of homes with surface area outside the established limits is reviewed.
    3. Assignment of variables. The information received is complete; however, in some observations where errors have been detected in the variables: municipality, postal code, surface area or type of dwelling, the correct values are assigned. .
  • 18.5Data compilation

    The HPI is a chained Laspeyres index.

    - Calculation of indices

    In the first place, the elementary indices are calculated as the quotient of estimated prices (using the regression model) for each type of reference quarter housing from the last quarter of the previous year.

    Subsequently, the elementary indices are added using a weighted arithmetic mean.

    - Weightings

    The weightings of each type of dwelling represent the expenditure on the purchase of that type of dwelling with respect to the total expenditure on the purchase of a dwelling, in the reference period.

    Due to the dynamism of the real estate market, the HPI updates the set of housing types and their weightings on an annual basis to represent the market situation as accurately as possible.

    The annual weightings are obtained using quantities of homes sold in the previous two calendar years valued at prices estimated in the fourth quarter of the previous year.

    - Quality setting

    The objective of the HPI is to measure the "pure" evolution of housing transaction prices, meaning that the prices observed must be adjusted to exclude changes in the composition and quality of housing transferred from one period to another.

    The method used by HPI to adjust for quality combines stratification with a regression model. The latter allows us to define the strata or types of dwellings in more detail and considerably improve the fit.

    As explanatory variables, the econometric model includes the main characteristics of the home as well as its location. To obtain some of these characteristics (groups of provinces, municipalities and postal codes) information from other sources is used.

    The variables included in the model are the following:

    - Type of home (flat/single-family)

    - New/second hand

    - Garage (s/n)

    - Storage room (s/n)

    - Cooperative (s/n)

    - Surface (10 intervals)

    - Floor (6 categories)

    - Cluster of provinces (6 groups)

    - Municipality size (4 classes)

    - Tourist (4 categories)

    - Environment type (14 types)

    In addition, the model includes some of the most important double interactions.

    Each quarter, an estimate of the model parameters is obtained; these represent the implicit characteristic prices; therefore, the method applied consists of estimating the prices for all types of housing included in the calculation each quarter.

    These estimated prices are used to calculate the elementary indices.

    The model is subject to yearly revision; new variables may also be incorporated to update those created from other sources, with the latest available information.

  • 18.6Adjustment

    No adjustments have been made

• 19Comment
  • 19.1Comment