Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
D.G. for Economic Statistics; S.G. for Short-Term Statistics; Housing Price Index Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
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1.5. Contact mail address
Avenida de Manoteras 50-52
28050 MADRID - SPAIN
1.6. Contact email address
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1.7. Contact phone number
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1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last update
6 November 2025
2.2. Metadata last certified
6 November 2025
2.3. Metadata last posted
6 November 2025
3.1. Data description
The House Price Index (HPI) is a quarterly indicator that measures the evolution of the transaction prices of dwellings that are purchased by households. Furthermore, the index measures pure price changes, differences in quality of the dwellings acquired in different periods are adjusted. Transaction prices include the value of land.
HPIs are based on harmonized definitions and concepts and they are calculated following methodological standards to ensure comparability of HPI indices across Member States.
3.2. Classification system
According to the Commission implementing regulation 2023/1470 (art. 3), the HPI covers the following expenditure categories:
H.1. Purchases of dwellings
H.1.1. Purchases of newly built dwellings
H.1.2. Purchases of existing dwellings.
3.3. Coverage - sector
Household sector.
3.4. Statistical concepts and definitions
Adjustment for quality and composition changes: Registration prices are adjusted in order to eliminate changes in the quality and composition of the dwellings transacted from one period to another.
Aggregate index: Weighted arithmetic mean of elementary indices.
Elementary index: Ratio of the estimated prices in the current quarter and in the last quarter of the previous year (multiplied by 100).
Interaction: Explanatory variable in the regression model, resulting from the combination of other explanatory variables (main effects) of the model.
Hedonic regression model: In the context of the HPI, the regression model connects dwelling prices and its different features, in order to estimate the implicit price of each one.
Weights: Weights for each dwelling typology represent the proportion of household expenditure incurred in the purchase of those dwellings.
Prices: The prices considered for calculating the national HPI are the transaction prices registered at the notaries, without taxes. For harmonized HPI series, VAT is added to the new dwelling’s prices. Transaction prices include the value of land.
Rate of change: This shows price changes from one time period to another.
Dwelling typology: Combination of the possible values of the variables or features (main effects in the regression model) that define each type of dwelling.
3.5. Statistical unit
Each index or rate of change refers to the expenditure by the household sector for acquiring residential property in the economic territory of Spain. Expenditure includes all acquisitions of residential property, covering transactions with other sectors and transactions that are internal to the household sector.
3.6. Statistical population
HPIs comprise all dwellings purchased in monetary transactions by households within the economic territory of Spain; those by both resident and non-resident households (i.e. 'domestic concept').
3.7. Reference area
Dwelling transactions cover the whole country.
3.8. Coverage - Time
Data are available from the fourth quarter of 2005.
3.9. Base period
The HPI is a Laspeyres chain index. The index reference period is 2015 = 100.
The reference period of prices is the fourth quarter of the previous year. Therefore, elementary indices (per dwelling typology) are calculated as a ratio of the estimated prices (from the regression model) in the current quarter and in the last quarter of the previous year. The reference period of weights is the last quarter of the previous year. Exactly, in accordance with the Laspeyres chain index formula, annual (expenditure) weights are calculated combining quantities (total square meters) of the dwellings transacted in the previous year with estimated prices (per square meter) of the last quarter of the previous year.
The set of dwelling typologies and their weights are updated every year.
Following units are used in data series:
index figures with current reference year: 2015 (unitless)
percentage changes on the previous quarter (quarterly rates)
percentage changes on the fourth quarter of the previous year (accumulated rates)
percentage changes on the same quarter of the previous year (annual rates)
percentage share of the total (weights)
total value of transactions expressed in national currency (€).
Quarter.
6.1. Institutional Mandate - legal acts and other agreements
EU level:
Regulation (EU) 2016/792 of the European Parliament and of the Council of 11 May 2016 on harmonised indices of consumer prices and the house price index
Commission implementing regulation 2023/1470 of 17 July 2023 laying down the methodological and technical specifications in accordance with Regulation (EU) 2016/792 of the European Parliament and of the Council as regards the house price index and the owner-occupied housing price index, and amending Commission Regulation (EU) 2020/1148.
National level:
Statistical National Plan 2021-2024 approved by Royal Decree 1110/2020, of December 15.
6.2. Institutional Mandate - data sharing
None.
7.1. Confidentiality - 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 (Article 13).
Law No. 15/1999 of December 13 on Protection of Personal Data, implemented by Royal Decree 1720/2007, contains provisions on confidentiality.
Royal Decree 994/1999, of 11 June, approves the Regulation on Mandatory Security Measures for the Computer Files which contain Personal Data.
7.2. Confidentiality - data treatment
According to policy rules (see point 7.1).
8.1. Release calendar
INE publishes the national HPI, approximately 70 days after the end of the reference quarter. The same date, the harmonized Spanish HPI is sent to Eurostat. The prices considered for calculating the Spanish HPI (that INE publishes) are the transaction prices registered at the notaries, without taxes. For harmonized HPI series (used for the calculation of the European HPI), VAT is added to the new dwelling’s prices. In addition, the way weights are calculated is different, in HPI as one-year average instead of two-years used in national HPI.
The advance release calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.
The data are released simultaneously to all interested parties. At the time the information is published on the website, the press release is sent to the main users.
INE publishes a quarterly press release highlighting the main changes in national HPI (IPV). An English version is available. This includes detailed results (per region and separately for new and second-hand dwellings) of the reference quarter.
The figures sent to Eurostat are not disseminated by INE.
10.2. Dissemination format - Publications
The following annual publications include National HPI results:
National House Price Index database National HPI data (indices, rates of change and weights) are available on INE website.
10.4. Dissemination format - microdata access
Microdata are not publicly available. However, researchers may request access through special agreements with the INE for strictly scientific purposes. Access would be granted only after the approval of a research proposal and the signing of a confidentiality agreement, ensuring compliance with national data protection legislation. In the case of the HPI, no microdata information is provided so far.
10.5. Dissemination format - other
There are two papers on the national HPI in the following specialized magazines:
The quality of the HPI is assured to be very high. Its concepts and methodology follows the recommendations of the Technical Manual on Owner-Occupied Housing.
The use of an administrative source to obtain the data reduces the cost of the survey without affecting the accuracy of the indices. The sample used to calculate the indicator is almost exhaustive which allows highly accurate results to be published.
In addition, the HPI production includes validation and consistency controls to detect and correct errors in the data file received, which makes the precision and reliability of the final data very high.
11.2. Quality management - assessment
For the calculation of the HPI (National HPI and the figures sent to Eurostat), approximately 95% of the housing transactions made in the reference quarter are included.
Every year, priority quality indicators are calculated for HPI.
12.1. Relevance - User Needs
The main users are the Spanish Central Bank, the Ministry of Finance, financial institutions and economic analysts.
The most important HPI use is to measure the dwelling price evolution over time in the national territory and by region.
The harmonised Spanish HPI can be considered suited for cross-country economic comparisons of the evolution of house prices.
12.2. Relevance - User Satisfaction
Some satisfaction surveys are carried out periodically.
12.3. Completeness
Indices are provided for all, existing and newly built dwellings.
13.1. Accuracy - overall
The use of administrative data to calculate the HPI allows a high degree of accuracy and reliability of this statistics.
Almost all housing transactions made in the quarter (approximately 95%) enter in the HPI calculation. The production process of the index includes different actions to control the quality of the data and results, such as debugging, imputation of missing values and analysis of outliers.
Furthermore, the index measures pure price changes, a combination of stratification and hedonics is applied to adjust for quality changes in features and location of the dwellings acquired in different periods.
13.2. Sampling error
Not applicable.
13.3. Non-sampling error
Data files for HPI calculation include around 95% of the deeds held in the reference quarter. Therefore, the non-response rate is about 5%.
An automatic procedure is applied to detect errors in the records, some of them are automatically solved and others have to be analyzed one by one.
14.1. Timeliness
The national HPI is published each quarter according to a pre-announced schedule, approximately 70 days after the end of the reference quarter.
House Sales indicators are not published by INE, only data are sent to Eurostat publication.
14.2. Punctuality
Since it was launched in October 2008, the national HPI has always been published on the pre-announced release dates.
HPI/House Sales data have been delivered to Eurostat always before t+85 days (according to Reg. 2016/792).
HPI data are normally sent to Eurostat approximately in t+70, and House Sales (HS) indicators ten days later, in t+80.
15.1. Comparability - geographical
HPI data are fully comparable across Spanish regions.
15.2. Comparability - over time
HPI data are fully comparable over time.
15.3. Coherence - cross domain
HPI indices are fully consistent.
Nowadays, there are many statistics on housing prices in Spain. When comparing their results in terms of coverage, concepts and methods, the HPI appears to be the only one that focuses on transaction prices in the household sector and adjusts for quality changes. In the public sector, there is another official statistic on housing prices published by the Ministry for Public Works. It provides average prices (instead of price evolution) and is based on appraisal values (instead of transaction prices). In addition, the methodology does not include adjustments for quality changes and quantities change every quarter. Therefore, the results of both official indicators are different, although they show similar trends.
15.4. Coherence - internal
HPIs are internally coherent. Aggregates are compiled from the lowest level of detail to the highest, both geographical and functional.
The costs for production of HPI/HS data involve only employment cost, the administrative data used is free (then costs for purchasing data and cost of respondent burden are 0€).
17.1. Data revision - policy
The Spanish HPI/HS data are definitive from the first time they are published and they are not subject to systematic revisions.
17.2. Data revision - practice
Spanish HPI datafrom 2008to 2012 were revisedand sent to Eurostat in June, in orderto include VAT in newlybuilt dwelling prices and to calculate the weights using one year information (intead of three), as state in Regulation (EU) 2016/792 and Implementing Regulation (EU) 2023/1470 on OOH.
HPI indexes and weights are compiled basing on administrative sources, which are the same for both newly built and existing dwellings.
18.1.2. Weights
The source for HPI weights, both internal and external, is the same as for transaction prices: notaries.
18.1.3. Source data - House Sales indicators
The notaries database is the source used to calculate HS indicators.
18.2. Frequency of data collection
Data on dwelling transactions are received on a monthly basis. Data received in a given month (t) includes all notary acts signed during the previous four months (t-1, t-2, t-3 and t-4).
For the calculation of the HPI, data files are received six weeks later, (q+45) approximately 95% of the dwelling transactions made in the quarter are included.
Data files received a month later (q+75), with approximately 98% of total transactions are used for HS calculation.
18.3. Data collection
Data are received in electronic format.
18.4. Data validation
The validation procedure consists of the following tasks:
treatment of multi-object transactions. Transactions including more than one object (dwellings, garages, storage rooms) have a specific treatment in order to obtain one register per dwelling. The corresponding value of the rest of objects (garage or storage room) is excluded from the price, when possible. If there is no way to separate them, the total price is recorded and the variables garage and storage room are imputed to indicate it
study and correction of incoherent values in geographical variables (when municipalities and postcodes do not match). They are automatically detected but solved manually, consulting the complete address on the internet, and correcting the municipality or the postcode
control of extreme values. Based on the first model estimations, around 2% dwellings are filtered out as outliers and excluded from further index calculations. Thus, this procedure is objective and all explanatory variables are taken into account in order to determine whether a value is extreme or not. Nevertheless, an initial filter for extremely high/low values (for prices and surfaces) is made before applying the model. Surfaces are imputed using Cadaster information, however prices are never imputed
analysis and imputation of values. Sometimes, checking the cadastral information on the surface, errors in the type of dwelling (flat/house) are detected and consequently corrected. Also, some values of the variable floor are revised and corrected if they are errors, sometimes simultaneously mistakes in the type of dwelling are rectified.
During the production process, a number of data checks are performed. Indices for different strata are compiled but are not published, because they are used only for validation purposes.
18.5. Data compilation
See below.
18.5.1. Calculation and Aggregation
See below.
18.5.1.1. Index formulae
HPI is a Laspeyres-type price index.
18.5.1.2. Aggregation method
Elementary indices, per dwelling typology, are calculated as a ratio of the estimated prices (from the regression model) in the current quarter and in the last quarter of the previous year. These indices are aggregated using weights based on transaction values according to the Laspeyres formula.
18.5.1.3. Derivation of sub-index and elementary aggregate weights
The source for HPI weights, is the same as for transaction prices: notaries. The weight for each dwelling typology represents the household expenditure on that kind of dwellings in the reference period. The set of dwelling typologies and their weights are updated every year.
Reference period of current weights: The last quarter of the previous year. Exactly, in accordance with the Laspeyres chain index formula, annual (expenditure) weights are calculated combining quantities (total square meters) of the dwellings transacted in the previous year with estimated prices (per square meter) of the last quarter of the previous year.
HPI weights are updated annually.
18.5.1.4. Price updating
The weight reference period is the previous year, t-1. Exactly, quantities are based on transactions in t-1, and prices used for the weights calculation are estimated prices of the fourth quarter of the previous year.
Elementary aggregate weights are price-updated to the fourth quarter of the previous year, taking into account how weights are calculated: in accordance with the Laspeyres chain index formula, annual (expenditure) weights are calculated combining quantities (total square meters) of the dwellings transacted in the previous year with estimated prices (per square meter) of the last quarter of the previous year.
18.5.1.5. Chaining and linking method
The indices in base 2015 are obtained linking the indices referring to the fourth quarter of the previous year, according to the Laspeyres chain-index formula.
Therefore, indices are annually chained and the linking period is the fourth quarter of the previous year.
18.5.1.6. Compilation of sub-indices
A combination of stratification and hedonics is applied to adjust for quality changes in the features and location of the dwellings transacted from one period to another.
18.5.1.6.1. Hedonic method
Average characteristics method is used to calculate HPI. A semi-logarithmic equation is used, where the logarithm of the price per square meter is the dependent variable. The following dwelling characteristics are included in the model:
type of dwelling (flat/house)
new/second-hand
garage (Yes/No)
storage room (Yes/No)
cooperative (Yes/No)
area (10 intervals)
floor (6 categories)
cluster of provinces (6 groups)
municipality size (4 categories)
tourist municipality (4 types)
type of district (classification of postcodes in 14 groups).
The model is applied quarterly and the parameter estimations represent the implicit prices of the characteristics. Prices are estimated for a fixed set of dwelling typologies over the year. Annual weights per dwelling typology are combined with estimated prices each quarter, so that the indices capture pure price changes. The regression model is revised annually.
Average characteristics method is used to calculate HPI.
18.5.1.6.3. Stratification
Average characteristics method is used to calculate HPI.
18.5.2. Other processing issues
See below.
18.5.2.1. Timing for pricing
The price of the dwelling is the price recorded in the transfer of ownership. Therefore transactions enter the index on the date indicated in the notary act, when the sale takes place.
18.5.2.2. Treatment of VAT
Newly built dwelling prices do not include VAT in National HPI, VAT is added for the HPI transmitted to Eurostat.
18.5.2.3. Treatment of other taxes
Taxes other than VAT are not included in the price of dwellings.
18.5.2.4. Treatment of government subsidies
Subsidised houses are excluded from HPI, they represent around 3% of the total dwelling transactions. In this type of housing, surfaces and prices are regulated by the Authorities, as a condition to benefit from specific advantages of both, financial and fiscal nature. Buyers must also meet some conditions regarding their properties, family income, etc.
18.5.2.5. Treatment of land
The price of land is included in both prices and weights.
18.5.2.6. Housing cooperatives
Housing cooperatives are included in HPI; they represent around 0.5% of total dwelling transactions. They are identified in the regression model by a dichotomous variable. So, the coefficient corresponding to cooperatives reflects a price reduction. Therefore, it is taken into account in the HPI quality adjustment.
18.5.2.7. Treatment of non-market transactions
Ordinary transactions and cooperatives are included in the HPI/HS calculation, inheritances and other types of operations outside the free market are not considered.
18.5.2.8. Treatment of multi-object transactions
Transactions including more than one object (dwellings, garages, storage rooms) have a specific treatment in order to obtain one register per dwelling. The corresponding value of the rest of objects (garage or storage room) is excluded from the price, when possible. If there is no way to separate them, the total price is recorded and the variables garage and storage room are imputed to indicate it.
18.5.2.9. Treatment of fractional transactions
There is a single notarial act even if there is more than one purchaser of the house.
18.5.2.10. Outliers detection
Based on the first model estimations, around 2% of the dwellings are filtered out as outliers and excluded from further index calculations. Thus, this procedure is objective and all explanatory variables are taken into account in order to determine whether a value is extreme or not. Nevertheless, an initial filter for extremely high/low values (for prices and surfaces) is made before applying the model. Surfaces are imputed using Cadaster information, however prices are never imputed.
18.5.2.11. Treatment of incomplete data source coverage
Data received are completed, but extreme surface and other detected errors (in geographical variables, floor or type of dwelling) are imputed when the correct values are available in internet or in the Cadaster information.
In addition, the explanatory variable that is a classification of the postcodes sometimes its value has to be imputed, when a district is not classified (because a few transactions of dwellings belong to this postcode were transmitted in the previous year). The average of the classifications of the rest of the postcodes in the same municipality is automatically assigned.
18.6. Adjustment
No adjustments other than quality adjustment are applied to the HPI data.
None.
The House Price Index (HPI) is a quarterly indicator that measures the evolution of the transaction prices of dwellings that are purchased by households. Furthermore, the index measures pure price changes, differences in quality of the dwellings acquired in different periods are adjusted. Transaction prices include the value of land.
HPIs are based on harmonized definitions and concepts and they are calculated following methodological standards to ensure comparability of HPI indices across Member States.
6 November 2025
Adjustment for quality and composition changes: Registration prices are adjusted in order to eliminate changes in the quality and composition of the dwellings transacted from one period to another.
Aggregate index: Weighted arithmetic mean of elementary indices.
Elementary index: Ratio of the estimated prices in the current quarter and in the last quarter of the previous year (multiplied by 100).
Interaction: Explanatory variable in the regression model, resulting from the combination of other explanatory variables (main effects) of the model.
Hedonic regression model: In the context of the HPI, the regression model connects dwelling prices and its different features, in order to estimate the implicit price of each one.
Weights: Weights for each dwelling typology represent the proportion of household expenditure incurred in the purchase of those dwellings.
Prices: The prices considered for calculating the national HPI are the transaction prices registered at the notaries, without taxes. For harmonized HPI series, VAT is added to the new dwelling’s prices. Transaction prices include the value of land.
Rate of change: This shows price changes from one time period to another.
Dwelling typology: Combination of the possible values of the variables or features (main effects in the regression model) that define each type of dwelling.
Each index or rate of change refers to the expenditure by the household sector for acquiring residential property in the economic territory of Spain. Expenditure includes all acquisitions of residential property, covering transactions with other sectors and transactions that are internal to the household sector.
HPIs comprise all dwellings purchased in monetary transactions by households within the economic territory of Spain; those by both resident and non-resident households (i.e. 'domestic concept').
Dwelling transactions cover the whole country.
Quarter.
The use of administrative data to calculate the HPI allows a high degree of accuracy and reliability of this statistics.
Almost all housing transactions made in the quarter (approximately 95%) enter in the HPI calculation. The production process of the index includes different actions to control the quality of the data and results, such as debugging, imputation of missing values and analysis of outliers.
Furthermore, the index measures pure price changes, a combination of stratification and hedonics is applied to adjust for quality changes in features and location of the dwellings acquired in different periods.
Following units are used in data series:
index figures with current reference year: 2015 (unitless)
percentage changes on the previous quarter (quarterly rates)
percentage changes on the fourth quarter of the previous year (accumulated rates)
percentage changes on the same quarter of the previous year (annual rates)
percentage share of the total (weights)
total value of transactions expressed in national currency (€).
See below.
See below.
Quarterly.
The national HPI is published each quarter according to a pre-announced schedule, approximately 70 days after the end of the reference quarter.
House Sales indicators are not published by INE, only data are sent to Eurostat publication.
HPI data are fully comparable across Spanish regions.
