House price and sales index (prc_hpi_inx)

1.1. Contact organisation

Statistical Service of Cyprus (CYSTAT)

1.2. Contact organisation unit

Prices

1.3. Contact name

Confidential because of GDPR

1.4. Contact person function

Confidential because of GDPR

1.5. Contact mail address

Statistical Service of Cyprus

CY-1444

Nicosia

Cyprus

1.6. Contact email address

Confidential because of GDPR

1.7. Contact phone number

Confidential because of GDPR

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) measures changes in the selling prices of dwellings (including the value of land) purchased by households. Both newly built and existing dwellings are covered. The land component of the residential property is included.

3.2. Classification system

The HPIs are classified according to the following 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

ESA 2010 Sector S.14 (Household Sector).

3.4. Statistical concepts and definitions

The following data are available:

• Index HPI 2015=100;
• Percentage change compared to same quarter of the previous year;
• Percentage change compared to the previous quarter of the same year.

HPI measures the price change of residential dwellings in the reference period compared to the base period. All transactions of residential dwellings are included. Non-marketed prices (e.g., self-built  dwellings) are excluded. Residential dwellings bought for uses other than owner-occupancy are included (e.g., to rent it out). New and old dwellings are included.

Index figures for purchases of dwellings are compiled on the basis of full transaction price which includes the value of land. HPI is a Laspeyre’s type index as the Harmonized Index of Consumer Prices. Annual weights are the expenditure shares of strata in the previous year.

3.5. Statistical unit

Residential property transactions.

3.6. Statistical population

All  transactions of residential dwellings.

3.7. Reference area

Government controlled areas of the Republic of Cyprus.

3.8. Coverage - Time

Data are available since the first quarter of 2010.

3.9. Base period

2015=100.

Index figures can be interpreted as follows:

Index equals 100 in the base period. For any other period the index represents the amount that the buyer would have to spend on average in that period to buy a residential property having a value of 100 in the base period.

HPI is compiled quarterly. 

6.1. Institutional Mandate - legal acts and other agreements

Article 3 of the national Official Statistics Law, No. 25(I) of 2021 defines the functions of the Statistical Service of Cyprus regarding the production and dissemination of official statistics. Moreover, Article 13, explicitly stipulates the mandate for data collection and introduces a mandatory response to statistical enquiries by stipulating the obligation of respondents to reply to surveys and provide the data required. This relates not only to national but also to European statistics which, by virtue of Article 8 of the said Law, are incorporated in the annual and multiannual programmes of work without any further procedure.

• Commission Regulation (EU) 2016/792;
• EU regulation 2023/1470;
• Statistics Law No. 25(I) of 2021.

6.2. Institutional Mandate - data sharing

Not available.

7.1. Confidentiality - policy

Official statistics are released in accordance to all confidentiality provisions of the following:

• National Statistics Law No. 25(I) of 2021 (especially Article 16 on statistical confidentiality).
• Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality).
• European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
• CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.

7.2. Confidentiality - data treatment

The treatment of confidential data is regulated by CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.

8.1. Release calendar

Notifications about the dissemination of statistics are published in the release calendar, which is available on CYSTAT’s website. The annual release calendar, announced during the 4^th quarter of each year, includes provisional dates which are finalised the week before publication. 

8.2. Release calendar access

CYSTAT’s release calendar.

8.3. Release policy - user access

According to the Dissemination and Pricing Policy of the Statistical Service of Cyprus (section 2.3) CYSTAT΄s main channel for dissemination of statistics is the web portal, which offers the same conditions to everyone and is updated at the same time every working day (12:00 noon). No privileged pre-released access is granted.

In addition to the annual release calendar, users are informed of the various statistical releases through the 'Alert' service provided by CYSTAT.

Quarterly.

10.1. Dissemination format - News release

CYSTAT prepares a  press release and relevant tables for dissemination of quarterly HPI data.

10.2. Dissemination format - Publications

Not available.

10.3. Dissemination format - online database

All data concerning HPI is available on the website under the statistical theme Economy and Finance / House Price Index.

10.4. Dissemination format - microdata access

Statistical micro-data from CYSTAT’s surveys are accessible for research purposes only and under strict provisions as described below:

• Under the provisions of the Statistics Law, CYSTAT may release microdata for the sole use of scientific research. Applicants have to submit the request form 'Application for data for research purposes' giving thorough information on the project for which micro-data are needed.
• The application is evaluated by CYSTAT’s Confidentiality Committee and if the application is approved, a charge is fixed according to the volume and time consumed for preparation of the data. Micro-data may then be released after an anonymisation process which ensures no direct identification of the statistical units but, at the same time, ensures usability of the data. 

10.5. Dissemination format - other

The publication of the HPI is also made with an announcement to the media.

10.6. Documentation on methodology

HPI methodology is available on Eurostat’s website, under 'Housing Price Statistics'.

10.7. Quality management - documentation

On CYSTAT's website, an HPI metadata document is published in both Greek and English language.

11.1. Quality assurance

The quality of statistics in CYSTAT is managed in the framework of the  European Statistics Code of Practice which sets the standards for developing, producing and disseminating European Statistics as well as the ESS Quality Assurance Framework (QAF). CYSTAT endorses the Quality Declaration of the European Statistical System. In addition, CYSTAT is guided by the requirements provided for in Article 11 of the Statistics Law No. 25(I) of 2021 as well as Article 12 of Regulation (EC) No 223/2009 on European statistics, which sets out the quality criteria to be applied in the development, production and dissemination of European statistics.

11.2. Quality management - assessment

The quality of the House Price Index is assessed on the basis of the Technical manual on Owner-Occupied Housing and House Price Indices published by Eurostat. Every effort is made in order to maintain and improve the quality of the House Price Index.

12.1. Relevance - User Needs

The HPI interests all the users that follow  the developments in the house price market.

12.2. Relevance - User Satisfaction

Since 2008 (with the exception of 2010, 2013 and 2020) CYSTAT carries out an annual online 'Users Satisfaction Survey'. The results of the surveys are available on CYSTAT’s website. 

Overall, there is a high level of satisfaction of the users of statistical data published by CYSTAT.

12.3. Completeness

The HPI and all required sub-indices are transmitted to Eurostat quarterly.

13.1. Accuracy - overall

No estimates for overall accuracy of HPI are produced.

13.2. Sampling error

Not applicable.

13.3. Non-sampling error

No estimates of non-sampling errors are produced.

14.1. Timeliness

Data are transmitted to Eurostat according to the OOH Regulation (indices: 85 days after the reference period and weightsin June of the year following the year to which the weights relate). 

14.2. Punctuality

The HPI data is transmitted to Eurostat according to the transmission calendar and within 85 days after the end of the reference period.

15.1. Comparability - geographical

It is possible to compare the Cypriot House Price Index with the House Price Indices of other Member States.

15.2. Comparability - over time

For the period 2010-2014, a proxy for the indicator of luxury dwellings was used. An indicator of luxury dwellings  based on real data has been used since the first quarter of 2015. Although it is assumed that the proxy is a good approximation of the indicator, this change may cause a break in the series.

15.3. Coherence - cross domain

The OOHPI may partly overlap the scope of the HPI. The Central Bank of Cyprus (CBC) compiles a Residential Property Price Index based on property valuations. The Royal Institution of Chartered Surveyors in Cyprus publishes a quarterly price index that tracks property across all districts and across all property types in Cyprus.

15.4. Coherence - internal

All figures are checked for internal consistency.

Οnly the cost of employees.

17.1. Data revision - policy

A data revision policy is in place at CYSTAT. It is published on CYSTAT’s website, at the following document (Revision Policy).

17.2. Data revision - practice

The main reasons for revisions are new or revised datasets, calculation mistakes or revisions of the compilation method.

18.1. Source data

 See below.

18.1.1. Prices

The administrative data source that is used for newly built dwellings and for existing dwellings - prices and weights - is the Department of Lands and Surveys, Ministry of Interior.

18.1.2. Weights

The administrative data source used for both prices and weights is the Department of Lands and Surveys, Ministry of Interior.

18.1.3. Source data - House Sales indicators

The land's registry data are used.

18.2. Frequency of data collection

Quarterly.

18.3. Data collection

Administrative data are received quarterly from the Department of Lands and Surveys, Ministry of Interior. CYSTAT has allocated staff to the Department of Lands and Surveys in order to collect additional data needed for contracts of sales. CYSTAT has also come to an agreement with the Department of Lands and Surveys to receive all the necessary data regarding sales. 

18.4. Data validation

Data are checked for internal consistency.Particularly, a validation file with consistency tests is used to verify that there are no inconsistencies.

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

In order to calculate the sub-indices for old and newly built dwellings, a Rolling Year Hedonic Regression Model is used. These sub-indices are then aggregated together using transaction-based weights in order to produce the HPI. Therefore, the overall aggregate index is fully consistent with its component indices.

18.5.1.3. Derivation of sub-index and elementary aggregate weights

Calculation of weights

In order to calculate weights the following method is used:

For the 1^st quarter of each year, the annual weights of the previous year are used since the base period is the 4^th quarter of the previous year. In order to calculate these weights the following formulae are used: 

where p_i, is the transaction price for dwelling i, N₁ is the number of transactions of old dwellings for the previous year and N₂ is the number of transactions of new dwellings for the previous year and N₀=N₁ + N₂ is the number of transactions of all  dwellings for the previous year. 

For the 2^nd quarter the weights of the previous year are updated to the 1^st quarter of the year (which is the base period) in the following way:

where I_old1 is the HPI for old dwellings in the first quarter and I_new1 is the HPI for new dwellings in the first quarter (with base period the last quarter of the previous year).

For the 3^rd quarter the weights of the previous quarter are updated to the 2^nd quarter of the year (which is the base period) in the following way: 

where I_old2 is the HPI for old dwellings in the 2^nd quarter and I_new2 is the HPI for new dwellings in the 2^nd quarter (with base period the first quarter of the year).

For the 4^th quarter the weights of the previous quarter are updated to the 3^rd quarter of the year (which is the base period) in the following way: 

where I_old3 is the HPI for old dwellings in the 3^rd quarter and I_new3 is the HPI for new dwellings in the 3^rd quarter (with base period the second quarter of the year).

18.5.1.4. Price updating

The weights reference period is t-1.

18.5.1.5. Chaining and linking method

The Rolling Year Hedonic Regression Model which is a Time dummy variable hedonic approach is used for the production of a chain-linked index.

18.5.1.6. Compilation of sub-indices

Method of calculation of the index in each stratum

In order to calculate the sub-indices for old and newly built dwellings, a hedonic model of the following form is used in each stratum:

where p is the price, X is the matrix of characteristics, I_t, I_t-1, I_t-2 are the time dummy variables for the quarter t and the previous two quarters, respectively and ε are the error terms.

The rolling window method uses a rolling window length of M=4 quarters.

An initial regression model is estimated and the appropriate indices are calculated using data pertaining to the first M=4 quarters of the data set, where M is the window length, i.e. the number of periods used in each regression. In our case, the dataset includes all transactions of dwellings for all quarters from 2010 and the initial regression is based on the first 4 quarters of 2010.

For the next quarter, a new regression model is estimated where the data consist of the initial data less the data for period (quarter) 1 of 2010 but adding the data for period (quarter) M+1= 5, in our case the 1st quarter of 2011. Appropriate price indices are calculated for this new regression model, but only the rate of increase/decrease of the index from period M to M+1 is used to update the previous sequence of M index values. Given the estimated parameters of the model , the index from period M to M+1 is calculated as the ratio:

This procedure is continued with each successive regression dropping the data of the previous earliest period and adding the data for the next period, with one new update factor being added with each regression.

18.5.1.6.1. Hedonic method

Method of calculation of the index in each stratum

In order to calculate the sub-indices for old and new dwellings, a hedonic model of the following form is used in each stratum:

where p is is the price, X is the matrix of characteristics, I_t, I_t-1, I_t-2  are the time dummy variables for the quarter t and the previous two quarters, respectively and ε are the error terms. 

The rolling window method uses a rolling window length of M=4 quarters.

An initial regression model is estimated and the appropriate indices are calculated using data pertaining to the first M=4 quarters of the data set, where M is the window length, i.e. the number of periods used in each regression. In our case, the dataset includes all transactions of dwellings for all quarters from 2010 and the initial regression is based on the first 4 quarters of 2010.

For the next quarter, a new regression model is estimated where the data consist of the initial data less the data for period (quarter) 1 of 2010 but adding the data for period (quarter) M+1= 5, in our case the 1st quarter of 2011. Appropriate price indices are calculated for this new regression model, but only the rate of increase/decrease of the index from period M to M+1 is used to update the previous sequence of M index values. Given the estimated parameters of the model 

the index from period  M to M+1 is calculated as the ratio:

.

This procedure is continued with each successive regression dropping the data of the previous earliest period and adding the data for the next period, with one new update factor being added with each regression.

18.5.1.6.2. SPAR method

Not applicable.

18.5.1.6.3. Stratification

Strata

Existent and newly built dwellings.

18.5.2. Other processing issues

 See below.

18.5.2.1. Timing for pricing

For newly built dwellings the price is recorded when the binding contract is signed and the contract of sale is submitted to the Department of Lands and Surveys. For second hand dwellings the price is recorded when the contract of sale is signed and submitted to the Department of Lands and Surveys or when the Title Deed is transferred to the new owner.

18.5.2.2. Treatment of VAT

VAT is included in the price of new dwellings.

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

Dwellings purchased with the use of government subsidies are not included in the index compilation.

18.5.2.5. Treatment of land

The price of land is included in both prices and weights.

18.5.2.6. Housing cooperatives

Not applicable.

18.5.2.7. Treatment of non-market transactions

Non-market transactions such as inheritances are not included in the analysis.

18.5.2.8. Treatment of multi-object transactions

Transactions that include more than one property are single out by property.

18.5.2.9. Treatment of fractional transactions

Fractional transactions are excluded.

18.5.2.10. Outliers detection

Outliers are detected using Cook's distance method. The Cook's distance is calculated using SPSS (ANALYZE-LINEAR REGRESSION-SAVE-COOK'S) for all the available observations for the four quarters (the current and the three previous quarters) . Observations with Cook's distance greater than 4/n where n is the number of observations are considered as outliers.

18.5.2.11. Treatment of incomplete data source coverage

Since the data for contracts of sales on the excel file are not of good quality, staff is allocated by CYSTAT at the district offices of DLS to collect contracts of sales from physical files. A standard template is used for the collection of data for contracts of sales.

18.6. Adjustment

No adjustments other than quality adjustment are applied to the HPI data.

None.

The House Price Index (HPI) measures changes in the selling prices of dwellings (including the value of land) purchased by households. Both newly built and existing dwellings are covered. The land component of the residential property is included.

6 November 2025

The following data are available:

• Index HPI 2015=100;
• Percentage change compared to same quarter of the previous year;
• Percentage change compared to the previous quarter of the same year.

HPI measures the price change of residential dwellings in the reference period compared to the base period. All transactions of residential dwellings are included. Non-marketed prices (e.g., self-built  dwellings) are excluded. Residential dwellings bought for uses other than owner-occupancy are included (e.g., to rent it out). New and old dwellings are included.

Index figures for purchases of dwellings are compiled on the basis of full transaction price which includes the value of land. HPI is a Laspeyre’s type index as the Harmonized Index of Consumer Prices. Annual weights are the expenditure shares of strata in the previous year.

Residential property transactions.

All  transactions of residential dwellings.

Government controlled areas of the Republic of Cyprus.

HPI is compiled quarterly. 

No estimates for overall accuracy of HPI are produced.

Index figures can be interpreted as follows:

Index equals 100 in the base period. For any other period the index represents the amount that the buyer would have to spend on average in that period to buy a residential property having a value of 100 in the base period.

 See below.

 See below.

Quarterly.

Data are transmitted to Eurostat according to the OOH Regulation (indices: 85 days after the reference period and weightsin June of the year following the year to which the weights relate). 

It is possible to compare the Cypriot House Price Index with the House Price Indices of other Member States.

For the period 2010-2014, a proxy for the indicator of luxury dwellings was used. An indicator of luxury dwellings  based on real data has been used since the first quarter of 2015. Although it is assumed that the proxy is a good approximation of the indicator, this change may cause a break in the series.