Key information about Brazil Real Residential Property Price Index Growth

• Brazil Real Residential Property Price Index Growth was reported at 2.697 % in Sep 2024.
• This records an increase from the previous number of 2.661 % for Jun 2024.
• Brazil Real Residential Property Price Index Growth data is updated quarterly, averaging 2.202 % from Mar 2002 to Sep 2024, with 91 observations.
• The data reached an all-time high of 20.879 % in Dec 2009 and a record low of -11.342 % in Mar 2016.
• Brazil Real Residential Property Price Index Growth data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly: YoY %.

Land Registry Price Paid Data (PPD) have been published as open data since 2013. These data have been transformative for house price variation research in the UK as they are a comprehensive record of residential transactions at address level and cover the whole of England and Wales over a period dating back to 1995. Despite the utility of these data, a lack of attribute information relating to the properties, such as total floor area information, is identified as one of the major shortcomings of the PPD data. This means that the impacts of stock mix on broader price patterns cannot be fully accounted for. This research outlines one approach which addresses this deficiency by combining transaction information from the official open Land Registry Price Paid Data (PPD) with property size information form the official open Domestic Energy Performance Certificates (EPCs). A four-stage data linkage is created to generate a new linked dataset, representing 79% of the full market sales in the Land Registry PPD. This new linked dataset details 5,732,838 transactions in England and Wales between 2011 and 2019, along with each property's total floor area and the number of habitable rooms. Codes for other commonly used spatial units from Output Area to Local Authority are also included in the dataset. This offers greater flexibility for the exploration of house price variation in England and Wales at different spatial scales. The data collection includes the scripts used for linkage, as well as the resulting dataset.

Current residential house price variation research in the UK is limited by lack of an open and comprehensive house price database that contains both transaction price alongside dwelling attributes such as size. This research outlines one approach which addresses this deficiency in England and Wales through combining transaction information from the official open Land Registry Price Paid Data (PPD) and property size information form the official open Domestic Energy Performance Certificates (EPCs). A four-stage data linkage is created to generate a new linked data, representing 79% of the full market sales in Land Registry PPD. This new linked dataset offers greater flexibility for the exploration of house price (house price per square metre) variation in England and Wales at different spatial scales over postcode unit between 2011 and 2019.

The average costs for residential real estate across Ireland increased steadily over the past decade. The National Price Index reached 201.9 index point in June 2024, meaning that house prices increased by about 101.9 percent since 2012 - the base year for the index. Between June 2023 and June 2024, the price index exhibited an overall increase, with a minor decline in December 2023. In line with this upward trend, the house prices increased across every county.

Context

All residential properties sold in Ireland from 2010 to May 28th 2021 (28/05/21)

Content

• Date of sale (dd/MM/yyyy) | datatime64[ns]
• Address | string
• Postal Code | string
• County | string
• Price (€) | float32
• Not Full Market Price | int8
• VAT Exclusive | int8
• Description of Property | string
• Property Size Description | string

Acknowledgements

Data sourced from publicly available site - https://propertypriceregister.ie - Photo by Blake Wheeler on Unsplash

Inspiration

Granular property sale data in Ireland is openly available but is not easily accessible to the public in a meaningful way this .csv and .pkl file allow easier access and analysis.

Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q3 2024 about residential, HPI, housing, real, price index, indexes, price, and USA.

The figures of existing own homes are related to the stock of existing own homes. Besides the price indices, figures are also published about the numbers sold, the average purchase price, and the total sum of the purchase prices of the sold dwellings. The House Price Index of existing own homes is based on a complete registration of sales of dwellings by the Dutch Land Registry Office (Kadaster) and the (WOZ) value of all dwellings in the Netherlands. Indices may fluctuate, for example if a small number of a certain type of dwellings are sold. In such cases we recommended using the long-term figures. The average purchase price of existing own homes may differ from the price index of existing own homes. The change in the average purchase price, however, is not an indicator for price developments of existing own homes.

Data available from: 1st quarter 1995 to 4th quarter 2023

Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The numbers of existing owner-occupied sold homes can be recalculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

Changes as of 6 Juny 2024: This table has been discontinued. This table is followed by Existing own homes; purchase prices, price index 2020=100, type of dwelling. See paragraph 3.

From reporting period 2024 quarter 1, the base year of the House Price Index for Existing Dwellings (PBK) will be adjusted from 2015 to 2020. In April 2024, the first figures of this new series will be released. These figures will be available in a new StatLine table. The old series (base year = 2015) can still be consulted via StatLine, but will no longer be updated.

Key information about Lithuania Nominal Residential Property Price Index Growth

• Lithuania Nominal Residential Property Price Index Growth was reported at 8.865 % in Sep 2024.
• This records a decrease from the previous number of 10.356 % for Jun 2024.
• Lithuania Nominal Residential Property Price Index Growth data is updated quarterly, averaging 7.839 % from Dec 1999 to Sep 2024, with 100 observations.
• The data reached an all-time high of 55.634 % in Dec 2005 and a record low of -32.985 % in Sep 2009.
• Lithuania Nominal Residential Property Price Index Growth data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Nominal Residential Property Price Index: 2010=100: Quarterly: YoY %.

Key information about Thailand Gold Production

• Thailand Real Residential Property Price Index was reported at 137.701 2010=100 in Sep 2024.
• This records an increase from the previous number of 137.141 2010=100 for Jun 2024.
• Thailand Real Residential Property Price Index data is updated quarterly, averaging 111.975 2010=100 from Mar 1991 to Sep 2024, with 135 observations.
• The data reached an all-time high of 137.805 2010=100 in Dec 2023 and a record low of 83.224 2010=100 in Jun 1999.
• Thailand Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Dataset

This dataset was created by Brendan Hayes

Released under CC0: Public Domain

Contents

Actual price registration information for real estate sales cases, including target location (de-identified), area, total price and other information.

Housing Index in Portugal increased to 228.89 points in the third quarter of 2024 from 220.74 points in the second quarter of 2024. This dataset provides - Portugal House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Residential Property Prices for Spain (QESN628BIS) from Q1 1971 to Q3 2024 about Spain, residential, HPI, housing, price index, indexes, and price.

Housing Index in Ireland increased to 191.30 points in January from 191.20 points in December of 2024. This dataset provides the latest reported value for - Ireland Residential Property Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This repository is the second updated version of the attribute-linked residential property price dataset in UK Data Service ReShare 854240 (https://reshare.ukdataservice.ac.uk/854240/). As with the first updated version (ReShare 855033 https://reshare.ukdataservice.ac.uk/855033/) in 2021, this updated dataset contains individual property transactions and associated variables from both Land Registry Price Paid Dataset (LR PPD) and the Ministry for Housing, Communities and Local Government (MHCLG) Domestic Energy Performance Certificate (EPC) data. This is a linked result by address matching between LR-PPD data (1/1/1995-27/6/2022) and Domestic EPCs data (the twelfth version: ending with 30/6/2022). It is the whole of the 2022 update house price per square metre dataset published in the Greater London Authority (GLA) London Datastore (https://data.london.gov.uk/dataset/house-price-per-square-metre-in-england-and-wales).

The linked dataset in this repository is the uncorrected version, recording almost 20 million transactions with 106 variables in England and Wales between 1/1/1995 and 27/6/2022. We have offered technical validation and data cleaning code in UKDA ReShare 854240 to help users to evaluate the representation and to clean up the data. There is no unique way to clean this raw linked dataset, so we suggest users develop their own clean-up process based on their research requirements. In addition, this repository covers the original LR PPD and Domestic EPCs for the linked data (house price per square metre dataset). Similar to the first updated version, a field header has been added in LR PPD. Six variables (individual lodgement identifier, address, address 1, address 2, address 3, postcode) in Domestic EPCs are removed. A newly created unique identifier (id) is added in Domestic EPCs, this id is newly created for Version 12 Domestic EPCs. It is not the same id as in the Domestic EPCs from UK Data Service ReShare 854240 and ReShare 855033. Since November 2021 DLUCH has published Domestic EPCs with the Unique Property Reference Number (UPRN) hence the dataset in this repository contains the UPRN information from the Domestic EPCs.

Key information about France Nominal Residential Property Price Index

• France Nominal Residential Property Price Index was reported at 127.888 2010=100 in Sep 2024.
• This records an increase from the previous number of 125.984 2010=100 for Jun 2024.
• France Nominal Residential Property Price Index data is updated quarterly, averaging 42.824 2010=100 from Mar 1970 to Sep 2024, with 219 observations.
• The data reached an all-time high of 134.603 2010=100 in Sep 2022 and a record low of 6.112 2010=100 in Mar 1970.
• France Nominal Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Nominal Residential Property Price Index: 2010=100: Quarterly.

Key information about Portugal Gold Production

• Portugal Real Residential Property Price Index was reported at 165.055 2010=100 in Sep 2024.
• This records an increase from the previous number of 158.609 2010=100 for Jun 2024.
• Portugal Real Residential Property Price Index data is updated quarterly, averaging 112.245 2010=100 from Mar 2000 to Sep 2024, with 99 observations.
• The data reached an all-time high of 165.055 2010=100 in Sep 2024 and a record low of 80.037 2010=100 in Jun 2013.
• Portugal Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

This metadata document provides details of the data used for the dissertation: “Improving Commercial Property Price Statistics”. The study explores data related and methodological challenges in the construction of price statistics for commercial real estate.

Short abstract of the dissertation

Since the financial crisis of 2008, National Statistical Institutes (NSIs) have worked to develop commercial real estate (CRE) indicators for official statistics. These indicators are considered essential in financial stability monitoring and may help contain the consequences of future crises or even prevent future crises. However, progress at NSIs to develop these indicators has been slow due to challenges like low observation numbers and high heterogeneity. This dissertation addresses these challenges by exploring data issues and suggesting methodological improvements.

The first three studies focus on data challenges regarding share deals and portfolio sales. Both are real estate trading constructions that are specific to CRE. The results show that share deals and portfolio sales significantly differ from the rest of the market. Therefore, under specific circumstances, CRE indicators could benefit from including these trading types. The final two studies focus on methodological challenges regarding index construction methods and the role of sustainability in real estate pricing. The results show that, by combining established techniques, it is possible to construct price indices that meet official statistics’ standards. Furthermore, the results uncover a complex relationship between sustainability and prices: while energy efficiency generally involves price premiums, others aspects like health and environment display a discount for low sustainable properties.

Overall, this dissertation contributes to the legislative framework that is currently being developed for EU countries to publish official statistics for commercial real estate and adds to the academic discussion by presenting innovative techniques for data analyses and index construction.

Data sources

The following data sources were used:

1. Bussiness Register (Statistics Netherlands)
2. Transactions linked to the Register of Adresses and Buildings (BAG)
3. Linking table buildings and companies (Dutch Land Registry Office)
4. Property Transfer Tax data (Dutch Tax Authorities)
5. Building sustainability scores (W/E advisors)Commercial real estate transactions (Dutch Land Registry Office)
6. Commercial real estate transactions (Dutch Land Registry Office)

Processing methodology

1. The data is originally stored in an SQL database and is processed with SQL and R code (version 4.2). In the code, the name of the table is tbl_SPE_2_ABR_Bedrijfsinfo. The data is used for deriving company transfers by comparing ownership states of various periods. The first period that an ownership differs of the same company indicates an ownership transfer.
2. The data is originally stored in an SQL database and is processed with SQL and R code (version 4.2). In the code, the name of the table is tbl_SPE_6_ABR_CompleetMicro. The data is used for calcuting the size of real estate share deals and estimating price developments by applying appropriate filters and counting the output.
3. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is SPE_KADASTER. The data is used for finding real estate information that corresponds to company transfers by linking the company register (ABR) to the real estate register (BAG).
4. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is tbl_SPE_3_OVB_Bedrijfsinfo. The data is used for deriving real estate share deals by linking this table (Kadaster) to the real estate register (BAG).
5. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is duurzaamheid_input_regressie2. The data is used for finding the relationship between sustainabilty measures and real estate transaction prices by linking sustainabilty scores from a consultancy (WE) to transaction prices (Cadastre) and running regression analyses.
6. The data is originally stored in an SQL database and is processed with R code (version 4.2). In the code, the name of the table is tbl_OV20_pand. The data is used for 4 purposes (separate studies).

• (1) Chapter 3: Determining the price effect of portfolio sale by running regression analyses
• (2) Chapter 4: Developing methods to include portfolio sales in CPPI calcutions by using auxilary data of the real estate properties.
• (3) Chapter 5: Developing a price index method for small domains by using these data to test the outcomes
• (4) Chapter 6: Determining the relationship between sustatinability by running regression analyses

Data restrictions

As part of the CBS law, sharing micro-data outside of the CBS-environment is prohibited. Furthermore, CBS manages the data, but in some cases other parties are still formal owners of the data. The 2 other parties are The Land Registry Office and WE consultancy. Ownership and intellectual property rights are managed in contracts with both owners. It was agreed upon that the data can only be used for the purpose of the PhD study and that the microdata will never be externally disseminated. The data is still owned by them and the intellectual property rights of the analyses belong to me. An intended use of the microdata should be approved by both Statistics Netherlands and the formal data owner. Because of the above, no data can be publicly shared.

If one intends to do research on these data, an application for data use can be requested at CBS. CBS will charge costs for anonymising the data and providing a closed environment to work with the data. More information on this can be found at: https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research

Contact information

Author: Farley Ishaak

Statistics Netherlands | Henri Faasdreef 312 | P.O. Box 24500 | 2490 HA The Hague

TU Delft | Delft University of Technology | Faculty of Architecture and the Built Environment

Department of Management in the Built Environment | P.O. Box 5043 | 2600 GA Delft

M +31 6 46307974 | ff.ishaak@cbs.nl | f.f.ishaak@tudelft.nl