Graph and download economic data for Residential Property Prices for Cyprus (QCYN628BIS) from Q1 2002 to Q2 2025 about Cyprus, residential, HPI, housing, price index, indexes, and price.

Housing Index in Cyprus increased to 113.99 points in the second quarter of 2025 from 113.71 points in the first quarter of 2025. This dataset provides - Cyprus House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about House Prices Growth

• Cyprus house prices grew 4.7% YoY in Jun 2025, following an increase of 4.8% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2007 to Jun 2025, with an average growth rate of 2.8%.
• House price data reached an all-time high of 19.0% in May 2023 and a record low of 0.7% in Jul 1974.

Cyprus Market Capitalisation: CSE: Real Estate data was reported at 67,085,700.000 EUR in Mar 2020. This records a decrease from the previous number of 72,004,373.000 EUR for Feb 2020. Cyprus Market Capitalisation: CSE: Real Estate data is updated monthly, averaging 73,383,787.000 EUR from Dec 2019 (Median) to Mar 2020, with 4 observations. The data reached an all-time high of 75,438,769.000 EUR in Dec 2019 and a record low of 67,085,700.000 EUR in Mar 2020. Cyprus Market Capitalisation: CSE: Real Estate data remains active status in CEIC and is reported by Cyprus Stock Exchange. The data is categorized under Global Database’s Cyprus – Table CY.Z002: Cyprus Stock Exchange: Market Capitalisation.

Cyprus - Housing cost overburden rate: Tenant, rent at market price was 14.40% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Cyprus - Housing cost overburden rate: Tenant, rent at market price - last updated from the EUROSTAT on December of 2025. Historically, Cyprus - Housing cost overburden rate: Tenant, rent at market price reached a record high of 19.90% in December of 2012 and a record low of 11.20% in December of 2020.

The data in this dataset is collected from FRED.

I decided to create this dataset while reading the research paper Factors Affecting House Prices in Cyprus: 1988-2008 by Panos Pashardes & Christos S. Savva. This research paper is extremely informative and covers a lot of details regarding the macroeconomics involved in real estate market. So I would recommend you all to go through it once.

NOTE:

This dataset will be updated over a period of time and include the following: - Macroeconomic factors with quarterly, monthly frequencies. - Microeconomic factors such as house type, age, location, size (BR, BA, carpet area/built-up area), facilities, view, disability functions, region, house prices, etc.

NOTE 2:

I recommend you all to check the file in this dataset with the title Housing_Macroeconomic_Factors_US (2).csv, it includes both the supply and demand factors associated with the housing market.

General Defintions:

1. Macroeconomic Factors

• House_Price_Index: House price change according to the index base period set (you can check the date at which this value is 100).
• Stock_Price_Index: Stock price change according to the index base period set (you can check the date at which this value is 100).
• Consumer_Price_Index: The Consumer Price Index measures the overall change in consumer prices based on a representative basket of goods and services over time.
• Population: Population of USA (unit: thousands).
• Unemployment_Rate: Unemployment rate of USA (unit: percentage).
• Real_GDP: GDP with adjusted inflation (Annual version unit: billions of chain 2012 dollars in, Monthly version unit: Annualised change).
• Mortgage_Rate: Interest charged on mortgages (unit: percentage).
• Real_Disposable_Income (Real Disposable Personal Income): Money left from salary after all the taxes are paid (unit: billions of chain 2012 dollars).
• Inflation: Decline in purchasing power over time (unit: percentage). [Forgot to remove this column in Annual version since CPI is one of the measures used to determine inflation].

What can you do with this dataset?

• Perform statistical analysis, find significant features & find the value by which these features affect the house price index (recommend to use a percentage change instead of index).
• Perform multivariate regression and predict the price of houses using microeconomic features (soon).

Thanks! If you like this dataset, I'll appreciate it if you give this dataset a vote! Discussions, suggestions & doubts are always welcome. Happy Learning!!

In December 2024, the floor space of office buildings in the central business districts in Tokyo covered around **** million tsubo. The total floor area of office buildings with a standard floor area of 100 tsubo or more has increased by almost *** million tsubo over the past decade.