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.

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.

Building contractors and developers depend on various socio-economic factors, including property values, underlying sentiment in the housing market, the degree of optimism among downstream businesses and credit conditions. All of these drivers typically track in line with economic sentiment, with recent economic shocks spurring a difficult period for building contractors and developers. Nonetheless, the enduring need for building services, particularly to tackle housing shortages across the continent, ensures a strong foundation of work. Revenue is forecast to grow at a compound annual rate of 2.3% to reach €1.3 trillion over the five years through 2025. Operational and supply chain disruption caused by the pandemic reversed the fortunes of building contractors and developers in 2020, as on-site activity tumbled and downstream clients either cancelled, froze or scaled back investment plans. Aided by the release of pent-up demand and supportive government policy, building construction output rebounded in 2021. Excess demand for key raw materials led to extended lead times during this period, while input costs recorded a further surge as a result of the effects of rapidly climbing energy prices following Russia’s invasion of Ukraine. Soaring construction costs and the impact of interest rate hikes on both the housing market and investor sentiment led to a renewed slowdown in building construction activity across the continent. However, falling inflation and the start of an interest rate cutting cycle have spurred signs of a recovery in new work volumes, supporting anticipated revenue growth of 2.3% in 2025. Revenue is forecast to increase at a compound annual rate of 6.7% to €1.7 trillion over the five years through 2030. Activity is set to remain sluggish in the medium term, as weak economic growth and uncertainty surrounding the impact of the volatile global tariff environment on inflation and borrowing costs continue to weigh on investor sentiment. Contractors and developers will increasingly rely on public sector support, including measures to boost the supply of new housing, as countries seek to tackle severe housing shortages. Meanwhile, the introduction of more stringent sustainability requirements will drive demand for energy retrofits.

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!!