Data augmentation for housing prices
US Housing Data for 2008-2009 (pre crisis and crisis year) to predict housing prices more accurate
Housing price prediction competition on Kaggle
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Housing Index in the United Kingdom decreased to 511.60 points in June from 511.80 points in May of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Just as in many other countries, the housing market in the UK grew substantially during the coronavirus pandemic, fueled by robust demand and low borrowing costs. Nevertheless, high inflation and the increase in mortgage rates has led to house price growth slowing down. According to the forecast, 2024 is expected to see house prices decrease by ***** percent. Between 2024 and 2028, the average house price growth is projected at *** percent. A contraction after a period of continuous growth In June 2022, the UK's house price index exceeded *** index points, meaning that since 2015 which was the base year for the index, house prices had increased by ** percent. In just two years, between 2020 and 2022, the index surged by ** index points. As the market stood in December 2023, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next years. Growth is forecast to be stronger in 2024 and slow down in the period between 2025 and 2028. The rental market in London is expected to follow a similar trend, with Central London slightly outperforming Greater London.
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Using aggregate quarterly data for the period 1975:Q1-2010:Q4, I find that the US housing market changed from a stable regime with prices determined by fundamentals, to a highly unstable regime at the beginning of the previous decade. My results indicate that these imbalances could have been detected with the aid of real-time econometric modeling. With reference to Stiglitz's general conception of a bubble, I use the econometric results to construct two bubble indicators, which clearly demonstrate the transition to an unstable regime in the early 2000s. The indicators are shown to Granger cause a set of coincident indicators and financial (in)stability measures. Finally, it is shown that the increased subprime exposure during the 2000s can explain the econometric breakdown, i.e.?the housing bubble may be attributed to the increased borrowing to a more risky segment of the market.
The average resale house price in Canada was forecast to reach nearly ******* Canadian dollars in 2026, according to a January forecast. In 2024, house prices increased after falling for the first time since 2019. One of the reasons for the price correction was the notable drop in transaction activity. Housing transactions picked up in 2024 and are expected to continue to grow until 2026. British Columbia, which is the most expensive province for housing, is projected to see the average house price reach *** million Canadian dollars in 2026. Affordability in Vancouver Vancouver is the most populous city in British Columbia and is also infamously expensive for housing. In 2023, the city topped the ranking for least affordable housing market in Canada, with the average homeownership cost outweighing the average household income. There are a multitude of reasons for this, but most residents believe that foreigners investing in the market cause the high housing prices. Victoria housing market The capital of British Columbia is Victoria, where housing prices are also very high. The price of a single family home in Victoria's most expensive suburb, Oak Bay was *** million Canadian dollars in 2024.
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Graph and download economic data for Residential Property Prices for Japan (QJPN628BIS) from Q1 1955 to Q4 2024 about Japan, residential, HPI, housing, price index, indexes, and price.
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Graph and download economic data for Real Residential Property Prices for China (QCNR628BIS) from Q2 2005 to Q1 2025 about China, residential, HPI, housing, real, price index, indexes, and price.
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Research in modelling housing market dynamics using agent-based models (ABMs) has grown due to the rise of accessible individual-level data. This research involves forecasting house prices, analysing urban regeneration, and the impact of economic shocks. There is a trend towards using machine learning (ML) algorithms to enhance ABM decision-making frameworks. This study investigates exogenous shocks to the UK housing market and integrates reinforcement learning (RL) to adapt housing market dynamics in an ABM. Results show agents can learn real-time trends and make decisions to manage shocks, achieving goals like adjusting the median house price without pre-determined rules. This model is transferable to other housing markets with similar complexities. The RL agent adjusts mortgage interest rates based on market conditions. Importantly, our model shows how a central bank agent learned conservative behaviours in sensitive scenarios, aligning with a 2009 study, demonstrating emergent behavioural patterns.
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This dataset is about book subjects. It has 10 rows and is filtered where the books is Subprime nation : American power, global capital, and the housing bubble. It features 2 columns including publication dates.
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This paper utilizes quarterly panel data for 20 OECD countries over the period 1975:Q1-2014:Q2 to explore the importance of house prices and credit in affecting the likelihood of a financial crisis. Estimating a set of multivariate logit models, we find that booms in credit to both households and non-financial enterprises are important to account for when evaluating the stability of the financial system. In addition, we find that global housing market developments have predictive power for domestic financial stability. Finally, econometric measures of bubble-like behavior in housing and credit markets enter with positive and highly significant coefficients. Specifically, we find that the probability of a crisis increases markedly when bubble-like behavior in house prices coincides with high household leverage.
In this paper, the authors set out to date-stamp periods of US housing price explosivity for the period 1830–2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and when it recedes to long term stable prices. The first technique used is the Generalized sup ADF (GSADF) test procedure developed by Phillips, Shi, and Yu (Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500, 2013), which allows the recursive identification of multiple periods of price explosivity. The second approach makes use of Robinson’s (Efficient Test of Nonstationary Hypotheses, 1994) test statistic, comparing the null of a unit root process against the alternative of speced orders of fractional integration. The analysis date-stamps several periods of US house price explosivity, allowing us to contextualize its historic relevance.
This project will explore the impact of the economic recession on cities and households through a systematic comparison of the experiences of two English cities, Bristol and Liverpool.The research will use both quantitative and qualitative approaches. Interviews will be held in both cities with stakeholders from across the public, private and voluntary and community sectors. A social survey of 1000 households will also be conducted in the two cities covering 10 specific household types. A series of in-depth qualitative interviews will then be held with households drawn from the survey and chosen to illustrate the spectrum of experience.In the context of globalisation and the rescaling of cities and states, the research aims to develop our understanding of the relationship between economic crisis, global connectivity and the transnational processes shaping cities and the everyday lives of residents. It will explore the 'capillary-like' impact of the crisis and austerity measures on local economic development, and local labour and housing markets, as well as highlight the intersecting realities of everyday life for households across the life course.The research will document the responses and coping strategies developed across different household types and evaluate the impact and effectiveness of 'anti-recession' strategies and policies.
This data package includes the underlying data files to replicate the data and charts presented in Why China's housing policies have failed, PIIE Working Paper 23-5.
If you use the data, please cite as: Huang, Tianlei. 2023. Why China's housing policies have failed. PIIE Working Paper 23-5. Washington, DC: Peterson Institute for International Economics.
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Average House Prices in Canada decreased to 690900 CAD in May from 692400 CAD in April of 2025. This dataset includes a chart with historical data for Canada Average House Prices.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The result of variance decomposition of corporate R&D investment.
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Data augmentation for housing prices
US Housing Data for 2008-2009 (pre crisis and crisis year) to predict housing prices more accurate
Housing price prediction competition on Kaggle