At CoreLogic, we take pride in supporting the needs of higher education by providing access to our vast repository of data. University Data Portal is a secure, easy-to-use website that provides residential and commercial real estate data for qualified academic research, including academic journals, dissertations, grant proposals, research papers and white papers.
The portal allows university faculty and students to run unique queries, extract data and download reports—all online and with preferred academic rates. To date, over half a billion records have been delivered from the University Data Portal.
Two additional datasets were recently added to the more than 500 million property characteristics (tax) and property transaction (deed) records available on University Data Portal. In addition, up to 10 years’ historical tax assessment records---158 million current year tax records, covering 99.9% of U.S property records---are available.
Now, to be even more useful to academic researchers, the portal includes:
University Data Portal is used by faculty and students at some of the nation’s most prestigious higher learning institutions. Recent examples of subjects covered by academia include:
New users will need to request access by registering. Once approved, users can submit and track data requests, view and respond to request emails, submit payments at preferred academic rates, and download data.
CoreLogic property data is widely used in academic research. Below are some examples of research papers submitted in past years as entries for the CoreLogic CLARC Excellence Award. Congratulations to 2014 winners, Ben Keys of the University of Chicago, Devin Pope of the University of Chicago and Jaren Pope of Brigham Young University. Their winning paper is featured below.
Households that fail to refinance their mortgage when interest rates decline can lose out on substantial savings. Based on a large random sample of outstanding U.S. mortgages in December of 2010, we estimate that approximately 20% of households for whom refinancing would be optimal and who appeared unconstrained to do so, had not taken advantage of the lower rates. We estimate the present-discounted cost to the median household who fails to refinance to be approximately $11,500.
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This paper assesses the predictive power of variables that measure market tightness, such as seller’s bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search-and-matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs data on residential units offered for sale through a real estate brokerin the Netherlands and for certain U.S. regions. Individual records are used to constructquarterly home price indices, an index that measures seller’s bargaining power, and (quality adjusted) home sale probabilities. Using conventional time-series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets.
Using data from Pennsylvania and New York and an array of empirical techniques to control for confounding factors, we recover hedonic estimates of property value impacts from shale gas development that vary with geographic scale, water source, well productivity, and visibility. Results indicate large negative impacts on nearby groundwater-dependent homes, while piped-water-dependent homes exhibit smaller positive impacts, suggesting benefits from lease payments. At a broader geographic scale, we find that new wellbores increase property values, but these effects diminish over time. Undrilled permits cause property values to decrease. Results have implications for the debate over regulation of shale gas development.
The recent housing bust precipitated a wave of mortgage defaults, with over seven percent of the owner-occupied housing stock experiencing a foreclosure. This paper presents a model that shows how foreclosures can exacerbate a housing bust and delay the housing market's recovery. By raising the ratio of sellers to buyers, by making buyers more selective, and by changing the composition of houses that sell, foreclosures freeze up the market for retail (non-foreclosure) sales and reduce both price and volume. Because negative equity is necessary for default, these general equilibrium effects on prices can create price-default spirals that amplify an initial shock. To assess the magnitude of these channels, the model is calibrated to simulate the downturn. The amplification channel is significant. The model successfully explains aggregate and retail price declines, the foreclosure share of volume, and the number of foreclosures both nationwide and across MSAs. While the model can explain variation in sales across MSAs, it cannot account for the aggregate level of the volume decline, suggesting that other forces have reduced sales nationwide. The quantitative analysis implies that from 2007 to 2011 foreclosures exacerbated aggregate price declines by approximately 50 percent and declines in the prices of retail homes by approximately 30 percent.
Despite more than a quarter of all new homes today being built to EPA’s ENERGY STAR standards and nine of ten consumers in a recent NAHB survey demanding efficient homes, the mainstream financial system has been slow to target or differentiate loans made to borrowers seeking to finance energy efficient properties. It is reasonable to assume that lower utility bills, increased asset value, and protection from energy price volatility should improve loan performance of homeowners in more energy-efficient houses. However, credit policy decisions surrounding energy efficiency have lacked substantial basis in empirical research.
This is the first academic study to provide such analysis on the risks and returns of investments in residential efficiency. Our study was conducted by UNC’s Center for Community Capital, a respected leader in mortgage research and policy analysis. A treatment/control design and multinomial logit model was used to estimate the impact of energy efficiency on two competing mortgage termination risks: default and prepay. Controlling for the standard set of explanatory variables, the authors find that mortgage default risks are on average 32% lower in ENERGY STAR homes.
The findings have warranted widespread attention and impacted public discourse on energy efficiency and credit policy decisions. The report has been covered extensively in the media, including nationally syndicated columnist Ken Harney, NBCNews.com, and Fox Business News, and been presented to representatives of the U.S. Senate Banking, Finance, and Energy Committees. The paper has also been submitted for journal review and will be presented at the upcoming 2013 National AREUEA conference and the 2013 ACEEE Finance Forum
This research project would have been impossible without our partnerships with RESNET, who provided ENERGY STAR home data, and CoreLogic’s generous CLARC grant award.We are grateful for this opportunity to work with the definitive source for mortgage research.
Using a novel combination of administrative and proprietary data from 2007 to 2011 on King County, WA (metro Seattle), I estimate the eect of owner-occupants' home equity on their probability of sale and, indirectly, mobility. I exploit plausibly exogenous variation that follows only from changes in local housing price indices, and I account for confounding economic conditions that vary by time and location. The estimates indicate that sales decline dramatically over the combined loan-to-value ratio range from approximately 70% to 100%, well before homeowners reach negative equity.
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