Housing Price Index Patterns by Metro & State
-- interactive table to view/rank/compare metros & states 2013Q3 - 2014Q3
December 2014. The Housing Price Index (HPI), calculated using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages, continued upward momentum in U.S. house prices remained strong in the third quarter 2014, as prices rose 0.9 percent from the previous quarter. This is the thirteenth consecutive quarterly price increase in the purchase-only, seasonally adjusted index.
As measured with purchase-only indexes for the 100 most populated metropolitan areas in the U.S., third quarter price increases were greatest in the San Jose-Sunnyvale-Santa Clara, CA MSA where prices increased by 6.6 percent. Prices were weakest in the Greensboro-High Point, NC MSA, where they fell 4.4 percent. Eleven of the 20 metropolitan areas with the highest annual appreciation rates were in California.
View the HPI integrated with other subject matter in the MetroDynamics Metro Profiles. Examples: Houston ... Charlotte.
Use the interactive table in this section to view/rank/compare the non-seasonally adjusted "all transactions" HPI for the most recent 5 quarters for all Metropolitan Statistical Areas (MSAs), states and the U.S.
Visual Analysis of 2013Q3-2014Q3 HPI Patterns
The following graphic shows housing value appreciation 2013Q3-2014Q3 by metro based on the HPI.
Click graphic for larger view and details. This view developed using CV XE GIS and related GIS project. Members of the ProximityOne User Group (join now, no fee) may used the CV XE GIS software and GIS project to create similar views with different HPI measures. Zoom-in. Add labels. Add other geography/data. Create views/graphics for reports and stories.
Join us in the Using TIGER/Line Shapefiles one hour no fee Web session. Learn about the mechanics of making the HPI thematic pattern view shown above. Create variations of this view or entirely different visual analysis GIS projects.
2014Q3 HPI and the 2013 (Current) Metro Designations
This section provides the 2014Q3, and historically revised, HPI data using the 2013 (current) vintage metros. About 2013 vintage metros ...
2013 vintage metros & component areas: http://proximityone.com/metros2013.htm
- interactive ranking/query table
metro principal city demographic-economic characteristics: http://proximityone.com/places.htm
- includes all U.S. cities/places - interactive ranking/query table
metro component county characteristics: http://proximityone.com/countytrends.htm
- includes all counties - interactive ranking/query table
Situation & Outlook
The Housing Price Index (HPI) provides a measure to examine/analyze housing price levels and variations among metros and states. Use the interactive table in this section to examine the HPI quarter to quarter over the past year by state and metro. The ranking table provides an easy way to rank/compare housing prices for a single metro area or a group of metros.
The HPI alone provides only partial insights -- based on this one measure. Evaluation of housing markets, and the regional economy, trends and patterns need to use the HPI in combination with many other measures. Situation & Outlook reports integrate HPI data with other demographic-economic measures.
Examine Patterns/Characteristics for Areas of Interest. Use S&O demographic-economic profiles to view characteristics of the housing market for geographic areas of interest. Click on a link in the upper right scroll box to view a sample. When the page opens, click on Housing Characteristics link to view details about housing for the comparative analysis areas.
Quarterly Update. The ranking table shows the latest quarterly HPI data (3rd quarter 2014) and preceding quarters for one year earlier. This table will be updated on February 26, 2015, with 4nd quarter 2014 data and related prior quarterly estimates and re-computed quarterly change values (last column).
Housing Price Index Interactive Ranking Table - 2013Q3 - 2014Q3
Ranking Tables Main | Metros Main
Click column header to sort; click again to sort other direction.
View percent change from same quarter last year (rightmost column).
Steps to Develop Custom HPI Pattern Analysis Maps (requires Windows computer with Internet connection)
1. Install the ProximityOne CV XE GIS
... run the CV XE GIS installer
... take all defaults during installation
2. Download the HPI GIS project fileset
... requires ProximityOne User Group ID (join now, no fee)
... unzip HPI GIS project files to local folder c:\hpigis
3. Open the c:\hpigis\hpi14q3.gis project
... after completing the above steps, click File>Open>Dialog
... open the file named c:\hpigis\hpi14q3.gis
4. Done. The start-up view is shown at top of this section.
About the Housing Price Index
The Housing Price Index (HPI) is a broad measure of the movement of single-family house prices. It serves as a timely, accurate indicator of house price trends at various geographic levels. It also provides housing economists with an analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas. The HPI is a measure designed to capture changes in the value of single-family houses in the U.S. as a whole, in various regions and in smaller areas. The HPI is published by the Federal Housing Finance Agency (FHFA) using data provided by Fannie Mae and Freddie Mac.
More About the HPI ... scroll section
ProximityOne User Group
Join the ProximityOne User Group to keep up-to-date with new developments relating to metros and component geography decision-making information resources. Receive updates and access to tools and resources available only to members. Use this form to join the User Group. There is no fee.
Support Using these Resources
Learn more about metros, metro geographic drill-down, housing market demographic economic data and related analytical tools. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.
ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.