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Housing Price Index by 5-Digit ZIP Code
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July 2016. Of the 17,931 5-digit ZIP codes tabulated, 8,074 experienced a decrease in housing value during the period 2010 to 2015. At the same time, 8,672 ZIP code areas experienced an increase in housing value. These data are based on experimental estimates of the Housing Price Index (HPI) by 5-digit ZIP code based in part on home sales price data from Fannie Mae- and Freddie Mac-acquired mortgages. See more about these data and FAQs.

  • Use the interactive table below to view, rank, compare the HPI
    .. for all 5-digit ZIP code area for which the data are available.
  • Use GIS tools described below to develop thematic pattern maps.
    .. add your own data & geography, select different HPI measures or criteria.
    .. zoom to different geographic extents, label and modify colors as desired.

  • Gaining Insights in Housing Prices, Conditions & Markets
    .. Characteristics, Patterns & Trends
    .. one hour web session -- overview & connectivity details

Patterns of Housing Value Change by ZIP Code: 2010-15
The following graphic shows patterns of housing value appreciation by ZIP Code: 2010-15 for the Houston metro (bold brown boundary). The color patterns/intervals are shown in the inset legend. Data are not available, using the criteria applied (2000 base year), for areas not colored In the larger view (click graphic), ZIP codes are labeled with HPI percent change from 2010 to 2015. Click graphic for larger view. Expand browser to full window for best quality view. Use the GIS tools described below to develop thematic pattern maps for a range of data and criteria.

.. view developed using the CV XE GIS software.
.. click map for larger view and details.

Additional views:
  • Atlanta area
    .. illustrates use of ZIP code and 2010-15 ZIP housing value appreciation as labels
  • New York City area
  • Washington, DC area
  • Los Angeles area

Examining Recent Trends; Current Estimates & Projections
The interactive table below presents annual HPI data 2010 through 2015. A much larger set of these ZIP codes show a negative change between 2010 and 2015 compared to the one year change 2014-2015; The data generally show more ZIP codes experiencing housing value appreciation 2014-2015 compared to the longer period 2010 to 2015. These trends underscore the importance of having more recent data for use in analysis, planning and decision-making. The next update based on transaction data will be May 2017 or later.

ProximityOne uses the HPI transaction data with other data to develop HPI current estimates (2016) and annual projections to 2021 with quarterly updates as a part of the Regional Demographic-Economic Modeling System (RDEMS). Experimental county-up (metro, state, U.S.) and sub-county estimates and projections are planned for the fall 2016 quarterly update. The model based estimates and projections of the number of units by type and value that are added to the housing stock to compute a variation of the HPI.

Interactive Table
Use the interactive table below to examine the Housing Price Index (HPI) by 5-digit ZIP code. Key considerations in using this table and data include:
  • only ZIP codes for which the HPI is tabulated are included in the table.
  • there are three rows for each ZIP code corresponding to different HPI base years.
    .. use the "Base" drop-down to select one of these base years; start with "03" see details about base year
    .. when/if the HPI values are all 0 for a ZIP, the HPI values are not available for this Type/Base year

Housing Price Index by 5-Digit ZIP Code: 2010-2015 -- interactive table
  Use mouse-over on header column to view extended item/column name.
  Click ShowAll button between Find/Queries. See usage notes below table.
  Related ranking tables: http://proximityone.com/rankingtables.htm.
 


Usage Notes
  Use mouse-over on header column to view extended item/column name.
  Click ShowAll button to reset table.

  • View a range of ZIP codes using base year 2000 (one row per ZIP):
    .. Click ShowAll button to reset table.
    .. Key in low-end ZIP value in edit box where default value 01001 is showing.
    .. Key in high-end ZIP value in edit box where default value 99901 is showing.
    .. Click "ZIP Min-Max" button; table refreshes showing only ZIP codes in that range.

  • Locate ZIP codes for a city of interest:
    .. Option 1
    .. Click ShowAll button to reset table.
        - Key in part of city name (case sensitive) in edit box where default value San Diego is showing.
        - Click "Find in City" button; table refreshes showing only rows with matching city name value.
    .. Option 2 (too many cities with same name)
    .. Click ShowAll button to reset table.
        - Select State using drop-down button below table at left.
        - Click City column header cell; table sorts on this column.
        - Scroll down table to locate city name of interest.

Usage considerations:
  • any particular ZIP code may occur with one, two or three base years.
    .. that is the reason all three base years are included.
  • if a Type filter is applied, ZIP codes of interest may not appear in the refreshed table.
  • the percentage change, 2010 to 2015, will be the same regardless of base year.
  • compare how one ZIP code has changed relative to others while staying within the same base year.
  • a high percent change 2010-2015 compare might be misleading
    .. some zips experiencing large decreases after 2008 have experienced some rebound 2010 forward.

Column Descriptions
- ZIP5
- City
- State
- Base -- base year for HPI value
    .. Type 01 is the index value with a base of 100 when first recorded.
    .. Type 02 is the index value with a base of 100 in 1990.
    .. Type 03 is the index value with a base of 100 in 2000.
- HPI 2010 -- as computed for corresponding Type/Base year
- HPI 2011 -- as computed for corresponding Type/Base year
- HPI 2012 -- as computed for corresponding Type/Base year
- HPI 2013 -- as computed for corresponding Type/Base year
- HPI 2014 -- as computed for corresponding Type/Base year
- HPI 2015 -- as computed for corresponding Type/Base year
- HPI Change 2014-15 -- as computed for corresponding Type/Base year
- HPI %Change 2014-15 -- as computed for corresponding Type/Base year
- HPI Change 2010-15 -- as computed for corresponding Type/Base year
- HPI %Change 2010-15 -- as computed for corresponding Type/Base year

Analyzing HPI by ZIP Code using GIS Resources (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 GDP GIS project fileset
... requires ProximityOne User Group ID (join now)
... unzip HPI by ZIP Code GIS project files to local folder c:\hpizip
3. Open the c:\hpizip\hpizip1.gis project
... after completing the above steps, click File>Open>Dialog
... open the file named c:\hpizip\hpizip1.gis
4. Done. The start-up view is shown at top of this section.

ZIP code layer dbf fields
- ZIP
- ALAND10
- AWATER10
- HPIC10 HPI 2010 Type 01 Base Year
- HPIC11 HPI 2011 Type 01 Base Year
- HPIC12 HPI 2012 Type 01 Base Year
- HPIC13 HPI 2013 Type 01 Base Year
- HPIC14 HPI 2014 Type 01 Base Year
- HPIC15 HPI 2015 Type 01 Base Year
- HPID10 HPI 2010 Type 02 Base Year
- HPID11 HPI 2011 Type 02 Base Year
- HPID12 HPI 2012 Type 02 Base Year
- HPID13 HPI 2013 Type 02 Base Year
- HPID14 HPI 2014 Type 02 Base Year
- HPID15 HPI 2015 Type 02 Base Year
- HPIE10 HPI 2010 Type 03 Base Year
- HPIE11 HPI 2011 Type 03 Base Year
- HPIE12 HPI 2012 Type 03 Base Year
- HPIE13 HPI 2013 Type 03 Base Year
- HPIE14 HPI 2014 Type 03 Base Year
- HPIE15 HPI 2015 Type 03 Base Year
- HPIE1015 HPI 2010-2015 change Type 03 Base Year

About Base Years
Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. In cases where sample sizes are small for the five-digit ZIP Code area, an index is either not reported if recording has not started or a missing value is reported with a period. Index values always reflect the native five-digit ZIP index, i.e. they are not made with data from another area or year. Three HPI values are provided and, since the indexes reflect cumulative appreciation since a certain period, the values reflect the base year being used (annual appreciations are the same).
  • Type 01 is the index value with a base of 100 when first recorded.
  • Type 02 is the index value with a base of 100 in 1990.
  • Type 03 is the index value with a base of 100 in 2000.

About the Housing Price Index ... scroll section
The 5-digit ZIP code HPI data are a set of experimental annual house price indexes for 5-digit ZIP codes across the country from 1975 through 2015. The indexes are constructed using the typical "repeat-transactions" methodology. Unlike other housing price indexes, the 5-digit ZIP code measures are annual price measures, meaning that a single index value is produced for each year. See more in associated working paper.

The annual 5-digit indexes should be considered developmental. As with the standard HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the working paper, in cases where sample sizes are small for the 5-digit ZIP Code area, an index is either not reported if recording has not started or a missing value is reported with a 0.0. Index values always reflect the native 5-digit ZIP index, i.e., they are not made with data from another area or year. Three HPI values are provided and, since the indexes reflect cumulative appreciation since a certain period, the values reflect the base year being used (annual appreciations are the same). Type 01 is the index value with a base of 100 when first recorded, Type 02 is the index value with a base of 100 in 1990, and Type 03 is the index value with a base of 100 in 2000.

More in general about the HPI ...
HPI values are constructed using a large-scale panel of annual house price indices for cities, counties, 3-digit ZIP codes, and 5-digit ZIP codes in the United States from 1975 through 2015 using source data with nearly 100 million transactions. Appreciation rates decrease with distance from the central business district (CBD) in large cities, suggesting an overall increase in the desirability of housing units in CBD locations and a general steepening of the house price gradient. Real house prices are more likely to be non-stationary near the CBD than in the suburbs, a finding consistent with a higher elasticity of housing supply near the edge of the city. Sustained real price increases and high price volatility near the centers of large cities suggest a lower supply elasticity in these locations.

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 based on data developed by the Federal Housing Finance Agency (FHFA) using data provided by Fannie Mae and Freddie Mac.

The HPI is a measure designed to capture changes in the value of single-family homes in the U.S. by state and metropolitan area. The HPI equals 100 for all MSAs in the first quarter of 1995. States and divisions are normalized to 100 in the first quarter of 1980. The difference in normalization dates has no impact on appreciation rates obtained from the index. HPI data are estimates subject to errors of estimation.

Transactions Covered by HPI
The House Price Index is based on transactions involving conforming, conventional mortgages purchased or securitized by Fannie Mae or Freddie Mac. Only mortgage transactions on single-family properties are included. Conforming refers to a mortgage that both meets the underwriting guidelines of Fannie Mae or Freddie Mac and that does not exceed the conforming loan limit. For loans originated in 2009, the loan limit has been set by the American Recovery and Reinvestment Act of 2009. That Act, in conjuction with prior legislation, allows for loan limits up to $729,750 for one-unit properties in certain high-cost areas in the contiguous United States.
The purchase-only and all-transactions HPI track average house price changes in either repeat sales or refinancings on the same single-family properties. The purchase-only index is based on more than 7 million repeat sales transactions, while the all-transactions index includes more than 50 million repeat transactions (includes refinance appraisals). Both indexes are based on data obtained from Fannie Mae and Freddie Mac for mortgages originated over the past 39 years.

How the HPI is Computed
The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. The HPI is updated each quarter as additional mortgages are purchased or securitized by Fannie Mae and Freddie Mac. The new mortgage acquisitions are used to identify repeat transactions for the most recent quarter and for each quarter since the first quarter of 1975.

Comparison to Related Housing Price Measures
Census Bureau Constant Quality House Price Index (CQHPI). The FHFA HPI covers far more transactions than the Census survey. The CQHPI covers sales of new homes and homes for sale, based on a sample of about 14,000 transactions annually, gathered through monthly surveys. The quarterly HPI is based on more than 38 million repeat transaction pairs over 34 years. This gives a more accurate reflection of current property values than the Census index. The HPI also can be updated efficiently using data collected by Fannie Mae and Freddie Mac in the normal course of their business activity.

S&P/Case-Shiller® Home Price Index. Both FHFA and C-S HPIs employ the same fundamental repeat-valuations approach, there are a number of data and methodology differences. Among the dissimilarities:
. The S&P/Case-Shiller indexes only use purchase prices in index calibration, while the all-transactions HPI also includes refinance appraisals. The FHFA purchase only series is restricted to purchase prices, as are the S&P/Case-Shiller indexes.
. FHFA valuation data are derived from conforming, conventional mortgages provided by Fannie Mae and Freddie Mac. The S&P/Case-Shiller indexes use information obtained from county assessor and recorder offices.
. The S&P/Case-Shiller indexes are value-weighted, meaning that price trends for more expensive homes have greater influence on estimated price changes than other homes. The FHFA index weights price trends equally for all properties.
. The geographic coverage of the indexes differs. The S&P/Case-Shiller National Home Price Index, for example, does not have valuation data from 13 states. The FHFA U.S. index is calculated using data from all states.

Frequently Asked Questions

Q: Where is more information on other attributes about housing by ZIP Code?
A: While the source of the data differs, see this related interactive table.

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