Category Archives: Housing Market

Housing Value Appreciation by 3-Digit ZIP Code: 2015Q3-2016Q3

.. tools, data and methods to examine housing value appreciation from 2015Q3 to 2016Q3 by 3-digit ZIP code based on the Housing Price Index (HPI).  How is the housing value changing in areas of interest?  How does housing value appreciation compare among a set of ZIP codes? Which ZIP code areas have the highest and lowest housing value appreciation in a state, region custom defined areas of interest? The HPI is calculated in part using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. The U.S. all transactions HPI rose 5.6 percent from the 3rd quarter of 2015 to the 3rd quarter of 2016. Rank, compare, evaluate quarterly or annual housing value change for the approximate 900 3-digit ZIP code areas using the interactive table.

3-Digit ZIP Codes with Highest Housing Value Appreciation
Derived from the interactive table below this table shows the ten 3-digit ZIP codes having the highest housing value appreciation over the year 2015Q3-2016Q3. The areas are ranked on percent HPI change (rightmost column).

Gaining Insights in Housing Prices, Conditions & Markets
.. data, tools and methods to assess characteristics, patterns & trends
.. weekly Housing Data Analytics Lab sessions

Patterns of Housing Value Change by 3-Digit ZIP Code
The following graphic shows housing value appreciation 2015Q3-2016Q3 by 3-digit ZIP code based on the HPI. Use related GIS tools to zoom-in, assign labels, show in context with other geography.

– view developed using CVGIS and related GIS project.
– Click graphic for larger view and details;

Examining Housing Appreciation by 3-Digit ZIP Code
Use the interactive table below to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all 3-digit ZIP codes. The ranking table shows the latest quarterly HPI data and preceding quarters for one year earlier. This table will be updated on February 24, 2017, with 4th quarter 2016 data and related prior quarterly estimates and re-computed quarterly change values (last column).

Using the Interactive Table
The following graphic illustrates use of the HPI by 3-digit ZIP code interactive table. HPI data are shown for the quarterly period 2015Q3 through 2016Q3. The state selection below the table has been used to select only California ZIP codes. The Group1 button below the table has been used to select ZIP codes with a 2016Q3 HPI value of 175 ore more. The table is then sorted on the rightmost column. The resulting view shows that among all California 3-digit ZIPs having an HPI of 175 or more in 2016Q3, ZIP code 948/Richmond CA had the highest housing value appreciation — a 10.6% increase over the year.

Use the interactive table to examine states or ZIP code groups of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Housing Price Index by 5-Digit ZIP Code

.. tools to examine housing prices by 5-digit ZIP code and how they are changing .. 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. Housing prices increased for most ZIP codes from 2014 to 2014.  Find out more about housing prices and trends for ZIP codes of interest using tools described here. 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.

• Use the interactive table to view, rank, compare the HPI for all 5-digit ZIP code areas tabulated.
• Use GIS tools described here 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
  .. join in .. 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 here 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
New York City area
Washington, DC area
Los Angeles area

Examining Recent Trends; Current Estimates & Projections
The interactive table 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 include the number of units by type and value that are added to the housing stock used to compute a variation of the HPI.

Housing Price Index by 5-Digit ZIP Code: 2010-2015
  — Interactive Table
Use the interactive table to examine the Housing Price Index (HPI) by 5-digit ZIP code. The following graphic illustrates use of the table to show the 10 ZIP codes experiencing the largest percentage increase in the HPI from 2014 to 2015. Click graphic for larger view. Examine cities or ZIP code ranges of interest using tools below the table.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Metro Situation & Outlook Reports Updated

Regional Demographic-Economic Modeling System (RDEMS) county table links are now embedded in Metro Situation & Outlook (S&O) Reports. Easily access the RDEMS county demographic-economic tables for metros of interest.

Use this link to access the Metro S&O Reports:
http://proximityone.com/metro_reports.htm
… click link in the “Code” column to access a specific metro.

… selected metros …
Atlanta .. Boston .. Charlotte .. Chicago .. Dallas .. Denver .. Los Angeles .. Honolulu .. Houston .. Miami .. Minneapolis .. New York .. Philadelphia .. Phoenix .. San Diego .. San Francisco .. Seattle .. Washington

All metros are available.

Join in … join us in the Data Analytics Lab sessions to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

State and Regional Decision-Making Information

Organized on a state-by-state basis, use tools and geographic, demographic and economic data resources in these sections to facilitate planning and analysis. Updated frequently, these sections provide a unique means to access to multi-sourced data to develop insights into patterns, characteristics and trends on wide-ranging issues. Bookmark the related main Web page; keep up-to-date.

Using these Resources
Knowing “where we are” and “how things have changed” are key factors in knowing about the where, when and how of future change — and how that change might impact you. There are many sources of this knowledge. Often the required data do not knit together in an ideal manner. Key data are available for different types of geography, become available at different points in time and are often not the perfect subject matter. These sections provide access to relevant data and a means to consume the data more effectively than might otherwise be possible. Use these data, tools and resources in combination with other data to perform wide-ranging data analytics. See examples.

Select a State/Area

Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
D.C.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

Topics for each State — with drill-down to census block
Visual pattern analysis tools … using GIS resources
Digital Map Database
Situation & Outlook
Metropolitan Areas
Congressional Districts
Counties
Cities/Places
Census Tracts
ZIP Code Areas
K-12 Education, Schools & School Districts
Block Groups
Census Blocks

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Tip of the Day — Census Tract Data Analytics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

This section is focused on tools and methods to access and use census tract demographic-economic measures. Median household income ($MHI), median housing value ($MHV) and other selected items are used to illustrate operations and options.

This section illustrates use of census tract data from the 2014 American Community Survey (ACS1014) 5-year estimates. These are the most comprehensive demographic-economic data from the Census Bureau at the census tract level. These “5-year estimates” are centric to mid-2012. See more about 2010-2021 annual estimates and projections.

Methods described here apply to many other geographies; see related tip sections. See related section on ZIP code applications.

Five data access and use options are reviewed. Each method illustrates how $$MHI, $MHV and other data can be analyzed/used in different contexts.

Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related sections:
Census tracts main section
Evolution of Census Tracts: 1970-2010
Demographic-Economic Estimates & Projections
Census tract and ZIP code equivalencing
Using census tracts versus ZIP code areas
Single year of age demographics

Option 1. View the data as a thematic pattern map; use the GIS tools:
Patterns of Economic Prosperity ($MHI) by Census Tract … the following graphic shows $MHI for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals; expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.

See details about each option in the related Web page.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Tip of the Day – Median Housing Value by ZIP Code

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

.. 5 ways to access/analyze the most recent estimates of median housing value and other subject matter by ZIP Code area .. based on the American Community Survey (ACS1014) 5-year estimates. See related Web section.

Option 1. View the data as a thematic pattern map; use the GIS tools:
— Median Housing Value by ZIP Code Area; Los Angeles Area
Click graphic for larger view with more detail.

View developed with CV XE GIS software. Click graphic for larger view.
Use the Mapping ZIP Code Demographics resources to develop similar views anywhere in U.S.

Option 2. Use the interactive table:
– go to http://proximityone.com/zip14dp4.htm (5-year estimates)
– median housing value is item H088; see item list above interactive table.
– scroll left on the table until H088 appears in the header column.
– that column shows the 2014 ACS H088 estimate for for all ZIP codes.
– click column header to sort; click again to sort other direction.
– see usage notes below table.

Option 3. Use the API operation:
– develop file containing $MHV for all ZIP code areas in U.S.
– load into Excel, other software; link with other data.
– median housing value ($MHV) is item B25077_001E.
click this link to get B25077_001E ($MHV) using the API tool.
– this API call retrieves U.S. national scope data.
– a new page displays showing a line/row for each ZIP code.
– median housing value appears on the left, then ZIP code.
– optionally save this file and import the data into a preferred program.
– more about API tools.
Extending option 3 … accessing race, origin and $MHV for each ZIP code …
click on these example APIs to access data for all ZIP codes
.. get extended subject matter for all ZIP codes
.. get extended subject matter for two selected ZIP codes (64112 and 65201)

Items used in these API calls:
.. B01003_001E – Total population
Age
.. B01001_011E — Male: 25 to 29 years (illustrating age cohort access)
.. B01001_035E — Female: 25 to 29 years (illustrating age cohort access)
Race/Origin
.. B02001_002E – White alone
.. B02001_003E – Black or African American alone
.. B02001_004E – American Indian and Alaska Native alone
.. B02001_005E – Asian alone
.. B02001_006E – Native Hawaiian and Other Pacific Islander alone
.. B02001_007E – Some other race alone
.. B02001_008E – Two or more races
.. B03001_003E – Hispanic (of any race)
Income
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
Housing & Households
.. B25001_001E – Total housing units
.. B25002_002E – Occupied housing units (households)
.. B19001_017E — Households with household income $200,000 or more
.. B25003_002E — Owner Occupied housing units
.. B25075_023E — Housing units value $500,000 to $749,999
.. B25075_024E — Housing units with value $750,000 to $999,999
.. B25075_025E — Housing units with value $1,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

View additional subject matter options.

Option 4. View the $MHV in context of other attributes for a ZIP code.
click this link to select a ZIP code of interest.
– for example, this link shows a profile for 80204 (Denver area).
– when the report displays, scroll down in table to housing value section.

Option 5. View 5- and 10-mile circular area profile from ZIP center.
– profile for ZIP 80204 dynamically made using SiteReport tool.
– with SiteReport running, enter the ZIP code, radii and click Run.
– comparative analysis report is generated in HTML and Excel structure.
Click this link to view resulting profile.
– from the profile, site 2 is 1.9 times the population of site 1.
– Site 1 $MHV is $296,998 compared to Site 2 $MHV $269,734.
– GIS view with integrated radius shown below.

This section is focused on median housing value and ZIP code areas. Many other subject matter items will be apparent when these methods are used. Optionally adjust above details to view different subject matter for ZIP codes.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

American Community Survey 2014 Interactive Tables

.. examining demographic-economic patterns .. use the interactive tables described in this section to examine, view, compare, rank and assess demographic-economic patterns and characteristics of interest for wide-ranging geography based on ACS 2014 data.

It is very important to understand the demographic-economic make-up and patterns for wide-ranging geographies. Community and neighborhood challenges and opportunities are shaped by demographic-economic dynamics. Knowing more about “where we are now” is essential to understanding needs for policy and program management. The quality and precision of business marketing and operational plans and decisions can be improved using these data. School districts can better understand their school district community using these data. Elected officials and policymakers can better understand the needs and characteristics of constituents who they represent. Students can benefit by using these data in studies and research by attaching real world data to support, document and analyze topics of interest.

Data from the American Community Survey 2014 (ACS 2014) are key to these uses, users and processes. See more about the importance of these data. The ACS 2014 interactive tables are part of a larger set of tables comprised of multi-sourced data that are updated frequently. Additional ACS 2014 tables will be added. Join the User Group to receive updates as tables are added.

Median Household Income by ZIP Code Area; Los Angeles Area
Illustrating integration of data in tables using GIS tools & geospatial analysis. Larger view illustrates ZIP code area labeling and use of mini-profile feature.

View developed with CV XE GIS software. Click graphic for larger view; expand browser window for best quality view.

Using the Tables
The interactive tables are organized by type of geography (e.g., ZIP codes) using a standardized structure. There are four types of subject matter for each type of geography (general demographic, social, economic and housing). There is a table/web page for each combination of geography by type of subject matter.

Within each table there is a row that corresponds to a geographic area. Also within each table, columns provide geographic names and codes and a set of subject matter data standardized across all geographies. Similarly designed table controls are provided at the below the table. Usage notes are located below the table.

Terms of Use
These data may be used for any purpose, except that the data may not be bulk downloaded nor used to create similar interactive tables. There is no warranty of any type with regard to any aspect of the data, table or Web pages. The user is solely responsible for any use. It is requested that any use of any table reference the source of the data (ACS 2014), ProximityOne and a link to the Web page.

Data Analytics
ProximityOne has developed these interactive tables as part of a broader set of data analytics tools and data resources. Data shown in the tables are available in dataset structure (CSV, DBF, Excel) on a fee basis. These data are also available as data integrated into shapefiles for GIS applications and geospatial analysis. Most geographic table sections also provide access to ready-to-use GIS projects/datasets. These data are integrated with yet other data to develop/update the Situation & Outlook database and information system, ProximityOne Data Service,Situation & Outlook Metro Reports and other products. These data are also used in the ProximityOne Certificate in Data Analytics and custom service/study applications.

Where’s Waldo?
Use this interactive tool to key in an address and determine geographic codes (geocodes) that might be useful. After keying in an address, click Find button. If the address is located, the page refreshes with a set of geocodes presented below the demographic-economic statistical summary.

ACS 2014 Tables & Datasets
ACS summary data are are tabulated and released annually as 1-year and 5-year estimates. These data are all estimates, subject to errors of estimation and other errors, based on household surveys.
ACS 1-year estimates (for areas 65,000 population or more) become available in September; e.g. the ACS 2014 1-year estimates became available in September 2015.
ACS 5-year estimates (all geographies) become available in December; e.g. the ACS 2014 5-year estimates became available in December 2015.
• See this section for more information about 1-year versus 5-year estimates and comparing ACS data over time.
Table listing provided below are separated into two groups as to data source: ACS 1-year and ACS 5-year. All tables are U.S. national scope.

ACS 2014 1-Year Tables


Data in these tables are centric to mid-2014.
U.S., State, CBSA/Metro
General Demographics .. Social .. Economic .. Housing

114th Congressional Districts
General Demographics .. Social .. Economic .. Housing

ACS 2014 5-Year Tables


Data in these tables are centric to mid-2012 (mid-point of survey period 2010-2014).
Census Tracts
General Demographics .. Social .. Economic .. Housing

ZIP Code Areas
General Demographics .. Social .. Economic .. Housing

School Districts
General Demographics .. Social .. Economic .. Housing

State Legislative Districts
General Demographics .. Social .. Economic .. Housing

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about using these data in context of data analytics with other geography and other subject matter.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.