Tag Archives: Housing Price Index

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.

Real Purchasing Power by State & Metro

.. how does the real purchasing power in metros of interest compare to other metros? Use data and tools reviewed here to examine the purchasing power of the incomes in different metros and states … this section provides access to regional price parities (RPPs) estimates developed compare regions within the U.S. RPPs are regional price levels expressed as a percentage of the overall national price level for a given year. The price level is determined by the average prices paid by consumers for the mix of goods and services consumed in each region. See about these data. See example about using RPPs below in this section.

• Use the interactive table to view, rank, compare the RPPs
.. for all states and metropolitan statistical areas (MSAs).
• Use GIS tools described here to develop RPP 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.

Patterns of Regional Price Parities by Metro: 2014
The following graphic shows patterns of 2014 all items Regional Price Parities by metro (MSAs). The color patterns/intervals are shown in the inset legend. In additional views (below this graphic) metros are labeled with the 2014 all items RPP. 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 — install GIS project (see steps here) and create your own custom maps
Georgia & Region
Missouri & Region
Texas & Region

Using the RPP — Illustrative Examples
1. Comparing real purchasing power:
  — Houston, TX metro compared to Waco, TX metro.
The the all items RPP for the Houston metro in 2014 was 100.3 while the all items RPP for the Waco, TX metro in 2014 was 91.5. (from RPP table). On average, prices are 0.3 percent higher and 8.5 percent lower than the U.S. average for the Houston metro and the Waco metro, respectively. The per capita personal income (PCPI) for the Houston metro in 2014 was $54,820 and the per capita personal income for the Waco metro was $35,340 (get from the table at http://proximityone.com/reis.htm). The RPP-adjusted PCPI values are $53,223 ($54,820/1.03) and $38,622 ($35,340/0.915), respectively. The gap between the purchasing power of the two metro PCPIs is reduced when adjusted by their respective RPPs.

2. Comparing real purchasing power:
  — Washington, DC metro compared to Columbia, MO metro.
• Washington, DC metro 2014 all items RPP: is 119.4 (from RPP table); 2014 PCPI: $62,975 (from this table)
• Columbia, MO metro 2014 all items RPP: 93.0 (from RPP table); 2014 PCPI: $41,418 (from this table)
• The RPP-adjusted PCPI values are $52,742 ($62,975/1.194) and $44,535 ($41,418/0.93), respectively.

Using the RPP Interactive Table
Use the interactive table to examine the RPP by state and metro. The following graphic illustrates use of the table to show the 10 metros having the highest 2014 all items RPP. Click graphic for larger view. Examine metros and states of interest with more detail 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.

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.

Mapping Statistical Data Updates

.. statistical mapping & visual data analysis … ready-to-use GIS projects/datasets … Geographic Information Systems (GIS) provide flexible and powerful capabilities to combine maps with data. In our increasingly data rich environment, we often experience “drowning in data.” GIS tools can help harness disparate and voluminous data and assist with data linkage. This section provides links to other sections that provide information on no cost GIS software and “production” GIS projects and datasets that you can use.

• Recent Additions
– Real Gross Domestic Product by State & Area – 06/23/16 – details
– Housing Price Index by Metro; 2015Q1-2016Q1 – 07/02/16 – details
– Housing Price Index by 5-Digit ZIP Code; 2010-2015; 07/02/16; details

Example: Mapping Median Housing Value by ZIP Code;  Los Angeles Area
Make this type of view/map for any area. Click graphic for larger view. Larger view illustrates use of identify/select tool to show mini profile for a selected ZIP code (see at pointer). Expand browser window for best quality view. Using GIS resources described here.


View developed with CV XE GIS software.

Related Topics in Mapping Statistical Data section …
• K-12 Curriculum Program
Data Analytics & Mapping Statistical Data in the Classroom

• GIS Projects/Datasets/Applications
World by Country
U.S. by State
U.S. by Congressional District
State Legislative Districts
U.S. by Metropolitan Area
U.S. by County
U.S. by City/Place
U.S. by ZIP Code Area
State by Census Tract (each/all states)
State by Block Group
State by Census Block
K-12 Schools & School Districts
K-12 Schools & School District Data Analytics

Join in … participate in the weekly 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.

Staying Ahead of the Data in 2016

.. effective use of information in anticipation of data releases .. The Federal statistical system uses scheduled release dates for wide-ranging statistical data. Anticipation of the implications of the data by users builds ahead of the actual release date. This section reviews major statistical release dates to help stakeholders “stay ahead of the data” and be prepared to make better use of the data. The continuously updated Statistical Release Dates for 2016 table can be a useful reference throughout the year.

Anticipation of Data Releases & Implications of the Data
Each month, stakeholders around the world watch for news about the Jobs Report, the Employment Situation, data developed by the Bureau of Labor Statistics. The Employment Situation is one of many key economic measures used to assess the strength and direction of the U.S. economy.

For the November 2015 Jobs Report, released December 4, 2015, the New York Times December 2nd story reflected “In the United States, most of the focus will be on the November jobs report, to be released Friday. Expectations are high.”

Many, convinced that the November data would be good news, took action in advance of the actual data release. The New York Times December 4th story “The U.S. economy created 211,000 jobs in November … The numbers did not disappoint … U.S. stocks jumped more than 2 percent … Stocks rallied in a sign investors are taking their cue from economic performance …” The Jobs Report is but one of many with monthly implications for planning and decision-making.

Staying Ahead of the Data
Planning in advance of the statistical release dates can often be as important as taking action based on what the numbers actually say. Upon the actual data release, a CEO might ask, “what do these data mean for our company and what might be the impact on us?” Good opportunities might have passed by that time. And, in the face of less positive news, the opportunity to take action might have passed.

Statistical Release Dates for 2016
See the full 2016 calendar. The graphic below shows a partial view of the 2016 data release dates. Items include selected key Federal and other demographic-economic statistics and related geographic data. The list builds on the list of “Principal Federal Economic Indicators” prepared by OMB. That list was developed in part to prevent early access to information that may affect financial and commodity markets and preserve the distinction between the policy-neutral release of data by statistical agencies and their interpretation by policy officials.


– click graphic to view full table.

Each row in the table shows dates for data releases. The table will update throughout 2016 and knits together with the ProximityOne calendar. The “Staying Ahead of the Data” section in the Metropolitan Area Situation & Outlook Reportsreviews upcoming data releases and anticipates the possible effects on that metropolitan area.

Join me in a Data Analytics Lab session to discuss accessing, integrating and using these data with other data that relate 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.

Housing Price Index Metro & State Trends

.. HPI quarterly update … use the Housing Price Index (HPI) to examine quarterly or annual housing value appreciation by metro or state. How is housing value appreciation changing among metros of interest? The HPI is calculated in part using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. The U.S. HPI all transactions, non-seasonally adjusted, value increased by 5.25 percent from 2014Q2 to 2015Q2. During this period the Sebastian-Vero Beach, FL MSA experienced the highest rate of housing value appreciation among all metros.

Use the interactive table to compare and contrast HPI quarterly data for/among all metropolitan statistical areas, states and the U.S. Use the GIS tools and data resources reviewed below to visually examine and map these data. See related Web section for more detail.

Visual Analysis of 2014Q2-2015Q2 HPI Patterns
The following graphic shows housing value appreciation 2014Q2-2015Q2 by metro based on the HPI.

– click graphic for larger view and details; view developed using CV XE GIS.
Use the HPI GIS project with CV XE GIS software; create different views.
– view/analyze different HPI measures; zoom-in; add labels.
– apply queries; add other geography/data.
– create views/graphics for reports and stories.

HPI Metro & State Patterns Interactive Table
Use the interactive table 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. The graphic shown below illustrates the start-up view of the table. The blue highlighted value shows the U.S. national annual change 2014Q2 to 2015Q2.

– click graphic for larger view

Ranking Metros
The following graphic illustrates how the table can be used to 1) select only metros and 2) rank metros in descending order based on annual change 2014Q2-2015Q2. The Sebastian-Vero Beach, FL MSA experienced the highest rate of housing value appreciation among all metros.

– click graphic for larger view

Data Analytics Lab Web Sessions
The HPI provides one part of a larger picture of demographic-economic conditions and trends. Join me in Data Analytics Lab sessions where we explore the mechanics of making the HPI thematic pattern view shown above. Examine the process of integrating other data. Create variations of this view or entirely different visual analysis GIS projects.

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.