Tag Archives: Housing Market

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

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 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.

Regional Economic Information System: Annual Updates

.. which counties are experiencing the fastest economic growth? by what economic component? what does this look like on a per capita level?

.. access & analyze economic characteristics and patterns by county and state .. annual time series 1969 through 2015 with projections.  Personal income is the income available to persons for consumption expenditures, taxes, interest payments, transfer payments to governments and the rest of the world, or for saving. Use the interactive table to examine characteristics of counties and regions of interest. The table provides access to 31 personal income related summary measures. These data are a selection of a broader set of annual time series data from the Regional Economic Information System (REIS). REIS is a part of the ProximityOne State & Regional Income & Product Accounts (SRIPA) and Situation & Outlook (S&O) featuring current (2016) estimates and demographic-economic projections. Go to table.

Visual Analysis of Per Capita Personal Income Patterns
The following map shows the Houston metro (view profile) with bold brown boundary. Counties are labeled with county name and 2014 per capita personal income.

Click graphic for larger view. View developed with CV XE GIS software.

Per Capita Personal Income Change 2008-2014 by County
.. relative to U.S 2008-2014 change

Click graphic for larger view. View developed with CV XE GIS software.

Interactive Analysis – County or State Profiles
The following graphic illustrate use of the interactive table to view an economic profile for Harris County, TX. Use the table to examine characteristics of any county or state. Click graphic for larger view.

Interactive Analysis
– comparing per capita personal income across counties
The next graphics illustrates use of the interactive table to rank/compare per capita personal income across counties. Rank/compare states. Choose any of the economic profile items. Click graphic for larger view.

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.

Congressional District 2015 Demographic-Economic Characteristics

.. congressional districts vary widely in demographic-economic characteristics.  We have new data for 2015 providing insights to characteristics of the 114th Congressional Districts.  This section summarize a few of these characteristics and provides access to a wide range of data that you can use to view, sort, rank, and compare congressional districts using interactive tables.

Patterns of 2015 Educational Attainment
The following graphic shows patterns of educational attainment (percent college graduate) by congressional district in the Los Angeles area. White label shows the congressional district code; yellow label shows percent college graduate. Legend shows color patterns associated with percent college graduate intervals.

– View developed using CV XE GIS software and associated GIS project.

How Congressional Districts Compare
Reference items refer to items/columns shown in tables described below.

.. general demographics: congressional district UT03 has the smallest median age (27.5 years — item D017) and FL11 has the highest median age (53.5 years).

.. social characteristics: congressional district KY05 has the fewest number of people who speak English less than “very well” (2,676 — item S113) and FL27 has the largest number (281,053).

.. economic characteristics: congressional district ND00 has the lowest unemployment rate (2.6% — item E009) and MI13 has the highest unemployment rate (14.6%).

.. housing characteristics: congressional district MI13 has the lowest median housing value ($63,100 — item H089) and CA18 has the highest median housing value ($1,139,900).

Access the Detailed Interactive Tables
Click a link to view more thematic pattern maps and use the interactive tables.
.. General Demographics
.. Social Characteristics
.. Economic Characteristics
.. Housing Characteristics

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.

Why Data on Total Housing Units Are So Important

.. data on total housing units are important to the housing industry and many others .. to understand the characteristics, patterns and trends of the housing market, we need good data on the number of housing units. Understanding the how, where, when, how much housing market change might affect you … starts with the number of total housing units by geographic area. As of Census 2010, there were 131,704,730 housing units in the U.S. As of mid-2014, the total number of housing units had increased to 133,957,180 (2.25 million units, a 1.71% increase). See more detail in the related Web section.

Housing Unit Percent Change by County: 2010-2014
Patterns of housing unit percent change by county, 2010-2014, are shown in the map below. More than 1,000 counties (1,214 counties of 3,142) experienced a loss of housing units between 7/2010 and 7/2014 (orange and red fill patterns). Six counties lost more than 1,000 housing units during this period. Click graphic for larger view with details.

– view developed using CV XE GIS software and associated GIS project.
– data based partly on Census 2010 &s Census Bureau housing unit estimates.

Being Informed; Benefits of Using Total Housing Unit Data
Realtors, brokers and selling agents need to know how total housing units are trending — what has been changing where that might affect sales now and in the months ahead. The construction industry and builders need data on the number of housing units and data on the rental vacancy rate to assess likely demand by type of housing in the future. Businesses employing people who might tend to occupy rental properties need to know about the availability and affordability of nearby residential properties. Every school district needs to know how many students there will be enrolled; examining housing unit trends is imperative. By understanding that growth in the housing market may mean new jobs, and more, economic developers, planners and city/neighborhood stakeholders need to monitor what housing unit change in their area means to them. Lenders and financial institutions need these data to assess viability of loans to businesses planning to develop new housing units and assess value in making loans to potential housing buyers.

Understanding the housing stock size, trends and composition in an area, and how that differs from adjacent areas, can help determine the targeted planning for stabilizing and improving local housing markets, developing and preserving affordable rental housing and facilitating neighborhood investment.

Housing Units Defined
A housing unit is a house, apartment, mobile home, group of rooms or single room, which are occupied or intended as separate living quarters. The separate living quarters that define a housing unit are those where the occupants live and eat separately from other residents in the structure or building, and have direct access from the building’s exterior or through a common hallway.

Using the Interactive Table to Examine Housing Unit Patterns
Use the interactive table to examine housing units trends and change by county, metro and state. The following graphic illustrates use of the table to rank counties on the housing unit change from 2010 to 2014. The graphic shows that Wayne County, MI experienced the largest decrease among all counties. Click graphic for larger view with details.

Use the interactive table to examine areas of interest. Join me in a Data Analytics Lab session to discuss use of these data using analytical tools and methods applied to your situation.

Follow my blog (click button in upper right column) where I will review related market topics, using other data resources and analytical tools available to you at no fee. Upcoming topics include an update on the Housing Price Index and the Rental Vacancy Rate access, interpretation and role as a leading economic indicator.

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.

Metropolitan Area New Residential Construction

New residential construction begins with building permits. Overall U.S. housing starts are approximately 2.5% less than permits issued (22.5% less for multi-family units). Completions are approximately 4% less than starts (7.5% less for multi-family units). During the past year-plus, “residential fixed investment” has been approximately $500 billion and remained steady at 3.1% of real Gross Domestic Product. Our focus here is on data and tools to analyze new authorized residential construction activity by metro — how might changing patterns affect you — in your metros of interest? Where are areas of highest growth by type of units in structure? What is the value of new construction; how is it trending in selected metros? See related Web section for more detail and interactive data access.

Visual Analysis of New Residential Construction by Metro
This view shows the November 2014 total building permits per 1,000 housing units (2013 estimate) by Metropolitan Statistical Area (MSA).

View created with CV XE GIS. Click graphic for larger view.

Building permit data (housing units authorized by building permits for new residential construction) are economic leading indicators. Investors and housing developers use these data to examine the characteristics and trends in new residential housing development. Finance and real estate professional and researchers examine building permit patterns to develop strategic insights. Government and policy makers use these data to get a pulse on markets and changing patterns to administer programs and operations. Important strengths of building permits data include very recent/current data. There is a very short time lag between the data accessibility and the reference date (November building permit data are available in December). Geographic coverage and granularity are also strengths with national scope coverage by state, metro, county and city. Seemore about these data below in this section.

Accessing & Using New Authorized Residential Construction Data
Monthly building permits data are part of the Situation & Outlook (S&O) database and information system. Access/analyze these data in context of related geographic, demographic, economic and business data. This section provides no fee access to these data via interactive table, downloadable data and GIS project. Find upcoming release dates using the Calendar and related Find Event tool.

Interactive Data Analysis
Use the interactive table to view, query, rank, compare building permit data by metropolitan area. Data are provided in the interactive table by month for January 2014 forward. Earlier data are not available for the current vintage metropolitan areas.

The following graphic illustrates use of the table. The Year/Month May 2014 is selected. Metros are then ranked in descending order on Total Units. The Houston metro (blue highlighted) had the largest number of new authorized units (5,081) among all MSAs in May 2014. Select other measures of interest to rank/compare metros.


Click graphic for larger view.

Metropolitan Area New Residential Construction GIS Project
Use the U.S. by Metropolitan Area New Authorized Residential Construction GIS project to create thematic pattern views similar to the one shown above. Zoom-in to any metro/region. Add your own data; change colors, labeling, subject matter used for pattern analysis. See details in this related Web section.

New Residential Construction Data in Metro Profiles
Building permit data are updated monthly and are a part of the S&O MetroDynamics Database and Information System. View the MetroDynamics Metro Profiles that show building permits data contextually with other geographic, demographic, economic and business data. Click a metro link in column 2 of the metro interactive table to view a Metro Profile for a metro of interest. The building permits section is populated only for Metropolitan Statistical Areas. Examples: HoustonLos AngelesSan FranciscoAtlanta.

More About These Data
See additional information about these data and their use.

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. By academic background an econometrician, 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.

Housing Price Index 2013Q3-2014Q3

The Housing Price Index (HPI) is a popular economic measure available by state and metro in a timely manner with quarterly updates.  It fits into many decision-making applications where insights are needed into how housing prices are changing by state, region and metro. This section provides an update on the HPI 2014Q3 and quarterly data for the past year. See the related Web page for more detailed data and access to the HPI data via interactive table.

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.

The Larger Picture
By itself, the HPI provides limited insights into the broader picture of “the why” and “how otherwise” states and metros are changing. The MetroDynamics Metro Profiles provide an integrated view of the HPI measure in combination with other economic, demographic and business activity measure. View the HPI integrated with other subject matter in these examples … HoustonCharlotte. Metro Profiles are updated continuously and are available for each of the 917 metropolitan areas

About the HPI
The HPI is 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.

HPI Interactive Table
Use the HPI 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 use of the interactive table to rank all metros in descending order on the percent change over the past year.

Updates
Quarterly HPI measures are used to updated the interactive table, GIS project and Metro Profiles. Use the calender to view the year-ahead HPI release and integration schedule.

Support Using these Resources
Learn more about 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.