Tag Archives: Houston housing prices

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.

2015 Housing Price Appreciation by ZIP Code

.. housing value appreciated by 6.77% in the Houston 3-digit ZIP code 770 from the third quarter 2014 through the third quarter 2015 .. how has housing value appreciated in areas of interest during 2015?  Use the  Housing Price Index (HPI) to examine quarterly or annual housing value appreciation by 3-digit ZIP code, metro or state.  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 5.5 percent from 2014Q3 to 2015Q3. Use the interactive table in this section 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 in the related Web section to visually examine and map these data. Install the GIS project on your computer; add your own data.

Housing Value Appreciation 2014Q3-2015Q3 by 3-Digit ZIP Code
The following graphic shows housing value appreciation 2014Q3-2015Q3 by 3-digit ZIP code based on the HPI. Click graphic for larger view and details.

• View developed using CV XE GIS and related GIS project.
• Interactive table coming in December.
• Click to view Houston metro area .. with counties
.. Houston area view with counties shows mini-profile
for 3-digit ZIP code 770; housing appreciation 6.77% 2014Q3-2015Q3.

Related Housing Market Data & Analytical Resources
The HPI alone provides only partial insights. Evaluation of housing markets, and the regional economy, trends and patterns need to use the HPI in combination with many other measures.
2010-2014 annual population estimates: county, metro, state, U.S.
ACS 2014 1-year demographic-economic tables: county, metro, state, U.S.
Housing Unit Time Series, Trends & Patterns
Housing market conditions
ProximityOne Data Services: access/integrate these with other data
• Each data resource section has associated GIS project & datasets.
CV XE GIS software: data analytics, maps, geospatial analysis
• See related Interactive Ranking Tables

Using Tools & Data Resources in this Section
Use tools in this section to examine the quarterly HPI from 2014Q3 to 2015Q3. View/rank/compare HPI trends using the interactive table (see below). Use the GIS tools to visually and geospatially analyze patterns and characteristics of interest. Members of the ProximityOne User Group may download the HPI GIS project and use this project and datasets with the CV XE GIS software. Develop variations on maps shown in this section; add your own data.

Metro Housing Market Reports
Register for information on Metro Housing Market Reports. Updated quarterly, these reports provide a comprehensive housing market assessment and outlook for the U.S. by metro with geographic drill-down (tract and ZIP code) within individual metros.

Visual Analysis of 2014Q3-2015Q3 HPI Patterns by Metro
The following graphic shows housing value appreciation 2014Q3-2015Q3 by metro (MSA) based on the HPI. Click graphic for larger view and details.

– view developed using CV XE GIS and related GIS project.
User Group (join now) members: use HPI GIS project with CV XE GIS.

Interactive Table
The graphic shown below illustrates use of the interactive table to rank metros on the 2014Q3 to 2015Q3 quarter-to-quarter housing appreciation. Two Florida metros, Port St. Lucie and Palm Bay-Melbourne-Titusville, FL, led the nation.

– click graphic for larger view.

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.

HPI Updates
The HPI updates quarterly for 3-digit ZIP codes, metropolitan statistical areas and other geography. The next update is scheduled for revisions and the new 2015Q4 on February 25, 2016. See in calendar and set a reminder.

Upcoming Topics
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 Low & Moderate Income by Census Tract 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.