Analyzing ACS 2014 1-Year Supplemental Data

.. examining 2014 characteristics of areas with population 20,000 and over  .. this section summarizes how to use the America Community Survey (ACS2014) “supplemental” data (ACS2014S) to access more current estimates than otherwise available. The America Community Survey “supplemental” data are just that, a supplemental set of ACS 2014 1-year estimates — for areas 20,000 population and over. See the related Web section providing more detail.

The importance of the ACS 2014S data are two fold.
1 – 2014 1-year estimates for a larger number of areas than available from the ACS 2014 1-year (ACS2014) estimates.
2 – more current (2014) data for those areas only available from the 5-year estimates (centric to 2012) that are between 20,000 and 65,000 population.

The ten cities/places with the highest 2014 median family income based on 1-year estimates were all under 65,000 population. These cities were not included in the ACS 2014 1-year standard estimates but were included in the ACS 2014 1-year supplemental estimates. See list below.

This section provides an overview of the ACS 2014 supplemental data and provides a summary of tools, interactive table and GIS project, to analyze characteristics of these areas. These data are used by ProximityOne to develop/update annual county demographic-economic projections. See schedule of related 2016 updates.

Scope of Expanded Geography Available
As shown in the table below, 2014 1-year “supplemental” estimates are available for more than twice as many counties from the ACS2014S compared to the ACS2014 “standard” 1-year estimates. However, there area a more limited set of subject matter data available from the ACS2014S data compared to both the ACS 2014 1-year and 5-year estimates.

MSA/MISA: Metropolitan Statistical Areas/Micropolitan Statistical Areas Counties: county and county equivalent

ACS 2014S Data Availability by County
The following graphic shows the additional counties for which ACS 2014 1-year estimates are available using the “supplemental” data.
• ACS 2014 1-year “standard” estimate counties — blue fill pattern
• ACS 2014 1-year “supplemental” estimate counties — orange fill pattern
• Only ACS 2014 5-year estimates available for remaining counties
Click graphic for larger view; expand browser window for best quality view. The larger view shows metropolitan area (MSA) boundaries. Note that for example, ACS 2014 1 year data are available for all counties in the Austin and San Antonio metros (see pointer) — previously unavailable..

.. view developed with ProximityOne CV XE GIS and related GIS project.
.. any CV XE GIS user can create this view using the default US1.GIS project

ACS2014S Tables — scroll section
The ACS 2014 supplemental data include 42 tables and a total of 229 data items. Br> The table number and descriptions are summarized below.

View full table/item detail in tables shells: ACS 2014S Table shells (xls)

ACS 2014 Selected Supplemental Items for Selected Geography
  — interactive table
The interactive table contains all geography for which the ACS2014S data have been tabulated for these geographies: U.S., state, county, city/place, 114th Congressional District, MSA/MISA, PUMA, urban area and school district. The table provides access to key selected items.

The following graphic illustrates use of the interactive table. First cities/places were selected using the Type drop-down below the table. Next, the table is ranked in descending order on median family income. As shown in the graphic the largest 10 cities/places were under 65,000 population. 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.

Daytime Population by Census Tract & Neighborhood

.. examining workers living/working in area .. population change due to commuting & employment/residence ratio .. the concept of the daytime population refers to the number of people who are present in an area during normal business hours, including workers. This is in contrast to the resident population present during the evening and nighttime hours. Information on the expansion or contraction experienced by different communities/areas between nighttime and daytime populations is important for many planning purposes, including those dealing with market size, trade/service areas, transportation, disaster, and relief operations. See related Web section with more detail.

This section reviews use of analytical tools to examine daytime population and related measures by census tract using GIS resources. These data are based on the 2013 American Community Survey 5-year estimates (ACS2013).

Topics:
• Patterns of Resident Population by Census Tract
• Patterns of Daytime Population Census Tract
• Patterns of Employment-Residence Ratio by Census Tract

Patterns of Resident Population by Census Tract
The following graphic shows patterns of the resident population by census tract for the Los Angeles area. Census tracts are statistical areas designed to average 4,000 population as reflected in this view. See population size/color intervals in inset legend. Primary roads are shown in the graphic; the pointer shows the Los Angeles-Orange County boundary. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows Los Angeles city as a cross-hatched overlay. This graphic is presented to compare/contrast patterns of the daytime population shown in the next graphic.

– View created with CV XE GIS.

See more about the Los Angeles metro and California state & regional data resources.

Patterns of Daytime Population Census Tract
The following graphic shows patterns of the daytime population by census tract for the Los Angeles area. This graphic is presented to compare/contrast patterns of the daytime population shown in the above graphic. As the employed population commutes during the data, the daytime population of census tracts change as reflected in this view. See population size/color intervals in inset legend. Primary roads are shown in the graphic; the pointer shows the Los Angeles-Orange County boundary. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows Los Angeles city as a cross-hatched overlay.

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

Patterns of Employment-Residence Ratio by Census Tract
The following graphic shows patterns of the Employment-Residence (E-R) Ratio by tract for the Los Angeles area. See E-R/color intervals in inset legend. See about the E-R ratio below. Primary roads are shown in the graphic; the pointer shows the Los Angeles-Orange County boundary. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows Los Angeles city as a cross-hatched overlay.

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

About the Employment-Residence (E-R) Ratio
The E-R ratio is a measure of the total number of workers working in the area, relative to the total number of workers living in the area. The E-R ratio is used sn indicator of the jobs-workers balance in an area. A value greater than 1.00 shows there are more workers working in the area than living there (net importers of labor). A value of less than 1.00 is shown in areas that send more workers to other areas than they receive (net exporters of labor).

See related Web section for information on daytime population terms and concepts.

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.