Tag Archives: Economic data

U.S. Demographic-Economic Insights

The results of the Census 2020 will not provide us with a good picture of the United States demographic-economic situation, mainly as a result of limited scope subject matter. While the Census 2020 data are important due to their more accurate and up-to-date small area demographics, and data tabulated by census block, only a small number of demographic subject matter items are available from Census 2020. The scope of subject matter is limited by items tabulated based on the questionnaire.

In comparison, the annual American Community Survey (ACS) data provide a much broader range of subject matter. Based largely on the 2019 ACS (the most up-to-date with data for small area geography .. released in December 2020), ProximityOne has developed tools/data to develop demographic-economic insights for the most widely used types of geography.

Demographic-Economic Insights Role & Scope
ACS and related data and ProximityOne tools have been used to develop the U.S. demographic-economic insights report, reviewed here, illustrating the scope and organization of the data and how it can be used. You can develop similar comparative analysis reports for your areas of interest. See more about the role and scope of the Demographic-Economic Insights.

U.S. National Scope Demographic-Economic Insights
View the U.S. National Scope Demographic-Economic Insights report develop using the ProximityOne Insights tool. This report is organized into two subject matter description columns, four statistical data columns and four subject matter groups. The first two statistical data columns present data based on the ACS 2019 1-year estimates. The second set of statistical data columns show data based on the 2019 ACS 5-year estimates (values centric to mid 2017). This report is a useful resource to compare/contrast data values based on the 1-year estimates side-by-side with the 5-year values. The four subject matter groups are reviewed below.

General Demographics
Graphic shows partial list of “D” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Social Characteristics
Graphic shows partial list of “S” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Economic Characteristics
Graphic shows partial list of “E” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Housing Characteristics
Graphic shows partial list of “H” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Creating Insights and Talking Points
The four subject matter groups provide a dense array of tabular statistical data that can be overwhelming to consume. Yet, not every topic can be distilled to just a few numbers. The scope of key data depends on the objective presentation, audience and desired talking points.

For example, a briefing or synopsis might include only 10-15 subject matter items such as … this report tells us that in 2019 (based on 2019 1-year estimates), the total resident population was estimated to be 328,239,523. The median age was 38.5 years. The percent high school graduates was 88.6%. The number of housing units was 139,686,209. The percent owner occupied housing units was 64.1%. These measures are roughly the same today, at the end of 2020, even with the pandemic impact. Some other measures in the report as not as reflective “as of today”.

While data shown here do not fully summarize the state of the Nation, there provide many insights. The same can said for any of the geographic areas covered. To obtain a better picture of the state of the Nation, we need supplementary subject matter, more up-to-date data and trending data that give clues into what’s happening.

Learn more — Join me in the Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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.

Public Use Microdata Area GeoDemographics

Public Use Microdata Areas (PUMAs) provide most detailed U.S. wall-to-wall geography (2,378 areas) for which current year demographic-economic data are available and annually updated. Use the related Public Use Microdata Sample (PUMS) data to develop custom-defined subject matter estimates for one or all PUMAs.  While PUMS files contain data for respondents across the U.S., the PUMA is the most detailed unit of geography identified in the PUMS files.

PUMAs may now be one of the more obscure geographic areas for which American Community Survey (ACS) demographics are tabulated.  Their usage popularity will change in the years ahead.  In a sense PUMAs and PUMS are joined at the hip.  But 2010 vintage PUMAs are now both new and offer many analytical opportunities on their own.  “Using the PUMS data” will be blog topics in the near future.

2010 Vintage PUMA Geography
The 2,378 2010 vintage PUMAs are developed using Census 2010 geography, cover the U.S. wall-to-wall, conform to state boundaries, and where possible are comprised of whole Census 2010 census tracts. The first use of the 2010 vintage PUMAs is with the ACS 2012 PUMS and 1-year summary statistic data (released October 2013). Use this interactive table to examine 2010 PUMAs and PUMA component area geography.

PUMAs are special non-overlapping areas that partition each state into contiguous geographic units containing no fewer than 100,000 people each. 2010 PUMAs cover the entirety of the U.S.   In addition to the U.S. wall-to-wall coverage, PUMAs offer good geographic drill-down for larger metro counties and central city areas.  The graphic presented below shows PUMAs (red boundaries with yellow PUMA geocode label)  in the Phoenix, AZ area.  Viewing graphic with gesture/zoom enabled device suggested.

Phoenix, AZ area PUMAs

Phoenix, AZ area PUMAs

Where is My PUMA?
PUMA maps may be viewed in two ways.  PUMA maps are shown in state by state Web pages that may be accessed via the scroll section in the right panel of the PUMA2010 section. The maps appear in the form shown above.  Another option, providing more analytical opportunities, is to display the PUMA shapefile using GIS software such as CV XE GIS.  The second option provides the ability to view PUMAs in context with other geography, such as census tracts, and to display thematic pattern maps using the ACS 2012 data.

PUMA Summary Statistic Data
2010 vintage PUMA summary statistic data, based on the ACS 2012 1-year estimates, may be accessed via these interactive tables:
General | Social | Economic | Housing

Linking the Data to the Geography
The Phoenix area PUMA map above shows that PUMA 00110 intersects with the Scottsdale area.  We could see exactly how by adding the city/place shapefile layer to the GIS project that is also using a PUMA shapefile layer.   The five-digit code 00110 is unique only to Arizona.  To make the PUMA code nationally unique requires adding the Arizona FIPS code (04) to the PUMA code: 0400110.  Using the ACS 2012 PUMA economic characteristics interactive table (see above), we then navigate to the PUMA row of interest to see that the median household income for this PUMA (item E086) is $81,304.  This value is shown in the graphic presented below in column/item E086 for the row highlighted in blue (PUMA 0400110).  This is a close estimate to the $MHI for the Scottsdale area.  Viewing graphic with gesture/zoom enabled device suggested.

PUMA 0400110 $MHI

PUMA 0400110 $MHI

The ACS 2012-1 year estimates were released in October 2013.  The data are very fresh!  The ACS 2013-1 year estimates will be released in the fall 2014, and similarly on an annual basis — for the same PUMA geographic area definitions.  Soon we will have a time series .  Then we will able to examine trends based on wide-ranging demographic-economic data for each or all of the 2010 vintage PUMAs.

10 Reasons to Avoid ZIP Code GeoDemographics

Possibly the most obvious reason to use ZIP codes for small area demographic and economic analysis is that the analyst has ZIP Code-based data. Typically those data are addresses or address-based data.  The analyst seeks to assign demographic and economic data to the ZIP code records/locations so that more can be known about the demographic-economic characteristics of individual addresses or address vicinity.

ZIP Codes are well known to all of us. They are used by the U.S. Postal Service as a means to more efficiently deliver mail.  Census tracts may be less familiar. Census tracts are defined by the Census Bureau and organized as sub-county building blocks.  More about census tracts.

This sample profile shows side-by-side comparison demographic-economic views of two census tracts and associated ZIP Code Tabulation Area in the Scottsdale, AZ area.  See related section about equivalencing census tract and ZIP Code area geography.

10 Reasons to use Census Tracts Versus ZIP Code Geography & Demographics

1. Census tracts are polygons and cover a well-defined geographic area.
ZIP codes are clusters of lines; the U.S. Postal Service does not define ZIP Code boundaries.  A very large number of 5-digit ZIP Codes are P.O. boxes or specific street addresses and thus represent points not even one line.
2. Census tracts provide more granularity (73,000 areas) than ZIP Codes (43,000).
3. Census tracts are, generally, non-changing static geography from decennial census to census.  ZIP codes may change at any time; new ZIP codes may be created or eliminated at any time.
4. Census tracts cover the U.S. wall to wall.  ZIP codes exist only where U.S. mail service is provided.
5. Census tracts align coterminously to county boundaries.  ZIP codes do not.
6. Census tracts have well known/exact boundaries.  ZIP codes are groups of lines whose exact structural definition is not officially established.
7.  Census tracts provide more statistical uniformity averaging 4,000+ population.  The population of a single ZIP code can exceed 100,000.
8.  Census tracts have a large and richer set of associated, more reliable demographic-economic data. True ZIP Code data are only delivery statistics developed by the U.S. Postal Service.
9.  The total land area and water area are known for each census tract, to the square meter.  The total area covered by a ZIP Code is not known, let alone water area.
10. A unique set of census blocks, and hence demographics, can be associated with each census tract.  There is no good way to associate census blocks with ZIP codes.
11.. Who’s counting? It is entirely feasible to develop and analyze time series data for census tracts.  Time series data by ZIP code is risky due to the inherent potential for changing geographic scope.

So why do we keep using estimated ZIP Code areas and demographics? In the main, ZIP codes provide an easier and more comfortable way to associate or characterize demographic-economic conditions.  We all know our own ZIP code and generally quite a few others.  Few among us know what our census tract code is, let alone for other locations.