Tag Archives: Federal Statistics

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.

Importance of Census Tracts in Data Analytics

census tracts are important for many reasons. It is easy to misidentify or misunderstand patterns and characteristics within cities, counties and metros which become obfuscated using these higher level, more aggregate, geographies. Many cities and counties that might be experiencing demographic-economic decline will often have bright spots that are groups of a few or many census tracts.

Patterns of Percent Population with Bachelor’s Degree
— by Census Tract; Los Angeles Metro
The following graphic shows percent population age 25 years and over with bachelor’s degree by census tract based on ACS 2014 5 year estimates for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using census tract demographics and the relative ease to gain insights using geospatial data analytics tools.

– View developed using CV XE GIS and related GIS project.

Get a Custom Map for Your Area of Interest
Use this form to request a no fee map graphic similar to the one shown above for a county of interest. Enter the request with county name and state in the text section; e.g., “Requesting social characteristics tract map for Cook County, IL.”

This section reviews reasons for the importance of census tracts in data analyyics. See related Web sections on tools, resources and methods that you can use to access, integrate and analyze U.S. by census tract general demographics data. The U.S. national scope Census Tracts Demographic-Economic Dataset contains approximately 600 subject matter items tabulated for each census tract organized into four subject matter groups:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

Importance of Census Tracts for Data Analytics
Census tracts are important for many reasons.  A partial list of reasons is provided below.
• Covering the U.S. wall-to-wall, census tracts are the preferred “small area” geography for superior data analytics.
• The Census Bureau now produces annual tract demographic-economic data from the American Community Survey;  there is an evolving time-series at the tract level creating new analytical opportunities.
• Originally developed to equivalence neighborhoods, many still do.
• Defined by the Census Bureau in collaboration with local groups, tracts typically reflect boundaries meaningful for local area analysis.
• Defined generally for use with each new decennial census, most tract boundaries are stable and non-changing for ten years and many much longer.
• Designed to average 4,000 population, there are more than twice as many census tracts (73,056) than ZIP code areas (33,129).
• Tract boundaries are well-defined; unlike ZIP code areas which are subject to multi-sourced geographic definitions.
• Many data developers (e.g., epidemiologists) use census tract geography to tabulate their own small area data enabling more effective use of those data with Census Bureau census tract data.
• As a statistical geographic area (in contrast to politically defined areas, census tracts are coterminous with counties; data at the census tract level can be aggregated to the county level.
• Small area estimates for tracts are typically more reliable than for block groups.
.. census tracts are comprised on one or more coterminous block groups.
.. on average, a census tract is comprised of three block groups.
• Census tracts are used by many Federal, state and local governments for compliance and program management.

The annually updated American Community Survey provides “richer” demographic-economic characteristics for national scope census tracts. While Census 2010 provides data similar to those items in the General Demographics section, only ACS sourced data provide details on topics such as income and poverty, labor force and employment, housing value and costs, educational participation and attainment, language spoken at home, among many related items. The approximate 600 items accessible via the tract dataset are supplemented by a wide range of additional subject matter. ACS census tract data are updated annually in December of each year.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about using census tract geography and demographic-economic data.  Learn more about integrating these data with other geography, your data and use of data analytics that apply 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.

Establishments, Employment & Earnings Trends: 2015Q1

.. county & metro Establishment, Employment & Earnings (EEE) monthly-quarterly-annual time series by detailed type of business .. financial sector employment in Manhattan (New York County, NY) led the nation in average weekly wages at $8,932 during the first quarter 2015.  Use the interactive table to examine characteristics of establishments (number, employment, earnings) for counties and metros by type of business of interest. See the related Web section for more detail.  Follow that section for quarterly and interim data establishments by sector updates and use of tools to analyze patterns and trends.

The most current and comprehensive measures of business activity by county, metro and higher level geography are provided by the Establishments, Employment & Earnings (EEE) database. Use the interactive table to view, rank, query, compare data on establishments, employment and wages by county, metro and state for high level industries. Subscribers to the ProximityOne Data Service (PDS) database can use the more detailed (6-digit NAICS coverage) with data structured for time-series analysis supported with modeling and data analytics tools.

Where Does America Make Things?
The graphic below shows percent employment in the manufacturing sector (employment in the private manufacturing sector as a percent of total private sector employment January 2015 by county). Click graphic for larger view providing more detail. Use the GIS tools to analyze similar patterns for any industry. Interpreting this map graphic and alternative data resources … join us in a Data Analytics Lab session where we discuss making and interpreting this map view and alternatives.

– view developed with ProximityOne CV XE GIS and related GIS project.

The EEE quarterly data are based on employer reported data and provide EEE characteristics by detailed type of business collected and tabulated by the Bureau of Labor Statistics (BLS). Derived from reports submitted by every employer subject to unemployment insurance (UI) laws, the data cover 9.5 million employers and 136.2 million full- and part-time workers.

Important features of these data …
• Tabulated for all counties, metros, states and the U.S.
• Tabulated for detailed types of business (6-digit NAICS).
• Tabulated quarterly and annually, the data enable time-series modeling.
• Employer-based administratively collected data; not estimates.
• Short lag (5 months) between reporting date and date of data accessibility
– data for second quarter 2015 (2015Q2) are available mid-December 2015.
Limitations of these data.

Use these data to examine how a detailed type of business is changing in a county or metro … or how that type of business in one county/metro compares to another county or metro. Answer questions like how much of the healthcare sector in a particular metro is comprised by offices of physicians. Or, are the number of establishments in a business sector growing or declining? How are the characteristics of establishments in one metro changing relative to another metro?

Establishments, Employment, Earnings — Interactive Table
The following graphic illustrate use of the interactive table to examine characteristics of construction industry for California by county. The rows/counties are ranked on the rightnost column AWW15Q1 (average weekly wages, 1st quarter 2015) in descending order. It is easy to see that California was led by San Francisco county with $1,661 AWW reflecting activity of 1,564 establishments and January employment of 16,850. Click graphic for larger view.

Updates
These data update quarterly. The next update includes data for 2015Q2 and becomes available December 17, 2015 (set reminder).

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.