Tag Archives: Los Angeles

Examining County Gross Domestic Product

.. what is the annual per capita real-valued output of counties of interest? How is this measure trending? Why is this important? This section reviews tools and data to examine county-level Gross Domestic Product (GDP) trends and patterns. The first ever county-level GDP estimates to be developed as a part of the official U.S. national scope GDP estimates were released in December 2018. The county GDP estimates join the county-level personal income by major source, both now part of the Regional Economic Information System (REIS). See more detail about topics reviewed in this post in the related County GDP web section.

Patterns of Real Per Capita GDP by County
The graphic below shows patterns of per capita real GDP, 2015, by county.

– View developed using CV XE GIS and related GIS project.
– create custom views; add your own data, using the GIS project.

Gross Domestic Product (GDP) by county is a measure of the value of production that occurs within the geographic boundaries of a county. It can be computed as the sum of the value added originating from each of the industries in a county.

Example … use this interactive table to see that 2015 Los Angeles County, CA total real GDP of $656 billion was just slightly larger that than of New York County, NY (Manhattan) at $630 billion. Yet, the total 2015 population of Los Angeles County of 10.1 million is 6 times larger than that of New York County of 1.6 million — see about steps. GDP provides very different size measures, and economic insights, compared to population.

In 2015, real (inflation adjusted) Gross Domestic Product (GDP) increased in 1,931 counties, decreased in 1,159, and was unchanged in 23. Real GDP ranged from $4.6 million in Loving County, TX to $656.0 billion in Los Angeles County, CA.

This post is focused on U.S. national scope county level estimates of Gross Domestic Product (GDP) annually 2012 through 2015. This marks the first time county level GDP estimates have been developed, a part of the Regional Economic Information System (REIS). Use the interactive table to rank, compare, query counties based on per capita GDP, current GDP, real GDP by type of industry. Use the related GIS project to develop thematic map views such as the one shown below. See more about these data.

Current Annual Estimates & Projections
ProximityOne uses these and related data to develop and analyze annual Situation & Outlook demographic-economic estimates and projections. GDP items included in the table below are included in the “annual 5-year” projections as shown in the schedule of release dates; next release April 18, 2019 and quarterly.

Examining County GDP Using GIS Tools
Use the County REIS GIS project. Make your own maps; select different item to map; modify colors, labels. Zoom in views of selected states shown below. Graphics open in a new page; expand browser window for best view. Patterns: see highlighted layer in legend to left of map; MSAs bold brown boundaries with white shortname label
counties labeled with name and 2015 per capita real GDP
.. Arizona .. Alabama .. California .. Colorado .. Iowa .. Georgia .. Kansas .. Missouri
.. New York .. Nevada .. North Carolina .. South Carolina .. Nevada .. Texas .. Utah .. Vermont

Using the County GDP Interactive Table
The graphic below illustrates use of the interactive table. Tools below the table have been used to view only per capita real GDP for all sectors (total sources) and for county with total population between 50,000 and 60,000. Counties were then ranked on 2015 per capita real GDP (rightmost column).

– click graphic for larger view.

Using County GDP: Data Analytics Web Sessions
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.

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.

County-to-County Migration

Migration is one key element in determining how the demographics of an area are changing.  County to county migration data provide insights into how the county population might change in the future.

An average of approximately 130,000 people move every day in the U.S. Based on the American Community Survey 2010 5-year estimates data, 47.3 million people lived in a different house a year earlier and 17.3 million of them lived in a different county within the U.S.

Seven of the top 10 flows of movers were among counties in the Los Angeles and Riverside-San Bernardino, CA metro areas. An estimated 44,020 people, an average of about 121 per day, moved from Los Angeles County to San Bernardino County, CA.

Large County-to-County Yearly Flows 

Current County County of Residence 1 Year Ago Movers
San Bernardino, CA Los Angeles, CA 44,020
Orange, CA Los Angeles, CA 40,643
Riverside, CA Los Angeles, CA 30,443
Los Angeles, CA Orange, CA 28,450
Broward, FL Miami-Dade, FL 25,246
Riverside, CA San Bernardino, CA 23,942
Riverside, CA Orange, CA 23,663
Pinal, AZ Maricopa, AZ 21,969
Oakland, MI Wayne, MI 21,919
DuPage, IL Cook, IL 21,835
Los Angeles, CA San Bernardino, CA 20,921

Examining In-bound and Out-bound Movers in Counties of Interest
Use this interactive table (click link) to examine patterns of in-bound and out-bound county-to-county movers.  The table contains all combinations of from- and to- county movers and is quite large; it may take a minute to initially load.

The following graphic illustrates use of the interactive table showing movers from Los Angeles County “1 year ago” to the “current county of residence.”  The destination county with the largest number movers (44,020 – see pointer) was to San Bernardino County.  Note that the movers — 44,020 — is the same number as shown in the table above.  But using the interactive table, it is possible to view every destination county.  Conversely, you can determine the number of inbound movers for every origin county.

Los Angeles County Outbound Migration

Los Angeles County Outbound Migration

To develop the graphic shown above, follow the steps using the interactive table.
Click ShowAll button below table.
– Click Find R1YA button below table.
– Click R1YA Columns button below table. Table now looks similar to above view.
– Finally, click the header cell in the Movers column to sort in descending order.

Try this sequence for any county of interest — start with ShowAll button.

Determining More About Individual County Migration
View the migration profile for Oneida County, NY.  This profile can be developed for any county. The table presented in that section shows a row for each of the 182 areas (residence one year earlier) from which one or more people are estimated to have moved to Oneida County, NY.  Similar profiles for other counties:
San Diego County, CA
Broward County, FL
Honolulu County, HI
Wayne County, MI … Detroit
Stark County, ND … Bakken Field boom
Philadelphia, PA
Bee County, TX … Eagle Ford Shale development
Dimmit County, TX … Carrizo Springs
Harris County, TX … Houston

Contact me to obtain a migration profile for a county of interest.

More Current Estimates & Updates
A new post of county-to-county migration is planned for late 2013 or early 2014 using similarly structured data from ACS 2011 — a one year update to data reviewed here.   A subsequent new post of county-to-county migration is planned for mid 2014 using similarly structured data from ACS 2012 — a two year update to data reviewed here.   These three years of annual will be organized into a mini-time-series to examine annual county-to-county migration patterns over time.

Updated Views of the Urban Landscape

The geography of the urban landscape has been updated with new 2010 vintage urban areas (Urbanized Areas and Urban Clusters).  Census 2010 data have been tabulated by census block, categorizing each census block as either urban or rural.  Thus, all higher level Census 2010 geography (block groups, tracts, cities, and on up to the U.S. national level) can be characterized as percent urban and rural. See more about urban population and geography.

The graphic presented below shows the 2010 vintage Los Angeles–Long Beach–Anaheim, CA Urbanized Area (UA) with red boundary superimposed on MapQuest OpenStreetMap tile layer.  Other contiguous urban areas exist but are not shown in this view.  In this case, the UA encompasses all of the geography within the red boundary except two small areas (see pointer) north of Burbank and west of Glendale.  This reflects the fact that UAs are defined on the basis of census blocks either being urban or rural. Viewing graphic with gesture/zoom enabled device suggested.

Los Angeles 2010 Urbanized Area

Los Angeles 2010 Urbanized Area

More than 80-percent of America’s population is urban, but far more than 80-percent of America’s geography is rural.  Census 2010 shows that America’s urban population increased by 12.1 percent from 2000 to 2010, compared to the national overall growth rate of 9.7 percent. Urban areas now account for 80.7 percent of the U.S. population, compared to 79.0 percent in 2000. Use this interactive table to examine Census 2010 Urbanized Areas and how they have changed since Census 2000.

2012 Urban Area Richer Demographic-Economic Measures
Census 2010 provides very limited demographic data for urban areas (age, gender, race/origin, households, housing occupancy).  The first richer demographic-economic data for the 2010 vintage urban areas became available in September 2013 from the American Community Survey (ACS) 2012 1-year estimates.  These data are for urban areas with population 65,000 or more.  These data enable us to, for the first time, examine Urbanized Area attributes such as employment, education, language spoken, income, housing value and costs among a wide range of other measures.

Among all 2010 vintage Urbanized Areas 65,000 population or larger in 2012, the percent population 25 years and over who were college graduates ranged from 7.0% to 70.6%. Demographic-economic characteristics of urban areas are constantly changing.  Use this interactive table to view, rank, compare selected characteristics of urban areas using these data.

Access Detailed Urban Area 2012 Demographic-Economic Measures
Use the APIGateway to access detailed ACS 2012 demographic-economic profiles for any selected urban area.  A partial view of the Los Angeles UA DE-3 economic characteristics profile is shown below.  Install the no fee CV XE tools on your PC to view extended profiles for the Los Angeles or any UA. See complete Los Angeles UA DE-2 through DE-5 profiles at  Los Angeles UA demographic-economic profiles.  Viewing graphic with gesture/zoom enabled device suggested.

Los Angeles UA DE-3 Profile

Los Angeles UA DE-3 Profile

Thematic Mapping & Visual Pattern Analysis
The graphic presented below shows a thematic map of 2012 median household income (MHI) by 2010 Urbanized Area centered on Pennsylvania and the Northeast U.S.  The legend to the left of the map shows the MHI interval color pattern.  The view was developed using CV XE GIS software with items shown this interactive table integrated into the 2010 UA shapefile. Viewing graphic with gesture/zoom enabled device suggested.

2012 $MHI by 2010 UA

2012 $MHI by 2010 UA

Profile of Morgantown, WV UA (at pointer in above view)
UA Code 59275
2012 Population … 74,342
2012 Percent High School Graduates … 92.5%
2012 Percent College Graduates …  44.3%
2012 Percent in Poverty … 27.5%
2012 Median Household Income … $34,996

Hundreds or thousands of variations on pattern views such as the one shown above can be developed using the 2012 demographic-economic data in combination with the 2010 vintage UA boundary shapefile.

Related Sections
113th Congressional District Urban/Rural Characteristics
Urban/rural demographics by 113th Congressional District

State Legislative Districts Urban/Rural Characteristics
– Urban/rural demographics by 2013 State Legislative District