Tag Archives: county trends

County 5-Year Trends: Income & Income Inequality

.. tools and data to examine how the U.S. by county household income and income inequality are changing … how is household income changing in counties of interest? What are the trends; what is causing the change? What are the characteristics of income inequality and how is it changing? How might this change impact your living environment and business?

This section provides access to tools and data to examine U.S. by county measures of household income and income inequality between two 5-year periods (2006-10 and 2011-2015). These data can provide insights into how household income and income inequality are changing for one county, a group of counties and the U.S. overall. Use the interactive table to view median household income and measures income inequality for all counties. See more detail about these topics here. Measures of income inequality can be estimates/examined using the Gini Index.

The Gini Index & Measuring Income Inequality
The Gini Index is a dimensionless statistic that can be used as a measure of income inequality. The Gini index varies from 0 to 1, with a 0 indicating perfect equality, where there is a proportional distribution of income. A Gini index of 1 indicates perfect inequality, where one household has all the income and all others have no income.

At the national level, the 2015 Gini index for U.S. was 0.482 (based on 2015 ACS 1-year estimates) was significantly higher than in the 2014 ACS Index of 0.480 (based on 2014 ACS 1-year estimates). This increase suggests that income inequality increased across the country.

Examining Household Income & Income Inequality Patterns & Change
The following two graphics show patterns of the GIni Index by county. The first view is based on the American Community Survey (ACS) 2010 5-year estimates and the second is based on the ACS 2015 5-year estimates. The ACS 2010 estimates are based on survey respondents during the period 2006 through 2010. The ACS 2015 estimates are based on survey respondents during the period 2011 through 2015. One view compared with the other show how patterns of income inequality has changed at the county/regional level between these two 5-year periods.

Following these Income Inequality views are two corresponding views of median household income; using data from ACS 2010 and ACS 2015. Use CV XE GIS software with the GIS project to create and examine alternative views.

Patterns of Income Inequality by County; ACS 2010
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Income Inequality by County; ACS 2015
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Economic Prosperity by County; ACS 2010
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Economic Prosperity by County; ACS 2015
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

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.

New Residential Construction by County

.. what’s happening in the north Dallas metro? .. a lot, take a look at the patterns of new residential construction for Collin and Denton counties using data and tools presented in this section. Examine new residential construction, leading economic indicator, for counties and regions of interest to you anywhere in the U.S. Use of the Regional Demographic-Economic Modeling System (RDEMS) to examine patterns of residential construction in context of related wide-ranging, multi-sourced data.

This section provides a summary of new housing units authorized by building permits for new residential construction for each/all counties. Use data analytics tools and data described here analyze these data and related housing issues.
• interactive data analytics – details/access
• use GIS project/datasets – details/access
• access individual county profiles – details/access

Patterns of New Authorized Residential Units by County
The following graphic shows the 2015 per capita value of total units authorized by county. The four largest Texas metros are shown with bold brown boundaries.
See about subject matter included in datasets.

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

Additional views with counties labeled with name, 2015 housing units and 2015 total new housing units authorized.
Charlotte, NC-SC metro by county
Dallas, TX metro by county
Houston, TX metro by county

Leading Economic Indicator
Building permit data (housing units authorized by building permits for new residential construction) are economic leading indicators. Investors and housing developers use these data to examine the characteristics and trends in new residential housing development. The short time lag between the data reference date and data access date, 1-2 months, makes this set of indicators important in assessing the current situation and patterns during the past year or more. The national scope coverage and geographic granularity (state, metro, county and city) enable comparison among types of areas and peer groups. Finance and real estate professional and researchers examine building permit patterns to develop strategic insights. Government and policy makers use these data to get a pulse on markets and changing patterns to administer programs and operations. See more about these data below in this section.

New residential construction begins with building permits. Overall U.S. housing starts are approximately 2.5% less than permits issued (22.5% less for multi-family units). Completions are approximately 4% less than starts (7.5% less for multi-family units). During the past year-plus, “residential fixed investment” has been approximately $500 billion and remained steady at 3.1% of real Gross Domestic Product.

Access Individual County Profiles
The following graphic illustrates use of the Regional Demographic-Economic Modeling System (RDEMS) to access the HSG1 Housing Units & New Residential Construction tables for a selected county. Click graphic for larger view.

Mecklenburg County, NC [37119] located in the Charlotte, NC-SC metro

Add a link to your Web page for areas of interest: The URL structure for Mecklenburg County is:
http://proximityone.com/rdems/1/rdems37119hsg1.htm
– more in general, substitute the county state+county FIPS code (37119 in this case) to access a county of interest.

Using the Interactive Table
The interactive table includes a row for each county. Column structure and content are described below the table.
• Click the StCty link to view the housing unit/new construction profile.
• Select a metro to examine component counties

The following graphic illustrtaes use of the table to examine characteristics of the Dallas metro counties. 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.

Analyzing Business Establishment Change by County/ZIP & Industry

.. Harris County, TX (Houston) gained 1,658 business establishments between 2012 and 2013. How did the number and characteristics of business establishments in your counties or region of interest change? These data are available by county (and ZIP code) and can be used to determine which counties (ZIP codes) are experiencing business growth or decline and by how much. See more about this topic in the related Web section.

These data are based on a annual count of business establishments by physical location that have at least one paid employee. A single company may have multiple business establishments. Attributes of individual establishments, including payroll and employment, are summarized/aggregated by county and ZIP code area. The establishment data are also summarized by the NAICS type of business code. See more about these data.

Examine a specific industry such as construction. Among all counties, Harris County, TX had the highest 2013 employment in the construction industry (see more below). Where do your counties/ZIP code areas rank (in this or any other industry)?

The following views illustrate how Geographic Information System (GIS) tools can be used to visually examine change in business patterns. Use the CV XE GIS and associated GIS project to examine establishments, payroll and employment by detailed type of business. These applications shown change for one year; choose a different set of years. Integrate your own data such as market territories or customer/prospect data to examine how business opportunities match up with existing and changing patterns.

Change in Business Establishments, 2012-2013 — Texas by County
The following graphic shows the change in the number of business establishments by county in Texas and adjacent areas. Metros are shown with bold black outlines. Color patterns show change in the number of establishments between 2012 and 2013. It is easy to see which counties have business establishment growth (blue/green) or decline (orange/red). Use the GIS resources to develop similar business patterns views for any state/area in the U.S. The legend at left of map (click graphic for larger view with legend) shows establishment change intervals by color.

  — view created using CV XE GIS and associated GIS Project
— click graphic for larger view showing details.

Change in Business Establishments, 2012-2013 — Houston Area
The following graphic shows the change in the number of business establishments by county with a zoom-in view of the Houston area. Use the GIS resources to zoom in to any county/region of the U.S. The legend at left of map (click graphic for larger view with legend) shows establishment change intervals by color. Counties are labeled with county name and percent change in the number of establishments between 2012 and 2013.

  — view created using CV XE GIS and associated GIS Project
— click graphic for larger view showing details.

Profile of County Business Establishment Change
The following table shows a basic overview of the change. There is much more detail available. The GIS project enables mixing demographic with economic and business data.

Database Queries:
Counties with Highest Employment in Construction Industry
Consider a requirement to determine the list of 10 counties having the highest employment in the construction industry. The 2.1 million record database with county by type of business is opened with the CV XE GIS dBrowse operation/feature. Note that this database size exceeds the Excel limit. A query is placed on the database to show on NAICS (type of business) code “23—-” having number of 2013 employment of 10,000 or more. The query could have been any NAICS code in combination with another attribute or none. The table is then sorted in descending order on 2013 employment (by clicking the sort button). The resulting records/counties are displayed as shown. The county FIPS code 201 in state FIPS code 48 (Harris County) has the highest total construction industry employment in the U.S. It is easy to see the other top 10 (or some group) that are also highly ranked. The Count operation is used to shown how many counties meet this criteria; there are 118. Other selected attributes are shown in the table/graphic. This selection could optionally be exported to a file in a different format (e.g., CSV).

An upcoming section will review linking business establishment data with demographic data.

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.