Future of India: Trends & Age-Cohort Analysis

The population of India is projected to change from 1.17 billion in 2010 to 1.66 billion in 2050, an increase of 483.5 million or 41.2%. How will India age-cohort patterns in 2010 compare to those projected for 2050? How do these patterns compare with those of the United States; other countries? See related Future of India Web page

This section illustrates use of population pyramids to examine age by gender demographic patterns for India as of 2010 and 2050. Similar population pyramids can be developed for any country. Population pyramids help us visualize and more easily understand age-gender structure — and how it is changing over time.

As shown in the graphic below, the population of India is projected to be the largest of any country in 2050. See related interactive table with world by countypopulation projections.

Largest 10 Countries in 2050 based on Total Projected Population

India in Context of Region

View developed with CV XE GIS; see more about this GIS project below.

Population Pyramids
Population pyramids are bar-chart graphical depictions of the population size by gender by age group. They help us understand the implications of male-female population size by age and what that might suggest for the future.

A top-heavy pyramid suggests negative population growth that might be due to many factors, including high death rates, low birthrates and increased emigration. A bottom-heavy pyramid suggests high birthrates, falling or stable death rates and potential for rapid population growth.

The population pyramid shows a male population bar chart (left side of pyramid, blue) symmetrically with a female population bar chart (right side of pyramid, light red). Each bar shows the population by 5-year age group, 0-4 years to 80-84 years and 85 years and over.

India, Total Population, 2010

X-axis shows population in thousands. Click graphic for larger view with related data table.

India, Total Population, 2050

X-axis shows population in thousands. Click graphic for larger view with related data table.

More About India Demographics; Examining Other Countries
Use the ChartGraphics tools to get answers to these types of questions and gain insights world by country age-cohort patterns over time … into the future. Population pyramids developed using ChartGraphics provide an easy-to-develop and consume visual analysis of these patterns.

ChartGraphics is available at no fee to ProximityOne User Group members. Join now, there is no fee.

Support & DMI Web Sessions
Using age-cohort analysis tools … learn more about using age-cohort patterns and analysis. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants. We can address your specific questions about using metro and county demographic economic data and related applications.

2014 Metros: Atlanta-Sandy Springs-Roswell, GA

.. examining metropolitan area dynamics … how will the market for single family homes in the Atlanta-Sandy Springs-Roswell, GA metro change over the next 5 years? 20 years? How does the metro GDP in the Atlanta metro compare to others? What are the patterns in metro rental income and homeownership/vacancy rates? How are they trending? We examine these types of topics in this section. Stakeholders can replicate applications reviewed here for this and other metros using ProximityOne no fee resources. See related HTML/Web page version.

.. this section now continuously updated … see Atlanta Metro Situation & Outlook; see related Georgia Demographic-Economic Characteristics.

Metropolitan areas include approximately 94 percent of the U.S. population — 85 percent in metropolitan statistical areas (MSAs) and 9 percent in micropolitan statistical areas (MISAs). Of 3,143 counties in the United States, 1,167 are in the 381 MSAs in the U.S. and 641 counties are in the 536 MISAs (1,335 counties are in non-metro areas).

Focus on Atlanta-Sandy Springs-Roswell, GA MSA
This section is focused on the Atlanta-Sandy Springs-Roswell, GA MSA; Core-Based Statistical Areas (CBSA) 12060. It is not intended to be a study of the metro but rather illustrate how relevant decision-making information (DMI) resources can be brought together to examine patterns and change and develop insights. The data, tools and methods can be applied to any metro.

The Atlanta-Sandy Springs-Roswell, GA MSA is shown in the graphic below. The 30-county metropolitan statistical area is shown with bold brown boundary; counties appear with black boundaries and county name labels. The thematic pattern shows a measure of economic prosperity (median household income: MHI) by census tract.

Click graphic for larger view with details; the larger view shows interval values associating MHI with income levels. Develop variations of this map view using the Mapping Georgia Neighborhood Patterns GIS resources.

Metro-County Geographic-Demographic Structure
The Census 2010 population of the metro was 5,286,728 (9th largest) compared to 5,522,942 (9th largest) based on the 2013 estimate. Metros of similar size include Miami-Fort Lauderdale-West Palm Beach, FL and Boston-Cambridge-Newton, MA-NH. See interactive table to examine other metros in a similar manner.

Click here to view a metro by county profile for the Atlanta metro. Click the county component links below to view annual county population estimates and components of change.
• Barrow County (13013)
• Bartow County (13015)
• Butts County (13035)
• Carroll County (13045)
• Cherokee County (13057)
• Clayton County (13063)
• Cobb County (13067)
• Coweta County (13077)
• Dawson County (13085)
• DeKalb County (13089)
• Douglas County (13097)
• Fayette County (13113)
• Forsyth County (13117)
• Fulton County (13121)
• Gwinnett County (13135)
• Haralson County (13143)
• Heard County (13149)
• Henry County (13151)
• Jasper County (13159)
• Lamar County (13171)
• Meriwether County (13199)
• Morgan County (13211)
• Newton County (13217)
• Paulding County (13223)
• Pickens County (13227)
• Pike County (13231)
• Rockdale County (13247)
• Spalding County (13255)
• Walton County (13297

Use this interactive table to view demographic attributes of these counties and rank/compare with other counties.

Population Pyramids & Age-Cohort Patterns
The graphic below shows the Census 2010 Fulton County population pyramid. Click graphic to view as HTML section with related Census 2010 age-gender population distribution.
Fulton County, GA; Census 2010; Total population

Use ChartGraphics examine population by age-gender-race/origin for any county.

Metro Demographic-Economic Characteristics
In 2012, the metro median household income was $54,628, percent high school graduates 87.8%, percent college graduates 35.3% and 16.6% in poverty.
Use the following U.S.-state-metro interactive table to view/compare/rank compare this metro with other areas:
• General Demographics — http://proximityone.com/usstcbsa12dp1.htm
• Social Characteristics — http://proximityone.com/usstcbsa12dp2.htm
• Economic Characteristics — http://proximityone.com/usstcbsa12dp3.htm
• Housing Characteristics — http://proximityone.com/usstcbsa12dp4.htm

Metro Per Capita Personal Income
In 2012, the Atlanta metro had a per capita personal income (PCPI) of $40,963. This PCPI ranked 131st among all MSAs (374) and was 93.7 percent of the national average, $43,735. The 2012 PCPI reflected an increase of 2.7 percent from 2011. The 2011-2012 national change was 3.4 percent. In 2000, the PCPI of the Atlanta metro was $33,764 and ranked 33rd among all metros(374). See related interactive table.

Metro Per Capita Income as a Percent of the United States

Metro Real Per Capita Personal Income
View selected Atlanta metro real per capita personal income (RPPI) patterns in this interactive table. The Atlanta metro 2012 RPPI is estimated to be $40,647. The metro ranks 149th among all 381 metros, between Savannah, GA metro ($40,676) and Clarksville, TN-KY metro ($40,627).

Metro Gross Domestic Product
View selected Atlanta metro Gross Domestic Product (GDP) patterns in this interactive table.  The Atlanta metro 2012 GDP is estimated to be $294.6 billion.  The metro ranks 32nd among all 381 metros, between Boston, MA metro ($336.2 billion) and Miami, FL metro ($274.1 billion).

Metro Cities & Places
Click link to view profile for the metro principal cities:
• Alpharetta
• Atlanta
• Marietta
• Roswell
• Sandy Springs
View similar profile for any Georgia city — Georgia Community Profiles

Metro School Districts
School districts play an important role in the metro dynamics. See more about the school district community. Examine characteristics of the school age population by type of enrollment by school district.  The largest 6 school districts in the metro are shown in this graphic:

Use this interactive table to view/rank/compare all school districts.

Children’s Demographics Profiles by School District
See more Georgia profiles
• Atlanta City Schools, GA
• Bibb County Schools, GA
• Clayton County Schools, GA
• Cobb County Schools, GA
• DeKalb County Schools, GA
• Fulton County Schools, GA
• Gwinnett County Schools, GA

Gwinnett County Public Schools, GA
See largest 100 school districts
2013-14 school year enrollment: 169,150
Map shows patterns of economic prosperity by neighborhood.
.. ACS 2012 5-year median household income for district overall: $62,216.

School district bold black boundary; click graphic for larger view
View developed using CV XE GIS and Georgia DMI GIS Project.
Click this link to view detailed 5-part demographic-economic characteristics for this school district.
See related Gwinnett county projections to 2020.

Comparing Among All School Districts
Use the following interactive table to view/compare/rank compare school districts:
• General Demographics — http://proximityone.com/sd12dp1.htm
• Social Characteristics — http://proximityone.com/sd12dp2.htm
• Economic Characteristics — http://proximityone.com/sd12dp3.htm
• Housing Characteristics — http://proximityone.com/sd12dp4.htm

About Metropolitan Areas
By definition, metropolitan areas are comprised of one or more contiguous counties. Metropolitan areas are not single cities and typically include many cities. Metropolitan areas are comprised of urban and rural areas and often have large expanses of rural territory. A business and demographic-economic synergy exists within each metro; metros often interact with adjacent metros. The demographic-economic makeup of metros vary widely and change often. See more about metros.

Using these Resources
Learn more about using resources described in this section. Join us in a Decision-Making Information Web session. These no fee, informal one-hour Web sessions focus on selected specific topic. The open structure provides for Q&A and discussion of application issues of interest to participants. We can address your specific questions about using metro, county and geographic drill-down demographic economic data and related applications.

Building Block Group Demographic Economic Datasets

Small area demographic economic data are essential in many decision-making and analytical applications that focus on neighborhoods, corridors and location-specific markets.  Block groups are the smallest geographic areas for which the Census Bureau tabulates richer demographic economic data.  Covering the U.S. wall-to-wall, these approximate 220,000 areas average 1,200 population. Now, with annually updated block group demographic economic data, there are new possibilities for trend analysis.

Census sourced block group data have been traditionally difficult to access and develop into datasets for follow-on analysis.   The Demographic Economic Data Extraction (DEDE) software can be used extract demographic-economic data from various statistical programs and datasets. This section provides an overview of using the no fee version of DEDE to extract block group level data from Census 2000, Census 2010, ACS 2010, ACS 2011 and ACS 2012.

Benefits
DEDE enables you to setup custom data extraction (geographic code lists and subject matter code lists) that can be re-used. Downloaded data may be saved in Excel an d other popular formats. Use the data with your preferred statistical analysis software. Easily integrate you data into corresponding shapefiles for GIS applications.

DEDE makes use of Application Programming Interface (API) operations that enable downloading data directly from servers. As a result, the data extraction application makes little use of locally stored data. An Internet connection is required for most applications. The batch-oriented application makes use of a nominal user interface. See more about using DEDE.

Start-up View and User Interface

Click graphic for larger view. See pointer in grid at cell showing total population (item B01001_001E from ACS 2012 5 year estimates) of 1,510 for Census 2010 block group 51510200812. See subject matter and GEOID codes in lists at left. These lists were populated by reading the geocodes file and items file shown above the grid. Export data in the grid using FileSaveAs operation.

Illustration Application Area — Alexandria, VA
Alexandria, VA bold boundary, Census 2010 block groups black boundary and Census 2000 BGs red boundary.

Click graphic for larger view and details. In larger view, labels show Census 2010 BG codes. View developed using CV XE GIS. Integrate DEDE extracted data into block group shapefiles, as shown above, to create thematic/pattern maps.

Dataset Selection/Source Statistical Program
Statistical program datasets supported by Level 1 include:
• Census 2000 Summary File 3
• Census 2010 Summary File 1
• ACS 2010 5-year estimates
• ACS 2011 5-year estimates
• ACS 2012 5-year estimates

Getting started now
The Windows-based DEDE software is available at no fee to ProximityOne User Group members. User Group members can run the installer (requires User Group ID) and start using the DEDE tool. Join in a Web meeting to learn more about using DEDE. DEDE operations are covered in the next Using Small Area Demographic-Economic Data.

Use the companion CV XE GIS to create pattern maps and perform related geospatial analyses of DEDE extracts. Use the companion SiteAnalysis API tool to interactively access these same block group data, selecting geography visually (by mouse based on map view) and aggregating block group demographic economic data for study and site location areas.

ProximityOne User Group
Join the ProximityOne User Group to keep up-to-date with new developments relating to metros and component geography decision-making information resources. Receive updates and access to tools and resources available only to members. Use this form to join the User Group. There is no fee.

Support Using these Resources
Learn more about accessing and using demographic-economic data and related analytical tools. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Examining Life Expectancy by County

Life expectancy in the United States in 2007 ranged from 65.9 to 81.1 years for men and 73.5 to 86.0 years for women. When compared against a time series of life expectancy in the 10 nations with the lowest mortality, U.S. counties range from being 15 calendar years ahead to over 50 calendar years behind for men and 16 calendar years ahead to over 50 calendar years behind for women. Between 2000 and 2007, 80% (men) and 91% (women) of U.S. counties fell in standing against this international life expectancy standard. These are among the findings reported in Population Health Metrics.

This section reviews interactive tools and resources that you can use to examine county life expectancy and related data.

Male Life Expectancy by County, 2007

County Life Expectancy Interactive Table
Use the Web interactive table to view, compare, analyze the U.S. by county level data from the above study in combination with related demographic-economic measures.

The following graphic illustrates how the table can be used to examine life expectancy patterns by county. A query is used to select only Charlotte NC-SC metro counties, Each row shows data for a county. The 2000 and 2007 life expectancy data are shown at right in the graphic,

Visual Analysis using GIS Resources
Use GIS tools to visually examine life expectancy patterns. Create thematic pattern maps such as the male life expectancy by county pattern map shown above or corresponding female pattern map shown below. Members of the ProximityOne User Group may download and use the county life expectancy GIS project to develop maps like these. Zoom into regions of interest. Add other layers. Label the maps as desired. Use other subject matter to develop related pattern views. Modify the legend defining life expectancy intervals.

Female Life Expectancy by County, 2007

Healthcare Analysis and Situation & Outlook
The ProximityOne Situation & Outlook (S&O) Program is a combined database and interpretive resource that you can use to better understand the existing healthcare situation, find out how area demographic-economic conditions are changing, and assess how changing conditions might impact various components of the healthcare infrastructure.

Support Using these Resources
Learn more about healthcare geographic-demographic-economic data, patterns and related analytical tools. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Housing Price Index; 2014Q1 Update

The Housing Price Index (HPI), calculated using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages, continued upward momentum in U.S. house prices remained strong in the first quarter 2014, as prices rose 1.3 percent from the previous quarter. This is the eleventh consecutive quarterly price increase in the purchase-only, seasonally adjusted index.

As measured with purchase-only indexes for the 100 most populated metropolitan areas in the U.S., first quarter price increases were greatest in the Charleston-North Charleston, SC MSA where prices increased by 10.7 percent. Prices were weakest in the New Orleans-Metairie, LA MSA, where they fell 2.6 percent. Positive appreciation was recorded in 71 of the 100 MSAs. This section provides additional details on HPI change by metro from 2013Q1 to 2014Q1 and access to related analytical tools for extended analyses.

Visual Analysis of 2013Q1-2014Q1 HPI Patterns
The following graphic shows housing value appreciation 2013Q1-2014Q1 by metro based on the HPI.

Click graphic for larger view and details. This view developed using CV XE GIS and related GIS project. Members of the ProximityOne User Group (join now, no fee) may used the CV XE GIS software and GIS project to create similar views with different HPI measures. Zoom-in. Add labels. Add other geography/data. Create views/graphics for reports and stories.

Interactive Table
Use the interactive table to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all Metropolitan Statistical Areas (MSAs), states and the U.S. The interactive table provides an easy way to rank/compare housing prices for a single metro area or a group of metros.

Metros with Highest Appreciation, 2013Q1-2014Q1

Click graphic for larger view. Use interactive table for extended views/analyses,

Metros Experiencing Greatest HPI Decrease, 2013Q1-2014Q1

Click graphic for larger view. Use interactive table for extended views/analyses,

More About the HPI
The Housing Price Index (HPI) provides a measure to examine/analyze housing price levels and variations among metros and states. The HPI alone provides only partial insights — based on this one measure. Evaluation of housing markets, and the regional economy, trends and patterns need to use the HPI in combination with many other measures. Situation & Outlook reports integrate HPI data with other demographic-economic measures.

Quarterly Update
This section is updated quarterly. The latest quarterly HPI data are for the 1st quarter 2014 as reviewed here. These data will be update on August 26, 2014, with 2nd quarter 2014 data and related prior quarterly estimates and re-computed quarterly change values (last column).

Support Using these Resources
Learn more about accessing, integrating and using housing market data. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

2014 Elections: Data Driven Strategies

.. use of geodemographics will have a big impact on the outcomes of many 2014 elections. Many campaigns are gearing up now for the general elections to be held November 4, 2014. Elections will include all 435 seats in the U.S. House of Representatives, 33 seats in the U.S. Senate, 46 state legislatures among many others. How to more effectively examine characteristics and trends of the voting population?  Where are voters with a higher propensity to vote for your candidate located? Which elections might be most effectively impacted by the use of geodemographics?  Join in this no fee one-hour web session where we examine tools and resources to examine geodemographics relating to state legislative districts and congressional districts.

New York 12th Congressional District & vicinity
… using GIS resources to examine a congressional district by neighborhood
… examining neighborhood patterns of economic prosperity
… NY 12th Congressional District (bold black boundary)

click graphic for larger view with details. View developed using CV XE GIS.

Topics
2014 Elections: Data Driven Strategies
Geography of State Legislative Districts & 113th Congressional Districts
– State Legislative Districts
– Congressional Districts
Examining Characteristics & Patterns
– strategies for accessing & using demographic-economic data
– geographies: census blocks, voting districts, block groups, tracts, cities/places
– interactive analytical tables:  congressional districts;  state legislative districts
– examining 2012 elections & vote by candidate
– mapping patterns of economic prosperity by neighborhood across districts
– using ACS 2010 5 year estimates and Site Analytics tools to examine sub-district demographics
– accessing census block demographics via API
– voting-age population demographics
Redistricting: congressional; state legislative; city, special area; school districts
2014 elections & campaign strategic planning & analysis

Next Session: June 10, 2014
– Register here
– Related events

Analyzing Metro Characteristics & Trends

.. how to more effectively examine characteristics and trends of individual metros and among metro areas?  Where are the largest and fastest growing metros?  Join in this no fee one-hour web session where we examine tools and resources to rank, compare, and query metro geographic-demographic-economic patterns.

Topics
– 2013 Metro delineations — metro-county structure … principal cities
– Metro Gross Domestic Product
– Real Per Capita Personal Income
– Housing Price Index
– Metro Rental Market Conditions
– Model-based Population Estimates & Components of Change
– Demographic-Economic Interactive Tables
– Regional Economic Information System updates
– Projections & long-term change in metro demographic-economic patterns
– County Component Projections to 2020
– Examining metro dynamics — Austin-Round Rock, TX Metro
– geographic drill-down into Metros — linking multi-sourced county and census tract data

Next Session: July 29, 2014
– Register here
– Related events

Examining Children’s Demographics by Congressional District

Examining children’s demographics patterns by school district in context of the 113th Congressional Districts … GIS tools enable you to blend different types of geography and subject matter to support planning, analysis and decision-making.

The thematic map below shows patterns of percent grade relevant children ages 5-17 by school district for Ohio and adjacent states. The red pattern shows districts having %Relevant Children Not Enrolled Ages 5-17 value of 10% or more. Click the graphic for larger view and details. The expanded view shows legend and color/interval settings.

113th Congressional Districts are shown with bold black boundaries and yellow labels. It is easy to see groupings of school districts by congressional district with distinctive patterns.

View developed using CV XE GIS software and associated GIS project.

See more about resources to examine children’s demographic-economic characteristics by type of enrollment and school district.

Support Using these Resources
Learn more about accessing, integrating and using data for school districts and congressional districts. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.