This document provides an overview of Esri's 2012/2017 demographic updates. It discusses changes in population, households, housing, and other factors since the 2010 Census according to new data sources. It notes challenges in estimating changes from the Census to 2012 due to differences between American Community Survey multi-year estimates and past single-year sample data. The updates provide population and other demographic projections and estimates at various geographic levels through 2017.
Florida: An Economic Overview by Amy BakerAPA Florida
- Florida's economy grew 1.4% in 2010 after declining for two years, but personal income fell in Q3 2011 for the first time since 2009. Unemployment remained high at 9.9% in December 2011.
- While housing sales and permits have increased year-over-year, foreclosure rates remain high and home prices are flat. Population growth is expected to increase to around 1.1% by 2030, fueling economic growth.
- The recovery has been slow as the state has yet to regain the 779,700 jobs lost. Challenges remain such as high unemployment, tight credit conditions, and problems in the Eurozone economy.
This document provides an analysis of economic trends from 2010-2015 based on an Esri white paper. It finds that while some measures of economic recovery are present, such as stabilizing home values and population growth resuming in some areas, other indicators continue to decline, including ongoing job losses. Recovery has been uneven, with metropolitan areas generally faring worse than rural areas in terms of income declines and continued job losses. The economic outlook remains uncertain, with concerns about a potential double-dip recession.
This document provides a summary of demographic, economic, and labor market data for Jefferson County. The population increased slightly between 2000 and 2013, driven primarily by natural growth and domestic migration. The population is aging, with fewer residents of prime working age. Educational attainment improved modestly over this period. The county saw significant growth in the number of establishments between 2000 and 2011, largely through new business formation. The largest industries are manufacturing, government, retail trade, and healthcare, although manufacturing experienced job losses since 2002.
Regional Snapshot: Affordable Housing - July 2017 ARCResearch
- Home ownership and household formation rates have declined dramatically compared to historic trends, while home prices have risen significantly faster than wages due to dwindling housing supply. Adding transportation costs further worsens housing affordability.
- Rental costs have also risen sharply, especially in the suburbs, while the number of affordable units, particularly for extremely low-income households, has decreased.
- Most affordable housing is located in low-opportunity areas, maintaining the cycle of generational poverty.
The Atlanta region population grew by over 78,000 people between 2016 and 2017, with Fulton County experiencing the largest growth of 17,100 new residents. While population growth has slowed compared to previous decades, the 2017 increase was higher than the annual average of the 1990s and 2000s. Most new residential development, both single and multi-family, is occurring in the northern suburbs of the region. The City of Atlanta permitted over 8,000 new units in 2016, mostly multi-family, more than any other jurisdiction.
Whether the Great Recession has ended remains debatable in the second quarter of 2010, though many economists believe that the recession, begun in December 2007, probably ended sometime in the third or fourth quarter of 2009. Recovery also remains debatable. Fears over a double-dip
recession persist.
The Columbus MSA added 12,300 jobs in 2013 and continues to rank very well against comparable U.S. metros, according to Columbus 2020, the economic development organization in the Columbus Region. The final quarterly economic update for the 2013 calendar year covers regional economic data and development activities in the fourth quarter and throughout the year.
Florida: An Economic Overview by Amy BakerAPA Florida
- Florida's economy grew 1.4% in 2010 after declining for two years, but personal income fell in Q3 2011 for the first time since 2009. Unemployment remained high at 9.9% in December 2011.
- While housing sales and permits have increased year-over-year, foreclosure rates remain high and home prices are flat. Population growth is expected to increase to around 1.1% by 2030, fueling economic growth.
- The recovery has been slow as the state has yet to regain the 779,700 jobs lost. Challenges remain such as high unemployment, tight credit conditions, and problems in the Eurozone economy.
This document provides an analysis of economic trends from 2010-2015 based on an Esri white paper. It finds that while some measures of economic recovery are present, such as stabilizing home values and population growth resuming in some areas, other indicators continue to decline, including ongoing job losses. Recovery has been uneven, with metropolitan areas generally faring worse than rural areas in terms of income declines and continued job losses. The economic outlook remains uncertain, with concerns about a potential double-dip recession.
This document provides a summary of demographic, economic, and labor market data for Jefferson County. The population increased slightly between 2000 and 2013, driven primarily by natural growth and domestic migration. The population is aging, with fewer residents of prime working age. Educational attainment improved modestly over this period. The county saw significant growth in the number of establishments between 2000 and 2011, largely through new business formation. The largest industries are manufacturing, government, retail trade, and healthcare, although manufacturing experienced job losses since 2002.
Regional Snapshot: Affordable Housing - July 2017 ARCResearch
- Home ownership and household formation rates have declined dramatically compared to historic trends, while home prices have risen significantly faster than wages due to dwindling housing supply. Adding transportation costs further worsens housing affordability.
- Rental costs have also risen sharply, especially in the suburbs, while the number of affordable units, particularly for extremely low-income households, has decreased.
- Most affordable housing is located in low-opportunity areas, maintaining the cycle of generational poverty.
The Atlanta region population grew by over 78,000 people between 2016 and 2017, with Fulton County experiencing the largest growth of 17,100 new residents. While population growth has slowed compared to previous decades, the 2017 increase was higher than the annual average of the 1990s and 2000s. Most new residential development, both single and multi-family, is occurring in the northern suburbs of the region. The City of Atlanta permitted over 8,000 new units in 2016, mostly multi-family, more than any other jurisdiction.
Whether the Great Recession has ended remains debatable in the second quarter of 2010, though many economists believe that the recession, begun in December 2007, probably ended sometime in the third or fourth quarter of 2009. Recovery also remains debatable. Fears over a double-dip
recession persist.
The Columbus MSA added 12,300 jobs in 2013 and continues to rank very well against comparable U.S. metros, according to Columbus 2020, the economic development organization in the Columbus Region. The final quarterly economic update for the 2013 calendar year covers regional economic data and development activities in the fourth quarter and throughout the year.
The housing market has corrected significantly with home prices falling and affordability ratios declining. Housing production and starts are at their lowest levels since World War II. Completions and placements are nearing the low point seen from 1974-1983. However, household growth has slowed, vacancy rates remain high, employment growth has not reduced unemployment, and foreclosures continue to put pressure on prices. While long-run housing demand is estimated to be over 16 million units from 2010-2020 if headship rates remain steady, the recovery will likely be slow due to ongoing headwinds in the market like high inventory and tight credit.
This study projects the impact of population aging on future housing stock and prices in both provincial and national markets.
Mario Fortin,
Professor,
Université de Sherbrooke
The document discusses Esri's 2011/2016 updated demographic data. It notes that Census 2010 marked the end of a turbulent decade and new ways to measure population change. Esri's updated data incorporates Census 2010 counts and geography and evaluates and revises its forecasting models. The updates also accommodate differences in American Community Survey data compared to previous census sample data, such as smaller sample sizes and gaps in some variable reporting.
The Changing Family Structure in the Atlanta RegionARCResearch
- Between 1970 and 2010, the percentage of families with children headed by single parents in the Atlanta region increased dramatically from less than 14% to almost 34%.
- Every county in the region saw double-digit percentage point increases in single-parent families over this period, with only Fulton county seeing a decrease between 2000-2010.
- Conversely, the proportion of husband-wife families decreased significantly across the region from nearly 71% in 1970 to 46% in 2010.
1. The US Federal Reserve raised interest rates from 0.25-0.5% to 0.5-0.75% and plans additional rate hikes in 2017-2019, which will affect consumer borrowing and savings rates. Higher US rates also pose problems for China's high debt levels and capital outflows.
2. The evacuation of civilians from Aleppo was suspended amid accusations from all sides, leaving civilians at risk of killing and torture. The situation is a "synonym for hell."
3. The Philippine president said the country does not need US support and will likely repeal a military deal with the US. Meanwhile, China seized an American underwater drone in the South China Sea, raising tensions.
Regional Snapshot: ARC Employment Centers: Core Locations for Jobs, not for A...ARCResearch
This month’s Regional Snapshot picks up where the July Regional Snapshot on Affordable Housing left off. In the October Regional Snapshot we take a deeper dive into affordable housing data, mapping it onto our region’s employment centers in an effort to visualize the relationship between housing affordability and concentrations of regional employment.
The document discusses 10 major themes for 2010 and beyond related to offsetting economic forces. Some of the key themes discussed include: 1) The US dollar may be neutral in early 2010 but weaken later in the year as US economic weakness persists relative to other economies. 2) Rising US government borrowing needs may be offset by increasing consumer savings and shifts to fixed income. 3) The need for the US to cut spending and raise taxes may be offset by the US simply printing more money to avoid difficult political choices.
This document discusses the redevelopment of Kakaako, Hawaii into an urban core living area. It provides background on the creation of the Hawaii Community Development Authority in 1976 to redevelop Kakaako. While development was initially slow, the population has grown from 2,250 residents in 1990 to over 10,000 residents in 2010. The document examines demographic and housing trends in Kakaako based on 2010 census data, showing a vacancy rate of 14% and homeownership rate of 46.4%. It also discusses factors driving increased demand for urban core living, like changing household compositions and preferences for more convenient lifestyles among newer generations.
The document discusses projections for Orlando's future population, demographics, industries, and workforce by the year 2030. It projects that:
1) Orlando's population will grow to over 5.2 million people by adding over 1,500 new residents per week, with Osceola County growing the fastest at over 50%.
2) Seniors will outnumber children for the first time, with over 1 million seniors residing in the region.
3) Half of Orlando's population growth since 2010 has come from international migration, contributing significantly to its growing diversity.
4) The fastest growing industry will be home healthcare and social assistance, increasing employment by 64%, while manufacturing and construction jobs will also grow faster than national
The number of establishments in Harrison County doubled between 2000 and 2011, largely due to the natural increase of new businesses being launched. By 2011, the majority of establishments (57%) fell into Stage 1, having 2-9 employees. The top five employers in 2015 included Horseshoe Southern Indiana casino, Harrison County Hospital, Tyson Foods, Blue River Services housing nonprofit, and ICON Metal Forming, producing a mix of local, national and global goods and services.
The population of Harrison County increased 14% between 2000-2013, driven by natural increase and domestic in-migration. While the population grew, it aged, as seen in shifting population pyramids. The number of establishments doubled from 2000-2011, primarily through new establishments rather than relocating establishments. Top employers span local, national, and global industries. Government and manufacturing jobs declined the most between 2002-2013, while real estate grew 38%.
The document provides an analysis of the real estate market in Princeton and Greater Princeton, NJ from January 2020. It discusses inventory levels, pending sales, absorption rates and other metrics in different towns over the past 3-4 years. The markets show signs of stability with absorption rates around 10 months and inventory either steady or declining in most towns. The summary also notes signs of modest price increases in the state.
This document provides an overview and outlook for investments in 2017. It discusses how the Federal Reserve has kept interest rates low due to global economic fragility and negative yields abroad. It also notes that overall global debt continues to rise rapidly, including large increases in US government, corporate, and consumer debt as well as Chinese corporate debt. The outlook expects US economic growth to continue and for the Federal Reserve to gradually raise interest rates, while emphasizing the importance of diversification and managing risk.
Another Step in Canadian Federal Pension RepairEmily Jackson
The document summarizes Canada's trade performance in Q1 2014. Key points:
- Canada registered its first trade surplus since 2011, fueled by record energy trade surplus that offset a non-energy trade deficit.
- Exports and imports contracted in Q1 due to weather impacts and a trucker strike, but net exports are expected to contribute to GDP growth.
- The weaker Canadian dollar and stronger U.S. and European growth are expected to boost Canadian exports, especially energy and machinery, through 2015. Transportation constraints remain a challenge for some sectors like agriculture.
The total population of Floyd County increased by 8% between 2000 and 2013, driven by natural increase and domestic migration. The population is aging as the proportion of residents under 50 is declining. While remaining mostly white, racial and ethnic diversity is growing slowly. Educational attainment improved with more adults holding college degrees.
The document provides demographic, economic, and labor market data and analysis for Floyd County, Indiana. It summarizes that between 2000-2013, the county's population grew by 8% largely due to natural increase and domestic migration. While the population grew, it also aged as the proportion of residents under 50 declined. The county saw increases in racial, ethnic, and educational diversity over this period. Regarding the economy, the number of establishments doubled from 2000-2011 primarily through new business formation. The top five industries were government, manufacturing, healthcare, retail, and accommodation/food services, employing over 59% of workers. Government and healthcare added jobs while manufacturing and retail lost jobs from 2002-2013.
According to the most recent estimates from the Bureau of Labor Statistics, total nonfarm employment in Detroit stood at ~2.0 million payrolls, representing an annualized increase of 49,400 jobs or 2.6 percent.
Pulaski County experienced steady growth in the number of business establishments between 2000 and 2011. The number of establishments increased by 311, or 31%, due entirely to new businesses being launched within the county. By 2011, there were 1,304 total establishments, the majority of which (55%) had between 2-9 employees. Only 2 establishments had over 500 employees. While economic growth has occurred, most businesses in Pulaski County remain small in size.
Pew Hispanic: "La población inmigrante no autorizada 2010"Alcance Media Group
The document provides estimates of the unauthorized immigrant population in the United States from 2000 to 2010. The key points are:
1) The number of unauthorized immigrants living in the US was estimated to be 11.2 million in 2010, virtually unchanged from 11.1 million in 2009.
2) After increasing steadily since 1990, the unauthorized immigrant population peaked at 12 million in 2007 before declining to 11.1 million in 2009, representing the first significant reversal in the pattern of growth over the previous two decades.
3) The number stabilized in 2010 following the two-year decline, halting the reversal for now. Mexicans remain the largest group of unauthorized immigrants, accounting for 58% of the total population.
El documento habla sobre la promoción y publicidad. Define la promoción como el proceso de transmitir información sobre productos o una organización al mercado. Explica que la promoción incluye herramientas como la promoción de ventas, relaciones públicas, ventas personales y marketing directo. También describe los diferentes tipos de promoción de ventas y fuerza de ventas, así como conceptos como marketing directo y publicidad.
EPOP: Quantifying Violent Risk for Every Point on the PlanetEsri
EPOP is a risk evaluation tool that delivers precise political violence risk assessments for any location on Earth. It combines multiple data sources into a single model to produce risk scores from 0-10 for war, terrorism, civil unrest, and combined political violence. GIS software is used to automate the model, which calculates risk for over 2 billion points on the planet. Companies use EPOP to assess security risks at locations and along routes for applications like corporate security, insurance, and business development.
The housing market has corrected significantly with home prices falling and affordability ratios declining. Housing production and starts are at their lowest levels since World War II. Completions and placements are nearing the low point seen from 1974-1983. However, household growth has slowed, vacancy rates remain high, employment growth has not reduced unemployment, and foreclosures continue to put pressure on prices. While long-run housing demand is estimated to be over 16 million units from 2010-2020 if headship rates remain steady, the recovery will likely be slow due to ongoing headwinds in the market like high inventory and tight credit.
This study projects the impact of population aging on future housing stock and prices in both provincial and national markets.
Mario Fortin,
Professor,
Université de Sherbrooke
The document discusses Esri's 2011/2016 updated demographic data. It notes that Census 2010 marked the end of a turbulent decade and new ways to measure population change. Esri's updated data incorporates Census 2010 counts and geography and evaluates and revises its forecasting models. The updates also accommodate differences in American Community Survey data compared to previous census sample data, such as smaller sample sizes and gaps in some variable reporting.
The Changing Family Structure in the Atlanta RegionARCResearch
- Between 1970 and 2010, the percentage of families with children headed by single parents in the Atlanta region increased dramatically from less than 14% to almost 34%.
- Every county in the region saw double-digit percentage point increases in single-parent families over this period, with only Fulton county seeing a decrease between 2000-2010.
- Conversely, the proportion of husband-wife families decreased significantly across the region from nearly 71% in 1970 to 46% in 2010.
1. The US Federal Reserve raised interest rates from 0.25-0.5% to 0.5-0.75% and plans additional rate hikes in 2017-2019, which will affect consumer borrowing and savings rates. Higher US rates also pose problems for China's high debt levels and capital outflows.
2. The evacuation of civilians from Aleppo was suspended amid accusations from all sides, leaving civilians at risk of killing and torture. The situation is a "synonym for hell."
3. The Philippine president said the country does not need US support and will likely repeal a military deal with the US. Meanwhile, China seized an American underwater drone in the South China Sea, raising tensions.
Regional Snapshot: ARC Employment Centers: Core Locations for Jobs, not for A...ARCResearch
This month’s Regional Snapshot picks up where the July Regional Snapshot on Affordable Housing left off. In the October Regional Snapshot we take a deeper dive into affordable housing data, mapping it onto our region’s employment centers in an effort to visualize the relationship between housing affordability and concentrations of regional employment.
The document discusses 10 major themes for 2010 and beyond related to offsetting economic forces. Some of the key themes discussed include: 1) The US dollar may be neutral in early 2010 but weaken later in the year as US economic weakness persists relative to other economies. 2) Rising US government borrowing needs may be offset by increasing consumer savings and shifts to fixed income. 3) The need for the US to cut spending and raise taxes may be offset by the US simply printing more money to avoid difficult political choices.
This document discusses the redevelopment of Kakaako, Hawaii into an urban core living area. It provides background on the creation of the Hawaii Community Development Authority in 1976 to redevelop Kakaako. While development was initially slow, the population has grown from 2,250 residents in 1990 to over 10,000 residents in 2010. The document examines demographic and housing trends in Kakaako based on 2010 census data, showing a vacancy rate of 14% and homeownership rate of 46.4%. It also discusses factors driving increased demand for urban core living, like changing household compositions and preferences for more convenient lifestyles among newer generations.
The document discusses projections for Orlando's future population, demographics, industries, and workforce by the year 2030. It projects that:
1) Orlando's population will grow to over 5.2 million people by adding over 1,500 new residents per week, with Osceola County growing the fastest at over 50%.
2) Seniors will outnumber children for the first time, with over 1 million seniors residing in the region.
3) Half of Orlando's population growth since 2010 has come from international migration, contributing significantly to its growing diversity.
4) The fastest growing industry will be home healthcare and social assistance, increasing employment by 64%, while manufacturing and construction jobs will also grow faster than national
The number of establishments in Harrison County doubled between 2000 and 2011, largely due to the natural increase of new businesses being launched. By 2011, the majority of establishments (57%) fell into Stage 1, having 2-9 employees. The top five employers in 2015 included Horseshoe Southern Indiana casino, Harrison County Hospital, Tyson Foods, Blue River Services housing nonprofit, and ICON Metal Forming, producing a mix of local, national and global goods and services.
The population of Harrison County increased 14% between 2000-2013, driven by natural increase and domestic in-migration. While the population grew, it aged, as seen in shifting population pyramids. The number of establishments doubled from 2000-2011, primarily through new establishments rather than relocating establishments. Top employers span local, national, and global industries. Government and manufacturing jobs declined the most between 2002-2013, while real estate grew 38%.
The document provides an analysis of the real estate market in Princeton and Greater Princeton, NJ from January 2020. It discusses inventory levels, pending sales, absorption rates and other metrics in different towns over the past 3-4 years. The markets show signs of stability with absorption rates around 10 months and inventory either steady or declining in most towns. The summary also notes signs of modest price increases in the state.
This document provides an overview and outlook for investments in 2017. It discusses how the Federal Reserve has kept interest rates low due to global economic fragility and negative yields abroad. It also notes that overall global debt continues to rise rapidly, including large increases in US government, corporate, and consumer debt as well as Chinese corporate debt. The outlook expects US economic growth to continue and for the Federal Reserve to gradually raise interest rates, while emphasizing the importance of diversification and managing risk.
Another Step in Canadian Federal Pension RepairEmily Jackson
The document summarizes Canada's trade performance in Q1 2014. Key points:
- Canada registered its first trade surplus since 2011, fueled by record energy trade surplus that offset a non-energy trade deficit.
- Exports and imports contracted in Q1 due to weather impacts and a trucker strike, but net exports are expected to contribute to GDP growth.
- The weaker Canadian dollar and stronger U.S. and European growth are expected to boost Canadian exports, especially energy and machinery, through 2015. Transportation constraints remain a challenge for some sectors like agriculture.
The total population of Floyd County increased by 8% between 2000 and 2013, driven by natural increase and domestic migration. The population is aging as the proportion of residents under 50 is declining. While remaining mostly white, racial and ethnic diversity is growing slowly. Educational attainment improved with more adults holding college degrees.
The document provides demographic, economic, and labor market data and analysis for Floyd County, Indiana. It summarizes that between 2000-2013, the county's population grew by 8% largely due to natural increase and domestic migration. While the population grew, it also aged as the proportion of residents under 50 declined. The county saw increases in racial, ethnic, and educational diversity over this period. Regarding the economy, the number of establishments doubled from 2000-2011 primarily through new business formation. The top five industries were government, manufacturing, healthcare, retail, and accommodation/food services, employing over 59% of workers. Government and healthcare added jobs while manufacturing and retail lost jobs from 2002-2013.
According to the most recent estimates from the Bureau of Labor Statistics, total nonfarm employment in Detroit stood at ~2.0 million payrolls, representing an annualized increase of 49,400 jobs or 2.6 percent.
Pulaski County experienced steady growth in the number of business establishments between 2000 and 2011. The number of establishments increased by 311, or 31%, due entirely to new businesses being launched within the county. By 2011, there were 1,304 total establishments, the majority of which (55%) had between 2-9 employees. Only 2 establishments had over 500 employees. While economic growth has occurred, most businesses in Pulaski County remain small in size.
Pew Hispanic: "La población inmigrante no autorizada 2010"Alcance Media Group
The document provides estimates of the unauthorized immigrant population in the United States from 2000 to 2010. The key points are:
1) The number of unauthorized immigrants living in the US was estimated to be 11.2 million in 2010, virtually unchanged from 11.1 million in 2009.
2) After increasing steadily since 1990, the unauthorized immigrant population peaked at 12 million in 2007 before declining to 11.1 million in 2009, representing the first significant reversal in the pattern of growth over the previous two decades.
3) The number stabilized in 2010 following the two-year decline, halting the reversal for now. Mexicans remain the largest group of unauthorized immigrants, accounting for 58% of the total population.
El documento habla sobre la promoción y publicidad. Define la promoción como el proceso de transmitir información sobre productos o una organización al mercado. Explica que la promoción incluye herramientas como la promoción de ventas, relaciones públicas, ventas personales y marketing directo. También describe los diferentes tipos de promoción de ventas y fuerza de ventas, así como conceptos como marketing directo y publicidad.
EPOP: Quantifying Violent Risk for Every Point on the PlanetEsri
EPOP is a risk evaluation tool that delivers precise political violence risk assessments for any location on Earth. It combines multiple data sources into a single model to produce risk scores from 0-10 for war, terrorism, civil unrest, and combined political violence. GIS software is used to automate the model, which calculates risk for over 2 billion points on the planet. Companies use EPOP to assess security risks at locations and along routes for applications like corporate security, insurance, and business development.
This document provides a fact sheet summarizing demographic and spending data available for various countries from Esri. For each country listed, it describes the geographic levels for which data is available, the demographic and spending categories covered, data sources and years, and Esri products in which the data can be accessed. Michael Bauer Research is identified as the source for most of the country data from 2011.
ArcGIS for Server allows sharing of GIS resources as web services across organizations. It includes three editions - Basic, Standard, and Advanced - that provide different levels of functionality. It also includes two capacity levels - Workgroup and Enterprise - that determine the maximum storage, connections, and deployment options. The document provides a matrix comparing the editions and levels to help select the appropriate version based on required functionality and capacity needs.
Salsa music developed in New York City in the early 1970s from genres like boogaloo and pachanga created by Puerto Rican and Latino communities in Manhattan. It blended elements of jazz, soul, rock and roll with Afro-Cuban rhythms and Latin folklore. Some seminal salsa artists included Celia Cruz, a Cuban singer known for son montuno, guaracha and salsa, Hector Lavoe, a Puerto Rican salsa singer popular in the 1970s-80s, and Ismael Rivera, a Puerto Rican singer known as the "Sonero Mayor" who found success with Fania All Stars.
The document provides demographic, economic, and labor market data for Jackson County, Indiana from various sources. It shows that from 2000-2013 the population grew 5% to over 43,000 people, driven by natural increase and international migration. The number of establishments increased 33% during this period, with most growth coming from new businesses. Manufacturing is the top industry, employing 24.9% of the workforce. Educational attainment has improved but still lags the state average, with only 14% of adults having a bachelor's degree or higher.
The document provides demographic, economic, and labor market data for Jackson County, Indiana from various sources. It shows that from 2000-2013 the population grew 5% to over 43,000 people, driven by natural increase and international migration. The number of establishments increased 33% during this period, with most growth coming from new businesses. Manufacturing is the top industry, employing over 6,000, though transportation and warehousing jobs declined 33%. Educational attainment improved but still lags the state average.
The document provides data about Boone County including demographics, economic, and labor market information. Some key points:
- The population of Boone County increased 31% between 2000-2013 primarily due to domestic in-migration. Domestic migration accounted for nearly 11,000 new residents over this period.
- Educational attainment among adults 25+ improved significantly from 2000-2013, with the percentage of adults with a bachelor's degree or higher increasing from 28% to 41%.
- The number of establishments in Boone County nearly doubled from 2000-2011, growing from 2,738 to 5,170. Most of this growth was due to the creation of new establishments rather than the relocation of existing ones
Ten-X Mid-Year US Economic and CRE Market UpdateTen-X
The document provides an economic outlook and overview of capital markets and real estate segments from Ten-X Research. Key points:
1) Uncertainty in the US and globally has eased in recent months after spiking following the 2016 election. The current economic expansion is approaching the second longest in US history.
2) The labor market remains strong but wage growth is slowing. Housing sales fell in Q2 2017 due to tight inventory while prices rose. Consumer spending is rising supported by confidence.
3) US commercial real estate deal volume recovered in Q2 after declining in Q1. Pricing trends have weakened for four straight months. Capitalization rates rose again in Q2 for most property types.
4
The United States Census Bureau reports that about one in nine people moved homes between 2013 and 2014. In recent years, the rate of moving has maintained a steady percentage, settling between 11.5 and 12.5% as of the 2014 statistics.
AMERICA’S RENTAL HOUSING EVOLVING MARKETS AND NEEDS Joint Center for Housing ...JerryLewless
Rental housing has always provided
a broad choice of homes for people at
all phases of life. The recent economic
turmoil underscored the many advantages
of renting and raised the barriers to
homeownership, sparking a surge in
demand that has buoyed rental markets
across the country. But significant erosion
in renter incomes over the past decade has
pushed the number of households paying
excessive shares of income for housing to
record levels. Assistance efforts have
failed to keep pace with this escalating
need, undermining the nation’s longstanding
goal of ensuring decent and affordable
housing for all.
August 4, 2011 TAX FLIGHT IS A MYTH Higher State .docxtarifarmarie
August 4, 2011
TAX FLIGHT IS A MYTH
Higher State Taxes Bring More Revenue, Not More Migration
By Robert Tannenwald, Jon Shure, and Nicholas Johnson1
Executive Summary
Attacks on sorely-needed increases in state tax revenues often include the unproven claim that tax
hikes will drive large numbers of households — particularly the most affluent — to other states.
The same claim also is used to justify new tax cuts. Compelling evidence shows that this claim is
false. The effects of tax increases on migration are, at most, small — so small that states that raise
income taxes on the most affluent households can be assured of a substantial net gain in revenue.
The basic facts, as this report explains, are as follows:
Migration is not common. Most people have strong ties to their current state, such as job,
home, family, friends, and community. On average, just 1.7 percent of U.S. residents moved
from one state to another per year between 2001 and 2010, and only about 30 percent of those
born in the United States change their state of residence over the course of their entire lifetime.
And when people do relocate, a large body of scholarly evidence shows that they do so
primarily for new jobs, cheaper housing, or a better climate. A person’s age, education, marital
status, and a host of other factors also affect decisions about moving.
The migration that’s occurring is much more likely to be driven by cheaper housing
than by lower taxes. A family might be able to cut its taxes by a few percentage points by
moving from one state to another, but housing costs are far more variable. The difference
between housing costs in two different states is often many times greater than the difference in
taxes. So what might look like migration in search of lower taxes is really often migration for
cheaper housing.
Consider Florida, often claimed as a state that attracts households because of its low taxes
(Florida has no income tax). In the latter half of the 2000s, the previously rapid influx of U.S.
migrants into Florida slowed and then reversed — Florida actually started losing population.
The state enacted no tax policy change that can explain this reversal. What did change was
1 Dylan Grundman, Anna Kawar, Eleni Orphinades, and Ashali Singham contributed to this report.
820 First Street NE, Suite 510
Washington, DC 20002
Tel: 202-408-1080
Fax: 202-408-1056
[email protected]
www.cbpp.org
2
housing prices. Previously, the state’s lower housing prices had enabled Northeastern
homeowners to increase their personal wealth by selling their pricey houses and purchasing a
comparable or better home in Florida at a lower price. But housing prices in Florida rose
sharply during the mid-2000s, narrowing opportunities for Northeasterners to “trade up” on
their expensive homes. And consider California: its loss of househ.
The document provides demographic, economic, and labor market data and analysis for Clinton County. Between 2000-2013, Clinton County's population declined slightly due to domestic out-migration outweighing natural growth and international immigration. The number of establishments in the county grew 36% from 2000-2011 primarily through new business formation. The largest industries are manufacturing, government, and health care, though transportation and warehousing saw the largest employment growth between 2002-2013.
The document provides data about Clinton County, Indiana from 2000-2013/2020. It covers topics such as demography, economy, and labor market. Some key findings are:
- The county's population declined slightly between 2000-2013 due to domestic migration out of the county outpacing international migration and natural growth.
- The population is aging as the proportion of residents over 50 increased while the proportion of working-age residents declined.
- The Hispanic population doubled between 2000-2013, increasing their share of the county's population.
- Educational attainment rose but nearly half of adults still only have a high school degree.
- The number of business establishments grew 36% from 2000-2011, primarily through new
The document discusses two key topics:
1) The housing market recovery is expected to continue through 2014, with existing home sales, new home sales, and housing starts all increasing in the coming years. Home prices are also forecasted to rise steadily.
2) However, the looming "fiscal cliff" poses a major risk to the economic recovery. If Congress fails to address large automatic spending cuts and tax increases, it could trigger a recession. The housing market outlook is dependent on resolving this issue and avoiding further limitations on mortgage credit availability.
- Cochise County's population grew by 0.6% in 2009 to 140,263, a slower rate than the previous year, likely due to the economic downturn. Benson saw the fastest growth at 2.6% while Douglas' population declined by 2.5%.
- Sierra Vista's population grew by 1.5%, the second highest in the county. Its growth rate of 23.4% from 2000-2009 was the highest in the county if Douglas' prison annexation is excluded.
- The economic downturn has slowed population growth in Cochise County and Arizona as struggling housing and tight job markets deter relocation. Growth is expected to pick up again as the economy recovers.
State of Homelessness in America, January 2011, authored by M William Sermons and Peter Witte of the National Alliance to End Homelessness. Download at endhomelessness.org
Generations X and Y face greater financial challenges than previous generations in achieving common goals like home ownership, funding education, and saving for retirement. The costs of housing, education, and healthcare have risen much faster than incomes. These generations also have fewer traditional retirement benefits like pensions. As a result, generations X and Y will likely need to save more and work longer to attain their financial goals. Financial planning is important for navigating these complex challenges and competing priorities.
The document provides demographic, economic, and labor market data for Perry County. It shows that while the total population increased slightly from 2000 to 2013, domestic out-migration exceeded in-migration. The population is aging and becoming more educated. The number of establishments and jobs in the county grew significantly from 2000 to 2011, led by natural business formation. Manufacturing is the top employer but lost jobs since 2002, while accommodation and food services gained jobs.
The document summarizes key findings from the 2010 US Census regarding population changes in rural Minnesota. It finds that while the overall state population grew by 7.8%, many rural areas experienced population losses. The aging of the Baby Boomer generation is also impacting demographics. The transition to the American Community Survey makes rural data less precise due to smaller sample sizes.
The document discusses trends in homelessness in the United States from 1980-2020. It notes that after declines from 2005-2008, the overall homeless population and subgroups such as families and chronically homeless individuals increased from 2008-2009. The chronically homeless population remained stagnant despite an increase in permanent supportive housing units. The document also provides statistics on homelessness in Texas, including decreases in the total homeless population but increases in family homelessness. It discusses the economic drivers of homelessness and calls for prevention strategies to reduce homelessness.
Among the fifteen most populous metro areas, metro Atlanta ranks fourth in overall homeownership rates. Homeownership rates vary greatly across the metro Atlanta region and are highest for Asian residents but lowest for Black and Hispanic residents. Cobb and Gwinnett Counties have the largest differences in homeownership rates between White and Black residents, while Fayette County has a much smaller gap. Mortgage data shows White homebuyers purchasing homes in majority Black areas of DeKalb County and central Fulton County.
The document provides demographic, economic, and labor market data about Tippecanoe County, Indiana from 2000-2013. Some key findings include:
- The county's population increased 21% from 2000-2013, largely due to natural increase and international migration.
- Educational attainment among adults 25+ improved, with 43% now having at least a college degree.
- The number of business establishments grew 78% from 2000-2011, primarily through new business formation rather than relocation.
- Most establishments are small, with 58% having 2-9 employees in 2011.
The document provides demographic, economic, and labor market data for Rush County, Indiana from various sources. It summarizes that the county's population decreased 7% from 2000-2013 primarily due to domestic out-migration. The population is aging with declines in prime working age residents. Educational attainment has increased slightly but nearly half of adults only have a high school degree. The economy saw a 35% increase in establishments from 2000-2011 primarily through new business formation. Top employers are in manufacturing and healthcare. Manufacturing jobs declined 39% from 2002-2013 while government is the largest industry.
Commercial real estate market outlook for 2017 from the National Association of RealtorsⓇ
Economic overview
Commercial Real Estate Investments
Commercial Real Estate Fundamentals
Outlook
Similar to Esri Demographic Updates: 2012/2017 (20)
INIA- CISA: Análisis de las amenazas en la fauna silvestreEsri
El documento describe cómo un centro de investigación utilizó herramientas SIG para analizar datos sobre animales silvestres ingresados en un centro de recuperación con el fin de identificar especies, áreas y períodos con mayor riesgo de amenazas y sus relaciones con factores humanos y ambientales. Esto permitió enfocar medidas correctivas de manera más eficiente para conservar la fauna silvestre y prevenir amenazas. En particular, se analizó el riesgo de colisión de rapaces nocturnas con vehículos, identificando las zonas de mayor
Aena Aeropuerto Adolfo Suárez-Barajas crea potentes aplicaciones para sus cli...Esri
Aena Aeropuerto Adolfo Suárez-Barajas creó aplicaciones personalizadas para sus clientes internos utilizando ArcGIS, aprovechando su experiencia previa. Estas nuevas aplicaciones son fáciles de usar y gestionar, y permiten responder más rápidamente a las necesidades de los usuarios. Ahora los usuarios internos y externos tienen acceso a herramientas de mapeo actualizadas que mejoran la eficiencia de las operaciones en el aeropuerto.
El Ayuntamiento de Móstoles implementó una plataforma Smart City utilizando ArcGIS para mejorar la eficiencia, permitir la participación ciudadana y gestionar los activos municipales en tiempo real. La solución integró toda la información municipal en una sola plataforma e incorporó sensores para supervisar servicios como el alumbrado público. Además, una aplicación permite a los ciudadanos reportar incidencias y el ayuntamiento responder más rápido, ahorrando costos.
ArcGIS Online es una plataforma en la nube que permite crear y compartir mapas, aplicaciones y datos geográficos. Los usuarios pueden publicar y almacenar servicios web en la nube, crear mapas interactivos a partir de datos como hojas de cálculo, y colaborar y compartir contenido con otros mediante grupos privados o públicos.
Portal for ArcGIS is a content management system that provides a framework to easily manage and secure geographic assets within an organization. It extends the reach of GIS to everyone in an organization, enabling better decision making. Portal for ArcGIS can be used to implement web GIS on-premises or in the cloud for organizations with specialized security requirements. It will be included with ArcGIS for Server Standard and Advanced starting at version 10.3.
GIS-Based Web Services Provide Rapid Analysis and Dissemination of Maritime DataEsri
The Royal Australian Navy's Hydrography, Meteorology and Oceanography Branch is responsible for collecting, managing, analyzing, and disseminating meteorological and oceanographic data to enable defense users to properly consider environmental impacts. This data comes in large volumes and various formats. Using ArcGIS for Server and custom scripts, the branch can serve this data as OGC web services, including nautical charts and bathymetry as WMS and netCDF weather data as WMS and WCS. This allows for rapid analysis and dissemination of data to gain knowledge of the battlespace and environment.
An Effective Tool for Drinking Water ProtectionEsri
The document discusses ICWater, a tool developed by Leidos to predict the spread and impact of hazardous material releases in river systems. ICWater forecasts (1) where contaminants will travel, (2) if they will reach drinking water intakes, (3) when they will arrive, and (4) if concentrations will threaten human health. It interfaces with USGS stream gauges and databases on infrastructure to provide timely information to decision makers. ICWater successfully modeled the 2014 Elk River chemical spill in West Virginia to advise authorities and protect drinking water.
GeoCollector for ArcPad is a mobile GIS solution that combines Esri's ArcPad software with Trimble GPS hardware to improve the accuracy of collected location data. It provides field workers with a rugged tablet equipped with an integrated GPS receiver and ArcPad software for mapping and data collection. This solution allows organizations to make timely decisions based on reliable location information gathered by field staff.
GeoCollector for ArcGIS for Windows Mobile is a mobile GIS solution that combines Esri's GIS software with Trimble's GPS hardware to improve the accuracy of collected data. It allows field workers to visualize maps, collect geo-located data, and integrate accurate location information into organizational decision making. The solution includes a Trimble Geo 7X handheld device with integrated GPS receiver and ArcGIS for Windows Mobile software for mobile field mapping and data collection with minimal training.
Data Appliance for ArcGIS is an enterprise solution that provides high performance and secure access to terabytes of preloaded geospatial data stored on a network-attached storage device. It includes global basemaps that allow users to immediately build mapping applications. Organizations can publish maps and build apps to share securely behind their firewall. A server bundle is also available for organizations that do not have ArcGIS for Server.
This document describes new premium imagery services from Esri and BlackBridge that provide continuously updated 5-band, 5-meter imagery for use in ArcGIS. The services include a Living Image Basemap service sourced from BlackBridge's RapidEye constellation, regional Mosaics services with virtually cloud-free hand-picked images, and a Living Image Multispectral service providing temporal multispectral imagery through online services.
GeoPlanner for ArcGIS is a web-based app that helps users create, assess, and share planning designs using the geographic knowledge and tools of the ArcGIS platform. It allows users to bring in their own planning data, sketch design plans, compare alternative designs using dashboards, and enable collaboration throughout the planning process. GeoPlanner incorporates each aspect of a geodesign workflow into a single app so that designers, evaluators, and the public can assess the impacts of various scenarios. The app runs on both desktop and mobile devices with touch-enabled tools, supporting planning and design access from anywhere.
This document summarizes an Esri and AccuWeather partnership that provides weather data and warnings through ArcGIS Online. It allows key personnel to access real-time weather reports and warnings to communicate updates. The partnership protects people, property, and assets from severe weather threats with AccuWeather warnings developed by meteorologists. ArcGIS tools can analyze weather data to understand weather impacts and help determine emergency procedures. AccuWeather aims to provide the earliest warnings to enact procedures and save lives.
Esri and Airbus Defense & Space provide imagery products and services including thematic imagery layers with region-specific basemaps and fresh 50cm resolution orthorectified imagery. Their site monitoring service analyzes changes at targeted sites on a daily, weekly or monthly basis and delivers a detailed change detection report as an ArcGIS image service and Story Map app. Their satellite tasking and archive app allows users to task Airbus Defense & Space satellites to acquire new imagery over areas of interest or order images from the archive, with images delivered as an ArcGIS image service.
This document provides a summary of various US demographic and business data sources available from Esri, including descriptions, frequencies of updates, and data vintages. It describes datasets covering topics such as population, households, income, businesses, retail sales, crime, banking and demographics. The data comes from sources including the US Census Bureau, Bureau of Labor Statistics, Dun & Bradstreet and other public and private organizations. Most datasets are updated annually, with some updated decennially, quarterly or semiannually.
ArcGIS for Server on Microsoft Azure JumpstartEsri
This document discusses ArcGIS for Server on Microsoft Azure and the ArcGIS for Server on Microsoft Azure Jumpstart offering from Esri. It provides an overview of deploying ArcGIS for Server in the Microsoft Azure cloud, including advantages such as lower hardware costs, automatic scaling, and leveraging the Azure management portal. It then describes the Jumpstart as providing on-site support and training to help customers get started with ArcGIS Server on Azure, including orientation, VM setup, data loading, service creation, and custom VM configuration. It notes that Esri Professional Services can determine if the Jumpstart is a good fit or provide custom services if additional needs exist. The Jumpstart can be purchased through Esri Professional Services or a customer's
ArcGIS provides tools and capabilities to enable naval units to operate self-sufficiently in remote locations with limited bandwidth. It allows warfighters to access and analyze geospatial data through familiar applications like dashboards and Microsoft Office. The ArcGIS platform delivers low-cost and interoperable solutions to support maritime operations and command and control decisions. It helps transform raw data into actionable intelligence through geoanalytics and visualization.
Esri Geoportal Server is an open source product that enables discovery and use of geospatial resources like datasets, rasters, and web services. It helps organizations manage and publish metadata for their geospatial resources so users can discover and connect to those resources. Key features include supporting international standards, cataloging GIS resources regardless of location or type, and facilitating discovery through a customizable geoportal web interface.
GeoEvent Extension for Server allows users to connect streaming sensor data to GIS applications in real time to monitor assets and alert personnel of specified conditions. It can process and filter multiple data streams using user-defined rules, and includes connectors for common sensors. Key benefits include incorporating real-time data into existing GIS systems to show updated information and detect important spatial or attribute events. The software can be integrated with various monitoring applications and deployed on-premises or in the cloud.
MySQL InnoDB Storage Engine: Deep Dive - MydbopsMydbops
This presentation, titled "MySQL - InnoDB" and delivered by Mayank Prasad at the Mydbops Open Source Database Meetup 16 on June 8th, 2024, covers dynamic configuration of REDO logs and instant ADD/DROP columns in InnoDB.
This presentation dives deep into the world of InnoDB, exploring two ground-breaking features introduced in MySQL 8.0:
• Dynamic Configuration of REDO Logs: Enhance your database's performance and flexibility with on-the-fly adjustments to REDO log capacity. Unleash the power of the snake metaphor to visualize how InnoDB manages REDO log files.
• Instant ADD/DROP Columns: Say goodbye to costly table rebuilds! This presentation unveils how InnoDB now enables seamless addition and removal of columns without compromising data integrity or incurring downtime.
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• Grasp the concept of REDO logs and their significance in InnoDB's transaction management.
• Discover the advantages of dynamic REDO log configuration and how to leverage it for optimal performance.
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• Gain valuable insights into the row versioning mechanism that empowers instant column modifications.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
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What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
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What can you expect when migrating from MongoDB to ScyllaDB? This session provides a jumpstart based on what we’ve learned from working with your peers across hundreds of use cases. Discover how ScyllaDB’s architecture, capabilities, and performance compares to MongoDB’s. Then, hear about your MongoDB to ScyllaDB migration options and practical strategies for success, including our top do’s and don’ts.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
Lee Barnes - Path to Becoming an Effective Test Automation Engineer.pdfleebarnesutopia
So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
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It also can also help to reduce failure recovery and rebalancing downtimes, with demos showing sporty 100ms rebalancing downtimes for your stateful Kafka Streams application, no matter the size of the application’s state.
As a bonus accessing Cassandra State Stores via 'Interactive Queries' (e.g. exposing via REST API) is simple and efficient since there's no need for an RPC layer proxying and fanning out requests to all instances of your streams application.
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👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program: https://bit.ly/Africa_Automation_Student_Developers
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The best thing about databases is that they always work as intended, and never suffer any downtime. You'll never see a system go offline because of a database outage. In this talk, Bo Ingram -- staff engineer at Discord and author of ScyllaDB in Action --- dives into an outage with one of their ScyllaDB clusters, showing how a stressed ScyllaDB cluster looks and behaves during an incident. You'll learn about how to diagnose issues in your clusters, see how external failure modes manifest in ScyllaDB, and how you can avoid making a fault too big to tolerate.
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
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In migrating a massive, business-critical database, the Chief Technology Officer's (CTO) perspective is crucial. This endeavor requires meticulous planning, risk assessment, and a structured approach to ensure minimal disruption and maximum data integrity during the transition. The CTO's role involves overseeing technical strategies, evaluating the impact on operations, ensuring data security, and coordinating with relevant teams to execute a seamless migration while mitigating potential risks. The focus is on maintaining continuity, optimising performance, and safeguarding the business's essential data throughout the migration process
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Esri Demographic Updates:
2012/2017
An Esri White Paper
Contents Page
Introduction........................................................................................... 1
Change .................................................................................................. 1
Sample Data, Then and Now ................................................................ 3
2012/2017 Demographic Updates......................................................... 5
Summary Totals.............................................................................. 5
Population and Household Characteristics ..................................... 7
Housing........................................................................................... 8
Labor Force..................................................................................... 9
Income............................................................................................. 10
2012 Geography.................................................................................... 12
Use of Projections................................................................................. 12
Esri Data Development Team............................................................... 13
4.
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2012/2017
Introduction Two years after the decennial census have not clarified the progress of
postrecession recovery for neighborhoods across the country. There are
two good reasons for the lack of measurable progress over the past two
years: First, the sheer magnitude of the Great Recession abnegated any
hope for a quick recovery. Second, it takes many data sources two to
three years to recalibrate current databases to a new population base and a
new geographic base. Although the Great Recession officially lasted from
late 2007 through mid-2009, signs of recovery at the national level
postdate the 2010 Census. At the local level, the data is slower in coming.
However, there are nascent signs of growth and recovery included in Esri's
2012/2017 demographic updates.
Change Measures of change for the previous decade averaged the highs (2001–2006) that the
housing boom incited with the lows (2006–2010) that heralded the Great Recession.
Change from 2000 through 2010 appears more moderate than expected from these
catalytic events. The US population increased by 9.3 percent in 10 years. Households
increased by 9.9 percent. Housing units increased by 14 percent. Vacant housing units
grew more rapidly, by 44 percent, from 2000 to 2010. The increase in households
exceeds population growth due to the overall decline in the population per household.
Higher growth in the housing inventory relative to household demand effected the
increase in the inventory of vacant housing units. Some of the new housing units were
built as second homes or seasonal units, which are enumerated as vacant housing. But
occasional homes represent only 23 percent of the increase in vacancies.
Putting some numbers to these 2000–2010 trends shows the following:
■ Population grew by 2.7 million annually.
■ Households grew by 1.1 million annually.
■ Housing units grew by almost 2 million annually at the peak of the housing boom.
■ Vacant housing units grew by more than 456,000 annually.
Since 2010, housing growth has been sluggish—less than 900,000 units annually. Many
markets are still coping with an excess of vacant, for sale, and foreclosed properties left
over from the collapse of the housing market and the Great Recession. Recovery is taking
place at different rates across the nation. In many areas, no new housing units are being
built; however, in other areas, new construction is back in full swing, and demand is high.
The top 10 metropolitan statistical areas (MSAs) for housing growth since 2010 include
7 areas that are new to the top 10 list. These areas are growing for diverse reasons:
Jacksonville, NC; Killeen-Temple-Fort Hood, TX; and Manhattan, KS for the military
presence and Morgantown, WV; Auburn-Opelika, AL; Logan, UT-ID; and Manhattan as
large college towns with good climates and growing economies. Kennewick-Pasco-
Richland, WA is a retirement hot spot—especially for Californians. Rounding out the top
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November 2012 2
10 list are 3 MSAs that are continuing to grow: Austin, TX; Raleigh-Cary, NC; and
Myrtle Beach, SC.
Housing growth is generally keeping pace with population change in the fastest-growing
areas, although there are a couple of exceptions. Fairbanks, AK and Hinesville-Fort
Stewart, GA are among the 10 top metro areas for population growth only. Housing
change is lagging a bit in these areas. Each of these MSAs also benefits from military
presence.
What is driving the population and housing growth among these areas? Metropolitan
areas have been impacted differently by the anemic economic recovery. Among the top
10 metros for population or housing growth, civilian unemployment averages 8.5 percent:
better than the average for all metropolitan areas—9.6 percent—but not stellar. The
average masks a range of unemployment rates, from a low of 6.4 percent to a high of
16 percent—as diverse as the locales on the top 10 lists. What these local economies
appear to have in common is the benefit of exogenous revenue sources from seasonal
populations (including college students), military bases, or retirees. Their spending
contributes to local economies without competing with the local labor force.
Conversely, a review of the 10 MSAs with the lowest unemployment rates does not
reveal distinctive population or housing growth. The average annual rate of population
growth for these metros was 1.3 percent from 2010 to 2012, up from 1.2 percent for
2000–2010. Housing growth declined from an annual average of 1.5 percent in the past
decade to 1.1 percent since 2010. Demographic change is moderate for most of the areas
with the lowest unemployment rates. These metros are economically and geographically
diverse, with smaller population bases of less than 250,000 in 2012. The list covers every
region—ranging from Midland, TX and Odessa, TX, which benefit from the oil in the
Permian Basin, to Barnstable Town, MA, another beneficiary of tourism—but features
smaller metropolitan areas in the Midwest and mountain states of the West. Although
these areas were affected by the Great Recession, they were less impacted by the
boom/bust of the housing market and quicker to recover after the recession.
The same variability in recovery affects county trends since 2010. Counties experiencing
the most rapid growth in housing inventories—at least 2.5 percent annually—were also
growing rapidly in the previous decade. However, their current growth rates are much
lower, and they do not have the lowest unemployment rates in 2012. Compared to the
previous decade, housing growth rates have improved for one in four counties. The
fastest-growing areas, with oil/natural gas booms, offer high paying jobs—and housing
shortages. Workers flock to areas like the Bakken shale in North Dakota but quickly
deplete the available housing stock. Housing construction for new workers cannot keep
pace with the influx.
Almost one in four counties shows no growth or a loss of housing from Census 2010 to
2012. There were also some significant housing losses due to natural disasters in the past
year. Over 1,500 housing units were destroyed in the Bastrop County wildfire in Texas in
September 2011. Housing loss from the Indiana tornadoes in March was also factored
into the 2012 updates. Rebuilding the housing lost to the destructive May 2011 tornado
season is reflected in the Joplin, MO MSA.
Population change reflects the boom/bust in housing. Since 2010, the number of counties
losing population has dropped dramatically. The rate of growth among counties with an
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Esri White Paper 3
increasing population has not improved, but the stabilization of population decline has
increased the average county growth rate to 0.5 percent for 2010–2012.
Growth is evident but not widespread. Where are we in the recovery process? Esri
warned in the summer of 2010 that "uncertainty is the best outlook in the face of weak
job growth, growing debt, and persistent concern over a double-dip recession."1
More
than two years have passed, but this statement remains, regrettably, prescient today. The
economy is still struggling to gain traction:
■ The gross domestic product (GDP) increased by 1.8 percent in 2011. In the first
quarter of 2012, the GDP increased by 2 percent, and in the second quarter by only
1.3 percent (annualized rates). The GDP will increase, but an annual rate of 3 percent
is necessary for a more robust recovery.
■ Jobs lost from the beginning of the recession (December 2007) through 2010 have
not been wholly recovered. About half of the jobs have been replaced. To return to
the level of employment in December 2007, job creation needs to increase to
187,000 per month for the next two years (from a monthly average of 152,000 for the
past 2.5 years). Currently, there are seven applicants for every two jobs.2
■ National debt is growing faster than the economy. The current public debt is almost
73 percent of the GDP.
■ Consumer spending increased by 1.5 percent in the second quarter of 2012, down
from 2.4 percent in the first quarter. Like the GDP, there has been modest growth,
but the outlook must remain conservative while job growth and wage increases are
nominal.
New home sales are showing better gains, but credit remains tight for most home buyers.
Uncertainty pervades the economy. Banks and corporations are sitting on their cash.
Consumers are paying down their debt. Until banks and corporations stop sitting on their
assets and start spending, the pace of economic recovery is unlikely to improve.
Sample Data, Then
and Now
Gauging economic change in small areas is more challenging in this decade. Census 2010
was a game changer in the development of small area data because it collected no sample
data—variables like income, education, employment, and home value. The American
Community Survey (ACS) is the replacement for sample data, although differences from
the census version are significant. Single-year ACS data is reported only for areas with a
population of 65,000 or more. Data for all levels of geography, down to block groups, is
available only as a 5-year average.
Unlike census sample data, the American Community Survey represents a series of
monthly sample surveys that yield different measures of familiar variables. The
differences in measurement include continuous data collection and smaller sample sizes.
Naturally, ACS sample sizes are much smaller than a census survey taken once every
10 years. To represent the smallest sample areas—block groups—data must be collected
1
Esri. Esri Trend Analysis: 2010–2015.
2
Center on Budget and Policy Priorities: Economic Recovery Series.
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over 60 months. One-year ACS data is actually a 12-month average rather than a single
point in time, April 1.
How does this difference affect the annual demographic updates? Change must be
estimated differently now. Esri estimates change from April 1, 2010 (the census base), to
July 1, 2012—point estimates. ACS data are period estimates, which include at least
12 months. The differences are pronounced in areas with a seasonal population. The best
example of seasonal effects is unemployment rates. ACS does not report monthly survey
data, but the Bureau of Labor Statistics (BLS) does—both seasonally adjusted and not.
For the metro unemployment rate in Barnstable Town, MA, the 2010 monthly estimates
reveal the impact of seasonal population flows and the effects on period estimates (annual
averages) versus point estimates (monthly):
■ Unemployment rates were highest in January 2010, at 12.0 percent, and lowest in
August, at 6.7 percent.
■ The estimate for April (same time as the census) was 9.1 percent.
■ BLS's annual average was estimated at 8.8 percent, unadjusted, and 8.3 percent,
seasonally adjusted.
■ ACS's annual estimate for 2010 was 9.8 percent.
The time frame clearly impacts the size of the estimate in areas with seasonal
populations. Twelve-month averages smooth the highs and lows; 60-month averages for
small areas smooth out all trend lines. There are also methodological differences between
ACS and BLS in unemployment estimation. ACS's unemployment estimates tend to be
higher.3
Reconciling differences in source data is another challenge of applying ACS data to point
estimation. Unfortunately, the ACS base is also affected by sample size. In fact, some
estimates are simply not reported due to small sample sizes or missing responses. There
are gaps in the ACS data. For example, civilian employment is reported for block groups,
but labor force participation (including unemployment) is not.
Now there is an ACS base, albeit with some holes, but no comparable measures of
change. Does this represent the future of data updates? Yes and no. ACS retains the
appearance of past sample data but represents the changing future of data collection.
Although there will be annual releases of ACS data, only five-year data will be reported
for small areas. And there will still be missing data. ACS cannot be the sole measure of
the population for the next decade any more than a single decennial survey could. There
will always be a need for alternative data sources to measure the facets of change—
demographic and economic.
The good news is the proliferation of data sources, from administrative records to private
data sources. Government agencies continue to provide their data in convenient, digital
time series, while the private sector has been pioneering the indirect collection of data
from a host of sources, including Internet use and social media. Esri has been using a
3
See more information on differences between ACS and BLS estimates.
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Esri White Paper 5
variety of data sources for years to update small areas like block groups, beginning with
the latest census base, then adding a mixture of administrative records, like delivery
counts from the US Postal Service, and various private sources, like a comprehensive
address file, to capture change to the census base.
This approach has been effective in past updates, but it requires a solid census base and a
variety of sources and statistical models to capture change. Demographic updates must
incorporate both traditional and new data sources to remain current. The challenge now is
to retool forecast models to integrate changing traditional sources and exploit new data
sources.
2012/2017
Demographic
Updates
Esri's 2012/2017 demographic updates continue the new era in data development,
retaining the best from the past while adapting to changes in source data. Esri has
incorporated Census 2010 counts and geography and evaluated and revised its models.
The demographic updates are still point estimates, representing July 1 of the current and
forecast years. Esri presents the 2012/2017 demographic forecasts, including population;
age by sex; race by Hispanic origin; age by sex by race and by Hispanic origin;
households and families; housing by occupancy; tenure and home value; labor force and
employment by industry and occupation; and income—including household income
distributions, household income by age of householder, and per capita income. Updates
of household income are also extended to provide after-tax (disposable) income and a
measure of household wealth, net worth.
Forecasts are prepared initially for counties and block groups. From the county database,
forecasts are aggregated to Core Based Statistical Areas (CBSAs), states, or higher levels.
From the block group database, forecasts can be retrieved for census tracts; places;
county subdivisions; ZIP codes; congressional districts (currently, the 112th Congress);
Designated Market Areas (DMAs); or any user-defined site, circle, or polygon.
Summary Totals The change in total population is a function of changes in household population and the
population in group quarters, which are subject to different trends. The addition of a
prison, for example, produces a sudden increase in the group quarters population that is
unlikely to yield an attendant change in the household population or the projected
population growth of a county. The group quarters population is the Census 2010 count
of group quarters, with updates culled from a variety of federal, state, and local sources.
Forecasting change in the size and distribution of the household population begins at the
county level with several sources of data. Esri begins with county estimates from the US
Census Bureau. Because testing has revealed improvement in accuracy by using a variety
of different sources to track county population trends, Esri also employs a time series of
county-to-county migration data from the Internal Revenue Service, building permits and
housing starts, plus residential postal delivery counts. Finally, local data sources that
tested well against Census 2010 are reviewed. The result balances the measures of growth
from a variety of different data series.
Measuring the change in population or households at the county level is facilitated by the
array of data reported for counties. Unfortunately, there is no current data reported
specifically for block groups. Past trends can be calculated from previous census counts,
but nothing that is current. To measure current population change by block group, Esri
models the change in households from three primary sources—Experian, the US Postal
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Service (USPS), and Hanley Wood Market Intelligence—in addition to several ancillary
sources.
The USPS publishes monthly counts of residential deliveries for every US postal carrier
route. This represents the most comprehensive and current information available for
small, subcounty geographic areas. The USPS establishes carrier routes to enable
efficient mail delivery. Carrier routes are a fluid geographic construct that is redefined
continuously to incorporate real changes in the housing inventory and occupancy plus
administrative changes in staffing and budgets of local post offices. These frequent
changes in carrier routes are not the only difficulty.
Converting delivery statistics from postal carrier routes to census block groups is a
complex challenge. Carrier routes are defined to deliver the mail, while block groups are
constructed to collect and report census data. Comparing two different areas that are
defined for wholly different purposes provides one significant conversion issue. Carrier
routes commonly overlap multiple block groups. In many cases, a carrier route
encompasses disjointed areas that can be distant from each other, but block groups are
rarely divided into multiple polygons. These overlaps require an effective method of
allocating the postal delivery counts across multiple block groups.
Esri has developed a technique to link a carrier route to the correct block group(s) using
the actual locations of mail deliveries. Its proprietary Address Based Allocation (ABA)
was developed in 2005 to solve the complex challenge of converting delivery counts
from carrier routes to block groups. This allocation method uses household addresses that
are geocoded with carrier route and block group codes to serve as the foundation for the
conversion. The approach is unbounded by geographic borders or arbitrary assumptions
about the distribution of households or postal deliveries. ABA results have been tested
extensively against Census 2010 counts, including an independent evaluation that
encompassed data from four other vendors. This test confirmed the accuracy of Esri's
ABA method.4
To track new housing developments, especially in previously unpopulated areas, Esri
licensed a new data source in 2006, from Hanley Wood Market Intelligence—new and
planned residential construction in the top US housing markets. This database identifies
individual construction projects by location. The construction information includes the
following:
■ Total number of units planned
■ Inventory of units under construction, sold, and/or closed
■ Type of housing—detached homes, townhomes, condominiums, and so forth
■ Target markets—families, seniors, empty nesters, and so forth
Tracking residential development since 2010 with Esri's enhanced demographic and
spatial analysis tools also provides better information for the five-year forecasts than past
trends.
4
Vendor Accuracy Study: 2010 Estimates versus Census 2010.
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A revised housing unit methodology applies the change in households estimated from
address counts, delivery counts, and new housing construction to update household
population by block group. The best techniques are derived from a combination of
models and data sources. Discrepant trends are checked extensively against independent
sources. Finally, totals for block groups are controlled to the county totals. Despite the
appeal of microforecasting, there is simply more information available to track
population change by county than by household. Ignoring the advantage of county-level
data is throwing away information.
The integration of demographic and spatial analysis has not only enabled the
development of more accurate block group totals but also provided the opportunity to
update block totals. Blocks are the lowest common denominator in the geographic
hierarchy that progresses to block groups, tracts, counties, and states. Blocks are most
useful in the estimation of data for polygons, which can be any area outside the
geographic hierarchy, from places to ZIP codes to user-defined polygons (including
circles and drive-time polygons). For most areas, the application provides a good estimate
for the polygon. If the relationship between the blocks and the block group has changed
significantly since 2010, the estimate cannot incorporate that change unless both blocks
and block groups are updated.
Population and
Household
Characteristics
Esri's population and household characteristics include the population by sex and age,
race and Hispanic origin, sex by age by race and Hispanic origin, and household type.
Population by sex and age includes estimates by five-year age groups and by single years
from less than 1 year to 84 years.
The population by age and sex is projected via a cohort survival model that calculates the
components of population change separately, by age and sex. Applying survival rates
specific to the cohort carries the 2010 population forward. Changes in the population by
age and sex diverge at the household level. For example, an area that is losing population
can age more rapidly with the loss of population in prime migrant ages, 20–34 years—
unless there is a college nearby. Neighborhoods near colleges sustain high turnover from
student populations but retain their youthful age distributions.
To capture these variations, Esri's model first separates the group quarters population
from the household population and, second, keys the calculations to the size and
characteristics of the population. This stratification identifies several different patterns of
change by age and sex that can be applied in a cohort survival model.
The changing profile of the US population requires measuring population change by race
and Hispanic origin. The American identity is shaped by diversity. Tracking the changing
patterns of race and ethnicity provides a current portrait of our society. Historical trends
in race and ethnicity combined with the most current data sources by race and Hispanic
origin, including population estimates by county and state from the US Census Bureau
and survey data from the ACS, are analyzed to establish county population by race and
Hispanic origin. Forecasts by block group combine local changes in the distributions by
race and projected change for counties. The last step controls block group distributions to
county totals by race and Hispanic origin.
The changing face of our nation is evident in Esri's Diversity Index, which summarizes
racial and ethnic diversity in an area. This measure shows the likelihood that two persons,
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chosen at random from the same area, belong to different races or ethnic groups. The
index ranges from 0 (no diversity) to 100 (complete diversity). Esri's Diversity Index for
the United States has risen from 60.6 in 2010 to 61.4 in 2012, with a forecast of 63.8 in
five years.
Diversity describes the composition of American households, too. Husband-wife families
remain the dominant household type, but their share of all households continues to slip—
from 52 percent in 2000 to 48 percent in 2010. From 2000 to 2010, the real increase in
family households was in single-parent families, up by 22 percent, and multigenerational
households, up by 30 percent. Husband-wife families increased by less than 4 percent in
10 years, and husband-wife families with children declined.
All family households increased by 8 percent during 2000–2010 and nonfamily
households by 16 percent. The fastest-growing nonfamily households, however, are
unmarried partners—opposite-sex partners by 40 percent and same-sex partners by
52 percent from 2000 to 2010. Single-person households retain the highest proportion of
nonfamily households (80 percent), but the increase was less than 15 percent in the past
decade. Nontraditional family types are the growing segments of households.
The attendant change in average household size is nominal from 2000 to 2010—2.59 to
2.58—with no obvious change in 2012. The gradual change in household size has made it
uniquely suitable to forecasting the change in household population from the change in
households. Average household size is traditionally one of the most stable and
predictable components of the forecasts. Household forecasts are predicated on local
patterns of change, which are controlled to the more constant trends for states and
counties.
Few block groups represent a cross section of US households. For example, in areas that
gain population from immigration, the trend in average household size is increase. To
distinguish local variation, Esri's model is keyed to the characteristics of households at
the block group level. This stratification identifies several different patterns of change by
household type that are applied to forecast trends in the characteristics of households—
both family composition and tenure. Local change is emphasized in the 2012/2017
forecasts of households and families for counties and block groups. National and state
trends are monitored with sources such as the Current Population Survey (CPS) and
American Community Survey from the Census Bureau and then applied as controls.
Housing Esri's housing updates include total housing units, occupancy, tenure, and home value.
Total housing unit updates are created from recorded changes in the housing inventory
and estimated changes in occupancy rates since April 2010, applied to Census 2010 base
data. Recorded change in the housing inventory is culled from several data sources,
including multiple construction data inputs from Hanley Wood Market Intelligence, data
for new manufactured homes placed by state from the Census Bureau, and building
permits for permit-issuing places and counties. As of 2010, only half of the counties have
complete coverage with building permits. Numerous independent sources are leveraged
to obtain detailed information on housing development data where no building permits
exist. Independent estimates of change in occupancy are calculated from USPS
residential lists, the ACS, and various state and local data. Additionally, data from the
Current Population Survey and the Housing Vacancy Survey from the Census Bureau are
used to model trends in occupancy.
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The data for tenure represents owner- and renter-occupied housing units. Together, the
two components sum to total households, or total occupied housing units. A time series
model based on data from the Housing Vacancy Survey, combined with changes in the
Current Population Survey, the American Community Survey, and intercensal data guide
tenure forecasts. With a blend of top-down and bottom-up techniques, the forecasts take
advantage of the latest information from survey data at higher levels of geography while
employing local characteristics at the lower levels. The data from the lower levels of
geography are controlled to the higher levels to produce the tenure updates. Changes in
owner-versus-renter occupancy are forecast independently and then controlled to the total
households.
Esri tracks change in home value using several different sources, including the House
Price Index (HPI) from the Federal Housing Finance Agency (FHFA) and annual
estimates from ACS. The HPI is designed to monitor changes in average home prices
based on repeat sales or refinancing of the same properties. The index is derived from
mortgage loans purchased or securitized by Fannie Mae or Freddie Mac. FHFA affirms
the "significant advantages" of the HPI over Commerce Department surveys or other data
collections based on snapshots of sales figures. Employing the repeat-sales methodology
renders the index less susceptible to compositional effects, especially with data for
smaller geographic areas. If a higher proportion of lower-end homes are sold in the
current period than in an earlier period, survey data can underestimate home prices.
Local estimates of home value incorporate supply-demand characteristics, the
socioeconomic traits of householders in the area, and trends assessed for larger markets.
This approach to modeling small areas efficiently predicts home value for areas with
small housing bases or missing base data. The 2012 update implements sophisticated
techniques designed to target change in home value accurately and to address the outliers
that are expected in small area modeling.
Labor Force Esri forecasts the civilian labor force (employment and unemployment) and employment
by industry and occupation for 2012.5
The US labor market is emerging from the most
severe contraction since World War II. Since 2010, the economy added nearly three
million jobs, raising the total work force to 142 million. This growth has been
geographically broad, with every region and division adding people to payrolls. Only four
states (Alabama, Arizona, Hawaii, and Rhode Island) registered a net reduction in
workers.
Most of the 20 industrial sectors expanded over the past two years. The annualized rate of
change in employment was highest in Mining (10.3 percent); Arts, Entertainment, and
Recreation (7.2 percent); and Administrative and Support and Waste Management
Services (4.5 percent). Only three sectors contracted: Public Administration
(-5.1 percent), Educational Services (-4.2 percent), and Information (-1.5 percent).
The total number of unemployed shrank from 16.7 million to 14.9 million people.
Accordingly, the US rate of unemployment (the percentage of the unemployed within the
5
It is important to remind data users that Esri's civilian labor force estimates represent seasonally unadjusted
totals as of July 1 to stay consistent with the forecast base. While press releases of labor force statistics
produced by the Bureau of Labor Statistics report seasonally adjusted change each month, removing such
calendar influences, Esri's totals reflect actual estimated levels. As a result, Esri estimates and measures of
change can yield differences when compared to these official government statistics.
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civilian labor force) fell 1.2 percentage points to 9.5 percent. While the US
unemployment rate declined, so too did the US labor force participation rate (civilian
employed plus unemployed as a percentage of the population 16 years and older). This
rate fell by seven-tenths of a percentage point to 63.4 percent. Some of the reduction in
unemployment results from increasing employment; some of the decline is due to
workers leaving the labor force. Focusing on the unemployment rate to ascertain the
health of the labor market is misleading if the labor force base is contracting.
Estimates of the civilian labor force integrate recent change in the supply and demand for
labor from the Local Area Unemployment Statistics (LAUS), Occupational Employment
Statistics (OES), and Current Employment Statistics (CES) programs of BLS, as well as
the American Community Survey and Current Population Survey. Federal statistical
surveys are the principal sources for labor force trends. The LAUS program is the
premier resource for current and local economic conditions.
Last decade, Esri leveraged the Census 2000 sample data on employment status as the
forecast base for all areas from block groups to states. The ACS is the replacement source
for small area sample data; however, employment status is only reported for tracts and
larger areas. Esri is restricted to using tracts as the base geography. The 2012
employment and unemployment estimates are developed from a modified version of the
2006–2010 ACS tract base, using more current one-year totals from the 2010 ACS labor
force profile and current sources.
Esri's updated employment by industry and occupation captures temporal change from
the federal statistical sources: the ACS and CPS from the Census Bureau and the CES
and OES programs from BLS. National and state industry distributions are updated using
trends from the CES. The latest industry-occupation matrix from the OES is applied to
allocate 2010–2012 employment change by industry to the related occupations.
Income Esri's forecast base is the income that was reported in the 2006–2010 ACS. To estimate
income for households, Esri evaluates an extensive list of sources for household income
trends that includes both federal and proprietary sources. The review of national surveys
includes the Bureau of Economic Analysis's local personal income series, the Current
Population Survey, and the Bureau of Labor Statistics' Consumer Price Index. Esri's
updates emphasize the use of time series data from household surveys to establish a base
trend line.
After forecasting the state income distributions, household income is estimated for
counties and then block groups. Esri's income forecasts are uniquely designed to
distinguish local variation, changes in income inequality, and urbanicity as differentiators
of income growth. The model correlates the characteristics of households at the block
group level with changes in income. This stratification identifies several different patterns
of change by household type that are applied to forecast trends in income. Modeling links
the current income change to all households with similar socioeconomic characteristics.
Areas with small household bases or missing base data, where the model is unable to
capture the local variation, are forecast with another level of modeling to capture the
change in income by strata (a group of areas classified by their sociodemographic
characteristics).
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Separate forecasts of the change in income by strata are aggregated to compose the
income distributions. Median income for 2012 and 2017 is calculated from the
distributions using linear or Pareto interpolation. Average income is computed from
aggregate household income.
Household income reported by age of householder is updated to be consistent with the
2012/2017 distributions of household income and age of householder. To update the age
distribution of householders, the ratio of householders by age to the population by age in
2010 is updated to 2012/2017 and applied to the current age distributions. After the
targets are set, the base distributions of household income by age of householder by block
group are fitted to current distributions of households by income and by age of
householder.
Esri uses the definition of money income used by the Census Bureau. For each person
15 years of age or older, money income received in the preceding calendar year is
summed from earnings, unemployment compensation, Social Security, Supplemental
Security Income, public assistance, veterans' payments, survivor benefits, disability
benefits, pension or retirement income, interest, dividends, rent, royalties, estates and
trusts, educational assistance, alimony, child support, financial assistance from outside
the household, and other income.
Data for consumer income collected by the Census Bureau covers money income
received (exclusive of certain money receipts such as capital gains) before payments for
personal income taxes, Social Security, union dues, Medicare deductions, and so on.
Disposable income represents money income after taxes—an estimate of a household's
purchasing power. The proportion of household income left after taxes is estimated from
special studies conducted by the Census Bureau to simulate household taxes. Esri's 2012
disposable income incorporates data from the 2011 Annual Social and Economic (ASEC)
Supplement to the Current Population Survey. Starting with the 2011 ASEC release, the
Census Bureau has introduced a new technique to accommodate disclosure avoidance.
Previously, high dollar values were capped or top-coded; now, rank proximity swapping
is employed. Esri's analysis revealed that these changes have impacted the time series of
tax variables available, which is reflected in this release of disposable income.
Four types of taxes are deducted: federal individual income taxes; state individual income
taxes; Federal Insurance Contributions Act (FICA) contributions, or Social Security, and
federal retirement payroll taxes; and property taxes for owner-occupied housing. Internal
Revenue Service tax rates are used as guidelines for model testing. Esri then applies the
proportions of after-tax earnings to income intervals that are cross-tabulated by age of
householder for each state. State-specific proportions account for the variation in taxes by
state. The proportions, or multipliers, are then applied to the age by income forecasts for
block groups and counties to calculate disposable income.
Current income is only one component of a household's financial security. A
householder's net worth or accumulated wealth reflects the ability to stay afloat during a
financial shock as well as savings for future retirement. Net worth is estimated from
household wealth data collected from the Surveys of Consumer Finance (SCF) from the
Federal Reserve Board from 1992 through 2010. These triennial surveys feature
enhanced representation of wealthy households through the comprehensive measurement
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of net worth components. By definition, net worth equals total household assets less any
debts, secured or unsecured. Assets include ownership of homes, rental properties,
businesses, IRAs and Keogh accounts, pension plans, stocks, mutual funds, and motor
vehicles. Examples of secured debt include home mortgages and vehicle loans; unsecured
debt includes credit card and other bills or certain bank loans.
2012 Geography Changes in the areas for which data is tabulated and reported are critical to the analysis of
trends. Esri reports data for political and statistical areas that include states, counties,
census tracts, block groups, places, county subdivisions, CBSAs, and congressional
districts, plus special use areas like ZIP codes and DMAs. Of course, the provision of
small area data in Esri® software enables users to define their own areas of interest, too.
Data is reported in 2010 geography for the standard political and statistical areas.
Statistical areas, like block groups and census tracts, are defined by the Census Bureau
(with help from local officials) to collect and report data for neighborhoods. These areas
change every 10 years with each new census. Political areas like counties, cities, or
townships are subject to change by local governments. Larger political areas like counties
change less often than places, but boundary revisions were common with Census 2010.
Metropolitan areas are usually revised annually; however, the Office of Management and
Budget revises the definitions decennially with data from the census. The next revision of
metropolitan areas is expected in 2013. The 2012/2017 updates reflect the latest
definitions available, which have remained unchanged since December 2009. CBSAs
include 366 metropolitan and 576 micropolitan areas. Congressional districts still
represent the 112th Congress. The new congressional districts allotted by Census 2010
debut in January 2013.
ZIP codes, which are defined solely by the US Postal Service to expedite mail delivery,
can change monthly or whenever the US Postal Service revises delivery routes. ZIP codes
do not represent standard census geographic areas for data reporting. ZIP code
boundaries are not contiguous with census geographic areas or stable over time. Data
estimated for ZIP codes is also subject to change. Residential ZIP code data is estimated
from block group data using a correspondence created by assigning Census 2010 block
points to ZIP code boundaries from NAVTEQ. The vintage of the ZIP code boundaries is
fourth quarter 2011; the total residential ZIP codes in this release is 31,698.
Use of Projections Projections are necessarily derived from current events and past trends. The past and the
present are known; the future must be extrapolated from this knowledge base. Even
though projections represent the unknown, they are not uninformed. Guidelines for the
development of projections also inform the use of those projections:
■ The recent past provides a reasonable clue to the course of future events, especially if
that information is tempered with a historical perspective.
■ A stable rate of growth is easier to anticipate than rapid growth or decline.
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■ The risk inherent in forecasting is inversely related to the size of an area: the smaller
the area, the greater the risk.
■ The risk increases with the length of the projection interval. Any deviation of the
projected trends from actual events is amplified over time.
Esri revises its forecasts annually to draw on the latest data. However, this data can be
enhanced with personal knowledge of an area to provide the qualitative, anecdotal detail
that is not captured in a national database. It is incumbent on data users and producers to
incorporate as much information as possible when assessing local trends, especially for
areas that are subject to boom-bust cycles.
Esri Data
Development Team
Led by chief demographer Lynn Wombold, the Esri data development team has a 35-year
history of excellence in market intelligence. The combined expertise of the team's
economists, statisticians, demographers, geographers, and analysts totals nearly a century
of data and segmentation development experience. The team has crafted data
methodologies such as the demographic update, segmentation, diversity index, and Retail
MarketPlace that are now industry benchmarks. The accuracy of Esri's methodologies
was proved in a blind, independent study, Vendor Accuracy Study—2010 Estimates
versus Census 2010, in which Esri demographics were deemed to be most accurate.
Vendor Accuracy Study—2010 Estimates versus Census 2010.
18. Printed in USA
Contact Esri
380 New York Street
Redlands, California 92373-8100 usa
1 800 447 9778
t 909 793 2853
f 909 793 5953
info@esri.com
esri.com
Offices worldwide
esri.com/locations
Esri inspires and enables people to positively impact their
future through a deeper, geographic understanding of the
changing world around them.
Governments, industry leaders, academics, and nongovernmental
organizations trust us to connect them with the analytic knowledge
they need to make the critical decisions that shape the planet. For
more than 40 years, Esri has cultivated collaborative relationships
with partners who share our commitment to solving earth’s most
pressing challenges with geographic expertise and rational resolve.
Today, we believe that geography is at the heart of a more resilient
and sustainable future. Creating responsible products and solutions
drives our passion for improving quality of life everywhere.