Regional Snapshot: Metro Atlanta's Hispanic and Latino CommunityARCResearch
This month's Regional Snapshot explores the foreign born population in metro Atlanta, focusing on the largest contributor to our foreign born population growth - the Hispanic and Latino community.
MC_forecasts_finals series 17_feb2024.pdfARCResearch
Final summary slide deck for Series 17 population, employment by sector, age group forecasts for MPO region, counties, and smaller areas...February 2024
Diversity and Cultural Competency in Health Care Je.docxShiraPrater50
Diversity and Cultural
Competency in Health Care
Jean Gordon, RN, DBA
LEARNING OUTCOMES
After completing this chapter, the student should be able to:
☛ Define diversity.
☛ Define cultural competency.
☛ Define diversity management.
☛ Understand why changes in U.S. demographics affect the health care industry.
OVERVIEW
Demographics of the U.S. population have changed dramatically in the
past three decades. These changes directly impact the health care indus-
try in regard to the patients we serve and our workforce. By 2050, the term
“minority” will take on a new meaning. According to the U.S. Census Bureau,
by midcentury the white, non-Hispanic population will comprise less than
50 percent of the nation’s population. As such, the health care industry needs
to change and adopt new ways to meet the diverse needs of our current and
future patients and employees.
The American Heritage Dictionary of the English Language (4th ed.) defines
diversity as: “(1) the fact or quality of being diverse; difference, and (2) a point
in which things differ.” Dreachslin (1998) provided us with a more specific def-
inition of diversity. She defined diversity as “the full range of human similari-
ties and differences in group affiliation including gender, race/ethnicity, social
class, role within an organization, age, religion, sexual orientation, physi-
cal ability, and other group identities” (p. 813). For our discussions, we will
focus on the following diversity characteristics: (1) race/ethnicity, (2) age, and
(3) gender.
This chapter is presented in three parts. First, we discuss the chang-
ing demographics of the nation’s population. Second, we examine how these
changes are affecting the delivery of health services from both the patient’s
and employee’s perspectives. Because diversity challenges faced by the health
care industry are not limited to quality-of-care and access-to-care issues, in
part three of our discussions we explore how these changes will affect the
health services workforce, and more specifically the current and future leader-
ship within the industry.
15
CHAPTER 2
9781284087062_CH02_PASS02.indd 15 17/02/15 6:10 PM
CHANGING UNITED STATES POPULATION
There is no doubt that the demographic profile of the U.S. population has
undergone significant changes within the past 10 years regarding age, gender,
and ethnicity (see Table 2–1 ).
Data from the 2010 Census provide insights to our racially and ethnically
diverse nation (Humes, Jones, & Ramirez, 2011). According to the 2010 Cen-
sus, 308.7 million people resided in the United States on April 1, 2010—an
increase of 27.3 million people, or 9.7 percent, between 2000 and 2010. The
vast majority of the growth in the total population came from increases in
those who reported their race(s) as something other than White alone and
those who reported their ethnicity as Hispanic or Latino. For the first time in ...
Diversity and Cultural Competency in Health Care Je.docxAASTHA76
Diversity and Cultural
Competency in Health Care
Jean Gordon, RN, DBA
LEARNING OUTCOMES
After completing this chapter, the student should be able to:
☛ Define diversity.
☛ Define cultural competency.
☛ Define diversity management.
☛ Understand why changes in U.S. demographics affect the health care industry.
OVERVIEW
Demographics of the U.S. population have changed dramatically in the
past three decades. These changes directly impact the health care indus-
try in regard to the patients we serve and our workforce. By 2050, the term
“minority” will take on a new meaning. According to the U.S. Census Bureau,
by midcentury the white, non-Hispanic population will comprise less than
50 percent of the nation’s population. As such, the health care industry needs
to change and adopt new ways to meet the diverse needs of our current and
future patients and employees.
The American Heritage Dictionary of the English Language (4th ed.) defines
diversity as: “(1) the fact or quality of being diverse; difference, and (2) a point
in which things differ.” Dreachslin (1998) provided us with a more specific def-
inition of diversity. She defined diversity as “the full range of human similari-
ties and differences in group affiliation including gender, race/ethnicity, social
class, role within an organization, age, religion, sexual orientation, physi-
cal ability, and other group identities” (p. 813). For our discussions, we will
focus on the following diversity characteristics: (1) race/ethnicity, (2) age, and
(3) gender.
This chapter is presented in three parts. First, we discuss the chang-
ing demographics of the nation’s population. Second, we examine how these
changes are affecting the delivery of health services from both the patient’s
and employee’s perspectives. Because diversity challenges faced by the health
care industry are not limited to quality-of-care and access-to-care issues, in
part three of our discussions we explore how these changes will affect the
health services workforce, and more specifically the current and future leader-
ship within the industry.
15
CHAPTER 2
9781284087062_CH02_PASS02.indd 15 17/02/15 6:10 PM
CHANGING UNITED STATES POPULATION
There is no doubt that the demographic profile of the U.S. population has
undergone significant changes within the past 10 years regarding age, gender,
and ethnicity (see Table 2–1 ).
Data from the 2010 Census provide insights to our racially and ethnically
diverse nation (Humes, Jones, & Ramirez, 2011). According to the 2010 Cen-
sus, 308.7 million people resided in the United States on April 1, 2010—an
increase of 27.3 million people, or 9.7 percent, between 2000 and 2010. The
vast majority of the growth in the total population came from increases in
those who reported their race(s) as something other than White alone and
those who reported their ethnicity as Hispanic or Latino. For the first time in.
An overview of recent population trends in Illinois, its origins and potential implication. This research was compiled by Northern Illinois University researcher Brian Harger.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
4. 4
Purpose
This document provides information
and data about Clinton County that
can be used to guide local decision-
making activities.
The Data SnapShot showcases a variety
of demographic, economic and labor
market information that local leaders,
community organizations and others can
use to gain a better perspective on
current conditions and opportunities in
their county.
To strengthen the value and usability of
the information, we showcase the data
using a variety of visual tools, such as
charts, graphs and tables. In addition, we
offer key points about the data as a way
of assisting the user with the interpretation
of the information presented.
Finally, short takeaway messages are
offered at the end of each section in order
to highlight some of the more salient
findings.
Introduction
section 01
5. 5
About Clinton County
Introduction
section 01
County Background
Established 1830
County
Seat
Frankfort
Area 405 sq. mi.
Neighboring
Counties
Carroll, IN
Howard, IN
Tipton, IN
Hamilton, IN
Montgomery, IN
Tippecanoe, IN
7. 7
Population change
Components of Population Change, 2000-
2013
Total Change 360*
Natural Increase 2,048
International Migration 1,909
Domestic Migration -3,444
The total population is
projected to decrease
by less than 1 percent
between 2013 and
2020.
Demography
Sources: STATSIndiana, U.S. Census Bureau – 2000 Decennial Census, 2010 Decennial Census, 2012 Estimates, Estimates of the Components of Resident
Population Change
section 02
The total population of Clinton County decreased by 3
percent between 2000 and 2013. The major contributor
to the decline was net domestic migration, with a net
population loss of over 3,444 people. Domestic
migration examines the number of residents who moved
out of the county minus the number who moved into the
county from other counties in Indiana or other U.S.
states.
Natural increase (the difference between the number of
births versus deaths) shows that births outpaced deaths
by nearly 2,048 people. On the other hand, international
migration had a net increase of over 1,909 individuals,
indicating that the county experienced an influx of new
people from outside the U.S.
33,866 33,224 32,784
2020201320102000
Total population
projections
*Components of population extracted from Components of Population Change 2010
(CO-EST-2010) and Components of Population Change (PEPCOMP 2013).
Estimation residuals are leading to a positive total change in total population.
32,916
8. 8
Population pyramids
Population pyramids are visual representations of the age distribution of the
population by gender.
The male to female ratio of the population slightly
decreased between 2000 and 2013, indicating that a
larger share of the population is now made up of
females. In addition, the distribution of people across
the various age categories over the two time periods
has changed as well.
Demography
Source: U.S. Census Bureau – 2000 Decennial Census and 2013 Annual Population Estimates
section 02
The percent of people under 50 years old decreased
among males and females over the 2000-2013 period.
Noticeable declines have occurred among people of
prime working age—those 20 to 29, 30 to 39 and 40 to
49 years of age. Furthermore, about 35 percent of the
population is now 50 and over, up from 28 percent in
2000.
Male Female
20132000
Male Female
7.5%
8.1%
6.6%
7.2%
7.4%
4.8%
3.5%
2.7%
1.3%
7.2%
7.2%
6.0%
7.0%
7.3%
5.2%
4.2%
3.6%
3.1%
10 8 6 4 2 0 2 4 6 8 10
0-9
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80+
Percent of the Population
AgeCohort
7.3%
7.2%
6.0%
5.9%
6.5%
7.0%
5.0%
2.8%
1.6%
6.9%
6.8%
5.9%
6.0%
6.1%
7.2%
5.2%
3.5%
3.1%
10 8 6 4 2 0 2 4 6 8 10
0-9
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80+
Percent of the PopulationAgeCohort
9. 9
Race
The percentage of the population
that is non-White in Clinton
County did not change
dramatically between 2000 and
2013. As such, the racial make-up
of the county remains largely
Caucasian (white).
While every race, other than White,
experienced a numerical increase
between 2000 and 2013, the Asian
population remained basically stable
while the Mixed Descent category
increased the most, expanding from 0.4
percent to 0.8 percent of the total
population between 2000 and 2013.
Demography
Race Data Source: U.S. Census Bureau – 2000 and 2013 Annual Population Estimates
section 02
White,
99%
Other,
1%
2000
Black
Native
Asian
Two or More
Races
White,
98%
Other,
2%
2013
Black
Native
Asian
Two or More
Races
10. 10
Ethnicity
Hispanics are individuals of
any race whose ancestry is
from Mexico, Puerto Rico,
Cuba, Spain, the Dominican
Republic or any other
Spanish-speaking Central or
South American country.
There were 2,478 residing in
Clinton County in 2000. This
figure expanded to 4,783 by
2013, a 93 percent increase.
As a result, Hispanics now
represent 14 percent of the
population in the county (versus
around 7 percent in 2000).
Demography
Source: U.S. Census Bureau – 2000 and 2013 Annual Population Estimates
section 02
14%
7%
Hispanics - 2000
Hispanics - 2013
11. 11
Less than
High
School
20%
High
School
50%
Some
College
16%
Associate's
4%
Bachelor's
or more
10%
2000
Less than
High
School
15%
High
School
47%
Some
College
18%
Associate's
7%
Bachelor's
or more
13%
2013
Educational attainment
Educational attainment for adults
25 years old and over is
increasing, but at a slow rate.
The proportion of adults (25 years of age
and older) with a high school education or
more improved from 80 percent in 2000
to 85 percent by 2013.
The percent with less than a high school
education fell by 5 percentage points
between 2000 and 2013 (from 20 percent
to 15 percent). On the other hand, those
with some college or an associate’s
degree grew by a few percentage points.
The number of adults with a bachelor’s
degree or more grew by 3 percentage
points, from 10 percent in 2000 to 13
percent in 2013, still well behind the
statewide figure of over 23 percent.
Demography
Source: U.S. Census Bureau – 2000 Decennial Census and 2013 ACS
section 02
12. 12
Takeaways
The population of Clinton County is expected
to decrease over the next few years, and if
past trends hold, that decrease will be largely
due to out-migration. Were it not for natural
increase or the influx of international migrants
into Clinton County, the county’s total
population loss would have been much larger
over the past decade or more.
With the changing population has come shifts
in the age structure of the county. Since 2000,
the county has experienced a relative growth
of older residents (50 years of age or older),
Worthy of attention is the falling percentage of
people in the county of prime working age,
individuals in the 20 to 29, 30 to 39 and 40 to
49 age groupings.
While the racial make-up of the county remains
largely Caucasian (i.e., white), it has become
more ethnically diverse as a result of the
expansion of its Hispanic population – doubling
from 7 percent to 14 percent of the population
between 2000 and 2013. It is likely that the
Hispanic population will continue to expand its
presence in the coming years.
The educational attainment of the county’s adult
population (25 and over) has improved with more
people completing a four-year college education
or more. However, the percent of people with only
a high school education remains quite sizable at
47 percent, suggesting that securing jobs that
require high skilled, higher educated workers may
be difficult to achieve in the near future.
Demography
section 02
14. 14
Establishments
Components of Change for Establishments
Total Change (2000-11) 604
Natural Change (births
minus deaths)
620
Net Migration -16
The number of establishments in Clinton
County grew by 36 percent between 2000
and 2011.*
The growth of establishments was due to natural
change, with 1,930 establishments being launched in
the county between 2000 and 2011, while 1,310
establishments closed during this same time period.
The net migration of establishments was negative (-
16), suggesting that more establishments moved out
of than moved into the county during this time period.
All told, the county experienced a net gain of 604
establishments.
Economy
Source: National Establishment Time Series (NETS) – 2012 Database
section 03
An establishment is a
physical business location.
Branches, standalones and
headquarters are all
considered types of
establishments.
Definition of Company
Stages
0 1
2 3
4
Self-
employed
2-9
employees
10-99
employees
100-499
employees
500+
employees
*2012 data contains firm-births up to 2011 only
15. 15
Number of establishments by stage/
employment category
Economy
Source: National Establishment Time Series (NETS) – 2012 Database
section 03
2000 2011
Stage Establishments Proportion Establishments Proportion
Stage 0 541 32.6% 815 36%
Stage 1 910 54.8% 1 ,247 55%
Stage 2 188 11.3% 182 8%
Stage 3 20 1.2% 17 0.8%
Stage 4 2 0.1% 4* 0.2%
Total 1,661 100% 2,265 100%
The NETS Database is derived from the Dun & Bradstreet archival national establishment data, a population of known
establishments in the United States that is quality controlled and updated annually. Establishments include both private and
public sector business units and range in size from one employee (i.e., sole-proprietors and self-employed) to several thousand
employees.
*Reference USA database has only two stage 4 companies, as compared to
four stage 4 companies in NETS. The two companies in Reference USA are
contained in the NETS database.
16. 16
Number of jobs by stage/employment
category
Economy
Source: National Establishment Time Series (NETS) – 2012 Database
section 03
2000 2011
Stage Jobs Proportion Jobs Proportion
Stage 0 541 4% 815 5.3%
Stage 1 3,187 23.4% 3,857 24.9%
Stage 2 4,676 34.3% 5,015 32.4%
Stage 3 3,936 28.9% 3,361 21.7%
Stage 4 1,300 9.5% 2,420 15.6%
Total 13,640 100% 15,468 100%
17. 17
Number of sales by
stage/employment category
Economy
Source: National Establishment Time Series (NETS) – 2012 Database
section 03
2000 2011
Stage Sales Proportion Sales Proportion
Stage 0 $64,624,980 3.3% $55,500,028 3.3%
Stage 1 $403,520,821 20.8% $312,815,928 18.5%
Stage 2 $515,323,685 26.6% $431,034,445 25.5%
Stage 3 $657,687,590 34.0% $581,511,789 34.5%
Stage 4 $294,368,674 15.2% $306,999,752 18.2%
Total $ 1,935,525,753 100% $1,687,861,944 100%
18. 18
Top five industries in 2013
63 percent of jobs are tied to
one of the top five industries
in Clinton County.
Manufacturing is the largest industry
sector (3,698 jobs) followed by
Government (1,715 jobs), Health Care
and Social Assistance (1,273 jobs) and
Retail Trade (1,239 jobs).
Other services is the smallest of the
top industry sectors with 858 people
employed in this industry, a sector that
also experienced a 13 percent decline
between 2002 and 2013.
Economy
section 03
Manufacturing
27%
Government
12%
Health Care and Social
Assistance
9%
Other Services
6%
Retail Trade
9%
All other industries
37%
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
19. 19
Industry distribution and change
NAICS
Code
Description
Jobs
2002
Jobs
2013
Change
(2002-2013)
% Change
(2002-2013)
Average Total
Earnings
2013
11 Crop and Animal Production 755 857 102 14% $31,318
21 Mining, Quarrying, and Oil and Gas Extraction 19 26 7 37% $390,834
22 Utilities <10 0 ---- ---- ----
23 Construction 733 722 -12 -2% $40,680
31 Manufacturing 4,361 3,689 -673 -15% $57,634
42 Wholesale Trade 248 268 20 8% $58,874
44 Retail Trade 1,374 1,239 -141 -10% $23,409
48 Transportation and Warehousing 259 505 246 95% $61,088
51 Information 140 94 -46 -33% $45,468
52 Finance and Insurance 371 416 44 12% $53,514
53 Real Estate and Rental and Leasing 271 373 121 48% $21,941
54
Professional, Scientific, and Technical
Services
260 267 11 4% $33,908
55 Management of Companies and Enterprises 14 10 -3 -23% ----
56
Administrative and Support and Waste
Management and Remediation Services
440 580 140 32% $22,671
61 Educational Services 37 42 5 14% $16,960
62 Health Care and Social Assistance 1,347 1,273 -74 -5% $41,575
71 Arts, Entertainment, and Recreation 114 128 14 12% $17,706
72 Accommodation and Food Services 746 796 49 7% $13,815
81 Other Services (except Public Administration) 963 858 -131 -13% $19,466
90 Government 1,689 1,715 26 2% $44,322
99 Unclassified Industry ---- ---- 0 0% ----
All Total 14,148 13,859 -301 -2% $41,252
Economy
section 03
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
20. 20
Industry distribution and change
The largest employment gains
(in percent) in Clinton County
occurred in:
Transportation and Warehousing
(+95 percent)
Real Estate and Rental and
Leasing (+48 percent)
The largest employment
losses (in percent) occurred
in:
Information (- 33 percent)
Management of Companies and
Industries (-23 percent)
Economy
section 03
Employment Growth Employment Declines
Numerical job changes in the top five
industry sectors, 2002-2013
Transportation &
Warehousing
(+246)
Administrative &
Waste Management
(+140)
Manufacturing
(-673)
Retail Trade
(-141)
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
21. 21
Top five occupations in 2013
The top five occupations in
Clinton County represent 56
percent of all jobs.
Production and Sales and Related are
the occupations with the largest
number of workers, representing 17
percent and 11 percent of the
workforce, respectively.
Management occupations is the
smallest of the top five occupations in
the county (8 percent of jobs).
Economy
section 03
Production
17%
Sales and Related
11%
Transportation and
Material Moving
10%
Office and
Administrative Support
10%
Management
8%
All Other Occupations
44%
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
22. 22
SOC Description
Jobs
2002
Jobs
2013
Change
(2002-2013)
% Change
(2002-2013)
Hourly
Earnings 2013
11 Management 1,124 1,136 12 1% $23.09
13 Business and Financial Operations 353 351 -2 -1% $28.47
15 Computer and Mathematical 114 74 -40 -35% $24.14
17 Architecture and Engineering 187 112 -75 -40% $26.98
19 Life, Physical and Social Science 45 43 -2 -4% $25.06
21 Community and Social Service 158 133 -25 -16% $19.37
23 Legal 47 39 -8 -17% $35.16
25 Education, Training and Library 654 684 30 5% $18.31
27
Arts, Design, Entertainment, Sports and
Media
245 246 1 0% $16.10
29 Health Care Practitioners and Technical 467 482 15 3% $26.33
31 Health Care Support 380 410 30 8% $11.69
33 Protective Service 190 178 -12 -6% $17.19
35 Food Preparation and Serving Related 937 961 24 3% $9.11
37
Building and Grounds Cleaning
Maintenance
500 401 -99 -20% $11.13
39 Personal Care and Service 512 444 -68 -13% $10.05
41 Sales and Related 1,437 1,459 22 2% $13.98
43 Office and Administrative Support 1,572 1,413 -159 -10% $15.26
45 Farming, Fishing and Forestry 150 187 37 25% $12.36
47 Construction and Extraction 602 602 0 0% $16.24
49 Installation, Maintenance and Repair 573 547 -26 -5% $18.50
51 Production 2,472 2,324 -148 -6% $15.65
53 Transportation and Material Moving 1,273 1,417 144 11% $15.66
55 Military 112 107 -5 -4% $18.99
99 Unclassified 57 108 51 89% $11.01
All Total 14,160 13,859 -301 -2% $16.36
Occupation distribution and change
Economy
section 03
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
23. 23
Occupation distribution and change
Economy
Source: Economic Modeling Specialists International (EMSI) – 2014.3 Class of Worker
section 03
The largest percentage gains
in jobs in Clinton County
occurred in:
Unclassified Occupation (+89
percent)
Farming, Fishing and Forestry
Occupations (+25 percent)
The largest percentage loss in
employment occurred in:
Architecture and Engineering (-40
percent)
Computer and Mathematical
occupations (-35 percent)
Numerical changes in the top five
occupations, 2002-2013
Transportation &
Material Moving
(+144)
Unclassified (+51)
Farming, Fishing &
Forestry (+37)
Office &
Administrative
(-159)
Production
(-148)
Employment
Increase
Employment Decrease
24. 24
Income and poverty
2000 2006 2013
Total Population in
Poverty
8.3% 11.9% 14.4%
Minors (up to age 17)
in Poverty
11.4% 16.3% 21%
Real Median Income
(2013 US$)
$ 54,476 $ 50,802 $ 47,279
The median income for
households in Clinton County
dipped by $7,197 between 2000
and 2013 in real dollars (that is,
adjusted for inflation).
Both the total population in poverty
and the number of minors living in
poverty have increased by sizable
percentages since 2000. In fact, the
proportion of minors in poverty
expanded by nearly 10 percent from
2000 to 2013. However, child poverty
has improved since 2011 (see next
page).
The growth in poverty could be
linked to a number of factors,
including the remnants of the Great
Recession, the large number of
working adults with lower levels of
education, and the loss of higher
paying jobs in the manufacturing
sector.
Economy
Source: U.S. Census Bureau – Small Area Income and Poverty Estimates (SAIPE)
section 03
25. 25
Income and poverty
Median income in Clinton County has decreased in recent years, while poverty has
shown recent improvements, although still higher than in 2000.
Economy
Source: U.S. Census Bureau – Small Area Income and Poverty Estimates (SAIPE)
section 03
0
5
10
15
20
25
30
42,000
44,000
46,000
48,000
50,000
52,000
54,000
56,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
PopulationinPoverty(percent)
RealMedianIncome(2013dollars)
Year
Poverty and Income in Clinton, 2000 to 2013
Median Income
All Ages in
Poverty
Minors (age 0 -17) in
Poverty
26. 26
Takeaways
The greatest growth in establishments in
Clinton County occurred in businesses having
fewer than 10 employees. So, focusing on the
needs of the self-employed (Stage 0) and
Stage 1 establishments (those with 2 to 9
employees) may be worth considering. At the
same time, Stage 2 firms, while experiencing
a small decline in the number of
establishments over the 2000 to 2011 time
period, added nearly 340 jobs. So, attending
to the growth possibilities of Stage 2
establishments would be a smart move. Of
course, the impressive job gains among Stage
4 establishments in the county is worthy of
note; they added over 1,110 jobs to the
County’s economy between 2000 and 2011.
In sum, it is important for Clinton County to
continue pursuing a balanced economic
development portfolio. This includes a
concerted effort to promote the growth of
Stage 1 and 2 companies in the area.
Among the top five industries in Clinton County,
only government experienced growth between
2002 and 2013, a modest 2 percent increase.
While median income decreased over the past
decade, the percentage of people in poverty
grew, although recent data suggest that poverty
rates for both adults and children have
experienced modest declines since 2011.
Promoting job growth for occupations requiring
educated workers could be a good way to retain
working adults with higher levels of educational
attainment. Moreover, it would help boost the
median income of individuals in the county.
In light of the number of people falling below the
poverty line, it will be important to target
services to these individuals, especially those
with children. Efforts to expand training and
work opportunities for those able to move into
the workforce will be something worth
considering.
Economy
section 03
28. 28
Labor force and unemployment
2002 2007 2013
Labor Force 16,642 16,887 16,453
Unemploymen
t Rate
4.7% 4.5% 7.1%
The unemployment rate in Clinton
County expanded from 4.7 percent
in 2002 to 7.1 percent in 2013.
Despite the uptick in the unemployment
between 2002 and 2013, the actual
number of persons in the labor force did
not change dramatically over the 2002
to 2013 time period.
Labor market
Source: U.S. Bureau of Labor Statistics – Local Area Unemployment Statistics
section 04
29. 29
Unemployment rate
The unemployment rate in Clinton County peaked at 10.8 percent in 2009 and has
declined since that time.
Labor market
Source: U.S. Bureau of Labor Statistics – Local Area Unemployment Statistics
section 04
2.8%
5.6%
4.5%
10.8%
7.1%
0.0
2.0
4.0
6.0
8.0
10.0
12.0
Year
30. 30
Commuteshed 2011
A county’s commuteshed is the
geographic area to which its
resident work force travels to
work.
A large portion of employed residents
in Clinton County commute to jobs
located outside of Clinton County (over
7,100 workers).
The top destination counties for Clinton
County residents who work outside of
the county are Tippecanoe County,
Marion County and Boone County,
Indiana.
Just under 5,000 people both work and
live in Clinton county.
Labor market
Source: U.S. Census Bureau – Longitudinal Employer-Household Dynamics (LEHD)
section 04
7,142
Out-Commuters
4,961
Same Work/
Home
Counties Commuters Proportion
Clinton 4,961 41%
Tippecanoe 2,649 21.9%
Marion 971 8.0%
Boone 914 7.6%
Hamilton 333 2.8%
Carrol 280 2.3%
All Other
Counties 1,995 16.5%
31. 31
Commuteshed 2011
Labor market
section 04
Source: U.S. Census Bureau, OTM, LEHD, PCRD
Eighty percent of Clinton County’s
working residents are employed in
Clinton, Tippecanoe, Boone or
Marion Counties. Another 5 percent
commute to Carrol and Hamilton
Counties, while an additional 5
percent travel as far as Lake and
Allen Counties.
Collectively, these counties
represent 90 percent of the
commuteshed (or the journey to
work) characteristics of Clinton
County’s residents in the workforce.
32. 32
Laborshed 2011
Counties Commuters Proportion
Clinton 4,961 50%
Tippecanoe 941 9.50%
Howard 435 4.40%
Carrol 377 3.80%
Marion 318 3.20%
Boone 311 3.10%
All Other
Counties 2,576 25.9%
Labor market
Source: U.S. Census Bureau – Longitudinal Employer-Household Dynamics (LEHD)
section 04
4,958
In-Commuters
4,961
Same Work/
HomeA county’s laborshed is the
geographic area from which it draws
employees.
Nearly 5,000 individuals working in Clinton
County commute from other counties.
Tippecanoe County and Howard County
are the biggest sources of outside labor for
Clinton County.
Approximately half of the labor force needs
of Clinton County are being met by
employees who live outside of the county.
The most significant providers of outside
workers are Tippecanoe and Howard
Counties. Marion and Boone Counties
contribute just over 3 percent of the
workforce needs to Clinton County.
33. 33
Laborshed 2011
Labor market
section 04
Source: U.S. Census Bureau, OTM, LEHD, PCRD
The bulk (80 percent) of Clinton
County’s workforce is drawn from
the local workforce or from
surrounding counties (shown in
red on the map). Another 5
percent are drawn from Jasper,
White, Cass, Tipton and Hendricks
Counties (in yellow). An additional
5 percent of the labor force travel
to Clinton County for work from 11
additional counties in Indiana (in
green).
Combined, some 25 counties
represent 90 percent of Clinton
County’s laborshed.
34. 34
Takeaways
Clinton County’s unemployment rate swelled
between 2000 and 2009 but has since
declined. The major uptick in unemployment
was linked, in no small way, to the economic
challenges associated with the Great
Recession. With the improving economic
forces in the nation and state of Indiana, there
is every reason to believe that unemployment
rate will continue to improve in the county.
Over 7,100 labor members who live in Clinton
County are employed outside of the county,
while approximately 5,000 workers from
outside the county work in Clinton County. In
essence, this means that the county is
experiencing a net loss of over 2,100 workers.
Determining the human capital attributes of
workers who commute to jobs outside the
county
could be insightful. It could provide the
information needed to determine how best to
reduce the leakage of educated and skilled
workers to surrounding counties.
In light of the strong economic connection of
Clinton County to surrounding counties, it may
make sense to explore regional economic
development strategies that build on the
economic assets of the entire region.
Given the decline in the county’s median
income, finding ways to improve the skills of
the workforce could be critical. The recent
expansion of Ivy Tech in the county could be an
important conduit for expanding workforce
development opportunities for current and
future labor force participants.
Labor market
section 04
35. 35
Report Contributors
This report was prepared by the Purdue Center for Regional Development in
partnership with Purdue University Extension.
section 04
Data Analysis
Indraneel Kumar,
Ph.D.
Ayoung Kim
Michael Wilcox. Ph.D.
Report Authors
Elizabeth Dobis
Francisco Scott
Bo Beaulieu, Ph.D.
Report Design
Tyler Wright
Adeline Jackson
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