Southwestern Wisconsin Regional Housing Study

Transcription

Southwestern Wisconsin
Regional Housing Study
March 31, 2014
STAFF
Larry Ward
Executive Director
Troy Maggied
Planning Program Manager
Ed White
Economic Development
Program Manager
Katherine Burk
Assistant Planner
James Winters
Associate Planner
Ben Gultch
GIS Specialist
COMMISSIONERS
Grant County
Larry Wolf*
Eileen Nickels
Jerry Wehrle
Green County
Arthur Carter*
Nathan Klassy
Mike Doyle
Iowa County
David Bauer*
Shirley Barnes
Todd Novak
Lafayette County
Jack Sauer*
Timothy McGettigan
Table of Contents
Introduction ....................................................................... 4
Study Area .......................................................................... 5
Housing Demand ................................................................ 7
Demographic Trends ..................................................................... 7
Population................................................................................ 7
Ethnicity ................................................................................... 9
An Aging Population ............................................................. 10
Employment & Income Trends ................................................... 14
Employment........................................................................... 14
Income Trends ....................................................................... 15
Female Poverty Numbers ...................................................... 17
Housing Supply ................................................................. 17
Households .................................................................................. 17
Occupancy Status ........................................................................ 18
Foreclosures........................................................................... 21
Owning versus Renting .......................................................... 22
Housing Conditions ..................................................................... 24
Age of Housing Stock ............................................................. 24
New Home Development Trends .......................................... 26
Elevated Lead Blood Levels.................................................... 26
Housing Affordability .................................................................. 27
Fair Market Rents .................................................................. 28
Wisconsin Rent Guidelines .................................................... 28
Conclusion ........................................................................ 29
Housing Recommendations ........................................................ 32
Richland County
Jeanetta Kirkpatrick*
Robert Neal Smith
* denotes County Board Chair
P.O. Box 262
Platteville WI 53818
p: 608.342.1636 • f: 608.342.1220
e: [email protected]
www.swwrpc.org
2
About SWWRPC
Southwestern Wisconsin Regional Planning Commission (SWWPRC) is an extension of local government in
Southwestern Wisconsin. We provide low-cost expert planning and economic development services to the county,
city, village, and town governments of our five-county jurisdiction (Grant, Green, Iowa, Lafayette, and Richland
counties). We assist our local communities to save both time and money while planning for the future. SWWRPC
is one of nine Regional Planning Commissions in the State of Wisconsin and was created by an Executive Order in
1970.
Over 85% of our budget comes from funding outside the region, with the SWWRPC bringing in over $14 million of
economic development funding alone. We have leveraged these self-generated funds to help our counties and
their communities save costs and prevent redundancy while preparing for future challenges.
SWWRPC Vision
We envision a southwestern Wisconsin that has met its full potential. A place that is recognized for its resilient
and diverse economy, high quality of life, and distinctive Driftless landscape. It will be a place where
interconnected bonds between individuals and organizations form strong communities of inclusion and
cooperation. Southwestern Wisconsin will be a place where the richness of the land contributes to the healthy
lives of its residents and visitors—and the stewardship of our natural resources is a shared and valued
responsibility. Our region will be a place that fosters innovation and creativity, inspiring and empowering thinkers
and doers. With deep respect for the traditions that built southwestern Wisconsin, we strive to create the best
possible region for tomorrow.
SWWRPC Mission
The Southwestern Wisconsin Regional Planning Commission collaborates with communities and organizations to
build capacity within southwestern Wisconsin, serving as advocates for its residents. We create opportunities and
develop dynamic solutions to the challenges facing the region. We foster growth by supporting innovative
endeavors that provide tangible benefits to those we serve. We believe in the bold vision of southwestern
Wisconsin and work to build the region’s future.
Neighborhood Housing Services of Southwestern
Wisconsin
Neighborhood Housing Services of Southwestern Wisconsin (NHSSW) has been a regional leader in housing and
community development for over 30 years. NHSSW is committed to educating residents in affordable housing
services, revitalizing area communities, and building sustainable partnerships to build social capital. NHSSW is
committed to incorporating healthy and sustainable principles into every facet of their operations and throughout
their lines of business. NHSSW has administered and successfully executed several Neighbor Works green grants
through our CBO and Multi-Family Lines of Business and are currently administering a CBO Green Grant designed to
explore feasibility and make ready for the Neighbor Works Green Organization designation.
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Introduction
In October of 2010, Southwestern Wisconsin was one of 45 regions in the United States to receive federal funding to
plan for economic vitality and regional growth. This project, titled Grow Southwest Wisconsin, was a grassroots planning
initiative led by Southwestern Wisconsin Regional Planning Commission (SWWRPC). Grow Southwest Wisconsin was
largely successful because of its public outreach. Over the course of the planning process, 36 public meetings were held
with over 100 participants, and over 100 additional participants were surveyed. These meetings were divided into nine
distinct topic areas, each mapping an approach to subject matter critical to the region. Housing was one of those nine
topics areas.
Neighborhood Housing Services of Southwestern Wisconsin (NHSSW) has provided housing related services to
Southwestern Wisconsin for over 30 years. NHSSW offers a neighborly approach in providing low-cost affordable
housing services including: community organizing, home loans, foreclosure intervention, homebuyer education,
affordable housing construction, and senior housing. In addition to providing valuable insight through to the housing
group, NHSSW was awarded a technical assistance grant made possible through Grow Southwestern Wisconsin. This
grant allowed SWWRPC and NHSSW to collaborate on a number of initiatives to improve housing issues across the
region.
This document, Southwestern Wisconsin Regional Housing Study, specifically provides statistical and narrative data
identifying a housing profile in Southwestern Wisconsin. The Study describes the current situation related to housing
markets, home ownership, and affordability challenges. Nationally, changing demographics are shaping the housing
market for years to come. Southwestern Wisconsin communities must realize the local demographic shift to prepare and
accommodate for the changing housing markets. The emerging housing needs include: senior-assisted housing, rental
housing, more low- to moderate-income housing, and multi-family homes. Each county and municipality will experience
different housing needs, which will determine new policies and programs offered.
For more information visit the Grow Southwestern Wisconsin website: www.growsouthwest.org
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Study Area
The Study Area includes the counties of Grant, Green, Iowa, Lafayette, and Richland along with selected cities in the
region, such as County Seats, Communities of Higher Education and other selected cities (Figure 1).
The following items were analyzed to determine the workforce housing needs of the Study Area:
 Housing Demand
 Employment & Income Trends
 Housing Supply
The analysis reviews trends in each county, the county seats, Communities of Higher Education, selected cities in
Richland County, and cities that make up the Wisconsin River Corridor.
Counties





Grant County
Green County
Iowa County
Lafayette County
Richland County
County Seats





Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Communities of Higher Education


Fennimore
Platteville
Richland County Cities



Cazenovia
Lone Rock
Viola
Wisconsin River Corridor






5
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Figure 1 - Southwestern Wisconsin Regional Housing Study - Study Area
6
Housing Demand
Demographic Trends
Population
According to the USDA Economic Research Service (ERS), the number of people living in non-metropolitan1 counties now
stands at 46.2 million. The population dynamics produces a landscape pattern where 15 percent of U.S. residents are
spread across 72 percent of the land area of the U.S. The ERS conducts research related to the relationship between
population change and the socioeconomic well-being of rural and small-town residents, the aging population, and the
changing geography of migration. In addition, population change is uneven across rural and small-town America. Despite
these non-metropolitan counties losing population between 2010 and 2012, they nevertheless experienced rates of
population growth above the national rate of 1.7 percent.2
Tables 1 through 5 include the 2010 population, population projections for 2020 and 2030, and the growth rate from
2010 to 2030. The population of the Study Area was 146,594 in 2010. The Study Area’s population is expected to grow
8.1 percent by 2030, while Wisconsin will grow 12.1 percent.
Table 1 - County, Population Projections
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Wisconsin
United States
2010
2020
2030
51,208
52,420
52,960
36,842
39,270
42,125
23,687
25,035
27,105
16,836
17,355
17,720
18,021
18,275
18,575
146,594
152,355
158,485
5,686,986
6,005,080
6,375,910
310,384,000 335,605,444 361,680,000
Growth Rate
2010 - 2030
3.4%
14.3%
14.4%
5.3%
3.1%
8.1%
12.1%
16.5%
*Source: 2010 Census, State of Wisconsin DOA Population Projections
Table 2 - County Seat, Population Projections
County Seat
2010
2020
2030
Growth Rate
2010 - 2030
Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Average of Total
2,451
4,693
3,868
10,827
5,184
5,405
2,455
5,010
3,745
11,140
5,300
2,445
5,500
3,570
11,450
5,415
-0.2%
17.2%
-7.7%
5.8%
4.5%
5,530
5,676
3.9%
*Source: 2010 Census, State of Wisconsin DOA Population Projections
Non-metro counties include some combination of: open countryside, rural towns (places with fewer than 2,500 people), and
urban areas with populations ranging from 2,500 to 49,999 that are not part of larger labor market areas.
2 http://www.ers.usda.gov/topics/rural-economy-population/population-migration.aspx#.UvPBtfldXT8
1
7
Table 3 - Communities of Higher Education, Population Projections
City
2010
2020
2030
Growth Rate
2010 – 2030
Fennimore
Platteville
Average of Total
2,497
11,224
6,861
2,535
12,340
2,555
13,180
2.3%
17.4%
7,438
7,868
9.9%
*Source: 2010 Census, State of Wisconsin DOA Population Projection
Table 4 - Richland County Cities, Population Projections
City
2010
2020
2030
Growth Rate
2010 - 2030
Cazenovia
Lone Rock
Viola
Average of Total
314
888
477
560
305
905
500
305
930
530
-2.9%
4.7%
11.1%
570
588
4.3%
Table 5 - Wisconsin River Corridor, Population Projections
Growth Rate
2010 – 2030
City
2010
2020
2030
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Average of Total
1,456
637
434
3,231
1,299
185
1,207
1,540
660
435
3,255
1,225
195
1,660
715
435
3,245
1,150
195
14.0%
12.2%
0.2%
0.4%
-11.5%
5.4%
1,218
1,233
3.5%
In non-metro counties the USDA ERS and U.S. Census calculate urban and rural areas based on minimum population
density requirements3, proximity to larger labor markets and other factors. Both the Census and USDA ERS agree a
territory must encompass at least 2,500 people to qualify as an urban area, population less than 2,500 is considered
rural. Therefore in 2010, there were 103,975 people living in the rural areas of the Study Area, while 42,619 live in urban
areas (see Table 6). Due to U.S. Census methodology, Lafayette is considered rural only. Darlington’s population, the
county seat of Lafayette, falls just under the 2,500 minimum at 2,451 in the 2010 U.S. Census.
Table 6 - County, Urban and Rural Population Percentages
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
2010
Population
51,208
36,842
23,678
16,836
18,021
146,585
Urban
18,185
14,657
4,756
0
5,021
42,619
*Source: 2010 Census
3
8
http://www.census.gov/geo/reference/ua/urban-rural-2010.html
2010 %
Urban
35.5%
39.8%
20.1%
0.0%
27.9%
29.1%
Rural
33,023
22,185
18,931
16,836
13,000
103,975
2010 %
Rural
64.5%
60.2%
80.0%
100.0%
72.1%
70.9%
Ethnicity
Figure 2 displays the Hispanic population growth experienced in the Study Area from 2000 to 2010. In 2000, only 4
percent of Wisconsin’s population was Hispanic, but by 2010 this number grew to almost 6 percent of the statewide
population. The Hispanic population in the Study Area grew one percent from 2000 to 2010.
Figure 1 - County, Hispanic Population Change
Percent of Total Population
Hispanic Population as a Percentage of Total Population 2000 to 2010
7.00%
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
.00%
5.91%
1.32%
0.55%
0.89%
3.60%
3.10%
2.79%
2.05%
1.42%
0.93%
0.55%
0.32%
2.00%
0.64%
County
2000
2010
*Source: 2000 Census, 2010 Census
Figure 3 displays the Native American population growth rate in the Study Area from 2000 to 2010. Wisconsin’s total
Native American Population is only 1.33 percent in 2010, a slight increase from .80 percent in 2000. Richland County has
the highest percentage of Native American with the other counties close behind. All counties experienced growth in the
Native American population since 2000.
Figure 3 - County, Hispanic Population Change
Native American Population as a Percentage of Total Population,
2000 to 2010
1.4%
1.2%
1.0%
0.8%
0.6%
0.4%
0.2%
0.0%
1.33%
0.82%
0.37%
0.11%
0.34%
0.18%
0.44%
0.40%
0.11%
0.11%
County
2000
*Source: 2000 Census, 2010 Census
9
2010
0.54%
0.21%
0.39%
0.14%
An Aging Population
Age demographics continue to change dramatically in the United States, and southwest Wisconsin is no exception. The
older population is growing rapidly, and the aging of the “Baby Boomers” born between 1946 and 1964 (and who began
turning age 65 in 2011), are accelerating this growth. The large population of older Americans will be more racially
diverse and better educated than previous generations. Another significant trend is the increase in the proportion of
men age 85 and over who are veterans. This older generation will face challenges such as a higher percentage of
functional limitations in activities of daily living and a greater likelihood of having a disability. This trend will have
consequences on the demand for health care services, particularly in the area of long-term care.4
Wisconsin’s senior population, defined as those 65 and older, will hit 15 percent in 2015, up from 13 percent in 2000. 5
The aging population will affect the Wisconsin housing markets in coming years. The aging population will drive demand
for assisted living facilities, other senior-friendly housing such as single-level housing and housing that is near medical
facilities and transportation. If those facilities are not available, the seniors may move to areas with available resources.
The data shows that the population 65 years and older is increasing in the counties, but it is decreasing in the county
seats. One explanation could be counties will see an influx of seniors who own vacation homes in the Study Area, but
live elsewhere like Madison. The vacation homes are located in the county, but not the county seats. As the senior
population begins to retire, they may decide to sell their city homes and move permanently to their vacation homes. The
occupancy status section displays the occupied status in each county. A good percentage of those vacant homes are
vacation homes, particularly for Richland County. The Study Area’s senior population grew since 1990 as seen in Figure
4. The population trend of seniors in the selected cities of the Study Area can be seen in figures 5 through 8.
Figure 4 - County, Percent of Population 65+
Percent of Population 65 Years and Older, 1990 - 2010
20.0%
18.0%
16.0%
14.0%
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
Grant
Green
Iowa
Lafayette Richland Study Area Wisconsin
United
States
County
1990 %
2000 %
2010 %
*Source: 1990 Census, 2000 Census, and 2010 Census
4
5
Federal Interagency Forum on Aging Related Statistics, http://www.agingstats.gov/agingstatsdotnet/main_site/default.aspx
State of Wisconsin Department of Administration (DOA) Population Projections
10
Figure 5 - County Seat, Percent of Population 65+
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Darlington
Dodgeville
Lancaster
Monroe
Richland
Center
Total
County Seats
1990 %
2000 %
2010 %
Figure 6 - Communities of Higher Education, Percent of Population 65+
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Fennimore
Platteville
Total
Municipality
1990 %
2000 %
2010 %
Figure 7 - Richland County Cities, Percent of Population 65+
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Cazenovia
Lone Rock
Municipality
1990 %
2000 %
11
Viola
2010 %
Total
Figure 8 - Wisconsin River Corridor Cities, Percent of Population 65+
20.0%
15.0%
10.0%
5.0%
0.0%
Arena
Avoca
Blue River Boscobel
Muscoda
Woodman
Total
Municipality
1990 %
2000 %
2010 %
In order to understand the dynamic shift in population, it is also necessary to understand the distribution of various age
groups in the Study Area. The age structure within communities is a vital element of the future workforce supply, as
well as the need for workforce and senior-friendly housing. Additionally, this graph illustrates those aged 35 to 64 are
the highest percentage of the population in each county, which has implications for those turning 65 in the coming
years. Figures 9 through 13 displays the age groups in the Study Area. The label for 35 to 64 years is noted on each
graph.
Figure 9 - County, Population Age Groups
County, Population Age Groups
50.0%
40.0%
43.1%
43.8%
35.7%
40.7%
40.2%
40.0%
40.5%
Study Area
Wisconsin
30.0%
20.0%
10.0%
0.0%
Grant
Green
Iowa
Lafayette
Richland
Municipality
under 5
5 to 14
12
39.7%
15 to 19
20 to 34
35 to 64
65 and Older
United
States
Figure 10 - County Seats, Population Age Groups
County Seat, Population Age Groups
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
40.0%
34.3%
31.2%
Darlington
Dodgeville
32.8%
30.4%
Lancaster
Monroe
30.0%
Richland
Center
Total
Municipality
under 5
5 to 14
20 to 34
15 to 19
35 to 64
65 and Older
Figure 11 - Communities of Higher Education, Population Age Groups
Communities of Higher Education, Population Age Groups
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
29.3%
22.3%
19.6%
Fennimore
Platteville
Total
Municipality
under 5
5 to 14
13
15 to 19
20 to 34
35 to 64
65 and Older
Figure 12 - Richland County Cities, Population Age Groups
Richland County Cities, Population Age Groups
38.0%
36.9%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Cazenovia
36.4%
33.1%
Lone Rock
Viola
Total
Muncipality
under 5
5 to 14
20 to 34
15 to 19
35 to 64
65 and Older
Figure 13 - Wisconsin River Corridor Cities, Population Age Groups
Wisconsin River Corridor Cities, Population Age Groups
60.0%
52.5%
50.0%
41.3%
41.5%
40.0%
40.2%
43.1%
49.7%
38.2%
30.0%
20.0%
10.0%
0.0%
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Total
Municipality
under 5
5 to 14
20 to 34
15 to 19
35 to 64
65 and Older
Employment & Income Trends
Employment
Table 7 displays the unemployment rate for 2010 and 2012 in order to provide a snapshot of the employment trends in
each of the five counties. Lower unemployment and strong labor market trends positively impact housing markets as
consumers are able and more willing to invest in home ownership. This trend creates a housing market of more
homeowners than renters, which consumes less of household income than renting, as is described in the “Home
Ownership" section. The 2012 unemployment rate decreased since 2010 for each county.
14
Table 7 - County, Workforce Development
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Wisconsin
United States
2010
Unemployment Rate
7.2%
8.3%
7.6%
7.0%
8.6%
7.7%
8.3%
9.6%
2012
Unemployment Rate
5.8%
6.4%
6.2%
5.6%
6.0%
6.0%
6.9%
8.1%
*Source: Department of Workforce Development
An additional snapshot of the employment trends can be presented with the type of employment in the Study Area. The
Wisconsin Worknet summarized the 2011 top Industry sub-sectors, top employers, and number of employees within
each county. The data suggests a diverse employment sector across the region ranging from Education, Government,
Manufacturing, Agriculture, and others. The tables for each county are available in Appendix A.
As a brief summary, Iowa County’s top industry sub-sector is non-store retailer6, driven largely by Lands’ End. Grant
County's top industry sub-sector is Education Services with the University of Wisconsin – Platteville and Southwest
Wisconsin Vocational Technical Institute. Green County has four employers that have 500 – 999 employees. The County
of Lafayette is the biggest employer in that county. In Richland County, the top six employers have 250 to 500
employees, and so there is no definitive employer.
Income Trends
Comparing the 2010 per capita personal income with previous years illustrates the dramatic changes for the Study Area,
since 2000. In 2000, Wisconsin’s overall per capita personal income was significantly higher than that of the counties in
the Study Area, however this gap shrunk in 2010. Lafayette County experienced an impressive percent change with 54.5
percent growth. Green County had slightly lower percent change with 34.9 percent, yet still higher than Wisconsin’s 33
percent. While the actual per capita personal income may not be as high as the Wisconsin average or National average of
$39,791, each county per capita personal income significantly increased.
Table 8 - County, Per Capita Personal Income
County
2000
2010
Grant
Green
Iowa
Lafayette
Richland
Study Area Average
Wisconsin
$22,291
$26,913
$25,463
$20,749
$20,971
$23,277
$29,141
$32,750
$36,298
$37,639
$32,056
$31,765
$34,102
$38,755
Percent
Change
46.9%
34.9%
47.8%
54.5%
51.5%
46.5%
33.0%
*Source: Bureau of Economic Analysis (BEA)
6Non-store
retail refers to selling of goods and services outside the confines of a retail facility. This generally refers to electronic commerce –
online shopping.
15
Income is one of the single most important factors influencing quality of life in relation to well-being and health for
individuals, communities and households. Income levels indicate the ability of people to purchase essential and nonessential goods and services. The median household income ranges from $43,222 to $53,051 in the Study Area,
compared to a median household income in Wisconsin of $50,401. Figure 14 graphs the median household income
distribution for each county in the Study Area.
Figure 14 - County, Median Household Income Distribution
Grant County
11%
7%
Green County
4%
18%
6%
Iowa County
5%
6%
17%
10%
13%
12%
Median
Household
Income $45,748
Median
Household
Income $53,051
15%
5%
9%
Median
Household
Income $51,740
16%
11%
11%
12%
22%
15%
22%
17%
23%
Richland County
Lafayette County
12%
10%
5%
6%
6%
11%
15%
13%
Median
Household
Income $48,231
7%
13%
Median
Household
Income $43,222
11%
12%
12%
21%
22%
18%
19%
Household Income Distribution Categories
Less than $10,000
$10,001 - $14,999
$15,000 - $24,999
$25,000 - $34,999
$35,000 - $49,999
$50,000 - $74,999
$75,000 - $99,999
$100,000 or more
*Source: Selected Economic Characteristics 2008 - 2012 American Community Survey
16
Female Poverty Numbers
One in three women in America live in or near poverty, which is 42 million women along with 28 million dependent
children. These women are struggling while working and providing for their families. “They’re doing it all, yet they and
their families can’t prosper and that’s weighing the U.S. economy down.”7
Families headed by a single adult are more likely to be headed by women, and these female-headed households are at a
greater risk of poverty. Almost 31% of households headed by a single woman were living below the poverty line – nearly
five times the 6.3 percent poverty rate for families headed by a married couple, nationally.8 Table 9 provides estimates9
for number of people living below the poverty level and the number and percentage of female-headed households
below the poverty level in the Study Area.10
Table 9 - County, Estimated number of Female-Headed Households
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Number of
Households
used for
Estimates
46,753
35,984
23,449
16,577
18,002
140,765
Estimate of
Households below
Poverty Level
Female
Householder, No
Husband Present
6,232
3,248
1,682
1,507
2,071
14,740
1,303
812
262
238
517
3,132
Percent of Female
Householder in
Poverty
20.9%
25.0%
15.6%
15.8%
25.0%
21.2%
*Source: U.S. Census Bureau, 2006-2010 American Community Survey
Housing Supply
The availability of adequate housing is necessary to attract and retain a qualified and diverse labor force. Appropriate
housing also plays an important role in contributing to residents’ financial security and quality of life. This report
provides direction as to the types of housing that are likely to be needed in the future as the basis for developing
appropriate strategies relating to housing mix, density, and community form.
Households
In addition to population numbers, total number of households illustrate another component of an areas’ economic
vitality. The number and characteristics of household members affect the types of relationships and the pool of
economic resources available within the household.11 Since 1990, nationally household compositions shifted from the
common combination of householder, spouse, and natural and/or adopted children to householders living alone in
2000.12 Then in 2010, a greater number of adults lived in shared households13. Adults and families coped with
Shriver Report on Female Poverty http://usnews.nbcnews.com/_news/2014/01/12/22254801-new-report-says-millions-of-women-atrisk-of-falling-into-poverty-economic-ruin?lite
8 Poverty in the United States: A Snapshot http://www.nclej.org/poverty-in-the-us.php
9 The American Community Survey estimates the number of occupied housing units by multiplying the number of ACS addresses by an
estimated occupancy rate at the census block level.
10 The numbers are only estimates obtained from the 2006 – 2010 American Community Survey based on income from the previous 12
months.
11 Population Reference Bureau http://www.prb.org/Publications/Reports/2012/us-household-change.aspx
12 http://www.census.gov/prod/2005pubs/censr-24.pdf
13 Shared households is a process by which people join or combine households. The additional adults are not householders, their spouses, or
cohabitating partners.
7
17
challenging economic circumstances over the course of the recession by joining households or combining households
with other individuals or families.14 An additional household combination is multigenerational (3 or more generations),
which consist of the householder, child, and grandchild generations. Multigenerational households increased faster than
two-generation households in 2000.
The data in table 10 demonstrates that 3,561 total households were added in the Study Area from 2000 to 2010. Only
656 total households are expected to be added between 2010 and 2015. Since 2010, total households are not increasing
at the same rate as in 2000. What implications does this mean for the Study Area? Are more adults living in shared
households? Are there more multigenerational households? Richland and Lafayette County are expected to decrease in
total households by 2015. Grant County will grow, but only by .02 percent and Green County will have the highest
change with a 1.86 percent increase in households.
Table 10 - County, Projected Change in Total Households
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Wisconsin
United States
2000
2010
2015
18,465
13,212
8,764
6,211
7,118
53,770
2,084,544
105.5 million
19,109
14,820
9,624
6,424
7,354
57,331
2,279,768
116.7 million
19,115
15,383
9,843
6,377
7,269
57,987
2,347,919
118.6 million
Percent Change
2000 - 2015
3.52%
16.43%
12.31%
2.67%
2.12%
7.84%
12.42%
12.63%
*Source: 2000 Census, 2010 Census, ESRI 2015 Projections
Occupancy Status
Housing tenure refers to the conditions under which property is occupied. The two basic forms of occupancy is renteroccupied and owner-occupied. However, not all housing units in a community are occupied. Occupancy status is
analyzed by looking at the percentage of occupied units to vacant units, and is another indicator of economic vitality in
the Study Area. However, "vacancy" refers not only to empty houses available for sale, but also those available for rent,
rented but not occupied, sold but not occupied or units seasonal use, recreational or occasional use, units temporarily
occupied by people who live elsewhere, provided that the place of residence is not offered for rent or for sale, and
additional homes used farm for seasonal farm labor.
Figures 15 through 19 display the percentage of occupied and vacant homes in the Study Area.15 The region average is
89.4 percent. Figure 15 and 16 displays the occupancy status for the five counties and county seats, respectively.
Considering Richland County and Richland Center have low occupancy rates of the county and county seats, detailing the
exact type of vacancy is necessary. After reviewing the types of vacancy, it can be seen that Richland County’s low
occupancy rate is due to a disproportionately high 9.8 percent seasonal use (see Table 11). Units for rent or sale are
under 2 percent each. Excluding the seasonal use percentage, Richland County would have a 92.8 percent occupied
status. Woodman exhibits a low occupancy status also. There are a total of 112 housing units in Woodman, 77 are
occupied, and 35 are vacant. However, 32 of the 35 vacant homes are for seasonal use.
Four additional cities have significantly high unoccupied rates; Cazenovia, Woodman, Muscoda, and Avoca. Cazenovia’s
high unoccupied rate could be attributed to Richland County’s high seasonal use. Additional research is necessary to
understand the underlying condition in Woodman, Muscoda, and Avoca.
http://www.census.gov/prod/2012pubs/p60-242.pdf
Due to large occupancy rates, the charts only display from 75 to 100 percent for all figures except for Wisconsin River Corridor, which
displays 65 to 100 percent. Charts were created in this manner to allow greater visibility of data.
14
15
18
Figure 15 - County, Occupancy Status
County
County Occupancy Status
89.9%
93.8%
89.1%
91.4%
82.9%
89.9%
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
Percent of Occupied and Vacant Homes
Occupied %
Vacant %
Figure 16 - County Seat, Occupancy Status
County Seat Occupancy Status
91.9%
92.8%
91.9%
94.3%
90.4%
92.7%
Municipality
Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Total
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
Occupied %
Vacant %
Figure 17 - Communities of Higher Education, Occupancy Status
Municipality
Communities of Higher Education Occupancy Status
92%
Fennimore
94.9%
Platteville
94.2%
Total
75.0%
80.0%
85.0%
90.0%
95.0%
Occupied %
19
Vacant %
100.0%
Figure 18 - Richland County Cities, Occupancy Status
Municipality
Richland County Cities Occupancy Status
83.6%
Cazenovia
88.7%
Lone Rock
91.5%
Viola
88.4%
Total
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
Occupied %
Vacant %
Figure 19 - Wisconsin River Corridor, Occupancy Status
Wisconsin River Corridor Occupancy Status
87.8%
Arena
75.2%
Municipality
Avoca
88.5%
91.4%
82.3%
Blue River
Boscobel
Muscoda
Woodman
68.8%
86.6%
Total
65.0%
70.0%
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
Occupied %
Vacant %
Table 11 - Richland County & Richland Center, Type of Vacant Units
Total Housing Units
Total Vacant
For rent
Rented, not occupied
For sale only
Sold, not occupied
For seasonal, recreational,
or occasional use
For migrant workers
Other Vacant
Richland
County
8,868
1,519
172
6
142
19
% of Housing
Units
17%
1.9%
0.1%
1.6%
0.2%
Richland
Center
2,613
252
115
5
47
5
% of Housing
Units
9.6%
4.4%
0.2%
1.8%
0.2%
872
9.8%
21
0.8%
3
305
0.0%
3%
0
59
0.0%
2.3%
20
Foreclosures
Housing foreclosures impact communities in several ways: by causing declines in property values and physical
deterioration, health and safety issues, and an increase in displaced households. There are other impacts such as
increased vandalism and crime, but are more prevalent in Metro areas. “Research in Chicago found that the cost of a
single foreclosed home to a municipality can range from a few dollars up to as much as $34,000.”16
According to the UW-Extension Center for Community and Economic Development, which tracks foreclosures in
Wisconsin, the region had 474 foreclosures in 2011 up from 328 in 2006. Figure 20 displays the number of foreclosure
cases for each county from 2006 to 2011 and region average, which is the most current foreclosure data. For most of the
counties, 2010 seen an exceptionally high number of foreclosures. One noticeable trend is foreclosures are not dropping
in Grant as in the other counties. Two reasons given for foreclosures to continually rise include an eroding labor market
and available programs to assist homeowners with their mortgage. These two examples require further research in each
county, Grant County in particular.
Figure 20 - County, Number of Foreclosure Cases
Number of Foreclosure Cases
Total Number
200
150
2006
100
2007
2008
50
2009
2010
0
Grant
Green
Iowa
Lafayette
Richland
Region
Average
2011
County
*Source: UW Extension Center for Community & Economic Development
Table 12 details the market trends with the current median list price and homes for sale by county as of January 2014.
The most current county foreclosures numbers are in Figure 20. Table 13 through 16 details the market trends, which
include median list price, number of foreclosures, and number of homes for sale.17
Table 12 - County, Current Market Trends
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Average
Wisconsin
Median List Price
$112,000.00
$138,950.00
$144,900.00
$124,900.00
$99,900.00
$124,130.00
$139,900.00
Homes for Sale
226
231
216
97
94
172.8
30,688
*Source: RealtyTrac
UW – Extension Cooperative Extension Wisconsin Housing Profile, http://learningstore.uwex.edu/Wisconsin-Housing-ProfilesP1582.aspx
17 Foreclosures, median list price and number of homes for sale were homes listed when accessed in January 2014.
16
21
Table 13 - County Seat, Current Market Trends
City
Median List Price
Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Total/Average
$122,436.36
$119,000.00
$142,450.00
$128,400.00
$109,900.00
$124,437.27
Number of
Foreclosures
1
6
12
6
83
108
Homes for Sale
29
68
30
84
55
266
*Source: RealtyTrac
Table 14 - Communities of Higher Education, Current Market Trends
City
Median List Price
Fennimore
Platteville
Total/Average
$89,900.00
$99,900.00
$94,900.00
Number of
Foreclosures
19
Homes for Sale
8
18
45
37
53
*Source: RealtyTrac
Table 15 - Richland County Cities, Current Market Trends
City
Median List Price
Cazenovia
Lone Rock
Viola
Total/Average
$86,860.42
$85,800.00
$119,657.50
$97,439.31
Number of
Foreclosures
18
38
10
66
Homes for Sale
14
21
4
39
*Source: RealtyTrac
Table 16 - Wisconsin River Corridor, Current Market Trends
City
Median List Price
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Total/Average
$261,630.77
$76,640.00
$82,175.00
$111,228.00
$88,560.00
$110,800.00
$121,838.96
Number of
Foreclosures
2
0
17
28
17
2
66
Homes for Sale
13
5
4
25
5
3
55
*Source: RealtyTrac
Owning versus Renting
According to the Housing Assistance Council (HAC), there is a shortage of rental options in rural communities as defined
by the U.S. Census, and as demographic shifts occur there is likely to be a growing demand for rental housing.
Additionally, rural renters often have much lower incomes than rural homeowners, with nearly one-third of rural and
small town renters living below the poverty level, compared to just 7 percent of rural homeowners. Racial and ethnic
minorities are more likely to rent than non-white Hispanics in non-metro counties.18
18
22
National Low Income Housing Coalition, http://nlihc.org/article/affordable-rental-housing-rural-america
Tables 17 through 21 display the percentages of owners and renters in the Study Area. The counties' overall percent of
renters ranges between 20 and 22 percent, below the national average of 28.4 percent19. However, Grant County is the
outlier with 26.3 percent, which may be due to the communities of higher education. As Students and younger adults
are more prone to rent than to buy a home. Students plan to temporarily plan in these communities and it is not realistic
to purchase a home. This is evidenced by the high number of renters in Platteville, which is considerably higher than any
other community in the Study Area.
Table 17 - County, Owning versus renting
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Wisconsin
United States
Total
population in
occupied
housing units:
47,311
36,437
23,473
16,716
17,685
141,622
5,536,772
300,758,215
Owned
Owned
with a
Renter
free and
mortgage
occupied
clear
or a loan
23,766
11,104
12,441
21,925
6,659
7,853
13,902
4,687
4,884
9,431
3,870
3,415
9,671
4,157
3,857
78,695
30,477
32,450
3,044,716
919,680
1,572,376
153,443,527 47,834,966 99,479,722
Owner - with
& without a
mortgage
Renter
73.7%
78.4%
79.2%
79.6%
78.2%
77.1%
71.6%
66.9%
26.3%
21.6%
20.8%
20.4%
21.8%
22.9%
28.4%
33.1%
Table 18 - County Seat, Owning versus renting
County Seat
Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Total
Total
population in
occupied
housing units:
2,353
4,622
3,772
10,660
5,007
26,414
Owned
with a
mortgage
or a loan
1,103
2,563
1,991
5,171
2,332
13,160
Owned
free
and
clear
457
684
826
2,022
860
4,849
Renter
occupied
Owner - with
& without a
mortgage
Renter
793
1,375
955
3,467
1,815
8,405
66.3%
70.3%
74.7%
67.5%
63.8%
68.2%
33.7%
29.7%
25.3%
32.5%
36.2%
31.8%
Renter
occupied
Owner - with
& without a
mortgage
Renter
685
4,469
5,154
71.8%
47.2%
52.7%
28.2%
52.8%
47.3%
Table 19 - Communities of Higher Education, Owning versus renting
City
Fennimore
Platteville
Total
Total
population in
occupied
housing units:
2,433
Owned
with a
mortgage
or a loan
1,211
Owned
free
and
clear
537
8,471
2,851
1,151
10,904
4,062
1,688
19
23
National Low Income Housing Coalition, http://nlihc.org/article/affordable-rental-housing-rural-america
Table 20 - Richland County Cities, Owning versus renting
City
Cazenovia
Lone Rock
Viola
Total
Total
population in
occupied
housing units:
311
888
477
1,676
Owned
with a
mortgage
or a loan
152
472
262
886
Owned
free
and
clear
74
163
97
334
Renter
occupied
Owner - with
& without a
mortgage
Renter
85
253
118
456
72.7%
71.5%
75.3%
72.8%
27.3%
28.5%
24.7%
27.2%
Renter
occupied
Owner - with
& without a
mortgage
Renter
230
201
82
890
48
31
1482
84.2%
68.2%
81.1%
67.7%
83.8%
83.2%
74.3%
15.8%
31.8%
18.9%
32.3%
16.2%
16.8%
25.7%
Table 21 - Wisconsin River Corridor, Owning versus renting
City
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Total
Total
population in
occupied
housing units:
1,456
632
434
2,753
297
185
5,757
Owned
with a
mortgage
or a loan
905
259
231
1,367
158
106
3,026
Owned
free
and
clear
321
172
121
496
91
48
1,249
Housing Conditions
Age of Housing Stock
Older housing stock in rural areas may not have basic amenities or up-to-date standards, and therefore require
restoration or higher maintenance costs. Tables 22 through 26 list the percent of housing stock by construction period.20
The definitive era for construction of the Study Area's housing stock is before 1949, with a few exceptions. In Arena,
Muscoda, and Platteville the majority of structures were built between 1950 and 1979. A majority of Lone Rock homes
were built after 1980.
Table 22 - County, Percent of Housing Stock by Construction Period
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
Wisconsin
United States
Built Prior to 1949
40.9%
42.0%
44.3%
52.6%
45.6%
43.7%
31.1%
22.3%
Built 1950 to 1979
39.0%
33.5%
26.8%
31.7%
31.4%
33.8%
41.4%
44.9%
Built 1980 - 2000
20.1%
24.5%
29.0%
15.7%
23.0%
22.5%
27.6%
32.8%
*Source: Census 2000
Table 23 - County Seat, Percent of Housing Stock by Construction Period
20
24
The data is from the 2000 Census because the 2010 Census does not contain updated year structure built.
County Seat
Darlington
Dodgeville
Lancaster
Monroe
Richland Center
Total
Built Prior to 1949
52.4%
41.3%
50.9%
39.8%
30.6%
20.1%
Built 1950 to 1979
37.0%
32.7%
32.9%
39.6%
40.3%
37.0%
Built 1980 - 2000
10.6%
26.0%
16.1%
20.5%
29.1%
42.9%
Table 24 - Communities of Higher Education, Percent of Housing Stock by Construction Period
City
Fennimore
Platteville
Total
Built Prior to 1949
40.5%
Built 1950 to 1979
37.3%
Built 1980 - 2000
22.2%
27.0%
46.9%
26.0%
36.4%
43.7%
19.9%
Table 25 - Richland County Cities, Percent of Housing Stock by Construction Period
City
Cazenovia
Lone Rock
Viola
Total
Built Prior to 1949
61.9%
36.6%
68.0%
49.8%
Built 1950 to 1979
16.3%
25.1%
24.6%
23.2%
Built 1980 - 2000
21.9%
38.3%
7.4%
27.0%
Table 26 - Wisconsin River Corridor, Percent of Housing Stock by Construction Period
City
Arena
Avoca
Blue River
Boscobel
Muscoda
Woodman
Total
Built Prior to 1949
29.1%
41.5%
52.8%
39.2%
29.4%
55.0%
38.1%
25
Built 1950 to 1979
38.5%
25.2%
25.9%
35.8%
37.9%
26.3
33.5%
Built 1980 – 2000
32.4%
33.2%
21.3%
25.0%
32.7%
18.8%
28.4%
New Home Development Trends
Figure 21 shows the number of new home construction since 2009 for the unincorporated areas of each county. New
home data is not available for the years 2010 and 2013 for Green County. This data demonstrates the trends in new
construction. Lafayette issued more permits in 2013 than in the last 4 years. Iowa’s number of permits issued have
declined since 2009. Richland County permits have not fluctuated like the rest of the Study Area.
Figure 21 - County, Number of New Home Permits
Number of New Home Permits
Total Number
50
40
30
20
10
0
Grant
Green
2009
Iowa
2010
2011
Lafayette
2012
Richland
2013
*Source: County Zoning Departments
Elevated Lead Blood Levels among Children 6 and Under
Lead poisoning is a concern in older homes, mainly homes built before 1978 contain some lead-based paint. Lead
poisoning is a concern for both children and adults because breathing or eating anything that contains lead can cause
serious health problems. Young children can experience learning, behavior, and health problems. Lead poisoning is
preventable by testing the home for lead paint, removal of exterior and interior lead paint, removing carpet that may be
contaminated, and additional measures. Considering the number of older homes in the Study Area, lead paint is a
concern.
Table 27 displays the elevated blood level of lead measure, which represents the percentage of lead tests on children
under age 6 that tested positive for lead poisoning in the Study Area.21 Outside of the cities of Milwaukee and Racine, all
children under age 6 attending a well-child clinic are screened to determine if they are at high risk of exposure to lead
poisoning; children are tested only if they are considered at high risk. The table shows the only data collected on
elevated levels of lead in blood in children 6 and under, and is not considered a random sample.22 However, the
numbers are useful to review the prevalence of elevated blood lead levels in each county. The number screened is not
consistent for each county.
Table 27 - County, Prevalence of Elevated Blood Levels
County
Grant
Green
Iowa
Lafayette
Richland
Study Area Total
# Screened
726
507
236
209
280
1,958
# Tested Positive
7
6
3
3
5
24
% Test Positive
.96%
1.18%
1.27%
1.44%
1.79%
1.23%
*Source: County Health Rankings
21
22
26
This measure is not based on a complete or random sample and should be interpreted with caution.
County Health Rankings - http://www.countyhealthrankings.org/
Housing Affordability
Table 28 examines the housing affordability gap for the five county seats based on data specific to each county and
specific indicators using the following bullet points as assumptions.
 An affordable home should not cost more than 2.5 times the annual household income.
 Area Household Median Income (AMI)23
 Moderate income is suggested to be between 60 and 80 percent of the Area Median Income
 Median list price24 & median annual rent25
Using Lancaster as an example
Owner Occupied
 County Area Household Median Income (AMI), = $41,311
 60% of the AMI = $24,787
 Median list price = $142,450
 Affordable mortgage would be 2.5 times $24,787 = $61,968
 Subtract $61,968 from the median list price $142,450 = $80,483.
 The same methodology is used for the 80% of the AMI = $33,049
Renter Occupied
 The same methodology is used for the renter occupied affordability gap.
 The average rent for each county multiplied by 12 to arrive at the annual rent.
After reviewing the housing affordability gap table several suggestions begin to form. First, more housing for moderate
income households would benefit each county seat. The moderate income households are at 80 percent of the area
household median income. For Lancaster, more housing priced at $82,622 would be beneficial. Darlington has the most
affordable rent out of the Study Area, while Dodgeville has the most affordable owner-occupied housing. Second,
assisting borrowers to meet the affordability gap by developing programs that educate borrowers and/or aid with down
payments or saving for a down payment.
Table 28 - Housing Affordability Gap
Area Household Median Income
Area Household Median Income (60%)
Median List Price
Affordable Mortgage
Affordability Gap - Owner Occupied
Area Household Median Income (80%)
Median List Price
Affordable Mortgage
Affordability Gap - Owner Occupied
Median Annual Rent
Affordable Rent
Affordability Gap - Renter Occupied
Darlington
$42,333
$25,400
$122,400
$63,500
($58,900)
$33,866
$122,400
$84,666
($37,734)
$5,748
$7,619.94
$1,871.94
Dodgeville
$51,107
$30,664
$119,000
$76,660
($42,340)
$40,886
$119,000
$102,214
($16,786)
$7,776
$9,199.26
$1,423.26
Lancaster
$41,311
$24,787
$142,450
$61,968
($80,483)
$33,049
$142,450
$82,622
($59,828)
$6,108
$7,435.98
$1,327.98
Monroe
$41,197
$24,718
$128,400
$61,795
($66,605)
$32,958
$128,400
$82,394
($46,006)
$7,236
$7,415.46
$179.46
Richland Center
$33,750
$20,250
$109,900
$50,625
($59,275)
$27,000
$109,900
$67,500
($42,400)
$6,312
$6,075.00
($237.00)
**Usually the median sale price is used, however only the median list price was available and used for this calculation.
23
Area Median Income (AMI) is the dollar amount where half the population earns less and half earns more
RealtyTrac, http://www.realtytrac.com/home/index2, accessed January 2014.
25 Areavibes.com was used to determine the housing score, a combination of factors were used including: median home values in relation to
median household income, as well as median rent values in relation to median household income for renter occupied dwellings. Also included were
appreciation rates for average home prices for the previous 10 years. The score is then calculated based on comparisons to both state and national
averages.
24
27
As stated previously, financial experts recommend that housing should consume 30 percent or less of a household’s
monthly income. Table 29 used the recommended 30 percent, $50,000 median household income, and four different
percentages of median income to provide an illustration for affordable mortgage payments. A $50,000 median
household income was used considering the regional average is $48,398 and to calculate with a round number.
Table 29 - Sample Household Incomes and Affordable Housing Payments
Percentage of Median
Household Income
30% Toward Housing
Monthly Amount
60%
$30,000
$9,000
$750
80%
$40,000
$12,000
$1,000
100%
$50,000
$15,000
$1,250
120%
$60,000
$18,000
$1,500
Fair Market Rents - By County
The Fair Market Rents (FMR) is a concept used by the Housing and Urban Development (HUD) to determine how much
rent is covered by the government for those tenants who are part of Section 8, as well as other governmental
institutions. HUD publishes FMRs and Income Limits for how much program administrators will subsidize housing units,
and the maximum incomes that tenants may not exceed in order to qualify for subsidized housing on an annual basis.
FMR is defined as the dollar amount below which 40 percent of the standard quality rental housing units are rented.
They are calculated for each county on an annual basis using a combination of Census and American Community Survey
data such as local economic conditions and housing demand. Table 30 shows the 2014 FMRs for each county.26 Green
and Lafayette County have the lowest fair market rents.
Table 30 - County, Fair Market Rents
County
Efficiency
Grant
$437
Green
$404
Iowa
$522
Lafayette
$404
Richland
$419
1 Bedroom
$484
$494
$560
$488
$468
2 Bedrooms
$637
$637
$757
$637
$596
3 Bedrooms
$810
$871
$980
$867
$764
4 Bedrooms
$987
$1,128
$1,012
$931
$789
*Source: Huduser.org
Wisconsin Rent Guidelines
There are publicly funded programs available to sponsor the development of affordable rental housing. The Low Income
Housing Tax Credit (LIHTC) was enacted as part of the Tax Reform Act of 1986 in order to encourage production of
affordable multi-family rental housing for low-to-moderate income households. Tax credits make development of
affordable units feasible by increasing investor/owner down payment in a housing development by lowering mortgage
and financing costs, therefore allowing lower rents.
In Wisconsin, the Tax Credit Program is managed by the Wisconsin Housing and Economic Development Authority
(WHEDA), which annually sets guidelines for determining rent limits based on a project’s target population by household
income. Guidelines are based on percentage of county median income (CMI). The WHEDA LIHTC for each county are listed
in Appendix B.27
26
HudUser http://www.huduser.org/portal/datasets/fmr/fmrs/FY2014_code/select_Geography.odn
WHEDA http://www.wheda.com/root/uploadedFiles/Website/Business_Partners/Property_Managers/
Other_Reports/14_Standard%20MTSP.pdf
27
28
Conclusion
Like the state and the country, the five county Study Area experienced abnormally high levels of unemployment and
property vacancy coming out of the recession. However, over the past two years the region’s unemployment rate has
been dropping and the region has been posting consistent job gains. A majority of these gains have come in the
education and health, trade, transportation and utilities, and the manufacturing sectors - a sector identified as a high
growth industry in the Study Area. Below is a summary of the strengths and weaknesses in the Study Area.
Counties
Grant:

Strengths
o Highest population and population projections to grow over the next couple decades
o Highest number of household projections
Concerns
o Second lowest per capita personal income & median household income
o Lowest number of owner-occupied housing
o Highest number of female-headed householders below the poverty level
o Second highest number of foreclosures
o Second highest number of homes for sale
o Second highest number of individuals aged 65 and older

Green:

Strengths
o Highest number of occupied housing
o Second highest population and second highest population projection over the next couple decades
Concerns
o Lowest per capita personal income
o Highest number of unemployment rates
o Highest number of foreclosures
o Highest number of homes for sale

Iowa:


Strengths
o Lowest number of individuals aged 65 and older
o Lowest median list price
Concerns
o Second lowest number of occupied housing
o Second highest unemployment rate
Lafayette:


29
Strengths
o Lowest unemployment rate
o Lowest number of females below poverty
Concerns
o Lowest population, lowest population projections and household projections
o Highest number of housing stock built prior to 1949
Richland:

Concerns
o Lowest median household income
o Lowest number of occupied housing
o Highest median list price
o Second lowest number of population and households
o Highest number of individuals aged 65 and older
o Second highest number of housing stock built prior to 1949
County Seats
Darlington:

Strengths
o Lowest number of homes for sale
o Second most affordable housing at 80 percent of area median income
 Concerns
o Lowest population numbers
o Lowest population projections
o Second lowest number of owner-occupied housing
o Highest number of housing stock built prior to 1949
Dodgeville:

Strengths
o Smallest housing affordability gap
o Lowest number of individuals aged 65 and older
o Second highest number of population numbers
o Second highest number of occupied housing
o Second highest number owner-occupied housing
o Second lowest number of foreclosures
o Second lowest number of housing stock built prior to 1949
Lancaster:


Strengths
o Highest number of owner-occupied housing
Concerns
o Second lowest population number
o Second lowest population projections
o Second highest number of vacant properties
o Biggest housing affordability gap at 60 and 80 percent of area median income
Monroe:

30
Strengths
o Highest population
o Highest number of population projections
o Highest number of occupied housing
o Lowest number of homes for sale
Richland Center:


Strengths
o Second smallest housing affordability gap
o Second highest number of population
o Lowest number homes built prior to 1949
Concerns
o Lowest number of occupied housing
o Lowest number of owner-occupied housing
o Highest amount of individuals aged 65 and older
o The only city to have a renter-affordability gap
Communities of Higher Education


Strengths
o Platteville’s population will grow by 17%
o Platteville has a low population of residents 65 years and older
o Both cities have an occupied status above 92%
Concerns
o Will lose population
o Fennimore has a low number of homes for sale
o Platteville has 47% owner-occupied rate
Richland County Cities


Strengths
o Viola will gain population
Concerns
o Cazenovia will lose population
o Cazenovia has a high number of residents 65 years and older
o All three cities have an occupied status below 92%
o Viola only has 7% of housing stock since 1980
Wisconsin River Corridor


31
Strengths
o Arena is expected to gain population
o Most residents fall into the 35 to 64 age group for all six cities
Concerns
o Muscoda is expected to lose population
o The occupancy status ranges from 68% to 91%
o Boscobel City has a high number of foreclosures
o Avoca has 68% owner-occupied rate
o On average homes were built prior to 1949
Housing Recommendations
This study provides direction for identifying housing types likely to be needed in the future and as a basis for developing
appropriate strategies related to housing markets, home ownership, and affordability challenges. This study allows for
agencies to understand the current conditions in the Study Area and focus their programs for each county or
municipality based on the local data and their program goals. A program implementation table is presented first, then a
series of housing concerns that emerged during the study and which should be addressed first are highlighted below.
Agencies could utilize the table below as a foundation for next steps of program implementation within various
jurisdictions. The table highlights selected jurisdictions within the Study Area where standard housing programs could
occur based on data from this study. Foreclosure intervention highlights areas that had high foreclosures or increasing
foreclosure rates, such as Grant County. The impact of homebuyer education is thought to reduce mortgage default
rates, but could be developed to encourage renters to move towards homeownership. For that reason, the jurisdictions
highlighted under the homebuyer education had higher percentage of renters than homeowners. The jurisdictions
highlighted under the home improvement loan program were selected based on percentage of houses built prior to
1949. This table is a starting point and should be discussed further within specific agencies.
Table 31 - Housing Programs and Jurisdictions Implementation
Housing
Programs
Jurisdiction
Foreclosure
Intervention
Grant County
Green County
Richland Center
Lone Rock
Boscobel
Homebuyer Education
Green County
Lafayette County
Darlington
Richland Center
Lone Rock
Boscobel
Home Improvement
Loan Program
Lafayette County
Darlington
Lancaster
Fennimore
Cazenovia
Viola
Blue River
Woodman
Senior Housing
Richland Center
Fennimore
Viola
The first concern is to address the owner-occupied housing affordability gap evident in the County Seats. The housing
affordability gap is considerably extensive, the gap ranges from $42,000 to $80,000 at 60 percent area median income
(AMI), with Lancaster at the higher end of the range. The average income disparity between the county seats is roughly
$17,000, Richland Center AMI is $33,750. One approach would be more housing at the “mortgage” price, which may be
difficult to build houses at that price. Another approach is recognizing the buying capacity of the residents and develop
programs that would educate borrowers and/or aid with down payments or saving for a down payment.
Education programs would be a means to help borrowers succeed as homeowners and to remedy problems that impede
borrowers’ abilities to pay their mortgages. Homeownership education and counseling gives consumers more
information or guidance that will improve their decision making when it comes to purchasing a home, managing their
finances, and handling obstacles that may limit their ability to make monthly mortgage payments.
The second concern is the type of housing crucial for the various jurisdictions. There is opportunity to create more
affordable workforce housing for individuals, possibly renters who are looking for housing near their workplace at their
income levels. New development or more workforce housing options are needed in Dodgeville and Monroe due to
increased population projections. The new development must include units that will be accessible to those households
earning at or below the area median income. The communities of higher education may need more rentals options due
to high percentage of renters. Multi-family homes are essential to creating more diverse housing options, considering
single-family homes make up 81 percent of all housing types in the Study Area.
32
The third concern is the 65 and older population in Richland Center, Fennimore, and Viola, since this age group
comprised more than 20 percent of the individual city’s population. A next step would be an analysis of available senior
housing compared to senior population projections. These areas experiencing a growing elderly population need to
ensure community support and assistance is available, including identification of land and parcels appropriate for
development of senior living facilities.
The fourth concern is population projections and availability of housing units. Green County population is expecting to
increase by 14 percent by the year 2030. Municipalities with high population projections include: Dodgeville, Monroe,
and Platteville. In addition, Green County, Monroe, and Platteville have a small percentage of vacant housing units.
Housing demand will need further research in these areas to accurately forecast the amount and type of new homes
needed. Net new households, net change in vacant units and second homes, and net removals from the existing stock
are the three components that need to be researched further in these areas.
Finally, within the municipalities, officials should review public subsidies available for low income housing and utilize
them to interest developers. The municipalities may also want to look closely at current zoning requirements in order to
identify impediments to development. Southwestern Wisconsin communities must realize the local demographic shift to
prepare and accommodate for the changing housing markets. The emerging housing needs include: senior-assisted
housing, rental housing, more low- to moderate income housing, and multi-family homes. Each county and municipality
will experience different housing needs, which will determine new policies and programs offered.
33
References
1. 2000- 2011 annual foreclosure data by county. (02, May 12). Retrieved from
http://fyi.uwex.edu/housing/2012/05/02/2000-2011-annual-foreclosure-data-by-county/
2. Affordable Rental Housing in Rural America. (26, April 13). Retrieved from http://nlihc.org/article/affordablerental-housing-rural-america
3. AreaVibes, Apartment locator. Retrieved from Areavibes.com
4. County Health Rankings & Roadmaps. (n.d.). Retrieved from http://www.countyhealthrankings.org/
5. ESRI 2015 Projections (ESRI)
6. Final FY 2014 fair market rent documentation system. (n.d.). Retrieved from
http://www.huduser.org/portal/datasets/fmr/fmrs/docsys.html&data=fmr14
7. Hobbs, Frank. United States. U.S. Census Bureau. Examining American Household Composition: 1990 and 2000.
Washington, D.C.: U.S. Government Printing Office, 2005. Web. <http://www.census.gov/prod/2005pubs/censr24.pdf>.
8. Housing affordability. (n.d.). Retrieved from
https://www.nahb.org/page.aspx/category/sectionID=1292/print=true
9. Kamp, K., & Ghena, J. Wisconsin Partnership for Housing Development, (2011). Market Study for the City of
Richland center and Richland County
10. Local area personal income. (n.d.). Retrieved from http://www.bea.gov/iTable/iTable.cfm?ReqID=70&step=1
11. Mykyta, Laryssa, and Suzanne Mccartney. United States. U.S. Census Bureau. Sharing a Household: Household
Composition and Economic Well-Being: 2007 - 2010. Washington, D.C.:, 2012. Web.
<http://www.census.gov/prod/2012pubs/p60-242.pdf>.
12. New report says millions of women at risk of falling into poverty, economic ruin. (12, January 14). Retrieved from
http://usnews.nbcnews.com/_news/2014/01/12/22254801-new-report-says-millions-of-women-at-risk-offalling-into-poverty-economic-ruin?lite
13. Population & migration. (13, May 13). Retrieved from http://www.ers.usda.gov/topics/rural-economypopulation/population-migration.aspx
14. RealtyTrac, Local level foreclosure resource. Retrieved from
http://www.realtytrac.com/statsandtrends/wi/greencounty/monroe/?address=Monroe%2C%20WI%20&parsed=1&ct=monroe&cn=green%20county&stc=wi
15. U.S. Census Bureau, American Community Survey, 2006 - 2010, Selected Population Tables
16. U.S. Census Bureau; American Community Survey, 2008 - 2012, Selected Economic Characteristics; using
American Factfinder
17. U.S. Census Bureau, U.S. Summary: 2000, Census US Profile, Web, Washington, D.C.
18. U.S. Census Bureau, U.S. Summary: 2010, Census US Profile, Web, Washington, D.C.
19. Wisconsin Department of Workforce Development, (2012). Local area unemployment statistics. Retrieved from
website: http://worknet.wisconsin.gov/worknet/dalaus.aspx?menuselection=da
20. Wisconsin Department of Workforce Development, (2012).County summary files. Retrieved from website:
http://worknet.wisconsin.gov/worknet/downloads.aspx?menuselection=da&pgm=County Profile
21. "Wisconsin MLS Listings, Wisconsin Homes." Wisconsin MLS Listings, Wisconsin Homes. N.p., n.d. Web. 21 Feb.
2014.
22. Wisconsin Population & Household projections. (n.d.). Retrieved from
http://www.doa.state.wi.us/divisions/intergovernmental-relations/demographic-services-center/projections
23. Wisconsin standard multifamily tax subsidy project estimated maximum income and rent limits. (18, December
13). Retrieved from
http://www.wheda.com/root/uploadedFiles/Website/Business_Partners/Property_Managers/Other_Reports/1
4_Standard MTSP.pdf
34
Appendix A Top Employment Sectors
The following tables list the Top Employment Sectors with number of jobs, the top employers and number of employees
as mentioned in section 1.2.1 Workforce Development Data.
Grant County
Sector
Education Services
Food Services & Drinking Places
Executive, Legislative, and General Government
Nursing and Residential Care Facilities
Top Employers
University of Wisconsin - Platteville
County of Grant
Southwest Health Center, Inc.
Milprint
Walmart
Nu-Pak, Inc.
Southwest Wisconsin Vocational Technical
Institute
WI Secure
Platteville Public School
School District of Boscobel Area
Jobs
2,454
1,114
991
717
# of Employees
500-999
500-999
250-499
250-499
250-499
250-499
100-249
100-249
100-249
100-249
Green County
Sector
Nonstore Retailers
Educational Services
Food Manufacturing
Data Processing, Hosting, and related
services
Top Employers
Monroe Clinic, Inc.
Colony & Brands, Inc.
School District of Monroe
S C Data Center, Inc.
County of Green
Monroe Truck Equipment, Inc.
Kuhn North America, Inc.
Ipacesetters, LLC
Walmart
LSI, Inc. - New Glarus
35
Jobs
1,048
1,060
967
suppressed
# of Employees
500-999
500-999
500-999
500-999
250-499
250-499
250-499
250-499
100-249
100-249
Iowa County
Sector
Nonstore Retailers
Machinery Manufacturing
Nursing and Residential Care Facilities
Top Employers
Lands' End, Inc.
Cummins Emissions Solutions Inc.
Upland Hills Health, Inc.
County of Iowa
Walmart
Dodgeville School District
Vivid, Inc.
Mineral Point Public School
American Players Theatre
Iowa-Grant School District
Jobs
3,394
687
550
402
# of Employees
1,000 or more
500-999
250-499
250-499
100-249
100-250
100-251
100-252
100-253
100-254
Lafayette County
Sector
Food Manufacturing
Executive, Legislative, and General Government
Merchant Wholesalers, Nondurable goods
Top Employers
County of Lafayette
Lactalis USA, Inc.
Darlington Community School District
Mexican Cheese Producers, Inc.
Betin, Inc.
Shullsburg Creamery II, LLC
School District of Black Hawk
Merkle-Korff Industries, Inc.
School District of Argyle
Shullsburg Public School
36
Jobs
452
suppressed
343
228
# of Employees
250-499
100-249
100-249
100-249
50-99
50-100
50-101
50-102
50-103
50-104
Richland County
Sector
Agriculture, forestry, fishing, and hunting
Manufacturing
Government
Retail
Top Employers
Rockwell Automation, Inc.
County of Richland
Schreiber Foods, Inc.
The Richland Hospital, Inc.
Richland School District
Walmart
S & S Cycle, Inc.
Morningstar Foods, LLC
Foremost Farms USA Co-Op
Schmitt Woodlands Hills, Inc.
37
Jobs
1,754
1,507
1,169
1,138
# of Employees
250-499
250-500
250-501
250-502
250-503
250-504
100-249
100-249
100-249
100-249
Appendix B Rent Guidelines
The following tables list the Wisconsin Housing and Economic Development Authority (WHEDA) Low-Income Housing
Tax Credit (LIHTC) rent guidelines for each county as mentioned in section 2.3.2. WHEDA uses the County Median
Income (CMI) to determine the rent guidelines.
Grant
30% CMI
40% CMI
50% CMI
60% CMI
Efficiency
$309
$413
$516
$619
Green
30% CMI
40% CMI
50% CMI
60% CMI
Efficiency
$353
$471
$588
$706
Iowa
30% CMI
40% CMI
50% CMI
60% CMI
38
Efficiency
$378
$504
$630
$756
Lafayette
30% CMI
40% CMI
50% CMI
60% CMI
Efficiency
$325
$434
$542
$651
Richland
30% CMI
40% CMI
50% CMI
60% CMI
Efficiency
$309
$413
$516
$619
1 Bedroom
$331
$442
$553
$663
1 Bedroom
$378
$504
$630
$756
1 Bedroom
$405
$540
$675
$810
1 Bedroom
$348
$465
$581
$697
1 Bedroom
$331
$442
$553
$663
2 Bedroom
$398
$531
$663
$796
2 Bedroom
$453
$605
$756
$907
2 Bedroom
$486
$648
$810
$972
3 Bedroom
$459
$613
$766
$919
3 Bedroom
$524
$699
$873
$1,048
4 Bedroom
$513
$684
$855
$1,026
4 Bedroom
$585
$780
$975
$1,170
3 Bedroom
$561
$748
$935
$1,122
4 Bedroom
$626
$835
$1,043
$1,252
2 Bedroom
$418
$558
$697
$837
3 Bedroom
$483
$645
$806
$967
4 Bedroom
$540
$720
$900
$1,080
2 Bedroom
$398
$531
$663
$796
3 Bedroom
$459
$613
$766
$919
4 Bedroom
$513
$684
$855
$1,026
39

Southwestern Wisconsin Regional Housing Study

Transcription

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