Residents Financial Survey

Residents Financial SurveyNorma B. Coe and April Yanyuan Wu

Center for Retirement Research

at Boston College

Residents Financial Survey

The contents of this publication summarize research findings from a survey

conducted in 2011 by the Center for Retirement Research at Boston College

performed pursuant to a grant from the American Seniors Housing Association,

National Investment Center for the Seniors Housing & Care Industry, and the

Assisted Living Federation of America.

Table of Contents

Article 1:

Residents in Seniors Housing and Care Communities: Overview of the Residents Financial

Survey

Article 2:

Financial Well-Being of Residents in Seniors Housing and Care Communities

Article 3:

Costs and Concerns Among Residents in Seniors Housing and Communities

Article 4:

Geographic Mobility Among Residents in Seniors Housing and Care Communities

Residents Financial Survey Summary The Seniors Housing Residents Financial Survey was designed and conducted by the Center for Retirement Research at Boston College (CRR) to better understand the current and future economic situation of the individuals living in private pay independent living and assisted living communities.

The survey gathered information on the income and assets of the population at the time of the survey (2011), as well as retrospective information concerning living arrangements, care provision, and finan-cial gifts given. Topics addressed include the costs and satisfaction with the communities, methods of paying for the community, evidence of spending down or giving away assets, financial concerns, and the geographic mobility among the residents.

The survey’s sample consists of 2,617 respondents living in freestanding independent living commu-nities, freestanding assisted living communities, and communities that offer both independent living and assisted living care segments. The survey respondents completed an anonymous questionnaire consisting of 41 questions posed across eight (8) pages. The results of the survey are so extensive that the findings are presented in a four-volume set of papers spanning 107 pages.

Key results from the survey reported by the CRR include:

Residents in independent living and assisted living communities are generally mid- to high-income households who receive most of their income in annuitized forms: Social Security, pensions, and private annuities. Investment income is also relatively common among the residents.

The majority of residents report that they are self-reliant, with few relying on family to pay for their community and care. While about one-third of the residents report paying for their expenses out of their income alone, many report actively spending down their assets for their care.

Overwhelmingly, residents feel as if they are getting good value for their money. There is substantial geographic mobility among the residents from their previous residence,

which was typically an arrangement where they lived alone or only with a spouse. Many residents received non-financial assistance before they moved to their current com-

munity, either from family or another type of care community. Combined independent living/assisted living communities seem to attract residents from

longer distances than do freestanding communities.

The research was performed pursuant to a grant from the National Investment Center for the Seniors Housing & Care Industry (NIC), the Assisted Living Federation of America (ALFA) and the American Seniors Housing Association (ASHA).

For more information regarding the survey results, contact Jessica Palmeri, director of marketing, NIC at [email protected] or 410-267-0504.

RESIDENTS IN SENIORS HOUSING AND CARE COMMUNITIES: OVERVIEW OF THE RESIDENTS FINANCIAL SURVEY

Norma B. Coe and April Yanyuan Wu

CRR WP 2012-6

Date Released: April 2012 Date Submitted: November 2011

Center for Retirement Research at Boston College Hovey House

140 Commonwealth Avenue Chestnut Hill, MA 02467

Tel: 617-552-1762 Fax: 617-552-0191 http://crr.bc.edu

Norma B. Coe is associate director for research at the Center for Retirement Research at Boston College (CRR). April Yanyuan Wu is a research economist at the CRR. The research reported here was performed pursuant to a grant from the National Investment Center for the Seniors Housing & Care Industry (NIC), the Assisted Living Federation of America (ALFA), and the American Seniors Housing Association (ASHA). The opinions and conclusion expressed are solely those of the authors and do not represent the opinions or policy of NIC, ALFA, ASHA, or Boston College. The authors are grateful for comments supplied on an earlier draft by Charles Harry. They would also like to thank the team at ProMatura Group, LLC, especially Edie Smith and Margaret Wylde, and Mashfiqur Khan, Madeline Medenica and Zhenya Karamcheva for research assistance. All errors are their own. Corresponding author: Norma B. Coe, Center for Retirement Research at Boston College, Hovey House, 258 Hammond St., Chestnut Hill, MA 02467; Tel: (617) 552-1762; Fax: (617) 552-0191; e-mail: [email protected] © 2012, Norma B. Coe and April Yanyuan Wu. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.

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About the Center for Retirement Research The Center for Retirement Research at Boston College, part of a consortium that includes parallel centers at the University of Michigan and the National Bureau of Economic Research, was established in 1998 through a grant from the Social Security Administration. The Center’s mission is to produce first-class research and forge a strong link between the academic community and decision-makers in the public and private sectors around an issue of critical importance to the nation’s future. To achieve this mission, the Center sponsors a wide variety of research projects, transmits new findings to a broad audience, trains new scholars, and broadens access to valuable data sources.



phone: 617-552-1762 fax: 617-552-0191 e-mail: [email protected]

crr.bc.edu

Affiliated Institutions: The Brookings Institution

Massachusetts Institute of Technology Syracuse University

Urban Institute

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TABLE OF CONTENTS 1. Introduction Page 4

2. Survey Instrument and Design Page 5

3. Data Cleaning and Quality Page 6

4. Statistical Analysis for Data Quality Page 10

5. Comparing Health and Demographic Characteristics with Previous Studies Page 11

6. Conclusions and Future Directions Page 14

7. References Page 16

ASSOCIATED PAPERS 1. Coe, Norma B. and April Yanyuan Wu. 2012. “Financial Well-Being of Residents in

Seniors Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2011-7. Chestnut Hill, MA: Center for Retirement Research at Boston College.

2. Coe, Norma B. and April Yanyuan Wu. 2012. “Costs and Concerns Among Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2011-8. Chestnut Hill, MA: Center for Retirement Research at Boston College.

3. Coe, Norma B. and April Yanyuan Wu. 2012. “Geographic Mobility Among Residents in Seniors Housing and Care Communities: Evidence From the Residents Financial Survey.” Working Paper 2011-9. Chestnut Hill, MA: Center for Retirement Research at Boston College.

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Introduction

With the leading edge of the baby boom generation reaching retirement age,

decisionmakers need a comprehensive understanding of their social, economic, and health

characteristics – both in terms of resources and needs – in order to adopt effective public policies

and private services to meet the needs of an aging population. One area of particular importance

is their need for housing and long-term care services. A variety of options is available to meet

these needs, including independent living (IL) and assisted living (AL) residences.1

Previous research has examined various aspects of the individuals who use these seniors’

housing and care communities. In the late 1990s, the National Investment Center for the Seniors

Housing & Care Industry (NIC) sponsored survey research on the economic status of residents of

AL communities. This research found that AL residents had significantly lower incomes than

were reported in other industry-sponsored surveys, suggesting that other payment sources – such

as asset liquidation and financial assistance from family members – could be important in

covering the costs of care. More recently, Coe and Boyle (2012) used three existing, nationally

representative surveys to compare the economic circumstances of the elderly based on their

living arrangements: in private residences, in ALs, in ILs, and in continuing care retirement

communities (CCRCs). Their study concludes that while we can learn from nationally

representative surveys, they have significant limitations in addressing questions concerning the

financial security of residents for three main reasons: (1) it is difficult to consistently identify

individuals in senior care communities across the surveys; (2) the sample sizes are very limited

for those you can identify, making longitudinal analysis difficult; and (3) the wealth data are

insufficient to paint a reliable picture of the economic status of residents of these communities.

To fully understand the current and future economic situation of this population, we

designed and conducted a new survey, the Residents Financial Survey (RFS), with assistance

from ProMatura Group, LLC (ProMatura), to obtain a current economic profile of individuals

living in ALs and ILs. This survey gathered information on the income and assets at the time of

the survey (2011), as well as retrospective information concerning living arrangements, care

provision, and financial gifts given.

1 Nursing homes and continuing care retirement communities – which include independent living care segments – are also important providers of housing and care, but outside the scope of this research.

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This paper provides an overview of the survey instrument and design, and details the

data-quality analysis undertaken. Further, this paper provides descriptive statistics of the sample

and compares it to other available surveys of the same population. We conclude that the data

quality is high and quite reliable, and the survey contains a wealth of information about the

economic well-being of seniors living in IL and AL communities.

1. Survey Instrument and Design

The Residents Financial Survey (RFS) was designed to measure the assets and incomes

of individuals in freestanding ILs, freestanding ALs, and communities that offer both IL and AL

arrangements. With assistance from ProMatura, we fielded a pilot survey in March 2011, which

led to 47 completed surveys. To help ensure better participation, ProMatura reached out to

individual communities and corporate offices to secure their support. Surveys were mailed to the

staff of the 283 communities that agreed to participate, who then distributed them to the

residents. The response rate was almost 56 percent at the community level (158 communities).

The questionnaire changed slightly between the pilot and the final survey. Two questions

were added to the final survey; one question was reworded and shortened to make it easier to

understand; and a “none of the above” option was added to three questions to help differentiate

non-response from not having the item in question. The final survey was mailed between June 9

and July 29, 2011, and can be found in the Appendix. The 10,845 surveys mailed to IL

residents, yielded 1,309 responses (12 percent response rate); and 14,146 to AL residents,

yielded 1,261 responses (9 percent) – for a 10.2 percent combined response rate. While these

response rates are low, they are typical for surveys of individuals in these communities. For

example, the Income Confirmation Study, a survey of AL residents, had an overall response rate

of 19 percent including returned surveys due to individuals passing or moving away, which is a

7.6 percent response rate for completed surveys. Importantly, we received more surveys than

our initial target of 1,000 responses per IL and per AL, ensuring sufficient sample size for

statistical analyses for each residence type. We tested for differences between the pilot and the

final survey and found very few; thus, we combined the samples and used the full 2,617

responses.2

2 Pilot survey respondents were slightly more likely to skip more questions, even when taking the fact that “none-of-the-above” answer was not available to them for three questions. They were also more likely to fill out the survey

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The RFS questionnaire is designed to build on existing data and broaden the range of

information covered. When possible, we used pre-tested questions from existing surveys to help

in comparing our results with nationally representative surveys. However, due to the average

age and potential health limitations of the population, some question simplification was

necessary. In the survey, we defined terms such as “current income,” “community type,” “long-

term care insurance,” and “net worth.” We also allowed many questions to have an “other:

please specify” option, so that individuals could include income/assets from sources by the

names they are used to but which did not correlate exactly with those on our list. We then used

this free-form answer information to place the income/assets into consistent categories. The next

section discusses in detail the data evaluation process, including item non-response, outliers, skip

patterns, re-coding of “other” responses, and internal consistency checks.

There are 477 individuals, or about 18 percent of the sample, living in ILs; 880 (34

percent) living in ALs; and 1,260 (more than 48 percent) living in communities that offer both IL

and AL arrangements (with 32.6 percent in the IL portion and 15.5 percent in the AL portion).

2. Data Cleaning and Quality

2a. Item non-response

As an incentive to participate in the survey, individuals were eligible to enter a lottery for

a $100 cash prize. However, to maintain individual confidentiality, the lottery drawings were

mailed to a different address; it is possible that a person could enter the lottery without actually

mailing in the survey.3

Surveys were complete, for the most part, and responding individuals did not seem to

suffer from question fatigue. Despite the length – 41 questions on seven pages (four double-

This makes it less likely that individuals would not take the survey

seriously just to enter the lottery drawing. However, given the age and the health status of the

target populations, we need to undertake extensive testing to determine whether item non-

response or data outliers are random – essentially white noise that can be ignored – or correlated

with other characteristics of the individual, thus requiring corrections or potentially dropping the

individual from the survey results.

with the help of others. Based on the final survey responses, we re-coded missing values to questions 34 and 35 as none-of-the-above, but kept the missing responses to question 37 because it was not clear from the final survey whether the missing responses really indicated none-of-the-above responses. 3 It actually seems that the reverse is true. There were a total of 2,318 lottery entries and 2,617 surveys received. The lottery drawing was held September 14, 2011, and the 20 winners were notified via telephone.

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sided) – only 24 people did not answer a single question on the last page. The first page of the

survey was on the back of the first page of the pamphlet, and 2 percent of the sample missed this

page. However, the most-skipped page (7) was skipped by only 4 percent of the sample, and no

one skipped all of the back pages. Importantly, only 4 percent skipped the entire income section

(V), which was the most-skipped section, and 2 percent skipped the entire asset section (VI).

Overall, item non-response was minimal. The most-skipped question, taking into account

the acceptable skip pattern, was 23b, with 76 non-responses. The least-skipped question was 41,

with 25 not answering. The most questions skipped by any individual, accounting for the skip

pattern, was 37. And 31 percent of the respondents answered every question they should have

answered. Figure 1 illustrates the number of questions skipped within the sample.

2b. Outliers

Another concern is outliers. The primary concern is in questions 23, 23b, and 39 for fill-

in dollar amounts.4

The other outliers are not obviously due to reporting error. For question 39, the top

recorded value is almost twice the second-largest value, but there is a long right tail to the

distribution of responses, so it is more difficult to assess if these outliers are due to reporting

errors or true variation in the sample. Question 23b also has a long right tail, so while the

highest value is more than 45 times the median, conditional on reporting additional services, it is

only 1.1 times the next highest value. Therefore we conducted no additional data trimming or

editing.

There was one outlier for question 23 concerning the monthly cost of the

residence: it was more than 1.5 times the next highest reported amount, and almost 7.5 times the

next highest amount reported for the same residence, given the type of care received and the

number of people the charge was for. This was corrected by dropping a zero from the reported

amount, which brings it in-line with fees reported by the community and fees reported by others

within the community.

4 Outliers are also of concern for questions 25, 31, and 33, which are also fill-in monthly dollar amounts. However, since we also have a categorical question about total monthly income (question 36) as well as needs-based income from government sources, we have built-in check-points for questions 31 and 33. We can also check question 25, the amount paid towards regular expenses by other source than income, with questions 23 and 23b (monthly costs), and question 24 (how much of the monthly costs are met with regular income). Discussion of the cleaning of these questions is in section 5, internal consistency.

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2c. Skip Patterns

Skip patterns were built into the survey and indicated at the end of the selected answer.

For example, after indicating that all daily living expenses were covered by current income

(answer 1 to question 24), individuals were prompted to skip question 25 (concerning what other

resources they used to cover these expenses) and move to question 26. However, because this

was a paper survey and not a computer-assisted personal interview (CAPI), the skip patterns

were not always followed. The skip pattern that most people did not follow was question 23a to

question 23b, where 25 percent of the respondents skipped 23b when they should not have. The

skip pattern followed most closely was question 13 to question 14, where only 2 percent of the

respondents incorrectly answered the second question. There are also a few cases where people

should have skipped a question but did not. The most frequent case of this “reverse skip” pattern

is between questions 24 and 25, where 54 individuals answered the follow-up question when

they did not need to.

2d. Recoding “other/specify source” answers

For many of the income and asset questions, we included the ability for the respondent to

answer “other” and fill-in the specific income/assets they were referring to. This method

revealed that individuals were using different classification systems than we had originally

intended. For example, in question 25, some individuals responded that they were using an

inheritance to pay for regular expenses – we would have categorized this as spending down

current assets/savings. Table 1 indicates how we classified the “other” responses for questions

25, 35, and 37.

In addition, the fill-in responses in the “other” categories often informed us on other

questions. For example, many people indicated in question 25 that long-term care (LTC)

insurance helped pay for their current care. Thus, we edited answers to question 26 about LTC

insurance accordingly. Fill-ins on question 25 also indicated Medicaid coverage, housing

subsidies, and other government assistance programs, which we used to re-code these variables

in question 35. Answers to the “other” category of income from federal or state governments

indicated receipt of Social Security, federal pensions, and government bonds. While these were

not the means-tested programs we intended to elicit with this question, we used these answers to

double-check the answers to questions 29, 32, and 34. Finally, fill-in answers to question 37

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were used to check the answers concerning Social Security receipt, pensions, and LTC insurance

coverage.

Moreover, respondents were asked to list all the reasons they think that they will move

out of the current community within the next 12 months (question 21). We have categorized the

open-ended answers to the most important reason into five categories: financial, health,

unsatisfactory service, family and other reasons. This classification is detailed at the end of

Table 1.

2e. Internal Consistency

Including questions on specific types of income and total income and specific types of

assets and total net worth provide a way to check for internally consistent answers. For example,

if an individual reports receiving $1,200 in Social Security benefit income per month (question

31) and $2,000 in pension or annuity income per month (question 33), we expect the individual

to report that he or she has at least $3,200 in total monthly income. Not following the skip

pattern can also become a problem if answers are not internally consistent, i.e., someone

indicates that all of his or her expenses are covered by current income in question 24 and

indicates that he or she is using other assets to pay regular expenses in question 25.

We created variables to indicate when individuals were internally inconsistent. Forty-

nine people state that they received more money from Social Security (question 31), pensions

(question 33), and income from other sources (question 34), than they report as their total income

(question 36). Ninety-six individuals report that their current monthly bills (question 23 and

question 23b) exceed their current income, yet state that they pay all their bills with their current

income (question 24). Thirty-two respondents report high income (greater than $2,500 per

month) and report getting needs-based government assistance. Seventy-one people stated an

extremely large value for their monthly bill for the community (question 23) – both in terms of

their self-report compared to others in the same community (top 10 percent of reported fees) and

compared to the community-reported fees (the difference between their monthly bill and

maximum fees reported by the community was more than 30 percent of the maximum fee

reported by their community).5

5 The fee information was provided by matching respondents to the NIC Map database. Monthly fees were reported for studio, one-bedroom, and two-bedroom apartments.

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An additional 81 people stated an extremely small value for their monthly bill – both in

terms of their self-report compared to others in the same community (bottom 10 percent) and

compared to the community-reported fees (the difference between their monthly bill and

minimum fees reported by the community) – was more than 30 percent of the minimum fee

reported by their community. In addition, they did not report getting any financial assistance

from the government. This could be due to family members receiving bills directly from the

community, and the resident being unaware of these payments. See Overview of Assisted Living

(2006) for more detail.

3. Statistical Analysis for Data Quality

We conducted regression analysis to test if item non-responses, section non-responses,

page non-responses, outlier responses, and internally inconsistent responses are predictable using

the other information available in the dataset. We were primarily concerned that some

individuals were not reliable in their answers, either through inconsistencies or non-response.

We created an index variable that counted the number of missing or “wrong” answers, as defined

above. On average, almost three questions per respondent were either missing or considered

questionable, but it varies between 0 and 37. There are not significant differences among the

four types of respondents surveyed, those living in freestanding ILs (ILs), freestanding AL

(ALs), IL residents in IL/AL, and AL residents in IL/AL). We tested to see if other factors could

predict the quality of the survey answers. Respondents who filled out the survey themselves

with no assistance had, on average, 1.5 additional problematic answers. This is not surprising

given the age of the population surveyed. However, once the data are segmented by whether the

respondent received help or not, virtually nothing predicted unreliable answers. While

regression analysis shows that non-response does not relate to the quality of the survey answers,

we further tested to see if individuals who missed a significant portion of questions were not

reliable in their answers. We find that individuals who missed 15 questions or more (78

individuals, or less than 3 percent of the total sample) still provided reasonable answers to the

questions of health and demographic characteristics, and the questions related to costs, income

and assets. Their answers are very unlikely to fall into the category of outliers (at most 4 percent

in question 23) or to be internally inconsistent (less than 1 percent provided questionable

answers). We also conducted the same analysis on individuals who missed over 25 questions

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(only 15 individuals) and found that the quality of their answers is not a concern. Therefore, we

have maintained the full sample of 2,617 respondents. We have re-coded answers that are

questionable based on our internal consistency checks and report the percent of respondents who

did not answer each particular question.

4. Comparing Health and Demographic Characteristics with Previous Studies

Table 2 presents the RFS sample’s health and demographic characteristics, separate by

living arrangement. We tested to see if respondents could be pooled across freestanding AL,

freestanding IL, or communities offering both, and found significant differences based on

community type. Therefore, all of the statistics presented below are separated by freestanding

IL, freestanding AL, IL residents in combined IL/AL communities, and AL residents in

combined IL/AL communities. We also report item non-response and the percent of

questionable answers as separate categories for each variable of interest. 6

The average age of our sample is just over 86, with no significant differences across four

types of living arrangements. The age distribution is slightly skewed to the right, with the

median respondent being 87 years old. The age differences between the men and women are

significant, however, with the women being older. Compared to earlier work, our sample is

significantly older.

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About one-quarter of the respondents living in freestanding ALs were men, with slightly

higher representation in the other community types (31 percent for the AL portion of IL/ALs; 29

percent for ILs; and 35 percent for the IL portion of IL/ALs.). While this might seem low, the

RFS has higher male representation for ALs than previous work.

The average age at which our respondents moved into their current

community is 83.3 years old, with a median age of 84.4.

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These residents are predominantly Caucasian, with more than 92 percent self-identifying

as such. Almost 3 percent of the freestanding IL respondents are African-American, compared

The proportion of men in ILs

is comparable to the samples studied in Coe and Boyle (2012).

6 In the tables presented in the paper, we include non-response and questionable answers in the percentages so the reader has the full information. Appendix Table 1 presents the descriptive statistics percentages re-calibrated as a percent of those who answered correctly, instead of the percent of people in the survey, so comparison across the types of communities is easier for the reader. 7Coe and Boyle (2012), the Independent Living Report, ALFA (1998), and NIC (1998) all had average ages of 80-85. 8 See NIC (1998), ALFA (1998), and Coe and Boyle (2012).

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to less than 1 percent from the other community types. Even adjusting for the regional

composition of our sample, Hispanics and African-Americans are underrepresented in these

communities, compared to the U.S. 65-plus population of about 19 percent.9

Marital status varies among the communities. Less than 10 percent of residents in

freestanding ALs are currently married, and 72 percent are widowed. Respondents in the other

community types are much more likely to still be married (16 percent for the AL portion of

IL/ALs; 13 percent for ILs; and 20 percent for the IL portion of IL/ALs). The marital pattern for

ILs and the IL portion of IL/ALs is comparable to that reported by Coe and Boyle (2012). It is

lower than that reported in the Independent Living Report (about 35 percent), but that is not

surprising considering their focus was on new entrants and included CCRCs in the sample. For

freestanding ALs and the AL portion of IL/ALs, our sample is much less likely to be married

than the 20-percent marriage rate among AL residents found in Coe and Boyle (2012).

Consistent with the existing literature, we find that the educational achievement of

residents in these four types of communities is higher than the U.S. as a whole. Specifically, 41

percent of residents in the IL portion of the IL/ALs had a college degree, which is higher than

residents in freestanding ILs (28 percent), freestanding ALs (23 percent), and the AL portion of

the IL/ALs (29 percent). Only 20 percent of the overall U.S. 65-plus population has a college

degree. The RFS sample exhibits slightly lower educational attainment than found in the

Independent Living Report. When we compare recent movers to longer-term residents within the

RFS, we find similar levels of education among recent movers (33 percent with a college degree

versus 30 percent of the longer-term residents), which suggests that the difference with the

Independent Living Report is driven by the inclusion of CCRCs being in the sample, which

apparently attract an even more educated clientele.

Overall, the average number of residents’ living children among our sample is almost 2.5,

with little variation between the types of living arrangements. These numbers are comparable to

Coe and Boyle (2012), but slightly lower than the U.S. 65-plus population of almost 3.10

One-quarter to one-third of the respondents report themselves to be in very good or

excellent health compared to their peers. Figure 2 explores this further, showing that 6-9 percent

9 Authors’ calculations using the 2010 Current Population Survey (CPS). The fraction of non-white in the CPS is about 17 percent for over-85 population, suggesting that the low minority representation is not just an age-effect. 10 Author’s calculations of the Survey of Consumer Finances (2007). The average number of living children of the over-85 population is 2.5.

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rated their health as excellent, which is lower than reported in the Independent Living Report (11

percent for ILs and 14 percent for the IL portion of IL/AL). However, the RFS sample is

healthier than that reported in the Independent Living Report when we focus on recent movers.

About one-third of respondents in freestanding ILs rated their health as very good, 37 percent as

good, 21 percent as fair, and 2 percent as poor. In contrast, self-reported health is relatively

worse for the residents in ALs and the AL portion of IL/AL, with about 9 percent and 7 percent

reporting poor health, respectively. We also find that more than 50 percent of respondents rate

their current health as “Much better now,” “Somewhat better now,” or “About the same” as

compared to two years ago. Further, there does not appear to be a relationship between health

changes and the length of time living in the current community. This suggests that individuals

are not experiencing rapid or continuous health declines.

While the survey spanned the continental U.S., our responses show regional

concentration. Forty percent of the entire sample is located in the West, with another 30 percent

located in the South. However, the regional variation depends on the type of community. Over

60 percent of the freestanding IL sample is located in the Midwest, with very few observations

coming from the South or the North. Conversely, over 20 percent of the AL sample (both

freestanding and combined) is located in the North. Despite the geographic variation in the

community types, we see very little difference in the sample characteristics by community, such

as race, age, education, and number of children, which do have regional variation in the

population as a whole.

Finally, we examined who actually answered the survey. Figure 3 shows that two-thirds

of the respondents completed the survey, either by themselves or with the help of others. Family

members participated in the completion of 38 percent of the surveys, staff assisted in the

completion of 2 percent, and friends participated in completion of 1 percent. In many instances,

more than one person (resident and family or staff member) participated in the completion of the

survey. Not surprisingly, being in very good or excellent health is positively correlated with the

resident filling in the survey on their own. The percent of the residents participating in

completing their own surveys is comparable (almost 60 percent) to those reported in NIC (1998).

However, what does differ is others’ involvement. Our respondents’ families were much more

involved than in previous work (only 20 percent of family members were involved in NIC

(1998)) instead of relying as heavily on staff assistance (40 percent). We also examined the

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characteristics of family members who participated in the completion of the survey. More than

half of the family members completing the surveys are daughters; more than one-quarter are

sons; 6 percent are spouses; and the rest are extended family, including brother/brother-in-law,

sister/sister-in-law, cousin, niece/nephew, and grandchildren.

It is not surprising that residents in ILs (both freestanding and combined IL/AL) are more

likely to complete or participate in the completion of the surveys: 91 percent of residents who

live in the IL portion of ILs/ALs and 72 percent in freestanding ILs participated in completing

the surveys, compared to only 46 percent in freestanding ALs and 60 percent in the AL portion

of IL/ALs. In contrast, 61 percent of residents who live in freestanding ALs have their family

members participate in the completion of the surveys. The corresponding numbers for residents

are 44 percent in the AL portion of IL/ALs, 32 percent in freestanding ILs, and 15 percent in the

IL portion of IL/ALs.

5. Conclusions and Future Directions

After extensive study of item non-responses, skipped questions, outliers, and internal

inconsistencies, we are confident that the data quality is high. We have concluded that for the

most part the responses are reasonable, and when they are not, they seem to be “noise” and not a

sign of systematic reporting errors. Given the time, effort, and cost of the survey, this is

reassuring.

The Residents Financial Survey indicates that residents in the four types of care

communities examined (freestanding ILs, freestanding ALs, IL portion and AL portions of

IL/AL communities) are over 80 years old, on average, and predominately white, female, and

college educated. The survey achieved regional variation, although part of this variation is

driven by the different types of communities surveyed. Many of the respondents are widows, but

unlike previous work, we also pick up a relatively high percentage of intact couples. Individuals

tend to rate their health relatively favorably to others in their age group. Accordingly, they also

seem more willing and able to undertake the survey responses, either by themselves or with

assistance of family or staff.

This survey is a new and important contribution to the research community. There are

many research questions that can be addressed with this new dataset. In a series of companion

papers, we explore the costs of the communities and concerns residents have about paying for

15

these costs, the financial well-being of residents, and their geographic mobility patterns (Coe and

Wu 2012a-2012c). However, there are many other potential uses for this new data source. For

example, future work could include examining the role of family, in paying for care and

provision of care, and how that relates to the past, current, and future living arrangements.

16

References Assisted Living Federation of America (ALFA). 1998. “The Assisted Living Industry: An

Overview – 1998”. Fairfax, VA: Price Waterhouse and ALFA. Coe, Norma B. and Melissa Boyle. 2012. “The Asset and Income Profile of Residents in

Seniors Care Communities.” Research on Aging, forthcoming. Coe, Norma B. and April Yanyuan Wu. 2012a. “Financial Well-being of Residents in Seniors

Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2012-7. Chestnut Hill, MA: Center for Retirement Research at Boston College.

Coe, Norma B. and April Yanyuan Wu. 2012b. “Costs and Concerns among Residents in Seniors

Housing and Care Communities: Evidence from the Residents financial survey.” Working Paper 2012-8. Chestnut Hill, MA: Center for Retirement Research at Boston College.

Coe, Norma B. and April Yanyuan Wu. 2012c. “Geographic Mobility among Residents in

Seniors Housing and Care Communities: Evidence from the Residents financial survey.” Working Paper 2012-9. Chestnut Hill, MA: Center for Retirement Research at Boston College.

“Income Confirmation Study of Assisted Living Residents and the Age 75+ Population.” 1998.

Annapolis, MD: National Investment Center for the Seniors Housing & Care Industry. National Investment Center for the Seniors Housing & Care Industry. 1998. “National Survey

of Assisted Living Residents: Who is the Customer?” Annapolis, MD. “Overview of Assisted Living.” 2006. Washington, DC: American Association of Homes and

Services for the Aging, American Seniors Housing Association, National Association for Assisted Living; Alexandria, VA: Assisted Living Federation of America; and Annapolis, MD: National Investment Center for the Seniors Housing & Care Industry.

“The Independent Living Report.” 2009. Washington, DC: American Seniors Housing

Association.

17

18

19

Figure 3. Who Completed the Survey

58.2% completed by

residents

30.0% completed by

family members

1.8% 1.0%

9.3% completed by both

residents and family member

or staff

7.9% completed by both

residents and family members

0%

10%

20%

30%

40%

50%

60%

70%

80%

Resident Family Staff Friends

67.4%

37.9%

20

Table 1. Reclassifying “Other” Responses Question 25: Other sources that pay regular expenses

Spending Down Saving/Assets

My children/family Other sources of income

Inheritance Bonds CDs Capital Gains Stocks Trust/Trust Fund IRA Investments/Mutual Funds Retirement Funds Sale of house Sold land (owner finance) Credit card Equity line of credit on home

Friend LTC insurance Medicaid Medicare Low-rent housing Federal/state Aid VA benefits Renting home Alimony Social Security Annuity/ Retirement income/ Pension Disability Business income/farm Employment

Question 35: Other sources of government support HUD Rental Assistance

Disability benefits

Other

MI Housing Allowance MISHDA Rent Assistance Section 8 Housing

100 percent disability VA Disability Medicare Disability SS Disability Temp. total disability Workers' Compensation

Agency for Living Aid for Assisted Living American Eldercare Heart and Home Hospice Low income assistance Navy Mutual Aid

Question 37: Other assets Brokerage/stock/ bonds/mutual fund

401(k), IRA, SEP or KEOGH

Trusts

A House, Property or Land

$52,000 15 year note. Investment-low risk Investments Money from sale of car Money from sale of house

Annuities and IRA Annuity fund and retirement equity fund Deferred compensation 2nd retirement income

Husband trust fund can be used 1st Deed of trust Trust

Contract on mobile home House-being sold Vacation home Time shares

21

Table 1 (cont’d). Reclassifying “Other” Responses Question 37: Other assets (cont’d) Farm or business

A car or other vehicles

Personal

Other

Partnerships

2007 Kia paid for 1981 Ford Fairlane

Antique furniture Personal property Art work Clothes and jewelry Computer and Printer Doll Collection Furnishings/Furniture Porcelain collectibles Jewelry Stamp and coin collection

Interest from private loan Leased mineral rights Mortgage on properties Savings Royalties Gold/Gold pieces Boat

Question 21: Primary reason for moving out Financial

“$3295.00 per month is pricy.” “Assets depleting.” “Becoming too expensive” “Better accommodation at lower total expense.” “Can only afford to stay a few more months.” “Can own cheaper than this outrageous rent.” “Can't afford it” “Can't afford services.” “Care paid for is NOT being provided.” “Cost” “Cost - Personal service fee increased at least 15% this year and additional

“Expenses.” “Expensive” “Finances” “Financial reasons.” “Family runs out of money to pay fees.” “I will run out of money” “If SS folds, not enough income.” “If they keep raising rent.” “If they raise my rent beyond my ability to pay.” “Inability to sell home.” “Increase in rent.” “Increase in rental fees and new fees for services formerly provided.” “Increases are above the cost of living. New residents are upgraded before

“To save money” “Too costly.” “Too expensive” “Too expensive for services needed.” “Unable to continue paying.” “Will run out of money.” “Cost-they are raising fees almost $2000.” “Cost/Value” “Excessive increase of fees.” “Rent cost” “Rent is beyond our income” “Rent is too high.” “Lack of money.” “Medical assistance too

“Rent is too high and unevenly (unfairly) administered.” “Run out of money” “This community does not accept Medicaid” “Need more affordable assisted care for wife.” “No money left to pay for living expenses” “No more money to pay.” “Not enough money to pay for where I live.” “Price goes up annually and I get no pay increase.” “Raise in fees.” “Rate increases.” “Rent beyond my income” “Cost, won't be able to afford it anymore.” “Cost too high.” “Lack of financial support.”

22

Table 1 (cont’d). Reclassifying “Other” Responses Question 21: Primary reason for moving out (cont’d) Health Service Family Other services needed. Rent also increased 15%.” “Cost increases” “Cost of Living at the community.”

old residents.” “Increasing costs and declining service.” “Insufficient funds to remain here.”

expensive.” “Money” “Money-taxes and insurance very costly.” “My insurance policy is up.”

“Age.” “Alzheimer's Progressing” “Alzheimer's-need more care.” “Death” “Declining mental health.” “Dementia.” “Deteriorating health condition.” “Deteriorating health.”

“Food-not enough vegetables, too much fish and chicken.” “Food.” “If some things don't change.” “Lack of activities for people in wheelchairs” “Lack of care” “Lack of maintenance.” “Lack of staff and staff competence.”

“Family is in Denver, Co.” “Going to live with daughter.” “Live closer to family.” “Moving back home.” “Moving home.” “No family here.” “Return to home state.”

“Can't adjust to apartment living.” “Discrimination” “Independent-not quite so.” “More disabled residents moving in.” “Lack of privacy and independence.” “May not need service offered here.” “Not appropriate placement.”

“Deteriorating health.” “Existing brain tumor.” “Failing health.” “Health” “Health doesn't warrant assisted living anymore” “Health improving.” “Higher level of assisted living required.” “I will be well and can return to unassisted living.” “If my health

“Lack of staff and staff competence.” “Lots of scorpions in this apartment building.” “Meal quality.” “More frequent transportation to stores, community affairs, outings” “More skilled nurses.” “No meals” “Noisy dogs” “Non-interest of management to

“To be closer to children and grandchildren.” “To be closer to family” “To be near daughter.” “To be near family.” “To be near my children.” “To be with family.” “Want to be closer to

“Not appropriate placement.” “Not familiar with the area” “People are much older and disabled.” “Religious community” “Residents here are too old, only a few close in age to me.” “Residents here require various levels of care and many have physical and mental challenges.” “Think I can live alone.” “To be near VA Hospital” “Too many mistakes.” “Too many moving in that should be in AL not IL due to physical/mental health concerns.” “Too many people who cannot converse with each other.” “Too many residents need to be in assisted living.” “Very unhappy.”

23

Table 1 (cont’d). Reclassifying “Other” Responses Question 21: Primary reason for moving out (cont’d) Health Service Family Other diminishes.” “Improvement of physical condition.” “Medical” “Need more care.” “Need more help.” “Needs extra care.” “Need assistance with ADL's” “Need assisted living.” “Need for a higher level of care including skilled nursing.” “Physical status.” “Too sick” “Unable to care for myself.” “Unable to walk alone.”

problems.” “Not handicap accessible” “Not happy with assisted living service.” “Point system is ridiculous and unfair.” “Poor food.” “Poor staffing and services.” “Problems with medications-nurse's not reading current doctor’s orders.” “Quality of care, management emphasis on profit rather than compassion” “Quality of the food.” “Repairs to infrastructures are lagging (roof leaks)” “Security is lacking.” “Services” “Size of room.” “Staff has favorites, if you aren't one you're ignored.” “Staffing issues.” “Under staffed, untrained aides”

daughter” “Want to go home.” “Want to live with my daughter.”

“Want a CCRC with skilled nursing care.”

24

Table 2. Demographic and Health Characteristics of Residents

Freestanding IL

Combined IL Freestanding AL

Combined AL

Current age

Average age 86.2

86.4

86.4

86.3

Median age 87.0

87.0

87.0

87.0

Non-response 7.3 % 5.2 % 3.3 % 5.2 %

Age moved into current community

Average age 82.6

83.4

83.7

83.2

Median age 83.7

83.9

84.8

84.8

Non-response 14.5 % 14.4 % 11.1 % 13.1 % Gender*

Male 28.5 % 34.7 % 24.9 % 30.5 %

Non-response 4.2

2.9

1.8

3.7

Race*

African-American 2.7 % 1.0 % 0.8 % 0.3 %

White 92.0

94.5

96.3

96.1

Non-response 3.8

2.6

1.4

2.7 Marital status*

Married 13.2 % 20.1 % 9.4 % 15.5 %

Widowed 66.9

67.5

71.7

67.7

Divorced 9.9

5.9

11.5

8.9

Non-response 3.6

2.3

1.3

2.5

Education*

Less than high school 12.6 % 4.5 % 13.5 % 10.6 %

College educated 28.3

40.6

23.1

29.1

Non-response 4.2

2.8

1.6

3.0 Number of children

Average number of children 2.5

2.5

2.3

2.2

Median number of children 2.0

2.0

2.0

2.0

Non-response 8.0 % 9.6 % 7.2 % 4.9 % Health*

Self-rated excellent or very good 31.5 % 37.6 % 27.8 % 27.3 %

Non-response 3.8

2.3

1.3

2.7

Same/better compared to two years ago 56.4

58.9

51.3

53.2

Non-response 4.0

2.6

1.5

2.7

25

Table 2 (cont’d). Demographic and Health Characteristics of Residents

Freestanding IL


Combined AL

Census region

Northeast

1.1 %

3.9 %

24.0 %

20.4 %

Midwest

62.9

12.1

8.5

5.2

South

2.9

37.8

30.7

30.1

West

33.1

46.3

36.8

44.3

Who completed the survey (multiple answers possible)*

Resident 71.7 % 90.6 % 46.1 % 59.9 %

Family 32.1

14.6

60.9

44.1

Staff 2.1

0.5

1.5

5.4

Friend 0.4

0.2

0.9

3.2

Non-response 1.5

0.8

1.1

0.3 Observations 477 854 880 406

Source: Authors' calculations of the Residents Financial Survey. *: See Appendix Table 1 for calculations of the percentages that treat non-response as missing observations.

26

Appendix Table 1. Characteristics of Residents, Adjusted for Non-Response and Questionable Answers

Freestanding IL


Combined AL

Gender

Male

29.8 %

35.7 %

25.4 %

31.7 %

Race

African-American

2.8 %

1.0 %

0.8 %

0.3 %

White

95.6

97.0

97.6

98.7

Marital status

Married

13.7 %

20.6 %

9.5 %

15.9 %

Widowed

69.3

69.1

72.6

69.4

Divorced

10.2

6.0

11.6

9.1 Education

Less than high school

13.1 %

4.6 %

13.7 %

10.9 %

College educated

29.5

41.8

23.4

29.9

Health

Self-rated excellent or very good

32.7 %

38.5 %

28.2 %

28.1 %

Same/better compared to two years ago

58.7

60.5

52.0

54.7

Who completed the survey (multiple answers possible)

Resident

72.8 %

91.4 %

46.7 %

60.0 %

Family

32.6

14.8

61.6

44.2

Staff

2.1

0.5

1.5

5.4 Friend 0.4 0.2 0.9 3.2

Source: Authors' calculations of the Residents Financial Survey.

Appendix:

Survey Instrument

Consumer Finance Survey

of Independent and Assisted Living Residents Please help us improve.

This survey is being conducted by the ProMatura Group on behalf of the National Investment Center for the

Seniors Housing & Care Industry (NIC). NIC helps community owners and operators learn about the customers

they serve. We are being helped in the interpretation of the survey results by experts at the Center for

Retirement Research at Boston College. The Center provides decision-makers in the public and private sectors

with critical information to better understand the issues facing an aging population.

Topic of the Survey. As the title suggests, this survey asks you (resident and/or family members on behalf of a

resident) to provide information about your income, expenses, investments, pensions, and just about everything

dealing with your finances and how you pay for your residence and services at this community. We know this is

a sensitive issue, but it is important for this industry to know the financial impact of communities, (such as the

one in which you live), on you and your family. All questions are about the resident or his or her finances.

Your Survey is Anonymous. There is no place for you to put your name on the survey. We do not want or

need to know who you are.

Confidentiality Guarantee

Because we are not capturing any personally identifying information from you and because your data will be

put into a database with 1,999 other unidentified surveys, I give you my personal guarantee that your

information cannot and will not be traced to you.

I guarantee that none of your information in this survey will be viewed by anyone except a data entry clerk at

the ProMatura Group, LLC in Oxford, Mississippi (where you will mail the survey). I guarantee that no one at

your community or any other location will see your information, ever.

We are sincerely grateful to you because this survey will be of enormous help for communities to provide

better service and greater value.

Thank you, we are grateful to you for your help,

Margaret A. Wylde, Ph.D.

President, CEO, and Owner

ProMatura Group, LLC

Complete the survey and you will have 20 chances to win $100!

Odds of winning are 1 in 100.

All answers should relate to the resident.

2

SECTION I: DEMOGRAPHIC and HEALTH INFORMATION

1. In what year were you born? 1 9

2. What is your gender? 1 Male 2 Female

3. What race/ethnicity do you consider yourself to be? (Please check all that apply)

1 White 2 Black/African American 3 Hispanic 4 Asian 5 Other

4. What is the highest level of education you have completed? (Please check one)

1 Grade school or less 2 Some high school 3 High school graduate or G.E.D. (Earned diploma) 4 Some college or Associate Degree (2-year) 5 College, graduate or professional degree (BA, BS, MA, Ph.D., M.D., etc.)

5. How many living children do you have? ______ 6. What is your marital status? (Please check one) 1 Married 2 Widowed…………In what year did your spouse die? 3 Divorced (Write in year) 4 Separated 5 Single, never married 6 Other ___________________________________________________ 7. Compared to other people your age, would you say your health is: (Please check one) 1 Excellent 2 Very good 3 Good 4 Fair 5 Poor 8. Compared to two years ago, how would you rate your current health? (Please check one)

1 Much better now 2 Somewhat better now 3 About the same

4 Somewhat worse now 5 Much worse now

? Call 800•201•1483. Ask for Connie Hay. Refer to the Consumer Finance Survey.


3

SECTION II: BEFORE MOVING TO THIS COMMUNITY

9. Where did you live just before you moved to this community? City:_______________ State:__ __ ZIP Code:

10. With whom did you live just before you moved to this community? (Please check one) 1 No one, I lived by myself

2 I lived with only my spouse 3 I lived with my spouse and others (Relationship? ______________________)

4 I lived with family other than a spouse (Relationship? ___________________) 5 I lived with someone other than family (Relationship?___________________)

11. Did you live in another community where residents must be at least 55 or 62 years of age at any

time before you moved to this community? 1 Yes 2 No [Skip to question 13]

3 Don’t Know

12. In which type of age-qualified community did you live? (Please check one) 1 Active Adult community: the community typically has amenities such as a club house,

fitness center, swimming pool, etc. The services, if any are provided, are typically related to the upkeep of the facilities, maintenance of the roads, sidewalks, driveways and sometimes lawn/ landscaping services.

2 Independent Living community (may be part of a community with a continuum of care, CCRC): The fee to live in the community typically includes a dining program, housekeeping, and transportation services. The community typically provides various educational, entertainment, cultural, fitness, and wellness opportunities.

3 Assisted Living community (may be part of a community with a continuum of care, CCRC): is one designed to assist residents with activities of daily living such as bathing, toileting, and dressing. Most communities also offer assistance with and/or reminders to take medication.

4 Rehabilitation Center or Nursing Care Center: this type of residence may be where services are provided by licensed health care professionals such as nurses, nurse aides, and physical therapists.

13. During the six months before moving to this community, did anyone regularly assist you with any

daily activities such as: shopping, preparing or providing meals, dressing, bathing, toileting, managing or taking your medications?

1 Yes 2 No [Skip to next page, question 15] 14. Who provided assistance to you? (Please check all that apply) 1 Family and/or friends (either paid or unpaid). 2 Individuals whose job it is to provide the services.


4

SECTION III. THIS COMMUNITY - The Residential Property Where You Live Today 15. When did you move to this community? Month Year 16. Where is your community located? ZIP Code 17. Is there a fund at your community that will pay for housing and services if a resident is unable to

do so? (Please check one) 1 Yes 2 No 3 I don’t know

18. If you are married, do the two of you live in the same residence in the community, or live in

separate locations? (Please check one.) 1 Not applicable.

2 We live together in the same residence. 3 We live separately in different apartment/residences in this community. 4 My spouse continues to live in our previous home. 5 My spouse lives in a nursing home or medical center not in this community. 6 Other. Please explain:__________________________________________

19. The community where I live now offers me good value for my money. (Please check one.)

1 Strongly agree 2 Agree 3 Neutral 4 Disagree 5 Strongly disagree

20. Within the next 12 months, do you think you will move out of this community? By “out of this

community,” we mean that you will not live anywhere on the premises. 1 Yes 2 No [Skip to next page, question 23]

21. Please list all the reasons why you think you will move out of this community.

Most important:

Important: Less important:

22. Where will you most likely move? (Please check one) 1 To an apartment that does not include any services in the monthly fee. 2 To another community similar to the one in which I am living currently.

3 To a community that offers assisted living services. 4 To a community that offers or nursing care.

5 To my home. 6 To the home of a family member (child, sibling, etc.).

7 Other___________________________________________________


5

SECTION IV. FINANCING CURRENT RESIDENCE AND SERVICES

23. Based on your most recent monthly bill, how much do you pay in total for your residence and all services you receive in this community?

$_________ per month is for 1 One person

2 Two people

23a.Do you pay any additional amount (not included in 23 above) to another agency such as a home health care agency and/or a person such as a “sitter,” “care companion,” or helper to provide services to you in your residence within the community?

1 Yes 2 No [Skip to question 24]

23b. List the service you receive that is not included in your monthly bill from the community in which you live.

Who provides the service (agency or private individual)? Please check all that apply.

Typical total amount paid per month for service

Agency Individual

Agency Individual

Agency Individual

24. Which one of the following statements best describes how much you pay of the monthly fees at this community and your other regular expenses such as: groceries, dining out, gasoline, entertainment, clothing, beautician fees, etc? Do not include one-time or unusual expenditures.

(Please check one.)

1 All of these expenses are covered by my current income. [Skip to question 26] 2 Most of these expenses are covered by my current income, with the rest paid by my

savings, assets, children, or other sources. 3 Some of these expenses are covered by my current income, with the rest paid by my

savings, assets, children, or other sources. 4 None of these expenses are covered by my current income, and all are paid by my savings,

assets, children, or other sources. 25. Which of the sources, in addition to your income, are used to pay your regular expenses?

(Please check all that apply)

Current Income: includes Social Security, pensions, rental income from real estate, business income, income from interest and dividends, and income from government assistance.

Monthly amount, if applicable 1 Spending down my savings and/or my assets $__________ 2 My children/family $__________ 3 Other sources

Please specify: _______________ $__________


6

26. Which of the sources, in addition to your income, are used to pay your regular expenses Do you own a private long-term care insurance policy that pays for your stay in a nursing home, assisted living, or home care? This does not include funds from VA Benefits, Medicaid, Medicare, or any other government program. This refers only to a long-term care insurance policy that you purchased. 1 Yes 2 No 3 Don’t know

27. Relative to my ability to afford the fees at this community, I have… (Please choose one)

1 No concern 2 Some concern

3 Considerable concern

28. What is it about your financial situation that causes you to have this opinion?

___________________________________________________________

SECTION V: INCOME

29. Do you (or your spouse) receive Social Security payments? 1 Yes

2 No [Skip to 32]

30. At what age did you begin receiving Social Security? 31. About how much in total did you (and your spouse) receive from Social Security last month?

$__________

32. Do you (or your spouse) receive regular income from a pension or annuity from a former employer or the military?

1 Yes 2 No [Skip to 34]

33. About how much in total did you (and your spouse) receive from these pensions/annuities last month? $__________

34. Please identify if you receive regular income from any of the following sources. (Please check

all sources of income that you receive). 1 Interest income from bank accounts, CDs, money market accounts

2 Interest or dividend income from stocks, mutual funds, bonds or other investments 3 Rental income from real estate 4 Income from a business or farm 5 Income from a trust fund

6 Income from a reverse mortgage 7 None of the above


7

35. Please identify if you receive any income or assistance from any of these government agencies.

(Please check all sources of assistance that your receive). 1 Veteran’s Administration Aid and Attendance Pension

2 Medicaid or a state needs-based health insurance 3 Supplementary Security Income (SSI) 4 Food stamps 5 HUD Rental Assistance Program 6 Any income from any other government sources. Please specify: ________________________________________ 7 None of the above

36. Please indicate the approximate total amount of income you receive each month from all sources. (Please check only one box.)

1 Less than $850 monthly 2 Between $850 and $1,199

3 Between $1,200 and $1,499 4 Between $1,500 and $1,999 5 Between $2,000 and $2,499 6 Between $2,500 and $2,999 7 Between $3,000 and $3,499 8 Over $3,500 per month

SECTION VI: ASSETS

37. Please check each of the following types of assets that you own. (Please check all that apply)

1 A checking, savings, Certificate of Deposit, or Money Market account 2 A brokerage, stocks, bonds, or mutual fund account 3 A 401(k), IRA, SEP, or KEOGH 4 A trust 5 A house, property, or land 6 Part or all of a farm or business 7 A car or any other vehicles 8 Any additional assets. Please describe:______________________________

9 None of the above

38. Taking into account all the financial holdings of your household, including the value of any other properties you own, and subtracting any money that you owe, which of the following categories best represents your total net worth?

(Please check only one) 1 Under $50,000 2 $50,000 to $100,000

3 $100,000 to $299,999 4 $300,000 to $499,999 5 $500,000 to $749,999 6 $750,000 to $999,999 7 $1,000,000 to $1,999,999 8 $2,000,000 or more



8

39. In the last five years (since 2006), have you given a monetary gift in a single year of more than $10,000 to a person or entity such as heirs, trusts, or charitable institutions (please exclude college tuition or weddings)?

1 Yes What is the approximate total value of financial gifts given in the past 5 years $__________

2 No

40. Do you (or your spouse, if applicable) on a regular basis (such as bi-weekly or monthly) give financial help totaling $500 or more to any of your relatives?

1 Yes 2 No 41. Who completed this survey?

1 Resident 2 Resident with assistance from __________________(relationship of person assisting you) 3 Family member_______________(relationship to resident) 4 Other__________________(Title and relationship to resident)

We thank you for your trust, time, thoughtfulness, and generous spirit!

Please be sure to send in your entry for your chance to win $100. It’s the small card with the accompanying envelope. The National Investment Center for the Seniors Housing & Care Industry (NIC) will draw the names of 20 people from the enrollment cards that are submitted. Your odds of winning $100 are approximately 1 out of 100. For a drawing, those are very good odds. Send your Drawing Entry card in the envelope to the National Investment Center in Annapolis, Maryland. Send your completed survey in the large postage paid business reply envelope to the ProMatura Group in Oxford, Mississippi. We guarantee your confidentiality. Thank you again for participating in the survey.


RECENT WORKING PAPERS FROM THE CENTER FOR RETIREMENT RESEARCH AT BOSTON COLLEGE

Social Security Claiming: Trends and Business Cycle Effects Owen Haaga and Richard W. Johnson, February 2012

Economic Consequences of the Great Recession: Evidence from the Panel Study of Income Dynamics Barry Bosworth, February 2012 The Changing Causes and Consequences of Not Working Before Age 62 Barbara A. Butrica and Nadia Karamcheva, February 2012 The Impact of Temporary Assistance Programs on Disability Rolls and Re-Employment Stephan Lindner and Austin Nichols, January 2012 Understanding the Growth in Federal Disability Programs: Who Are the Marginal Beneficiaries, and How Much Do They Cost? Adele Kirk, January 2012 What Explains State Variation in SSDI Application Rates? Norma B. Coe, Kelly Haverstick, Alicia H. Munnell, Anthony Webb, December 2011 How Do Subjective Mortality Beliefs Affect the Value of Social Security and the Optimal Claiming Age? Wei Sun and Anthony Webb, November 2011 How Does the Personal Income Tax Affect the Progressivity of OASI Benefits? Norma B. Coe, Zhenya Karamcheva, Richard Kopcke, Alicia H. Munnell, November 2011 The Pension Protection Act of 2006 and Diversification of Employer Stock in Defined Contribution Plans Gary V. Engelhardt, November 2011 Prescription Drug Insurance Coverage, Drug Utilization, and Cost-Related Non-Adherence: Evidence from the Medicare Part D Expansion Gary V. Engelhardt, November 2011 Social Security on Auto-Pilot: International Experience with Automatic Stabilizer Mechanisms Barry Bosworth and R. Kent Weaver, November 2011

All working papers are available on the Center for Retirement Research website (http://crr.bc.edu) and can be requested by e-mail ([email protected]) or phone (617-552-1762).

FINANCIAL WELL-BEING OF RESIDENTS IN SENIORS HOUSING AND CARE COMMUNITIES: EVIDENCE FROM THE RESIDENTS FINANCIAL SURVEY


CRR WP 2012-7






2





crr.bc.edu



Urban Institute

3


2. The Residents Financial Survey Page 5

3. Income Page 7

4. Assets Page 9

5. Evidence of Spending Down or Giving Away Assets? Page 11



ASSOCIATED PAPERS 1. Coe, Norma B. and April Yanyuan Wu. 2012. “Residents in Seniors Housing and Care

Communities: Overview of the Residents Financial Survey.” Working Paper 2012-6. Chestnut Hill, MA: Center for Retirement Research at Boston College.


3. Coe, Norma B. and April Yanyuan Wu. 2012. “Geographic Mobility Among Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2012-9. Chestnut Hill, MA: Center for Retirement Research at Boston College.

4

Introduction

With the leading edge of the baby boom generation reaching retirement age,

decisionmakers need a comprehensive understanding of their social, economic, and health

characteristics – both in terms of resources and needs – in order to adopt effective public policies

and private services to meet the needs of an aging population. One area of particular importance

is their need for housing and long-term care services. A variety of options is available to meet

these needs, including independent living (IL) and assisted living (AL) residences.1

In the late 1990s, the National Investment Center for the Seniors Housing & Care

Industry (NIC) sponsored survey research on the economic status of residents of AL

communities. This research found that residents had significantly lower incomes than reported

in other industry-sponsored surveys, suggesting that other payment sources – such as asset

liquidation and financial assistance from family members – could be important in covering the

costs of care. More recently, Coe and Boyle (2012) used three existing, nationally representative

surveys to compare the economic circumstances of the elderly in various living arrangements: in

private residences, in ALs, in ILs, and in continuing care retirement communities (CCRCs).

Their study concludes that while we can learn from the nationally representative surveys, they

have significant limitations in addressing questions concerning the financial security of residents

for three main reasons: (1) it is difficult to consistently identify individuals in senior care

communities across the surveys; (2) the sample sizes are very limited for those you can identify,

making longitudinal analysis difficult; and (3) the wealth data are insufficient to paint a reliable

picture of the economic status of the residents of these communities.

To fully understand the current and future economic situation of this population, we

designed and conducted a new survey, the Residents Financial Survey (RFS), with assistance

from ProMatura Group, LLC.2

This paper explores the financial well-being of individuals in IL and AL communities, by

first examining their monthly income amount and sources. Using reported Social Security

benefits, we also compute a measure of lifetime earnings instead of relying only on point-in-time

This survey gathered information on the income and assets at the

time of the survey (2011), as well as retrospective information concerning living arrangements,

care provision, and financial gifts given by the elderly.

1 Nursing homes and continuing care retirement communities – which include independent living care segments – are also important providers of housing and care, but outside the scope of this research. 2 See Coe and Wu (2012) for more details of the survey.

5

measures taken once the individual is already elderly. We then examine net worth, both the

levels and the types of assets that residents hold. We compare income and assets among

individuals, which emphasizes the need to include both measures in one survey in order to assess

seniors’ financial security. Finally, we examine how gift-giving and assets are related to one’s

tenure in their community, to look for patterns of asset spend-down or asset depletion.

1. The Residents Financial Survey

The Residents Financial Survey, fielded in 2011, was designed to measure the assets and

incomes of individuals in freestanding ILs (ILs), freestanding ALs (ALs), and communities that

offer both IL and AL arrangements. The final sample consists of 2,617 respondents. There are

477 individuals, or about 18 percent of the sample, living in ILs; 880 (34 percent) in ALs; and

1,260 (more than 48 percent) in communities that offer both IL and AL arrangements (with 32.6

percent in the IL portion and 15.5 percent in the AL portion).

Table 1 presents the RFS sample’s health and demographic characteristics, separated by

living arrangement.3 The average age of our sample is just over 86, with no significant

differences across four types of living arrangements. The age distribution is slightly skewed to

the right, with the median respondent being 87 years old. The age differences between the men

and women are significant, however, with the women being older. Compared to earlier work,

our sample is significantly older.4


higher representation in the other community types (31 for the AL portion of IL/ALs, 29 percent

for ILs, and 35 percent for the IL portion of IL/ALs). While this might seem low, the RFS has

higher male representation for ALs than previous work.

The average age at which our respondents moved into their

current community is 83.3 years old, with a median age of 84.4.

5



The proportion of men in ILs is

comparable to the samples studied in Coe and Boyle (2012).

3 In the tables presented in the paper, we include non-response and questionable answers in the percentages so the reader has the full information. Appendix Table 1 presents the descriptive statistics percentages re-calibrated as a percent of those who answered correctly, instead of the percent of people in the survey, so comparison across the types of communities is easier for the reader. 4Coe and Boyle (2012), the Independent Living Report, ALFA (1998), and NIC (1998) all had average ages of 80-85. 5 See the NIC (1998), ALFA (1998), and Coe and Boyle (2012).

6



communities, compared to the U.S. 65-plus population of about 19 percent.6

Marital status varies among the different types of communities. Less than 10 percent of

residents in freestanding ALs are currently married, and 72 percent are widowed. Respondents

in the other community types are much more likely to still be married (16 percent for the AL

portion of IL/ALs, 13 percent for ILs, and 20 percent for the IL portion of IL/ALs). The marital

pattern for ILs and the IL portion of IL/ALs is comparable to that reported by Coe and Boyle

(2012). It is lower than that reported in the Independent Living Report (about 35 percent), but

that is not surprising considering their focus was on new entrants and included CCRCs in the

sample. For the freestanding ALs and the AL portion of IL/ALs, our sample is much less likely

to be married than the 20-percent marriage rate found in Coe and Boyle (2012).


residents in these four types of communities is higher than the U.S. as a whole. Specifically,

more than 40 percent of residents in the IL portion of the IL/ALs had a college degree, which is

higher than residents in freestanding ILs (28 percent), freestanding ALs (23 percent), and the AL

portion of the IL/ALs (29 percent). At the same time, only 20 percent of the U.S., 65-plus

population has a college degree. The RFS sample exhibits slightly lower educational attainment

than found in the Independent Living Report.7

Overall, the average number of residents’ living children among our sample is almost 2.5,

with little variation between the types of living arrangements. These numbers are comparable to

Coe and Boyle (2012), but slightly lower than the overall 65-plus population of almost 3.

8

6 Authors’ calculations using the Current Population Survey (CPS), 2010. The fraction of non-white in the CPS is about 17 percent for over-85 population, suggesting that the low minority representation is not just an age-effect.

One-

quarter to one-third of the respondents report themselves to be in very good or excellent health

compared to their peers. About one-third of respondents in freestanding ILs rated their health as

very good, 37 percent as good, 21 percent as fair, and 2 percent as poor. In contrast, the self-

reported health is relatively worse for the residents in ALs and the AL portion of IL/AL, with

7 When we compare recent movers to longer-term residents within the RFS, we find similar levels of education among recent movers (33 percent with a college degree versus 30 percent of the longer-term residents), which suggests that the difference with the Independent Living Report is driven by the inclusion of CCRCs being in the sample, which apparently attract an even more educated clientele. 8 Author’s calculations of the Survey of Consumer Finances (2007). The average number of living children of the over-85 population is 2.5.

7

about 9 percent and 7 percent reporting poor health, respectively. We also find that more than 50

percent of respondents rate their current health as “Much better now,” “Somewhat better now,”

or “About the same” as compared to two years ago. Further, there does not appear to be a

relationship between health changes and the length of time living in the current community. This

suggests that individuals are not experiencing continuous health declines.

2. Income

In order to assess the financial security of respondents, it is important to examine their

income streams, both the total dollar amount and the sources. Table 2 presents the breakdown of

total monthly income by community type.9 The distribution is quite skewed to the right, with

one-quarter to one-third of the respondents having total income of at least $3,500 a month.

Freestanding IL and AL communities have lower income than combined properties, at both the

median and the average. This distribution is broadly consistent with the U.S., age 65-plus

population, but these residents are much richer than their age group in the community, where

only the top 15 percent of the age 85 and above population have income over $3,500 per

month.10

The income sources are quite interesting. Table 2 also presents the percent of

respondents in each type of living arrangement who report receiving income from each source

(multiple sources possible). As expected, Social Security payments, pensions, and annuities are

widespread. About two-thirds of the sample report receiving pension benefits, which is

consistent with the population at large (Munnell at al. 2009). Upon further examination of the

responses, many individuals indicate that they sold their houses and purchased additional

annuities with the proceeds, increasing the percentage with annuity income. Annuities are less

prevalent among widow(er)s than those currently married or never married, which suggests that

annuities were not purchased as part of the will. However, trusts may be part of the estate

dissolution, since trust income is more prevalent among widow(er)s.

Only one-third of respondents in freestanding ALs receive interest income from

investments, compared to a majority of respondents in the IL portion of IL/AL communities.

9 Total monthly income was asked directly in the questionnaire. For those who did not answer this question, we estimated the total monthly income by adding together their Social Security benefits and their pension benefits as their total income, as long as they did not report getting regular income from other sources. 10 Authors’ calculations from the 2006 Health and Retirement Study.

8

Reverse mortgages are not a popular income source, topping out with less than 5 percent among

freestanding AL residents. Means-tested government programs are also relatively rare, with the

one exception being Medicaid coverage, with 8 percent of AL residents reporting Medicaid or

other state need-based health insurance coverage.

Based on respondent’s self-reported Social Security benefits, marital status, and age at

which they began collecting Social Security benefits, we are able to estimate their Average

Indexed Monthly Earnings (AIME), which provides a good overall summary measure of lifetime

earnings.11 The average monthly lifetime earning is $3,778 with a median of $ 3,191. Residents

of freestanding ALs and the AL portion of IL/ALs have, on average, lower lifetime earnings than

residents of ILs; this holds after controlling for demographic and socio-economic characteristics.

These are high lifetime earnings measures. To put this measure in perspective, respondents

collecting Social Security benefits in the Health and Retirement Study (HRS) have an average

AIME of almost $2,900 and a median of $2,650.12

To further test if there are differences in lifetime earnings among the different

communities, we conducted regression analysis, which allows us to hold individual

characteristics constant and see if community type is still important. Table 3 presents the

results.

However, it is worth noting that there are

low-lifetime earning individuals living in these communities. The bottom 10 percent of the

distribution of lifetime earnings have an average AIME of less than $1,000.

13

11 We take self-reported Social Security benefits to estimate lifetime earnings. For married individuals, we divide the benefit by 1.5, to account for the spousal benefit. Then we discount the monthly benefit for COLA adjustments received since claiming benefits. Then, using the actual and full retirement ages, we take into account any actuarial adjustment made for early or delayed retirement, based on the self-reported year in which the individual began receiving Social Security. This gives us the primary insurance amount (PIA) at the age of retirement. The last step involves reversing the PIA formula, which is the sum of 90% of the AIME up to the first Bend Point, 32% of any amount between the first and second Bend Points and 15% above the second Bend Point. This gives us the average indexed monthly earnings (AIME), which is the average of the top 35 years of earnings, adjusted for average wage growth over one’s career. We then put the number in real 2008 dollars.

Not surprisingly, wealth and marital status are positively correlated with lifetime

earnings. Having children, age, and being in excellent or very good health are also positively

12 While it is possible to merge the HRS survey data to Social Security earnings records, we did not do that for this calculation. Instead, we used the same methodology as used in the RSF data and back-out the AIME from the reported Social Security benefit amount, marital status, and age at which one started claiming Social Security. 13 We run an ordinary least squares regression of the natural log of lifetime earnings on demographic and wealth information. The control variables include: age, age squared, gender, education, marital status, self-rated health, race, presence of children, net worth brackets, and indicator variables for missing responses for each variable, in addition to dummy variables for the type of community in which the individual currently resides.

9

correlated with lifetime earnings.14

We then investigated how much “other” sources of income matter among individuals

(938 respondents, or about 36 percent of the sample) who answered four different income

questions: total monthly income, Social Security benefits, pension income, and other regular

income from sources such as assets, businesses, or government assistance. We compared the

sum of Social Security and pension benefits to total income. About 61 percent reported that

Social Security benefits and pension income are their major sources of income, while other

sources of income matter substantially for the remaining 39 percent.

However, even after we control for wealth and demographic

information, we find that community type remains significant. IL residents have higher lifetime

earning than AL residents. Residents in the AL portion of the combined IL/AL community have

12 percent lower lifetime earnings, and residents in freestanding AL communities have 19

percent lower lifetime earnings than residents in freestanding ILs.

Overall, the income statistics suggest that most survey respondents are mid- to high-

income, especially for these ages, and, on average, their income covers most or all of their

monthly fees.

3. Assets

Table 4 presents the total net worth and asset holdings by each community. Unlike the

income picture, the self-reported total net worth is quite low, and more skewed to the left than

the general aged population. One-fifth to one-third of the residents reported their total net worth

as less than $50,000. Calculations from the HRS of individuals age 65-plus show that one-fifth

of the population reports their total net worth as less than $50,000. The median response for

three of the four living arrangements in the RFS is a net worth between $100,000 and $300,000,

consistent with calculations from the HRS.15 Table 4 also reports the percent of the respondents

in each living arrangement that own different types of assets. Long-term care (LTC) insurance

holding is comparable to that found in the U.S. age 65-plus population.16

14 We estimated a similar model using the Health and Retirement Study and find that relationship between lifetime income and the demographic characteristics (age, age squared, gender, college educated, married, self-reported health, race, and presence of children) is remarkably similar to what we find using the survey data.

Ten to 15 percent hold

15 For IL-residents living in combined IL/AL communities, the median net worth is between $300,000 and $500,000. 16 The authors’ calculations from the HRS find that 14.1 percent of the 65-plus population held private long-term care insurance in 2008.

10

a trust and, surprisingly, one-fifth to one-quarter still own a house, property, or land.17

One reason the net worth picture seems so different from the income statistics is the

active conversion from assets to income among this population, such as buying annuities. Table

5 presents the cross-tabulation between income and assets for freestanding IL residents. Two

things emerge from this table. First, low-income individuals are also low-asset individuals. The

stereotype is that these types of communities do not serve low-income seniors, but this is not true

in the data. These low-income and low-asset individuals could be long-term disabled or

individuals who have spent down their savings. The average monthly lifetime earning measure

(AIME) for the group in the lowest net worth and income categories is under $1,400, suggesting

at least some were lifetime low-earners. Second, low-net-worth individuals are not necessarily

low-income. Median income among the lowest three net worth categories is between $2,000 and

$2,500 per month.

Many

also indicated that they owned antiques, jewelry, gold, and other personal items that could be

sold if needed.

To further explore net worth, Figure 1 presents the distribution by age.18

Given this counterintuitive correlation between age and net worth, we explore the

relationship further using regression analysis.

Typically, one

finds a relatively stable or negative relationship between net worth and age within this

population, meaning that older individuals have the same or lower total net worth. This does not

seem to be the case for these residents. Younger residents report lower net worth. The median

net worth is $100,000 to $300,000 for all age groups, except those under age 77, where the

median is between $50,000 and $100,000.

19

17 This category includes time-shares.

The results are presented in Table 6. Not

surprisingly, monthly income is positively correlated with net worth, as is being college-educated

and being in excellent or very good health. African-Americans in the sample have lower net

worth, all things held constant. Women, surprisingly, report higher net worth, even after

18 Due to sample size concerns, Figure 1 presents all respondents together regardless of community type. 19 We estimated an ordered probit model. The outcome variables are net worth in 8 categories: under $50,000, $50,000 to $100,000, $100,000 to 299,999, $300,000 to 499,999, $500,000 to 749,999, $750,000 to $999,999, $1,000,000 to 1,999,999, $2,000,000 or more. The explanatory variables include age, gender, race, education, marital status, indicators for health status, measure of length being in the current community, whether lived in another age-qualified community before, total current income, lifetime income, total net worth, whether have given a monetary gift in a single year of more than $10,000 in the last five years, indicators for having moved to a state with more generous Medicaid regulations and for current living arrangements.

11

controlling for marital status. Controlling for all of these demographics does not eliminate the

positive correlation between age and net worth, however. We suspect this is due to differential

mortality – richer individuals tend to live longer, and these correlations are simply picking up a

survival bias. To check this theory, we ran similar regressions using the HRS dataset for

individuals over age 65. We again find this positive correlation, suggesting that this pattern,

while counterintuitive, is not due to problems with the data or unusual behavior within the

sample and warrants further investigation within the overall older population.

4. Evidence of Spending Down or Giving Away Assets?

We wanted to see if net worth is related to the time one has lived in their current

community, something that could not be done in much of the previous work that either did not

measure the time in the community (Coe and Boyle 2012) or focused on new entrants

(Independent Living Report). Interestingly, we find that years spent in the current community is

not correlated with net worth, once controlling for other factors. Further exploration of the data

suggests that net worth remains uncorrelated with time living in the community even after the

sample is limited to the respondents that have only lived in their current age-eligible community.

However, we do find that individuals who have moved between two or more communities have

significantly less wealth. Figure 2 shows how the distribution of net worth has shifted: more

people who had lived in another community have less than $300,000 in net worth. Figure 3

illustrates the relationship between income and net worth, holding all else constant. It is clear

that as one progresses up the income distribution, the asset distribution tends to follow. But it

also illustrates that there is a lot of heterogeneity in the income-net worth distributions, with 13

percent of the lowest income group having a predicted net worth of at least $1 million, and 7

percent of the highest income group having a predicted net worth of less than $100,000.

Giving a substantial gift is positively correlated with net worth. The raw tabulations

show that about 14 percent of the sample reported that they have given a monetary gift of more

than $10,000 to a person or entity in a single year, excluding college tuition and weddings (Table

4). Residents in the IL portion of IL/AL communities are more likely to give financial gifts (17

percent). There is huge variation in terms of the value of financial gifts given in the past five

years: among 340 respondents who reported the value of the gifts, the mean is $73,000 while the

median is $40,000. When examining the relationship between net worth and gift giving, we find

12

that individuals who have given gifts are still substantially richer than those who have not,

holding other things constant (Figure 4).

To further explore gift-giving behavior, we conduct regression analysis on the probability

of giving a gift.20

The regression results, presented in Table 7, show that older residents and

those who have a college degree are more likely to give a gift, while women, African-Americans,

and residents who are currently married are less likely to give gifts. Health – and likely

longevity expectations – could be an important factor in gift-giving behavior. Those who rated

their health as excellent, very good, or good are less likely to give a gift while those who

experienced a decline in health in the past two years are more likely to give gifts. However, the

relationship between the likelihood of giving a gift and health loses significance when net worth

is controlled for. Residents who have the total net worth of $300,000 and above are much more

likely to give a gift compared to those have less than $300,000. In addition, residents of the IL

portion of IL/ALs are relatively more likely to give gifts than residents of other types of

communities. In some specifications, we also controlled for whether respondents moved from a

state with financial eligibility rules set at the minimum levels allowed under federal law for

Medicaid. Interestingly, gift giving is not correlated with the generosity of the state’s Medicaid

rules – either the state one is moving from or the state one is currently living in. Thus, it does

not seem that gift giving is a way for residents to get rid of their money sooner in order to qualify

for Medicaid.


Overall, the survey responses suggest that residents in IL and AL communities are mid-

to high-income households who receive most of their income in annuitized forms: Social

Security, pensions, and private annuities. Investment income is also relatively common. The

assets profile of the survey respondents is very interesting and a few facts are worth noting.

First, low-income individuals are also low-asset individuals, but the converse is not true – low-

asset individuals do not necessarily have low incomes. Part of that is due to active conversion

between assets and income, including high annuitization rates. Second, despite the active spend-

down of assets reported, the cross-sectional evidence shows that assets are positively correlated

20 We estimated a probit model. The marginal effects are presented in Table 7. The explanatory variables include age, gender, race, education, marital status, indicators for health status, having children, the length of time living in the current community, total net worth, and indicators for current living arrangement.

13

with age, and not correlated with the time since the individual moved into the community. This

could be due to positive mortality selection, and suggests that follow-up work is needed to

reconcile the cross-sectional patterns with the self-reported accounts of how seniors pay for their

community and care. Finally, while net worth is not correlated with time in the current

community, individuals who have moved between different types of communities do have less

wealth. Further work could examine whether the lower wealth levels caused the move – i.e., one

could no longer afford the fees at one community and moved out – or whether these individuals

have simply lived in care communities longer overall and are simply spending down their assets

over a longer period.

14

References Assisted Living Federation of America (ALFA). 1998. The Assisted Living Industry: An

Overview – 1998. Fairfax, VA: Price Waterhouse and ALFA. Bank of America. 2008. “Bank of America Survey Finds Despite Tightening Their Wallets,

Americans Are Further from Achieving Their Retirement Goals Amidst Weakening Economy.” Boston, MA.

Coe, Norma B. and Melissa Boyle. 2012. “The Asset and Income Profile of Residents in

Seniors Care Communities.” Research on Aging, forthcoming. Coe, Norma B. and April Yanyuan Wu. 2012. “Residents in Seniors Housing and Care


Munnell, Alicia, H., Francesca Golub-Sass, and Dan Muldoon. 2009. “An Update on 401(k)

Plans: Insights from the 2007 SCF.” Issue in Brief 9-5. Chestnut Hill, MA: Center for Retirement Research at Boston College.

National Investment Center for the Seniors Housing & Care Industry. 1998. “National Survey of

Assisted Living Residents: Who is the Customer?” Annapolis, MD. “The Independent Living Report.” 2009. Washington, DC: American Seniors Housing

Association.

15

16

17

18

19


Average ageMedian ageNon-response % % % %


Male % % % %Non-response

African-American % % % %WhiteNon-response

Married % % % %WidowedDivorcedNon-response

Less than high school % % % %College educatedNon-response

Average number of childrenMedian number of childrenNon-response % % % %

Self rated excellent or very good % % % %Non-responseSame/better compared to two years ago Non-response

Source : Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 1 for calculations of the percentages that treat non-response as missing observations.

Health*31.5 37.6 27.8 27.3

Number of children

2.0 2.0 2.0 2.0

28.3 40.6 23.1 29.14.2 2.8 1.6 3.0

Education*

2.5 2.5

82.6 83.4 83.7 83.2

58.9 51.3 53.2

8.0 9.6 7.2 4.9

2.3 2.2

12.6 4.5 13.5 10.6

2.5

880 406

13.2 20.1 9.4 15.5

4.0 2.6 1.5 2.7

3.8 2.3 1.3 2.756.4

Observations 477 854

66.9 67.5 71.7 67.79.9 5.9 11.5 8.93.6 2.3 1.3

Marital status*

4.2 2.9 1.8 3.7Race*

2.7 1.0 0.8 0.396.3 96.1

3.8 2.6 1.4 2.792.0 94.5

Current age86.2 86.4 86.4 86.3

Gender*28.5 34.7 24.9 30.5

83.7 83.9 84.8 84.814.5 14.4 11.1 13.1


Freestanding IL

Combined IL Combined ALFreestanding AL

87.0 87.0 87.0 87.07.3 5.2 3.3 5.2

20

Table 2. Income Information, by Community Type

< $850 % % % %$850-$1,200$1,200-$1,500$1,500-$2,000$2,000-$2,500$2,500-$3,000$3,000-$3,500$3,500+QuestionableNon-response

Income by source (multiple answers possible)Social Security % % % %Pension/annuityInterest from bank accountsInterest from stocks/bondsRental incomeBusiness or farmTrust fundReverse mortgageMedicaidSSIFood StampsHUD rental assistanceOther means-tested sources

Lifetime earnings measure (AIME)Average value $ 3,911 $ 4,130 $ 3,327 $ 3,915Median value $ 3,364 $ 3,390 $ 2,895 $ 3,083

Source: Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 1 for calculations of the percentages that treat non-response as missing observations.

Observations 477 854 880 406

Freestanding IL


Combined AL

6.7 3.2 9.1 7.47.1 5.2 10.2 8.1

Monthly income amount*2.3 0.7 4.3 3.9

12.6 10.9 10.5 7.1

13.2 9.1 12.2 11.313.8 11.4 11.6 8.9

9.0 13.0 9.1 9.1

7.3 10.1 8.8 7.9

43.5 56.2 33.3 44.1

98.0 97.8 97.2 96.7

26.6 34.1 22.8 34.01.3 2.5 1.5 2.2

7.0 7.7 6.2 8.4

66.9 68.6 58.7 61.546.0 55.2 44.2 47.3

0.2 0.3 3.6 0.54.2 1.6 8.5 8.2

2.5 2.2 1.3 3.64.3 7.0 3.4 7.1

2.2 0.3 0.0 0.50.6 0.1 0.0 0.5

0.9 0.0 3.5 1.81.5 0.1 0.2 2.6

21

Table 3. Characteristics correlated with Lifetime Earnings (log)Coefficient Standard

ErrorAge 0.251 *** 0.039Age squared (in hundreds) -0.159 *** 0.023Female -0.059 0.043College educated -0.050 0.046Currently married 0.309 *** 0.059Excellent/very good health (self-rated) 0.068 * 0.041Have children 0.164 ** 0.065Black 0.007 0.150Total net worth (in thousands)

$50-$100 -0.004 0.059$100-$300 0.052 0.052$300-$500 -0.060 0.074$500-$750 0.111 0.080$750-$1,000 0.108 0.084$1,000-$2,000 0.200 ** 0.096$2,000+ 0.266 ** 0.107

In IL portion of IL/ALs -0.078 0.052In freestanding AL -0.190 *** 0.049In AL portion of IL/ALs -0.115 * 0.060Observations 1,968 Note : We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

22

Table 4. Asset Information, by Community Type

< $50 % % % %$50-$100$100-$300$300-$500$500-$750$750-$1,000$1,000-$2,000$2,000+Non-response

LTC insurance % % % %Checking/savingsBrokerage/stocks/bonds401(k), IRATrustHouse, property, landFarm, businessAutomobile

Gifts given in the last five years*Yes 11.3 % 17.4 % 12.2 % 13.6 %No 84.5 77.5 83.6 82.8Non-response 4.18 5.03 4.2 3.7

The total value of the gifts givenAverage value $ 72,751 $ 70,943 $ 72,512 $ 80,196Median value $ 50,000 $ 39,671 $ 40,000 $ 41,000



2.5 2.6 1.4 1.328.3 40.2 15.0 17.2

10.5 14.6 10.3 12.020.9 17.7 23.6 23.7

40.3 56.5 34.5 48.418.9 26.9 17.3 18.8

86.9 90.6 84.9 84.98.4 13.9 14.2 17.5

Asset types (multiple answers possible)11.5 13.8 15.0 12.8

5.7 8.3 4.6 3.7

1.9 4.5 2.3 3.55.5 6.4 3.6 5.7

17.2 16.6 18.4 17.57.1 12.7 9.9 8.96.9 9.5 6.3 7.6

11.5 10.5 11.4 13.6

Total net worth (in thousands)*32.7 17.7 28.6 26.9

Freestanding IL


Combined AL

23

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.912

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.7$3

00,0

00-$

499,

999

0.0

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5.9

2.9

8.8

23.5

20.6

38.2

$500

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9 0.

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03.

06.

19.

19.

115

.254

.5$7

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7.4

3.7

18.5

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66.7

$1,0

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00-$

1,99

9,99

90.

00.

00.

03.

83.

87.

73.

880

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.7So

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: A

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rs' c

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he R

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ents

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y.N

ote:

Row

per

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ages

are

show

n.

Tabl

e 5.

Inco

me

vs. N

et W

orth

in F

rees

tand

ing

ILs

Inco

me

< $8

50$8

50-$

1,20

0$1

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-$1,

500

$1,5

00-$

2,00

0$2

,000

-$2,

500

$2,5

00-$

3,00

0$3

,000

-$3,

500

$3,5

00+

24

Table 6. Characteristics Correlated with Net Worth Coefficient Standard

ErrorAge 0.115 ** 0.050Age squared (in hundreds) -0.059 * 0.030Female 0.215 *** 0.059College educated 0.271 *** 0.054Currently married 0.118 0.071Excellent/very good health (self-rated) 0.255 *** 0.053Same/somewhat better/much better (compared to two years ago) -0.023 0.049

-0.088 0.081Black -0.597 ** 0.235Years in current community -0.010 0.008Lived in another age-qualified community before -0.157 *** 0.053Gave monetary gift in the past 5 years 0.614 *** 0.071Monthly income amount

$850-$1,200 0.332 0.226$1,200-$1,500 0.516 ** 0.219$1,500-$2,000 0.550 ** 0.216$2,000-$2,500 0.706 *** 0.215$2,500-$3,000 0.791 *** 0.217$3,000-$3,500 0.988 *** 0.218$3,500+ 1.486 *** 0.216

Moved to a state with more generous Medicaid regulations 0.137 0.116Moved to a state with less generous Medicaid regulations -0.065 0.105In IL portion of IL/ALs 0.289 *** 0.067In freestanding AL 0.082 0.067In AL portion of IL/ALs 0.067 0.081Cut 1 -0.330 0.327Cut 2 0.088 0.328Cut 3 0.701 0.329Cut 4 1.124 0.329Cut 5 1.518 0.329Cut 6 1.926 0.331Cut 7 2.536 0.333Observations 2,212 Note : We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

Have children

25

Standard Error

Age 0.028 ** 0.014Age squared (in hundreds) -0.015 * 0.008Female -0.032 ** 0.016College educated 0.041 *** 0.015Currently married -0.039 ** 0.015Excellent/very good health (self-rated) 0.007 0.015Same/somewhat better/much better (compared to two years ago) -0.018 0.014Have children 0.002 0.021Black -0.080 *** 0.027Years in current community 0.001 0.002

0.014 0.015Monthly income amount

More than $2,000 0.094 *** 0.015Total net worth (in thousands)

$50-$100 0.030 0.029$100-$300 0.012 0.024$300-$500 0.031 0.029$500-$750 0.194 *** 0.042$750-$1,000 0.222 *** 0.048$1,000-$2,000 0.402 *** 0.054$2,000+ 0.366 *** 0.067

Moved to a state with more generous Medicaid regulations 0.031 0.037Moved to a state with less generous Medicaid regulations 0.005 0.027In IL portion of IL/ALs 0.026 0.020In freestanding AL 0.019 0.020In AL portion of IL/ALs 0.016 0.024Observations 2,453Note : We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

Table 7. Probability of Giving a Monetary Gift of More than $10,000 in the Last Five YearsMarginal

Effect

Lived in another age-qualified community before

26


Male 29.8 % 35.7 % 25.4 % 31.7 %

African-American 2.8 % 1.0 % 0.8 % 0.3 %White 95.6 97.0 97.6 98.7

Married 13.7 % 20.6 % 9.5 % 15.9 %Widowed 69.3 69.1 72.6 69.4Divorced 10.2 6.0 11.6 9.1

Less than high school 13.1 % 4.6 % 13.7 % 10.9 %College educated 29.5 41.8 23.4 29.9

Self rated excellent or very good 32.7 % 38.5 % 28.2 % 28.1 %Same/better compared to two years ago 58.7 60.5 52.0 54.7

< $850 2.5 % 0.8 % 4.8 % 4.4 %$850-$1,200 7.3 3.6 10.1 8.2$1,200-$1,500 7.8 5.9 11.4 9.0$1,500-$2,000 14.5 10.4 13.5 12.6$2,000-$2,500 15.1 13.0 12.9 9.9$2,500-$3,000 13.8 12.4 11.6 7.9$3,000-$3,500 9.9 14.9 10.1 10.1$3,500+ 29.1 39.0 25.4 37.8

< $50 37.0 % 20.5 % 33.7 % 30.8 %$50-$100 13.0 12.2 13.4 15.5$100-$300 19.4 19.3 21.7 20.1$300-$500 8.1 14.7 11.6 10.2$500-$750 7.8 11.0 7.4 8.8$750-$1,000 6.4 9.6 5.4 4.2$1,000-$2,000 6.2 7.5 4.3 6.5$2,000+ 2.1 5.2 2.7 4.0

Gifts given in the last five yearsYes 11.8 % 18.3 % 12.7 % 14.1 %

Source: Authors' calculations of the Residents' Financial Survey.

Marital status

Education

Health

Monthly income amount

Total net worth (in thousands)


Combined AL

Gender

Race

Freestanding IL


27


Residents in Senior Housing and Care Communities: Overview of the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Social Security Claiming: Trends and Business Cycle Effects Owen Haaga and Richard W. Johnson, February 2012

Economic Consequences of the Great Recession: Evidence from the Panel Study of Income Dynamics Barry Bosworth, February 2012 The Changing Causes and Consequences of Not Working Before Age 62 Barbara A. Butrica and Nadia Karamcheva, February 2012 The Impact of Temporary Assistance Programs on Disability Rolls and Re-Employment Stephan Lindner and Austin Nichols, January 2012 Understanding the Growth in Federal Disability Programs: Who Are the Marginal Beneficiaries, and How Much Do They Cost? Adele Kirk, January 2012 What Explains State Variation in SSDI Application Rates? Norma B. Coe, Kelly Haverstick, Alicia H. Munnell, Anthony Webb, December 2011 How Do Subjective Mortality Beliefs Affect the Value of Social Security and the Optimal Claiming Age? Wei Sun and Anthony Webb, November 2011 How Does the Personal Income Tax Affect the Progressivity of OASI Benefits? Norma B. Coe, Zhenya Karamcheva, Richard Kopcke, Alicia H. Munnell, November 2011 The Pension Protection Act of 2006 and Diversification of Employer Stock in Defined Contribution Plans Gary V. Engelhardt, November 2011 Prescription Drug Insurance Coverage, Drug Utilization, and Cost-Related Non-Adherence: Evidence from the Medicare Part D Expansion Gary V. Engelhardt, November 2011


COSTS AND CONCERNS AMONG RESIDENTS IN SENIORS HOUSING AND CARE COMMUNITIES: EVIDENCE FROM THE RESIDENTS FINANCIAL SURVEY


CRR WP 2012-8





Norma B. Coe is associate director for research at the Center for Retirement Research at Boston College (CRR). April Wu is a research economist at the CRR. The research reported here was performed pursuant to a grant from the National Investment Center for the Seniors Housing & Care Industry (NIC), the Assisted Living Federation of America (ALFA), and the American Seniors Housing Association (ASHA). The opinions and conclusion expressed are solely those of the authors and do not represent the opinions or policy of NIC, ALFA, ASHA, or Boston College. The authors are grateful for comments supplied on an earlier draft by Charles Harry. They would also like to thank the team at ProMatura Group, LLC, especially Edie Smith and Margaret Wylde, and Mashfiqur Khan, Madeline Medenica and Zhenya Karamcheva for research assistance. All errors are their own. Corresponding author: Norma B. Coe, Center for Retirement Research at Boston College, Hovey House, 258 Hammond St., Chestnut Hill, MA 02467; Tel: (617) 552-1762; Fax: (617) 552-0191; e-mail: [email protected] © 2012, Norma B. Coe and April Yanyuan Wu. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.

2





crr.bc.edu



Urban Institute

3


2. The Residents Financial Survey Page 4

3. Income and Assets Page 6

4. Costs and Satisfaction with the Community Page 7

5. Paying for the Community Page 8

6. Financial Concerns Page 9



ASSOCIATED PAPERS 1. “Residents in Seniors Housing and Care Communities: Overview of the Residents

Financial Survey” Working Paper 2011-6. Chestnut Hill, MA: Center for Retirement Research at Boston College.

2. “Financial Well-Being of Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey” Working Paper 2011-7. Chestnut Hill, MA: Center for Retirement Research at Boston College.

3. “Geographic Mobility Among Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey” Working Paper 2011-9. Chestnut Hill, MA: Center for Retirement Research at Boston College.

4

Introduction

With the leading edge of the Baby Boom generation reaching traditional retirement ages,

decisionmakers need a comprehensive understanding of the boomers’ social, economic, and

health characteristics – both in terms of resources and needs – in order to adopt effective public

policies and private services to meet the needs of an aging population. One area of particular

importance is their need for housing and long-term care services. A variety of options is

available to meet these needs, including independent living (IL) and assisted living (AL)

residences.1

Despite the general impression that seniors housing and care communities are very

costly, less is known about what types of costs residents of these communities are facing and

how they pay their expenses. To fully understand the current and future economic situation and

various aspects of residents in seniors housing and care communities, we designed and

conducted a new survey, the Residents Financial Survey (RFS), with assistance from ProMatura

Group, LLC, to obtain a current economic profile of individuals living in ALs and ILs. This

survey gathered information on the income and assets at the time of the survey (2011), as well as

retrospective information concerning living arrangements, care provision, and financial gifts

given.

In this paper we use the RFS to explore the costs associated with seniors housing and care

communities and how individuals pay these costs. We also explore the relationship between

individual characteristics and how they pay for their community. We are able to examine how

payment methods are related to how long they have been living in their current community,

something that most of the previous literature could not look at due to data limitations. Finally

we examine the concerns residents have for meeting these financial obligations in the future.

1. The Residents Financial Survey

The Residents Financial Survey, fielded in 2011, was designed to measure the assets and

incomes of individuals in freestanding ILs, freestanding ALs, and communities that offer both IL

and AL arrangements.2

1 Nursing homes and continuing care retirement communities – which include independent living care segments – are also important providers of housing and care, but outside the scope of this research.

The final sample consists of 2,617 respondents. There are 477

individuals, about 18 percent of the whole sample, who live in ILs; 880 (34 percent) live in ALs;

2 See Coe and Wu (2012a) for a detailing of the survey.

5

and 1,260 (more than 48 percent) live in communities that offer both IL and AL arrangements

(with 32.6 percent in the IL portion and 15.5 percent in the AL portion).

Table 1 presents the RFS sample’s characteristics, separated by living arrangement.3 The

average age of our sample is just over 86, with no significant differences across four types of

living arrangements. The age distribution is slightly skewed to the right, with the median

respondent being 87 years old. The age differences between the men and women are significant,

however, with the women being older. Compared to earlier work, our sample is significantly

older.4


higher representation in the other community types (31, 29, and 35 percent for AL portion of

IL/ALs, ILs, and the IL portion of IL/ALs, respectively). While this might seem low, the RFS

has higher male representation for ALs than previous work.

The average age at which our respondents moved into their current community is 83.3

years old, with a median age of 84.4.

5





communities, compared to the U.S. 65-plus population of about 19 percent.

The proportion of men in ILs is

comparable to the samples studied in Coe and Boyle (2012).

6

Marital status varies among the different types of communities. Less than 10 percent of

residents in freestanding ALs are currently married, and 72 percent are widowed. Respondents

in the other community types are much more likely to still be married (16 percent for the AL

portion of IL/ALs, 13 percent for ILs, and 20 percent for the IL portion of IL/ALs). The marital

pattern for ILs and the IL portion of IL/ALs is comparable to that reported by Coe and Boyle

(2012). It is lower than that reported in the Independent Living Report (about 35 percent), but

3 In the tables presented in the paper, we include non-response and questionable answers in the percentages so the reader has the full information. Appendix Table 1 presents the descriptive statistics percentages re-calibrated as a percent of those who answered correctly, instead of the percent of people in the survey, so comparison across the types of communities is easier for the reader. 4Coe and Boyle (2012), the Independent Living Report, ALFA (1998), and NIC (1998) all had average ages of 80-85. 5 See the NIC (1998), ALFA (1998), and Coe and Boyle (2012). 6 Authors’ calculations using the Current Population Survey (CPS), 2010. The fraction of non-white in the CPS is about 17 percent for over-85 population, suggesting that the low minority representation is not just an age-effect.

6

that is not surprising considering their focus was on new entrants and included continuing care

retirement communities (CCRCs) in the sample. For the freestanding ALs and the AL portion of

IL/ALs, our sample is much less likely to be married than the 20-percent marriage rate found in

Coe and Boyle (2012).


residents in these four types of communities is higher than the U.S. as a whole. Specifically,

more than 40 percent of residents in the IL portion of the IL/ALs had a college degree, which is

higher than residents in freestanding ILs (28 percent), freestanding ALs (23 percent), and the AL

portion of the IL/ALs (29 percent). At the same time, only 20 percent of the overall U.S. 65-plus

population has a college degree. The RFS sample exhibits slightly lower educational attainment

than that found in the Independent Living Report.7

Overall, the average number of living children among our sample is almost 2.5, with little

variation between the types of living arrangements. These numbers are comparable to Coe and

Boyle (2012), but slightly lower compared to the overall 65-plus population of almost 3.

8

One-quarter to one-third of the respondents report themselves to be in very good or

excellent health compared to their peers. We also find that more than 50 percent of respondents

rate their current health as “Much better now,” “Somewhat better now,” or “About the same” as

compared to two years ago. Further, there does not appear to be a relationship between health

changes and the length of time living in the current community. This suggests that individuals

are not experiencing rapid or continuous health declines.

2. Income and Assets

Before turning to costs and financial concerns, we first describe the finances of the

residents.9

7 When we compare recent movers to longer-term residents within the RFS, we find similar levels of education among recent movers (33 percent with a college degree versus 30 percent of the longer-term residents), which suggests that the difference with the Independent Living Report is driven by the inclusion of CCRCs being in the sample, which apparently attract an even more educated clientele.

Table 2 presents the descriptive statistics of the income and asset information.

Overall, the RFS suggests that residents in independent living and assisted living communities

8 Author’s calculations of the Survey of Consumer Finances (2007). The average number of living children of the over-85 population is 2.5. 9 Coe and Wu (2012b) use the RFS to examine the income and wealth profile of residents in great detail, and emphasize the importance of both income and assets in assessing financial well-being. Here we discuss the highlights of that paper.

7

are mid- to high-income households who receive most of their income in annuitized forms:

Social Security, pensions, and private annuities. Investment income is also relatively common.

Combining the assets profile with the income information, we find that low-income individuals

are also low-asset individuals. This could be due to some people having long-term disabilities

whose onset was during their working life, thus limiting their ability to earn or accumulate assets

for their retirement years. The converse is not true: low-asset individuals do not necessarily have

low income. This is due in part to active conversion between assets and income and high

annuitization rates.

Another interesting finding from Coe and Wu (2012b) is that despite the active spend-

down of assets reported, the cross-sectional evidence shows that assets are positively correlated

with age, and not correlated with the time since the individual moved into the community. This

is likely due to positive mortality selection. Finally, while net worth is not correlated with time

in the current community, we find that individuals who have moved between different types of

communities have lower wealth. This could be due to lower wealth causing the move – i.e. one

could no longer afford the fees at one community and therefore moved out – or by living in care

communities longer overall and thus are simply spending down their assets over a longer period.

3. Costs and Satisfaction with the Community

On average, the residents in ALs and the AL portion of IL/ALs paid more for their

residence and services they received in the community, which correlates with the higher level of

services provided (Table 3).10

In addition to their monthly bill, a small fraction of residents, about 13 percent in total,

report that they pay for additional services provided by other agencies. Among residents who

report these additional expenses, those in the assisted living communities pay more, on average,

($1,343 for residents in freestanding ALs and $2,021 for those in the AL portion of IL/AL), than

residents in the independent living communities. The types of services this additional money

Self-reported monthly bills for residents in these communities is

$3,741 and $3,655 on average per person, respectively, compared to $2,442 for ILs and $2,809

for the IL portion of IL/ALs. We also find significant variation within each living arrangement,

with the greatest variation occurring in assisted living communities.

10 We report item non-response and the percent of questionable answers as separate categories for each variable of interest. See Appendix Table 1 for the statistics recalculated as a percent of the valid responses.

8

buys include caregivers/care companion/helper, medication assistance, and personal care.

Including the additional fees, residents on average pay $3,271 for the housing and care they

receive, while those in assisted living communities pay more ($3,832 for residents in

freestanding ALs and $3,803 for those in the AL portion of IL/AL), than residents in the

independent living communities.

4. Paying for the Community

While residents differ in their monthly bill and fees, they also differ in how they pay

these expenses. Figure 1 shows that about 40 percent of residents in the IL portion of IL/ALs

reported that all of their expenses are covered by their current income, with an additional 28

percent stating that their current income covers most of their expenses. In contrast, only 21

percent in the ALs reported all of their expenses are covered by their current income, with an

additional 26 percent stating most expenses are covered by their current income. We also find

that a vast majority of residents – over 84 percent – report that they are the primary payer by

themselves, either with current income combining with spending down their savings and/or

assets. Less than 5 percent of our sample, across all communities, indicates that their family is

the primary payer. These statistics are in-line with recent work reported in the Overview of

Assisted Living (2009), where 80 percent of the sample report themselves to be the primary

payer.

We then examined how residents are paying for their remaining housing and care

expenses in Table 4. Among those residents with most expenses covered by their current

income, 86 percent reported that savings and assets are used to pay for the housing and care and

19 percent indicated that they receive help from family. Those who reported that none of their

expenses are covered by current income are more reliant on their families, with 27 percent

reporting getting help from family and 77 percent reporting spending down savings and/or assets.

Furthermore, about 11 percent in this group reported using both savings and family assistance.

Breaking down the sample by the type of community shows that, among those whose expenses

are not fully covered by the current income, residents of the IL portion of IL/AL are more likely

to spend down savings and assets, and less likely to rely on family, while residents of

freestanding ALs show the reverse pattern.

9

We also found that among those who reported that all of their expenses are covered by

their current income, 16 percent own a private long-term care insurance policy. Interestingly,

those who report none of their current expenses are paid by their income are actually more likely

to own long-term care insurance. This could indicate that individuals are not considering their

insurance coverage as income or that their insurance does not cover their current community.

To double check the accuracy of the self-reported payment method, we examined the

income sources of those reporting that none of their expenses are covered by current income.

We find that they are less likely to have income from pensions, bank accounts, stocks or rents,

but much more likely to have Medicaid. This pattern of income sources helps to confirm their

assessment of not substantially contributing to their care from current income.

We explore the correlations between individual factors and how people pay for their

community and care expenses using regression analysis.11

The coefficients are reported in Table

5. Not surprising, higher wealth and higher education are associated with paying more of the

community costs out of your own income. Single men are also more likely to be paying more of

their costs out of their own income than single women and married couples. Interestingly, those

who have lived in their current community for more than four years are actually more likely to

be paying more of their bills out of their own income. Because the coefficients do not have a

direct interpretation beyond the direction, Figure 2 presents the marginal effect of the time living

in the current community on the predicted probability of paying expenses out of current income.

Compared to individuals who have lived in their community for less than 4 years, those living

there 4 years or longer are 7 percentage points more likely to pay for their community fees

completely out of their current income, with the differences mostly coming from being less

likely to have their current income pay for some of their expenses.

5. Financial Concerns

When asked whether their current community offers good value, a majority of

respondents, across all community types, stated they either “strongly agree” or “agree,” while

11 We estimated an ordered probit, with 1 being that they pay nothing for their current expenses, and 4 that they pay all of their expenses out of current income. Covariates include the length of time staying in the community, an indicator for a long-distance mover, household type indicators (single men, married couples, with single women being the omitted category), education, self-reported health, current health compared to two years ago, race, whether this is their first time in an age-qualified community, net worth, the natural log of their housing costs, the type of community, and the natural log of lifetime earnings.

10

about one-third were neutral. Less than 10 percent disagreed or strongly disagreed with the

statement, suggesting very little discontent.12

These concerns are likely tied to the macroeconomy. Between October 9, 2007 and

March 9, 2009, the stock market lost over 56 percent of its value (as measured by the Wilshire

5000 index), impacting individuals who need to use their assets invested in the stock market.

Housing lost one-third of its value between the fourth quarter of 2006 and the first quarter of

2009, impacting anyone who still owns a house – including their current residence – and was

planning on using that money to fund consumption before the market has time to recover.

While people are satisfied with the costs and

services, there is concern about their ability to afford the fees. Overall, about 40 percent of

respondents expressed “some concern” and an additional 15-30 percent indicated “considerable

concern.” Residents in ALs show the most concern about their ability to afford the fees, with

about 70 percent expressing some or considerable concern (Table 3).

13

Further, overall inflation was low or negative, causing Social Security to not give a cost of living

adjustment (COLA) for 2010 and 2011. That likely happened to other defined benefit pension

plans, if they had a COLA to begin with. While this means that their incomes likely remained

stable, their medical costs are likely increasing. Overall medical costs increased by 6.3 percent

between September, 2009 and September, 2011.14 Given this macro-environment, concern about

ability to pay bills in the future is not unfounded. According to a survey by the LIFE

Foundation, 64 percent of Americans age 45 and older say that the recent economic downturn

has had a major negative impact on their ability to pay for long-term care services.15

12 Coe and Wu (2012c) delves into this issue of discontent further by examining plans to move out of the community, both why and where individuals plan to move.

While most

academic work to date has focused on individuals nearing retirement age instead of the currently

retired, concerns about the financial future are relatively widespread. The 2008 Bank of America

Retirement Saving Survey finds that more than 40 percent of workers felt they faced more years

in the workforce than expected a year ago. The 2009 Retirement Survey, a nationally

representative survey of individuals age 45-59, finds that half of the population would change

their future work and/or retirement decisions because of the downturn (Munnell et al. 2010).

13 “The NRRI and the House.” 2010. NRRI Fact Sheet No 1. Chestnut Hill, MA: Center for Retirement Research at Boston College. 14 Authors’ calculations of the CPI-medical care (CUSR0000SAM) series. 15 The LIFE survey was conducted by KRC Research October 30 – November 2, 2008. The survey polled a nationally representative sample of 1,006 Americans, ages 18 and older via telephone. The survey has a margin of error of +/- 3.1 percent at the 95 percent confidence level. More information can be found at www.lifehappens.org/.

11

We further explored factors that relate to concerns about the ability to afford the fees in

the context of regression analysis (Table 6).16

We present the marginal effect of the self-perceived value of the community to their

financial concerns in Figure 3. This figure illustrates that, controlling for income, net worth and

the cost of the community, the self-perceived value is in itself an important factor in determining

financial concerns. Eighty-eight percent of people who report their community is a good value

are not concerned or only somewhat concerned about their ability to pay. On the contrary, 44

percent of individuals who say they are not getting a good value report they are very concerned

about their ability to pay. This could be reflecting the fact that the most financially constrained

individuals are also the most likely to demand high quality services for their money.

Alternatively, this pattern could occur because individuals who do not feel like they are getting a

good value for the money are reporting their willingness to continue paying the monthly fees,

instead of their ability to pay these fees.

The results show that those who stated they

“strongly agree” or “agree” that their current community offers good value are much less likely

to have concerns about their ability to afford the fees. Respondents who are currently married

are more likely to have concerns. Not surprisingly, high-income residents and those with higher

net worth are much less likely to be concerned about their ability to pay. Interestingly, those

who rate themselves in excellent or good health and who state their current health is better or the

same as two years ago, holding income and asset levels constant, are less likely to have financial

concerns despite their likely longer lifespan. Furthermore, respondents who pay higher fees in

housing and care are more likely to have concerns, again, holding wealth and income constant.


The timing of the RFS, fielded in the summer of 2011, is at least one reason why we find

that residents are concerned about their ability to continue to pay for their community and care

costs. We find that individuals overwhelmingly report that they are self-reliant, with very few

relying on family to pay for their community and care. The average monthly fees range between

$3,200 and $3,800 per month, after accounting for additional services individuals pay for that are 16 We estimated an ordered probit model. The explanatory variables include age, gender, race, education, years living in the current community, whether lived in another age-qualified community beforehand, distance moved to current community, income, total net worth, self-rated value of the community, and indicators for health and marital status. The magnitude of the coefficients in Table 6 cannot be directly interpreted, but give an indication of the direction of the correlation.

12

not included in their monthly bill from the community. While about one-third report paying for

these expenses out of their income alone, many report actively spending down their assets for

their care. Given the relatively recent stock market and housing market drops, being concerned

about their ability to continue paying these bills seems reasonable. Overwhelmingly, though,

residents feel as if they are getting good value for their money. Those who are not satisfied with

the services they are receiving for their monthly payments are much more likely to be concerned

about their ability to pay. Since 40 percent of respondents expressed “some concern” and an

additional 15-30 percent indicated “considerable concern,” further exploration is warranted on

how these concerns relate to plans about moving out of the community.

13

References Assisted Living Federation of America (ALFA). 1998. The Assisted Living Industry: An

Overview – 1998. Fairfax, VA: Price Waterhouse and ALFA. Bank of America. 2008. “Bank of America Survey Finds Despite Tightening Their Wallets,

Americans Are Further from Achieving Their Retirement Goals Amidst Weakening Economy.” Boston, MA.

Coe, Norma B. and Melissa Boyle. 2012. “The Asset and Income Profile of Residents in

Seniors Care Communities.” Research on Aging, forthcoming. Coe, Norma B. and April Yanyuan Wu. 2012a. “Residents in Seniors Housing and Care


Coe, Norma B. and April Yanyuan Wu. 2012b. “Financial Well-being of Residents in Seniors

Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2012-7. Chestnut Hill, MA: Center for Retirement Research at Boston College.

Coe, Norma B. and April Yanyuan Wu. 2012c. “Geographic Mobility among Residents in

Seniors Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2012-9. Chestnut Hill, MA: Center for Retirement Research at Boston College.

Munnell, Alicia H., Norma B. Coe, Kelly Haverstick, and Steven A. Sass. 2010. “Overview of

the CRR 2009 Retirement Survey.” Working Paper 2010-15. Chestnut Hill, MA: Center for Retirement Research at Boston College.

National Investment Center for the Seniors Housing & Care Industry (NIC). 1998. “National

Survey of Assisted Living Residents: Who is the Customer?” Annapolis, MD. “Overview of Assisted Living.” 2009. Washington, DC: American Association of Homes and

Services for the Aging, American Seniors Housing Association, National Association for Assisted Living; Alexandria, VA: Assisted Living Federation of America; and Annapolis, MD: National Investment Center.

“The Independent Living Report.” 2009. Washington, DC: American Seniors Housing

Association. “The NRRI and the House.” 2010. NRRI Fact Sheet No 1. Chestnut Hill, MA: Center for

Retirement Research at Boston College.

14

15

16

17





African-American % % % %WhiteNon-response

Married % % % %WidowedDivorcedNon-response

Less than high school % % % %College educatedNon-response

Average number of childrenMedian number of childrenNon-response % % % %

Self rated excellent or very good % % % %Non-responseSame/better compared to two years ago Non-response

Source : Authors' calculations of the Residents' Financial Survey.*: See AppendixTable 1 for calculations with the percentages that treat non-response as missing observations.


56.4 58.9 51.3 53.24.0 2.6 1.5 2.7

Health*31.5 37.6 27.8 27.3

3.8 2.3 1.3 2.7

2.0 2.0 2.0 2.08.0 9.6 7.2 4.9

4.2 2.8 1.6 3.0Number of children

2.5 2.5 2.3 2.2

Education*12.6 4.5 13.5 10.628.3 40.6 23.1 29.1

9.9 5.9 11.5 8.93.6 2.3 1.3 2.5

Marital status*13.2 20.1 9.4 15.566.9 67.5 71.7 67.7

92.0 94.5 96.3 96.13.8 2.6 1.4 2.7

4.2 2.9 1.8 3.7

2.7 1.0 0.8 0.3

82.6 83.4 83.7 83.283.7 83.9 84.8 84.8

Race*

14.5 14.4 11.1 13.1Gender*

28.5 34.7 24.9 30.5

7.3 5.2 3.3 5.2

Freestanding IL


Combined AL


Current age86.2 86.4 86.4 86.387.0 87.0 87.0 87.0

18

Table 2. Income and Asset Information, by Community Type

< $850 % % % %$850-$1,200$1,200-$1,500$1,500-$2,000$2,000-$2,500$2,500-$3,000$3,000-$3,500$3,500+QuestionableNon-response

Income by source (multiple answers possible)Social Security % % % %Pension/annuityInterest from bank accountsInterest from stocks/bondsRental incomeBusiness or farmTrust fundReverse mortgageMedicaidSSIFood StampsHUD rental assistanceOther means-tested sources

< $50 % % % %$50-$100$100-$300$300-$500$500-$750$750-$1,000$1,000-$2,000$2,000+Non-response

Source: Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 1 for calculations with the percentages that treat non-response as missing observations.

Observations 477 854 880 40611.5 13.8 15.0 12.8

5.5 6.4 3.6 5.71.9 4.5 2.3 3.5

7.1 12.7 9.9 8.96.9 9.5 6.3 7.65.7 8.3 4.6 3.7

Total net worth (in thousands)*32.7 17.7 28.6 26.9

17.2 16.6 18.4 17.511.5 10.5 11.4 13.6

26.6 34.1 22.8 34.01.3 2.5 1.5 2.27.3 10.1 8.8 7.9

12.6 10.9 10.5 7.19.0 13.0 9.1

Monthly income amount*

6.7 3.2 9.1 7.47.1 5.2 10.2 8.1

2.3 0.7 4.3 3.9

9.1

Freestanding IL


Combined AL

13.2 9.1 12.2 11.313.8 11.4 11.6 8.9

98.0 97.8 97.2 96.7

46.0 55.2 44.2 47.366.9 68.6 58.7 61.5

7.0 7.7 6.2 8.443.5 56.2 33.3 44.1

4.3 7.0 3.4 7.12.5 2.2 1.3 3.6

0.2 0.3 3.6 0.54.2 1.6 8.5 8.20.9 0.0 3.5 1.8

0.6 0.1 0.0 0.52.2 0.3 0.0 0.51.5 0.1 0.2 2.6

19

Average $ 2,442 $ 2,809 $ 3,741 $ 3,65525 percentile $ 1,780 $ 1,995 $ 2,800 $ 2,52150 percentile $ 2,250 $ 2,700 $ 3,500 $ 3,70075 percentile $ 2,967 $ 3,495 $ 4,500 $ 4,767Questionable % % % %Non-response % % % %

Percent paid % % % %Average additional amount (among people who paid) $ 636 $ 905 $ 1,343 $ 2,021Median additional amount (among people who paid) $ 295 $ 300 $ 400 $ 535

Average $ 2,553 $ 2,884 $ 3,832 $ 3,803Median $ 2,360 $ 2,700 $ 3,500 $ 3,729Non-response % % % %

Strongly agree % % % %AgreeNeutralDisagreeStrongly disagreeNon-response

No concern % % % %Some concernConsiderable concernNon-response


Monthly bill per person

Table 3. Costs and Concerns of the CommunityFreestanding

ILCombined IL Freestanding

ALCombined AL

5.5 2.3 9.9 4.76.7 10.4 13.6 11.8

14.9 14.6 13.8 17.0The community offers me good value for my money*

Additional fees20.7 10.3 9.9 13.8

Total monthly bill per person

6.5 10.4 13.6 11.8

1.7 1.9 1.9 1.0

46.1 43.4 40.8 41.630.4 31.6 33.0 32.3

6.3 7.0 8.9 7.40.6 1.4 1.7 0.7

Relative to my ability to afford the fees*

44.7 44.9 39.7 41.928.5 34.1 23.9 28.6

21.2 15.0 30.0 23.95.7 6.1 6.5 5.7


20

Tabl

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21

Table 5. Characteristics correlated with how respondents pay their expensesCoefficient Standard

ErrorStayed in current communtity for 2 to 4 years 0.024 0.058Stayed in current communtity for more than 4 years 0.189 *** 0.062Moved over 100 miles to live in current residence 0.044 0.058Single male 0.369 *** 0.060Currently married 0.024 0.070College educated 0.144 *** 0.053Excellent/very good health (self-rated) 0.041 0.053Same/somewhat better/much better health compared to two years ago 0.115 ** 0.049Black 0.144 0.235Lived in another age-qualified community before -0.037 0.052Total net worth (in thousands)

$50-$100 0.002 0.080$100-$300 -0.042 0.071$300-$500 0.064 *** 0.085$500-$750 0.421 *** 0.097$750-$1,000 0.392 *** 0.110$1,000-$2,000 0.554 *** 0.117$2,000+ 0.872 *** 0.152

Total monthly expenses for housing and care (log) -0.482 *** 0.053In IL portion of IL/ALs 0.105 0.068In freestanding AL -0.138 ** 0.069In AL portion of IL/ALs -0.043 0.080Lifetime earnings (log) 0.030 0.032Cut 1 -1.448 0.573Cut 2 -0.183 0.572Cut 3 0.620 0.572Observations 2,411Note: We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

22

Table 6. Characteristics correlated with Concerns about Ability to PayCoefficient Standard

ErrorStrongly agree/agree current community provides good value for price paid -1.012 *** 0.096Neutral about current community provides good value for price paid -0.545 *** 0.097Years in current community -0.003 0.009Age 0.040 0.048Age squared (in hundreds) -0.029 0.029Female 0.087 0.056Currently married 0.310 *** 0.076College educated -0.032 0.054Excellent/very good health (self-rated) -0.166 *** 0.055Same/somewhat better/much better health compared to two years ago -0.086 * 0.050Black 0.092 0.242Lived in another age-qualified community before 0.061 0.055Monthly income amount

$850-$1,200 0.075 0.210$1,200-$1,500 0.070 0.205$1,500-$2,000 0.081 0.198$2,000-$2,500 -0.008 0.197$2,500-$3,000 -0.189 0.199$3,000-$3,500 -0.144 0.197$3,500+ -0.417 ** 0.193

Total net worth (in thousands)$50-$100 -0.166 * 0.088$100-$300 -0.406 *** 0.074$300-$500 -0.737 *** 0.093$500-$750 -0.773 *** 0.103$750-$1,000 -0.915 *** 0.112$1,000-$2,000 -1.196 *** 0.128$2,000+ -1.437 *** 0.165

Total monthly expenses for housing and care (log) 0.448 *** 0.065Cut 1 0.057 0.333Cut 2 1.506 0.327Observations 2,409Note: We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

23


Male 29.8 % 35.7 % 25.4 % 31.7 %

African-American 2.8 % 1.0 % 0.8 % 0.3 %White 95.6 97.0 97.6 98.7

Married 13.7 % 20.6 % 9.5 % 15.9 %Widowed 69.3 69.1 72.6 69.4Divorced 10.2 6.0 11.6 9.1

Less than high school 13.1 % 4.6 % 13.7 % 10.9 %College educated 29.5 41.8 23.4 29.9

Self rated excellent or very good 32.7 % 38.5 % 28.2 % 28.1 %Same/better compared to two years ago 58.7 60.5 52.0 54.7

< $850 2.5 % 0.8 % 4.8 % 4.4 %$850-$1,200 7.3 3.6 10.1 8.2$1,200-$1,500 7.8 5.9 11.4 9.0$1,500-$2,000 14.5 10.4 13.5 12.6$2,000-$2,500 15.1 13.0 12.9 9.9$2,500-$3,000 13.8 12.4 11.6 7.9$3,000-$3,500 9.9 14.9 10.1 10.1$3,500+ 29.1 39.0 25.4 37.8

< $50 37.0 % 20.5 % 33.7 % 30.8 %$50-$100 13.0 12.2 13.4 15.5$100-$300 19.4 19.3 21.7 20.1$300-$500 8.1 14.7 11.6 10.2$500-$750 7.8 11.0 7.4 8.8$750-$1,000 6.4 9.6 5.4 4.2$1,000-$2,000 6.2 7.5 4.3 6.5$2,000+ 2.1 5.2 2.7 4.0

Expenses covered by current incomeAll of the expenses 38.3 % 43.3 % 24.1 % 33.3 %Most of the expenses 30.4 30.5 29.9 26.7Some of the expenses 26.8 22.2 38.5 33.3None of the expenses 4.5 4.0 7.6 6.7

The community offers me good value for my moneyStrongly agree 15.1 % 14.9 % 14.0 % 17.2 %Agree 46.9 44.3 41.6 42.0Neutral 30.9 32.2 33.6 32.6Disagree 6.4 7.2 9.0 7.5Strongly disagree 0.6 1.4 1.7 0.7

Relative to my ability to afford the feesNo concern 30.2 % 36.3 % 25.5 % 30.3 %Some concern 47.3 47.8 42.4 44.4Considerable concern 22.4 16.0 32.1 25.3


Race

Freestanding IL


Combined AL

Gender

Marital status

Education

Health

Monthly income amount

Total net worth (in thousands)


24


Financial Well-Being of Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Residents in Senior Housing and Care Communities: Overview of the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Social Security Claiming: Trends and Business Cycle Effects Owen Haaga and Richard W. Johnson, February 2012

Economic Consequences of the Great Recession: Evidence from the Panel Study of Income Dynamics Barry Bosworth, February 2012 The Changing Causes and Consequences of Not Working Before Age 62 Barbara A. Butrica and Nadia Karamcheva, February 2012 The Impact of Temporary Assistance Programs on Disability Rolls and Re-Employment Stephan Lindner and Austin Nichols, January 2012 Understanding the Growth in Federal Disability Programs: Who Are the Marginal Beneficiaries, and How Much Do They Cost? Adele Kirk, January 2012 What Explains State Variation in SSDI Application Rates? Norma B. Coe, Kelly Haverstick, Alicia H. Munnell, Anthony Webb, December 2011 How Do Subjective Mortality Beliefs Affect the Value of Social Security and the Optimal Claiming Age? Wei Sun and Anthony Webb, November 2011 How Does the Personal Income Tax Affect the Progressivity of OASI Benefits? Norma B. Coe, Zhenya Karamcheva, Richard Kopcke, Alicia H. Munnell, November 2011 The Pension Protection Act of 2006 and Diversification of Employer Stock in Defined Contribution Plans Gary V. Engelhardt, November 2011


GEOGRAPHIC MOBILITY AMONG RESIDENTS IN SENIORS HOUSING AND CARE COMMUNITIES: EVIDENCE FROM THE RESIDENTS FINANCIAL SURVEY


CRR WP 2012-9






2





crr.bc.edu



Urban Institute

3

TABLE OF CONTENTS 1. Introduction Page 4 2. Prior Living Arrangements Page 4

3. Recent Movers Page 6

4. Short-distance vs. Long-distance Movers Page 8

5. Future Living Arrangements Page 9

6. Conclusions Page 11


ASSOCIATED PAPERS 1. Coe, Norma B. and April Yanyuan Wu. 2012. “Residents in Seniors Housing and Care


2. Coe, Norma B. and April Yanyuan Wu. 2012. “Financial Well-Being of Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey.” Working Paper 2012-7. Chestnut Hill, MA: Center for Retirement Research at Boston College.


4

Introduction

There is relatively little known about the geographic mobility of the elderly in general.

Despite the stereotype of retiring in Florida, recent work has documented very little home equity

changes among the elderly (Venti and Wise 2002, 2004; Anderson, French, and Lam 2004;

Fisher et al. 2007), and that most home equity changes are precipitated by a major life event,

such as a spouse passing or entry into a nursing home. Haverstick and Zhivan (2009) find that

the 2-year moving rate for homeowners is less than 10 percent, and that most of those moves are

short-distance (less than 20 miles).

There is even less known in the academic realm about the geographic mobility of

individuals who choose to move to Independent Living (IL) or Assisted Living (AL)

communities. These communities offer services in addition to housing, such as group meals or

activities, help with medication, and often have nursing staff on location. Research to date has

been limited by data constraints. To help fill this void, we designed and conducted a new survey,

the Residents Financial Survey (RFS), with assistance from ProMatura Group, LLC, to obtain a

current economic profile of individuals living in ALs and ILs.1

This paper explores the geographic mobility patterns of individuals in IL and AL

communities using the RFS. We find there is substantial mobility among respondents. We

explore the factors that relate to their decisions of moving to a community, moving across

communities, and moving out of their current community by investigating the prior living

arrangements, characteristics of recent movers, the differences between short- and long-distance

movers, and the plans to move in the future.

This survey gathered

information on the income and assets at the time of the survey (2011), as well as retrospective

information concerning living arrangements, care provision, and financial gifts given. The final

sample consists of 2,617 respondents living in freestanding ILs, freestanding ALs, and

communities that offer both IL and AL arrangements.

1. Prior Living Arrangements

The vast majority (80-90 percent) of respondents previously lived by themselves or only

with their spouses, with the number being slightly higher for those in the IL portion of IL/ALs

1 See Coe and Wu (2012) for more details of the survey.

5

and lower for freestanding AL residents (Table 1).2

Interestingly, there is considerable inter-community movement. Close to 30 percent of

residents in freestanding ALs lived in another community beforehand, with the number being

somewhat lower for residents in freestanding ILs (about 19 percent). Using self-reported and

community-reported location and zip code information, we calculated whether people moved

across state lines as well as computed the distance people moved between their previous location

and their current community.

More than one-half of residents in

freestanding ALs received regular assistance during the six months before moving to the

community, while this was true for only 15 percent of respondents living in the IL portion of

IL/ALs. While many report receiving assistance before moving in, they were largely not living

with family, friends, or a caregiver.

3 While they tend to stay within their state – only 15 to 20 percent

move across state lines, depending on the community type – people are moving quite far, in fact.

While the median distance moved is less than 10 miles, the average distance is 150-175 miles. A

close look at the data also shows that a handful of residents moved from other countries,

including England, France, Mexico, and Italy.4

Despite the fact that AL residents are in poorer health, the respondents living in

freestanding ILs had actually been living in the community longer. These respondents reported

living in ILs for more than 3.5 years, on average. The respondents from the other living

arrangements had moved there six months later, on average. Compared to the NIC (1998) and

ALFA (1998), our residents in the AL communities have lived there longer.

In Table 2, we present the cross-tabulation of prior living arrangements and current living

arrangements. About 66 percent of the first-time care community residents received regular

assistance before they moved into the current community. While overall 32 percent of these

first-time residents moved to the IL portion of the IL/ALs and 33 percent moved to freestanding

ALs, the pattern differs by prior living arrangements: respondents who lived with extended

2 We present the percentages and the item non-response in all of the tables. Appendix Tables 1 and 2 present the recalculated percentages of only the responders. 3 Individuals were asked their previous city, state, and zip code, as well as their current zip code. We also matched survey respondents to the NIC Map database, which provides community characteristics, monthly charges, and zip code. We use NIC Map zip codes for those who match to the database, self-reported zip for everyone else. For respondents who did not report zip code but reported state and city, we use zip code of the central area for the calculation. The distance between the previous residence and the current community is computed using latitude and longitude coordinates from the center of the zip code and the Haversine formula. 4 These international moves were not used to compute the distance due to lack of zip code coordinates outside the United States.

6

family are more likely to move to freestanding ALs (49 percent) and much less likely to be in

ILs. This pattern seems sensible, assuming that a certain level of care is achieved by living with

family. A closer look at our sample also indicates that respondents who lived alone are less

likely to rate their health as poor or fair compared to those who lived with extended

family/friends or care givers (29 percent vs. 36 percent), suggesting that informal care provided

by extended family may delay entry. Furthermore, about 70 percent of those who received

regular assistance before moving decided to move to ALs (49 percent to freestanding ALs and 19

percent to the AL portion of IL/ALs), while 62 percent of those who did not receive assistance

before moving decided to move into ILs (21 percent to freestanding ILs and 42 percent to the IL

portion of IL/ALs).

For residents who lived in another age-qualified community before, 38 percent moved to

freestanding ALs, with another 33 percent moving to the IL portion of IL/ALs. When breaking

down respondents by community type they lived in prior to the current community, a general

pattern of moving to a community of higher level of care is observed. For instance, 42 percent of

residents who lived in an active adult community before are currently living in the IL portion of

IL/ALs with an additional 29 percent in freestanding ALs. Among those who lived in a

rehabilitation center or nursing home before, 85 percent currently live in ALs.

2. Recent Movers

Among those who reported how long they have been in the current community, about 50

percent have moved into the community in the past 24 months and another 14 percent moved

during the past six months. It is interesting to further explore the characteristics of these recent

movers. Understanding recent movers makes it possible to identify the type of people who

demand care communities or the different types of care communities, and the reasons impacting

their decisions to move. Table 3 presents the demographic and socioeconomic information of

recent movers.

Not surprisingly, recent movers are relatively younger with an average age of 85 years

and a median age of 86 years, more likely to be male (35 to 29 percent), and more likely to be

currently married (22 to 14 percent), compared to residents who lived in the current community

for over six months. There are no significant differences in terms of race, education, total

monthly income or net worth. Recent movers are more likely to say their health has declined

7

recently, more likely to have moved from another community, and more likely to have received

help prior to living in the current community. This pattern suggests that declining health and the

demand for assistance may be one of the reasons for the new residents moving to these types of

communities.

Interestingly, while income and asset totals do not seem to vary between recent movers

and long-stayers, the sources of each do differ. Recent movers have higher Social Security

benefits, on average, and are less likely to have income from rental property, bank accounts, or

be covered by Medicaid. They are also more likely to own an automobile and a house – which

may be a temporary effect of not yet having sold these items. They are much less likely to have

a trust.

Table 4 examines the characteristics of new movers based on the type of community

where they currently reside. First the age differences between residents who moved to the AL

portion of IL/ALs and the other three communities are significant, with the former being

relatively older (an average age of 87.5 years). Compared to earlier work, our sample of recent

movers is again significantly older.5 We also find that recent movers to the freestanding ALs are

much less likely to still be married as compared to the other community types.6 While about 33

percent of all recent movers had a college degree, the highest representation, 52 percent, is

among recent movers to the IL portion of IL/ALs. 7

While no statistically significant differences in self-rated health emerged between the

new movers and long-time residents, differences were observed, however, between new residents

based on their community type. Freestanding ALs had the lowest proportion of new residents

who rated their health as excellent or very good (less than 20 percent).

Although differences in monthly income and net worth of new residents were not

statistically significant compared to those who lived in the community longer, the differences

among new residents across communities are substantial. New residents to freestanding ILs and

ALs have lower income and lower net worth than new residents in combined properties.

5 According to The Independent Living Report, the resident who moved to independent living in the past six months was an average of 81.7 years and a median age of 82.8 years. In our sample, the resident who moved to independent living in the past six months was an average of 85 years and a median age of 84.5 years. 6 Our sample of recent movers to IL is much less likely to be married than the 35-percent marriage rate found in The Independent Living Report. 7 Our numbers are slightly lower than those reported in The Independent Living Report.

8

Finally, recent movers to different community types vary by where they moved from.

Particularly, 41 percent of the new residents to the IL portion of IL/ALs reported living in

another community before. This is statistically significant from the other three types of

communities. The corresponding numbers for the freestanding ILs, freestanding ALs, and the

AL portion of the IL/ALs are 22, 29 and 23 percent.

3. Short-distance vs. Long-distance Movers

Another interesting dimension of the mobility of these care-community residents is how

far they moved when selecting their community. The rich information of the survey allows us to

distinguish long-distance movers from short-distance movers and further explore the differences

between these two groups (Table 5).

About 21 percent of the sample moved over 100 miles, which we use as the definition of

a long-distance mover. There are no statistical differences between short- and long-distance

movers on race, gender, marital status, or total monthly income. Long-distance movers are

relatively older, better educated, and in better health – both in terms of self-rated health and

likelihood of receiving assistance before moving into the community.

The combined IL/ALs communities are more likely to be destinations for the long-

distance movers compared to freestanding ILs or ALs. Interestingly, long-distance movers are

both more likely to have lived in another age-qualified community before and have stayed in the

current community longer, on average. Given the health and education results, this is likely

reflecting a survivor bias – that long-distance movers live longer than short-distance movers.

While long-distance movers are less likely to have Medicaid, they are more likely to move from

a state that has less generous Medicaid eligibility rules.

On average, long-distance movers pay more for their residence and services. They also

have relatively higher total expenses including other services they receive. Despite this and

virtually no difference in total monthly income, long-distance movers are more likely to report

that all of their expenses are covered by their current income (40 to 34 percent) and are more

likely to have no concern about their ability to afford the fees of the community (34 to 28

percent), compared to short-distance movers.

While the income distribution does not vary between long- and short-distance movers,

the sources of income differ. Long-distance movers are more likely to have income from stocks

9

or bonds, and less likely to have rental income, a reverse mortgage, a veteran’s pension, or

income from government assistance, including SSI, Medicaid, and the HUD rental assistance

program. Long-distance movers are relatively wealthier, being less likely to have total net worth

less than $100,000 (31 to 39 percent). They also are more likely to hold a brokerage, stock or

mutual fund account and to hold a trust, but much less likely to own a house. In addition, the

probability of giving a monetary gift is higher among long-distance movers (19 to 13 percent).

To further explore the characteristics of long-distance movers, we conducted regression

analysis.8

The results are presented in Table 6. We find that having children is positively

correlated with being a long-distance mover, perhaps a signal of a motivating factor for the new

location. African-Americans in our sample do not move as far as Caucasians. Medicaid

recipients are less likely to be long-distance movers, as are those who own a house. Individuals

who lived in another age-qualified care-community before are more likely to move far away.

Not surprisingly, higher net worth is correlated with higher probability of being a long-distance

mover. Interestingly, previously living in a state with less generous asset and income tests for

Medicaid eligibility makes one more likely to be a long-distance mover.

4. Future Living Arrangements

We then examined the relationship between respondents’ current living arrangement and

their plan to move out (Table 7). About 10 percent of respondents indicated that they will move

out of their community within the next 12 months. While residents of different types of

communities are not significantly different in their likelihood of moving out, they differ in where

they plan to move. Residents of freestanding ILs are more likely to want to move to a

community that provides a higher level of care, such as to a community that offers assisted living

services or nursing care (35 percent), while residents of the IL portion of IL/ALs are more likely

to move to another community similar to the one in which they are living currently (48 percent).

We also found that 28 percent of residents in freestanding ALs and 20 percent in the AL portion

of IL/ALs are planning to move to communities that offer nursing care. In addition, about 25 to

8 We estimated a probit model. Marginal effects are presented in Table 6. The explanatory variables include age, gender, race, education, marital status, indicators for health status, indicator of having children, measure of length being in the current community, total current income, total net worth, housing ownership, whether receive Medicaid, indicators of whether current state of residence has strict asset eligibility rules for Medicaid, whether previous state of residence has strict asset eligibility rules for Medicaid, indicators for current living arrangements, and controls for state of residence.

10

35 percent of residents are planning to move to non-care-communities, such as to their own

home, a home of a family member, or an apartment that does not include any services in the

monthly fee.

Finally, we explored the stated reasons for wanting to move out. The financial reason is

the predominant reason for wanting to move out, with over 50 percent of respondents who plan

to move out in the next 12 months mentioning they “Can't afford it” or “Costs too high.” About

18 percent stated that health is the primary reason for them to move, either getting better or

worse. Family concerns, such as the desire to be near a family member, are listed as the primary

reason by 7 percent of residents. Another 15 percent mentioned that they are not satisfied with

the services, including the quality of food and services.

There are apparent differences across communities in terms of reasons to move out.

Residents of ALs are much more likely to move out for financial reasons (59 percent for

freestanding ALs and 63 percent for the AL portion of IL/ALs), while other reasons, such as

health or being unsatisfied with services, are more prevalent among IL residents (34 percent of

residents in freestanding ILs mentioned health reasons and another 16 percent reported being

unhappy with the services). Further investigation on the relationship between reasons to move

and where to move shows that respondents who indicated financial concerns as the primary

reason to move are more likely to move to another community similar to the one they are living

in currently, while those planning to move for health reasons are more likely to move to

communities offering assisted living services or nursing care.

The reasons individuals would like to move also varies significantly by the distance one

moved originally (Table 8). Twenty-one percent of short-distance movers mentioned that health

is the primary reason to move, while it is the reason for only 4 percent of the long-distance

movers. In contrast, about 20 percent of long-distance movers stated that unsatisfactory service

is the primary reason for a future move, compared to only 13 percent of short-distance movers.

This finding is interesting because on the one hand, one might assume that long-distance movers

may spend more time on their search. Thus the quality of match should be higher. On the other

hand, those who moved a long way may have higher expectations for the service; consequently,

they are more likely to be unhappy given a standard level of service. In terms of where to move,

53 percent of long-distance movers are most likely to move to an apartment that does not include

any services in the monthly fee or to another community similar to the current one, and the

11

corresponding number for short-distance movers is 14 percentage points lower. In addition, over

22 percent of short-distance movers plan to move to a community that offers nursing care, while

the corresponding number for long-distance movers is only 13 percent.

The evolution of living arrangements shows that there are strong correlations among

respondents’ current living arrangements, previous living arrangements, and their plan to move

in the future. The underlying need for care seems to be one of the reasons that impact the

decision to move, and the reasons for moving out also predict where people want to move. We

further investigate factors that relate respondents’ desire to move out in the next 12 months using

regression analysis.9

The regression results are summarized in Table 9. Respondents who are

older, college educated, own their home, rate themselves in excellent or very good health, and

experienced a decline in health in the past two years are more likely to want to move out within

the next 12 months. On the other hand, those who are wealthier or who are Medicaid recipients

are less likely to move out soon. We find that compared to those who have no concern,

respondents that have some or considerable concerns about their ability to pay are significantly

more likely to move out in the near future.

5. Conclusions

There is substantial geographic mobility among the respondents. Between 15 and 20

percent moved across state lines, and the average person moved between 150 and 175 miles

away from their previous residence, which was typically an arrangement where they lived alone

or only with their spouse. Many were getting assistance before they moved to their current

community, either from family or another type of care community. For those moving between

communities, there tends to be a pattern of moving towards more services. Interestingly, new

residents in freestanding ILs and freestanding ALs have lower income and lower net worth than

new residents in combined IL/AL properties.

Combined IL/AL properties seem to attract residents from longer distances than

freestanding properties. These long-distance movers seem to be different from individuals who 9 We estimated a probit model. The explanatory variables included basic demographics, such as age, age squared, and indicator for gender, married, race, college education, having kids, having lived in another community before, and whether moved over 100 miles. We also controlled for variables related to health, including indicator for self-rated health condition as excellent or good health, self-rated health condition compared to two years ago as much better, somewhat better, or about the same health, and indicators for receiving regular care before moving in. Income, net worth and indicator variables for home ownership and Medicaid are included in the analysis. Moreover, indicators for current living arrangement are controlled for.

12

only move a short distance (less than 100 miles). Long-distance movers tend to be in better

health, wealthier, and more educated. While their incomes are comparable, they pay more for

their services and are less concerned about their ability to continue paying these bills.

Interestingly, long-distance movers are more likely to come from states with stricter Medicaid

eligibility rules.

Finally, we explored future plans to move. About 10 percent of the sample plans to move

out within the next year; moving to places with more services, fewer services, and the same level

of services are all roughly equally likely. Finances are the most important reason stated,

followed by health and dissatisfaction with current services.

13

References

Anderson, Kate, Eric French, and Tina Lam. 2004. “You Can’t Take It With You: Asset Run-Down at the End of the Life Cycle.” Economic Perspectives 3: 40-54.

Assisted Living Federation of America (ALFA). 1998. The Assisted Living Industry: An

Overview – 1998. Fairfax, VA: Price Waterhouse and ALFA. Coe, Norma B. and April Yanyuan Wu. 2012. “Residents in Seniors Housing and Care


Fisher, Jonathan D., David S. Johnson, Joseph T. Marchand, Timothy M. Smeeding, and Barbara

Boyle Torrey. 2007. “No Place like Home: Older Adults and Their Housing.” Journal of Gerontology 62B(2): S120-S128.

Haverstick, Kelly and Natalia A. Zhivan. 2009. “Older American on the go: How Often, Where

and Why?” Issue in Brief 9-18. Chestnut Hill, MA: Center for Retirement Research at Boston College.

National Investment Center for the Seniors Housing & Care Industry (NIC). 1998. “National

Survey of Assisted Living Residents: Who is the Customer?” Annapolis, MD. “The Independent Living Report.” 2009. Washington, DC: American Seniors Housing

Association. Venti, Steven F. and David A. Wise. 2002. “Aging and Housing Equity.” In Innovations in

Retirement Financing, edited by Olivia. S. Mitchell, Zvi Bodie, P. Brett Hammond, and Stephen Zeldes, 254-281. Philadelphia, PA: University of Pennsylvania Press.

Venti, Steven F. and David A. Wise. 2004. “Aging and Housing Equity: Another Look.” In Perspectives on the Economics of Aging, edited by David A. Wise, 127-175. Chicago, IL: University of Chicago Press.

14

Living by themselves or only with spouse % % % %Living with extended family, friends, or caregiver 11.1 7.6 17.2 12.3Non-responseLiving in another community In active adult community In ILs In ALs In rehabilitation center or nursing homeNon-response 4.2 3.0 1.8 2.5

Health*Received assistance before moving inNon-response

Crossed state boundary 14.26 % 16.7 % 18.0 % 20.4 %Within-state move 80.3 79.4 79.2 76.9Non-response/not computable 5.5 3.9 2.8 2.7

Average distanceMedian distanceNon-response/not computable % % % %

Months in the current communityAverage monthsMedian monthsQuestionable % % % %Non-response % % % %

477 854 880 406Source: Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 1 for calculations of the percentages that treat non-response as missing observations.

Table 1. Prior Living Arrangements, by Community Type

Observations

19.0 27.0 29.0 28.0

34.1 39.0 30.0 33.03.8 28.2 22.3

2.3 0.9 7.3

Freestanding IL


Combined AL

50.0 56.3 34.7 40.8

Prior living arrangement*85.1 89.7 81.1 85.0

Distance moved (miles)165.0 183.6 168.7 189.9

43.8 36.4 37.7 35.6

6.7 8.2 7.4 8.56.5 5.0 3.9 3.4

7.8 8.8 7.8 7.4

4.6 3.4 2.4 2.7

25.0 25.0 22.0 25.01.0 2.1 1.3 1.7

54.3 42.4

1.7 2.7

3.9

Distance moved, over state boundary

31.9 14.8

3.8 2.7

13.6

15

Tabl

e 2.

Com

parin

g Pr

ior t

o C

urre

nt L

ivin

g A

rran

gem

ents

Obs

erva

tions

Not

in a

noth

er a

ge-q

ualif

ied

com

mun

ity19

.8%

32.2

%32

.7%

15.4

%1,

856

72.9

%W

ho th

ey liv

ed w

ithBy

them

selve

s or o

nly w

ith sp

ouse

20.0

%34

.2%

30.4

%15

.5%

1,59

986

.2%

With

ext

ende

d fa

mily

18.3

18.8

49.0

15.5

208

11.2

With

frien

ds o

r car

e giv

ers

20.4

24.5

38.8

16.3

492.

6Re

ceive

d as

sista

nce

befo

re m

oving

inRe

ceive

d as

sista

nce

18.4

%12

.9%

49.4

%19

.2%

1,22

566

.0%

Did

not

rece

ive a

ssist

ance

20.6

41.8

24.8

13.6

619

33.4

Non

-res

pons

e8.

341

.750

.00.

012

0.6

In a

noth

er a

ge-q

ualif

ied

com

mun

ity13

.4%

33.2

%37

.8%

15.6

%68

927

.1%

Type

of c

omm

unity

Act

ive a

dult

com

mun

ity14

.8%

41.6

%28

.9%

14.8

%29

843

.3%

Inde

pend

ent l

iving

com

mun

ity13

.938

.532

.914

.723

133

.5A

ssist

ed liv

ing c

omm

unity

10.3

6.9

62.9

19.8

116

16.8

Reha

bilita

tion

cent

er o

r nur

sing

care

cen

ter

7.4

7.4

70.4

14.8

273.

9N

on-r

espo

nse

0.0

47.1

17.6

35.3

172.

5So

urce

: A

utho

rs' c

alcula

tions

of t

he R

esid

ents

' Fin

anci

al S

urve

y.

Perc

enta

ge

Prio

r Liv

ing

Arr

ange

men

tTo

tals

Free

stand

ing

IL

Com

bine

d IL

Free

stand

ing

AL

Com

bine

d A

L

Cur

rent

Liv

ing

Arr

ange

men

t

16

Average age 84.9 86.7 ***Non-response 2.0 2.9

Male 35.1 % 29.4 % **Non-response 2.0 2.9

White 97.7 % 97.3 %Non-response 2.0 2.5

Married 21.7 % 13.8 % ***Non-response 1.4 2.3

College educated 33.3 % 30.2 %Non-response 2.0 2.7

Self rated excellent or very good 33.2 % 30.8 %Non-response 1.7 2.3Same/better compared to two years ago 46.7 52.2 *Non-response 1.7 2.5Received assistance before moving in 45.5 35.4 ***Non-response 2.3 3.2

Living in another community 31.0 % 25.7 % **Non-response 2.0 3.8

Average distance 149.6 171.5Non-response/not computable 3.1 3.7

Income by sourceSocial Security 98.5 % 97.4 % Average Social Security benefits $ 1,351 $ 1,276 **Pension/annuity 65.1 64.6 Average pension income $ 1,632 $ 1,705Interest from bank accounts 43.8 50.7 **Interest from stocks/bonds 43.2 45.2Rental income 4.4 7.8 **Business or farm 2.4 2.1Trust fund 3.8 5.5Reverse mortgage 0.1 0.0Medicaid 3.5 5.7 *SSI 1.7 1.2Food Stamps 0.0 0.0HUD rental assistance 0.0 0.0Other means-tested sources 0.0 0.0

LTC insurance 15.3 % 15.5 %Checking/savings 87.4 87.8Brokerage/stocks/bonds 45.6 45.2401(k), IRA 23.7 20.8Trust 8.5 12.8 **House, property, land 33.0 19.3 ***Farm, business 1.1 2.1Automobile 39.2 24.0 ***

355 2,023* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 2 for calculations of the percentages that treat non-response as missing observations.

Table 3. Comparing Characteristics of Recent Movers to Those Stayed Longer

Observations

Prior living arrangement*

Distance moved (mile)

Asset types

Age

Gender*

Race*

Marital status*

Education*

Health*

Recent movers Residents who stayed longer than six months

17

Table 4. Characteristics of New Movers, by Community Type

Average ageNon-response % % % %


Married % % % %Non-response

College educated % % % %Non-response

Self rated excellent or very good % % % %Non-responseSame/better compared to two years ago Non-responseReceived assistance before moving inNon-response

Living in another community % % % %Non-response

Average distance 168.2Median distance 9.8Non-response/not computable % 3.5 % % %

< $850 0 % 0 % % 0 %$850-$1,200$1,200-$1,500$1,500-$2,000$2,000-$2,500$2,500-$3,000$3,000-$3,500$3,500+Questionable 0 0Non-response

Income by sourceSocial Security % % % %Pension/annuityInterest from bank accountsInterest from stocks/bondsRental incomeBusiness or farmTrust fundReverse mortgageMedicaidSSIFood StampsOther means-tested sources

< $50 31.8 % 14.8 % 31.5 % 26.4 %$50-$100 12.7 13.9 10.5 9.4$100-$300 20.6 17.4 25.0 17.0$300-$500 12.7 15.7 8.9 1.9$500-$750 6.4 8.7 5.7 18.9$750-$1,000 6.4 9.6 4.0 9.4$1,000-$2,000 1.6 6.1 2.4 0.0$2,000+ 1.6 5.2 1.6 5.7Non-response 6.4 8.7 10.5 11.3

LTC insurance % % % %Checking/savingsBrokerage/stocks/bonds401(k), IRATrustHouse, property, landFarm, businessAutomobile


45.2 60.9 25.0 18.0Observations 63 115 124 53

35.5 31.8 35.0 28.01.6 2.7 0.0 0.0

19.4 27.3 24.2 20.09.7 9.1 6.7 10.0

87.1 90.0 88.3 80.033.9 63.6 31.7 54.0

Total net worth (in thousands)*

Asset types9.8 16.2 16.1 19.9

1.6 0.0 3.3 2.01.6 0.0 0.0 0.0

8.1 10.1 14.9 11.80.0 0.0 6.6 7.8

4.8 2.8 4.2 4.10.0 1.8 0.0 0.0

3.2 4.6 4.2 6.13.2 4.6 0.0 2.0

40.3 56.9 39.2 30.635.5 61.5 30.0 44.9

98.4 98.2 98.3 100.067.7 67.0 63.6 61.2

0.0 1.73.2 7.0 2.4 9.4

11.1 16.5 16.1 13.219.1 35.7 17.7 35.9

15.9 11.3 11.3 7.617.5 10.4 10.5 7.6

11.1 5.2 11.3 5.719.1 9.6 15.3 15.1

1.6 3.2 5.7Monthly income amount*

4.83.2 2.6 10.5 5.7

Distance moved (mile)136.5 139.7 148.7

6.2 7.2 6.4

Prior Living arrangement*22.0 41.4 29.0 23.1

0.0 3.5 0.0 1.9

40.3 21.6 71.3 42.31.6 3.5 1.6 1.9

45.2 53.2 36.3 59.61.6 3.5 0.8 1.9

Health*32.3 48.7 19.4 34.6

1.6 3.5 0.0 1.9

Education*27.4 51.8 22.6 26.9

1.6 4.3 0.0 1.9

Marital status*17.7 33.0 12.9 23.1

1.6 2.6 0.0 1.9

1.2 3.5 0.8 1.9

6.3 6.1 0.8 7.5Gender*

38.7 41.4 30.9 26.9

Freestanding IL


Combined AL

Age84.1 84.6 84.6 87.5

18

Table 5. Comparing Characteristics of Long-distance to Short-distance Movers

Average age 87.0 86.2 **Non-response 2.3 2.7

College educated 35.2 % 30.7 % **Non-response 0.4 0.7

Self rated excellent or very good 36.5 % 30.9 % **Non-response 0.2 0.3Received assistance before moving in 30.0 38.5 ***Non-response 0.8 1.1

Living in another community 33.6 % 24.8 % **Non-response 1.1 1.7

Months in the current communityAverage months 42.6 34.4 ***Non-response 9.4 7.8

All of the expenses 40.1 % 33.6 % ***Most of the expenses 22.9 27.9 **Some of the expenses 25.4 28.0None of the expenses 5.7 4.9Non-response 5.9 5.6

No concern 33.8 % 27.5 % ***Some concern 38.7 44.4 **Considerable concern 22.9 22.4Non-response 4.6 5.8

Average 3,312.7 3,128.9 **Non-response 9.2 10.5

Income by SourceSocial Security 97.2 % 97.8 % Average Social Security benefits $ 1,308 $ 1,282Pension/annuity 65.8 63.1 Average pension income $ 1,820 $ 1,645Interest from bank accounts 50.3 48.5Interest from stocks/bonds 50.9 43.0 ***Rental income 4.6 7.9 **Business or farm 2.4 1.8Trust fund 6.8 5.1Medicaid 3.8 5.9 *SSI 0.1 1.6 *Food Stamps 0.0 0.1HUD rental assistance 0.0 0.1 *

< $50 22.1 % 26.4 % **$50-$100 9.2 12.1 *$100-$300 17.0 17.7$300-$500 12.0 9.9$500-$750 9.0 7.5$750-$1,000 5.7 6.0$1,000-$2,000 7.1 4.8 **$2,000+ 5.5 2.5 ***Non-response 12.4 13.0

LTC insurance 17.3 % 14.9 %Checking/savings 87.1 87.5Brokerage/stocks/bonds 52.5 43.4 ***401(k), IRA 22.3 21.0Trust 14.5 11.5 *House, property, land 22.9 15.1 ***Farm, business 2.0 1.9Automobile 25.6 25.9

Gifts given in the last five yearsYes 19.2 % 13.4 %Non-response 5.7 3.7 %

524 1,971* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.*: See Appendix Table 2 for calculations of the percentages that treat non-response as missing observations.

Total net worth (in thousands)*

Asset types

Observations

Monthly bill per person

Relative to my ability to afford the fees*

Expenses covered by current income*

Long-distance Movers

Short-distance Movers

Age

Education*

Health*

Prior Living arrangement*

19

Standard Error

Years in current community 0.009 *** 0.003Age 0.023 0.015Age squared (in hundreds) -0.013 0.009Female -0.001 0.020College educated 0.020 0.020Currently married -0.009 0.025Excellent/very good health (self-rated) 0.032 0.020Same/somewhat better/much better (compared to two years ago) 0.009 0.018Black -0.110 ** 0.052Have children 0.057 ** 0.025Lived in another age-qualified community before 0.076 *** 0.021Received regular assistance prior to moving into community -0.030 0.019Monthly income amount

$850-$1,200 0.062 0.070$1,200-$1,500 0.109 0.073$1,500-$2,000 0.046 0.064$2,000-$2,500 0.066 0.066$2,500-$3,000 0.113 0.071$3,000-$3,500 0.011 0.061$3,500+ 0.044 0.059

Total net worth (in thousands)$50-$100 -0.028 0.029$100-$300 0.016 0.028$300-$500 0.061 * 0.036$500-$750 0.064 0.042$750-$1,000 0.014 0.042$1,000-$2,000 0.099 ** 0.050$2,000+ 0.202 *** 0.066

Own a house -0.073 *** 0.020Medicaid recipient -0.061 * 0.036Current state of residence has strict asset eligibility rules for Medicaid 0.133 0.222Previous state of residence has strict asset eligibility rules for Medicaid 0.077 ** 0.033In IL portion of IL/ALs -0.049 0.036In freestanding AL -0.040 0.035In AL portion of IL/ALs 0.023 0.043State Indicators YesObservations 2,413Note : We included indicator variables for non-response for each of explanatory variables.* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

Marginal Effect

Table 6. Probability of Being a Long-distance Mover

20

Tabl

e 7.

Cur

rent

ver

sus

Futu

re L

ivin

g A

rran

gem

ents

Obs

erva

tions

Plan

to m

ove

out

Yes

9.9

%8.

1%

11.5

%9.

7%

249

9.7

%N

o90

.292

.088

.590

.32,

309

90.3

Whe

re to

mov

eTo

an

apar

tmen

t tha

t doe

s not

inclu

de a

ny

serv

ices i

n th

e m

onth

ly fe

e11

.1%

12.9

%10

.6%

8.3

%26

11.0

%To

ano

ther

com

mun

ity si

mila

r to

the

one

in w

hich

I am

living

cur

rent

ly26

.348

.424

.525

.074

31.2

To a

com

mun

ity th

at o

ffers

ass

isted

living

se

rvice

s15

.66.

58.

513

.924

10.1

To a

com

mun

ity th

at o

ffers

nur

sing

care

20.0

6.5

27.7

19.4

4619

.4To

my

hom

e4.

46.

58.

513

.919

8.0

To a

hom

e of

a fa

mily

mem

ber

11.1

6.5

8.5

13.9

229.

3O

ther

11.1

12.9

11.7

5.6

2611

.0Th

e pr

imar

y re

ason

to m

ove

out

Fina

ncial

38.6

%43

.6%

58.9

%62

.9%

119

51.5

%H

ealth

34.1

8.1

17.8

14.3

4117

.7Fa

mily

reas

ons

4.6

11.3

5.6

5.7

166.

9U

nsat

isfied

with

serv

ice15

.916

.313

.317

.135

15.2

Oth

er6.

821

.04.

40.

020

8.7

Sour

ce:

Aut

hors

' calc

ulatio

ns o

f the

Res

iden

ts' F

inan

cial

Sur

vey.

Perc

enta

ge

Cur

rent

Liv

ing

Arr

ange

men

tTo

tals

Free

stand

ing

IL

Com

bine

d IL

Free

stand

ing

AL

Com

bine

d A

L

21

Table 8. Future living arrangements: Comparing Long-distance Movers to Short-distance Movers

Plan to move outYes 9.7 % 9.6 %Non-response 3.2 1.6

The primary reason to move outFinancial 54.4 % 51.2 %Health 4.4 21.3Unsatisfied with service 19.6 13.2Family 8.7 6.6Other 13.0 7.5

Where to moveTo an apartment that does not include any services in the monthly fee 17.0 % 10.1 %To another community similar to the one in which I am living currently 36.2 29.1To a community that offers assisted living services 6.4 11.2To a community that offers nursing care 12.8 22.4To my home 4.3 7.8To a home of a family member 10.6 10.1Other 12.8 9.5

524 1,971Source : Authors' calculations of the Residents' Financial Survey.



Observations

22

Standard Error

Years in current community -0.001 0.002Age 0.016 * 0.008Age squared (in hundreds) -0.011 ** 0.005Female -0.003 0.012College educated 0.023 * 0.013Currently married -0.002 0.016Excellent/very good health (self-rated) 0.023 * 0.013Same/somewhat better/much better (compared to two years ago) -0.019 * 0.011Black 0.048 0.067Have children -0.017 0.018Lived in another age-qualified community before 0.006 0.012Monthly income amount

$850-$1,200 -0.030 0.025$1,200-$1,500 -0.038 * 0.022$1,500-$2,000 -0.028 0.025$2,000-$2,500 -0.012 0.029$2,500-$3,000 -0.017 0.028$3,000-$3,500 -0.015 0.029$3,500+ -0.029 0.028

Total net worth (in thousands)$50-$100 0.002 0.017$100-$300 -0.031 ** 0.013$300-$500 -0.027 * 0.016$500-$750 -0.041 *** 0.015$750-$1,000 -0.022 0.021$1,000-$2,000 -0.010 0.026$2,000+ -0.042 * 0.023

Own a house 0.032 ** 0.016Medicaid recipient -0.023 0.022Moved over 100 miles to live in current residence 0.007 0.013Total monthly expenses for housing and care (log) 0.016 0.012Have no concern about ability to pay fees -0.107 *** 0.010Have some concern about ability to pay fees -0.099 *** 0.011In IL portion of IL/ALs -0.007 0.015In freestanding AL -0.001 0.015In AL portion of IL/ALs -0.015 0.016Observations 2,510Note : We included indicator variables for the non-response of each of explanatory variables* significant at 10%, ** significant at 5%, *** significant at 1%.Source: Authors' calculations of the Residents' Financial Survey.

Marginal Effect

Table 9. Probability of Moving Out Within the Next 12 Months

23


Prior Living arrangementLiving by themselves or only with spouse 88.5 % 89.7 % 81.1 % 85.0 %Living with extended family, friends, or caregiver 11.5 7.8 17.5 12.7Living in another community 19.8 27.8 29.5 28.7

HealthReceived assistance before moving in 33.4 % 15.3 % 55.7 % 43.5 %

Panel B: New Mover Sample (Table 4)Gender

Male 39.2 42.9 31.1 27.4Marital Status

Married 18.0 33.9 12.9 23.5Education

College educated 27.9 54.2 22.6 27.4Health

Self rated excellent or very good 32.8 50.4 19.4 35.3Same/better compared to two years ago 45.9 55.1 36.6 60.8Received assistance before moving in 41.0 22.4 72.5 43.1

Monthly Income< $850 0.0 0.0 5.0 0.0$850-$1,200 3.3 2.9 10.7 6.2$1,200-$1,500 11.5 5.7 11.6 6.2$1,500-$2,000 19.7 10.5 15.7 16.7$2,000-$2,500 16.4 12.4 11.6 8.3$2,500-$3,000 18.0 11.4 10.7 8.3$3,000-$3,500 11.5 18.1 16.5 14.6$3,500+ 19.7 39.0 18.2 39.6

Total net worth (in thousands)< $50 33.9 16.2 35.1 29.8$50-$100 13.6 15.2 11.7 10.6$100-$300 22.0 19.0 27.9 19.1$300-$500 13.6 17.1 9.9 2.1$500-$750 6.8 9.5 6.3 21.3$750-$1,000 6.8 10.5 4.5 10.6$1,000-$2,000 1.7 6.7 2.7 0.0$2,000+ 1.7 5.7 1.8 6.4


Panel A: Entire Sample (Table 1)

Freestanding IL


Combined AL

24


GenderMale 35.8 % 30.3 % 69.4 % 69.7 %

RaceWhite 99.7 % 99.8 % 98.1 % 97.1 %

Marital StatusMarried 22.0 % 14.1 % 14.7 % 15.1 %

EducationCollege educated 34.0 % 31.0 % 35.4 % 30.9 %

HealthSelf rated excellent or very good 33.8 % 31.5 % 36.6 % 31.0 %Same/better compared to two years ago 47.5 53.6 30.2 38.9Received assistance before moving in 46.5 36.6 30.0 38.6

Prior living arrangementLiving in another community 31.6 % 26.7 % 34.0 % 25.2 %

Expenses covered by current incomeAll of the expenses 42.6 % 35.6 % 42.6 % 35.6 %Most of the expenses 24.3 29.6 24.3 29.6Some of the expenses 27.0 29.7 27.0 29.7None of the expenses 6.1 5.2 6.1 5.2

Relative to my ability to afford the feesNo concern 35.4 % 29.2 % 35.4 % 29.2 %Some concern 40.6 47.1 38.7 44.4Considerable concern 24.0 23.8 22.9 22.4

Total net worth (in thousands)< $50 27.9 % 28.9 % 25.3 % 30.4 %$50-$100 13.0 13.3 10.5 13.9$100-$300 22.7 20.5 19.4 20.4$300-$500 11.8 11.7 13.7 11.4$500-$750 9.6 8.9 10.2 8.6$750-$1,000 7.8 6.6 6.5 6.9$1,000-$2,000 3.4 6.3 8.1 5.5$2,000+ 3.7 3.8 6.3 2.9


(Table 3) (Table 5)

Recent movers

Residents who stayed longer



25


Costs and Concerns among Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Financial Well-Being of Residents in Seniors Housing and Care Communities: Evidence from the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Residents in Senior Housing and Care Communities: Overview of the Residents Financial Survey Norma B. Coe and April Yanyuan Wu, April 2012 Social Security Claiming: Trends and Business Cycle Effects Owen Haaga and Richard W. Johnson, February 2012

Economic Consequences of the Great Recession: Evidence from the Panel Study of Income Dynamics Barry Bosworth, February 2012 The Changing Causes and Consequences of Not Working Before Age 62 Barbara A. Butrica and Nadia Karamcheva, February 2012 The Impact of Temporary Assistance Programs on Disability Rolls and Re-Employment Stephan Lindner and Austin Nichols, January 2012 Understanding the Growth in Federal Disability Programs: Who Are the Marginal Beneficiaries, and How Much Do They Cost? Adele Kirk, January 2012 What Explains State Variation in SSDI Application Rates? Norma B. Coe, Kelly Haverstick, Alicia H. Munnell, Anthony Webb, December 2011 How Do Subjective Mortality Beliefs Affect the Value of Social Security and the Optimal Claiming Age? Wei Sun and Anthony Webb, November 2011 How Does the Personal Income Tax Affect the Progressivity of OASI Benefits? Norma B. Coe, Zhenya Karamcheva, Richard Kopcke, Alicia H. Munnell, November 2011

All working papers are available on the Center for Retirement Research website

(http://crr.bc.edu) and can be requested by e-mail ([email protected]) or phone (617-552-1762).

American Seniors Housing Association5225 Wisconsin Avenue, NWSuite 502Washington, DC 20015(202) 885-5560Fax (202) 237-1616www.seniorshousing.org

Documents

Residents Financial Survey