SCF Credit Section: Literature related to Emergency Funds, etc.

Article Summaries Regarding Household Financial Behavior:

Credit, Financial Ratios, Emergency Funds, Life Insurance

Citation 1: Chang, Y.R. & Huston, S. (1995). Patterns of adequate household emergency fund holdings: A comparison of
household in 1983 and 1986. Financial Counseling and Planning, 6, 119-128.

Abstract: The 1983 and 1986 Survey of Consumer Finance were used to analyze patterns of meeting a guideline of
holding enough liquid assets to cover three months of income (emergency fund adequacy). In both years,
only 32% of households met the guideline. Only 21% of households met the guideline in both years.
Logistic regression analyses show a consistent pattern. The probability of having adequate emergency
funds increased with education, home equity, and age, and decreased with house size. Households with a
Black head had significantly lower probabilities of having adequate emergency fund holdings than similar
households headed by a White.

Citation 2: Chang, Y.R. (1995). Effects of expected future income and other factors on adequacy of household emergency fund
savings. In Karen F. Folk (Ed.), Proceedings of the 41st Annual Conference of the American Council on
Consumer Interests, pp. 220-221. Columbia, MO: American Council of Consumer Interests.

Abstract: The 1983-86 Survey of Consumer Finances panels were used to test the relationship between expected
income growth and emergency fund levels. The guideline that liquid assets should be 3 months income
was met by 37% of households. A logit on meeting the guideline showed that expected income growth did
not have a significant effect. Age, homeownership, and income had positive and household size and being
Black had negative effects on meeting the guideline.

Citation 3: DeVaney, S. A. (1995). Emergency fund adequacy among U.S. households in 1977 and 1989. Consumer Interests
Annual, 41, 222-223.

Abstract: The purpose of this study was to compare the level of emergency funds held by households in 1977 and
1989. About one-third of all households were adequately prepared in both years. As age and education
increased, households were more likely to meet the rule of thumb of holding liquid assets equal to 3
months of income.

Citation 4: Hanna, S. & Wang, H. (1995). The adequacy of emergency funds to cover household expenditures. In Karen F. Folk
(Ed.), Proceedings of the 41st Annual Conference of the American Council on Consumer Interests,
pp.224-225. Columbia, MO: American Council of Consumer Interests.

Abstract: An analysis of households in the Consumer Expenditure Survey confirmed previous findings, with only
31% having enough liquid assets to cover 3 months of spending. A logit showed that meeting the
guideline increased with income, age and education and decreased with household size. Black households
were significantly less likely than similar non-Black households to meet the guideline.

Citation 5: Hanna, S., Chang, Y.R., Fan, J.X. & Bae, M.K. (1993). Emergency fund levels of households: Is household behavior
rational? In Teresa Mauldin (Ed.), Proceedings of the 39th Annual Conference of the American Council
on Consumer Interests, pp. 215-222. Columbia, MO: American Council of Consumer Interests.

Abstract: Empirical studies have found that most households do not have recommended levels of liquid savings. An
analysis of the 1990 Consumer Expenditure Survey confirms previous findings. A three period model of
optimal consumption is presented. The results suggest that many consumers who do not have the
recommended levels of liquid assets may be acting rationally. The results may be useful for financial
counselors and educators, as well as for insight into empirical patterns of savings.

Citation 6: Johnson, D.P. & Widdows, R. (1985). Emergency fund levels of households. In Karen P. Schnittgrund (Ed.),
Proceedings of the 31st Annual Conference of the American Council on Consumer Interests, pp. 235-241.
Columbia, MO: American Council of Consumer Interests.

Abstract: 1977 and 1983 Survey of Consumer Finances are used to examine households’ holdings
of emergency funds. Analysis shows that most families had low levels of emergency
funds. Data also show that families were less prepared in 1983 than in 1977 to face
financial emergencies. Cross-tabulations of data with socio-demographic characteristics
of families show how emergency funds varied among households.

Emergency funds are defined as certain household liquid asset holdings. Three
different measures of assets are used in the study: 1) quick emergency fund, comprises
assets which can very quickly be turned into cash — checking and savings account,
money market funds and accounts; 2) intermediate emergency fund, adds to quick
emergency fund the value of CDS and saving certificates; 3) comprehensive emergency
fund, adds to intermediate emergency fund the value of stocks and bonds which can be
converted to supplement the more liquid assets should intermediate emergency fund
prove inadequate to meet needs.

Citation 7: DeVaney, S. A. & Lytton, R. H. (1995). Household insolvency: A review of
household debt repayment, delinquency, and bankruptcy. Financial Services
Review, 4(2), 137-156.

Abstract: Insolvency can be simply defined as having either a positive or negative net worth. In
the equity sense, insolvency refers to the failure to submit timely repayment of debts as
they mature which can result in an increase in liabilities and a reduction in the equity in
assets held. In the bankruptcy sense, insolvency means that net assets at fair market
value are less than liabilities which can necessitate the liquidation of assets through a
court-ordered bankruptcy process.

However, the study of household insolvency goes beyond concerns over increasing
debt levels and bankruptcy filings. For consumers who are delinquent, late fees and
other collection costs simply add to liabilities that are already not being reduced. Also,
insolvent households impact the “write-off rate” and profit margin of businesses. The
cost for losses and operation of credit scoring systems which are being increasingly
used by businesses to screen good and bad accounts are indirectly passed on to
consumers. The increased cost is borne by those who pay on time as well those who
do not.

While businesses use credit scoring to determine the risk of potential credit applicants,
financial educators, counselors and planners are advocating the use of financial ratios
as tools to help consumers monitor financial progress and anticipate problems.
Beginning with Griffith’s seminal work on the use of ratios in 1985 and continuing with
articles by Mason and Griffith (1988), Lytton, Garman, and Porter (1991), empirical
studies (Prather & Hanna, 1989; DeVaney, 1993, 1994; Fanslow, 1994; Hanna et al.
1993) have attempted to analyze household financial status with financial ratios.
DeVaney (1994) showed that comparing the value of a financial ratio to a guideline was
a statistically significant predictor of insolvency three years later. Ratios which were
most likely to predict insolvency were: the liquidity ratio, the assets-to-liability ratio,
and the annual non-mortgage debt/disposable income ratio.

Educators are encouraged to work with creditors to learn what they are including in
predictive models so that consumers can be better informed and to educate clients to
monitor their financial situation and notify creditors when problems arise as opposed to
the common practice of creditor avoidance. The credit industry is encouraged to
accept responsibility for providing credit information and education to the public.

Citation 8: DeVaney, S. A. & Hanna, S. (1994) The effect of marital status, income, age and
other variables on insolvency. Journal of Consumer Studies and Home
Economics, 18, 293-303.

Abstract: The prediction of insolvency among U.S. households was the focus of this study with
the use of data drawn from the 1983 and 1986 Surveys of Consumer Finance. Analysis
of panel data for a random sample of 1,934 households showed that age of the
household head had a negative relationship with insolvency while income had a strong
negative effect. In 1983, married couples had lower predicted insolvency rates than
other household types. In 1986, the relationship between marital status and insolvency
was not as clear, but married couples with children had substantially lower predicted
insolvency than did single-parent households.

The effects of income and age in reducing the probability of insolvency were generally
reasonable. The results for both years suggest that a single parent would have a much
higher probability of being insolvent than would a married couple at the same income
and age. Obviously, after a divorce, custodial mothers may have low incomes, and
thus, they would have a double disadvantage according to these results. The lack of
significance for race in either 1983 or 1986 suggests that income and marital status/life-cycle differences between whites and non-whites may account for differences in
insolvency between those groups. The lack of a significant effect for education might
be similarly explained.

Citation 9: DeVaney, S. A. (1994) The usefulness of financial ratios as predictors of household
insolvency: Two perspectives. Financial Counseling and Planning, 5, 5-24.

The purpose was to examine the usefulness of financial ratios as predictors of
household insolvency. Financial ratios were developed for 1,934 households using data
from the Survey of Consumer Finances. Guidelines for each financial ratio were
developed based on Lytton, Garman & Porter (1991). Insolvency was defined as
holding net worth less than one month’s income. Two statistical methods—logistic
regression and a classification tree procedure (CART) were used for analysis. The
1983 Liquidity ratio was the most important predictor of 1986 insolvency according to
the logistic regression while the 1983 Assets/Liabilities ratio was the most important
variable in the classification tree. The Gross Annual Debt Payments to Disposable
Income was second in importance for each of the two methods.

The financial goals and expertise of the client and the financial information which is
available to the practitioner and the client may determine the application of ratios to a
client’s financial status. The Gross Annual Debt Payments/Disposable Income ratio
consists of items which are quite readily identified (shelter costs, consumer debt
payments, and disposable income). If families are want to know what amount is
recommended for a cash reserve for emergencies, the Liquidity ratio and guideline
would be useful.

Citation 10: Choi, H. N. & DeVaney, S. A. (1995). Determinants of bank and retail credit card
use. Consumer Interests Annual, 41, 148-154.

Abstract: Data from the 1989 Survey of Consumer Finances were analyzed to find factors related
to credit card use. The findings from logistic regression show that a positive attitude
toward credit, a professional or managerial occupation, and home ownership were
positively associated with the likelihood of using both types of credit cards after
controlling for other socioeconomic factors. With only one exception, retail card use,
the attitude variable was significantly related to credit card use. The attitude held by
consumers toward credit needs to be explored with further research. Whether a
positive attitude toward credit is indicative of the belief that credit cards are a safe and
convenient means of payment or that the attitude encourages over use of credit as a
means of obtaining goods and services. Educators and financial counselors should
work with over-indebted consumers to determine if attitude is a contributing factor in
their debt burden.

Citation 11: DeVaney, S. A. & Keaton, E. (1994). Determining purchasers of whole life insurance
using a classification tree. Research Review: Journal of the Society of
Insurance Research, VII(2), Summer, 33-45.

Classification and regression trees (CART) were used with data from the 1986 Survey
of Consumer Finance to determine purchasers of whole life insurance. Classification
trees were constructed for the total sample, married couples, singles with family, and
singles. The classification tree can be used to predict the unknown response variable of
future cases. In addition to the classification tree, the statistical program produces a
table or relative values for each variable used as a criterion in developing the tree. To
fully understand a classification scheme, the table of relative importance and the
classification tree should be examined.

In determining purchase of whole life insurance, Net Worth was the most important
variable for married couples and singles while Age was the most important variable for
singles with family. Income was second in importance for married couples and third
for singles with family. Net Worth was second in importance for singles with family.
Apparently the purchase of whole life insurance by singles with family is a complex
decision.