URC

An Examination of Americans' Time Spent in Financial Management

MaryPat Peeples
Melissa J. Wilmarth*

University of Alabama

Abstract

In-depth analysis of individual time use and comparison of time use and finances as problems within financial management can be addressed. The 2012 panel of the American Time Use Survey (ATUS) was utilized to investigate how minutes spent in financial management varied by demographic characteristics: education, gender, race, if children are present in the household, marital status, income, and employment status. On average, Americans spent 1.86 minutes (SD=18.24) in financial management daily (N=12,443). Differences in minutes spent in financial management were tested by characteristic via one-way ANOVAs and t-tests. Results indicated that time spent in financial management varies with the presence of children in the household, marital status, education, and employment status, but not by gender, race, or income level.

Introduction and Background Literature

Today it is common for American's to experience a time crunch from many activities competing for time. Studying time use is important in order to identify areas that create a time crunch or where individuals lack productivity. When identified, these problem areas can be addressed and individuals can become more productive, which in turn creates a more productive society. "How people allocate the 24 hours that they have in each day has important implications for their financial security, physical health, emotional well-being and general level of happiness" (Hamermesh, Frazis, & Stewart, 2005, p. 221). Time use data can shed light on important economic measures, such as time spent working in the labor force, how leisure time is used, and household production activities.

People are regularly confronted with household problems and tasks that need to be solved or completed within their households. Two options are present: they can choose to purchase or outsource the service or they can choose to perform the service on their own (Krantz-Kent, 2009). Past research of time spent in home production has been dominated by investigations of women's time in home production, specifically activities such as cleaning, cooking, and home maintenance (e.g., Hersch, 2009; Hersch & Stratton, 2002). For example in a traditional viewpoint, a family may choose to cook a meal at home or go out for the meal at a restaurant. Further, consumers can choose to manage their finances themselves at home or seek outside help in various forms. To our knowledge, no research has specifically investigated the area of home production as specifically identified as time spent in financial management.

Time-use and financial wellness are directly connected. Financial management connects the link between productivity and financial wellness. By in-depth analysis of individual time use and comparison of time use and financial wellness, problems within financial management can be addressed. Many variables are present when analyzing the connection between time use and financial management. Education, gender, race, presence of children in the household, marital status, and income are all factors that should be considered during analysis.

On an individual level, financial wellness is directly dependent upon the degree of importance placed in financial management. The greater the investment of time spent analyzing individual finances, the greater the return and stability of the individual financially. To form a better understanding of Americans' time use as it relates to financial management, we examined the following research questions and hypotheses.

  1. How much time do Americans spend in financial management daily?
     
  2. Does time in daily financial management differ by demographic characteristics?

    Gender Hypothesis: Male respondents spent more time in financial management than female respondents.

    Children Hypothesis: Respondents without children present in the household spent more time in financial management than those with children.

    Race Hypothesis: White respondents spent more time in financial management than Black respondents or respondents of other races.

    Marital Status Hypothesis: Married respondents spent more time in financial management than single respondents.

    Income Hypothesis: Respondents with higher income spent more time in financial management than those with lower income.

    Education Hypothesis: Respondents with higher education spent more time in financial management than those with lower education.

    Employment Hypothesis: Respondents not employed or not in the labor force spent more time in financial management than employed respondents.

Methodology

Data

To examine the research questions we utilized the 2012 panel of the American Time Use Survey (ATUS), which outlines how Americans use their time. Sponsored by the Bureau of Labor Statistics and collected by the U.S. Census Bureau, the ATUS measures how the American public spends time. The ATUS is a collection of nationally representative data that measures how Americans spent time in both market and nonmarket activities. The ATUS sample is drawn from an existing sample of the Current Population Survey (CPS). In general, individuals are sampled approximately 3 months after completing their final CPS survey.

Administered by a computer assisted telephone interview (CATI) survey, the ATUS chronicles a 24-hour time diary of the sample participants. The respondents report their activities from the previous day by giving an hourly description of their designated diary day. The description is coded by the interviewer into the outlined categories in which the ATUS categorizes time usage into seventeen top level categories and many second and third level categories for additional detail of activities (the ATUS has over 400 detailed time use categories used for classification). Information on personal and household characteristics also is collected during the ATUS interview. See Hamermesh, Frazis, and Stewart (2005) for more detailed information about the types of activities recorded in the ATUS.

Sample

The sample for this study was constructed using the ATUS-X Extract Builder, version 2.4 (Hofferth, Flood, & Sobek, 2013). The extract builder allowed us to build the data file to include all respondents in the 2012 panel and specify variables of interest for the research questions. This study had a final sample size of 12,443 respondents.

Demographic information about the sample is included in Table 1. The average age of the sample was about 48 years old. Just over half of the sample (55.51%) were women and just less than half (44.13%) of households had children present. Over three-fourths of the respondents were white (78.85%) and 15.23 percent were black. Almost half of the sample (48.31%) were married while the rest were single, but previously married (26.56) or single never married (25.13%). When considering employment, almost half (46.68%) of the sample were employed full-time and more than a third (39.95%) were either not in the labor force or unemployed.

Table 1
Demographic information

Variable

Mean (SD)/Frequency

Range

Minutes Spent in Financial Management

1.86 (18.24)

0-985

Age

47.91 (17.83)

15-85

Gender (%)

 

 

Male

44.49

 

Female

55.51

 

Children Present (%)

 

 

Yes

44.13

 

No

55.87

 

Race (%)

 

 

White

78.85

 

Black

15.23

 

Other

5.92

 

Marital Status (%)

 

 

Married

48.31

 

Single (previously married)

26.56

 

Single (never married)

25.13

 

Income (%)

 

 

Less than 20,000

20.02

 

20,000-39,999

23.15

 

40,000-59,999

17.39

 

60,000-99,999

21.06

 

100,000 and over

18.37

 

Education (%)

 

 

Less than HS

14.48

 

HS Degree or GED

25.37

 

Associate's or Some College

27.59

 

Bachelor's Degree

20.13

 

Graduate Degree

12.42

 

Employment Status (%)

 

 

Full-Time Employment

46.68

 

Part-Time Employment

13.36

 

Not in Labor Force or Unemployed

39.95

 

Note. N=12,443

Analysis

Univariate and bivariate statistics were used to answer the proposed research questions. Differences in the amount of time (minutes) spent in financial management were tested by a variety of characteristics via one-way ANOVAs and t-tests. We investigated how time (minutes) spent in financial management varied by demographic characteristics, including education, gender, race, if children were present in the household, marital status, income, and employment status.

Measurement of Variables

Variables were accessed and transformed from the ATUS-X Extract Builder, version 2.4 (Hofferth, Flood, & Sobek, 2013). Time spent in financial management and age were both measured as continuous variables. The time spent in financial management variable was measured in minutes, including zero for no time spent in financial management. Gender and children present in the household are both dummy variables; gender (0=male and 1=female) and children present (0=no children and 1=children present in household). The inclusion of children refers to all children living in the household at the time of the interview (whether or not related to the respondent).

The other variables (race, marital status, income, education, and employment status) were all measured as categorical variables. Race was measured as White, Black, or other race. Marital status categories included currently married, single-previously married, and single-never married. The income and education variables each were measured in five categories; income (less than $20,000; $20,000-$39,999; $40,000-59,999; $60,000-$99,999; $100,000 and over) and education (Less than High School; High School or GED; Associate degree or Some College; Bachelor's Degree; Graduate Degree). Employment status included the categories of full-time employed, part-time employed, and unemployed or not in the labor force.

Results

The first research question was answered using the univariate statistic of a mean. On average, Americans spent 1.86 minutes in financial management daily (N = 12,443). The second research question was investigated using bivariate statistics. Analyses indicate that time spent in financial management varied by four of tested characteristics, but not by three of the characteristics. The characteristics that did not statistically differ in amount of time spent in financial management were gender, race, and income. Results for the second research question are presented in Table 2.

Table 2
Bivariate analysis

T-Tests for 2 Category Variables

Mean of Financial Management (SD)

T-Value

P-value

Gender

 

 

 

Male

1.95 (23.18)

0.44

0.6592

Female

1.80 (12.99)

 

 

Children Present

 

2.79

0.0002***

Yes

1.22 (10.19)

 

 

No

2.37 (22.64)

 

 

ANOVAs for Categorical Variables

Mean of Financial Management (SD)

F-Value

P-value

Race

 

1.96

0.1406

White

2.03 (19.81)

 

 

Black

1.28  (9.63)

 

 

Other

1.15 (12.30)

 

 

Marital Status

 

3.64

0.0262**

Married

1.99 (15.38)

 

 

Single (previously married)

2.31 (21.46)

 

 

Single (never married)

1.13 (19.52)

 

 

Income

 

1.06

0.3743

Less than 20,000

1.74 (21.89)

 

 

20,000-39,999

1.77 (13.94)

 

 

40,000-59,999

1.51 (13.41)

 

 

60,000-99,999

2.49 (24.22)

 

 

100,000 and over

1.73 (14.19)

 

 

Education

 

2.63

0.0323**

Less than HS

0.81 (6.27)

 

 

HS Degree or GED

1.63 (18.64)

 

 

Associate's or Some College

2.05 (22.97)

 

 

Bachelor's Degree

2.15 (16.93)

 

 

Graduate Degree

2.67 (16.84)

 

 

Employment Status

 

2.34

0.0962*

Full-Time Employment

1.64 (21.15)

 

 

Part-Time Employment

2.74 (18.54)

 

 

Not in Labor Force or Unemployed

1.82 (13.49)

 

 

Note. N=12,443
* p < 0.10, ** p < 0.05, *** p < 0.01

On average, households with children (M = 1.22) spent less time in financial management than households without children (M = 2.37). There was a statistically significant difference in how much time people spent in financial management when comparing married individuals (M = 1.99), single-previously married (M = 2.31), and single-never married (M = 1.13). Examining education, time spent in financial management varied when comparing those having less than a high school degree (M = 0.81), high school or GED (M = 1.63), associate degree or some college (M = 2.05), bachelor's degree (M = 2.15), and graduate degree (M = 2.67). Employment status showed marginally significant differences in time spent in financial management; those with full-time employment (M = 1.64), part-time employment (M = 2.74), and those not in the labor force and unemployed (M = 1.82).

Conclusions and Implications

There are many issues impacting American time use. For general time use, there has been an increase in demands on families' time. Specifically related to financial time use, during the recent recession many households experienced drastic drops in financial resources (i.e., income, investments, wealth), unemployment reached record levels, and consumer confidence fell to an all-time low. These refocused the attention of many Americans to their specific financial situation. The core of this work investigated seven hypotheses about how different demographic categories of American's spend time in financial management.

Three hypotheses were not supported with statistical significance; gender, race, and income. Two hypotheses, children present in the household and education of respondents, were fully supported. As expected, households with children spent less time in financial management than households without children. This is most likely due to the time demands that caregiving of children places on respondents, reducing the amount of time available for financial management. Those with higher levels of education spent more time in financial management than those with lower education, which may be due to more awareness of the need for financial management, time availability for financial management, or more resources needing financial management. Education may be acting as a proxy for income and acting differently than the income variable we used, so those with higher education levels may have higher incomes and more assets they need to manage.

The hypotheses for marital status and employment status were both partially supported, meaning that one of the categories acted as expected, but one did not. For marital status, it was hypothesized that married respondents would spend more time in financial management than single respondents. This was partially supported in the fact that married respondents spent more time in financial management than those who were single and never married before. This is most likely happening because of possible resource pooling in the marriage as well as having more needs to be met in a marriage than for a single respondent. Respondents who were single but previously married spent more time in financial management than both married and single, never married respondents. This could be due to the experience of previously being married specific to the result of a divorce or a loss of a spouse. Both of those experiences have large financial effects which may cause a need for more vigilance in financial management.

It was hypothesized that respondents who were not employed or not in the labor force would spend more time in financial management than employed respondents. This was partially supported in that those not in the labor force or unemployed spent more time in financial management than those with full-time employment. What was not expected was that respondents with part-time employment spent more time in financial management than those with full-time employment. This could be because of less resources needing to be stretched further (assuming part-time employees make less than full-time employees), the availability of time to spend in financial management (assuming part-time employees spend less hours in the labor market than those with full-time employment), or a combination of both.

A greater understanding of Americans' time use in financial management gives researchers an idea of level of importance and demand for the activity as well as the need for outsourcing this task. The topic of time use and financial management has many options for future research projects. Investigating time spent in financial management over time (i.e., before and after the economic crisis to see how consumers respond); identifying the correlates of time spent in financial management to better understand what predicts time use in this area; and time spent in financial management and its relationship to financial wellness will give a better understanding of consumers' financial health.

Overall, the data show that Americans are spending time in financial management on a daily basis as part of their work in household production. The demographic differences in who is spending more or less time in financial management are interesting to know who is conducting financial management activities. The results of this study will help those working in financial education and financial services industry to target their services—who needs help with more efficient financial management techniques because they have less time to spend in financial management or who may not spend much time in financial management and may benefit from outsourcing financial management to a financial services professional like a financial planner.

Works Cited

Hamermesh, D. S., Frazis, H. & Stewart, J. (2005). Data watch: The American Time Use Survey. Journal of Economic Perspectives, 19(1), 221–32.

Hersch, J. (2009). Home production and wages: Evidence from the American Time Use Survey. Economic Review of the Household, 7, 159-178.

Hersch, J. & Stratton, L. S. (2002). Housework and wages. The Journal of Human Resources, 37(1), 218-229.

Hofferth, S.L., Flood, S. M., & Sobek, M. (2013). American Time Use Survey Data Extract System: Version 2.4 [Machine-readable database]. Maryland Population Research Center, University of Maryland, College Park, Maryland, and Minnesota Population Center, University of Minnesota, Minneapolis, Minnesota. Available at: http://www.atusdata.org.

Krantz-Kent, R. (2009). Measuring time spent in unpaid household work: Results from the American Time Use Survey. Monthly Labor Review, U.S. Bureau of Labor Statistics.

 


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