Why Collect Time-Use Data?

Mary Joyce, Jay Stewart, Bureau of Labor Statistics

Jay Stewart, BLS, 2 Massachusetts Ave. NE, Rm. 4945, Washington, DC 20212-0001

The views expressed here are those of the authors and do

not necessarily represent those of the Bureau of Labor

Statistics.

Keywords: Time use, National Income and

Product Accounts.

The study of economics often is concerned with

optimal decisionmaking in the face of some sort of

constraint. Economist Thomas Juster has argued

that the ultimate constraint on human activity is

time.1 We are each given 24 hours per day to devote

to competing uses, and how we use that time has

important implications for our financial security,

health, emotional well-being, and general level of

happiness. Time-use surveys attempt to measure the

numerous and diverse ways in which people use

those precious 24 hours.

The Bureau of Labor Statistics (BLS) recently

completed a proposal to conduct a time-use survey

on an ongoing basis. In this paper we describe

BLS’s involvement in time use and what types of

questions time-use data can answer.

BLS Involvement in Time Use

Time use surveys are nothing new. They have

been conducted in many countries going back to the

1920s, although most were conducted after 1970.

However, there have been very few studies in

conducted in the United States. And, except for

except for the United States Department of

Agriculture surveys in the 1920s and 1930s, none

have been conducted by the federal government.

The BLS started looking into measuring time use

after the “Unremunerated Work Act” was introduced

into the 103rd Congress in February 1993. That bill,

which was introduced by Rep. Barbara-Rose Collins

(D-MI), called for BLS to “conduct time-use surveys

of unremunerated work performed in the United

States and to calculate the monetary value of such

work.” Later that year, BLS sent a representative to

a conference sponsored by Statistics Canada entitled

“The Measurement and Valuation of Unpaid Work.”

Following the conference, a report was written for

the BLS Commissioner that reviewed the literature

 

1

 See Juster (1999).

and summarized some of the conceptual issues

related to measuring and valuing unpaid work.

The UN Fourth World Conference on Women

held in Beijing in 1995 highlighted the substantial

interest that exists in measuring and valuing

unremunerated work. The following language is

taken from that conference’s Platform for Action

(item 206), which refers to actions that should be

taken “...by national, regional and international

statistical services and relevant governmental and

United Nations agencies, in cooperation with

research and documentation organizations, in their

respective areas of responsibility.”

“206(g). Develop an international

classification of activities for time-use statistics

that is sensitive to the differences between

women and men in remunerated and

unremunerated work, and collect data

disaggregated by sex. At the national level,

subject to national constraints:

(i) Conduct regular time-use studies to

measure, in quantitative terms, unremunerated

work, including recording those activities that

are performed simultaneously with remunerated

or other unremunerated activities;

(ii) Measure, in quantitative terms,

unremunerated work that is outside national

accounts and work to improve methods to

assess and accurately reflect its value in

satellite or other official accounts that are

separate from but consistent with core national

accounts.” (United Nations, 1995.)

In response to this interest, during 1997, BLS

undertook two significant activities related to the

feasibility of conducting a time-use survey: (1) BLS

hired Westat to conduct a pilot study of two

alternative versions of a time-use survey using a

telephone methodology,2 and (2) BLS co-sponsored a

time-use conference with the MacArthur Network on

Family and the Economy.

Many important messages came out of the

conference. First, there is a great deal of policy and

research interest in time-use data within the U.S.

 

2

 Linda Stinson’s (1999) paper in this section

discusses the issues involved in collecting time-use data.
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Second, the international community is eager for the

U.S. Federal Government to conduct a time-use

survey. In the 1990s, governments in Australia,

Canada, Denmark, Finland, France, Japan, New

Zealand and Germany have conducted time-use

studies. These data provide the U.S. with the

potential for interesting cross-national comparisons

of time use, as well as a wealth of survey experience

from which BLS can draw on when conducting a

time-use survey. Lastly, it was evident from the

conference that the lack of time-use data is regarded

by some, including economist William Nordhaus of

Yale University, as “the single most important gap

in our federal statistics.”

Following the conference, BLS Commissioner

Abraham asked that a working group be set up for

the purpose of producing a report examining the

feasibility of conducting a survey on how Americans

spend their time. The working group’s report was

presented at the National Academy of Sciences

Workshop on Measurement of and Research on

Time Use. This paper and the ones that follow

present some of the highlights from that report.

What Can We Learn From Time-Use Data?

Time-use data could contribute to research and

policy analysis in a number of areas. One area that

has recently received considerable attention is the

prospect of measuring and valuing unpaid but

productive activities (that is, nonmarket work) with

the ultimate goal of including the value of these

activities in a satellite account of the National

Income and Product Accounts (NIPAs). Although

the valuation of nonmarket work has been the

primary political impetus behind the collection of

time-use data, it is by no means the only use of these

data. In this article, we discuss some of the many

applications of time-use data.

National estimates

Perhaps the most fundamental application of

time-use data would be to provide nationally

representative estimates of the amount of time that

Americans spend in various activities. The types of

activities that could be captured include: productive

nonmarket activities such as housework; home

maintenance and repairs; child care and care of

elderly and disabled persons; leisure activities such

as watching television, reading books or magazines,

pursuing hobbies, and socializing with friends; and

nonproductive, nonleisure activities, such as waiting

in line and commuting.3

If time-use data were combined with

demographic information, such as that available

from the Bureau of Labor Statistics Current

Population Survey (CPS), it would be possible to

compare time use across different groups. For

example, analysts could compare time spent in

housework and child care between men and women;

time spent on educational activities between students

and nonstudents, or between students at different

grade levels; time spent on leisure activities between

single and married parents; time spent watching

television between persons in families of differing

earnings and income levels; and time spent cooking

and cleaning between persons with differing levels of

market work. Conducting a time-use survey on an

ongoing basis would allow researchers to study how

the time spend in various activities changes over

time.

The availability of national time-use data would

also facilitate comparisons of time-use patterns in

the United States with patterns in other countries. In

addition to comparing measures of material wellbeing such as GDP, analysts could also study how

Americans fare on such nonmaterial dimensions as

hours of free time.

Valuing nonmarket work

A long-standing criticism of our system of NIPAs

is that they count only productive activities that are

transacted in the market economy and ignore

productive activities that take place outside the

market, particularly those done in the home. In

recent years, there has been renewed interest, as

evidenced by the Beijing Conference’s Platform for

Action, in placing a monetary value on nonmarket

work.

Aside from putting a dollar figure on household

work, accounting for the value of nonmarket

production would provide a more comprehensive

picture of aggregate output, income, and productivity

in the United States. For example, the increase in

women’s labor force participation has resulted in a

shift from nonmarket work to market work. This

increase in market work caused measured gross

national product and per capita income to rise,

resulting in a somewhat distorted pictured of the

trends in aggregate production and income because

 

3

 See Stinson (1999) for a description of various

activity classification systems that have been used to

capture the ways in which people spend their time.
-3-

the accompanying decrease in nonmarket work was

never accounted for.

Valuing the time spent in nonmarket activities

will undoubtedly be challenging and controversial.

A key conceptual issue in measuring nonmarket

work is deciding on exactly what should be

measured. In order to distinguish between

productive and personal activities, the “third person

criterion” is often used. Under this criterion, an

activity is deemed productive if it could be delegated

to someone else while achieving the desired result.

For example, preparing a meal would be considered

nonmarket work, but eating it would not be.4

After deciding which activities are productive,

the next step is to place a value on these activities.

This valuation can be done a number of ways. One

approach, known as the output approach, involves

identifying the outputs (that is, goods or services)

that result from these productive activities and then

assigning a price to those outputs. Although this

approach is conceptually closer to the way market

goods are treated in the NIPAs, data availability

issues make it difficult to implement in practice.5 A

second approach, known as the input approach,

requires an estimate of the amount of time spent in

productive activities that is then multiplied by a

wage rate. The time spent in nonmarket work can be

readily obtained from a time-use survey, and the

wage rate can be imputed in a number of ways.

To illustrate, consider the simple example of

building a deck for a house. There are three possible

wage rates that could be used to value this activity:

(1) the individual’s wage rate at his or her job, (2)

the “specialist” wage rate (the average wage for

carpenters), or (3) the “generalist” wage (the average

wage for handymen). Although there are advantages

 

4

 The third person criterion is the most general

criterion used to distinguish unpaid work from personal

activities. However, Statistics Canada (1995) and

INSTRAW (1995) have developed other criteria that are

used to qualify the third person criterion.

5

Ironmonger (1997) argues for the construction of

national household accounts that would be completely

separate but analogous to the national income and product

accounts (which he would believes should be renamed the

national market accounts). These accounts would not only

measure outputs from household production but also

households use of labor, capital, and intermediate

materials. In order to construct such accounts, he argues

that three types of household surveys are essential:

household time-use surveys, household expenditure

surveys, and household output surveys. According to

Ironmonger, the latter has not been done by any national

statistical office.

and disadvantages to each, most analysts use the

“generalist” wage.6

There are three drawbacks to the input approach.

First, as with market work, the time spent in an

activity may not be a good indicator of the value of

the output produced. For example, someone who has

never built a deck would take longer than someone

with more experience to build a deck of similar

quality. Second, the choice of wage rates used to

value various activities is somewhat arbitrary.

Finally, many types of nonmarket activities are

performed simultaneously with other activities (for

example, providing child care and watching

television) and researchers have not yet reached a

consensus on how to value the time spent doing

simultaneous activities.

Verifying and interpreting existing series

Time-use data can also aid analysts in verifying

data that currently are collected in a number of

surveys. Data on hours worked provide an example.

It has been noted by researchers (Abraham, Spletzer,

and Stewart, 1998 and Robinson and Godbey, 1997)

that, over the past 20 years or so, average weekly

hours as measured by the Current Employment

Statistics survey (CES), a BLS establishment survey,

have declined, while average weekly hours in the

CPS, a BLS household survey, have remained fairly

constant.7 This discrepancy has called into question

the accuracy of hours worked data reported in

household surveys such as the CPS.

Robinson and Bostrom (1994) compared hours

worked measures obtained from time-diary data with

those obtained from a CPS-like question. They

found that respondents tended to report more hours

worked in the CPS-like question than in time diaries,

that people who worked more hours tended to

overreport by a larger amount, and that

overreporting increased between 1965 and 1985.

However, Jacobs (1998), using data from the 1992

National Survey of the Changing Workforce, found

that the CPS-style measures of the workweek

correlate well with a new measure of work time

derived from questions that ask for departure and

return times from work (less commuting time).

Jacobs also argued that the discrepancy between the

time-use diaries and CPS estimates of the length of

 

6

 See Goldschmidt-Clermont (1997) and Landefeld

and Howell (1999)

7

 Note that the levels of the two measures are expected

to differ because they measure different concepts (hours

worked in the CPS and hours paid in CES). However, this

should not affect the trends.
-4-

the workweek may be a statistical artifact resulting

from random measurement error in both measures.

Conducting a time-use survey would be a useful way

of studying whether respondents tend to overreport

hours worked in the CPS survey.8

Similarly, existing information on the time spent

commuting could also be verified with time-use data.

National data on hours spent commuting typically

come from a standard survey question that asks,

“How many minutes does it usually take you to get to

work?” This question was asked in the 1990 Journey

to Work Survey conducted by the Census Bureau as

part of the decennial Census. These data could be

compared to those obtained from a time-use survey

that collects information on start and stop times for

all activities, including traveling to work.

Time-use data could also be helpful in

interpreting price index data. It has been argued that

part of the reason that inflation has been so low is

that consumers have to wait more for some services

and that they shop around more for bargains. For

example, health maintenance organizations typically

charge less than fee-for-service health plans, but

their patients also typically wait longer to see a

health-care provider. This reasoning implies that

people are increasingly substituting time for money.

A time-use survey that is linked to an

expenditure survey, such as the Consumer

Expenditure Survey, would make it possible to attach

a “time cost” to specific goods and arrive at an

alternative price index. In the absence of this

linkage, time-use data collected over multiple

periods could shed light on trends in these types of

time expenditures. For example, a stable inflation

rate of, say, 3 percent per year may indicate

inflationary pressures if consumers are, in actuality,

spending increasing amounts of time waiting or

shopping for bargains.

Measuring real income and well-being

Typically, analysts use quantifiable measures,

such as real income or earnings, to assess changes in

the quality of life over time. Collecting information

on time use would permit a more complete

assessment of changes in quality of life. For

 

8

 There are two drawbacks to using time-use data to

verify CPS hours, however. First, time use is measured

during one 24-hour period, so that comparisons would only

be made possible by constructing synthetic workweeks.

Second, the effect of proxy reporting in the CPS, which

may account for some of differences between household

labor force information and time diary data, could not be

determined.

example, stories in the popular press report that

some individuals have quit high salary jobs that

require long working hours to take lower paying jobs

with fewer hours. While these people consider

themselves “better off,” any objective measure of

income or earnings would indicate that these

individuals are “worse off.” Data from a time-use

survey that is linked to a household survey, such as

the CPS, would permit analysts to account for the

increase in nonmarket production and leisure time

when assessing changes in quality of life.

A broader income measure also would improve

analyses of earnings and income inequality, both of

which have increased in recent years. However,

analyses that ignore home production and leisure

may be misleading. This point also applies to the

measurement of poverty. With time-use data, it is

possible to measure a family’s command over a

broader set of resources.

Education and training

One important form of investment for any society

is the amount of time and resources spent by both

children and adults in learning activities. Many

learning activities, particularly among young

children, take place at home rather than in formal

educational institutions. A time-use survey,

particularly one that collects diaries from or about

children, can provide information on the amount of

time that preschoolers spend reading or interacting

with parents and the amount of time that school-age

children spend doing homework. Comparisons, both

over time and across countries at a point in time, of

the time spent in these learning activities would be

informative.

Policy and business cycle changes

At present, we know a great deal about how

policy changes affect individuals’ labor market

behavior. For example, higher income taxes tend to

reduce labor supply. But little is known about how

government policies affect the way individuals spend

their nonworking time. Do they engage in more

nonmarket production or do they consume more

leisure? Time-use data can shed light on this issue.

If time-use data are collected on a continuous

basis, as are CPS data, analysts could examine how

time-use patterns change over the business cycle.

For example, during recessions, do people shift from

take-out meals to home cooked meals, or from

purchased laundry services to doing their own

laundry? Time-use data could also be used to study

how unemployed persons use their time—how much
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time is spent on job search, retraining and education

activities, nonmarket production, and leisure? Timeuse among the nonemployed could also help refine

our definitions of a “discouraged” worker.

Business and legal applications

Marketing is one area of business that would

likely be interested in time-use data. Marketers

could use this information to determine how time

spent in various activities (for example, television

viewing, radio listening, shopping, eating out)

differs by demographic characteristics, earnings, and

income.

Time-use data also have legal applications. For

example, these data may be useful to those

estimating the economic damages in personal injury

and wrongful death cases. Typically, economic

damages primarily include lost earnings. The value

of home production either is omitted from the

valuation, is based on old survey data, or is created

from the survivors’ estimates of nonmarket

production. Time-use data on a nationally

representative sample would provide a more

complete picture from which to estimate the

economic loss associated with an injury or wrongful

death.

Timing of activities

In addition to providing information on the

duration of time spent in various activities, a timeuse survey also captures the time of day that

activities take place and the sequence in which

activities are undertaken. This type of information

could be used in a variety of research applications.

For example, data on when and how much people

sleep could be used by researchers interested in the

studying sleep patterns. Data on when people work

could be used to determine the wage premium

required to compensate workers for working at

undesirable times. Psychologists could also use

time-use data to study the degree and nature of

multitasking. What types of people typically do

more than one thing at a time? What types of tasks

usually get grouped together?

Conclusions

Because time-use surveys collect information on

all the activities that individuals engage in during a

24-hour period, time-use data are remarkably wide

in scope. Availability of such information would

allow researchers to answer a host of questions that

have long been neglected because the data were not

available to address them. In this article, we have

listed some of the potential applications of time-use

data. Undoubtedly, we have only scraped the

surface. As Rebecca Blank, an economist at the

Council of Economic Advisors stated it at a recent

National Academy of Sciences conference: “After

having time-use data, researchers will wonder how

they ever did research without it.”

References

Abraham, Katharine, James Spletzer, and Jay

Stewart (1998) “Divergent Trends in Alternative

Wage Series,” in Labor Statistics Measurement

Issues, John Haltiwanger, Marilyn Manser, and

Robert Topel, eds., University of Chicago Press,

1998.

Goldschmidt-Clermont, Luisella (1993) “Monetary

Valuation of Non-Market Productive Time:

Methodological Considerations.” Review of

Income and Wealth, series 39, no. 4, pp. 419-

434, December 1993.

Gronau, Reuben (1986) “Home Production: A

Survey,” in Handbook of Labor Economics,

edited by Orley Ashnefelter and Richard Layard,

Vol. 1, Elsevier Science, New York.

INSTRAW (1995) “Measurement and Valuation of

Unpaid Contribution: Accounting through Time

and Output,” INSTAW, Santo Domingo,

Dominican Republic.

Ironmonger, Duncan (1996) “Time Use and

Satellite Accounts for Modeling the Household

Economy”, prepared for the IARIW 24th General

Conference, Lillehammer, Norway, August 1996.

Ironmonger, Duncan (1997) “ National Accounts of

Household Productive Activities”, prepared for

the Conference on Time Use, Non-Market Work,

and Family Well-Being, November 1997.

Jacobs, Jerry A. (1998) “Measuring time at work:

are self-reports accurate?”, Monthly Labor

Review 121(12), December 1998, pp. 42-53.

Jackson, Chris (1997) “The Valuation of Unpaid

Work-A Canadian Perspective”, prepared for the

Conference on Time Use, Non-Market Work, and

Family Well-Being, November 1997.
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Juster, Thomas (1999) “Time Use Data: Analytic

Framework, Descriptive Findings, and

Measurement Issues,” Paper prepared for the

Workshop on Measurement of and Research on

Time Use (National Academy of Sciences,

Washington, D.C.), May 1999.

Landefeld, Steven and Stephanie Howell (1999)

“Accounting for Nonmarketed Household

Production within a National Accounts

Framework”, unpublished manuscript, Bureau of

Economic Analysis, Washington, D.C., April

1999.

Robinson, John and Ann Bostrom (1004) “The

overestimated workweek? What time diary

measures suggest,” Monthly Labor Review

117(8), August 1994, pp. 11-23.

Robinson, John and Godbey, Geoffrey (1997) Time

for Life: The Surprising Ways Americans Use

Their Time, Pennsylvania State University Press.

Statistics Canada (1995) “Household’s Unpaid

Work: Measurement and Valuation,” Catalogue

No. 13-603E. No 3—occasional.

Stinson, Linda (1999) “Measuring how people

spend their time,” ASA Papers and Proceedings,

August 1999.