Monthly Labor Review • August 2010 17

Time-Use Surveys

Time-use surveys: issues in data

collection on multitasking

Secondary-activity reports from the American Time Use

Survey are not as good as those from the Family

Interaction, Social Capital, and Trends in Time Use

survey; statistical analysis reveals that the difference

is attributable to the fact that such reports are

requested in the former, but volunteered in the latter

Robert W. Drago

and

Jay C. Stewart

Robert W. Drago is research director at the Institute for Women’s 

Policy Research, Washington, 

DC; Jay C. Stewart is Division 

Chief, Division of Productivity 

Research and Program Development, Office of Productivity and 

Technology, Bureau of Labor 

Statistics. E-mail: drago@iwpr.org 

or stewart.jay@bls.gov

Time-use surveys collect information on how people spend their time. In the American Time 

Use Survey (ATUS), as in many other 

time-use surveys, respondents are asked 

to report sequentially what they did on 

the day before the interview. The reports 

they provide offer a detailed look at how 

Americans spend their time. However, the 

picture is not complete because the ATUS

does not have information on multitasking (secondary activities).

Why might researchers be interested 

in multitasking? First, researchers studying work-life balance are interested in the 

extent to which people, especially women, 

multitask to get more out of their day. 

Second, researchers who wish to measure 

household production would want to include household work that is done as a secondary activity. Third, for many questions, 

it is important to capture all episodes of a 

particular activity. For example, researchers 

interested in the causes of obesity may want 

to examine eating as a secondary activity or 

which activities people combine with eating 

when it is the primary activity. Fourth, secondary activities can provide a more complete picture of childcare, because much 

childcare is done as a secondary activity. The 

ATUS already collects information on passive 

childcare (having children “in your care” while 

doing something else), but does not capture activities such as reading to and playing with children while waiting or traveling (as a passenger).

Although the ATUS does not ask respondents to report secondary activities, the information is recorded if the respondent volunteers 

that he or she was doing something else at the 

same time. However, only the primary activity 

is coded. For example, if the respondent reports 

eating as a primary activity and watching television as a secondary activity, both activities are 

recorded but only eating is coded. Surveys that 

systematically collect information on secondary activities (for example, the Australian Government’s time-use survey and some of the earlier U.S. surveys) do so by asking respondents, 

“What else were you doing?”

It is well known that respondents are more 

likely to report information when they are 

directly asked to do so than when they must 

volunteer to give the information.1 Thus, one 

would expect the former approach to result 

in better information on secondary activities 

than the latter. But when respondents report 

a secondary activity, it can be either simultaneous with the primary activity or sequential. 
Time-Use Surveys

18 Monthly Labor Review • August 2010

The question “What else were you doing?” is designed 

to collect information about activities that are done at 

the same time as the primary activity (simultaneous 

activities), such as listening to the radio while driving 

or reading to a child while riding the subway. However, respondents may find it convenient to report certain 

short-duration activities as secondary, even though 

they were really the primary activity. For example, if 

a respondent interrupts his or her dinner preparation to answer the phone, these activities should be 

recorded as cooking, talking on the phone, and cooking. Instead, the respondent might report the single 

activity of cooking and report talking on the phone as 

a secondary activity. 

In a perfect world, respondents would identify all 

sequential activities as primary, taking the time to 

report the starting and stopping times, whom they 

were with, and where they were. Only true simultaneous activities would be reported as secondary (or 

ignored if secondary activities are not collected). But 

interviewers and respondents are not perfect: it may 

be less burdensome for respondents to report shortduration sequential activities as secondary activities 

rather than as primary activities because they do not 

have to provide any additional information about 

the activity. Thus, secondary-activity reports almost 

certainly include short-duration sequential activities 

that respondents did not report separately, as well 

as true simultaneous activities. However, the collection of secondary activities could help respondents 

recall their primary activities more accurately. Consequently, it is not clear how the quality of primaryactivity reports is affected by the collection of secondary activities.

The extent to which respondents report short-duration sequential activities as secondary may depend, 

in part, on the survey’s procedures. For example, when 

faced with a volunteered secondary-activity report, 

ATUS interviewers are instructed to “try to break apart 

[secondary] activities [into primary activities] if you 

can but do not challenge the [respondent].”2 All timeuse surveys entail some interaction between interviewers and respondents, to clarify respondents’ reporting 

of their activities. However, one would expect to see 

less reporting of sequential activities as secondary in 

the ATUS than might be the case if interviewers were 

not so instructed or if the ATUS used leave-behind paper diaries, which allow respondents to choose how 

to report these activities. If there is no mechanism for 

collecting secondary activities (either requested or volunteered), one might expect respondents to be more likely to 

report a short-duration sequential activity as primary.

An earlier study by Ragne Kitterod sheds light on this issue.3

 She used a unique survey from a Norwegian survey that 

collected diaries for two consecutive days. On the first day, 

respondents were asked to report only primary activities; on 

the second day, they were asked to report secondary activities 

as well. Kitterod’s empirical findings strongly suggest that 

the pattern of primary-activity reports differs across the two 

diary days. When women with children were asked to report 

secondary activities, the most common ones reported were 

socializing (136 minutes per day), watching television (87 

minutes), providing childcare (48 minutes), and engaging in 

other leisure activities (23 minutes). When respondents were 

not asked to report secondary activities, a slightly greater 

amount of primary-activity time was reported for these activities, with 4 additional minutes of socializing, 6 additional 

minutes watching television, 12 additional minutes providing childcare, and 4 additional minutes engaging in other 

leisure activities. The pattern for men with children is similar, 

except that, contrary to expectation, they report more time 

socializing as a primary activity when secondary activities 

are collected.

Kitterod’s findings still leave unanswered the question 

of whether the ATUS approach leads respondents to report 

more sequential activities as primary activities. Here, it is 

important to note that the ATUS approach is not comparable 

to that used in the Norwegian study. As noted, the ATUS interviewers ask respondents to determine whether activities 

are truly simultaneous. In contrast, respondents to the Norwegian survey were instructed on the first day to list “only 

one task during each period.”4 It is possible that respondents 

reported more short-duration sequential and simultaneous 

activities as primary activities on the first day, when there 

was no secondary-activity option. In addition, keep in mind 

that the diaries were leave-behind diaries, which means that 

there was no interviewer to prompt the respondent to break 

apart activities.

The purpose of the study presented in this article is to 

examine alternative approaches to collecting information 

on secondary activities and the implications for collecting 

information on primary activities. The study addresses two 

issues:

1. How is the quality of information on secondary activities affected by the method of collection?

2. How does the collection of information on secondary 

activities affect the quality of primary-activity reports?

For this study, the 2006 ATUS secondary-activity reports were 
Monthly Labor Review • August 2010 19

specially coded, making it possible to compare those reports with secondary-activity reports from the 1998–99 

Family Interaction, Social Capital, and Trends in Time 

Use (FISCT) survey, the most recent time-use survey that 

asks respondents to report secondary activities.5

Data

The ATUS is a stratified three-stage sample drawn from 

households that recently completed their participation in 

the Current Population Survey (CPS). CPS households are 

stratified on the basis of their characteristics, and ATUS

sample households are randomly selected from the resulting strata. One individual is then randomly selected from 

the list of adult (15 years or older) household members. 

All adults in the household have the same probability of 

selection. The survey is designed to be nationally representative of the civilian noninstitutional population 15 

years and older.

The ATUS is sponsored by the Bureau of Labor Statistics and is conducted by the U.S. Census Bureau via 

computer-assisted telephone interviewing (CATI). All 

ATUS respondents are assigned an initial diary day and are 

called the next day. If a complete interview is not obtained 

on the initial interview day, subsequent contact attempts 

are made on the same day of subsequent weeks. This procedure maintains the assignment of respondents to days 

of the week.

The ATUS core time diary is similar to time diaries of 

other surveys. The respondent is asked to describe his 

or her day sequentially from 4 a.m. “yesterday” through 

4 a.m. “today.” The respondent describes each activity, 

which the interviewer either records verbatim or, for a 

limited set of commonly performed, unambiguously defined activities (such as sleeping or watching television), 

enters an activity precode. The verbatim responses are 

coded to a three-tiered scheme, going from major activity categories, to subcategories, to descriptions of specific 

actions that together are considered to make up a single 

third-tier activity. As noted earlier, only the primary 

activity is coded and interviewers ask respondents to 

break apart secondary activities into primary activities. 

For each activity reported, the ATUS interviewer records 

either the ending time or the duration of the activity. 

The interviewer also asks where the respondent was and 

whom the respondent was with, unless the activity is 

sleeping, grooming, a personal activity, “refused” (none 

of your business, and so forth), or “don’t know.” For paid 

work, respondents are asked to report where they were, 

but not whom they were with. 

After the time diary has been completed, the ATUS interviewer asks several summary questions, including questions on passive childcare that obtain information which 

cannot readily be obtained from the core time diary. These 

questions ask about times or activities during which children under 13 were “in your care.” In 2006 and 2007, the 

“Eating and Health” module in the ATUS collected information about eating and drinking as a secondary activity, 

along with other information.

For this study, the Census Bureau coded secondary activities reported in the 2006 ATUS data. Each secondary 

activity was coded by two independent coders and was 

adjudicated when there were differences (as is done in 

coding primary activities). Coding was performed by the 

same team that codes the primary activities in the ATUS, 

thereby ensuring that the coding of secondary activities 

is of high quality and is consistent with that of primary 

activities.

The FISCT was conducted between March 1998 and 

March 1999, and its sample of 1,151 respondents is representative of the population 18 years and older. FISCT

interviews were conducted via CATI from the Survey 

Research Center at the University of Maryland. The information on primary activities collected in the FISCT

diaries is similar to that collected in the ATUS, although 

the FISCT reference day runs from midnight to midnight, 

rather than from 4 a.m. to 4 a.m. The difference in reference period should not matter much, except that the 

FISCT captures fewer episodes of sleep. For example, an 

individual who always goes to sleep after midnight, but 

before 4 a.m., will have one sleep episode per day in the 

FISCT and two in the ATUS.

To make ATUS data comparable with FISCT data, 

respondents under the age of 18 years were excluded, 

reducing the ATUS sample to 12,200 respondents. Because the ATUS excludes individuals reporting fewer 

than five episodes on the reference day, the three FISCT

respondents reporting fewer than five episodes were excluded from the analyses, resulting in a sample of 1,148 

respondents. All of the analyses use sample weights, 

except where explicitly stated otherwise. Weighting is 

necessary for comparability, because it corrects for stratification of the samples and ensures correct day-of-week 

representation.6

The FISCT collects information on secondary activities 

through the question “What else were you doing?” FISCT 

data also include a small number of tertiary activities that 

respondents reported, in addition to both primary and 

secondary activities, during a given episode. Tertiary activities are present in a weighted 3.1 percent of all FISCT
Time-Use Surveys

20 Monthly Labor Review • August 2010

episodes. ATUS data include some tertiary activities, but 

they were not coded; therefore, tertiary activities in both 

the FISCT and the ATUS are ignored here. The FISCT does 

not collect starting and stopping times separately for secondary activities, so durations are assumed to be the same 

as for the corresponding primary activities.

Activity codes in the ATUS are more detailed than 

those in the FISCT (462 categories compared with 93). 

To make the codes more comparable, the activity codes 

in both datasets were collapsed into 13 major categories. 

Although some of these categories are not standard (due 

to differences across the surveys), they are consistently defined across the two surveys. (See the appendix.) 

Before proceeding, it is worth noting some selection 

issues that could complicate the analysis. An individual’s 

propensity to report secondary activities may be correlated with how busy he or she is, although it is not clear 

which way the correlation goes. On the one hand, busy 

people’s time may be more valuable, making it more costly for them to report secondary activities. On the other 

hand, they may want to tell the interviewer how busy 

their lives are. The same factors come into play when 

they decide whether or not to participate in the survey. 

There is no research on how being busy might affect the 

reporting of secondary activities, but research by Katharine Abraham, Aaron Maitland, and Suzanne Bianchi 

finds that busy people are no less likely to participate in 

the ATUS.

7

 What does seem to matter is the degree to 

which individuals have strong ties to their communities. 

Those with weaker ties are less likely to participate, but 

that is due mainly to the lower probability of contacting 

these individuals. On the basis of a propensity-score reweighting of the data, Abraham, Maitland, and Bianchi 

conclude that, despite the low response rate in the ATUS, 

there is no evidence of systematic bias. Thus, the analysis 

will proceed as though there is little or no systematic 

bias in the propensity of busy people to report secondary 

activities.

Respondents also may differ with respect to the level 

of detail they provide. Again, the effects of the differences 

are ambiguous. Conscientious respondents provide a lot 

of detail, so one would expect them to report both more 

primary and more secondary activities than less conscientious respondents. However, they also may make a greater 

effort to correctly report short-duration sequential activities as primary, rather than reporting them as secondary. 

The latter type of respondent would tend to reduce the 

number of secondary activities reported, but increase the 

number of primary activities.

In addition to the issues discussed thus far, the sample 

selection process for the two surveys likely generated some 

differences in the samples obtained. The ATUS sample is 

drawn from households that recently completed their 

participation in the CPS, whereas FISCT respondents were 

selected by random-digit dialing. It is not clear how these 

differences would affect the decisions to participate in the 

surveys.8 Differences in the assignment of respondents to 

days of the week also could affect comparisons. In contrast 

to the ATUS contact strategy of preassigning each selected 

individual to a specific day of the week and calling on the 

same day of the week on subsequent contact attempts, 

the FISCT calls on consecutive days until the individual 

is reached. If people are less likely to respond to a survey 

on busy days (or on days that they are mostly away from 

home), then the FISCT will oversample busy days (or days 

when the person is away from home).9

Weighting should correct for biases that are related 

to the (observable) characteristics used to generate the 

weights. However, nothing can be done if selection propensities are related to unobservable characteristics.

Table 1 shows weighted means of the demographic 

variables in the ATUS and FISCT samples. To test for differences between the two surveys, the samples were combined and separate ordinary least squares regressions were 

run for men and women. (See tables A-1 through A-4 

in the appendix for the results.) In general, the samples 

are similar for men, except that the ATUS respondents are 

Means of selected characteristics of the 2006 

American Time Use Survey (ATUS) and 1998–99 

Family Interaction, Social Capital, and Trends in 

Time Use (FISCT) survey samples

[In percent, except for age and sample size] 

 Characteristic

Men Women

ATUS FISCT ATUS FISCT

Employed ...................... 74.3 75.0 160.2 65.4

Age, years...................... 45.0 45.0 46.6 45.3

Earned at least a 

bachelor’s degree ...

27.4 26.0 226.5 19.6

Married........................... 64.5 61.5 58.9 60.6

Any children................. 30.4 31.8 241.3 58.9

Children younger 

than 6 years............... 16.3 13.7 18.4 21.6

African American........ 11.4 10.0 14.5 18.4

Hispanic ......................... 213.6 7.6 212.0 5.2

Sample size................... 5,147 494 7,053 657

1 p < .05. 2 p < .01. 

NOTE: T-tests are of coefficients from linear regressions with a 

characteristic as the dependent variable and an ATUS dummy for the 

subsamples of men and women.

 Table 1. 
Monthly Labor Review • August 2010 21

more likely to be Hispanic. Compared with women in the 

FISCT, women in the ATUS are more likely to be Hispanic, 

to be more highly educated, not to be employed, and not 

to have children in the household. Tests for whether the 

weighted samples included more diaries from any particular weekday were uniformly insignificant, except that men 

in the FISCT sample were less likely to have completed a 

diary on a Tuesday.10

Analysis

The first step in analyzing secondary-activity data is to 

document differences between the ATUS and the FISCT

in reporting such activities, using the number of episodes 

as a measure of quality. The implicit assumption, which is 

fairly standard among time-use researchers, is that a larger 

number of episodes implies more detail and thus higher 

quality. As before, ordinary least squares regressions were 

run on the combined ATUS-FISCT dataset, with the dependent variable being the number of primary-activity 

episodes. The main variable of interest is the indicator 

variable for whether the observation is from the ATUS. 

To control for differences between the two datasets, the 

regressions included variables for Hispanic ethnicity, education, employment status, and the presence of children 

in the household.11 An indicator variable for whether the 

diary day was a Tuesday was included, because Tuesdays 

were underrepresented in the male sample for the FISCT. 

To account for the greater number of sleep episodes reported in the ATUS (because of the difference in reference 

periods), a variable for the number of sleep episodes as 

a primary activity was included. Finally, the regressions 

include a measure of interviewer tenure, because ATUS interviewers were more experienced than FISCT interviewers and one would expect more experienced interviewers to 

collect more detailed responses.

In the ATUS data, interviewer identifiers made it possible to construct interviewer tenure from the 2003–06 

call-history files. Tenure is equal to the number of months 

between the interviewer’s initial ATUS interview (sometimes dating to January of 2003) and the current month in 

2006. This measure slightly underestimates actual experience, because some ATUS interviewers were collecting test 

data for several months before “live” data collection started in January of 2003. For the FISCT, which does not have 

interviewer identifiers, interviewer tenure was constructed 

under the assumption that there was no interviewer turnover; thus, tenure is simply the number of months from 

the beginning of the survey (March 1998) to the current 

survey month. This measure tends to overestimate interviewer tenure to the extent that there was turnover among 

FISCT interview staff. The mean of the tenure variable is 

28.7 months for the ATUS and 5.5 months for the FISCT.

12

Tenure is specified as a quadratic in order to account for 

possible diminishing returns.

ATUS respondents reported an average of 20.14 primary-activity episodes, while FISCT respondents averaged 18.43 episodes. As expected, secondary activities 

in the ATUS are relatively rare, averaging 0.45 episode 

per respondent. In contrast, FISCT respondents reported an average of 8.74 secondary-activity episodes per 

respondent. Using the simple regression analysis just 

described results in differences in both the number of 

primary-activity episodes and the number of secondary-activity episodes that are significant at the 1-percent level. Adding the quadratic control for interviewer 

experience decreases the ATUS coefficient from 1.7 to 

0.97, suggesting that much of the difference between 

the two surveys is in fact due to the greater experience 

levels of ATUS interviewers.13 Adding controls for sleep 

episodes, Hispanic origin, education, employment, children, and a Tuesday diary day drops the coefficient to a 

still-significant 0.80. For the count of secondary activities, the ATUS regression coefficient varies from –8.29 

with no controls to –8.50 with all of the controls and is 

uniformly significant.

Table 2 shows the frequency and duration of secondary 

activities for the 13 broad categories of time use. The first 

two columns show the number of episodes of each activity, expressed as a percentage of all episodes. Television, 

leisure and sports, and eating and drinking are the most 

common secondary activities in both datasets, although 

ATUS respondents report secondary activities significantly 

less often than FISCT respondents in 10 of the 13 activities. 

In the ATUS, about one-half of 1 percent of all episodes 

have leisure and sports, television, or eating and drinking 

as a secondary activity, about one-quarter of 1 percent have 

household work as a secondary activity, and the remaining secondary activities each cover less than 0.1 percent 

of total episodes. In contrast, in the FISCT data, television 

was a secondary activity in 4.6 percent of all episodes and 

leisure and sports in 35 percent of all episodes, with figures 

for other categories falling to 2.1 percent for eating and 

drinking, 1.2 percent for household work, and less than 

1.0 percent for each of the remaining categories. These differences clearly show that the secondary-activity reports 

from the two datasets are not comparable and that the two 

methods of collecting secondary activities yield very different results.

The last two columns of table 2 show average total time 
Time-Use Surveys

22 Monthly Labor Review • August 2010

spent in the 13 secondary activities. Summing over the 

columns reveals that ATUS respondents spent 36.8 minutes in secondary activities per day, compared with 541.4 

minutes for FISCT respondents, a difference of more than 

8 hours per day. With the exception of adult care, which 

accounts for less than 20 seconds per day in both surveys, 

FISCT respondents spend more time in each secondary activity, with the differences being statistically significant in 

8 of the 13 activities. The largest absolute difference is for 

leisure and sports, which accounts for more than 6 hours 

per day of secondary activities in the FISCT, but less than 

10 minutes in the ATUS. There are also large differences 

for eating and drinking (41 minutes) and for television 

(33 minutes). A closer look reveals that 287.5 minutes of 

the secondary leisure and sports time in the FISCT, or just 

under 5 hours per day, is accounted for by conversation.

The large amount of time spent in conversation reported 

by FISCT respondents seems unlikely and suggests some 

type of misreporting. It is possible that some of this time 

represents short episodes of conversation interspersed 

among episodes of other activities, and there is some support for this explanation in the data: FISCT respondents 

report an average of 21.4 minutes of conversation as a 

primary activity, whereas ATUS respondents report 40.1 

minutes. This difference suggests that the requested approach led respondents to report short conversations as 

secondary, rather than primary, activities in the FISCT. But 

even if the difference is attributable entirely to a shifting 

of conversation from primary to secondary activities, it 

accounts for only a small fraction of the large amount of 

time spent in conversation as a secondary activity in the 

FISCT.

Even if conversation recorded as a secondary activity is 

truly simultaneous, the duration is almost certainly misreported in both surveys because neither instrument allows 

the respondent to report a separate duration for secondary 

activities. For example, a respondent whose 1-hour spell 

of household work is interrupted by a 5-minute conversation would correctly report the series of activities as a 

25-minute episode of household work, a 5-minute conversation, and a 30-minute episode of household work. 

But if the conversation is reported as a secondary activity, 

the diary would show a 1-hour episode of household work 

and a 1-hour episode of conversation as a secondary activity. Thus, the shifting of the conversation from a primary 

activity to a secondary activity, along with the common 

duration of primary and secondary activities, could lead to 

a large overstatement of time spent in conversation and a 

small overstatement of household work.

The 2006 ATUS Eating and Health Module sponsored 

by the Economic Research Service of the U.S. Department 

of Agriculture sheds some light on the possible distortion. 

The module asks about eating and drinking as secondary 

activities in a fashion similar to the way the ATUS asks 

about secondary childcare, but it also asks respondents to 

report the duration of each secondary episode of eating 

and drinking. Respondents reported an average of 15.7 

minutes of secondary eating and 41.6 minutes of secondary drinking. If, however, the duration of the primary activity is used instead, then secondary eating time increases 

to 111.7 minutes per day and secondary drinking time 

increases to 89.8 minutes. So, for these secondary activities, using the duration of the primary activity overstates 

time by a factor of 2 to 7.

For primary activities, the mean number of episodes 

for each of the 13 primary-activity categories is shown 

in the first two columns of table 3. As expected, given 

the difference in the reference periods for the two surveys, ATUS respondents report more episodes of sleep 

than do FISCT respondents. The reason for this small, 

Distribution of secondary-activity episodes and 

of total time spent in secondary activities, 2006 

American Time Use Survey (ATUS) and 1998–99 

Family Interaction, Social Capital, and Trends in 

Time Use (FISCT) survey

Secondary activity

Episodes with 

secondary 

activities, as a 

percentage of all 

episodes

Minutes per day

ATUS FISCT ATUS FISCT

 Total...............................

Sleep .......................................

2.0731

.0140

44.5004

.0884

36.81

.391

541.64

2.75

Grooming and not 

elsewhere classified....... 1

.0119 .4013 11.84 5.43

Travel....................................... 2.0170 .0521 .057 .720

Work........................................ 1.0528 .3077 1.476 10.6

Childcare................................ 1.0756 .1471 11.07 18.2

Adult care.............................. .0178 .0195 .214 .198

Education .............................. 2.0057 .0715 .164 1.48

Leisure and sports.............. 1.571 35.1 19.76 387.8

Organizational activities.... .0233 .0678 .277 .750

Purchasing goods and 

services............................... 1

.0250 .275 1.297 4.86

Television............................... 1.586 4.61 110.1 43.5

Household work ................ 1.228 1.22 14.89 16.1

Eating and drinking........... 1.445 2.14 17.27 49.0

1 p < .01. 2 p < .05.

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed on a Tuesday, and an interviewer experience quadratic.

 Table 2. 
Monthly Labor Review • August 2010 23

but statistically significant, difference is that relatively 

few sleep episodes start between midnight and 4 a.m.: 

only 11.46 percent in the 2006 ATUS and 10.75 percent 

in the FISCT. About 90 percent of FISCT respondents 

reported at least two episodes of sleep. ATUS respondents 

also reported more episodes than did FISCT respondents 

in each of the remaining activity categories (except for 

grooming), with the difference being statistically significant for work, childcare, adult care, television, and eating 

and drinking, even after controlling for interviewer experience and differences in demographic characteristics 

between the two surveys.

The last two columns of table 3 show the average total time spent in the various primary-activity categories. 

Compared with FISCT respondents, ATUS respondents 

spent more time in sleep and watching television, and less 

time in leisure and sports and traveling. These differences 

are large and statistically significant. For sleep, the difference is slightly more than one half hour per day, while for 

television, the difference is just under one half hour. For 

personal care activities (sleeping and grooming), where 

there is no discernible difference in the weighted means, 

the ATUS coefficient in the regression with controls is a 

statistically significant 9.6 minutes, suggesting that ATUS

respondents report spending more time on personal care.

If there was no actual change in behavior between 

1999 and 2006, the television result could be explained 

by a change in how television time is reported. For example, television time that would have been reported as 

a secondary activity. in the FISCT might be reported as a 

primary activity in the ATUS Other differences are more 

difficult to explain, particularly the apparent decline in 

leisure and sports time. If there was an actual change in 

behavior between the times the two surveys were conducted, then, to the extent that individuals switched from 

television to Internet usage over the period (as seems 

likely), measured time spent on leisure and sports (including Internet usage) should have been greater in the 

ATUS than the FISCT. Instead, the opposite appears to 

have occurred.

If changing time-use patterns are part of the difference 

between the two surveys, then one also would expect to see 

changes in the ATUS between 2003 and 2006. However, 

there was virtually no change in the time spent in any activity during that period.14 Thus, any changes in behavior 

would have to have occurred between 1999 and 2003. It is 

far more likely that there are other differences between the 

two surveys that this study could not account for.15

One difference worth noting is how respondents were 

contacted. As mentioned earlier, the FISCT contact strategy tends to oversample busy days and days when the 

respondent spends a lot of time away from home. This 

is consistent with the findings here that FISCT respondents report spending more time working, traveling, and 

engaged in leisure and sports, and less time watching 

television and sleeping. The difference in time spent doing housework is inconsistent with the contact-strategy 

explanation, but the difference is relatively small. Unfortunately, there is no way to quantify this effect.

It is reasonable to suppose that multitasking is related 

to respondents’ characteristics. For example, people who 

are employed, work longer hours, have children (especially 

younger children), or are women may be busier, so one 

would expect them to report secondary activities more 

often. However, busy people may be less likely to take the 

time to report secondary activities.

Table 4 compares the characteristics of respondents 

who did, and respondents who did not, report secondary 

activities in the two surveys. The expected pattern emerges 

in the FISCT data: employed respondents, those with children, and women are significantly more likely to report 

secondary activities. In the ATUS, however, the results are 

Distribution of primary-activity episodes and 

of total time spent in primary activities, 2006 

American Time Use Survey (ATUS) and 1998–99 

Family Interaction, Social Capital, and Trends in 

Time Use (FISCT) survey 

Primary activity

Episodes per day Minutes per day

ATUS FISCT ATUS FISCT

 Total...........................

Sleep ...................................

20.14

1

2.21

18.43

1.96

1,440

1

514.7

1,440

484.0

Grooming and not 

elsewhere classified.... 1

1.65 2.05 157.1 57.3

Travel................................... 4.16 4.11 175.1 92.6

Work.................................... 11.24 1.11 217.3 226.0

Childcare............................ 2.979 .796 230.2 34.6

Adult care.......................... 1.230 .071 7.05 3.27

Education .......................... .138 .095 14.4 11.7

Leisure and sports.......... 2.36 2.05 1143.9 165.5

Organizational 

activities......................... .207 .158 15.0 15.3

Purchasing goods and 

services........................... .837 .701 31.7 31.9

Television........................... 11.49 1.18 1156.2 126.8

Household work.............. 2.57 2.31 2109.5 117.9

Eating and drinking....... 12.07 1.84 168.0 73.1

1 p < .01. 2 p < .05.

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed on a Tuesday, and an interviewer experience quadratic. 

 Table 3. 
Time-Use Surveys

24 Monthly Labor Review • August 2010

the opposite: although women are more likely to report 

secondary activities, the employed, those who work longer 

hours, and respondents with children are significantly less 

likely to do so. Respondents who are younger, less educated, African American, or Hispanic also are less likely to 

report secondary activities. Save the result for Hispanics, 

these patterns do not appear in the FISCT, and they are 

consistent with the hypothesis that the quality of secondary-activity reports is higher when they are requested than 

when they are volunteered without a prompt.

To examine the relationship between the numbers of 

primary and secondary activities reported, linear regressions of the count of primary-activity episodes on the 

count of secondary-activity episodes were run separately 

on the FISCT and ATUS samples. The coefficient in the 

FISCT sample was .88 (significant at the 1-percent level), 

while the coefficient in the ATUS sample was 2.59 (significant at 1 percent as well). The positive coefficients 

suggest that respondents who provide more detail by 

reporting secondary activities also report more primary 

activities. 

The final analysis moves down to the episode level to 

analyze which primary and secondary activities commonly appear as a combination. In the unweighted ATUS data, 

5,829 out of 249,599 total episodes include secondary activities (2.3 percent of all episodes—close to the weighted 

percentage shown in table 2). The most frequently reported secondary activities are leisure and sports (1,556 

episodes), television (1,513 episodes), and eating and 

drinking (1,143). Household work accounts for only 677 

secondary-activity episodes. The most frequent combinations of primary and secondary activities (in that order) 

are leisure and sports with eating and drinking (629 episodes), followed by eating and drinking with leisure and 

sports (594 episodes), leisure and sports with television 

(534 episodes), and eating and drinking with television 

(515 episodes).

These patterns suggest that eating meals, watching 

television, and other leisure activities are often performed 

together. Nonetheless, the estimated (weighted) amounts 

of time involved are not great on a daily basis. The combination of leisure and sports as a primary activity with 

eating and drinking as secondary accounts for 4.0 minutes 

per day, with the reverse accounting for 2.9 minutes. The 

combination of leisure and sports with television covers 

4.7 minutes, and that of eating and drinking with television accounts for 1.8 minutes.

In the FISCT data, 10,458 out of 21,766 episodes (48 

percent) included secondary activities, and 8,090 of the 

21,766 episodes (37 percent of all episodes) were episodes of leisure and sports. The main primary activities 

associated with the episodes of leisure and sports were 

travel (3,357 episodes), eating and drinking (1,130), 

other leisure and sports (811), housework (731), work 

(568), and television (421). All of the remaining primary-secondary activity pairs account for fewer than 400 

episodes each.

If the ATUS approach to collecting secondary activities results in respondents doing a better job of reporting 

sequential activities as primary, then one would expect 

to see more short-duration episodes in that survey and 

one also would expect secondary activities to be reported 

less frequently during these short-duration activities. A 

comparison of short-duration activities in the two surveys 

provides some support for this hypothesis. Although the 

fraction of episodes that last 15 or fewer minutes is similar in the two surveys—34 percent in the ATUS and 32 

Characteristics of respondents reporting 

secondary activities, 2006 American Time Use 

Survey (ATUS) and 1998–99 Family Interaction, 

Social Capital, and Trends in Time Use (FISCT) 

survey

[In percent, except for usual work hours, age, and sample size]

Characteristic

ATUS FISCT

No 

secondary 

activity 

reported

Secondary 

activity 

reported

No 

secondary 

activity 

reported

Secondary 

activity 

reported

Employed ............. 169.0 62.0 68.0 270.6

Usual work 

hours.................. 1

27.3 23.3 34.8 30.6

Any children........ 133.8 29.7 22.4 237.7

Children younger 

than 6 years...... 1

18.5 14.9 10.8 18.2

Woman.................. 49.9 156.1 25.9 154.0

Age, years............. 44.6 148.7 44.7 45.2

Earned at least 

a bachelor’s 

degree................ 25.5 1

30.4 23.6 22.8

Married.................. 61.6 62.1 69.7 60.7

African 

American........... 2

13.0 10.9 11.0 12.5

Hispanic ................ 115.2 7.2 18.2 5.6

Sample size.......... 8,409 3,791 47 1,101

 (weighted

 percent)............. (70.2) (29.8) (5.2) (94.8)

1 p < .01. 2 p = .05. 

NOTE: Significance is obtained from t-tests for the coefficient on 

a dummy variable for respondents who report secondary activities. 

Separate regressions were carried out on the ATUS and FISCT data, with 

both regressions including controls for Hispanic ethnicity, education, 

employment, number of children, diaries completed on a Tuesday, and 

an interviewer experience quadratic. 

 Table 4. 
Monthly Labor Review • August 2010 25

percent in the FISCT—secondary activities are reported 

relatively less frequently in the ATUS than in the FISCT. In 

the ATUS, short-duration episodes are less likely to have 

a secondary activity than is the full sample (1 percent and 

2.3 percent, respectively), whereas secondary activities are 

equally likely in short- and long-duration episodes in the 

FISCT (49 percent compared with 48 percent). Moreover, 

when secondary activities are reported, the types of activities differ across the two subsamples: ATUS respondents 

report participating in leisure and sports (27 percent), eating and drinking (19 percent), and television (18 percent), 

whereas FISCT respondents report participating mainly in 

leisure and sports (86 percent), with listening to the radio 

and engaging in conversation accounting for 52 percent 

and 46 percent, respectively, of these episodes.

With regard to household work, the unweighted FISCT

data yield 297 episodes of household work reported as a 

secondary activity. Many of these episodes (134) involved 

household work as both the primary and the secondary 

activity. Most other episodes of household work as a secondary activity were associated with the primary activity of watching television (43 episodes) or of leisure and 

sports (38 episodes). ATUS respondents reported an average of 5 minutes of household work as a secondary activity, whereas FISCT respondents reported 16 minutes. The 

16.1 minutes they spent performing household work as a 

secondary activity was done mainly in conjunction with 

household work (7.7 minutes), television (2.5 minutes), 

leisure and sports (2.4 minutes), or childcare (1.8 minutes) 

as primary activities. FISCT respondents also reported that 

they participated in a leisure activity during about 25 percent of the time they spent performing household work as 

a primary activity (30.4 minutes out of 117.9 minutes, on 

a weighted basis). 

These results suggest that the ATUS underestimates the 

time spent on household work because it misses household work done as a secondary activity. The amount of 

time missed is less than 10 percent of the time spent in 

household work as a primary activity, but this omission may 

be important for researchers who are interested in valuing 

household production. At first blush, these results suggest 

that the public ATUS data may miss as much as 16 minutes 

of household work as a secondary activity. But almost half 

(7.7 minutes) of the secondary household work reported in 

the FISCT has already been counted as household production, because the primary activity was also household work. 

Moreover, it would be reasonable to discount the value of 

the remaining secondary household worktime—especially 

when the primary activity was leisure.16 If one follows the 

usual, though admittedly ad hoc, approach of dividing the 

duration of the episode equally among the reported activities, the missed secondary household worktime amounts 

to 4 minutes per day. Of course, if household work that is 

done as a secondary activity is discounted in this way, then 

it would make sense also to discount household work done 

as a primary activity when the secondary activity is something other than household work.

Another component of household production is secondary childcare. One study compared the two approaches to 

collecting data on this component and showed that the 

ATUS “in your care” questions identify far more childcare 

time—over 5 hours per day more—than do traditional 

secondary-activity reports.17 The study identified two possible reasons for the difference. First, the ATUS questions 

specifically ask about childcare, whereas the standard approach to collecting secondary activities is to ask, “What 

else were you doing?” Second, the concept of childcare differs between the two approaches. The ATUS question specifically asks about time the respondent spent with children 

in his or her care (passive childcare), whereas the standard 

approach is more activity oriented. It is likely that respondents do not view passive childcare as an activity per se.

For parents of children under the age of 18 years, secondary childcare time in the FISCT averages three-quarters of an hour per day. The ATUS measure, which includes 

only care of children under 13 years, averages 4.64 hours 

per day. Even if the ATUS average is recomputed to include 

13- to 17-year-olds (as the FISCT measure does, assuming 

zero minutes of “in your care” time for this group), it is still 

quite a bit larger than the FISCT estimate of 3.35 hours 

per day for the same age group of 13- to 17-year-olds. 

The FISCT estimate of secondary childcare is therefore 

2.63 hours per day less than the ATUS estimate for parents 

or, assuming that one-third of all adults are parents, 53 

minutes less per day for an average adult. If the desired 

concept of secondary childcare includes passive childcare, 

then the FISCT substantially underestimates the amount 

of time spent in secondary childcare.

Discussion

The evidence presented here clearly shows that secondary-activity reports from the ATUS are not comparable to 

secondary-activity reports from the FISCT or from other 

time-use surveys that explicitly request data on secondary activities. Further, by every available indicator, the 

quality of secondary-activity reports from the ATUS is 

not as good as that for the FISCT. Episodes of secondary 

activities in the ATUS are reported an average of less than 

one-twentieth as often as in the FISCT and account for a 
Time-Use Surveys

26 Monthly Labor Review • August 2010

little more than a half-hour per day, compared with over 

9 hours in the latter survey. Clearly, respondents provide 

substantially more information about secondary activities 

when asked to do so than when the information must be 

volunteered. Further, respondents who report secondary 

activities when asked are also those who may lead the 

busiest lives, while respondents who volunteer such information seem to be those who are willing to provide more 

detail. All of these differences provide cause for concern 

regarding the validity, accuracy, veracity, and general usefulness of secondary-activity reports from the ATUS. That 

said, the FISCT data likely overstate the amount of time 

spent in secondary activities, because FISCT respondents 

report some short-duration activities as secondary and the 

FISCT does not collect durations separately for secondary 

activities.

Less clear is the extent to which the collection of secondary activities affects the reporting of primary activities, 

although the available evidence points toward better reporting of primary activities with the ATUS approach, which 

includes asking respondents to break apart simultaneousactivity reports if possible. Kitterod’s research suggests that, 

even without an ATUS-type prompt, omitting the collection 

of secondary-activity reports might improve the quality of 

primary-activity reports because respondents may then 

be more likely to correctly report short-duration sequential activities as primary, rather than secondary, activities.18 

Consistent with her research, the results presented here 

show that ATUS respondents report more primary activities 

than do FISCT respondents, even after controlling for interviewer experience and sampling differences. Thus, activities 

that account for a large fraction of secondary-activity time 

in the FISCT—such as conversation, television, and eating 

and drinking—may really be sequential primary activities. 

Moreover, the analysis presented here indicates that ATUS

respondents spend a statistically significant greater amount 

of time in conversation and television as primary activities 

than do FISCT respondents (about 20 and 30 minutes more 

per day, respectively). FISCT respondents report more time 

eating as a primary activity, but the difference, though also 

statistically significant, is only 5 minutes per day. The differences for conversation and television are consistent with 

respondents shifting secondary activities into primaryactivity reports when no secondary-activity option is explicitly provided.

There are two main implications of this study’s findings. First, regardless of whether or not data on secondary 

activities are systematically collected, it is important to ask 

respondents to break apart activities; such requests make 

respondents more likely to report short-duration sequential activities as primary rather than secondary. Second, if 

secondary activities are requested, it is important to collect information on their duration. Results from the ATUS 

“Eating and Health” module clearly show that there is a 

potential to grossly overestimate time spent in secondary 

activities, unless data on the duration of the secondary activity are collected separately.

Whether or not data on secondary activities should be 

systematically collected depends on the goals of the survey. If one of the goals is to provide information for the 

construction of satellite accounts to the National Income 

and Product Accounts, then one must consider the effect 

on measured time spent in household production activities.19 Compared with FISCT respondents, ATUS respondents report 8 fewer minutes per day of household work as 

a primary activity. This finding echoes Kitterod’s that respondents reported less household work as a primary activity when they could not report secondary activities. The 

FISCT uncovers more household production as a secondary 

activity, but half of this time already was counted because 

the primary activity also was household production.

The systematic collection of secondary activities should 

not be viewed as a substitute for the “in your care” childcare questions in the ATUS. Respondents do not appear 

to view passive childcare as an activity per se and tend 

not to report that type of care unless specifically asked. 

For the purpose of generating satellite accounts that incorporate the value of household production time, the 

secondary-childcare information that is collected in the 

ATUS is more relevant than traditional secondary-activity 

reports because passive childcare represents unpaid work 

that traditional activity-based measures miss.20

Finally, even if it were possible to collect data on secondary activities perfectly, it is not clear how to analyze such 

data. One article notes that, even when they are available, 

secondary-activity data are seldom analyzed.21 Currently, 

there is no consensus among time-use researchers on how 

to incorporate secondary activities into their analyses. In 

some instances, it might be reasonable to double count the 

time spent in simultaneous activities. For example, a parent 

who reads to her child while riding the subway is truly engaged in two activities, and neither activity is compromised 

by the other. But in most cases it makes sense to limit the 

day to 24 hours.22 To see why, consider a respondent who 

reports that she was ironing clothes while watching television. Presumably, this respondent would be less productive 

than a similar respondent who was not watching television 

while ironing. Thus, it would make sense to divide the time 

spent doing the simultaneous activities into time spent 

watching television and time spent ironing. One rela-
Monthly Labor Review • August 2010 27

tively crude strategy for dealing with secondary activities 

is to split the duration of an episode evenly between the 

primary and the secondary activities.23 Therefore, before 

considering the collection of secondary-activity data in the 

ATUS, researchers will have to give serious thought to how 

the data will be analyzed.

Notes

ACKNOWLEDGMENT: Thanks go to the National Science Foundation, American Statistical Association, and Bureau of Labor Statistics 

for providing a fellowship under which Robert Drago performed much 

of the empirical analysis required for this article. Thanks also to Vanessa 

Wight of the University of Maryland for providing a crosswalk between 

the two datasets that was used to help develop the harmonized coding 

scheme. Dori Allard, Jill Lacey, and Anne Polivka gave helpful comments.

1 F. J. Fowler, Survey Research Methods, Applied Social Research 

Methods series, vol. 1 (Newbury Park, CA, Sage Publications, 1993). 

2 American Time Use Survey Jefferson Telephone Center Interviewer 

Manual, Sept. 13, 2007, version.

3 Ragne H. Kitterod, “Does the recording of parallel activities in 

time use diaries affect the way people report their main activities?” Social Indicators Research, November 2001, pp. 145–78. 

4 Ibid., p. 174.

5 See John P. Robinson, Suzanne M. Bianchi, and Stanley Presser, 

Family Interaction, Social Capital, and Trends in Time Use (FISCT), 

1998–1999 (College Park, MD, University of Maryland Survey Research Center [producer], 1999; and Ann Arbor, MI, Inter-university 

Consortium for Political and Social Research [distributor], 2001).

6 Relevant weights are designated as TUFINLWGT in the ATUS 

and DAYWT in the FISCT. The ATUS weight corrects for seasonality; 

the FISCT weight does not. A check revealed that only 20.0 percent of 

the weighted FISCT observations were from December, January, and 

February, whereas 29.2 percent were from September through November. However, summer is the season that is most likely to be different from the others, and 24.7 percent of FISCT observations are from 

June, July, or August. The 24.7-percent figure is close to the 25-percent 

figure that a uniform seasonal distribution of survey administration 

would yield.

7 Katharine G. Abraham, Aaron Maitland, and Suzanne M. Bianchi, “Nonresponse in the American Time Use Survey,” Public Opinion 

Quarterly, vol. 70, no. 5 (special issue), 2006, pp. 676–703.

8 One would expect individuals who were selected for the ATUS

to be more willing to respond, compared with those selected for the 

FISCT, because ATUS respondents participated in the CPS. But many 

of those who were selected to participate in the ATUS refused because 

of survey fatigue. One study conducted a response analysis survey of 

ATUS respondents and nonrespondents, and found that about onethird of nonrespondents did not respond to the ATUS because they 

felt that they had done enough by participating in the CPS. (See 

Grace E. O’Neill and Jessica R. Sincavage, Response Analysis Survey: A 

Qualitative Look at Response and Nonresponse in the American Time Use 

Survey (Bureau of Labor Statistics, 2004). Household members who 

were not the CPS respondent may actually have a lower propensity 

to respond to surveys than does the population, on average, because 

people with a higher propensity to participate in surveys are more 

likely to be the CPS respondent. Many of these people were in the CPS

only because someone else in the household was willing to provide a 

proxy response.

9 Jay C. Stewart, “Assessing the Bias Associated with Alternative 

Contact Strategies in Telephone Time-Use Surveys,” Survey Methodology, December 2002, pp. 157–68. 

10 A weighted 11.1 percent of male FISCT, and 15.6 percent of 

male ATUS, respondents were surveyed with Tuesday as the reference 

day. A uniform distribution of days would yield a figure of 14.3 percent 

for male FISCT participants, which is closer to the ATUS figure.

11 Note that a regression with gender as the dependent variable and 

the ATUS dummy as an independent variable did not yield a significant 

coefficient, so gender is not controlled for in what follows. 

12 The FISCT measure is less precise than that of the ATUS, because 

the former fails to account for interviewer turnover. Nonetheless, an 

alternative approach that substitutes average tenure (about 5 months 

in the FISCT) for all FISCT interviewers yielded a marginally lower tstatistic when the number of daily diary episodes was regressed against 

a dummy for the ATUS and the experience variable. 

13 The experience quadratic achieves a maximum at 38.6 months, 

or 3.2 years, of experience in the regression with no other controls, and 

31.7 months, or 2.6 years, in the regression with controls, suggesting 

that experience effects indeed taper off.

14 See “American Time Use Survey—2006 Results,” news release 

(Bureau of Labor Statistics, June 28, 2007), table 12, “Average hours 

per day spent in primary activities for the civilian population, 2003–06 

quarterly and annual averages,” on the Internet at www.bls.gov/news.

release/archives/atus_06032008.pdf (visited Aug. 30, 2010).

15 As a further comparison, the results shown in table 3 were replicated with the FISCT and the 2003 ATUS primary-activity data. The 

pattern of differences was virtually identical to that appearing in table 

3, although far more of the differences were found to be significant, 

presumably because the 2003 ATUS sample was almost twice as large 

as the 2006 sample. (See tables A–5 and A-6 in the appendix.) 

16 It may also be reasonable to discount the household work done 

as a primary activity when leisure is the secondary activity, because the 

individual is not devoting his or her full attention to household work. 

We do not do so, however: because ATUS respondents likely engaged 

in secondary activities even though those activities were not reported, 

it is not possible to do similar discounting in that survey.

17 Mary Dorinda Allard, Suzanne Bianchi, Jay Stewart, and Vanessa 

R. Wight, “Comparing childcare measures in the ATUS and earlier timediary studies,” Monthly Labor Review, May 2007, pp. 27–36. The authors found no difference between the two approaches in the amount 

of time spent in childcare as a primary activity.

18 Kitterod, “Does the recording of parallel activities?”

19 See, for example, J. Steven Landefeld and Stephanie H. McCulla, 

“Accounting for Nonmarket Household Production within a National 

Accounts Framework,” Review of Income and Wealth, September 2000, 

pp. 289–307.

20 Nancy Folbre and Jayoung Yoon, “The value of unpaid child care 

in the U.S. in 2003,” in Jean Kimmel (Ed.), How do we spend our time? 

Evidence from the American Time Use Survey (Kalamazoo, MI, W. E. 

Upjohn Institute, 2008), pp. 33–58. 

21 Michelle J. Budig and Nancy Folbre, “Activity, Proximity, or Responsibility? Measuring Parental Child Care Time,” in Nancy Folbre 

and Michael Bittman (Eds.), Family Time: The Social Organization of 
Time-Use Surveys

28 Monthly Labor Review • August 2010

Care (New York: Routledge, 2004), pp. 51–68. 

22 Suzanne M. Bianchi, John P. Robinson, and Melissa A. Milkie, 

Changing Rhythms of American Family Life (New York, Russell Sage 

Foundation, 2006).

23 Robert Drago, Robert Caplan, David Costanza, Tanya Brubaker, 

Darnell Cloud, Naomi Harris, Russell Kashian, and T. Lynn Riggs, 

“New estimates of working time for elementary school teachers,” 

Monthly Labor Review, April 1999, pp. 31–40. 

APPENDIX: Harmonization and subsidiary results

Harmonization of activity codes

To compare data from the ATUS with data from the FISCT, the 

cross-coding scheme shown in exhibit A–1 was developed. 

Comparability was straightforward for some categories, such as 

sleep, television, and housework. Travel was coded as a subset of 

broad categories within the FISCT, but was placed in a single, 

broad ATUS category, allowing comparability. However, some 

conceptual divergence led to the creation of large categories. For 

example, caregiving in the ATUS is divided into care for household members and care for nonhousehold members, whereas it 

is split across care for children and care for adults in the FISCT. 

Because care for household and nonhousehold children could 

not be distinguished in the FISCT, the division between care for 

children and care for adults was used. Two ATUS codes for care 

(0399 and 0499) do not distinguish between care for children 

and care for adults, but these are empirically minor and mainly 

children were present, so both codes are categorized as care for 

children. Note also that the consumption of government services is classified under purchasing goods and services. A single 

ATUS code (1099) that could represent either the performance 

of civic duties or the receipt of government services is left unclassified; because only one 2006 ATUS episode of primary activities was covered by the code, that episode is excluded from 

the analysis. 

A major difference between the surveys is that computer and 

Internet usage have specific codes in the FISCT (56–58), whereas 

in the ATUS computer use is intermingled with various categories and is coded according to the purpose, such as household 

and personal email or computer use for leisure. Because these 

approaches are not formally comparable, all identifiable computer usage, along with writing and nontelephone messaging, 

was categorized as leisure and sports. This approach places some 

household tasks, such as bookkeeping or correspondence, in the 

leisure and sports category, but provides greater consistency in 

classifying these activities, given that the ATUS does not break 

out computer and Internet usage. In addition, it seemed possible that the approach misclassified some FISCT work activities, 

namely, those performed on a computer at work, as leisure and 

sports. As an empirical matter, the problem is minor, with only 

5 out of a total of 155 episodes of computer usage in the FISCT

occurring while the respondent was at the workplace (presumably because most computer usage for work was classified as 

work); by way of context, 1,255 episodes of work as a primary 

activity are reported in the FISCT. Further, Internet shopping is 

classified as shopping in the ATUS, but likely as Internet usage 

in the FISCT. However, Internet shopping was probably of minor importance in 1998 (for example, amazon.com did not turn 

a profit until 2002), so this misclassification should not pose a 

serious problem for the analyst. 

Finally, the relevant comparison category for ATUS category 

50 (not otherwise classified) in the FISCT is category 48, which 

includes time gaps and refusals, but also sex and family affection 

time, so all of these are placed into the category with personal 

care.

Cross-coding for the 2006 American Time 

Use Survey (ATUS) and 1998–99 Family Interaction, Social Capital, and Trends in Time Use 

(FISCT) survey

Code Label ATUS codes FISCT codes

1 Sleep ......................... 0101 45

2 Personal care and 

not otherwise 

classified............... 0102–0199, 50 40, 41,44,47,48

3 Travel......................... 18 03, 09, 29, 39, 49, 59, 

69, 79, 89, 99

4 Work.......................... 05 (except 050202) 01, 02, 05, 08

5 Childcare.................. 0301–0303, 

0401–0403

(except 030202 

and 040202), 0399, 

0499

20–27

6 Adult care................ 0304–5, 0404–5 42

7 Education ................ 06 50–55

8 Leisure and sports. 020903, 020904,13, 

16, 12 (except 

120303 and120304)

56–58, 70–78, 80–87, 

90, 92–98

9 Organizational 

activities............... 14, 15, 030202, 

040202, 1002, 

1004, 100303, 

100399

60–68

10 Purchasing goods 

and services........ 07, 08, 09, 1001, 

100301, 100302

30–38

11 Television................. 120303, 120304 91

12 Household work .. 02 (except 020903 

and 020904)

10–19

13 Eating and 

drinking................. 11, 050202 06, 43

 NOTE: ATUS codes 0399 and 0499 are for care not otherwise 

classified. For 2003–2006, 38 of 62 relevant episodes (61 percent) 

occurred with children present and hence are classified as childcare.

 Exhibit A-1. 
Monthly Labor Review • August 2010 29

Subsidiary results

Tables A–1 through A–6 show partial results of ordinary least 

squares regressions run for the tables presented in this article, 

except that table A-5 replicates table 3 after replacing the 2006 

with the 2003 ATUS data and table A-6 shows the regression 

results relevant to table A-5.

Partial ordinary least squares regression 

results for table 1, 2006 American Time Use 

Survey (ATUS) and 1998–99 Family Interaction, 

Social Capital, and Trends in Time Use (FISCT) 

survey 

Characteristic Men Women

Employed ........................................ –0.018

(.026)

[.0001]

–0.052

1

(.025)

[.001]

Age, years........................................ –.117

(1.039)

[.000]

1.33

(.964)

[.0004]

Earned at least a bachelor’s 

degree........................................... .010

(.023)

[.000]

.069

2

(.017)

[.002]

Married............................................. .030

(.027)

[.0003]

–.018

(.025)

[.0001]

Any children................................... –.019

(.026)

[.0001]

–.067

2

(.025)

[.002]

Children younger than 6 years. .024

(.018)

[.0003]

–.032

(.020)

[.0005]

African American.......................... .019

(.019)

[.0001]

–.012

(.020)

[.0001]

Hispanic ........................................... .064

2

(.017)

[.003]

.068

2

(.012)

[.004]

Minimum sample size................. 5,260 7,674

1 p < .05.

 2 p < .01.

NOTE: T-tests are of coefficients from linear regressions with a 

characteristic as the dependent variable and an ATUS dummy for the 

subsamples of men and women. Numbers shown in each cell are 

2006 ATUS coefficient, (standard error), [adjusted R2].

 Table A-1. 

Partial ordinary least squares regression results 

for table 2, 2006 American Time Use Survey 

(ATUS) and 1998–99 Family Interaction, Social 

Capital, and Trends in Time Use (FISCT) survey 

Secondary activity Episodes per day Minutes per day

Sleep .................................................. –.0006

(.0003)

[.004]

–1.89

(1.13)

[.003]

Grooming and not elsewhere 

classified........................................

–.003

1

(.0006)

[.009]

–3.26

1

(1.24)

[.005]

Travel.................................................. –.0005

2

(.0002)

[.005]

–.725

(.373)

[.004]

Work................................................... –.0028

1

(.0007)

[.017]

–10.16

1

(2.83)

[.017]

Childcare........................................... –.014

1

(.002)

[.080]

–17.61

1

(2.25)

[.062]

Adult care........................................ –.0002 –.184

(.0001) (.122)

[.002] [.001]

Education ......................................... –.0007 –1.27

2

(.0004) (.661)

[.007] [.005]

Leisure and sports......................... –.351

1

(.007)

[.696]

–386.1

1

(10.11)

[.576]

Organizational activities............. –.0004

(.0003)

[.002]

–.494

(.333)

[.002]

Purchasing goods and services. –.002

1

(.0005)

[.018]

–4.39

1

(1.39)

[.011]

Television.......................................... –.043

1

(.003)

[.137]

–36.08

1

(3.29)

[.041]

Household work ........................... –.010

1

(.001)

[.039]

–11.40

1

(1.77)

[.015]

Eating and drinking...................... –.017

1

(.002)

[.055]

–42.64

1

(4.33)

[.051]

1 p < .01. 2 p < .05.

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed on a Tuesday, and an interviewer experience quadratic. 

Numbers shown in each cell are 2006 ATUS coefficient, (standard error), 

[adjusted R2].

 Table A-2. 
Time-Use Surveys

30 Monthly Labor Review • August 2010

Partial ordinary least squares regression results 

for table 3, 2006 American Time Use Survey 

(ATUS) and 1998–99 Family Interaction, Social 

Capital, and Trends in Time Use (FISCT) survey 

Primary activity Episodes per day Minutes per day

Sleep ..................................... .179 31.9

1

(.029) 1(5.75)

[.040] [.042]

Grooming and not

 elsewhere classified.... –.251 9.62

1

(.062) 1(3.35)

[.014] [.012]

Travel..................................... .016 –15.8

(.119) 1

(3.88)

[.044] [.032]

Work...................................... .182 8.44

1

(.060) (9.43)

[.248] [.330]

Childcare.............................. .129 –5.57 2

(.063) 1(2.83)

[.263] [.200]

Adult care............................ .111 2.32

1

(.019) (1.26)

[.010] [.006]

Education ............................ .026 .476

(.031) (3.35)

[.007] [.007]

Leisure and sports............ .107 –27.8

(.083) 1(7.52)

[.059] [.073]

Organizational 

 activities............................ .045 .057

(.025) (2.09)

[.011] [.007]

Purchasing goods and services............................. .078 –2.45

(.050) (2.69)

[.012] [.007]

Television............................. .236 20.6 1

(.050) 1(6.69)

[.062] [.110]

Household work .............. .126 –13.8

(.100) 2(5.85)

[.070] [.068]

Eating and drinking......... .129 –8.05 1

(.043) 1(2.70)

[.015] [.017]

1 p < .01. 2 p < .05. 

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed 

on a Tuesday, and an interviewer experience quadratic. Numbers shown 

in each cell are 2006 ATUS coefficient, (standard error), [adjusted R3].

 Table A-3. Partial ordinary least squares regression results 

for table 4, any secondary activities, 2006 

American Time Use Survey (ATUS) and 1998–99 

Family Interaction, Social Capital, and Trends in 

Time Use (FISCT) survey

 Characteristic Secondary 

activity, ATUS

Secondary 

activity, FISCT

Employed ..................................... –0.067 0.006 1

(.012) (.020)

[.005] [.000]

Usual work hours....................... –.002 –.0004 1

(.000) (.0004)

[.007] [.002]

Any children................................ –.039 .026 1

(.011) (.016)

[.002] [.003]

Children younger than 6 

years........................................... –.053 .020 1

(.012) (.017)

[.001] [.001]

Woman.......................................... .052 .049 1

(.011) 1(.018)

[.003] [.012]

Age.................................................. .003 .0001 1

(.0003) (.0005)

[.012] [.000]

Earned at least a bachelor’s 

degree........................................ .052 –.002 1

(.012) (.018)

[.003] [.000]

Married.......................................... .004 –.019

(.012) (.017)

[.000] [.002]

African American....................... –.020 .025 2

(.007) (.024)

[.000] [.001]

Hispanic ........................................ –.149 –.088 1

(.014) (.054)

[.012] [.009]

Minimum sample size.............. 1,148 1,145

1 p < .01. 2 p < .05.

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed on a Tuesday, and an interviewer experience quadratic. Relevant 

dummy is for any simultaneous or secondary activity reported within 

the ATUS or FISCT sample. Numbers shown in each cell are 2006 ATUS

coefficient, (standard error), [adjusted R2].

 Table A-4. 
Monthly Labor Review • August 2010 31

Partial ordinary least squares regression results 

for table A-5, 2003 American Time Use Survey 

(ATUS) and 1998–99 Family Interaction, Social 

Capital, and Trends in Time Use (FISCT) survey 

Primary activity Episodes per day Minutes per day

Sleep ......................................... 0.177 25.1

1

(.026) 1(4.57)

[.027] [.044]

Grooming and not 

elsewhere classified......... –.450 –2.58

1

(.051) (2.51)

[.010] [.003]

Travel......................................... .225 –14.7

2

(.101) 1(2.97)

[.040] [.026]

Work.......................................... .133 –3.23

1

(.050) (8.02)

[.231] [.321]

Childcare.................................. .086 –5.73

(.055) 2(2.64)

[.229] [.161]

Adult care................................ .226 6.03

1

(.014) 1(.960)

[.007] [.005]

Education ................................ .020 2.15

(.023) (2.68)

[.004] [.006]

Leisure and sports................ .267 –17.2

1

(.071) 2(6.67)

[.042] [.060]

Organizational activities.... .069 2.10

1

(.017) (1.85)

[.012] [.009]

Purchasing goods and 

services................................. .161 –.712

1

(.043) (2.35)

[.009] [.007]

Television................................. .250 26.3

1

(.042) 1(5.95)

[.055] [.101]

Household work .................. .146 –10.7

(.080) 2(5.18)

[.053] [.057]

Eating and drinking............. .074 –6.87

2

(.036) 1(2.57)

[.014] [.022]

1 p < .01.

 2 p < .05.

NOTE: Significance is obtained from t-tests for the coefficient 

on an ATUS dummy variable in regressions, including controls for Hispanic ethnicity, education, employment, number of children, diaries 

completed on a Tuesday, and an interviewer experience quadratic. 

Numbers shown in each cell are 2003 ATUS coefficient, (standard error), 

[adjusted R2].

Distribution of primary-activity episodes and Table A-6. 

time, 2003 American Time Use Survey (ATUS) 

and 1998–99 Family Interaction, Social Capital, 

and Trends in Time Use (FISCT) survey

Primary activity

Episodes per day Minutes per day

ATUS FISCT ATUS FISCT

 Total.........................

Sleep ................................

19.92

1

2.15

18.43

1.96

1,440

1

511.1

1,440

484.0

Grooming and not 

elsewhere classified.. 1

1.59 2.05 54.0 57.3

Travel................................ 24.30 4.11 177.3 92.6

Work................................. 11.18 1.11 213.1 226.0

Childcare......................... .96 .796 231.9 34.6

Adult care....................... 1.30 .071 19.31 3.27

Education ....................... .12 .095 14.0 11.7

Leisure and sports....... 12.30 2.05 2145.5 165.5

Organizational 

activities...................... 1

.22 .158 17.0 15.3

Purchasing goods 

and services............... 1

.87 .701 31.9 31.9

Television........................ 11.46 1.18 1155.9 126.8

Household work........... 2.54 2.31 2112.3 117.9

Eating and drinking.... 21.93 1.84 166.8 73.1

1 p < .01.

 2 p < .05. 

NOTE: Significance is obtained from t-tests for the coefficient on 

an ATUS dummy variable in regressions, including controls for Hispanic 

ethnicity, education, employment, number of children, diaries completed on a Tuesday, and an interviewer experience quadratic. (See 

table 3, except that sample size is 19,759 for the 2003 ATUS.)

 Table A-5.