## BLS WORKING PAPERS

U.S. Department of Labor U.S. Bureau of Labor Statistics Office of Employment and Unemployment Research

Secondary Activities in the 2006 American Time Use Survey

Robert Drago

, Institute for Women’s Policy Research

Wo rking Paper 44 6 February 201 1

All views expressed in this paper are those of the author s and do not necessarily reflect the views or policies of the U.S. Bureau of Labor Statistics.1 

## Secondary Activities in the 2006 American Time Use Survey 1

Report to the U.S. Bureau of Labor Statistics August 8, 2008

Robert Drago
Research Director Institute for Women’s Policy Research

All views expressed in this paper are those of the author and they do not necessarily reflect the views or policies of the U.S. Bureau of Labor Statistics.

1 This research was supported by a fellowship from th e American Statistical Association, National Science Foundation, and Bureau of Labor Statistics, and the research was performed at BLS. The author thanks those organizations and Mary Dorinda Allard and Jay Stewart for their generous help with the data and analyses, and the Bureau of the Census for coding the secondary activities data and for providing the precoding results reported in Table 4. The STATA program and data used to generate all other results reported here are available from the author at IWPR, 1200 18 th St NW, Suite 301, Washington DC 20009,

or drago@iwpr.org

.2 Abstract

A major criticism of the American Time Use Survey (ATUS) is that, with the exception of childcare, the survey does not systemati cally collect information about activities respondents did while they were doing someth ing else. The ATUS focuses on collecting information about respondents' main (or prim ary) activities; when respondents volunteer that they were doing seconda ry activities, this inform ation is recorded by the interviewers, but it is not coded and does not appear in the final da ta. This study is an analysis of these additiona l secondary activity data fr om 2006. The study provides descriptive information about who reported secondary activities and the activities they reported. It also quantifies the secondary activity time that was spent in nonmarket work and examines whether the omission of these da ta impacts valuations of nonmarket work. Finally, it evaluates the qualit y of the voluntarily-reported secondary activity data.3 

## Secondary Activities in the 2006 American Time Use Survey

Traditional time-use diaries ask respondents “what they were doing” and if they “were doing anything else” during various portions of a 24-hour day (e.g., Bianchi, Robinson and Milkie, 2006). These questi ons are used to collect info rmation about activities that people do simultaneously. The first question ge nerates information about the primary, or main, activities people were doing at a given time while the second question yields data on additional, or secondary, activities that they were doing. For example, someone who was preparing dinner and watching television at the same time would need to identify which of these was his primary activity and wh ich was his secondary activity in reporting
this information.

The American Time Use Survey (ATUS), the largest-scale time-use study administered in the United States to date, does not e xplicitly ask respondents to report secondary activities other than secondary childcare; instead, its fo cus is on the collection of information about respondents' primary activ ities. However, if respondents voluntarily report doing two or more activities at the sa me time, the ATUS interviewers record all activities that were mentioned. Secondary activity data from the ATUS were neither coded nor analyzed until recently; here, I explore these data from the 2006 ATUS. For present purposes, I distinguish secondary activity reports according to whether the information was explicitly requested from re spondents or was instead volunteered, as is done in the ATUS.

Background Many time-use researchers have argued that time-use studies should systematically collect data about secondary activities. Al exander Szalai, an early pioneer of time-use studies, wrote:

Elimination of secondary or parallel ac tivities from the circ le of observation naturally distorts in a rather arbitrary fa shion the picture of what people do the daylong and leads to a biased account of the amounts of time they devote to the various tasks of life. (1972, p. 3)

In practice, however, secondary activity data usually are ignored in time-use analyses (e.g., see Bianchi, et al., 2006). When they ar e analyzed, the resear chers typically take the naïve approach of dividing the time spent in the episode between the two activities. A person who is eating and watching television for an hour would be classified as having spent one-half hour in each activity.

It is not obvious how time spent in seconda ry activities should be counted, because reported secondary activities can be either tr ue simultaneous activit ies or short-duration sequential activities that are reported as secondary. An example of true simultaneous activities is "preparing dinner" while "listeni ng to the radio," whereas an example of a4 short-duration sequential activity reported as secondary might be "getting the mail" while "watching TV."

One reason time-use data are collected is to learn more about the time people spend doing unpaid work. Unpaid work refe rs to activitie s one could hire someone else to do rather than doing for oneself, and it can be measured directly as a primary activity in any timeuse data set, including the ATUS. Unpaid work is typically captured in two time-use categories: household activities (which ma inly involve unpaid work in and around the home) and childcare. However, many unpaid wo rk activities are eith er of short duration or lend themselves to being done simultaneou s to other activities. For example, an individual may shift laundry from the washer to the dryer in the middle of watching a television show, or mind a child while cooking, cleaning, or reading a novel. In each of these cases, it is possible that some unpaid work would be excluded from the reported primary activities, but included in the secondary activity data.

Childcare tends to account for mo st of the time devoted to un paid work as a secondary activity. Harvey analyzed data from one Au stralian and four U.S. studies, and found that childcare accounted for between three-quarters and nine-tenths of the secondary activity
time classified as either household ac tivities or childcare (2006, p. 201).

The ATUS collects information on the time re spondents spent caring for any child under the age of 13 by asking whether a child of th is age was “in your car e” and, if so, during which activities. This constr uct was designed to capture tim e the respondent was “able to provide assistance to the child if necessary” (Allard, et al., 2007, p.34). As such, it fits within the definition of unpaid work as a ny “activity... that... might be delegated to a paid [employee]” (Reid 1934, p. 11). The restri ction of the measure to younger children (those under age 13) is sensible when viewed in this light since parents of young children typically do not leave them untended for long periods of time. Admittedly, around 7 percent of children below the age of 13 regular ly spend some portion of their day in selfcare (Drago 2007, p. 41), but that number is sm all enough to suggest that most parents would and do often find or pay someone else to care for the child when they cannot provide assistance.

The ATUS measure of secondary childcare cap tures more time than traditional measures of childcare as a secondary activity. In a comparison of the 2003-04 ATUS data with figures from the 2000 National Survey of Pare nts (NSP)–which used the more traditional "what else were you doing?" question—it wa s found that parents averaged around threequarters of an hour on childcare as a secondary activity in th e NSP, but that parents of children under 13 averaged almost 6 hours pe r day on secondary childcare in the ATUS (Allard et al., 2007, p. 31). Consistent with the view that “in your care” time represents unpaid work, Folbre and Yoon (2008) placed a m onetary value on this time in an analysis of the 2003 ATUS data.

Given that the ATUS does not request info rmation on secondary activities other than childcare, it is reasonable to conclude that , on the one hand, measur es of unpaid work developed from the data will be understate d because time devoted to housework as a5 secondary activity is not counted. On the ot her hand, measures of unpaid work that are generated from time-use surveys asking "W hat else were you doing?" to collect secondary activities will understate time spent in childcare as a sec ondary activity. Given the amounts of time involved, the understateme nt of childcare time in traditional surveys is likely far larger than th e understatement of housework in the ATUS, perhaps by a factor of as much as 25 for pare nts of children un der the age of 13. 2 Regardless of the much larger magnitude of the childcare divergence, it would be desirable to pick up missing housework time in the ATUS, and secondary activity data might serve that

purpose.

Not surprisingly, given the discussion to this point, earlier studies find that secondary activities tend to occur in and around the home (Harvey 2006, p. 208). However, childcare and housework comprise only a minority of those activities. Passive leisure in the form of watching television, listening to the radio, or having a conversation accounts for a majority of secondary activity time in those studies. Arguably, being at home lends itself to messy, overlapping and short duration uses of time in a way that being in the workplace or even traveling does not (Kitterod 2001). To the extent that secondary activity reports reflect this messiness, there ma y be more secondary activity reports in the ATUS data for times when respondents were at home.

It also seems reasonable to expect that busier people will more often report secondary activities. If an individual experiences significant time pressures, he or she may respond by speeding up activities and re ducing the average duration, a nd short duration activities may be reported as secondary activities. Further, busy individuals might respond by multitasking—that is, doing multiple activities at once—in an effort to alleviate time pressures and, with the exception of childcare, secondary activity reports provide the only method for respondents to provide informa tion on multitasking in the ATUS. Busy respondents seem most likely to be those who are women, who work long hours, and who have children and part icularly young children.

As suggested earlier, secondary activity reports are likely to include both truly simultaneous as well as short duration, sequentia l activities. Kitterod (2001) argues that truly simultaneous activities should be reporte d as secondary, while sequential activities belong in primary activity reports. To the exte nt there is an advantage to the volunteered method of secondary activity data collection used with the ATUS, it is that respondents may be more likely to report short duration, se quential activities as in fact primary.

In sum, volunteered ATUS secondary activity data (not including the ATUS measure of secondary childcare) will: a) capture housework that would otherwise be missed, b) tend to be located in the home, c) be associated with people who are busy, and d) tend to pick up truly simultaneous rather th an short duration, sequential activities. The analysis below is more general, but these four issues receive much attention.

2 If individuals report three-quarters of an hour of secondary childcare (as in the 2000 NSP), Harvey’s results suggest that the ATUS misses around one-quarter of an hour of secondary housework. The “in your care” figure suggests that traditional secondary childcare measures miss around five hours per day, which is around 25 times as large.6 Data The ATUS is a stratified three-stage sample drawn from households that have recently completed their participation in the Current Population Survey (CPS). CPS households are stratified based on their characteristics, and ATUS sample households are randomly selected from those strata. On e individual is then randomly se lected from the list of adult (age 15 or older) household members. All a dults within a household have the same probability of being selected. One-half of the adults are then assigned a weekend day and one-half are assigned a weekday about which th ey are interviewed a bout their time use. The survey is designed to be nationally re presentative of the civilian noninstitutional population age 15 and older.

The ATUS is sponsored by the Bureau of La bor Statistics and is conducted by the U.S. Census Bureau using computer-assisted telephone interviewing (CATI) technology. All ATUS respondents are assigned an initial day about which they will be interviewed about their time use, and they are called on the follo wing day. If the respondent is unavailable on that day, subsequent contact attempts are ma de on the same day of subsequent weeks. This procedure maintains the pr oportional assignment of resp ondents to days of the week.

The ATUS’s core time diary is very si milar to other time-budget surveys. The respondent is asked to sequentially describe his or her day from 4 AM “yesterday” through 4 AM “today.” The respondent desc ribes each activity, which the interviewer either records verbatim or, for a limited set of commonly-performed, unambiguouslydefined activities (such as sleep ing or watching television), enters a pre-code. When a pre-code is used, an activity code is au tomatically assigned to the activity. If a respondent voluntarily mentions secondary ac tivities, an ATUS interviewer asks the respondent to try to separate the activities into distinct time episodes. If he is unable to divide the activities, the inte rviewer asks the respondent wh ich of the activities was his main activity and records this activity first, followed by the secondary activity. 3 While both the primary and secondary activity data are recorded, only the primary activity is assigned a code and appears in the final ATUS data set. The verbatim responses are coded to a three-tier scheme, going from major activity categories, to sub-categories, to descriptions of very specific actions that together comprise a single third-tier activity.

For each episode, the ATUS interviewer collect s either the ending time or the duration of the activity. In addition, for each activity th e interviewer asks where the respondent was and whom she was with, unless the activity is sleeping, grooming, “refused” (none of your business, etc.), or “don’t know.” For pa id work, respondents are asked to report where they were but not who they were with. 4 The “who” codes for household members identify specific individuals.

3 Source “American Time Use Survey Jefferson Tele phone Center Interviewer Manual,” September 13, 2007 version.

4 In 2010, the ATUS started collecting information about who was present while respondents were working.7 After the time diary has been completed, the ATUS interviewers ask several summary questions that obtain information on childcare , paid work, and volunteering that cannot readily be obtained from the core time diar y. These questions produce the “in your care”
data discussed earlier. Note al so that the “in you care” data are constructed to exclude any episodes involving childcare as a primary activity.

Since the ATUS uses the CPS as a sampling frame, the ATUS data files contain some demographic information that was collected in the CPS, such as information about race and ethnicity. Demographic informati on on household members who were present during the final CPS interview appears in the ATUS data, except that information is excluded about household members who move d out between CPS and ATUS survey administration. For new household members, the ATUS collects only age, sex, and relationship to the responden t; for all household members, th e age, sex, and relationship information provided in the CPS is verified and, if needed, updated. The ATUS updates the respondent's labor force status using an abbreviated version of the basic CPS questionnaire and also updates informati on on usual hours of work, class of worker, industry, occupation, earnings, and school enro llment. In addition, the ATUS collects basic labor market information (whether em ployed or not and full-time or part-time employment status) for the respondent ’s spouse or unmarried partner.

For this project, the Census Bureau code d secondary activitie s 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 when coding primary activities). The coding was performed by the same team that codes the primary activities in the ATUS, so the coding of secondary activities is of high quality and is cons istent with that for primary activities. The Census Bureau coders we re asked to code only secondary activities mentioned first, so if a respondent listed three or four activitie s for a single time-use episode, the third and fourth we re not coded and are not analy zed here. Fortunately, even in traditional time-use diaries with request ed secondary activity reports, episodes with more than two activities provided for a single episode are rare, and even more rarely analyzed (e.g., Harvey 2006; Kitterod 2001), so the loss of information here should be
minimal.

It is important to note that ATUS interviewe rs do not record the starting and ending times of secondary activities. I follow the usual pr actice of using the duration of the primary activity, which implicitly assumes that the secondary activity was done for the entire period.

The ATUS data can be analyzed at either the respondent- or episode-level. In the 2006 data, there were 12,943 respondents who repor ted a total of 263,046 time-use episodes. The weighting variable TUFINL WGT is designed to correct for stratification of the sample. The weight can be applied at the respondent level to approximate figures for the civilian noninstitutional population over the age of 14 and, except where explicitly mentioned, that weight is applie d to all figures below. The we ight is also applied at the episode level for the same reasons, but note that respondents who report a greater number of episodes are implicitly weighted more h eavily in those results. Therefore, episode-8 level analyses should not be considered representativ e of the population, although it could be argued that weighting makes the resulting figures representative of the population of time-use episodes.

The 2006 ATUS includes 17 major time-use categories, an 18 th category that accounts for data that cannot be assigned a code, and 462 detailed categories. 5 The major time-use categories are used in most of the following analyses.

Respondent-Level Analyses On a weighted basis, 29.3 percent of ATUS respondents report at least one secondary activity (3,955 out of 12,943 res pondents). This rate seems high given that respondents are not asked to report secondary activities. But in time-use surveys that systematically collect secondary activities, th e rate is close to 90 pe rcent (Harvey 2006, p.199). The magnitude of this difference suggests that vo lunteered secondary activities in the ATUS are not comparable to traditi onal secondary activity reports.

Table 1 shows the average time spent in the major activity categories in the ATUS, both as primary and secondary activities. On av erage, respondents reported a little over onehalf hour per day engaged in s econdary activities, and fully ha lf of that time was devoted to socializing, relaxing, and leisure, with just over 7 minutes spent on eating and drinking, and just under 5 minut es on household activities. As previously discussed, respondents reported spending less time in secondary activities under the volunteered approach than when they were asked to re port secondary activities. When respondents were asked to report seconda ry activities, most reported over 3 hours (Harvey 2006, p. 210).

On the other hand, when secondary activities are requested, respondents may be more inclined to report short-duration sequential ac tivities as secondary rather than taking the time to break them apart and report them as pr imary activities. A comparison of the data
used here and of data from an earlier nationally-representative, time-use study that explicitly requested se condary activity reports suggests th at this might be the case: the ATUS generates a greater mean number of ep isodes per respondent, even with extensive controls (see Drago and Stewart 2010).

5 For documentation, see the ATUS 2006 Coding Lexicon available at the ATUS web site: http://www.bls.gov/tus.9 Table 1: Average Cumulative Duration of S econdary and Primary Activities, Minutes

Secondary Primary Time-Use Category activities activities Personal care and sleep 0.93 563.69

Household activities 4.84 109.33 Caring for household members 0.79 26.93 Caring for nonhousehold members 0.43 8.99

Work 0.45 207.23

Education 0.23 27.39 Consumer purchases 0.17 24.25 Professional and personal care services 0.06 5.18

Household services 0.06 1.08
Government services 0.00 0.63 Eating and drinking 7.04 66.79 Socializing, relaxing, and leisure 18.46 271.73 Sports, exercise, and recreation 0.60 18.93 Religious and spirit ual activities 0.15 7.24

Volunteer activities 0.11 7.78 Telephone calls 0.46 7.06

Travel 0.07 74.59

Uncoded activities 1.20 11.20

Total time per day 36.05 1440.00 Sample size, N 12,943 12,943
Source: 2006 ATUS. Note: The to tal time per day spent doing primary activities does not sum to 1440 minutes due to rounding.

Time spent on primary activities has a very di fferent distribution than that for secondary activities. Primary activities mainly invol ve personal care and sleep (over 9 hours); socializing, relaxing, and leisure (over 4.5 hour s); work (just under 3.5 hours); household activities (almost 2 hours); travel (1.25 hours); and eating and drinking (just over 1 hour). Sleep and work are likely less often done while in engaging in other simultaneous activities or short sequential activities, agai n suggesting that the secondary activity data are picking up rele vant activities.

Turning to unpaid work, respondents spent ju st over 6 minutes per day in household activities (including caring for household a nd nonhousehold members) as a secondary activity. Only 1.02 minutes of this time was spent on childcare, which is already captured by the more inclusive “in your care” measure. Given the brief amount of time spent in household activitie s as a secondary activit y–5.04 minutes after excluding childcare—it follows that the use of the seconda ry activity data, as cu rrently collected, to improve estimates of household production would not contribute much time or value.10 The incidence of secondary activ ities is not distributed evenly across days of the week. Instead, the average respondent reports a low of 0.359 second ary activities for Tuesdays, rising to 0.436 activitie s on Wednesdays, 0.483 activities on Thursdays, with a peak at 0.533 activities on Fridays, followed by a declin e to 0.431 activities on Saturdays, with a mean of 0.414 activities on Sundays and Monda ys. A negative binomial regression, with the number of secondary activities as the de pendent variable and dummies for the diary day (omitting Wednesday), reveals that signif icantly fewer secondary activity episodes occur on Tuesdays and significantly more occu r on Fridays, both at the 5 percent level. 6 It is possible that respondent s engage in more simultaneous or short-duration activities on Fridays; alternatively, respondent s may be willing to take mo re time to do the interview and report secondary activities on Saturday s. Ultimately, it is impossible to know whether the latter possibility is correct because the reporting of secondary activities might either increase the reporting burden on respondents to the extent they are providing additional information, or decr ease the burden if respondents us e secondary reports as an alternative to providing more de tailed primary activity data.

We can, however, shed some indirect li ght on the reason for reporting secondary activities by comparing the characteristics of those who do and do not report secondary activities, as shown in Tabl e 2. The figures are mainly percentages, an d significance levels are from a simple logit regression predicting whether or not the respondent reported any secondary activity. 7 Significant differences suggest that women are more likely to report secondary ac tivities and that re spondents reporting these activities are around 5 years older, that they ar e only half as likely to be Hispanic, that they are around 5 percentage points more likely to hold at leas t a bachelor’s degree, and that they worked around 3.5 hours per week less than respondents who did not report secondary activities.

6 Wednesday is omitted because the 0.436 average for th at day is closest to the mean for the entire sample (0.439). Note that OLS performs poorly in the presence of many zero values, as is true here. Tobit could be applied, but this technique assumes that many of the zero values represent latent negative values, and it is not obvious what meaning negative values would convey. The negative binomial is a count regression method with a natural lower bound of zero. See Appendix table A1 for results.

7 Logit is a typical regression procedure when the dependent variable is dichotomous, as is the case here. A relevant alternative, the simple probit, yields identical signs and significance on th e relevant variables. See Appendix table A2 for results.11 Table 2: Characteristics of Respondents who Do and Do Not Report Secondary Activities

One or more No secondary secondary activ ities activities Characteristic reported reported Women (percent) 55.8** 49.8 Any children (percent) 38.0 43.9 Child under 6 years (percent) 16.1 20.0 Married (percent) 59.2 57.4 Age (years) 47.2** 42.7 African-American (percent) 11.3 12.9 Hispanic (percent) 7.5** 15.6 Bachelor’s degree or higher (percent) 29.0** 23.8 Employed (percent) 60.7 66.6 Weekly work hours 22.4** 25.9

Sample size, N 3,955 8,988 Source: 2006 ATUS. ** for figure that is signi ficantly larger in a logit predicting any secondary activity, 1% significance level.

Women and those with high levels of educat ion may be busier, which may lead these respondents to report more second ary activities. Consistent with this interpretation, the correlation between primary and secondary activity counts is 0.269. But consistent with this explanation, one would expect that respond ents with children or those who work long hours would more often report secondary activities; but this is not the case. 8 Further, it seems unlikely that older respondents are busie r, yet an age quadratic in an otherwise identical linear OLS regressi on yields a maximum probability of reporting secondary activities among respondents over 80 years of age. 9 It is at least possible that older respondents are willing to take the time to report their activities more completely. 10 Alternatively, some older respondents ma y suffer from recall difficulties and use secondary activity reports inst ead of providing more detailed primary activity reports. A disproportionate number of older respondents’ interviews are dr opped from the ATUS sample because they spent too much time in uncodeable activities (for example, “don’t know”). That possibility suggests that the positive correlation between the number of primary and secondary activity episodes will be negative for older respondents. In fact, the correlation coefficient rises from 0.269 for the overall sample to 0.280 for the 1,460 respondents over the age of 70 years, sugge sting we can discount this alternative

8 Further, introducing an interaction between gender and children (i.e., a mother variable) did not yield a significant coefficient.

9 See Appendix table A3.

10 Consistent with this possibility, the simple corr elation between age and primary time spent on the category of socializing, relaxing, and leisure is a pos itive 0.280. A linear OLS regression with socializing, relaxing, and leisure time as the dependent variable, an d an age quadratic as the dependent variable, yields an estimated minimum at age 35.1 years, suggesting the greatest amount of leisure and related time is available to respondents over the age of around 70 years.12 explanation. Also, note that there is no obvious explanation for why Hispanic respondents report secondary activities less of ten; perhaps the difference is cultural. 11

An alternative way to examine the same issues lies in a regression of the cumulative daily time devoted to secondary activities on independ ent variables for the same characteristics listed in Table 2. Using the negative binomial method yields results very similar to those just discussed except that women are no more likely than men to report more time in secondary activities, while those who are employed report significantly less time in secondary activities (at the 1 percent level). 12

As a more direct test for whether busy respondents are associated with secondary activities, the regressi ons discussed above were replicated with the amount of leisure time as a primary activity serving as the indepe ndent variable. In both the logit for any activities and the negative binomial for cumulative time, relevant coefficients are significant at the 1 percent level. 13 Simulations from OLS regressions suggest the effects are indeed positive though small; a 60-minute increase in leisure time raises the probability of reporting any s econdary activity by 0.5 percent and expands the average amount of time spent on secondary activities by 3.4 minutes per day. However, it is important to note that leisure is historically associated with sec ondary activity reports, and this correlation may in fact represen t the relative ease with which simultaneous activities can be performed while engaging in leisure activities.

In sum, there is mixed evidence of secondary activity reports being associated with busy respondents, casting doubt on th e validity of the data.

Episode-Level Analyses Moving down from the level of the res pondent, there are 6,046 secondary activity episodes, or a weighted 2.19 percent out of 263,046 total episodes. The average respondent reports 20.1 episodes per day, with 0.44 episodes having secondary activities. Somewhat surprising given the small number of secondary activities reported, nearly onethird of all respondents report at least one secondary activity.

Table 3 shows the percentage of episodes accounted for by each of the major activity categories. The first column shows the dist ribution of secondary ac tivities. The second column shows the distribution of primary ac tivities for episodes in which a secondary activity was reported, and the last column shows the distribution of all primary activities. The distributions in the three columns were computed independently. I discuss the links between primary and seconda ry activities later.

The distribution of episodes in Table 3 is si milar to the distribution of time spent in the different activities shown in Table 1. Almost half of all secondary activity episodes are

11 Drago and Stewart (2008) find that Hispanics are only around one-th ird as likely to report secondary activities when they are requested, although th e difference is not sta tistically significant.

12 The negative coefficient on work hours only achieves significance at the 5 percent level in this regression, presumably because it is collinear with employment. See Appendix table A4 for results.

13 See Appendix tables A5and A6.13 socializing, relaxing or leisur e, followed by eating and drinking, and household activities. The remaining time-use categories each accoun t for less than 5 pe rcent of secondary activity episodes.

Table 3: Distribution of Secondary and Primary Activity Episodes, Percentages (weighted)

Primary

activities

with a Secondary secondary Primary Time-Use Category activities activity activities Personal care and sleep 2.04 2.44 18.37
Household activities 11.96 13.39 13.23 Caring for household members 3.59 5.25 4.61 Caring for nonhousehold members 1.80 1.47 1.21
Work 1.35 3.08 5.92

Education 0.45 0.80 1.12 Consumer purchases 1.09 1.20 3.34 Professional and personal care services 0.16 0.23 0.58

Household services 0.16 0.10 0.12

Government services 0.02 0.05 0.05 Eating and drinking 20.06 22.59 10.27 Socializing, relaxing, and leisure 49.33 41.74 16.15 Sports, exercise, and recreation 1.08 1.38 1.19 Religious and spirit ual activities 0.57 0.30 0.50

Volunteer activities 0.41 0.72 0.50 Telephone calls 1.24 1.45 1.15

Travel 1.02 2.37 20.82

Uncoded activities 3.68 1.44 0.88
Total 100.00 100.00 100.00 Sample size, N 6,046 6,046 263,286
Source: 2006 ATUS.

There are, however, marked differences in the distribution of primary activities depending on whether or not a secondary ac tivity was reported. When the respondent reports a secondary activity, ove r 40 percent of related prim ary activities fall into the category of socializing, relaxi ng, and leisure, followed by eating and drinking, and then by household activities. In th e overall sample, the most fr equent activity is travel, followed by personal care and sleep, with the th ree categories just discussed trailing those14 two. 14 It seems likely that socializing, rela xing, and leisure; eati ng and drinking; and household activities lend themselves to both truly simultaneous and short-duration, sequential activities, so we cannot ascertain whether the volunteered method of secondary activity data collection focuse s respondents on truly simultane ous activities as secondary. I return to this issue in the analysis of detailed time-use categories below.

One possible linkage between specific primary activities and secondary activity reports lies in the pre-codes available to ATUS in terviewers for a set of 15 detailed primary activities. Because the pre-codes speed up th e process of data entr y, it is possible that interviewers will be more likely to collect secondary activity reports for activities that can be pre-coded. Table 4 shows that 125,038 (or 47.5 percent) of episodes were coded using a pre-code. If the use of pre-codes leads to greater reporting of s econdary activities, the percentage of secondary activ ity episodes reported during pr e-coded activities should be larger. In fact, only 2,544 of 6,046 secondary activity episodes, or 42.1%, have precoded primary activity reports. Further, in over 2,100 of those episodes the primary activities were pre-coded as watching televi sion or eating and dri nking, activities which are traditionally associated with secondary activities. 15 Therefore, it seems reasonably safe to conclude that the use of pre-code s does not affect the reporting of secondary activities.

14 In the ATUS, if a respondent reports doing simulta neous activities that involve a travel episode, the travel will be collected and coded as the respondent's primary activity. For example, if someone reports driving to work and talking on the phone at the same time, the episode would be coded as travel.

15 For all but one of the sleep episodes where a secondary activity was reported, the latter activity involved watching “television and movies (not religious).”15 Table 4: Pre-coded Primary Activit ies and Secondary Activity Episodes
Number
of Number of Percent of pre-coded pre-coded pre-coded

primary primary Total primary

activities activities number of activities

with a without a pre-coded with a Primary activity secondary secondary primary secondary description activity activity activities activity Sleeping 9 27,652 27,661 0.03 Grooming (Self) 45 16,791 16,836 0.27 Watching television 902 18,683 19,585 4.61 Working, main job 40 9,907 9,947 0.40 Working, second job 1 392 393 0.25 Preparing meals and snacks 137 10,798 10,935 1.25 Eating and drinking 1,200 24,811 26,011 4.61 Cleaning the kitchen 53 3,886 3,939 1.35 Laundry 130 3,311 3,441 3.78 Grocery shopping 4 2,099 2,103 0.19 Attending religious services 0 1,008 1,008 0.00 Paying household bills 3 46 49 6.12 Caring for animals and pets 20 2,208 2,228 0.90

Do not know 0 853 853 0.00
Refusal 0 49 49 0.00 Total 2,544 122,494 125,038 23.76
Source: 2006 ATUS.

Splitting out childcare from the two care cate gories (Caring for and helping household members and Caring for and helping nonhousehol d members) reveals that 4.71 percent of all primary activity episodes, but a sligh tly lower 4.37 percent of secondary activity episodes, were childcare.

Table 5 shows the distribution of where codes for episodes that have secondary activities and for all episodes. The “home or yard” ca tegory accounts for ju st under 40 percent of all episodes, but almost three-quarters of secondary activity episodes. The only other
location that accounts for at l east 5 percent of secondary activity reports is someone else’s home. These findings are consistent w ith the interpretation th at secondary activity
data are to some extent reflecti ng the messiness of home life.16 Table 5: The Location of Primary and Seconda ry Activity Episodes, Percentage of All Episodes Secondary All activity Location Episodes episodes Home or yard 39.36 72.11

Unknown 1 18.18 1.10 Car, truck, or motorcycle (driver) 14.28 1.74 Workplace 7.05 4.67 Car, truck, or motorcycle (passenger) 3.57 0.00 Other place 3.19 3.97

Someone else’s home 3.14 7.39
Other store or mall 2.19 1.24

Restaurant or bar 1.88 3.55 Walking 1.80 0.00

School 1.60 1.11 Other categories, accounting for
<1% of the total 3.76 3.12

Total 100.00 100.00 Sample size, N 263,286 6,046

1 Location data are not collected for ti mes respondents were sleeping, grooming, doing personal activities, and when they didn't know or refused to provide information about what they were doing.
Source: 2006 ATUS.

Information about who respondents were with is not collected for times they reported sleeping, grooming, and a few other personal activities, which together account for 24.1 percent of all episodes. Th ese activities rarely generate secondary activities, and whowith information is missing for only 3.7 percen t of episodes with s econdary activities.

Ignoring episodes during which the who-with information was not collected, figures for who respondents were with during all episode s and during secondary activity episodes are shown in Table 6. Note that these figures do not sum to 100 percent because multiple individuals may be present during an activity. Respondents were slightly less likely to be alone while engaging in secondary activities (a 3 percentage point divergence), and this difference is explained by the more frequent presence of either a partner or spouse or other adult during the episode.

Children were only about 2 percentage points less likely to be present during secondary activity episodes. This result does not, howev er, imply that childcare is rarely done as a secondary activity, since a full 34.8 percent of “in your care” episodes occur when the child is not in the same location (e.g., is inst ead in the next room or outdoors). That time is, as noted earlier, linked to secondary activity reports.17 In earlier U.S. time-diary surveys, alone time accounted for a smaller fraction of episodes—between 22.7 and 36.6 percent (Harvey 2006, p. 208). Although other explanations might be plausibl e, it is possible that the grea ter incidence of being alone during secondary (and perhaps primary) ac tivity episodes in the ATUS reflects the dramatic growth of single-person households in recent decades (Fields and Casper 2000).

Table 6: Who Respondents were with as a Percentage of Non-missing Episodes

All Secondary activity activity

Who with episodes episodes

Alone 45.96 42.78 With partner or spouse 21.49 25.96

With child 22.42 20.39 With partner or spouse and child 7.03 7.20

With other adult 22.92 27.51
Sample size, N 203,937 5,852 Source: 2006 ATUS. Note that percenta ges do not add up to 100 because respondents can be with people from more than one category.

The final analyses connect primary and secondary activities across the major time-use categories. For the most-frequently-repor ted secondary activities, I examine detailed time-use categories for both sec ondary and primary activities.

The major time-use categories for secondary ac tivity episodes were matched with those for primary activities, resulting in an 18-by-18 matrix with 6,046 unweighted observations. I restrict my attention to the seve n cells that have at l east 2 percent of these episodes (more than 130 observations each). These cells account for 4,143, or about twothirds, of the 6,046 secondary activity episodes. The cells are listed in descending order of prevalence in Table 7. Considerin g the number of episodes, linkages between socializing, relaxing, and leis ure, and eating and drinking are by far the most common, and comprise over half of all secondary activit y episodes. Household activities as either secondary or primary account for around one-s ixth of these episodes, and caring for household members covers a small fraction of the episodes.

The last column of Table 7 reports the average amount of time per day spent on the linked activities. Recalling that secondary activity repor ts account for just over 36 minutes per day, on average, the figures show that around one-quarter of that time is accounted for by leisure as either a primary or a secondary activity. Indeed, over half of all secondary activity time ( 18.43 minutes) can be attributed to some mixture of leisure and eating and drinking.18 Table 7: Related Secondary and Primary Ac tivity Episodes, Number of Episodes and Cumulative Duration Related Number Average Secondary primary of minutes

activity activity episodes per day

Socializing, Relaxing, Eating and

and Leisure Drinking 1,108 4.25

Socializing, Relaxing, Soci alizing, Relaxing,

and Leisure and Leisure 1,042 8.82

Eating & Socializing, Relaxing, Drinking and Leisure 899 5.47

Socializing, Relaxing, Household

and Leisure activities 351 2.08

Household Household

activities activities 318 2.01

Household Socializing, Relaxing,

activities and Leisure 273 2.15

Socializing, Relaxing, Ca ring for household

and Leisure members 152 0.28

Total sample size, N 6,046 12,943
Source: 2006 ATUS.

In two instances, the primary and secondary ac tivities are in the sa me major category. Earlier in Table 1, we saw that responde nts spent just under 5 minutes per day in household activities. In calcula tions of the time spent in unpa id work, the 2 minutes per day when household activities were reported as both the primary and secondary activities
must be subtracted from this tota l so that it is not double-counted.

For a more fine-grained look at linkages between the secondary and linked primary activities, I analyzed detailed activity categor ies where the relevant major categories for the secondary activity are either: house hold activities; eating and drinking; or socializing, relaxing, and leisure, as shown in Table 8. Thes e three broad categories not only figure prominently in the analysis presente d in Table 6, but are also most prevalent in terms of both the cumulative amount of time involved (see Table 1), and the number of episodes reported (see Table 3). Note that, for the secondary activity reports, eating and drinking is both a broad activity category a nd a single detailed category. For simplicity, detailed categories accounting for less than 5 percent of relevant episodes are excluded
from the table.19 A total of 3,014 secondary activity reports ar e categorized as soci alizing, relaxing, and leisure, with watching television, socializ ing, and reading accounting for most of the episodes. Related primary activities involve eating and drinking, watching television, socializing, and readi ng. For the 1,190 episodes of ea ting and drinking as a secondary activity, primary activities mainly involve wa tching television, soci alizing, and reading. For the 757 episodes of household activities as secondary, detailed ac tivities are largely comprised of doing laundry; inte rior cleaning; food and drink preparation; care for pets; household and personal organization and pl anning; household and personal mail and messages excluding email; and sewing, repair ing, or maintaining textiles. The main associated primary activities in this case include watching televisi on, interior cleaning, socializing, and doing laundry.

Table 8: Detailed Secondary Activity Ep isodes and Related Primary Activities

Secondary Related

activity Detailed secondary activity primar y activity

Socializing, Television (51.9% ) Eating and drinking (38.8%)

Relaxing, and Socializing (18.9%) Television (9.3%)
Leisure Reading (11.9%) Socializing (8.8%)

(3,014 episodes) Reading (13.5%)

Eating and Eating and dri nking Television (25.5%)

Drinking Socializing (24.6%)
(1,190 episodes) Reading (13.5%)

Household Laundry (21.6%) Television (22.8%)

activities Interior cleaning ( 14.8%) Interior cleaning (10.2%)

(757 episodes) Food and drink prep aration (11.5%) Socializing (9.2%)

Care for pets (9.3%) Laundry (5.6%)

Household and personal
organization and planning (8.0%)
Source: 2006 ATUS.

Overall, the analysis of detailed categories suggests that secondary activities largely revolve around watching tele vision and eating and drinking, either as a secondary or associated primary activity.

In terms of the validity of the data, we need to know whether these activities are more often performed as truly simultaneous activitie s, or instead in short duration, sequential episodes. Unfortunately, both watching televisi on and eating and drinking are subject to either interpretation. We simply have no way of knowing which is the case.20 Conclusion The quotation from Alexander Szalai provided earlier in this report suggested that the ATUS should have taken a more traditional a pproach and explicitly requested secondary activity data from respondents. This analysis has examined the secondary activity reports collected in the 2006 ATUS. In some ways, the volunteered secondary activity data seem to mimic traditionally-requested secondary activity reports. Most secondary activities occur in the home and women are more like ly to report secondary activities, which together reflect the messiness of home life and the prominent role that women continue to play in the home. Consistent with exp ectation, more-highly-e ducated respondents are also more likely to report s econdary activities. When s econdary activities are reported, the most common activities are socializing, relaxing, and leisure; eating and drinking; and household activities. But, contrary to exp ectations, respondents who work longer hours were less likely to report sec ondary activities, while responde nts who are over the age of 70 were more likely.

One reason for collecting data on secondary activ ities is to obtain a better measure of household production for national income and product accounts. However, very little household production beyond childcare was identified in this analysis. Further, the little time that was identified – around 5 minutes – was mainly done in conjunction with household activities as a primary activity, or with socializing, re laxing, and leisure, suggesting that the 5 minutes would need to be discounted substantially before incorporating that time into satellite accounts.

The results presented here make it clear that ATUS respondents report secondary activities far less frequently and secondary activities account for far less time compared with traditionally-c ollected secondary activ ity reports. Thus, the secondary activity data that are currently collected in the ATUS are of limited value. Given the low quality of these data, it is hard to make the case for incurring the expense of coding the data for other years and incorporating th em into analyses. If the data used for this study were made available from the BLS, at a minimum, researchers would be wise to treat the data with caution.

Would it make sense to start systematically collecting secondary activ ities in the ATUS? Collecting these data would provide richer information about how Americans spend their time. It would also provide a more comple te picture about the amount of time spent in household activities, which would be useful fo r constructing satellite national income and product accounts to measure the value of household production. The amount of time involved is likely to be rela tively small – Harvey’s results suggest pe rhaps 15 minutes per day. In the grand scheme of economic pr oduction, 15 minutes of unpaid work per day, applied to an entire adult popul ation over an entire y ear, is arguably nontrivial. However, in a comparison of the data used here with results from an earlier nationallyrepresentative time-use surve y, Drago and Stewart (2010) c onclude that the relevant undervaluation of housework due to the ATUS not explicitly requesting secondary activity data involves the economic va lue of only around one minute per day. 16

16 The much smaller figure arises from three factors: 1) much housework as a primary activity is performed in conjunction with leisure, so should be discounted, 2) around half of housework as a secondary activity is21 The major danger of changing the ATUS to systematically collect secondary activities is that it may change the way that primary activit ies are reported. Two analyses suggest this danger is potentially significant. Kitterod (2001) analyzed two days of Norwegian timeuse diaries wherein secondary activity reports were explici tly requested of respondents only on the second day. She found differences in the pattern of primary activity reports across the two days, and suggests the data ar e not strictly comparable. Further, a comparison of the ATUS data analyzed here, and of 1998-1999 U.S. time-use data including traditional secondary activity reports, suggest not only that primary activity reports are altered by the inclus ion of explicit seconda ry activity options, but also that the quality of primary activity reports may be compromised in the process (Drago and Stewart 2008). The main issue is that if respondents are asked to report secondary activities, they may report s hort-duration primary activities as secondary. For example, someone who spends 20 minutes cooking, 5 minutes talking on the phone, and then another 20 minutes cooking may report a singl e 45-minute episode of cooking with the secondary activity of talking on the phone. Ho wever, evidence in the Drago and Stewart study suggests that the ATUS pr actice of encouraging respondents to break apart these activities mitigates this problem. In the Kitterod (2001) study, respondents were given leave-behind diaries, so there was no inte rviewer to prompt respondents to break these activities apart. If such a change is seriously contemplated, it would be wise to begin with a pilot, wherein some respondents are and othe rs are not requested to provide secondary activity reports. If that pilot demonstrated that the quality of primary activity reports would not be substantially impaired, it might then be reasonable to expand secondary activity data collecti on to include all future ATUS respondents.

performed in connection with housework as a primary activity, and it would not make sense to double the value of housework when it is performed as both a primary and secondary activity, and 3) much of the remaining housework as a secondary activity is related to leisure as a primary activity, so it should also be discounted.22 REFERENCES

Allard, M.D., S. Bianchi, J. Stewart and V.R. Wight. 2007. “Comparing Childcare Measures in the ATUS and Earlier Time-Diary Studies.” Monthly Labor Review
130:27-36. Bianchi, S.M., J.P. Robinson and M.A. Milkie. 2006. Changing Rhythms of American Family Life . New York, NY: Russell Sage. Budig, Michelle and Nancy Folbre. 2004. “Ch ild Care vs. Child-Mi nding: Measuring Activities, Responsibilities, and Time,” in Family Time: The Social Organization of Care , Nancy Folbre and Michael Bittman, eds. New York: Routledge. Drago, Robert. 2007. Striking a Balance: Work, Family, Life . Boston: Dollars and Sense. _______ and Jay Stewart. 2010. “Time-use Surveys: Issues in Data collection on Multitasking.” Monthly Labor Review 133:17-31. Fields, Jason, and Lynne M. Casper. 2000. “America’s Families and Living Arrangement: Population Characteristics,” Current Population Reports , P20-537. Washington, DC: U.S. Bureau of the Census. Folbre, Nancy. 2001. The Invisible Heart: Economics and Family Values . New York:
Free Press. Folbre, Nancy and Jayoung Yoon. 2008. “The Va lue of Unpaid Child Care in the U.S. in 2003,” in How Do We Spend Our Time? Evidence from the American Time Use Survey , ed. Jean Kimmel. Kalamazoo, MI: W.E. Upjohn Institute, 33-58. Harvey, Andrew S. 2006. “Nonmarket Produc tion and Historical Time-Use Data: Potential and Issues,” Time Use Resarc h Program, Saint Mary’s University, Halifax, Nova Scotia, Canada, May 15. Kitterod, Ragni Hege. 2001. “Does the Recordin g of Parallel Activities in Time Use Diaries Affecct the Way People Report Their Main Activities?” Social Indicators Research 56: 145-178. Landefeld, Steven J., Barbara M. Fraume ni, and Cindy M. Vojtech. 2009. "Accounting for Nonmarket Production: A Prototype Sa tellite Account Using the American Time Use Survey." Review of Income and Wealth 55: 205-225. Reid, Margaret. 1934. Economics of Household Production . New York: John Wiley &
Sons. Szalai, Alexander. 1972. The Use of Time . The Hague: Mouton.23 APPENDIX

Table A1: Negative Binomial Regression - Number of Secondary Activities

Variable Coefficient Std Error p-value Sunday -0.0442 0.0714 0.5360 Monday -0.0536 0.0893 0.5480 Tuesday -0.1957 0.0872 0.0250 Thursday 0.1021 0.0845 0.2270 Friday 0.1994 0.0870 0.0220 Saturday -0.0133 0.0713 0.8520

Constant -0.8295 0.0593 <0.0001

Table A2: Logistic Regression – Any Secondary Activities Variable Odds Ratio Std Error p-value

Woman 1.1763 0.0643 0.0030 Any children 1.0339 0.0740 0.6420 Child under 6 years 0.9300 0.0679 0.3200

Married 0.9472 0.0567 0.3640 Age 1.0273 0.0088 0.0020 Age_squared 0.9998 0.0001 0.0350 Employed 1.0767 0.1044 0.4460

African-American 0.8756 0.0626 0.0630 Hispanic 0.4972 0.0451 <0.0001 Bachelor’s degree or higher 1.2780 0.0785 <0.0001 Weekly work hours 0.9921 0.0021 <0.000124 Table A3: Linear Regression – Any Secondary Activities

Variable Coefficient Std Error p-value

Woman 0.0323 0.0110 0.0030 Any children 0.0055 0.0141 0.6970 Child under 6 years -0.0135 0.0138 0.3290

Married -0.0098 0.0122 0.4250 Age 0.0049 0.0017 0.0050 Age_squared <0.0001 <0.0001 0.0930 Employed 0.0144 0.0199 0.4710

African-American -0.0191 0.0082 0.0190 Hispanic -0.1183 0.0135 <0.0001 Bachelor’s degree or higher 0.0515 0.0130 <0.0001 Weekly work hours -0.0016 0.0004 <0.0001

Constant 0.1722 0.0373 <0.0001

Table A4: Negative Binomial – Cumulati ve time for Secondary Activities

Variable Coefficient Std Error p-value

Woman 0.0861 0.0574 0.1340 Any children -0.0532 0.0815 0.5140 Child under 6 years -0.0906 0.0845 0.2830

Married -0.0836 0.0633 0.1860 Age 0.0266 0.0092 0.0040 Age_squared -0.0002 0.0001 0.0220 Employed -0.3212 0.0999 0.0010

African-American -0.0303 0.0878 0.7300 Hispanic -0.6308 0.0935 <0.0001 Bachelor’s degree or higher 0.1897 0.0598 0.0020 Weekly work hours -0.0044 0.0022 0.0460

Constant 3.2073 0.2168 <0.0001

Table A5: Logistic Regression – Any Secondary Activities

Variable Odds Ratio Std Error p-value

Total Leisure Time 0.0004 0.0001 <0.0001

Constant -0.9979 0.0431 <0.0001

Table A6: Negative Binomial – Cumulati ve time for Secondary Activities

Variable Coefficient Std Error p-value

Total Leisure Time 0.0015 0.0002 <0.0001

Constant 3.1419 0.0557 <0.0001