Introduction (continued)
In this document:
The nature of time use data
The time use data are collected by means
of time diaries. Respondents record their activities in time diaries, using
their own words. The diary covers 24 hours. With some exceptions each
respondent fill in diaries for two diary days. In HETUS the diary instrument
records four recording domains:
1. Main activity: “What did you do?”,
2. Parallel or secondary activity : “Did you do anything else? If so, what?”,
3. Who with: “Were you alone or together with somebody you know, if so,
who?”,
4. Location (incl. mode of transport)
As a result the data consists of a sequence of episodes or events, each
characterised by these four recording domains. In addition, there are
individual and temporal identifiers. The individual identifier (“diary/person
id”) connects the episode to a particular respondent and a particular diary
day. The individual identifier also connects to background information on
the respondent’s household and individual circumstances. The temporal
identifiers indicate starting and ending time, and, hence, also duration of
the episodes. In order to comprehend what the data has to offer in terms of
analysis, which is a lot, it is rewarding to keep the structure of the data,
i.e. the sequence of episodes, in mind.
The background information is collected by means of interviews. The purpose
of this information is to form the population groups for which the time use
estimates are to be calculated.
Guide to interpretation of the statistical measures
The most essential statistical measures in time use statistics are mean time
spent on various activities and the proportion of the individuals that
spent some time doing the activities during the day they kept the time
diary (“participation rate”). All measures may be calculated for a great
variety of population groups depending on which background information has
been collected.
Mean time for an activity is calculated as follows: Assume the activity paid
work and the population group women. Now, for all diaries filled in by
women,
the duration of all episodes of paid work is summed up. Some women will
then contribute with many hours of paid work, and other women that did not
work for pay at all during the diary day, will not contribute to the sum.
The sum, i.e. all women’s total hours of paid work is divided by the total
number of women (or rather the number of women’s diaries), regardless
of whether or not they carried out any paid work. The mean contains no
information on the distribution of number of hours of paid work within the
population group. Entirely different distributions may result in the same
mean. Suppose the mean is 4 hours a day. If all women work 4 hours a day,
the mean will be 4 hours a day. The result will be the same if half of the
women work 8 hours and the other half do not work at all. Consequently, the
mean conceals differences.
In this case the mean is a characteristic of the population group; the
population group women spends all together a certain number of hours of paid
work. If the number of hours is evenly distributed within the group, all
women would have worked 4 hours. But, as mentioned, the distribution may
also have a completely different shape.
Now, if the means in two population groups differ, it implies that one of
the population groups, i.e. the individuals in the group all together, spend
more time on paid work.
Some information on the distribution is contained in the participation rate,
i.e. the proportion of the individuals that devote some time to the
activity. If the proportion is 100 percent, everyone carried out some paid
work, if it is 50 percent, half of them did, etc. If two population groups
have the same mean, but the participation rates differ, one can conclude
that individuals belonging to the population group with the lowest
participation rate on average worked longer hours than those belonging to
the other population group, provided that they worked at all. This measure,
mean time for those who in fact performed the activity, is often found in
time use statistics publications. Note that this measure also conceals the
distributions behind. The present system permits calculation of all three
measures mentioned above.
Measurement at group level
The respondents fill in diaries for one or two randomly designated days.
Hence short, random moments in people’s lives are studied. They can not be
regarded as representative to the single individuals. Therefore measures of
the time use are meaningful only when they are calculated for groups of
individuals of considerable size. The groups are formed by the information
collected by means of interviews. Significant population groups are sex, age,
stage in the family cycle, number of children etc. In the system these and
many other population groups may be formed.
Interpretation of the recording domains
Research has demonstrated that it is necessary to apply some kind
chronological recording of episodes in time diaries (of some kind) – like it
is in HETUS  in order to obtain reliable data on time use.
In HETUS the respondents record their activities in time diaries using own
words. This is done for one or two randomly designated diary days. In case
two activities were carried out simultaneously, there is space in the diary
to record both, a main and a secondary (or parallel) activity. The third
recording domain is presence of other persons. Consequently, each recorded
episode in the diary is characterised by a main activity and possibly by a
secondary activity and by information on presence of other persons. A
temporal identifier carries information on the time and duration for the
episode. At the stage when the activities in the diaries are coded,
information on location, i.e. where the activity took place is inferred and
coded into a few different categories. This domain also contains information
on means of transportation.
The episode is a behavioural unit. The recording domains, one by one or
taken together in various combinations, offer insights in various aspects of
people’s behaviour. When the data is used for statistical description and
analysis of what people are doing, which activities they undertake, multiple
alternative approaches are offered. Which to choose depends on objectives 
on which aspects of behaviour, and hence which episodes correspond to the
particular interest.
Suppose the question at issue concerns having a meal, it might be quite
sufficient to select all episodes in the episode file for which the main
activity (the answer to the diary question ”What did you do?” or secondary
activity (“Did you do anything else?”) is having a meal. If the meal was
eaten in solitude or not, where it was eaten or whether some other activity
was going on at the same time, e.g. reading a newspaper is not relevant to
the question, so the main and secondary activity together might offer
necessary and sufficient information for an adequate classification of the
episode. If, however, we were to consider the main activity alone, we would
exclude circumstances where the diarist was both eating and watching
television, but gave priority to TV in the diary record; having a meal would
as a result be undercounted.
A second example. Some years ago it was reported in Swedish media that the
people in Sweden on average spent 2 minutes a day talking with children. The
basis for this was a figure that had been found in a statistical table
published in a report on the Swedish time use survey. The figure is in it
self correct but the interpretation of it is completely wrong.
The correct interpretation rather is: when a random sample, drawn from the
Swedish population (2064 years old) record in a time diary of the HETUS
kind which activities they undertake and how much time they devote to them (during
a randomly designated day), the result is that episodes of a total average
duration of two minutes have been described in words that clearly state
that the main activity was talking with children. This, however, does not
imply that no other talking with children took place. If one wants to
estimate the time people spend talking with their children, a different
approach is necessary. In principle, each episode in the episode file should
be analysed and classified according to whether or not talking with children
is likely to occur. For example, assume a respondent is the mother of a
child, the mother’s main activity is having a meal and the child is present,
no secondary activity is recorded, then it is more likely that the mother
talks with the child than that she does not. Hence, to estimate the time for
talking with children, all episodes in which it is likely that talking
occurs, need to be identified, the durations added and the mean calculated.
The information to make use of in order to find the relevant episodes, is
contained in the total of the recording domains, not just one of them. How
to make use of the information contained in the recording domains depends on
the purpose of the analysis. For certain purposes it is – of course –
sufficient to restrict the analysis to one or the other recording domain.
An example of a somewhat more intricate activity is childcare. The meaning
of the concept determines how to extract it from the diary record. If childcare
is defined as activities that directly involve and are directed to the
child, as feeding, putting a child to bed, changing nappies, etc. it might be
satisfactory to select episodes characterised by main activity codes that
indicate these particular activities. If, on the other hand, child care is
given a broader meaning, e.g. forming the child’s human and social capital,
then additional episodes have to be added. The recording domains, parallel
activities and “who with” will certainly have to be considered. And if the
concept is expanded further, to, say, custodial care, still more episodes
might have to be considered.
Figure 2 sets out some of the possible estimators of childcare. First, there
is the primary childcare time. The 2000/01 Swedish evidence suggests that
mothers in households with children up to the age of seven devote a little
more than two hours and the corresponding fathers a little more than one
hour per day to childcare as a primary activity.
Now add in childcare as a secondary activity, and the total rises to three
hours for mothers and one and a half hours for fathers. But of far greater
significance is the time that parents spend not engaged in explicit
childrelated activities, but still in the presence of their children.
If meals together with the child are included still one hour is added. If the
mothers´ free time activities with the child present are regarded as childcare
two more hours are added. And finally, if we regard housework with the child
present, we end up with eight hours childcare per day, four times as much as
the original 2 hours of primary activity childcare. For the fathers the
corresponding estimates increases from about 1 hour a day to a little more
than five hours.
Figure 2. Mean time for various sorts of childcare. Married or cohabiting
parents with small children, 06 years. Swedish population 2000/01.
Which of these is the appropriate base for estimating the extent of
nonmarket provision of childcare services? The primary activity alone is
clearly insufficient. But the total of child copresence time is, arguably,
excessive, particularly insofar as it may involve the copresence of both
parents with a single child. Again, the objective gives guidance.
The bottom line is: select all episodes that are relevant to the purpose.
The system offers such a possibility for the advanced users.
Differences in structure vs. behaviour
The interpretation of a difference in the mean time spent on one or
the other activity between for example some population groups and/or between
countries, is not always straightforward. A difference is not necessarily an
expression of differences in behaviour. The explanation could also be
differences in structure. Or a combination of both.
Assume there is a difference in the time use of married/cohabiting mothers
with small children (under 7 years) in two countries. In addition, assume
that there are differences in the composition of the population groups. In
one country the fertility rate is relatively higher and the mean age of
women at the first birth lower compared to the other country. As a
consequence the average age of the mothers are lower and the average number
of children are larger in one of the countries. If age and number of
children influence the time use, the result would differ between the
countries even if there is no difference in time use, given the same age of
the mothers and the same number of children. Hence, in this case there is no
difference in behaviour, only in the composition of the population groups.
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