Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
The Time Use Survey was implemented for the seventh time in Hungary: it provided a comprehensive examination of social stratification. The surveyed population consist of individuals aged from 10 to 84 living in private households. Data collection was conducted for 12 months. This time period was divided into four 13-week quarters. The sample was more than 9000 individuals in each quarter selected randomly using mathematical and statistical method. Half of the sample was a panel sample, and the other half was a cross-sectional sample. The panel subsample was included in the survey every quarter, whereas the cross-sectional sample changed every quarter and was included only once.
In each quarter, respondents were expected to complete one diary. Each respondent was assigned a predesignated diary day. If the predesignated day was not suitable, respondents were offered up to two alternative diary days, postponed by 7 or 14 days, provided that the replacement day was the same day of the week. The diary day was assigned to sampled individuals using a random but systematic procedure to ensure an even distribution of diary days across the reference year.
Compared with previous Hungarian Time Use Surveys, a methodological innovation of the survey was that respondents could participate either with the assistance of an interviewer or independently through an online questionnaire. To support this mixed-mode approach, all data collection was conducted electronically. Data were collected using either Computer-Assisted Web Interviewing (CAWI), or Computer-Assisted Telephone Interviewing (CATI).
Each sampled individual received an invitation letter by post, which included the following information: a unique identifier required for login, the website of the survey, access to the completion guidelines, the predesignated day and information about the incentive provided for participation. The data collection tool (software) used for the survey was developed by HCSO. During the data collection procedure, a smartphone app was not available, however an online interface was used. This was responsive also for mobile.
The survey had its own registration webface, where every sampled person could indicate their intention to participate by choosing from the following options: participate individually; participate with the assistance of an interviewer. They could also determine whether the designated day, or a „postponed diary” day were suitable for them to fill a diary. On this registration webface, respondents could also indicate if they did not wish to participate in the survey. The invitation letter had been sent approximately 10-14 days before their predesignated day. After that they could begin the registration and complete the household and individual questionnaires. The diary could only be filled out from the predesignated day onward, as permitted by the system. If there was no entry to the registration platform, an interviewer contacted the address in the days prior to the designated day. Even at this stage, respondents still had an opportunity to participate independently.
Instruments used in the survey were compliant with the Harmonized European Time Use Survey elements.
3.2. Classification system
See below.
3.2.1. Versions and breakdowns (level) of the classifications used for the data collection
Acronym
Version
Level
NACE
Rev. 2
3-digit
ISCO
ISCO 08
2-digit
ISCED
ISCED 2011
1-digit
NUTS
Other: HETUS ACL
2018 (2020 edition)
3.2.2. Deviations from ESS or international standards
3.3. Coverage - sector
Not requested.
3.4. Statistical concepts and definitions
Activity: The activities recorded in the time-use diary as free-text were later assigned codes, from the list containing more than 300 activity codes, which cover a large variety of activities.The codes were assigned according to the HETUS ACL classification. However, at the Hungarian analytical level, more detailed four-digit codes were used where neccessary.
Average day: An average day is the mean average of the days represented with the same weight within the data registration time-period.
Defined day: A day defined in advance, which the examined sample population has to provide time use diaries about. Those included in the panel subsample had four such days during the year. When selecting the days, a key consideration was their equal distribution across the entire year.
Diary: The time of the activities recorded in the diary could be specified freely, it was not limited to 10-minute intervals. This means that respondents were able to indicate the start and end times. In the diary, not only one but up to four secondary („parallel”) activities could be recorded (in order to ensure comparability with previous Hungarian Time Use Surveys). Respondents decided which is the main and which is the secondary activity. Based on the instructions (what they received before responding), the expectation was that the primary activity should be the one that lasted longer or from which the secondary activity followed. As a result of the self-administered and free-text format, in some cases multiple activities were entered into a single cell. During coding, these activities were separated using the same principles. For secondary activities, start and end times also had to be specified, and the ICT-related question likewise had to be answered. The activities were subsequently converted into 10-minute interval diaries. ICT use was coded as “yes” if a “yes” response was given for either the primary or any secondary activity. Diaries in which fewer than four activities were recorded are considered invalid.
Household: A household is defined as a person or persons who live in a property or part of it and who share at least some of the costs of living (e.g. meals, daily expenses).
Participation: Participation was possible either independently or with the assistance of an interviewer. Respondents received an invitation letter by post, which allowed them to log in to the online interface and they were able to begin recording the data. The online interface consisted of three main components: a registration questionnaire, household and individual questionnaire, and diary. In the registration questionnaire, respondents could indicate whether they wished to participate in the survey and, if so, whether they would do independently or with interviewer assistance. This option was available starting two weeks before their assigned day. Those who did not register or complete the registration questionnaire were contacted by an interviewer.The diary did not open before the assigned day and could not be completed for an earlier date.
3.5. Statistical unit
Individuals aged 10-84 years living in private households.
3.6. Statistical population
See below.
3.6.1. Main characteristics of the survey population
The target population does not include individuals who are younger or older than the target population, those who do not live in private households, or those living in communal accommodation or institutions, such as military facilities, health institutions, residental care homes, nursing homes, and prisons.
3.7. Reference area
Data collection was carried out throughout the entire territory of Hungary, covering more than 240 settlements, all counties, and all districts of the capital city.
3.8. Coverage - Time
From April 2024 to April 2025.
3.9. Base period
Not applicable.
Daily average allocated time of population
Proportion of those carrying out activities
Allocated time of those carrying out activities
The data collection period covered a full year, 12 months, and 365 days. It was divided into four equal quarters, each consisting of 13 weeks. These quarters were independent units. In the first three quarters, the sample included 9,163 individuals, while in the fourth quarter it included 9,162 individuals. Half of the sample (4581 respondents) formed a panel subsample. Respondents in the panel subsample were included in the sample every quarter, whereas the other half of the sample (the cross-sectional subsample) changed in every quarter and participated only once. There was no requirement to fill a diary for both weekdays (Monday to Friday) and weekends (Saturday, Sunday). Respondents were required to fill out one diary in a quarter.
6.1. Institutional Mandate - legal acts and other agreements
Information on this concept is provided in the sub-concepts 6.1.1 and 6.1.2.
6.1.1. At European level
The current round of the harmonised European time use survey (HETUS) data collection has been carried out in the spirit of multi-national and multi-agency cooperation across Europe, in the form of an informal ’gentlemen's agreement’.
6.1.2. At National level
Act CLV of 2016 on Official Statistics
Government Decree 184/2017 (VII.15.) on implementing Act CLV on Official Statistics
Government Decree 388/2017 (XII.15.) on the Mandatory Reporting of the National Statistical Data Collection Program
6.2. Institutional Mandate - data sharing
The microdata file is available in the HCSO Safe Centre. Data requests are processed in accordance with the HCSO's data release policy.
7.1. Confidentiality - policy
Hungarian Act on statistics (CLV/2016) describes the confidentiality requirements for this survey. In the process of statistical data collection, processing and analysis and dissemination of statistical information, Hungarian Central Statistical Office fully guarantees the confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality policy of the Hungarian Central Statistical Office.
7.2. Confidentiality - data treatment
HCSO ensures confidentiality for all the data reported by data providers and the exclusive use of the data for statistical purposes. We disseminate only aggregated data in full compliance with the rules of confidentiality. Researchers have access to de-identified data sets and to anonymised microdata for scientific purposes with appropriate legal and methodological guaranties in place. As for the employees, they can work with datasets in their competence with registered and controlled access rights. For details see the information on confidentiality for data providers on the website of HCSO.
8.1. Release calendar
The dates of analyses, publications, summary tables, and the release of the microdata file are included in the release calendar.
The summary tables and the publication are available free of charge and openly to all users without registration. The microdata file is accessible through the HCSO Safe Centre.
The data are published within one year after the completion of data collection. The survey is conducted approximately every 10-15 years.
10.1. Dissemination format - News release
Not available.
10.2. Dissemination format - Publications
Data visualization of the results is available on the official website.
10.3. Dissemination format - online database
Summary tables containing preliminary data have been published on the official website of the Hungarian Central Statistical Office.
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
The anonymised Hungarian TUS microdata file is available for scientific purposes in the HCSO Safe Centre (further information on the website).
Summary tables, data visualisations, and a methodological description are available in English on the official website.
In addition, the activity coding list used in the survey and the related explanatory documents are available only in Hungarian on the website.
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
User-oriented quality reports on statistical domains are prepared in the framework of methodological documentation and are published as meta-information on the HCSO website.
11.1. Quality assurance
The HCSO Quality Policy lays out the principles and commitments related to the quality of statistics. The document is consistent with the goals set out in the Mission and Vision statements and with the principles of the European Statistics Code of Practice and is publicly available on the HCSO website.
Also, HCSO together with the member-organisations of the Hungarian Official Statistical Service created a National Statistics Code of Practice based on the European Statistics Code of Practice (currently the National Statistics Code of Practice is available only in Hungarian on the HCSO website).
11.2. Quality management - assessment
The survey provides essential information that fills important data gaps across several areas and is considered relevant by a wide range of user groups, with considerable interest in its use for various purposes. Its sampling design and consistent methodology ensure comparability over time and across geographical areas, while the online response rate exceeded expectations, indicating strong reliability.
12.1. Relevance - User Needs
This survey's purpose is to support the development of family policy, working time policy, and national accounts, in particular with regard to household production, and to provide information on travel behaviour and participation in cultural and leisure activities. The most important users are government organizations (ministries) and journalists, university students, PhD students, researchers writing their thesis.
12.2. Relevance - User Satisfaction
Below the summary tables and publication, users can rate the usefulness and interpretability of the content on a scale from 1 to 5, and may also provide their comments and development suggestions regarding the content they have viewed. When providing feedback, users must classify themselves into one of the following user groups: public administration, public sector; business, competitive sector; non-profit organization, church, political party; researchers, PhD student; educational institution, student, lecturer; media, press; international organization; private individual.
12.3. Completeness
These questions were not asked by the country: DDV6, DDV7, DDV8A, DDV8B, HHQ1, HHQ2, IND14, IND38.
12.3.1. Data completeness - rate
Not requested.
13.1. Accuracy - overall
The sample design and weighting scheme serve data collection and analysis needs. The estimated effective sample size (7776) exceeds the minimum set in Regulation (EU) 2019/1700 by far. The high non-response rate may indicate risk of bias which was intended to get reduced by weigh adjustment.
13.2. Sampling error
Information is provided in the following sub-concepts 13.2.1-13.2.3.
13.2.1. Sampling error - indicators
See below.
13.2.2. Sampling error - proportion and confidence interval
Parameter of interest (p̂)
Number of respondents - n
Standard error for p̂
95% confidence interval for p̂: Lower
95% confidence interval for p̂: Upper
Percentage of population aged 15 and over spending daily on average more than 10 % of time working in paid work
(weighted)
Number of individuals completed at least 1 diary day
(unweighted)
0.41936
6742
0.005596
0.40839184
0.43032816
13.2.3. Sampling error - method used for the variance (SE) estimation
According to ratio estimator and calibration method, linearisation method was applied. Technically, SAS Surveymeans procedure was used with STRATA and CLUSTER statements to reflect sample design elements (stratification and two-stage sampling) in variance estimation.
13.3. Non-sampling error
Information on this concept is provided in the sub-concepts 13.3.1-13.3.5.
13.3.1. Coverage error
The frame is the population register (individuals with registered address) which is continuously updated. For the selection of TUS sample, the frame of January in 2025 was used. The under-coverage is ~0.6% (individuals with no registered address).
13.3.1.1. Over-coverage - rate
0.0326
13.3.1.2. Common units - proportion
Not applicable.
13.3.2. Measurement error
During the survey, in some cases the data recording software did not function properly despite the default settings. In a small number of cases, respondents had to answer questions that, according to the skip logic rules, they should not have had access to.
There was no data loss. In addition:
we used CAPI mode, and the entire programmed questionnaire was tested
validation of answers was in place, with a possibility to correct or specify given answers during the interview
every interviewer got guidelines for the questionnaire
control of interviewers for quality assurance was performed
13.3.2.1. Questionnaire design and testing
When designing the questionnaire, the primary considerations were the experiences from the previous time-use survey pilot and the requirements of HETUS. The developed questionnaire underwent intensive and qualitative testing, during which we assessed how clear the questions were and how accurately respondents were able to provide their answers. Corrections have been made to facilitate easier completion. Furthermore, data collection tools underwent cognitive testing.
13.3.2.2. Interviewer training
Interviewer training was conducted in person both at the central office and at regional offices. Interviewers received an interviewer manual in advance, prior to the training. During the training, they were provided with all essential information and had the opportunity to ask questions. At the end of the training, they were required to fill a test diary, and to complete a test, successful completion of which was a prerequisite for participating in the survey as an interviewer.
13.3.2.3. Proxy interview rates
There was no proxy interview.
13.3.3. Non response error
At personal level the overall weighted unit non-response rate is 0.67. Non-respondents can be characterised by area and individual level data available from sampling frame. The remarkable characteristics are below.
Region HU12 is subject to non-response the most (76%). Western region HU22 is also far above the average with non-response rate 72%, while in other regions it varies in the range 59-69%.
Besides, it can be stated that males (with non-response rate 69%) and the younger adults (aged 20-24 with 74% and 25-34 with 73%) are harder to reach.
Data collection was hard to start yielding the first five months below the average. As for the weekdays, Mondays were the hardest day to reach sample persons.
This high non-response rate may indicate risk of bias which was intended to get reduced by weigh adjustment involving variables related to non-response mentioned below (see S.18.5.3.).
13.3.3.1. Unit non-response - rate
Not available.
13.3.3.1.1. Reasons for non-response
Non-contact: the interviewer did not start data collection at the designated address; the person had moved; was at an unknown location; had passed away; was not reachable despite three attempts; the address could not be identified, was inaccessible, or unoccupied.
Inability: non-response due to inability to respond or language difficulties.
Refusal: refusal to answer (personally, by phone, or via another person).
Other: the respondent began completing the survey independently but did not finish it; the interviewer did not finish data collection; technical problem.
13.3.3.1.2. Number of households in the gross sample according to the final results of the survey
Not available.
13.3.3.1.3. Characteristics of non-respondents
In the cases of the fieldwork monitoring, the non-respondents characteristics were the following: In 43,3% of cases, refused to answer (personally, by phone, or via another person). In 20,6% of cases, the interviewer either did not complete or did not start data collection at the designated address; irregularity was identified during verification process. In 21,8% of cases, the person was unavailable (had moved, was at an unknown location, had passed away, was not reachable despite three attempts); or was unable to respond or language difficulties. In 12,9% of cases, respondents agreed to participate and started completing the survey, but did not finish it, or the responses were subsequently invalidated based on quality criteria (e.g. amount of recorded activities in the diary). In 1,4% of cases, the address could not be identified, was inaccessible, or unoccupied.
13.3.3.1.4. Efforts to reduce non-response
When a phone number was available, respondents were contacted by phone and informed about how they could complete the survey independently.
Enhanced supervision of interviewers.
13.3.3.1.5. Adjustment of weights in order to reduce non-response
Please refer to S.18.5.3
13.3.3.1.6. Other comments regarding non-response errors
We do not have other comment regarding non-response.
13.3.3.1.7. Replacement of non-responding households (substitution)
Substitution rate
Rate
i.e. Number of substitute households successfully interviewed/Achieved sample size
Not applicable.
13.3.3.1.8. Description of the substitution
There was no substitution for the selected individuals.
13.3.3.1.9. Qualitative assessment of the bias associated with unit non-response
Not available.
13.3.3.2. Item non-response - rate
Non-response can be due to refusal (-7) or not available (-9). As for the Hungarian recording, if the answer from the questionnaire could not be transferred to the shortened questionnaire it received a „not available (-9)” value. The three highest non-response rate are observed for the following questions:
IND16 – 32%
HHQ9_1 – 21%
IND20 – 12.4%
13.3.3.2.1. Variables most subject to item non-response
Equivalised net current monthly household income
Able to start work in 2 weeks
Level of current education or training activity
13.3.4. Processing error
Data entry control was done via CAPI. To improve reliability, the coding of the activities was partially automated, and all manually coded cases were reviewed.
13.3.5. Model assumption error
No model was used to handle errors or for estimation.
14.1. Timeliness
Data collection was completed in April 2025. The preliminary data, as summary tables (STADAT) were first published on the official website in October 2025. The data was delivered to Eurostat in June 2026.
14.1.1. Time lag - first result
Not applicable.
14.1.2. Time lag - final result
Not applicable.
14.2. Punctuality
The fieldwork has been completed as expected in April 2025. The data structure required by Eurostat differed significantly from the Hungarian structure, which resulted in a longer-than-expected data transmission process. As a consequence, the data were submitted 14 months after the end of the data collection period.
14.2.1. Punctuality - delivery and publication
Not requested.
15.1. Comparability - geographical
NUTS2 region was a stratification variable in the TUS sample design. Naturally, region is always a predictor in weighting. Finally, the calibration used regional level population control totals. In this sense each regional subsamples are equivalent. Clearly, regional sample sizes differ and different regional non-response might have some effect on comparability.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
Comparable, time-disrupting factors did not play a role.
15.2.1. Length of comparable time series
Not requested.
15.3. Coherence - cross domain
In TUS weighting, the calibration population control totals came from the same population projection that is used in other houselhold surveys (e.g. LFS). No actions were taken to ensure other distributions to coincide.
15.3.1. Coherence - sub annual and annual statistics
Not applicable.
15.3.2. Coherence - National Accounts
Not requested.
15.4. Coherence - internal
In the panel subsample, respondents at the second wave completed a shortened questionnaire in which many questions were not asked in order to reduce the respondent burden. Some background variables were carried over from the first completed questionnaire. For example, respondents who reported at the first wave that they were not working were not asked in the shortened questionnaire why they were not working. If at the first questionnaire a respondent indicated that they were working, in the shortened questionnaire they had no opportunity to report that they were no longer working, even if their employment status had changed.
Information on this concept is provided in the sub-concepts 16.1-16.4.
16.1. Costs of the survey
The total cost of implementing the 2024 Hungarian TUS, excluding staff time at the Central Statistical Office, is estimated at approximately €625 thousand. A substantial share of expenditure was attributable to the direct costs of fieldwork (approximately €240 thousand). Expenditure on incentives designed to improve response rates amounted to nearly €335 thousand, while other costs, including communication, postal services, and printing, totalled €50 thousand.
16.2. Average time used for answering the survey questionnaires (in minutes)
30-40 minutes, based on cognitive tests
16.3. Average time used to fill in the diary (in minutes)
40-50 minutes, based on cognitive tests
16.4. Measures taken to reduce the cost and burden of the survey
Possibility to complete independently via electronic devices. Respondents were encouraged to participate online. The respondents included in the panel subsample completed a shortened questionnaire starting from ther second completion onward, for every subsequent completion.
17.1. Data revision - policy
No such policy is applied.
17.2. Data revision - practice
No such policy is applied.
17.2.1. Data revision - average size
Not applicable.
18.1. Source data
Information on sampling design, sampling frame and size is available under the full metadata concepts 18.1.1-18.1.3.
18.1.1. Sampling frame
Type
Name of data source used for building the sampling frame
Population census
Population register
Personal Data and Address Register
Household register
Dwelling register
List of phone numbers
If it was available, yes
Postcode address file
Another survey sample
Other
18.1.2. Sampling design of the survey
See below.
18.1.2.1. Sampling design(s)
Type
Description of Sampling Design
Simple random sampling
Systematic sampling
Stratified sampling
Cluster sampling
Other
22908 individuals were selected in 264 localities (PSUs).
The largest 90 Primary Sampling Units (PSUs) are certainty PSUs. The rest of PSUs are stratified by NUTS2 region, size, average income per capita and the proportion of those that spend daily over 20 minutes with going to school or work (census data). PSUs are selected with pps (Probability Proportional to Size) within strata. Individuals within PSU are selected with systematic random selection from the frame list sorted by date of birth. When calculating sample size different expected response rates by the type of localities were taken into account.
18327 of the sample persons constitute the cross-sectional subsample, requiring one diary from each of them. The rest of sample persons (4581) represent the panel subsample, requiring four diaries from each of them, one in each quarter. The cross-sectional and panel subsamples are equivalent differing by the sample size only.
36651 diary days were selected with some systematic selection, yielding a uniform distribution of diary days overall and within specific domains of the sample as well.
18.1.2.2. Ultimate sampling unit(s)
Individuals
18.1.2.3. Oversampling of specific populations
No subpopulation was oversampled. Only, when determining the final sample size, different response rates by the type of locality were taken into account.
18.1.2.4. Assumptions used for determining the sample size
The sampling design was developed taking into account both the required level of Precision Requirements to the Regulation (EU) 2019/1700 and the need to maintain comparability with previous survey waves.
18.1.3. Sample size
Sample size
Number
Gross sample size
i.e. initial sample size= responding units + non-responding units (these two groups make up the group of eligible units) + units with unknown eligibility (e.g. because they are not able to be reached/ contacted), + ineligible units.
i.e. net sample size= Gross sample size - units with unknown eligibility – ineligible units
20439 individuals
Achieved sample size = Total number of households which were successfully surveyed (interviews+diary)
10955 diaries from 7141 individuals
18.2. Frequency of data collection
Approximately every 10-15 years.
18.3. Data collection
See below.
18.3.1. Data collection method used
Mixed mode
18.3.2. Mode(s) and instruments for data collection: household and individual questionnaire
Interview
Specify Yes or No if used
% of completed household interviews
Paper assisted personal interview (PAPI)
no
Computer-assisted personal interview (CAPI)
yes
8%
Computer assisted telephone interview (CATI)
yes
43%
Computer assisted web-interview (CAWI)
yes
49%
Smart mode (e.g. smartphone app)
no
Other (e.g. administrative data).
no
18.3.3. Mode(s) and instruments for data collection: time use diary
Diary
Specify Yes or No if used
% of completed diaries
Paper diary
no
Computer based non online diary
no
Online web diary
yes
100%
Mobile based diaries (Smartphone apps, etc.)
no
18.3.4. Variables completed from an external source
There was no completion from an external source.
18.4. Data validation
Prior to the dissemination of the national data, the data quality and consistency were checked.
18.5. Data compilation
Imputation
Due to the self-administered nature of the survey, responses were not checked during data collection, and as a result some basic activities were occasionally not reported. One such example is eating. In diaries where eating was not recorded as either a primary or secondary activity, a lunch episode was imputed retrospectively. The timing and duration of the imputed lunch episode were based on the average timing and duration of lunch recorded by the population of the same age group. In these cases, the activity originally recorded during the overlapping time period was finished at the average lunch start time, the imputed lunch activity was inserted, and after lunch the originally recorded activity was resumed.
Some diaries did not cover the full 24-hour period. When the missing time did not exceed 3 hours (180 minutes), the gaps were coded as 999 “other, unspecified activity”. Diaries with more than 3 hours of missing time were considered invalid and excluded from further analysis. An exception was made when recording stopped at the end of the day. In such cases, the incomplete diary was supplemented with a Sleep activity to complete the 24-hour period. Additionally, when sleep was the last recorded activity of the day, but ended at 11.59 PM; it was extended to 4:00 AM.
Data editing and coding process
Respondents could indicate one or more modes of transport for each travel-related activity, multiple options could be selected. When multiple modes were reported, one mode was selected according to the following rules:
If walking was sleected together with another mode of transport, the other mode was assigned. Similarly, if one of the selected options was „other, not listed”, then the other mode was selected. When only walking and „other, not listed” were reported, then walking was selected. Furthermore, the chosen mode of transportation was determined by the circumstances of the activity, related activities (e.g. refueling), as well as the device specified for previous or later transportation recordings.
If a question was not asked or answered in the shortened questionnaire, the answer from the first wave questionnaire was used instead.
For the supplementary question on ICT device use, the response was coded as “yes” even if the device was used only during secondary activity.
To ensure comparability with the previous Hungarian TUS, multiple secondary activities could be recorded. If several secondary activities were recorded, the one that lasted the longest was included in the database submitted to Eurostat. If multiple activities lasted the same amount of time, the first activity recorded was retained.
Because of the data collection method, respondents entered their activities in free text rather than selecting from a predefined list. Consequently, the reported activities were not automatically assigned a code; they received a code during the coding process. In the first stage of coding, the most frequently reported and clearly identifiable activities were assigned codes automatically using Excel functions. Activities that could not be coded using this method were coded manually. For some activities, assigning the correct code also required information from supplementary questions. For example, a recorded "conversation" was coded as 511 if it involved a household member and as 519 if it involved a non-household member.
In many cases respondents recorded „shopping” without furher details. In accordance with the Hungarian coding system these activities were assigned code 369.
In some cases, respondents recorded multiple activities within a single diary cell. During the coding process, these activities were separated and evaluated individially. When a clear casual relationship could be identified between the activities, the activity from which the other activity resulted was retained as the main activity. If no such relationship could be established, the first activity entered by the respondent was retained as the main activity, while the remaining activities were recorded as secondary activities. Duration of each secondary ectivity was assumed to be equal to the duration of the corresponding main activity.
For selected indicators, internal consistency check were conducted by comparing responses across related variables. For example, cases in which respondents reported an unusually high level of educational attainment relative to their age were flagged as potential inconsistencies. Such cases were identified through comparisons between respondents' age and reported educational attainment.
18.5.1. Imputation - rate
0,019029
18.5.2. Method applied to correct for 'item non-response'
Methods
Specify Yes or No if used
Simple imputation (deterministic) method
yes
Simple imputation (stochastic) method
no
Multiple imputation approach
no
Other
no
18.5.3. Calculation of weighting factors and weight adjustments
Design weights are defined by the sample design. Design weights were adjusted in two major steps: weighting for non-response and calibration to population control totals.
Weighting to correct for non-response was carried out separately in the panel and cross-sectional subsamples. The logistic regression model to predict respose propensity used area, dwelling and individual level covariates available from frame as well as type of diary days.
To calibrate the sample, iterative raking method was applied. Diary and personal weights were calculated within one calibration process, both weights were bounded. At NUTS2 regional level the following control totals were used: population by gender and age categories (10-14, 15-19, 20-24, 25-34, 35-44, 45-54, 55-64, 65-69, 70-74, 75-84); population by degree of urbanisation; diary days by months; diary days by type of the day.
18.6. Adjustment
Not applicable.
18.6.1. Seasonal adjustment
Not applicable.
The Hungarian coding system is four digits deep. When the database was created, all activities were assigned three-digit codes. As a result, it sometimes happens that the primary and secondary activity codes are identical at three digits, even though they differ at the four-digit level.
The Time Use Survey was implemented for the seventh time in Hungary: it provided a comprehensive examination of social stratification. The surveyed population consist of individuals aged from 10 to 84 living in private households. Data collection was conducted for 12 months. This time period was divided into four 13-week quarters. The sample was more than 9000 individuals in each quarter selected randomly using mathematical and statistical method. Half of the sample was a panel sample, and the other half was a cross-sectional sample. The panel subsample was included in the survey every quarter, whereas the cross-sectional sample changed every quarter and was included only once.
In each quarter, respondents were expected to complete one diary. Each respondent was assigned a predesignated diary day. If the predesignated day was not suitable, respondents were offered up to two alternative diary days, postponed by 7 or 14 days, provided that the replacement day was the same day of the week. The diary day was assigned to sampled individuals using a random but systematic procedure to ensure an even distribution of diary days across the reference year.
Compared with previous Hungarian Time Use Surveys, a methodological innovation of the survey was that respondents could participate either with the assistance of an interviewer or independently through an online questionnaire. To support this mixed-mode approach, all data collection was conducted electronically. Data were collected using either Computer-Assisted Web Interviewing (CAWI), or Computer-Assisted Telephone Interviewing (CATI).
Each sampled individual received an invitation letter by post, which included the following information: a unique identifier required for login, the website of the survey, access to the completion guidelines, the predesignated day and information about the incentive provided for participation. The data collection tool (software) used for the survey was developed by HCSO. During the data collection procedure, a smartphone app was not available, however an online interface was used. This was responsive also for mobile.
The survey had its own registration webface, where every sampled person could indicate their intention to participate by choosing from the following options: participate individually; participate with the assistance of an interviewer. They could also determine whether the designated day, or a „postponed diary” day were suitable for them to fill a diary. On this registration webface, respondents could also indicate if they did not wish to participate in the survey. The invitation letter had been sent approximately 10-14 days before their predesignated day. After that they could begin the registration and complete the household and individual questionnaires. The diary could only be filled out from the predesignated day onward, as permitted by the system. If there was no entry to the registration platform, an interviewer contacted the address in the days prior to the designated day. Even at this stage, respondents still had an opportunity to participate independently.
Instruments used in the survey were compliant with the Harmonized European Time Use Survey elements.
31 August 2026
Activity: The activities recorded in the time-use diary as free-text were later assigned codes, from the list containing more than 300 activity codes, which cover a large variety of activities.The codes were assigned according to the HETUS ACL classification. However, at the Hungarian analytical level, more detailed four-digit codes were used where neccessary.
Average day: An average day is the mean average of the days represented with the same weight within the data registration time-period.
Defined day: A day defined in advance, which the examined sample population has to provide time use diaries about. Those included in the panel subsample had four such days during the year. When selecting the days, a key consideration was their equal distribution across the entire year.
Diary: The time of the activities recorded in the diary could be specified freely, it was not limited to 10-minute intervals. This means that respondents were able to indicate the start and end times. In the diary, not only one but up to four secondary („parallel”) activities could be recorded (in order to ensure comparability with previous Hungarian Time Use Surveys). Respondents decided which is the main and which is the secondary activity. Based on the instructions (what they received before responding), the expectation was that the primary activity should be the one that lasted longer or from which the secondary activity followed. As a result of the self-administered and free-text format, in some cases multiple activities were entered into a single cell. During coding, these activities were separated using the same principles. For secondary activities, start and end times also had to be specified, and the ICT-related question likewise had to be answered. The activities were subsequently converted into 10-minute interval diaries. ICT use was coded as “yes” if a “yes” response was given for either the primary or any secondary activity. Diaries in which fewer than four activities were recorded are considered invalid.
Household: A household is defined as a person or persons who live in a property or part of it and who share at least some of the costs of living (e.g. meals, daily expenses).
Participation: Participation was possible either independently or with the assistance of an interviewer. Respondents received an invitation letter by post, which allowed them to log in to the online interface and they were able to begin recording the data. The online interface consisted of three main components: a registration questionnaire, household and individual questionnaire, and diary. In the registration questionnaire, respondents could indicate whether they wished to participate in the survey and, if so, whether they would do independently or with interviewer assistance. This option was available starting two weeks before their assigned day. Those who did not register or complete the registration questionnaire were contacted by an interviewer.The diary did not open before the assigned day and could not be completed for an earlier date.
Individuals aged 10-84 years living in private households.
See below.
Data collection was carried out throughout the entire territory of Hungary, covering more than 240 settlements, all counties, and all districts of the capital city.
The data collection period covered a full year, 12 months, and 365 days. It was divided into four equal quarters, each consisting of 13 weeks. These quarters were independent units. In the first three quarters, the sample included 9,163 individuals, while in the fourth quarter it included 9,162 individuals. Half of the sample (4581 respondents) formed a panel subsample. Respondents in the panel subsample were included in the sample every quarter, whereas the other half of the sample (the cross-sectional subsample) changed in every quarter and participated only once. There was no requirement to fill a diary for both weekdays (Monday to Friday) and weekends (Saturday, Sunday). Respondents were required to fill out one diary in a quarter.
The sample design and weighting scheme serve data collection and analysis needs. The estimated effective sample size (7776) exceeds the minimum set in Regulation (EU) 2019/1700 by far. The high non-response rate may indicate risk of bias which was intended to get reduced by weigh adjustment.
Daily average allocated time of population
Proportion of those carrying out activities
Allocated time of those carrying out activities
Imputation
Due to the self-administered nature of the survey, responses were not checked during data collection, and as a result some basic activities were occasionally not reported. One such example is eating. In diaries where eating was not recorded as either a primary or secondary activity, a lunch episode was imputed retrospectively. The timing and duration of the imputed lunch episode were based on the average timing and duration of lunch recorded by the population of the same age group. In these cases, the activity originally recorded during the overlapping time period was finished at the average lunch start time, the imputed lunch activity was inserted, and after lunch the originally recorded activity was resumed.
Some diaries did not cover the full 24-hour period. When the missing time did not exceed 3 hours (180 minutes), the gaps were coded as 999 “other, unspecified activity”. Diaries with more than 3 hours of missing time were considered invalid and excluded from further analysis. An exception was made when recording stopped at the end of the day. In such cases, the incomplete diary was supplemented with a Sleep activity to complete the 24-hour period. Additionally, when sleep was the last recorded activity of the day, but ended at 11.59 PM; it was extended to 4:00 AM.
Data editing and coding process
Respondents could indicate one or more modes of transport for each travel-related activity, multiple options could be selected. When multiple modes were reported, one mode was selected according to the following rules:
If walking was sleected together with another mode of transport, the other mode was assigned. Similarly, if one of the selected options was „other, not listed”, then the other mode was selected. When only walking and „other, not listed” were reported, then walking was selected. Furthermore, the chosen mode of transportation was determined by the circumstances of the activity, related activities (e.g. refueling), as well as the device specified for previous or later transportation recordings.
If a question was not asked or answered in the shortened questionnaire, the answer from the first wave questionnaire was used instead.
For the supplementary question on ICT device use, the response was coded as “yes” even if the device was used only during secondary activity.
To ensure comparability with the previous Hungarian TUS, multiple secondary activities could be recorded. If several secondary activities were recorded, the one that lasted the longest was included in the database submitted to Eurostat. If multiple activities lasted the same amount of time, the first activity recorded was retained.
Because of the data collection method, respondents entered their activities in free text rather than selecting from a predefined list. Consequently, the reported activities were not automatically assigned a code; they received a code during the coding process. In the first stage of coding, the most frequently reported and clearly identifiable activities were assigned codes automatically using Excel functions. Activities that could not be coded using this method were coded manually. For some activities, assigning the correct code also required information from supplementary questions. For example, a recorded "conversation" was coded as 511 if it involved a household member and as 519 if it involved a non-household member.
In many cases respondents recorded „shopping” without furher details. In accordance with the Hungarian coding system these activities were assigned code 369.
In some cases, respondents recorded multiple activities within a single diary cell. During the coding process, these activities were separated and evaluated individially. When a clear casual relationship could be identified between the activities, the activity from which the other activity resulted was retained as the main activity. If no such relationship could be established, the first activity entered by the respondent was retained as the main activity, while the remaining activities were recorded as secondary activities. Duration of each secondary ectivity was assumed to be equal to the duration of the corresponding main activity.
For selected indicators, internal consistency check were conducted by comparing responses across related variables. For example, cases in which respondents reported an unusually high level of educational attainment relative to their age were flagged as potential inconsistencies. Such cases were identified through comparisons between respondents' age and reported educational attainment.
Information on sampling design, sampling frame and size is available under the full metadata concepts 18.1.1-18.1.3.
The data are published within one year after the completion of data collection. The survey is conducted approximately every 10-15 years.
Data collection was completed in April 2025. The preliminary data, as summary tables (STADAT) were first published on the official website in October 2025. The data was delivered to Eurostat in June 2026.
NUTS2 region was a stratification variable in the TUS sample design. Naturally, region is always a predictor in weighting. Finally, the calibration used regional level population control totals. In this sense each regional subsamples are equivalent. Clearly, regional sample sizes differ and different regional non-response might have some effect on comparability.
Comparable, time-disrupting factors did not play a role.
