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.
Road freight data collection consists of three datasets with quarterly periodicity and mandatory data collection: 1. Vehicle related variables dataset for a sample of road good motor vehicles contain, among others, indication about the type and age of the vehicle (from national vehicle register,) the economic activity of the owner of the vehicle (from national business register), the total kilometres loaded or empty. 2. Journey related variables dataset which contain, among other indications about weight of goods, regions of loading and unloading, distance driven, and tonne-kilometres performed during a journey 3. Goods related variables dataset which contain among others the type of goods transported and their weight and distance travelled, regions of loading and unloading.
3.2. Classification system
Statistics on carriage of goods by road apply the following statistical classifications:
The optional variable type of cargo follows the Classification of Cargo Types of UNECE (United Nations, Economic Commission for Europe - codes for types of cargo, packages and packaging materials, Recommendation 21 adopted by the Working Party on Facilitation of International Trade Procedures, Geneva, March 1986).
3.3. Coverage - sector
Statistics produced on the basis of Regulation (EU) No 70/2012 cover the road freight transport operations by heavy goods vehicles registered in the Sweden in all economic sectors. That is, no business sector (NACE) is excluded in the definition of the population of vehicles.
For example, both commercial road freight transport (NACE Rev.1.1 I6024; NACE Rev.2 H494), referred to as "Hire or reward" is included, as well as Road freight transport by vehicles owned by companies classified in other classes than professional road freight transport. This kind of transport is identified as "Own account" road freight and it covers transport operations by manufacturing industry, construction, trade and other companies.
A goods road motor vehicle is any single road transport vehicle (lorry), or combination of road vehicles, namely road train (lorry with trailer) or articulated vehicle (road tractor with semi-trailer), designed to carry goods
National transport is Road transport between two places (a place of loading and a place of unloading) located in the same country by a vehicle registered in that country.
International transport is Road transport between two places (a place of loading and a place of unloading) in two different countries and cabotage by road. It may involve transit through one or more additional country or countries.
Cross trade is International road transport between two different countries performed by a road motor vehicle registered in a third country.
Transit is any loaded or empty road motor vehicle, which enters and leaves a country at different points by whatever means of transport, provided the total journey within the country is by road and that there is no loading or unloading in the country.
Goods carried by road are any goods moved by goods vehicle
Place of loading/unloading is the geographical area for loading/unloading coded according to NUTS3-level
Place of loading/unloading of a goods road vehicle on another mode of transport
Place of loading (of the goods road transport vehicle on another mode of transport): The place of loading is the first place where the goods road motor vehicle was loaded on to another mode of transport (usually a ship or a rail wagon).
Place of unloading (of the goods road transport vehicle from another mode of transport): The place of unloading is the last place where the goods road motor vehicle was unloaded from another mode of transport (usually a ship or a rail wagon).
3.5. Statistical unit
The reporting unit for road freight transport statistics is the goods road transport vehicle.
A selected goods road vehicle report all basic transport operations (consignments) during the reference week. This information is transformed to journeys which constitutes the statistical unit used for estimating population parameters such as total tonnes, tonne-kilometres and vehicle-kilometres.
3.6. Statistical population
The target population is all goods transports on public roads carried out by Swedish registered trucks / tractors with a load capacity of 3.5 tonnes or more during the reference period. Other exclusion criteras regarding vehicles are:
Vehicles 30 years and older and vehicles that are not operating.
Some body type codes for which transport of goods is not possible, such as ambulances, hearses, breakdown lorries, fire engines (military vehicles are not included in the Vehicle Register).
Vehicles owned by companies that are not registered in the central register of corporations.
The population size of vehicles is around 60 000 to 70 000 vehicles. Since the population is large a (random) sample of vehicles is drawn each quarter.
3.7. Reference area
The data provided are goods vehicles registered in Sweden.
3.8. Coverage - Time
Quarterly data from year 2000.
In 2014 a break in the time series occurred. False reporting of no activity had for some time been a problem in Sweden. False reporting means that for a certain vehicle the reply to the questionnaire is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. In 2014 a new method to account for false reporting of no activity was introduced. This lead to a raise in the estimates with about 30 percent. Recalculated values and double time-series are available from reference year 2012-2014, to bridge the time series gap.
3.9. Base period
Not applicable.
Data are collected regarding each basic transport operation (BTO) during a selected vehicle. The metric variables are loaded goods in kg and driven distance in km. The variable tonne-km is a derived variable, hence the vehicle owner does not need to register ton-km. Regarding number of journeys this is obtained when BTO:s are converted to journeys.
The statistics presented in tables are in tonnes or thousands of tonnes for loaded goods, km or thousands of km for driving distance, in millions of tonne-km and in thousands of journeys.
The reference period is quarter (13 weeks), i.e. the data delivered to Eurostat can be used to estimate parameters for a quarter. If four quarters are added together the statistics can be presented regarding a year (52 weeks).
6.1. Institutional Mandate - legal acts and other agreements
National level:
For statistics included in Sweden's official statistics (SOS), special rules for quality and availability apply, see the act (2001:99) and the regulation (2001:100) on the official statistics as well as Statistics Sweden's regulations (SCB-FS 2016:17) on quality for the official statistics.
It is mandatory to reply to the questionnaire according to law 2001:99 and regulation 2001:100 regarding Official Statistics and also according to Transport Analysis (NSI) regulation (TRAFAFS 2014:2)
Transport Analysis (NSI) publish estimates of totals of tonnes, vehicle-kilometres and tonne-kilometres and also divided into several subgroups (domains) on a quarterly basis. Microdata or specialized tables to researchers and other users is provided by Transport analysis after approved secrecy examination and / or disclosure control.
Transport analysis obtains quarterly data about the vehicles and the vehicle charactertics from The Swedish Transport agency and driven kilomwetres from vehicles in the Swedish business register from Statistics Sweden.
From Eurostat :
Eurostat submits annually semi-aggregated data (data exchange tables, see Commission Regulation (EU) No 202/2010 amending the Commission Regulation (EC) 6/2003) back to the reporting countries so that they can compile the total road freight transport on their national territories, including the operations by national hauliers and also those of all other reporting countries.
These data exchange tables include more detailed breakdowns than the publicly available tables. They also include, for each value, the information on the number of observations that the estimates are based on. In this way, the reporting countries can estimate the reliability of results that they aggregate from the data exchange tables.
7.1. Confidentiality - policy
National level:
For production and publication of statistics in Sweden, public authorities are bound to secrecy according to chapter 24, 8 § in the Public and Privacy Act (2009:400) To protect individuals' or companies' confidential information it is ensured that they cannot be disclosed directly or indirectly in the statistics that are made public.
European level:
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Regarding the national publication based on vehicles registered in Sweden we do not currently apply any disclosure control. This is due to the fact that the survey is a sample survey which means that disclosure of single vehcilces or companies is impossible (regarding the the currrent subpopulations the estimates are broken down into).
Regarding the publication based on vehicles registered outside of Sweden (based on the so called D-tables): Estimates based on less than 4 observations, as well as estimates that are judged to be too uncertain, are not presented.
Microdata to researchers and other users is provided by Transport analysis after approved secrecy examination and / or disclosure control.
8.1. Release calendar
The survey is conducted and reported quarterly. Results (tables, database and press release) are published on Transport Analysis (NSI) web site almost three months after the reference quarter.
After each calendar year, a summary of quarterly data to annual data is carried out and a separate annual report is published. This report is published almost five months after reference year.
8.2. Release calendar access
Results are pulished on Transport Analysis (NSI) web site on the following link. On the web site
The statistics are published on Transport Analysis (NSI) web site www.trafa.se. An email to users and subscribers will be sent on the day the statistics are published. The date for quarterly and annual publication is stated in the autumn the year before the reference year. The statistical data are available to all users at the same time.
Quarterly and yearly. Se section 8.1 for more details.
10.1. Dissemination format - News release
Annual and qurterly publication: Press release regarding annual and quarterly publication is available on Transport Analysis (NSI) web page (only in swedish) https://www.trafa.se/om-oss/press#/
10.2. Dissemination format - Publications
Quarterly and annual publication: Technical documentation (quality declaration- in Swedish) in PDF. Annual publication: Summary report (PDF). All publications are available on Transport Analysis (NSI) web page: https://www.trafa.se/en/road-traffic/swedish-road-goods-transport/
Both manual controls, indata controls and contacts with reporting companies are made.
The quality assurance of the Swedish road freight transport statistics data is based on the following principles:
The statistical error (percentage standard error) of estimates based on the micro-data transmitted to Eurostat shall not be greater than 5% (special conditions apply to smaller countries, see Commission Regulation (EC) 642/2004).
In addition to the data, we inform Eurostat on the national characteristics of the data collection. This information is published as part of the quality documentation.
Eurostat validates the incoming micro-data, record by record, by applying detailed validation checks as described in Chapter 12 of Road freight transport methodology.
Benchmarking studies are carried out to verify the existence of possible bias in the road freight data by comparing the results with other independent data sources when needed.
11.2. Quality management - assessment
Tools for the assessment of the quality of the aggregated road freight data are for example by comparisons with other register-based sources.
The aim is to keep the users of the data informed on all these aspects by means of the methodological manuals.
Annual national evaluation of the statistics.
Regular national user councils with focus on relevance and accessibility.
12.1. Relevance - User Needs
The main users of the road freight statistics are the European Commission, national authorities, research institutions, trade organizations, industrial organization and contractors.
The statistics are used in the Government's work on freight and other transport issues analyses on competition, regional policies, modal shift analyses and environmental analyses.
12.2. Relevance - User Satisfaction
No formal survey towards users have been carried out. Instead, Transport Analysis have a Council of users. In the Council the most important users of the statistics are represented. The Council meets about once a year. In the meetings the users can express their view regarding the statistics in different matters.
12.3. Completeness
The published statistics are in line with the needs of most users. Two areas where the user needs are not fulfilled are:
dangerous goods
geographical breakdown
Regarding dangerous goods estimates are on a national level divided into national and international transport. Estimates are provided by ADR-classes. Some users would like to see estimates divided into finer subgroups which for the moment cannot be provided, because the sample size is not large enough.
Regarding geographical breakdown the user need is to provide estimates on municipality level, not NUTS3 level. This has until now not been possible, since municipality is not collected.
However, local geographical areas (LAU) has been collected since long ago. But without ability to connect the LAUs to the municipality. During the autumn 2019, due to a development project, we can now match the LAUs to the municipality. This has been done for data from 2012 and forward. This means that the geographical breakdown on municipalitys are possible from now on.
Still, many users ask for detailed data. If the published data does not include the statistics the users need, specialized tables can be provided by Transport Analysis after approved secrecy examination and / or disclosure control.
13.1. Accuracy - overall
The statistics are subject to uncertainty. The main sources of uncertainty are sampling, non-response and measurement. The uncertainty due to sampling is quantified using confidence intervals (95 percent). The non-response is compensated in the estimation procedures through straight expansion within strata. No special method or model is used for potential measurement uncertainty.
In 2014 an evaluation study was conducted regarding non-response. The results of the analysis show that for some variables (load capacity, geographical regions and age of the vehicle) no bias occurs, but for the variable register-based vehicle kilometers there is a bias. The non-response analyzes show that non-responding vehicles have a longer average daily (register-based) vehicle kilometers than the responders. Since there is a correlation between the register-based vehicle kilometers and the actual vehicle kilometers during the measurement week, this implies a risk of bias regarding mileage. This can lead to underestimation of the true levels for the total number of kilometers traveled.
One other aspect that affects the estimates is false reporting of no activity. False reporting means that for a certain vehicle the reply to the questionnaire is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. In 2014 a new method to account for false reporting of no activity was introduced. This lead to a raise in the estimates with about 30 percent. These higher levels better reflect the actual level of road freight transport and align better with corresponding data from other sources.
13.2. Sampling error
The sampling frame with vehicles is stratified into 52 strata. A simple random sample is drawn within each stratum. The total sample size per quarter is around 3000 vehicles which leads to roughly 12 000 sampled vehicles per year.
Uncertainty in the estimates derived from sampling is quantified via confidence intervals. The confidence intervals are dependent on the scale of the variable so to facilitate the comparison the relative uncertainty margin (also called the relative margin of error or sometimes the percentage standard error) is calculated for certain parameters. The precision requirement from Eurostat is that the relative margin of error shall not exceed ±5 % for the six parameters in the table below.
Relative margin of error
2018
2019
2020
2021
2022
2023
National transport
Tonnes transported
± 5.7%
± 5.4%
± 5.8%
± 5.4%
± 4.9%
± 5.3%
Tonne-kilometers performed
± 5.7%
± 5.1%
± 5.1%
± 4.6%
± 4.8%
± 4.5%
Vehicle-kilometres
± 4.5%
± 4.3%
± 4.0%
± 3.3%
± 3.6%
± 3.4%
Total
Tonnes transported
± 5.7%
± 5.3%
± 5.7%
± 5.3%
± 4.8%
± 5.2%
Tonne-kilometers performed
± 5.4%
± 4.9%
± 4.9%
± 4.4%
± 4.6%
± 4.4%
Vehicle-kilometres
± 4.3%
± 4.1%
± 3.9%
± 3.2%
± 3.5%
± 3.3%
In Sweden the sample size is dimensioned so the precision requirements should be fulfilled. With approximately 3000 vehicles per quarter (12 000 per year) the precision requirements are fulfilled for all parameters in 2023 (rounded to whole numbers).
13.3. Non-sampling error
A common classification of sources of non samling errors is frame coverage, measurement, non-response, data processing and model assumptions. Each source is described briefly below
Frame coverage
Frame coverage comprises both over- and under-coverage. Overcoverage, i.e. that a vehicle is included in the sampling frame, even though it does not belong to the target population, may occur, for example, because the vehicle does not carry out road freight transports on public roads but only within a defined area (e.g. industrial area). Another cause of over-coverage depends on the time aspect. The register that forms the base for the sampling frame is retrieved from the Swedish Transport Agency about 1.5 months before the quarterly start. The last weeks in a specific quarter thus occur just over four months after the register was taken. At that time, the vehicle can e.g. have been scrapped, canceled or unregistered.
There were 434 vehicles classified as over-coverage during 2023 in the Swedish survey. This corresponds to 3.7 percent of all 11 693 sampled vehicles. The calculation 100-3.7 = 96.3 percent gives a measure of the register quality in terms of non-over-coverage.
Under-coverage is generally a more serious problem than over-coverage. The under-coverage is methodologically handled in the estimation procedure. In principle, the method assumes that the number of vehicles in the frame (Nh) is replaced by an estimated value for the number of vehicles at the midpoint of the quarter. The sampling frame for e.g. quarter 2 in a certain year took place on February 15 that year, which is the midpoint for quarter 1 the same year. This means that the number of vehicles from the sampling frame for quarter 2 serves as (best) estimate of the number of vehicles for quarter 1. A similar procedure is used for all quarter.
Measurement
The method with questionnaires depends on accurate and truthful answers from the respondents. The respondents also depend on the instructions and definitions being clear and understandable. The information requested is sometimes complicated and even with definitions that appear clear, misunderstandings can arise. It is difficult to know whether all the data collected is accurate and complete. Below are some examples of situations where measurement uncertainty occurs.
Uncertain vehicle kilometer data and missing empty runs may occur. In case of missing vehicle kilometers data, these are imputed by the statistical producer with the help of route planning programs.
For some types of consignments, the respondents have difficulties knowing the weight of goods. This can occur if the transport assignment is to pick up a semi-trailer at one loading terminal and transport it to another loading terminal. The importance of the goods may in some of these cases be unknown to the responder. In these cases, the weight must be estimated. In these cases, the type of goods may also be unknown.
A potential measurement error is the under-reporting of individual consignments during the measurement week. This can happen if a vehicle owner responds to the survey but forgets to include certain consignments, such as empty runs. In some situations, this can be identified at registration. No in-depth studies of the extent of under-reporting of individual consignments have been conducted.
Another important measurement uncertainty is that some responders report no activity during the measurement week when in fact activity was done, i.e. false reporting. This problem is serious but from 2014, a new estimation method, taking false reporting of no activity into account was introduced.
Non-response
Unit non-response affects the statistics in two ways. On one hand the base (number of responders) is reduced, which adds to the uncertainty. However, this is not a major problem, at least for high aggregation level estimates. The other effect, which is more serious, is the risk that results are biased due to non-response. If those who do not respond differ systematically (regarding the survey variables) from those who have answered, there is a risk of bias in the estimates. The method to compensate for non-response, straight expansion within strata, is based on the fact that the non-response occurres randomly within strata.
The response rate in the Swedish road freight survey was 59.2 percent 2023. Non-response is increasing in surveys and Transport analysis is investigating possibilitites to extracting traffic data from vehicle Fleet management systems in order to aviod non-response and to reduce the response burden.
In 2014 an evaluation study was conducted regarding non-response. The results of the analysis show that for some variables (load capacity, geographical regions and age of the vehicle) no bias occurs, but for the variable register-based vehicle kilometers there is a bias. The non-response analyzes show that non-responding vehicles have a longer average daily (register-based) vehicle kilometers than the responders. Since there is a correlation between the register-based vehicle kilometers and the actual vehicle kilometers during the measurement week, this implies a risk of bias regarding mileage. This can lead to underestimation of the true levels for the total number of kilometers traveled.
Item non-response is very limited in the survey. Regarding the mandatory variables, no item non-response exists in the databases delivered to Eurostat. Some (limited) imputations are however needed to obtain that. Regarding the voluntary variable degree of loading (volumetric situation), which is delivered to Eurostat, there exists some 30-40 percent item non-response.
Data editing and coding
Data editing and coding is also a source of uncertainty. This source of uncertainty is regarded as marginal. In support of this claim it can be mentioned that when data is submitted to Eurostat extensive validation checks are carried out. If incorrect values (errors) are detected they need to be corrected. However, errors in data submitted to Eurostat have been very uncommon.
Model assumptions
The most important model assumption in the survey concerns how compensation for the non-response and the method used to account for false reporting of no activity. The estimation method is called straight expansion within strata and means that the respondents within a stratum are considered as if they were the sample. Alternatively put, this implies an assumption that the non-response occurs randomly within strata, i.e. there is no systematic tendency who choose to answer or not to answer. Reasons for not responding may be refusal, forgetfulness, do not have time, the form, etc. An evaluation study regarding the non-response was conducted in 2014. Above, regarding non-response, this was described and what conclusions were drawn from the analysis.
The method to account for false reporting of no activity is based on a separate survey: The No Activity Survey. The frame for the No Activity Survey is the same as for the Road Freight Survey. The sample size is 500 vehicles every quarter The sample in the No Activity Survey is negatively coordinated with the ordinary survey, i.e. a vehicle sampled in the ordinary Road Freight Survey can not be selected in the No Activity Survey. Only one question is posed in this survey: Did you use the vehicle for goods transportation last week? Based on the answer from this survey and the answers from the ordinary road freight survey a correction factor (inflation factor) is calculated. This inflation factor is used in the estimation process. Normally the estimates are inflated some 30-40 percent compared to not using the inflation factor.
This assumption is difficult to verify. Rather, when comparing the level for the estimates from the road freight survey to data sources it has been found that the underestimation at national level is in the order of 30–40 percent. By using the inflation factor to account for false reporting of no activity, the estimates are raised 30-40 percent which should reflect the true levels better.
14.1. Timeliness
Quarterly data and publication: The publication of quarterly report, tables with estimates and documentation is normally done at Transport Analysis web site almost three months after reference quarter. The A1, A2 and A3 datasets are normally delivered to Eurostat 2.5 months after reference quarter.
Annual publication: The publication of annual report, tables with estimates and documentation is normally done at Transport Analysis web site almost five months after reference year. No additional annual data is delivered to Eurostat (only quarterly data).
14.2. Punctuality
The dates for quarterly and annual publication are stated on Transport analysis web page well in advance. The date for actual publication has, so far, always been the planned dates.
Regarding delivery of data to Eurostat, the Regulation (EU) 70/2012 stipulate that the A1, A2 and A3 datasets should be delivered within five months after reference quarter. Sweden normally delivers the datasets 2.5 months after reference quarter.
15.1. Comparability - geographical
Sweden conducts the road freight survey according to Regulation (EU) No. 70/2012. That means that the definitions are the same with those presented in the manual. As stated on Eurostat Road freight transport measurement (road_go) Reference Metadata in Euro SDMX Metadata Structure (https://ec.europa.eu/eurostat/cache/metadata/en/road_go_esms.htm) there are some national characteristics of the survey that should be kept in mind when comparing the estimates. Here we give comments regarding Sweden in those matters:
Weight. Gross weight of goods is collected (i.e. not gross-gross weight), which means that containers, swap bodies and pallets are excluded. However, for journeys with no goods but a container, the information to the respondents is to register the weight of the container and use NST-code 16.
Multi-stop journeys. Multi-stop journeys are coded by consignments. The respondent records each basic transport operation in the questionnaire. These records are then recalculated to journey level.
Classification of containers. Swap-bodies are reported as "large freight containers".
15.2. Comparability - over time
Sweden has provided data since 2000. The years 2000-2013 are fully comparables. In 2014 a break in the time series occurred. False reporting of no activity hade for some time been a problem in Sweden. False reporting means that for a certain vehicle the reply to the questionnaire is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. In 2014, a new method to account for false reporting of no activity was introduced. This lead to a raise in the estimates with about 30 percent. The years 2014 to present are fully comparable.
From 2015, total loaded freight weight is requested for distribution and collection rounds in the form. In previous years, the average loaded person was demanded. This has meant that the total evel of loaded goods during a quarter has increased with an estimated 6–8 percent.
15.3. Coherence - cross domain
As pointed out on Eurostat Road freight transport measurement (road_go) Reference Metadata in Euro SDMX Metadata Structure (https://ec.europa.eu/eurostat/cache/metadata/en/road_go_esms.htm) there are some principal differences between road freight transport and other transport modes. In addition to what is stated in that text, one might add that comparability cross domains is facilitated if the same nomenclature is used for different variables. For example, those transport modes that classifies geographic information according to NUTS3-levels (which is done in road freight transport) are coherent, and thus comparable, in that matter.
The road freight transport survey uses the classification system stated in section 3.2 above. Other transport modes that also use this classification systems are coherent and can be compared in those matters.
Previous estimates from 2020 of the total cost of collection and production of the survey in Sweden is around 6 millions SEK, corresponds to 523 000 EUR.
In Sweden the burden for the responders to reply to the questionnaire is estimated to approximately 4 300 hours in 2023. Please note that this is a very rough estimate. Assuming a certain cost per hour the corresponding total cost can be estimated. The estimate for 2023 is roughly 4.1 millions SEK which (approximately), corresponds to 357 000 EUR.
The median time to fulfill the questionnaire 2023 is 20 minutes for all respondents (among those who answered the question about time). For those with journey data the median time to fulfill the questionnaire is 35 minutes and for those without journey data the median time is 5 minutes.
Important major efforts that are being made and have been implemented are as follow:
Annual revision of the form
Reduced sample size in 2013
Introduction of web survey in 2015
A new web interface was introduced in 2022. In the web interface, there is an Excel template that has the same appearance and columns as the dispatch journal that respondents must fill in. Thus, an respondent can fill in dispatches in the Excel template and then paste this into the web survey.
When sending out the survey, there is now a possibility that a respondent can receive an invitation to the survey via e-mail, instead of a postal survey. This was introduced in 2022.
Planned future actions are as follow:
Retrieve data (answers) via the companies' IT systems instead of answering via questionnaires
Make general improvements to the web survey to make it easier to answer
It can also be stated that the policy in Sweden is that the datasets (A1, A2 and A3) should be 100% error-free (regarding the validation procedure at Eurostat).
17.2. Data revision - practice
If errors occurs in the validation process (regarding datasets A1, A2 or A3), the practice in Sweden is to immediately correct the errors and re-deliver all datasets. However, errors are very unusual.
18.1. Source data
Construction of sampling frame for the survey
Name of register:
Vehicle Register (VR), Commercial Traffic Register (CTR), Central register of corporations (FDB) and the vehicle-kilometre database (VKD). These registers are used to construct the sampling frame.
Name of organisation who maintains the register:
Swedish Transport Agency (the registers VR and CTR) and Statistics Sweden (the registers FDB and VKD).
Frequency of update:
VR, CTR and FDB: daily
Vehicle-kilometre data (VKD): yearly
Frequency of construction of frame:
Once a quarter
Statistical unit in sampling frame:
Tractive vehicle
Arrangements for accessing the register:
Transport Analysis is the responsible authority for the survey and they have since year 2009 commissioned the company Statisticon AB to produce the survey. Statisticon AB currently has the option for this production until reference year 2024. The VR and CTR is delivered from the Swedish Transport Agency to the producer at specified dates. For quarter Q the register data is received 1.5 months in advance. The specific dates each year are:
First quarter: November 15 (previous year)
Second quarter: February 15
Third quarter: May 15
Fourth quarter: August 15
The sampling frame is constructed based on the Vehicle Register data where the object is vehicle. In the process various steps are taken, including omitting vehicles not belonging to the target population (e.g. load capacity should be 3.5 tonnnes or more). One other step includes merging data from the central register of corporations (FDB) and only keeping those vehicles belonging to formally registered companies. Yet another step includes merging register based data on driving distance (kilometres travelled) from previous year for each vehicle based on information from the vehicle- kilometre database (VKD).
Information obtained from the register:
Most of the information regarding a vehicle is obtained from the Vehicle Register. Important variables are: vehicle registration number, organisation number of the enterprise/owner of the vehicle, name and address, year of first registration, vehicle in use/not in use, type of transport (hire/reward or own account), number of axles for the vehicle, vehicle body code plus the information is used in the stratification as follows:
County codes where the vehicle is registered are used to get the NUTS 2-level codes
Maximum permissible laden weight and the service weight of the vehicle. The difference between those two concepts gives the vehicle load capacity, which is used in the stratification
From the Commercial Traffic Register we obtain the number of permits for international traffic for an enterprise. This variable is used to form a stratification variable whether the vehicle has a permit for international traffic or not
The variable kilometres travelled previous year is also used in the stratification
Age for the vehicle (used in the stratification)
Types of vehicles excluded:
Vehicles with load capacity under 3.5 tonnes are excluded.
Vehicles that are not operating
Vehicles 30 years and older.
Some body type codes for which transport of goods is not possible, such as ambulances, hearses, breakdown lorries, fire engines (military vehicles are not included in the Vehicle Register).
Vehicles owned by companies that are not registered in the central register of corporations.
18.2. Frequency of data collection
Continuous, 52 weeks of the year (53 weeks when applicable).
18.3. Data collection
Sampling methodology
Statistical unit:
Tractive vehicle
Time unit for measurement week:
1 week
Time unit of quarter included in the survey:
All (13 weeks)
Stratification:
The lorries in the sampling frame are stratified in 52 strata. The stratification is done with respect to several variables. The first variable is whether the lorry owner has a permit for international traffic or not. If the owner (i.e. the company) has a permit for international traffic the lorry or the lorries are categorized to international stratum, otherwise to national stratum. There are 35 national and 17 international strata. The next stratification variable is where the lorry is registered. The eight NUTS2-regions in Sweden categorized into 5 geographic areas according to the following:
SE11 and SE12
SE21 (without the island Gotland) and SE23
SE22
SE31, SE32 och SE33
Gotland
Due to special circumstances regarding the island Gotland it is kept as a region of its own.
For the 35 national strata the stratification is done according to the following principles:
The lorries are geographically divided according to the geographic regions above
In every geographic region, except Gotland, the lorries are divided into two groups according to their age; lorries 0–5 years old and lorries older than 5 years old
Within each age group the lorries are divided into six subgroups according to total kilometres travelled per year (register variable) and load capacity (register variable) according to:
Lorries with load capacity up to 13 tonnes (regardless of yearly distance travelled)
Lorries with yearly distance travelled 100 000 km or less and load capacity 13 - 16 tonnes
Lorries with yearly distance travelled 100 000 km or less and load capacity over 13 tonnes
Lorries with yearly distance travelled more than 100 000 km and load capacity over 13 tonnes
Lorries registered in Gotland are divided into two groups according to load capacity; 13 tonnes or less and over 13 tonnes
The 35 national strata
Nr
Stratum code
Geographic division
Age
Yearly distance travelled (km)
Load capacity (Kg)
1
110101
SE11, SE12
0–-5 year
Regardless of distance
–13 000
2
110112
0–5 year
0–100 000
13 001–16 000
3
110113
0–5 year
0–100 000
16 001+
4
110122
0–5 year
100 001+
13 001+
5
110201
6+ year
Regardless of distance
–13 000
6
110212
6+ year
0–100 000
13 001–16 000
7
110213
6+ year
0–100 000
16 001+
8
110222
6+ year
100 001+
13 001+
9
120101
SE21 exkl. Gotland, SE23
0–5 year
Regardless of distance
–13 000
10
120112
0–5 year
0–100 000
13 001–16 000
11
120113
0–5 year
0–100 000
16 001+
12
120122
0–5 year
100 001+
13 001+
13
120201
6+ year
Regardless of distance
–13 000
14
120212
6+ year
0–100 000
13 001–16 000
15
120213
6+ year
0–100 000
16 001+
16
120222
6+ year
100 001+
13 001+
17
130101
SE22
0–5 year
Regardless of distance
–13 000
18
130112
0–5 year
0–100 000
13 001–16 000
19
130113
0–5 year
0–100 000
16 001+
20
130122
0–5 year
100 001+
13 001+
21
130201
6+ year
Regardless of distance
–13 000
22
130212
6+ year
0–100 000
13 001–16 000
23
130213
6+ year
0–100 000
16 001+
24
130222
6+ year
100 001+
13 001+
25
140101
SE31, SE32, SE33
0–5 year
Regardless of distance
–13 000
26
140112
0–5 year
0–100 000
13 001–16 000
27
140113
0–5 year
0–100 000
16 001+
28
140122
0–5 year
100 001+
13 001–16 000
29
140123
0–5 year
100 001+
16 001+
30
140201
6+ year
Regardless of distance
–13 000
31
140212
6+ year
0–100 000
13 001–16 000
32
140213
6+ year
0–100 000
16 001+
33
140222
6+ year
100 001+
13 001+
34
150001
Gotland
Regardless of age
Regardless of distance
–13 000
35
150002
Regardless of age
Regardless of distance
13 001+
For the 17 international strata the stratification is done according to the following principles. In a first step road tractors that fulfil the following criteria are placed in a separate stratum (200000):
Lorry owned by company with 16 or more permits for international traffic.
The lorry is younger than 11 years old
The lorry is registered in NUTS2 region SE11 or SE12 or the counties Blekinge or Västra Götaland and has a yearly total distance travelled over 100 000 km and a load capacity over 10 tonnes
The lorry is registered in the county Skåne or Halland and has a load capacity over 10 tonnes
In a second step the additional 16 strata are created by dividing the lorries into four geographic regions according to:
NUTS2 region SE11, SE12 och SE21
NUTS2 region SE22
NUTS2 region SE23
NUTS2 region SE31,SE32 och SE33
For each geographic region, road tractors are divided into a separate stratum regardless of yearly distance travelled or load capacity. The remaining lorries are divided into three strata according to yearly distance travelled and load capacity according to:
Lorries with yearly distance travelled 100 000 km or less and load capacity 10 tonnes or less
Lorries with yearly distance travelled 100 000 km or less and load capacity 10 tonnes or more
Lorries with yearly distance travelled more than 100 000 km
The 17 international strata:
Nr
Stratum code
Geographic division
Type of lorry
Yearly distance travelled (km)
Load capacity (Kg)
36
200000
37
211000
SE11, SE12 och SE21
Road tractor not belonging to stratum 200000
Regardless of distance
Regardless of load capacity
38
212011
SE11, SE12 och SE21
Other lorries
0–100 000
–10 000
39
212012
SE11, SE12 och SE21
Other lorries
0–100 000
10 001+
40
212020
SE11, SE12 och SE21
Other lorries
100 001+
Regardless of load capacity
41
221000
SE22
Road tractor not belonging to stratum 200000
Regardless of distance
Regardless of load capacity
42
222011
SE22
Other lorries
0–100 000
–10 000
43
222012
SE22
Other lorries
0–100 000
10 001+
44
222020
SE22
Other lorries
100 001+
Regardless of load capacity
45
231000
SE23
Road tractor not belonging to stratum 200000
Regardless of distance
Regardless of load capacity
46
232011
SE23
Other lorries
0–100 000
–10 000
47
232012
SE23
Other lorries
0–100 000
10 001+
48
232020
SE23
Other lorries
100 001+
Regardless of load capacity
49
241000
SE31, SE32 och SE33
Road tractor not belonging to stratum 200000
Regardless of distance
Regardless of load capacity
50
242011
SE31, SE32 och SE33
Other lorries
0–100 000
–10 000
51
242012
SE31, SE32 och SE33
Other lorries
0–100 000
10 001+
52
242020
SE31, SE32 och SE33
Other lorries
100 001+
Regardless of load capacity
Allocation of the sample:
The initial quarterly total sample size is 2800 vehicles. These are allocated according to
1800 to national strata
150 to stratum 200000
850 to international strata
The allocation among strata within the national and international strata is Neyman allocation according to the variables tonnes based on data from the eight most recent available quarterly data. If a stratum, according to the allocation principle, obtain fewer than 18 vehicles, the sample size is raised to 18 vehicles. This means that the actual quarterly sample size is slightly larger than 2800, normally slightly more than 100 extra vehicles which gives a quarterly sample size of slightly more than 2900 vehicles.
Sampling procedure:
The vehicles are randomly selected within strata according to a simple random sampling procedure. In a second step the each vehicle is assigned a randomly selected week during the quarter. The week is also selected accoring to a simple random sampling procedure.
Data collection and weighting
Recording of journey data sent to Eurostat:
Single stop: The respondent is allowed to record the main type of goods if there are several types of goods. Otherwise the respondent will record mixed goods for such a journey.
Multi stop: Multi-stop journeys are coded by consignments. The respondent records each basic transport operation in the questionnaire. These records are then recalculated to journey level by the producer. The method used can be described as follows:
The tonne-kilometres per consignment (each basic transport operation) is calculated by multiplying tonnes with travelled distance (km).
The tonne-kilometres for each congsignment is added to a total tonnes-kilometres for the journey
The kilometres driven for the journey is registrated by identifying the distance between loading point and unloading point (normally not the same as adding the km driven for each basic operation)
Then the tonnes for the journey is caclulaed according to
A / B = C
A = Tonne-kilometres for the journey
B = Kilometres driven on the journey
C = Average tonnes for the journey
Tonne-kilometres will be the same regardless of which file, A2 or A3, that is used for their calculation. Exact figures in kilos are used in the calculations.
The type of goods for the total journey is calculated as the main type of goods (in respect of kilos).
Regarding journey type 2 (multi-stop-journeys), we use the principle that if a trailer was used for the first consignment of the journey a trailer was used for the entire journey.
Collection/delivery: In the Swedish survey we allow the respondents to decide if the journey can be seen upon as a collection (c) or distribution (d) round or a combined collection/distribution round (c/d). If the journey consists of five or more stops the respondent is allowed to give information on the journey as a whole. The respondent is asked to indicate the c/d-round with a “D” for distribution or “U” for collection (the U refers to the swedish wording) or “DU” for combined distribution/collection rounds in the questionnaire. The respondent is also asked to registrer the number of stops (or approximate number if there are hundreds of stops). If the journey is considered as a c, d or c/d-round the respondent is asked to indicate the total weight for the round as a whole, the total kilometres driven during the round and the main commodity group. In the instructions to our respondents it is stated that the round is considered to start at the first loading point and finished at the last unloading point. This means that the possible empty leg must be recorded as a separate journey before and/or after the round. The information from the Swedish survey in the A2 file and the A3 file is the same regarding type 3 journeys. The tonne-kilometres are calculated according to the principles in the manual vol 1 2016 in section 6.5. More specifically, for delivery rounds (only) the type 1-principle is used. For collection rounds (only) the type 2-principle is used. For combined delivery and collection rounds the type 5-principle is used.
Special notes on some variables:
The respondents are asked to fill in the UN-number instead of the ADR-number for hazardous goods. The UN-number is then converted into ADR-number.
Other variables: Regarding trailers we allow the respondent to record the most common trailer or combination of trailers used during the week for measurement.
Calculation of weighting factors:
The weighting factor is based on the methodology called straight expansion within strata. However, since 2014 the weighting factor is multiplied with an inflation factor that accounts for false reporting of no activity. False reporting means that for a certain vehicle the reply is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. Inflating the weighting factors leads to a raise in the estimates with about 30 percent. These higher levels are better estimates of the true levels of the parameters, e.g. total km driven. The weighting factor is given by
h = is the index for stratum, h=1,2,…,H (and H=52)
Nh = the number of vehicles in stratum h
mh = the number of responding vehicles in stratum h. A vehicle is regarded as responding if it belongs to category B1:5 (vehicles responding with journey data) or B1:6 (vehicles responding without journey)
g = is the index for stratum in the No Activity Survey (help survey) g=1,2,…,G (and G=11).
wg = an inflation factor that account for false reporting of no activity
Remark regarding Nh: For a certain quarter the number of vehicles in a stratum is taken from the following quarter (to account for under-coverage, se 13.3 above). Example: for quarter 1 the numbers of vehicles in a stratum is taken from the frame from quarter 2. The rationale behind this is that the frame for Q2 originates from February 15, i.e. the midpoint of Q1 in time. The number of vehicles at the midpoint of Q1 is a better source for the population size than the number of vehicles in the frame for Q1 which is originated from November 15 the previous year. This method agrees with the suggested method in the reference manual vol 1 2016 chapter 7.2.2.
Remark regarding wg: A parallel help survey called the No Activity Survey (NAS) is performed together with the ordinary Road Freight Survey (RFS). The target populations are the same and the same frame is used in both surveys. The sample size in the NAS is 500 vehicles each quarter and in the Road Freight Survey (RFS) about 3 000 each quarter. The stratification in the NAS is based on company characteristics rather than vehicle characteristics which are used in the RFS. If a vehicle is selected in the RFS it is non-eligible in the NAS for one year. The reason for the NAS is that there are (strong) indications that the amount of no activity is too large in the RFS Survey. If a vehicle falsely reports no activity, when in fact journeys were performed, the estimates of e.g. total km driven will be underestimated. In the NAS, performed by telephone, only one question is posed: “Did you use the vehicle for goods transportations last week”. Since only one question is posed we believe that an accurate answer is obtained. Based on each survey, NAS and RFS, the proportion of vehicles with activity and no activity can be estimated. The ratio between the two estimates of proportion of vehicles with activity forms an inflation factor wg. If, for example, the proportion of vehicles with activity in the NAS is 0.85 and 0.70 in the RFS (in a certain stratum), then the inflation factor is wg = 0.85/0.7 = 1.21, i.e. a raise of 21 %. Since the sample size in the NAS is fairly small the inflation factors can vary between quarters. A stabilizing procedure is used. For a certain quarter Q a weighted average of the inflation factors from year t, t-1 and t-2 is calculated. One (weighted) inflation factor wg is calculated for each stratum g and is multiplied with the straight expansion weight 13×(Nh/mh). Since the stratification is different in both surveys the weighting factors will not be constant within a stratum h. Hence no weighting factors can be presented in the supplementary table B1.
Estimation of maximum permissible laden weight:
The variable maximum permissible laden weight regarding the vehicle is register based information. The maximum permissible laden weight for the trailer or semi-trailer is collected through the questionnaire. If no trailer or semi-trailer is used the maximum permissible laden weight registered in the A2 dataset (variable A1.4) is thus only based on register information. If a trailer or semi-trailer is used, the maximum permissible laden weight for the entire vehicle configuration is calculated as the sum of the vehicle and trailer/semi-trailer maximum permissible laden weight.
Optional variables covered:
Vehicle empty kilometres
Type of cargo
Vehicle operator’s NACE category of activity (register information)
Axle configuration (register information regarding vehicle, collected information regarding trailer or semi-trailer)
Degree of loading of the vehicle
Additional variables compared to the legal requirements:
A1. Vehicle-related variables:
possibility of using vehicles for combined transport: No, not delivered in dataset A1
vehicle operator’s NACE Rev. 2 at class level (four-digit level); Yes, delivered in dataset A1 - (register information)
vehicle empty kilometres : Yes, delivered in dataset A1
A2. Journey-related variables:
axle configuration according to the nomenclature defined in the Regulation on road transport statistics: Yes, delivered in dataset A2
place of loading, if any, of the road transport vehicle on another means of transport: Yes, delivered in dataset A2
place of unloading, if any, of the road transport vehicle from another means of transport: Yes, delivered in dataset A2
situation ‘fully loaded’ (procedure 2) or ‘not fully loaded’ (procedure 1) of the goods road transport vehicle during the journey in question, in terms of maximum volume of space used during the journey (procedure 0 = by convention for unladen journeys): Yes, delivered in dataset A2
A3. Goods-related variables:
type of freight (Cargo types) as defined in the Regulation: Yes, delivered in dataset A3
Procedure for reminders:
First reminder: sent out by post monday two weeks after the due date.
Second reminder: sent by post after another week.
Third reminder: performed by telephone after another week. The telephone reminder process continues for two weeks.
A normal figure for the response rate is around 60 percent. Considering the potential effect the non-response might have on the estimates, we judge the response rate to be satisfactory for the purpose of the survey.
Some main figures regarding frame, sample and data collection
2015
2016
2017
2018
2019
2020
2021
2022
2023
Total number of relevant goods vehicle in the country (B1.1)
61 521
61 822
63 728
64 991
65 618
64 869
65 806
66 856
66 966
Number of vehicles selected for initial sample and questionnaires despatched to vehicle owners (B1.2)
11 607
11 627
11 542
11 695
11 668
11 592
11 756
11 741
11 693
Number of cases classified as non-respondents (B1.3)
3 969
4 182
4 328
4 553
4 558
4 841
4 942
5 016
4 766
Number of cases where sample register information was wrong and response could not be used (B1.4)
501
612
506
498
472
444
398
361
434
Number of questionnaires used in analysis (B1.5)
4 194
4 027
3 914
3 944
3 923
3 810
3 973
4 000
3 975
Number of cases where no vehicle activity was recorded during the sampled period but the vehicle could be considered as part of the active stock (B1.6)
2 943
2 806
2 794
2 700
2 715
2 497
2 443
2 364
2 518
18.4. Data validation
National level :
The data is controlled at several stages and in numerous ways at the national level (in Sweden). Briefly, the data in the paper questionnaire and in the web questionnaire are manually controlled by staff that register the data as well as automatically controlled. If necessary the vehicle owner is contacted for clarification and/or correction. At the end of a quarter, the data is controlled programmatically regarding allowed codes and amounts as well the variables logical consistency. The vehicle owners can be contacted at this stage to for clarification and/or correction. After this step, the data is processed in several steps before a final database is obtained. Among other things, the weighting factor is calculated and some imputation is performed. Each step in the procedure is controlled and monitored. The final data is then delivered to Eurostat.
From Eurostat :
Since 1999, micro-data from the reporting countries have to be submitted according to Commission Regulation 2163/2001. The data are then checked and validated by EUROSTAT (verification of many different codes used (NUTS 3, numeric or alphabetic variables) correctness of linked questionnaires in the different dataset, etc…). Detected errors are then reported back to the data sender with the request for correction, this is an iterative process until at least 99.5% of all data records are validated and loaded in the database.
18.5. Data compilation
In section 18.4 the data editing or data processing was breifly described. In 18.3 the calculation of weighting factor was described.
18.6. Adjustment
Road freight data is not seasonally adjusted.
However, one aspect regarding adjustment can be mentioned. If a year contains 53 weeks the last quarter contains 14 weeks. This is taken into consideration in the estimation procedure in Sweden. At first glance it might seem straight forward to replace the expansion factor 13 in the weighting factor (se section 18.3) with the factor 14. But that is not how it is handled in Sweden.
First, we establish what parameter we are interested in. Let t denote the true parameter for a total during a quarter containing 14 weeks, e.g. total tonnes loaded during 14 weeks. We introduce a “normal quarter” adjusted parameter that is defined as tn=(13/14)×t. The parameter tn can be interpreted as the down-adjusted total of e.g. tonnes loaded as if the quarter would have consisted of 13 weeks. tn is (obviously) always smaller than t. The rational for the formulation of the parameter tn is that comparing the parameter t the 4th quarter a certain year (that consists of 14 weeks) to the parameter t the 4th quarter previous year (that consists of 13 weeks) is misleading. A larger value in e.g. tonnes loaded for current year compared to previous year is not due to more activity in the sector, but rather due to an extra week in the quarter. Hence, the parameter tn is more relevant for comparisons.
How do we estimate the parameter tn? The weighting factor when estimating parameter t if the quarter containes 14 weeks is 14×(Nh/mh)wg (this is due to the fact that the selection of 1 measurement week should be expaneded to 14 weeks). Then, estimating the “normal quarter” adjusted parameter tn the weighting factor is (13/14)× 14×(Nh/mh)wg=13×(Nh/mh)wg.
The conclusion is that the “normal quarter” adjusted parameter tn is estimated by using the “ordinary” weighting factor with factor 13. A more thorough technical description can be found in the Swedish technical documentation.
Road freight data collection consists of three datasets with quarterly periodicity and mandatory data collection: 1. Vehicle related variables dataset for a sample of road good motor vehicles contain, among others, indication about the type and age of the vehicle (from national vehicle register,) the economic activity of the owner of the vehicle (from national business register), the total kilometres loaded or empty. 2. Journey related variables dataset which contain, among other indications about weight of goods, regions of loading and unloading, distance driven, and tonne-kilometres performed during a journey 3. Goods related variables dataset which contain among others the type of goods transported and their weight and distance travelled, regions of loading and unloading.
A goods road motor vehicle is any single road transport vehicle (lorry), or combination of road vehicles, namely road train (lorry with trailer) or articulated vehicle (road tractor with semi-trailer), designed to carry goods
National transport is Road transport between two places (a place of loading and a place of unloading) located in the same country by a vehicle registered in that country.
International transport is Road transport between two places (a place of loading and a place of unloading) in two different countries and cabotage by road. It may involve transit through one or more additional country or countries.
Cross trade is International road transport between two different countries performed by a road motor vehicle registered in a third country.
Transit is any loaded or empty road motor vehicle, which enters and leaves a country at different points by whatever means of transport, provided the total journey within the country is by road and that there is no loading or unloading in the country.
Goods carried by road are any goods moved by goods vehicle
Place of loading/unloading is the geographical area for loading/unloading coded according to NUTS3-level
Place of loading/unloading of a goods road vehicle on another mode of transport
Place of loading (of the goods road transport vehicle on another mode of transport): The place of loading is the first place where the goods road motor vehicle was loaded on to another mode of transport (usually a ship or a rail wagon).
Place of unloading (of the goods road transport vehicle from another mode of transport): The place of unloading is the last place where the goods road motor vehicle was unloaded from another mode of transport (usually a ship or a rail wagon).
The reporting unit for road freight transport statistics is the goods road transport vehicle.
A selected goods road vehicle report all basic transport operations (consignments) during the reference week. This information is transformed to journeys which constitutes the statistical unit used for estimating population parameters such as total tonnes, tonne-kilometres and vehicle-kilometres.
The target population is all goods transports on public roads carried out by Swedish registered trucks / tractors with a load capacity of 3.5 tonnes or more during the reference period. Other exclusion criteras regarding vehicles are:
Vehicles 30 years and older and vehicles that are not operating.
Some body type codes for which transport of goods is not possible, such as ambulances, hearses, breakdown lorries, fire engines (military vehicles are not included in the Vehicle Register).
Vehicles owned by companies that are not registered in the central register of corporations.
The population size of vehicles is around 60 000 to 70 000 vehicles. Since the population is large a (random) sample of vehicles is drawn each quarter.
The data provided are goods vehicles registered in Sweden.
The reference period is quarter (13 weeks), i.e. the data delivered to Eurostat can be used to estimate parameters for a quarter. If four quarters are added together the statistics can be presented regarding a year (52 weeks).
The statistics are subject to uncertainty. The main sources of uncertainty are sampling, non-response and measurement. The uncertainty due to sampling is quantified using confidence intervals (95 percent). The non-response is compensated in the estimation procedures through straight expansion within strata. No special method or model is used for potential measurement uncertainty.
In 2014 an evaluation study was conducted regarding non-response. The results of the analysis show that for some variables (load capacity, geographical regions and age of the vehicle) no bias occurs, but for the variable register-based vehicle kilometers there is a bias. The non-response analyzes show that non-responding vehicles have a longer average daily (register-based) vehicle kilometers than the responders. Since there is a correlation between the register-based vehicle kilometers and the actual vehicle kilometers during the measurement week, this implies a risk of bias regarding mileage. This can lead to underestimation of the true levels for the total number of kilometers traveled.
One other aspect that affects the estimates is false reporting of no activity. False reporting means that for a certain vehicle the reply to the questionnaire is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. In 2014 a new method to account for false reporting of no activity was introduced. This lead to a raise in the estimates with about 30 percent. These higher levels better reflect the actual level of road freight transport and align better with corresponding data from other sources.
Data are collected regarding each basic transport operation (BTO) during a selected vehicle. The metric variables are loaded goods in kg and driven distance in km. The variable tonne-km is a derived variable, hence the vehicle owner does not need to register ton-km. Regarding number of journeys this is obtained when BTO:s are converted to journeys.
The statistics presented in tables are in tonnes or thousands of tonnes for loaded goods, km or thousands of km for driving distance, in millions of tonne-km and in thousands of journeys.
In section 18.4 the data editing or data processing was breifly described. In 18.3 the calculation of weighting factor was described.
Construction of sampling frame for the survey
Name of register:
Vehicle Register (VR), Commercial Traffic Register (CTR), Central register of corporations (FDB) and the vehicle-kilometre database (VKD). These registers are used to construct the sampling frame.
Name of organisation who maintains the register:
Swedish Transport Agency (the registers VR and CTR) and Statistics Sweden (the registers FDB and VKD).
Frequency of update:
VR, CTR and FDB: daily
Vehicle-kilometre data (VKD): yearly
Frequency of construction of frame:
Once a quarter
Statistical unit in sampling frame:
Tractive vehicle
Arrangements for accessing the register:
Transport Analysis is the responsible authority for the survey and they have since year 2009 commissioned the company Statisticon AB to produce the survey. Statisticon AB currently has the option for this production until reference year 2024. The VR and CTR is delivered from the Swedish Transport Agency to the producer at specified dates. For quarter Q the register data is received 1.5 months in advance. The specific dates each year are:
First quarter: November 15 (previous year)
Second quarter: February 15
Third quarter: May 15
Fourth quarter: August 15
The sampling frame is constructed based on the Vehicle Register data where the object is vehicle. In the process various steps are taken, including omitting vehicles not belonging to the target population (e.g. load capacity should be 3.5 tonnnes or more). One other step includes merging data from the central register of corporations (FDB) and only keeping those vehicles belonging to formally registered companies. Yet another step includes merging register based data on driving distance (kilometres travelled) from previous year for each vehicle based on information from the vehicle- kilometre database (VKD).
Information obtained from the register:
Most of the information regarding a vehicle is obtained from the Vehicle Register. Important variables are: vehicle registration number, organisation number of the enterprise/owner of the vehicle, name and address, year of first registration, vehicle in use/not in use, type of transport (hire/reward or own account), number of axles for the vehicle, vehicle body code plus the information is used in the stratification as follows:
County codes where the vehicle is registered are used to get the NUTS 2-level codes
Maximum permissible laden weight and the service weight of the vehicle. The difference between those two concepts gives the vehicle load capacity, which is used in the stratification
From the Commercial Traffic Register we obtain the number of permits for international traffic for an enterprise. This variable is used to form a stratification variable whether the vehicle has a permit for international traffic or not
The variable kilometres travelled previous year is also used in the stratification
Age for the vehicle (used in the stratification)
Types of vehicles excluded:
Vehicles with load capacity under 3.5 tonnes are excluded.
Vehicles that are not operating
Vehicles 30 years and older.
Some body type codes for which transport of goods is not possible, such as ambulances, hearses, breakdown lorries, fire engines (military vehicles are not included in the Vehicle Register).
Vehicles owned by companies that are not registered in the central register of corporations.
Quarterly and yearly. Se section 8.1 for more details.
Quarterly data and publication: The publication of quarterly report, tables with estimates and documentation is normally done at Transport Analysis web site almost three months after reference quarter. The A1, A2 and A3 datasets are normally delivered to Eurostat 2.5 months after reference quarter.
Annual publication: The publication of annual report, tables with estimates and documentation is normally done at Transport Analysis web site almost five months after reference year. No additional annual data is delivered to Eurostat (only quarterly data).
Sweden conducts the road freight survey according to Regulation (EU) No. 70/2012. That means that the definitions are the same with those presented in the manual. As stated on Eurostat Road freight transport measurement (road_go) Reference Metadata in Euro SDMX Metadata Structure (https://ec.europa.eu/eurostat/cache/metadata/en/road_go_esms.htm) there are some national characteristics of the survey that should be kept in mind when comparing the estimates. Here we give comments regarding Sweden in those matters:
Weight. Gross weight of goods is collected (i.e. not gross-gross weight), which means that containers, swap bodies and pallets are excluded. However, for journeys with no goods but a container, the information to the respondents is to register the weight of the container and use NST-code 16.
Multi-stop journeys. Multi-stop journeys are coded by consignments. The respondent records each basic transport operation in the questionnaire. These records are then recalculated to journey level.
Classification of containers. Swap-bodies are reported as "large freight containers".
Sweden has provided data since 2000. The years 2000-2013 are fully comparables. In 2014 a break in the time series occurred. False reporting of no activity hade for some time been a problem in Sweden. False reporting means that for a certain vehicle the reply to the questionnaire is that no activity was performed during the measurement week, when in fact activity was performed, i.e. a false reply. In 2014, a new method to account for false reporting of no activity was introduced. This lead to a raise in the estimates with about 30 percent. The years 2014 to present are fully comparable.
From 2015, total loaded freight weight is requested for distribution and collection rounds in the form. In previous years, the average loaded person was demanded. This has meant that the total evel of loaded goods during a quarter has increased with an estimated 6–8 percent.
